PLACE IN RETURN BOX to remove this checkout from your record.
TO AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE

DATE DUE

DATE DUE

 

Ii R 2::7

 

'~ ' g6 :
Aublczei‘togag '

 

Mil—3W

 

APR 2 (3 20m
11A

‘ \

 

xv"

 

 

 

 

 

 

 

 

 

 

2/05 cJCfiC/DataDmJndd-pds

L"“=AF?{
MiChiyall State
University

 

This is to certify that the
dissertation entitled

CHILDREN AND ADOLESCENTS DIAGNOSED WITH TYPE
2 DIABETES IN PEDIATRIC AND ADULT ENDOCRINOLOGY
CLINICS IN MICHIGAN, GLYCEMIC CONTROL AND
ASSOCIATED FACTORS

presented by

DEEPA HANDU

has been accepted towards fulfillment
of the requirements for the

Doctoral degree in Food Science and Human
, . Nutrition

 

 

     
   

 

 

//M I /{536r’s Signafired
* 51/9105"
Date

MSU is an Affirmative Action/Equal Opportunity Institution

 

PLACE IN RETURN BOX to remove this checkout from your record.
TO AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE DATE DUE DATE DUE

 

1.: 3 311. 2;:7
. ' I: ” a x
A651226E50889

i W
I APR 2 ii 101:1J

 

 

 

 

A
I w“

 

 

 

 

 

 

 

 

 

 

2/05 cz/cfiaoammis

CHILDREN AND ADOLESCENTS DIAGNOSED WITH TYPE 2 DIABETES IN
PEDIATRIC AND ADULT ENDOCRINOLOGY CLINICS IN MICHIGAN,
GLYCEMIC CONTROL AND ASSOCIATED FACTORS
By

Deepa Handu

A DISSERTATION

Submitted to
Michigan State University
In partial fulfillment of the requirements
For the degree of

DOCTOR OF PHILOSOPHY
Department of Food Science and Human Nutrition

2005

ABSTRACT
CHILDREN AND ADOLESCENTS DIAGNOSED WITH TYPE 2 DIABETES IN
PEDIATRIC AND ADULT ENDOCRINOLOGY CLIINICS 1N MICHIGAN,
GLYCEMIC CONTROL AND ASSOCIATED FACTORS
By

Deepa‘Handu
Type 2 diabetes (T2DM) in children and adolescents is a “newly recognized” pediatric
disease, for which childhood overweight/obesity has been shown to be a strong predictor.
The prevalence of overweight/obesity in youth is a serious concern in Michigan and there
is no data on T2DM in this vulnerable age group. The purpose of this study was to: 1)
estimate the proportion of diagnosed T2DM among youth (6-19 yr) with either Type 1
(TlDM) or T2DM at endocrinology Specialty clinics in Michigan; 2) to determine
glycemic control and associated factors in cases of T2DM compared to TIDM; and 3) to
determine the ecological factors that influence glycemic control in a sample of youth with
T2DM. A two-phase study was conducted using an in-depth medical chart review for

youth (6-19 yr) diagnosed with diabetes (Phase 1), and in-depth qualitative interviews

and surveys of youth diagnosed with T2DM (Phase 2).

Of 2,018 subjects diagnosed with either Type 1 or Type 2 diabetes, 220 (11%) had
T2DM. Among those 10-19 yr, the proportion of children with T2DM increased
significantly (14%). Based on the census data for 2002 and study results, it was
estimated that the minimum prevalence of T2DM in the lower peninsula of Michigan was
11.03/100,000. The mean (iSD) age and body mass index (BMI) for those with T2DM

were 13 :t 2.8 yrs and 35 :I: 12.5 kg/mz, respectively. The mean age of onset for T2DM

was significantly higher than for TlDM (13 yr vs 8.7 yr, p<0.01) with the majority at
Tanner stage 3 or higher for puberty (83% vs 28%, p<0.01). T2DM was also
significantly higher among African Americans (52%) compared to Caucasians (15%) and
Hispanics (12%). Based on body mass index (BMI) percentiles, 78% of youth with
T2DM had BMI >95‘h %tile (overweight), the BMI percentile for youth with TlDM was
between the 5m-85th %tile (normal) for 81%. Sixty five percent of youth with T2DM
were living in single parent families compared to 40% of youth with TlDM (p<0.01).
There was a significantly higher prevalence of metabolic risk factors in youth with
T2DM compared to those with TlDM: low HDL-C (48% vs 12%), elevated serum
triglyceride (33% vs 9%), and hypertension (85% vs 74%). Compared to youth with
TlDM, youth with T2DM were less likely to follow a prescribed diet (80% vs 42%,
p<0.01) or exercise recommendations (64% vs 38%, p<0.01). The key findings of the
qualitative interviews were that dietary recommendations were difficult to adhere to, and
that family support as well as friends and institutions were important facilitators of self-

management in general.

The results of this multi-clinic study indicated that T2DM among youth in Michigan is
high, mimicking the national estimates, and concomitant with the high obesity rates. The
higher metabolic aberrations may be additional compounding factors that have serious
long-term implications. Therefore, appropriate screening and targeted interventions are

critical for effective diabetes management in this vulnerable population.

Dedicated to my parents and family
and

all those youth who have Type 2 diabetes

iv

ACKNOWLEDGEMENTS

I would like to take this opportunity to thank everybody who has stood by me
through this process and helped me become successful.

I would like to express my deepest gratitude to my advisor, Dr. Lorraine
Weatherspoon, for her excellent guidance, patience, and for providing me an excellent
atmosphere and great opportunity for conducting research.

I would also like to thank my committee members Dr. Sharon Hoerr, Dr. Wanda
Chenoweth, Dr. Nan Johnson, and Dr. Marsha Carolan for offering constant support,
brilliant insights, and constructive criticism. Thank you all for your guidance and
tremendous help with my research work.

I am grateful to Alison, Jodi, Karina, and Amy for their help and friendship. It
was their company that made life in this lab more interesting and will always remain a
part of my graduate memories. I would also like to thank Dr. Hoerr’s lab for their
friendship and support.

I extend my deepest gratitude to my parents and sisters for their love,
encouragement, and guidance. And last but not least, I would like to thank my husband,
Rahat for always being my pillar of support. Thank you for being so understanding and
standing by me through the good and bad times. It was your love and support that helped

me endure the tough times.

TABLE OF CONTENTS

LIST OF TABLES ................................................................... ix
LIST OF FIGURES ................................................................ xi
CHAPTER 1
Introduction ............................................................................. 1
1.1 Organization of the dissertation ....................................... 9
CHAPTER 2
Review of literature ................................................................... 11
1) Diabetes Mellitus (DM) .................................................. 11
2) Type 2 diabetes in children and adolescents ......................... 13
2.1) Epidemiology .................................................. 13
2.2) Diagnosis ....................................................... 17
2.3) Associated Factors ............................................ 23
2.4) Treatment of Type 2 diabetes in
children and adolescents ................................... 29
3) Assessment of control in diabetes .................................... 31
3.1) Definition of Control .......................................... 31
3.2) Glycemic Control ............................................. 32
3.3) Lipid management ............................................ 34
4) Determinants of diabetes control ....................................... 34
4.1) Socio-demographic Factors .................................. 34
4.2) Biomedical Factors ............................................ 36
4.3) Self-care Behaviors ........................................... 36
4.3.1) Medication .......................................... 40
4.3.2) Home diabetes status monitoring......... . 41
4.3.3) Exercise .............................................. 42
4.3.4) Diet .................................................. 43
4.3.5) Weight Control ..................................... 45
4.3.6) Education ......................................... 47
5) Theoretical foundation for conducting in-depth interviews
related to self-care behaviors ...................................... 48
CHAPTER 3
Methods ................................................................................ 56
Objectives and hypotheses ................................................. 56
Design ......................................................................... 57
Sites ........................................................................... 57
Target Population ............................................................ 58
PHASE 1 ..................................................................... 60
Procedure for objectives 1 and 2 .................................. 60

vi

Variable definitions ................................................ 61

Data processing and analyses ..................................... 65
PHASE 2 ..................................................................... 65
Procedure for objective 3 .......................................... 65
Rationale for qualitative approach ............................... 67
Validity ............................................................... 68
Subject recruitment and eligibility ............................... 69
Data collection ...................................................... 71
Data analysis ......................................................... 73
In-depth interview ................................................... 73
Physical activity ..................................................... 74
24-hr dietary recall data ............................................ 74
Working definition of terms ........................................ 76
CHAPTER 4
Proportion of children and adolescents with Type 2 diabetes in
Michigan ............................................................................... 78
Abstract ....................................................................... 78
Introduction ................................................................... 80
Research methods ............................................................ 82
Results ........................................................................ 87
Discussion .................................................................... 89
References .................................................................... 96
CHAPTER 5
Comparison of glycemic control and associated factors in
youth (6-19 years) with Type 2 or Type 1 diabetes in Michigan .............. 105
Abstract ........................................................................ 105
Introduction ................................................................... 107
Research methods ............................................................ 110
Results ........................................................................ 1 14
Discussion .................................................................... l 18
References .................................................................... 125
CHAPTER 6
Ecological factors influencing adherence to self-care behaviors
among children and adolescents with Type 2 diabetes .......................... 134
Abstract ....................................................................... 134
Introduction ................................................................... 136
Research methods ............................................................ 140
Results ........................................................................ 146
Discussion .................................................................... 1 53
References .................................................................... 160
CHAPTER 7
Summary and conclusions ........................................................... 173

vii

APPENDD( A ........................................................................ 185

APPENDIX B ........................................................................ 186
APPENDIX C ........................................................................ 191
APPENDD( D ........................................................................ 194
APPENDIX E ........................................................................ 200
APPENDIX F ........................................................................ 202
APPENDIX G ........................................................................ 206
REFERENCES ...................................................................... 212

viii

LIST OF TABLES

Chapter 2
Table 1. Estimates of the magnitude of Type 2 diabetes in

children and adolescents .......................................................... 14
Table 2. American diabetes association criteria for the diagnosis of

Type 2 diabetes in children and adolescents ................................... 19
Table 3. Differentiating Type 1 from Type 2 diabetes in

children and adolescent ............................................................ 21
Table 4. Metabolic syndrome definition ................................................... 28
Chapter 3
Table 1: Themes and Sub themes derived based on data analysis ..................... 75
Chapter 4
Table 1: Proportion of diagnosed Type 2 diabetes mellitus cases

among youth diagnosed with and treated for diabetes (6-19 yrs.) ........... 100
Table 2: Characteristics of patients with Type-2 diabetes mellitus .................... 101
Table 3: Presence of risk factors among Type 2 diabetes youth

by ethnicity and gender ............................................................ 102
Table 4: Presence of clinical parameters among youth with

Type 2 diabetes ..................................................................... 103
Chapter 5

Table 1: Descriptive characteristics of youth with
Type 1 or Type 2 diabetes ........................................................ 128

Table 2: Risk factor comparisons of youth with Type
or Type 2 diabetes youth .......................................................... 129

Table 3: Comparison of Clinical Parameters between Type 1
and Type 2 diabetes cases by ethnicity and gender ........................... 130

Table 4: Reported adherence to recommended self-care behaviors
for youth with Type 1 or Type 2 youth ......................................... 131

Table 5: Risk for being diagnosed with Type 2 diabetes compared
to Type 1 diabetes, serum triglyceride 2 150 mg/dl, and serum
I-IDL—C S 40 mg/dl by a logistic regression model

Type 2 diabetes ..................................................................... 132
Chapter 6
Table 1: Descriptive characteristics of the total sample ................................. 166
Table 2: Themes and Sub themes derived based on data analysis ..................... 167
Table 3: Responses of subjects to the themes identified ................................ 168
Table 4: Barriers and facilitators indicated by Type 2 diabetes youth ............... 170
Table 5: Dietary intake descriptives for total sample (N=16) .......................... 171

LIST OF FIGURES

Chapter 2

Figure 1. Postulated clinical presentation ................................................ 22

Figure 2. Bubolz and Sontag’s model: Process by which support
leads to diabetes control .......................................................... 51

Figure 3. Model of supportive systems in etiologies of children

and adolescents with Type 2 diabetes .......................................... 53
Figure 4: Conceptual framework adapted from Bubolz & Sontag,

and McLeroy’s theory ............................................................. 55
Chapter 3
Figure 1: Figure showing different sources of data ...................................... 66
Chapter 4
Figure 1: BMI percentile distribution of youth with Type 2 diabetes ................. 104
Chapter 5
Figure 1: BMI percentile distribution of youth by Type 1 or Type 2 DM ............ 133
Chapter 6

Figure 1: Conceptual model with new emerging theme and
barriers or facilitators identified in this study ................................. 172

xi

CHAPTER 1

Introduction

Type 2 diabetes in children is a “newly recognized” pediatric disease. Historically
diabetes mellitus occurring in children and adolescents was believed to be primarily
Type 1. There are two major classes of diabetes: Type 1 (requiring exogenous insulin),
which typically begins in those under 30 years of age; and Type 2 (may or may not
require exogenous insulin depending on severity). Type 2 is the more predominant form
of the disease (90%) and mainly occurs in adults (Centers for Disease Control and
Prevention (CDC), 2002). An initial report of high occurrence of Type 2 diabetes in
children came from the Pima Indians, who have the world’s highest prevalence of Type 2
diabetes in adulthood (Savage etal., 1979; F agot-Campagna, 1999). Savage et a1. (1979)
reported that >1 % of 15—24 year old Pima Indians had diabetes associated with obesity
and long-term diabetes complications (Savage et al., 1979; F agot-Campagna, 1999). In a
longitudinal study by Dabelea et a1. (1998), in the Gila River Indian Community in
Arizona, which is dominated by Pima Indians, it was observed that the prevalence of
Type 2 diabetes in Pima Indian children had increased over a 30-year period. The results
demonstrated that in boys 10-14 years, the prevalence of Type 2 diabetes increased from
0% in 1967-1976 to 1.4% in 1987-1996. In the 15-19 year old age group of boys, it
increased from 2.43% to 3.78%. In girls 10-14 years of age, it increased from 0.72% in
1967-1976 to 2.88% in 1987-1996 and from 2.73% to 5.31% for the 15-19 year old age

group (Dabelea et al., 1998).

More recently, several clinical reports have published an increasing incidence of Type 2
diabetes among Afiican American children in Cincinnati and Arkansas (Pinhas-Hamiel et
al., 1996; Pihoker et al., 1998); first nation (American Indian) children in Manitoba
(Dean, 1998; Dean et al., 1992); Native Americans in Ontario (Harris et al., 1996);
Hispanic children in Califomia (Fagot-Campagna et al., 2001); and Japanese children in

Tokyo (Kitagawa et al., 1994; Kitagawa et al., 1998).

Children and adolescents diagnosed with Type 2 diabetes are generally between 10 to 19
years old (usually at or close to puberty) (Pinhas-Hamiel et al., 1996; Henry, 1998).
However, there have been reported cases as young as 6 years of age (Henry, 2001;
Cicinelli-Timm, 2002). The primary distinguishing characteristics observed are obesity,
insulin-resistance, a strong family history of Type 2 diabetes, and ethnicity with higher
prevalence rates in Native American, African American or Hispanic Americans (Henry,

1998).

A recent study by Weatherspoon et al., (2000) showed that for children (12-19 years)
from the National Health & Nutrition Examination Survey III, established risk factors for
Type 2 diabetes as well as some family factors were associated with a glycated
hemoglobin (GHB) >90th percentile (upper limit of average blood sugar for past 3
months) as follows: ethnicity (odds ratio = 3.43), family history (odds ratio = 1.53),
gender (odds ratio = 1.81), Body Mass Index (BMI- calculated as weight in kilograms
divided by height in meters squared) (odds ratio = 2.82), poverty income ratio (odds

ratio= 1.50 and 1.46) and domicile area (odds ratio= 0.55 for rural compared to urban

dwellers). These data suggest that glycated hemoglobin >90th percentile might be a
usefiil indicator for Type 2 diabetes in children, but findings also demonstrated a need to
recognize the importance of including diabetes screening tests in youth < 18 in such
national survey data. In addition, more convenient and reliable screening tools for Type
2 diabetes in children and adolescents at the national level, will allow the health

professional to better address this growing health issue.

The spiraling rate of childhood obesity in America, which was declared an epidemic by
Dr. David Satcher, former Surgeon General of the US in November 1998, is believed to
be the most significant factor in the escalating numbers of children with Type 2 diabetes.
Reports by the CDC illustrated that approximately 80% of youth with Type 2 diabetes are
overweight (CDC, 1998). Moreover, obesity rates also are higher in Afiican American
and Hispanic populations (Kuczmarski et al., 1994). Most recent data from NHANES
1999 to 2000 and 2000 to 2004 indicated that among children aged 6-19 years in 1999—
2002, 31.0% were at risk for overweight or overweight and 16.0% were overweight
(Headley et al., 2004). Obesity prevalence over the past 20 to 30 years has doubled for
children 2-5 years and almost tripled for those 6 to 19 years (Liu et al., 2004). In a
Cincinnati clinic study to determine the rise in diagnosis of Type 2 diabetes among
adolescents, 92% of subjects were obese and in a similar study in Arkansas, 96% were
Obese (Pinhas-Hamiel et al., 1996; Pihoker et al., 1998). Studies on obesity in Michigan
have shown that in children 4 to 17 years of age, among boys, 38% were above the 85th

percentile (at risk of overweight) and 16% above 95th percentile (overweight) for weight.

Of the girls, 33% were above the 85th percentile and 13% were above the 95th percentile

for weight (Gautheir et al., 2000).

Several other factors that are associated with the prevalence and may be major
contributors to the increase in Type 2 diabetes during childhood and adolescence include:
(1) a condition called acanthosis nigricans characterized by dark irregular folds of skin
around the neck, under the arms or behind the knees (Dean, 1998; Stuart et al., 1998).
Acanthosis nigricans is a marker of insulin resistance and is associated with many
different conditions and symptoms that include insulin resistance and compensatory
insulin secretion (Liu et al., 2004); (2) socio-demographic and family factors (Jones,
1998; Dean, 1998); (3) family history of diabetes (Neufeld et al., 1998; Pinhas et al.,
1996); (4) low level of physical activity (Ludwig et al., 2001; American Diabetes
Association, 2000); (5) weight at birth (Dabelea et al., 1998); (6) pubertal status (Pinhas-
Hamiel et al., 1996; Arslanian, 2000); as well as (7) exposure to diabetes in utero

(Dabelea et al.,1998).

In addition to diagnosing diabetes, disease management is important for control and
hence prevention of complications. Typically assessed as glycemic control, glycosylated
hemoglobin (GHB) is currently considered the best indicator of a patient’s average blood
glucose over the past 120 days period (Lenzi et al., 1987; ADA, 2000). Treatment
modalities for Type 2 diabetes are based on the belief that early diagnosis and careful
control of blood sugar and related atherosclerosis risk factors (e. g. blood lipids, weight,

diet and activity level) can reduce, delay or prevent complications or early mortality

(Anderson and Svardsudd, 1995; Ohkubo et al., 1995; Diabetes Control & Complications
Trial Group, 1993; Turner et al., 1998). Lifestyle factors such as diet, exercise as well as
medication compliance, regular medical assessments, and self-monitoring of blood
glucose are critical components of diabetes care. Generally, children and adolescents
with Type 2 diabetes may have poor glycemic control (GI-TB: 10%-12%), and hence an
increased likelihood of developing complications of poorly controlled diabetes at a
substantially younger age than the older person with Type 2 diabetes (CDC, 1998).
Glycemic control is difficult to manage among Type 2 diabetes cases because the
insidious nature of this condition makes it difficult for individuals to believe they actually
have a serious problem. Type 2 diabetes cases are less likely to exhibit noticeable signs
and symptoms if they initially fail to adhere to their recommended regimens. Therefore,
self-care behaviors might be less likely to be practiced in the individual with Type 2
diabetes. In contrast, Type 1 cases become very ill if they omit their medication because
the body response is immediate and serious. Aberrations in plasma glucose, in people
with diabetes, may result in abnormal lipid metabolism, and elevated plasma cholesterol
and triglycerides could increase the possibility of atherosclerosis (American Diabetes
Association, 2000). Thus, serum lipid values are also a good indicator of diabetes

management.

The ability of children and adolescents diagnosed with diabetes to comply with
recommended behaviors is influenced by many ecological factors. Besides physiological
influences, children are also vulnerable to influences of culture, family and economics

(United States Department of Health and Human Services (DHHS), 2002). Meal

preparation and food choices can be influenced by cultural beliefs and practices (Keith
and Doyle, 1998). Economic status also plays a role in food choices, access to food and
food preparation materials that might make it difficult for families to follow healthy
eating habits (DHHS, 2002). Evidence from studies with families with a member with
diabetes, indicates that diabetes and control may also be linked with cohesion and
adaptability in families (Anderson et al., 198q). Families, which have extremely high or
low cohesion, are associated with poor diabetes control. Tubiana-Rufi et al., (1998)
demonstrated that children from less cohesive families had a significantly higher number
of hypoglycemic episodes and had 6 times as many episodes of ketoacidosis than the
children from more cohesive families (Tubiana-Rufi et al., 1998). An individual’s
susceptibility to intense emotional processes within the family and subsequent situational
depression in response are also linked with diabetes and diabetes control (Lustman et al.,

1998).

As the problem of Type 2 diabetes in children and adolescents continues to be defined
and described, there remains a vast scope for research. Medical scientists recognize that
inadequate research efforts and resources have been directed to Type 2 diabetes in
children and adolescents, and insufficient public health and research data exist even to
adequately describe the pathology of the disease in children and adolescents in the USA
(Henry, 1998). According to Rosenbloom et al., (1999) many leading scientists advocate
the necessity for both cross sectional and longitudinal studies to accurately document
prevalence and incidence of Type 2 diabetes and its wide realm of associative factors in

children and adolescents. Furthermore, it is not clear if the increased incidence of

diabetes among Afiican American, Hispanic American and Native American adolescents
is due to greater reporting or improved discrimination between Type 2 and Type 1
diabetes (CDC, 1998). Lack of sufficient data on the prevalence and incidence of Type 2
diabetes and associated factors, as well as how well the diagnosed disease is being
managed in children and adolescents in Michigan, and in the general US population,

makes it difficult to plan interventions to delay onset or manage the disease.

Theoretical/ Knowledge Framework: This study is exploratory in nature. The
ecological model (Bubolz and Sontag, 1993) best describes the approach, which
encompasses both biomedical and environmental factors in the identification of risk
factors for both prevalence and glycemic control in a defined population sample. The
long term goal is to better understand the prevalence and risk factors for Type 2 diabetes
in children and adolescents as well as determine efficacy of disease management
including barriers and facilitators in order to design and implement effective strategies for
the prevention and treatment of this disease. The objective of this study is to determine
the magnitude of the problem of Type 2 diabetes in children and adolescents as depicted
by medically diagnosed cases at endocrinology clinics in Michigan and the extent to
which this disease is being effectively treated. Weatherspoon et al., (2001) investigated
the risk for Type 2 diabetes in children and adolescents in Primary Care and Family
Practice Clinics in Michigan. Data obtained were inconsistent and limited. Therefore,
specialty endocrinology clinics were used in this study because of the anticipated greater

likelihood for keeping complete and accurate medical records and the fact that Primary

Care and Family Practice clinics were shown (Weatherspoon et al., 2001) to have

minimal patients with this disease.

There is a critical need for information on the magnitude of Type 2 diabetes in youth and
management. Increased awareness about the disease occurrence and early identification
of poor control and compliance-related issues will result in more timely and effective
efforts to intervene in an appropriate manner and delay or prevent debilitating outcomes
at a young age. Because this is a topical area of research, there is a paucity or very
limited data, both nationally and for Michigan. True prevalence is difficult to determine,
since there is undoubtedly an undiagnosed population similar to the situation, which
exists for adults. However, the proportion of those who have been recognized as having
the disease and who are being treated at endocrinology clinics will provide useful
information. The fact that Type 2 diabetes in children is strongly linked to obesity and
Michigan was recently ranked number three in the country for adult obesity, and one city
Detroit, was classified as the “fattest city”, warrants the importance of this study
(Michigan Department of Community Health, 2004). Moreover, many debilitating
complications like cardiovascular or renal diseases or retinopathy of uncontrolled
diabetes may occur at a younger age if early diabetes onset is not recognized and/or
controlled through treatment compliance during the teenage years. This study allowed us
to estimate the number of children and adolescents (6-19 years) who have diagnosed
Type 2 diabetes among those who have either Type 1 or Type 2 diabetes at
endocrinology clinics in Michigan. Review of clinic data systems and medical chart

reviews helped achieve this objective. In addition useful information was obtained for

professionals who diagnose or counsel Type 2 diabetes children on glycemic control
differences between Type 2 and Type 1 diabetes and associated biomedical, family, and
health behaviors factors.

Specific Objectives were :

 

1) To estimate the proportion of diagnosed Type 2 diabetes among children and
adolescents (6-19 years) who have either Type 1 or Type 2 diabetes at
endocrinology specialty clinics in Michigan.

2) To determine glycemic control and associated factors (including biomedical,
socio-demographic and family factors) in this population compared to Type 1
cases.

3) To determine the ecological factors that influence glycemic control in the

population of children and adolescents with Type 2 diabetes.

1.1 Organization of the dissertation

This dissertation is organized into six chapters. Chapter one presents the general
introduction of the problem and the rationale for this study. Chapter two provides a
review of literature on the concepts of pathophysiology and types of diabetes, prevalence
of Type 2 diabetes in children and adolescents, assessment of control of diabetes, and
determinants of Type 2 diabetes. Chapter three presents the methods used to achieve the
objectives of this study. This study is organized into 2 Phases: Phase 1 involved an in-
depth medical chart reviews; and Phase 2 encompassed an in-depth qualitative interview
study. This chapter also discusses the rationale for conducting a qualitative study for the

second phase of this study. Chapter four presents article number one titled “Proportion of

children and adolescents diagnosed with Type 2 diabetes in Michigan”. This article
addresses Obj ective one of the study. Chapter five presents article number two titled
“Glycemic control and associated factors in youth (6-19 years) with Type 2 or Type 1
diabetes in Michigan”. This article compares Type 2 and Type 1 diabetes cases in terms
of associated factors and self-care behaviors. It addresses objective two of this study.
Chapter six presents article three titled “Ecological factors influencing adherence to self-
care behaviors among children and adolescents with Type 2 diabetes”. This is the
qualitative part of the study trying to study the influence of social and institutional factors
on self-care behavior for Type 2 diabetes. This chapter addresses objective three of the

study.

Chapter seven provides an overall summary of the three studies and presents some
conclusions. This chapter also presents recommendations for future research. This report
is mainly targeted for nutrition and health professionals and others concerned with
nutrition, health, and quality of life of children in US. The discussion and conclusions in
this report focus on the prevalence of Type 2 diabetes in Michigan, the associated factors

with Type 2 diabetes, and views of youth regarding their Type 2 diabetes.

10

CHAPTER 2

Review of Literature

The literature reviewed includes a description of diabetes mellitus and Type 2 diabetes in
children and adolescents. A general description of epidemiology, diagnosis, associated
factors, treatment, and diabetes control are also examined. Finally, reviewed are socio-

demographic, biomedical, and self-care behaviors as they relate to diabetes control.

1) Diabetes Mellitus

Diabetes mellitus is a group of diseases characterized by high levels of blood glucose
resulting from defects in insulin production, insulin action, or both. Diabetes can be
associated with serious complications that are costly to manage and premature death, but
steps to control the disease and lower the risk of complications can be taken. There are
two main types of diabetes, Type 1 diabetes (insulin-dependent diabetes mellitus) and

Type 2 diabetes (non-insulin—dependent diabetes).

Type 1 diabetes develops when the body’s immune system destroys pancreatic beta cells,
the only cells in the body that make the hormone insulin that regulates blood glucose.
This form of diabetes usually strikes children and young adults, who need external insulin
to survive. The typical age for onset ranges from 3 to 30 years of age. Type 1 diabetes
may account for 5 to 10% of all diagnosed cases of diabetes. Risk factors for Type 1
diabetes includes autoimmune, genetic, and environmental factors (Centers for Disease

Control and Prevention (CDC), 2004).

11

Type 2 diabetes occurs as a result of the body’s inability to make enough insulin or
properly use insulin. The primary underlying problem is believed to be insulin
resistance, with some degree of insulin deficiency. The typical age of onset for Type 2
diabetes is over 45 years. Often Type 2 diabetes can be controlled with weight loss,
healthy eating behaviors and exercise alone, but sometimes these are not enough and

either oral medications and/or insulin must be used (CDC, 2002).

Prevalence of diagnosed diabetes for US adults 2 20 years of age is estimated to be 5.1%
(10.2 million people when extrapolated to the 1997 US population) (Harris et al., 1998).
According to data from CDC, the prevalence of diabetes among US adults 2 20 years of
age is 8.7% (18 million) as of 2002 (CDC, 2004). Results from Behavioral Risk Factor
Surveillance System (BRFSS) study between 1990 and 1998 demonstrated that
prevalence of diabetes rose from 4.9% in 1990 to 6.5% in 1999, an increase of 33%

(Mokdad etal., 2000).

Of the nearly 18.2 million Americans with diabetes, 90-95% of them have Type 2
diabetes (CDC, 2004). Of these, roughly a third are unaware they have the disease
(CDC, 2004). People with Type 2 diabetes usually develop the disease after the age of 45
years, but often are not aware they have diabetes until severe symptoms occur or they are
treated for one of its serious complications. The risk for Type 2 diabetes increases with
the age. Nearly 31% of the United States population aged 65 and older has diabetes and
more likely Type 2 diabetes (CDC, 2004). In 2002, the prevalence of diagnosed diabetes

among people aged 65-74 (16.8%) was almost 14 times that of people less than 45 years

12

of age (1.2%) (CDC, 2004). Studies indicate that diabetes is generally under-reported on
death certificates, particularly in the cases of older persons with multiple chronic
conditions such as heart disease and hypertension (Gu et al., 1998). Therefore, the toll of
diabetes is believed to be much higher than officially reported (CDC, 2002). Besides the
toll on health, diabetes also sets a toll on economy. The total cost of diabetes per year in
US is $ 132 billion (indirect = $ 40 billion & direct = $ 92 billion)(CDC, 2004). Type 2
diabetes was typically known as the disease of adults and was previously considered rare
in the pediatric population. Over the last decade, however, there has been a disturbing
trend of increasing cases of Type 2 diabetes in youth, particularly adolescents, with a

greater proportion being minority.

2) Type 2 diabetes in children and adolescents

2.1) Epidemiology

Epidemiologic data for Type 2 diabetes in children and adolescents is sparse. This
limited information is in large part due to the relatively recent recognition of the
emergence of the disease in this age group. There are currently no nationwide
epidemiological data focusing on Type 2 diabetes in children. However, clinic-based
reports and regional studies consistently emphasize the increasing prevalence of this
clinical entity. Table 1 summarizes the studies to date and reports that provide estimates
of the fiequency of occurrence of Type 2 diabetes in children. Pima Indians in Arizona,
known to have a high prevalence of Type 2 diabetes, have been extensively studied.

Results from a 1992 to 1996 analysis of Pima Indians in Arizona revealed a prevalence of

13

22.3 per 1000 for Type 2 diabetes among 10 to 14 year olds and 50.9 per 1000 in the 15

to 19 year old age group (Dabelea et al., 1998).

Table 1: Estimates of the magnitude of Type 2 diabetes in children and adolescents.

 

 

 

 

 

Study types Years Race/Ethnicity Age Estimates
(Years)
Population- Prevalence per 1000
based studies
Arizona, USA 1992-1996 Pima Indians 10-14 22.3
1 5-19 50.9
Manitoba, 1996-1997 First Nations 10-19 36.0 (girls)
Canada 1988-1994 Whites, AA, MA 12-19 4.1*
NHANES III,
USA
Clinic-based
studies
Indian Health 1996 American Indians 0-14 1.3*
Services (all
US.)
Manitoba, 1998 First Nations 15-19 4.5 *
Canada 5-14 1.0
15-19 2.3
Clinic-based Incidence per
studies 100,000/year
Cincinnati, OH 1994 Whites, AA 10-19 7.2
Case series % of Type 2 DM
among new cases of
DM [Type 2(n)/ Type
1(n) +Type 2(n)]
Cincinnati, OH 1994 Whites, AA 0-19 16 (20/ 1 19)
10-19 33 (19/58)
Charleston, SC 1997 Blacks 0-19 46**
San Diego, CA 1993-1994 Whites, AA, 0-16 8 (13/160)
Hispanics, Asian
Americans
San Antonio, TX 1990-1997 Hispanics, Whites 0-17 18
Ventura, CA 1990-1994 Hispanics 45 (14/31)

 

*Estimates include Type 1 and Type 2 diabetes; ** percentages of Type 2 diabetes among non-

incident cases of diabetes. Adapted from Fagot—Campagna et al., 2001.

AA = African American
MA = Mexican American

14

The National Institute of Diabetes and Digestive Kidney Diseases (NIDDK) and National
Institute of Child Health and Human Development (NICHD) estimates a rise in
diagnosed Type 2 diabetes from less than 5% in 1994 to 20-30% of all the cases of
childhood diabetes after 1994 (NIDDK/NICHD, 1999). Data assessment from National
Health And Nutrition Examination Survey (NHANES) III demonstrated that among
2,867 individuals aged 12-19 years between 1988 and 1994, thirteen of those sampled
had diabetes (F agot-Campagna et al., 2001). Of these 13, nine were based on insulin
treatment and two on treatment with oral agents, and two on elevated fasting or random
blood glucose levels. National prevalence estimates for all types of diabetes of 4.1 per
1000 in this age group were hence calculated (F agot-Carnpagna et al., 2001). NHANES
III has no actual diagnosis classification for diabetes among <18 year old, hence these

parameters were used as indicators to calculate estimates.

Additional evidence of an increase in prevalence comes from reports of diagnosed cases
in different states of the US. For example, in Cincinnati, Ohio, medical charts of
diagnosed diabetes cases from 1982 to 1995 were reviewed, and the incidence of Type 2
diabetes in 10 to 19 year old subjects increased from 0.7/ 100,000 in 1982 to 7.2/ 100,000
in 1994 (Pinhas-Hamiel et al., 1996). Evidence suggesting increases in Type 2 diabetes
in children and adolescents in US is accumulating. Data from Indian Health Service
(1988 to 1996), also documented a 54% increase in prevalence of reported diabetes in 15-
19 year old adolescents (Fagot-Campagna et al., 2002). Case studies in Ohio, South
Carolina and a few other states have shown increasing percentages of incident pediatric

cases of diagnosed diabetes, with fewer than 4% reported before 19905 and up to 45% in

15

recent studies (Pinhas-Hamiel et al., 1996; Willi et al., 1997; Fagot-Campagna etal.,
2000). Those believed to be at greatest risk are minority children (Native, African, and
Mexican-Americans) who are obese, inactive, and genetically predisposed to the

development of Type 2 diabetes (Dabelea et al., 1999).

This emergence of Type 2 epidemic is not limited to North America. Increases in Type 2
diabetes in children and adolescents have been detected in Tokyo (Kitagawa et al., 1998
& 1994), Libya (Kadiki et al., 1996), and aboriginal children in Australia (Daniel et al.,
1999) and Canada (Dean, 1998). In Tokyo, the annual incidence of Type 2 diabetes
among junior high school children, increased from 7.3 per 100,000 in 1976-1980 to
12.1/100,000 in 1981-1985, and to 13.9/100,000 in 1991-1995 (Kitagawa et al., 1998 &
1994). The age-specific prevalence of Type 2 diabetes in 5—14 year old in the First
Nations population in Canada is 765/ 100,000 (Dean, 1998). Researchers from Taiwan
reported an estimated rate of Type 2 diabetes as 65/100,000. In this study a total of 253
school children aged 6-18 years, registered in schools in Taiwan Province, were
identified with newly diagnosed diabetes, 24 (9.5%) had Type 1 diabetes, 137 (54.2%)
had Type 2 diabetes, and 22 (8.7%) had secondary diabetes (Wei et al., 2003). Among
newly diagnosed diabetic children and adolescents in Bangkok, Type 2 diabetes increased
from 5% of all cases during 1986-1995 to 17.9% during 1996-1999 (Likitrnaskul et al.,

2003)

16

2.2) Diagnosis

In the pediatric population, the huge variability in disease presentation and
symptomatology has made distinguishing the diagnosis of diabetes more difficult without
sophisticated laboratory evaluation. This has created confirsion over the criteria that
should be used to classify Type 2 diabetes in children. Obesity is perhaps the best and
most strongly associated clinical criterion for risk of Type 2 diabetes in youth followed
by a family history of Type 2 diabetes. The age of onset is believed to be usually over 8
years of age, ofien in the range of 12-14 years, coinciding with middle to late puberty
(American Diabetes Association, 2000). However, as the childhood population becomes
increasingly more Obese, Type 2 diabetes may be expected to occur in younger children
(American Diabetes Association, 2000). Indeed, cases as young as 6 years of age have

been reported in some clinics (Henry, 2001; Cicinelli-Tirnm, 2002).

Many cases of Type 2 diabetes are undiagnosed due to the absence of specific symptoms
early on in the disease process, or subjects are misdiagnosed due to a long-standing view
by health-care professionals that diabetes in the young is usually Type 1 (Hale et al.,
1998; Rosenbloom et al., 1999). Further complicating the difficulty of accurate diagnosis
of Type 2 diabetes is the presence of ketoacidosis sometimes, a primary feature of Type 1
diabetes (Sellers and Dean, 2000; Tan et al., 2000; Tanaka etal., 1999; Thai et al., 1997;

Scott etal., 1997; Pinhas-Hamiel et al., 1997; Yamada et al., 1996).

A clinical feature commonly found in children and adolescents with Type 2 diabetes is

acanthosis nigricans, a dermatological disorder associated with obesity and insulin

17

resistance (Stuart et al., 1998; Stuart et al., 1997; Stuart et al., 1994). Acanthosis
nigricans is a velvety, dark thickening of the skin, typically found on the nape of the
neck, axilla, and medial thighs. Some estimates suggest that it can be found in 90% of
children with Type 2 diabetes and 7% in all school-aged children (Callahan and
Mansfield, 2000; Hale and Danney, 1998; Glaser and Jones, 1998; Pinhas-Hamiel et al.,
1996). It is rare in patients with Type 1 diabetes. Obese children and adolescents who
present this clinical symptom, but are not overt, diabetes should be evaluated to exclude
the possibility of undiagnosed hyperglycemia (Pinhas-Hamiel and Zeilter, 2001). Hence,
the triad of obesity, a strong family history of Type 2 diabetes, and acanthosis nigricans

should provide justification to screen these youth for Type 2 diabetes.

The American Diabetes Association has put forward diagnostic criteria as well as

population selection criteria for the diagnosis of Type 2 diabetes in children and

adolescents (Table 2)(American Diabetes Association, 2000).

18

Table 2: American diabetes association criteria for the diagnosis of Type 2 diabetes in

children and adolescents.

 

Biochemical Parameters Description

 

Classic symptoms of diabetes and casual Classic symptoms of diabetes: polyuria,
plasma glucose 2200 mg/dl (11.1 mmol/l) polydipsia, & unexplained weight loss
0R Casual = any time of the day without

regard to time since last meal

Fasting plasma glucose 2126 mg/dl (7,0 Fasting: no caloric intake for at least 8
mmol/l) hrs

OR

2-hour plasma glucose 2 200 mg/dl (11.1 Glucose dosage= equivalent 0f 75 gm
mmol/l) during an OGTT anhydrous glucose dissolved in water

 

As shown in Table 2 above, three key considerations are proposed for the diagnosis of
Type 2 diabetes in children and adolescents. The Oral Glucose Tolerance Test (OGTT)
for these tests should be performed as described by the World Health Organization
(WHO, 1985), using a glucose load containing the equivalent of 75 gm anhydrous
glucose dissolved in water. Population selection criteria in the studies cited included

(a) Overweight (BMI >85th percentile for age and sex, weight for height >85th percentile,
or weight >120 % of ideal for height) plus (b) any of the following risk factors: (i) family
history of Type 2 diabetes in first or second degree relative (ii) Race/ethnicity and (iii)
Signs of insulin resistance or conditions associated with insulin resistance (acanthosis

nigricans, hypertension, dyslipidemia, polycystic ovarian syndrome (PCOS)). (c) Age of

19

onset: age 10 years or at onset of puberty if puberty occurs at a younger age.
((1) Frequency of all the above mentioned three points (a,b, and c) as well as Fasting

Plasma Glucose (F GP).

Table 3 outlines some general features usefiil in distinguishing between Type 1 and Type
2 diabetes. Presence of obesity, elevated C-peptide, belonging to minority ethnicity,
strong family history of Type 2 diabetes, and the presence of acanthosis nigricans would
suggest the diagnosis of Type 2 diabetes rather than Type 1 diabetes in the child or
adolescent with diabetes. Obesity is perhaps the best clinical criterion for the diagnosis
of Type 2 diabetes versus Type 1 diabetes in children and adolescents. In these children
effects of chronic hyperglycemia on the B-cell may result in decreased insulin secretion
and relative insulin deficiency resulting in an apparent clinical presentation of
insulinopenia and ketosis or ketoacidosis and the diagnosis of Type 1 diabetes.
Decreased B-cell responsiveness or premature B-cell death may be attributed to effects of
chronic. hyperglycemia on the B-cell resulting in glucose desensitizing or glucose toxicity
respectively (Robertson et al., 1994). Therefore, changes in B-cell function over time
may account for the variability of clinical presentations in children with Type 2 diabetes
but after B-cell recovery with improved metabolic control are determined to have Type 2

diabetes (Clark et al., 2001)(Figure 1).

20

Table 3: Differentiating Type 1 from Type 2 diabetes in children and adolescents.

 

 

 

 

 

Type 1 Type 2
Demographics
Family History 3% - 5% 74% - 100%
Age or pubertal status All ages but mostly mostly >10 year and
young children mostly after puberty
Gender Females = Males Females > Males
Presentation
Symptom duration Days or weeks Weeks or months
Weight All ranges Obese
Weight loss Common Uncommon
Physical Findings
BMI at diagnosis <20kg/m2 >27kg/m2
Acanthosis Ni gricans Rare Common
Hirsutism Rare Common
Biochemical Parameters
at Diagnosis
Hyperglycemia Variable Variable
Ketosis and ketonuria Common Common
Acidosis Common Variable
Other Markers
GHB Elevated Elevated
Insulin Low High
Autoimmune markers Common Uncommon

 

Source: NIDDK/NICHD, 1999

Figure 1: Postulated clinical presentation

(A) Insulin resistance with hyperinsulinism, (B) Glucose intolerance, (C) Diabetes
mellitus with hyperinsulinemia, (D) Insulinopenia with ketosis or Ketoacidosis, (E)

Hyperinsulinsm afler metabolic stabilization and recovery of beta cell function

Relative
blood A C
Insulin
level

 

 

Normal
Insulin
levels

Time

 

Source: Clark et al., 2001.

22

2.3) Associated Factors

Relationship to Obesity

Among adults, numerous studies document a significant correlation between the
prevalence of Type 2 diabetes and relative weight for height (Mokdad et al., 2000 and
2001). Ford et al., (1997) demonstrated that for every 1 kg increase in measured weight
the risk of diabetes increased by 4.5% in a national sample of adults. A significant
majority (85%) of children with Type 2 diabetes are overweight or obese at the time of
diagnosis (American Diabetes Association, 2000; Pinhas-Hamiel et al., 1996; Pihoker et
al., 1988). Obesity is perhaps the best clinical criterion for the diagnosis of Type 2
diabetes versus Type 1 diabetes in children and adolescents. The increase in diagnosis in
the last few years coincides with the increasing prevalence of obesity among American

children (NIDDK/NICHD, 1999).

Data on childhood and adolescent obesity levels between the 1960s and 19905 Show a
steady increase (Gortmaker, 1987 ; Campaigne, 1994; Webber et al., 1994). This raises a
special concern, as obesity is usually also associated with other deleterious health
outcomes such as high blood pressure, coronary artery disease and stroke (National
Center for Health Statistics, 1987). Current data from NHANES IH (1998-1994) of a
nationally representative sample of children, aged 6-11 years and adolescents, aged 12-17
years and the National Longitudinal Study of Adolescent Health (Add Health) (National
Center for Health Statistics (N CHS) 1994, F legal et al., 2001) indicate that approximately
14% of children and 12% of adolescents are overweight, with an almost equal

distribution among males and females. Black, non-Hispanic females and Mexican

23

American males had the highest percentage of overweight individuals. With regard to
obesity in certain ethnic groups, acculturation was deemed a factor to also consider
(Popkin and Udry, 1998). For the Hispanic and Asian American populations, children
born outside of US (first generation Americans) were less likely to be obese than children

born of US immigrants (second generation Americans).

The average BMI for the Type 2 diabetes pediatric population in published reports ranges
from 35 — 39 kg/mz, while the normal range is 15 — 27 kg/m2 (Pinhas-Hamiel et al.,
1999). One third of the children with Type 2 diabetes have a BMI greater than 40 kg/mz,
indicating morbid obesity and 17% have BMI greater than 45kg/m2. Waist to hip ratio of
adolescents with Type 2 diabetes indicates that obesity in these patients is central (the

“apple” shape) (Pinhas-Hamiel et al., 1999).

A key physiological implication of obesity and link to Type 2 diabetes is the adverse
effects on glucose metabolism. For example, 55 % of variance in insulin sensitivity
among healthy white children (i.e. non-diabetic) is accounted for by total adiposity
(Bogardus et al., 1985). The amount of visceral fat in obese adolescents was directly
correlated with hyperinsulinemia and inversely related with insulin sensitivity (Tamura et
al., 2000). Therefore, it is not surprising that the Type 2 diabetes-obesity association is

so strong.

Associations between low birth weight and an increased risk for Type 2 diabetes in adults

have been described in various populations. In Pima children, low birth weight subjects

24

(<2.5 kg) have a higher prevalence of diabetes than individuals with normal birth weight
(2.5-4.5 kg), but there is also a higher prevalence of diabetes in children with very high

birth weights (2 4.5 kg) (Dabelea et al., 1998).

Other Risk Factors:

Family History: Type 2 diabetes in children and adolescents is strongly associated with
family history (Hale and Danney, 1998; Hale, 2000). Children and adolescents with
Type 2 diabetes generally come from families in which the parents are also obese and
tend to have insulin resistance or overt Type 2 diabetes themselves (Pirrhas-Hamiel and
Zeitler, 2001). Approximately 74-100% of affected children have a first or second-
degree relative with Type 2 diabetes (Hale and Danney, 1998; Hale, 2000; Pinhas-Hamiel
et al., 1996). Healthy siblings of patients with Type 2 diabetes have been shown to have
elevated levels of proinsulin and C-peptide (Pinhas-Hamiel and Zeitler, 2001), both of
which are associated with high risk of developing Type 2 diabetes. In addition, the
authors reported first-degree family members to have “undiagnosed diabetes” on
subsequent evaluation. Other studies demonstrated that children and adolescents, with
mothers who had diabetes during pregnancy, are at a greater risk for a higher prevalence
of Type 2 diabetes, suggesting that an abnormal intrauterine environment may be an
independent risk factor for obesity and the early expression of diabetes in the offspring

(Pettitt et al., 1988; Lindsay et al., 2000; Phillips, 1996).

25

Puberty: Puberty may also be playing a role as an increasing risk factor for Type 2
diabetes in children. Pinhas-Hamiel et al., (1996) demonstrated that mean age for their
subjects was 13.8 years and that all their subjects were in mid-puberty. During puberty,
there is increased resistance to the action of insulin, resulting in hyperinsulinemia. It has
been shown that between Tanner stages I] and IV there is 30% lower insulin-mediated
glucose disposal compared with prepubertal children in Tanner stage I and compared
with young adults (Arslanian, 2000). Sinaiko et a1. (2004), indicated that increased
insulin resistance is associated with a significantly higher systolic blood pressure after
more than five years of follow- up. Since puberty is characterized by relative insulin
resistance, it may be an aggravating factor in the appearance of overt Type 2 diabetes in

obese adolescents.

Ethnicity: Results from the Bogalusa Heart Study demonstrated that after adjusting for
age, weight, ponderal index, and pubertal stage, African American children aged 7 to 11
years, had higher insulin responses suggestive of insulin resistance than their White
counterparts (Rosenbloom et al., 1999; Urbina et al., 1999). A study by Danadian et a1.
(1999), indicated that even among healthy, prepubertal African American children, a
family history of diabetes is associated with an approximately 20% reduction in insulin
sensitivity. High levels of insulin/hyperinsulinemia and decreased insulin sensitivity
observed among 8 to 12 year old Afiican American and Hispanic has been associated
with both increased insulin secretion and decreased clearance of insulin (Arslanian et al.,
2002; Goran et al., 2002). Studies from San Diego and Cincinnati demonstrated that two

thirds of their children and adolescents with Type 2 diabetes were African American or

26

Mexican American respectively (Pinhas-Hamiel et al., 1996; Glaser and Jones, 1998).

Thus, Type 2 diabetes tends to be more prevalent in some ethnicities.

Gender: Studies in Pima Indians, the First Nations of Canada, and Japanese school
children, showed that female adolescents appear to have increased risk of Type 2 diabetes
compared to male adolescents (F agot-Campagna et al., 2000; Fagot-Campagna et al.,
1999; Pinhas-Hamiel et al., 1996). Overall female-male ratio is of 1.7 :1 regardless of age

(Pinhas-Hamiel and Zeitler, 2001).

Hypertension: Hypertension occurs in 20 % to 30% of patients with Type 2 diabetes, but
is rare in patients with Type 1 diabetes. The presence of both acanthosis nigricans and
hypertension strongly suggests hyperinsulinemia (Pinhas-Hamiel & Zeitler, 2001).
Obese children and adolescents with hypertension should be asked about family history
of diabetes as well as examined for hyperglycemia (Pinhas-Hamiel & Zeitler, 2001).
Hypertension in Type 2 diabetes youth is a major risk factor for nephropathy and

cardiovascular disease (Alberti et al., 2004).

Metabolic Syndrome: National Cholesterol Education Program (N CEP) recently issued
major new clinical practice guidelines on the prevention and management of high
cholesterol. These guidelines, also known as Adult Treatment Panel III (ATP 111)
provided a definition of Metabolic Syndrome (MS) in adults and elicited the importance
of MS as a risk factor for Type 2 diabetes and cardiovascular diseases. According to

recent estimates, the age-adjusted prevalence of the metabolic syndrome was found to be

27

23.7% among US adults participating in NHANES III (Ford et al., 2002). Studies
suggest that a substantial percentage of overweight youth may be afflicted with metabolic
syndrome as many have 1 or more of the following: elevated triglycerides, low I-IDL-C,
and high blood pressure (Cook et al., 2003; Falkner et al., 2002; Freedman et al., 1999).
The definition for metabolic syndrome in adults and adolescents as defined by the NCEP
ATP III clinical cut off points and Cook et a1. (2003) respectively, are presented in Table
4. Metabolic syndrome is defined as having at least three of the following listed in the

table.

Table 4: Metabolic syndrome definition

 

Criterion Adults Adolescents

 

High Triglyceride level (mg/d1) Z 150 Z 110
Low HDL-C (mg/d1)
Males < 40 s 40
Females < 50 g 40

Abdominal obesity (waist circumference in cm)

Males > 102 _>_ 90th percentile
Females > 88 2 90th percentile
High fasting glucose level (mg/d1) Z 110 Z 110
High blood pressure (mm Hg) 2. 130/85 2 90th percentile

 

Source: Cook et al., 2003

28

Findings from the NHANES III (1988-1994) data indicated that overall prevalence of
metabolic syndrome among youth aged 12-19 years was 4.2% (Cook et al., 2003). In
adolescents with BMI 2 95th percentile, 28.7 % were classified as having the syndrome
compared to 6.8% of at-risk adolescents (BMI 2 85th percentile) and 0.1% of those with
BMI below the 85th percentile (p<0.001) (Cook et al., 2003). Another similar study
among overweight Hispanic youth demonstrated that 30% of the subjects were classified
as having metabolic syndrome (Cruz, et al., 2004). From these studies, it appears that in
general a high proportion of overweight youth may be at increased risk for Type 2

diabetes and cardiovascular diseases.

2.4) Treatment of Type 2 diabetes in children and adolescents

Although there is no set cure for diabetes, the ideal goal for treatment is normalization of
blood glucose values and Glycosylated Hemoglobin (GHB) (ADA, 1999). The ultimate
goal of treatment is to decrease the risk of the acute and chronic complications associated
with diabetes. There is strong evidence from the UK Prospective Diabetes study
(UKPDS) that the normalization of blood glucose substantially reduces the frequency of
microvascular complications of Type 2 diabetes in adults (UKPDS Group, 1998). The
early age of onset of Type 2 diabetes in children may particularly increase the risk of
microvascular complications such as, which are known to be directly related to duration
of diabetes and hyperglycemia (ADA, 2000). Hence, the goals for clinical management
of Type 2 diabetes mellitus in children and adolescents should include therapies directed
at treating the underlying pathologies of diabetes, effects of chronic hyperglycemia, and

the prevention of long-term complications. Prevention and treatment of associated co-

29

morbidities such as hypertension, hyperlipidemia, and obesity are important, but the
ultimate goal is to maintain blood glucose levels and the risk of end-organ damage from
diabetes, which is directly related to the duration of diabetes and level of hyperglycemia.
Similar to Type 2 diabetes mellitus in adults, the first lines of therapy in children with
Type 2 diabetes are diet, exercise and weight loss or maintenance, because these
therapies are directed at the underlying pathology: insulin resistance, which is a primary

associative feature of Type 2 diabetes.

Initial treatment of diabetes depends on the clinical presentation of the child or adolescent
at the time of diagnosis. Clinical conditions can range from diabetic ketoacidosis or
hyperglycemic hyperosmolar non-ketotic states that require aggressive initial therapy
(insulin) and metabolic stabilization to asymptomatic hyperglycemia, that can be

managed initially with diet and exercise (American Diabetes Association, 2000).

Diet and exercise are the foundation for the management of insulin resistance in Type 2
diabetes. Nutrition plans should be culturally appropriate, sensitive to family resources,
provided to all caregivers, and encourage healthy eating habits for the entire family and
suggest behavior modification strategies to promote physical activity and decrease high-
caloric, high-fat food choices. Improving physical inactivity is another aspect.
Structured exercise activities such as sports and athletic hobbies are recommended to
provide physical activity that may not be part of the child’s lifestyle. Reducing television
watching and computer use are also effective in decreasing physical inactivity in

children. Successful treatment with exercise and diet among youth is defined as cessation

30

of excessive weight gain with normal linear growth, near normal fasting blood glucose
levels (<126 mg/dl), near normal GHB (~7%), and the avoidance of hypoglycemia
(American Diabetes Association, 2000). Currently there is no data to evaluate the

efficacy of diet and exercise therapy in treating Type 2 diabetes in children.

In non-ketotic patients, the American Diabetes Association recommends that metformin
(biguanide), an oral hypoglycemic drug, should be the drug of choice in children if drugs
become necessary, because it lowers glucose levels without the risk of hypoglycemia,
maintains or decreases body weight, lowers LDL-cholesterol and triglyceride levels
(ADA, 2000; Silverstein and Rosenbloom, 2000). However, in patients who present with
severe hyperglycemia or ketosis, insulin therapy in addition to metformin is
recommended because of the potential for a transient insulin deficiency resulting from
glucose toxicity. Once control is achieved, the insulin dose can be reduced gradually
(Pinhas-Hamiel and Zeitler, 2001). There is currently no data pertaining to newer, so
called insulin-sensitizing drugs, such as thiazolidinediones. Studies need to be done to
examine the safety and efficacy of oral diabetes medications in the pediatric population.
Pharmacological agents used for the treatment of Type 2 diabetes are summarized in

Appendix A.

3) Assessment of control in diabetes
3.1) Definition of control
Diabetes control is defined as achieving and/or maintaining an ideal body weight,

euglycemia and normal glycosylated hemoglobin or GI-IB, as well as normal fasting

31

plasma cholesterol and triglycerides (American Diabetes Association, 2000). These
outcomes are desired since obesity may predispose an individual to poorer diabetes
control, such as aberrations in plasma glucose would result in abnormal lipid metabolism,
and elevated plasma cholesterol and triglycerides could increase the possibility of

atherosclerosis (American Diabetes Association, 2000).

3.2) Glycemic control

Glycosylated hemoglobin (GHB) is the glycosylated form of hemoglobin A, which
constitutes 90-95 % of adult hemoglobin and that of infants older than six months (Torre
et al., 1981). GHB is currently considered the best indicator of a patient’s average
glycemic control over the prior 120 days period (Blane et al., 1981; Gabbay, 1982; Lenzi
et al., 1987; Torre et al., 1981). The American Diabetes Association defines normal
glycemic control as HbAlc 4-6%, goal HbAlc is <7%, and additional action is required if
HbAlc >8% (ADA, 2004). This value Should reflect little to no change in blood glucose
and hence maintenance of as near as normal as possible in a well controlled individual.
Researchers have shown significant correlations between this measure and that of mean
values for other indices of glycemic control such as fasting blood sugar (Gabbay et al.,

1977; Rao et al., 1986)

GHB is generated by a non-enzymatic post synthetic modification of the beta chain in
hemoglobin A, involving the formation of a stable keto-arnine linkage at the terminal
amino group. It is formed in direct relation to the prevailing glycemia to which the

erythrocyte is exposed throughout its 120 days lifecycle (Galloway et al., 1988; Service

32

et al., 1987). This measure therefore reflects the average serum glucose concentration
due to the slow accumulation which occurs during the lifecycle of the erythrocyte.
Hence, the percentage of hemoglobin that is non-enzymatically glycosylated is increased
with chronic hyperglycemia. High repeatability and stability of GHB are attributed to the
irreversibility of the Amadori re-arrangement formed with the keto-amine linkage

(Galloway et al., 1988).

To date GHB has provided the most objective measure of control, which is independent
of patient compliance with self-monitoring of blood glucose, fluctuations in glucose, and
physical activity or food intake at a particular time (Gabbay et al., 1977). Advantages of
using serum glycosylated hemoglobin levels include: no need for the patient to fast prior
to the test; the test is not affected by recent physical and/or emotional fluctuations; and
the fact that the test may be performed on anyone at any time without prior instructions
(Skelton, 1986). In patients with either Type 1 or Type 2 diabetes, researchers have
found that when an index based on traditional methods of glucose control was used in
comparison to GHB, control in 30-40 % of patients was deemed incorrect when
compared with the GHB (Lenzi et al., 1987). They concluded that if one out of three
patients were incorrectly assessed on traditional methods, then the clinical usefulness of

the GHB assay was justified.
In spite of the utility of GI-IB as a measure of glycerrric control, there are some potential

limitations. It must be noted that GHB does not indicate ways to improve control nor

does it reflect the fact that a normal level might be at the price of hypoglycemia (Lenzi et

33

al., 1987). Also, depending on the assay method used for determination of the GHB,

other abnormal hemoglobin that occur in certain conditions may interfere with the result.

3.3) Lipid management

Individuals with Type 2 diabetes have an increased prevalence Of lipid abnormalities that
contributes to higher rates of cardiovascular diseases. Lipid management is aimed at:
lowering LDL cholesterol; raising HDL cholesterol; and lowering triglycerides.
Maintaining lipids within normal limits has been shown to reduce macrovascular disease
and mortality in adult patients with type 2 diabetes, particularly those who have had prior
cardiovascular events (American Diabetes Association, 2004). Normal lipid levels for
youth are: LDL S 110 mg/dl; HDL > 40 mg/dl; Triglyceride < 150 mg/dl; and cholesterol

<170 mg/dl (National Cholesterol Education Program, 2004).

4) Determinants of diabetes control
Determinants of control in Type 2 diabetes may be (1) sociodemographic (age, sex,
education, family income and culture); (2) biomedical (duration of diabetes, number of

co-morbidities); and (3) behavioral (diet, weight, exercise, compliance, and lifestyle).

4.1) Socio-demographic factors

Alleyene et a1. (1979) studied social factors in 54 patients with severe Type 2 diabetes
defined as clinical evidence of neurological or vascular complications, and 49 patients
with mild Type 2 diabetes without evidence of these complications in Jamaica, West

Indies. Control was measured by glycosuria of less than two pluses suggesting little to no

34

overflow of glucose in the urine due to hyperglycemia. Patients with severe diabetes, had
fewer social amenities, were less likely to be employed, were less educated, and had less
initial understanding and knowledge of the disease, and were more likely to use informal
medication than those with mild diabetes. These patients were overall more likely to
report difficulties in maintaining the dietary regimen because of unavailability of foods

and financial problems.

Robinson et a1. (1998), investigated the relationship between measures of social
deprivation and mortality in adults with diabetes. He found that odds ratios for diabetes
were higher for those of lower social class compared to higher social class (Type 1: OR=
1.34, CI= 0.61-2.96; Type 2: OR= 2.0, CI= 1.41-2.85); and were higher for those who left
school before 16 years of age compared to those who left school at or after 16 years of
age (Type 1: OR= 3.98, CI: 1.96-8.06; Type 2: OR= 2.86, CI= 1.93-4.25). Subjects who
were unemployed had higher mortality rates than those employed at the time of the study
(Type 1: OR= 3.10, CI= 1.67-5.97; Type 2: OR= 2.88, CI= 2.12-3.91), and those living in
council housing had a greater mortality than those who were living in other types of

housing (Type 1: OR= 2.57, CI: 1.35-4.91; Type 2: OR= 2.76, CI: 2.05-3.73).

McMurray et a1. (1998), demonstrated that female adolescents with a low socioeconomic
status were more likely to be overweight, while Mei et a1. (1998), reported an increased
prevalence of overweight among low-income preschool children. Since diabetes is a
chronic illness, the escalating costs of health care no doubt make it difficult for many to

cope with the rising costs (J ewler, 1988). Subsequently, many patients do not have

35

access to private specialized diabetes care where as the American Diabetes Associations
recommendations for standards of diabetes care are most likely to be part of routine

practice. Hence, socioeconomic status may have implications for persons with diabetes.

4. 2) Biomedical factors

Diabetes duration may have important implications for control. Duration of the disease is
ofien taken into consideration in analysis of studies related to control in diabetes because
Type 2 especially if not recognized or poorly controlled is assumed to have cumulative
negative effects over time (Alleyne et al., 1979; O’ Connor et al., 1987). Usually
measured by the date of first diagnosis, duration is more likely duration of treatment as
noted by a medical professional. It is not a precise measure of duration of disease from a
physiological standpoint since medical care access and utilization and symptomatology
may variably define the stage of the disease when diagnosed. Thus, it is difficult to know
how to interpret findings based on this variable. However, it does provide the best

method and some indication of time.

4.3) Self care behaviors

Appropriate behaviors as outlined under treatment strategies are imperative for diabetes
management and hence control. These behaviors, as specified in the American Diabetes
Association’s guide to diagnosis and treatment of Type 2 for physicians are medication
compliance as prescribed, home diabetes status monitoring to facilitate treatment
strategies, appropriate regular physical activity as tolerated by the patient and advised by

the health care provider, and dietary modification to enhance and maintain normal serum

36

glucose and lipid levels (American Diabetes Association, 2004). This ability to achieve
control of blood sugar in persons with diabetes depends to a large extent on the degree to

which these self care behaviors are adhered to.

Although adolescents start exerting more control over their health behaviors, as they
enter adulthood, results from studies have indicated that most adolescents do not relate
unhealthy behaviors with negative health outcomes (Radius et al., 1980). Studies in
Mexican-American youth in California (Jones, 1998), Native American youth in Canada
(Dean, 1998) and the US. (Watkins and Whitcomb, 1998) attribute non-adherence to
many factors such as denial about their diabetes because they are asymptomatic, and peer
pressure to consume high-caloric foods and beverages high in sugar content. Numerous
cultural and socioeconomic barriers interfere with implementation of dietary changes in
youth with diabetes (Rosenbloom et al., 1999). Youth may lack familiarity with
recommended food items, which may be costly, difficult for families to obtain, or may

require special preparation (Dean, 1998; Jones, 1998).

In the last decade there has been a concerted national effort to reduce the negative impact
of diabetes through improvements in self-care behaviors that lead to improved diabetes
management. The bases for this effort are supported by the findings of the UK.
Prospective Diabetes Study (Turner et al., 1998) and the Diabetes Control and
Complications Trial (DCCT, 1993). These findings emphasize the importance of self-
care behaviors being incorporated as a part of an integrated program to maintain good

blood glucose control over time. Type 2 diabetes patients require adoption and

37

maintenance Of multiple self-care behaviors to achieve and sustain good glycenric control
(DCCT, 1993; Turner et al., 1998). These behaviors mainly include self-monitoring of
blood glucose via finger prick tests, exercising regularly, and adhering to a recommended

eating regime.

A study by Rost et a1. (1990), evaluated the relationship of self-care behaviors to
metabolic control in Type 2 diabetes patients. Self care behaviors assessed were the
frequency of exercise, blood glucose monitoring and meal skipping. Results from this
study demonstrated that the frequency of self-blood glucose monitoring was significantly

associated with a decrease in glycated hemoglobin.

The Diabetes Prevention study demonstrated that lifestyle intervention (reduction of at
least 7% of initial body weight through a healthy diet and physical activity of moderate
intensity for 150 minutes/week) reduced the incidence of Type 2 diabetes by 58% as
compared to the placebo group (Diabetes Prevention Program Research Group, 2002).
On the other hand, research also demonstrates that adhering to a healthy diet and
increasing physical activity are the most difficult components of a self-care regime
(Sullivan and Joseph, 1998). People with diabetes were reported to be more resistant to
dietary change when compared to people with other chronic diseases (Groop and Toumi,

1997)

Studies have shown that these self-care behaviors are influenced by psychosocial,

behavioral, and environmental elements (Oltersdorf et al., 1999; Nestle et al., 1998).

38

Many studies, therefore have investigated behavioral and psychosocial issues influencing
food selection and eating patterns (Oltersdorf et al., 1999; Nestle et al., 1998). A study
by Travis (1997), among adults with Type 2 diabetes focused on psychosocial variables
affecting dietary adherence and identified the variables that influenced diabetes self-care.
Other quantitative studies specific to minority populations with adult Type 2 diabetes
have suggested that factors such as culture, ethnicity, socioeconomic status, and
psychosocial factors play a significant role in explaining certain self-care behaviors and
outcomes (Fitzgerald et al., 1997; Chipkin and De Groot, 1998; Bell et al., 1995;
Gilliland et al., 1998). A study by Wdowik et a1. (2001) among college students with
Type 1 diabetes indicated that, the most predictive attitude constructs of good diabetes
management were Intention and Importance of Health, whereas barriers to good diabetes

management were Emotional Response and Situational Factors (W dowik et al., 2001).

Qualitative research has provided some additional information on the many psychosocial
factors influencing the self-care behaviors of adults with Type 2 diabetes (Anderson et
al., 1996; El-Kebbi et al., 1996; Maillet et al., 1996). Although these studies identified a
number of important socio-cultural and psychosocial influences on self-management
behaviors, and particularly dietary behaviors, it is also necessary to have information on
the relative importance of these factors and how they are manifested in day-to-day living.
Moreover, there is limited information on how unique personal dimensions, behavioral
requirements, and environmental characteristics of those with Type 2 diabetes affect

lifestyle factors especially of the youth.

39

Phase 2 of this study proposes to accomplish this task by: employing the ecological
theory as a guide for identifying the structure, characteristics and function of systems that
faCilitate control of diabetes, based on what a group of Type 2 diabetes children and
adolescents identify as having been their supports after diagnosis of diabetes. The goals
for individuals with diabetes are to achieve and maintain a desirable body weight and
optimal glycemic control to reduce the morbidity and mortality associated with diabetes
(DCCT, 1993 and Turner et al., 1997). To achieve these goals for individuals with
diabetes, nutrition educators need to appreciate and take into consideration the issues
faced by those with diabetes as they strive to change and improve their eating patterns

and lifestyles (Boyle et al., 1998).

Hence, the main purpose of this study was to examine the beliefs and experiences of
youth with Type 2 diabetes regarding monitoring blood glucose, exercising regularly,
dietary recommendations, food selection and eating patterns, and the aspects of daily
living that influence their diabetes self-management practices. The end goal is to use this
information to construct a picture of a supportive ecology for children and adolescents

(with Type 2 diabetes) in managing their disease.

4.3.1) Medications

Chronic diseases such as diabetes mellitus, in conjunction with others such as
hypertension, coronary heart disease and arthritis, require complex medication
management regimens. The patient may inadvertently take or not take medications

contrary to that prescribed. Prescribing practices of physicians as well as the memory

40

and motivation of the patient may account for the ineffective accomplishment of this self-

care behavior (Heisler et al., 2002; Hulka et al., 1976).

4. 3.2) Home diabetes status monitoring

Self blood glucose monitoring, in the form of finger prick blood testing and/or urine
testing by persons with diabetes plays an important role in maintaining blood glucose
levels and is considered, the cornerstone of optimal self-care behavior in diabetes (Rubin
et al., 1989). However, the literature is controversial in this respect and most of the
studies are in relation to Type 1 diabetes in youth. Holmes and Griffiths (2002) reported
a reduction in GHB in those who monitored glucose levels compared to those who did
not measure. They also performed a meta-analysis on three studies (n=278) comparing
GHB in subjects who performed blood glucose monitoring with those who performed
urine monitoring. The reduction in GHB when monitoring blood glucose rather than
urine glucose was -0.03% (95% Cl -0.52 - +0.47). This result was not statistically
significant. The efficacy of blood and urine glucose monitoring testing alone, for people
with Type 2 diabetes, in improving glycemic control as measured by GHB levels is still
not conclusive. However, there is no doubt that knowledge of glycerrric status especially
if it is self determined could be a powerful motivating factor for action.

Rost etal., (1990) evaluated the relationship of self-care behaviors to metabolic control in
Type 2 diabetes patients. Self care behaviors assessed were the frequency of exercise,
blood glucose monitoring and meal skipping. Results from this study demonstrated that
the fi'equency of self-blood glucose monitoring was significantly associated with a

decrease in GI-IB.

41

4. 3.3) Exercise

Exercise along with diet and medication has been considered one of the three
cornerstones of diabetes therapy. A meta-analysis of 12 aerobic training studies and 2
resistance training studies among adults with Type 2 diabetes (mean age = 55 years)
demonstrated a significant reduction in GHB in the exercise groups compared to the
control groups (7.65% v/s 8.31%) (Boule et al., 2001). Mourier et a1. (1997),
demonstrated that physical training resulted in an improvement in insulin sensitivity with
concomitant loss of visceral adipose tissue in Type 2 diabetes patients. Patients, who
exercised, increased their V02 peak by 41% and their insulin sensitivity by 46%.
Physical training significantly decreased abdominal fat evaluated by magnetic resonance
imaging (umbilicus), with a greater loss of visceral adipose tissue (VAT) (48%) in
comparison with the loss of subcutaneous adipose tissue (18%), but did not significantly
affect body weight. In children, increased abdominal fat is associated with abnormal
blood pressure, elevated serum levels of total cholesterol, LDL-C, triglyceride, and
insulin, as well as lower levels of HDL (Freedman, et al.,1999). Research indicates an
inverse relationship between visceral fat and insulin sensitivity, hence, exercising can be
beneficial for people with diabetes.

Pan et al., (1997) demonstrated the effect of exercise and diet in delaying onset of Type 2
diabetes in subjects with impaired glucose tolerance. Results showed that the cumulative
incidence of diabetes after 6 years was 67.7% (95% CI, 59.8-75.2) in the control group
compared with 43.8% (95% CI, 35.5-52.3) in the diet group, 41.1% (95% CI, 33.4-49.4)
in the exercise group, and 46.0% (95% CI, 37.3-54.7) in the diet-plus-exercise group (P <

0.05).

42

Results from the Diabetes prevention trial demonstrated that lifestyle intervention
(reduction of at least 7% of initial body weight through a healthy diet and physical
activity of moderate intensity for 150 minutes/week) reduced the incidence of Type 2
diabetes by 58% compared to the placebo group (Diabetes Prevention Program Research

Group, 2002).

4.3.4) Diet

Nutritional factors concerned in blood glucose control are the total daily kilocalorie
intake (Zimmerman and Service, 1988; Franz, 2004); type of sugar (glucose, fi'uctose,
sucrose, lactose) (Franz et al., 2004); type and amount of fiber (V inkin and Jenkins, 1988;
Bantle, 1988); and the percentage distribution of carbohydrates (Bantle, 1988; Kabedi,
1996), fat (Bantle 1988; Reaven, 1986), and protein (Bantle, 1988) of total kilocalorie
intake. Before 1994, the nutrition principles and recommendations of the American
Diabetes Association attempted to define an ideal nutrition prescription for all the people
with diabetes (ADA, 1971; 1979 and 1987). After 1994, the nutrition recommendations
shifted to one that emphasizes effect of nutrition therapy on metabolic control (ADA,
1994; Franz et al., 1994; Franz et al., 2002). The goal of nutrition intervention is to assist
and facilitate individual lifestyle and behavior changes that will lead to improved
metabolic control, and this continued in 2002 but for the first time the 2002

recommendations specifically addressed lifestyle approaches to diabetes prevention.

Studies have shown that replacing carbohydrate with monounsaturated fat reduces

postprandial glycemia and triglyceridemia (Franz et al., 2004). However, there is a

43

concern that increased fat intake may promote weight gain. Therefore, the contributions
of carbohydrate and monounsaturated fat to energy intake should be individualized based
on nutrition assessment, metabolic profiles, and treatment goals (Franz, 2004). Studies
have demonstrated that in individuals with Type 2 diabetes, postprandial glucose levels
and insulin responses to a variety of starches and sucrose are similar if the amount of
carbohydrate is constant (Franz et al., 2002; Malerbi et al., 1996; Bantle et al., 1993).
Glycemic index, the measure of glycemic response to carbohydrate-containing foods, has
been used to physiologically classify dietary carbohydrates. Research indicated that
habitual consrunption of low glycemic index foods may lower the risk of Type 2 diabetes
mellitus (Salrneron et al., 1997;) and improve metabolic control once the disease has
developed (Miller, 2000). A Study by Brand et al. (1991), reported lower GHB in Type 2
patients consuming low glycemic index foods as compared to those consuming high
glycemic index foods. Studies have also shown beneficial effects of fiber on glycemia
(Chandalia et al., 2000; Jenkins et al., 1976). For example a diet supplemented with large
amounts of water-soluble, gel-forming fiber, such as guar gum, (in other words high fiber
diets) has been shown to reduce postprandial glycemia and plasma lipids (Chandalia et

al., 2000; Jenkins et al., 1976).

The primary goal regarding dietary fat in patients with diabetes is to decrease intake of
saturated fat and cholesterol (ADA 2001; Schwab et al., 2000; Hegsted et al., 1993). The
recommendations are the same as for the general population: fat intake <30 % of energy
intake, to reduce saturated fat intake to <10% of energy intake, and dietary cholesterol

intake <300 mg/day. In subjects with diabetes, restrained eating behaviors with dietary

44

fat restriction have shown to have beneficial effects on glycemia, plasmas lipids, and/or

weight (Heilbronn et al., 1999; Storm etal., 1997; Walker et al., 1995).

There is no research on the nutrient requirements for children and adolescents with
diabetes, and therefore the recommendations are based on requirements for all healthy
children and adolescents (Institute of Medicine, Food and Nutrition Board 2001, 2000,
and 1997; Food and Nutrition Board, 1989). Successful treatment for Type 2 diabetes in
children and adolescents with nutrition therapy and exercise is comprised of cessation of
excessive weight gain with normal linear growth and achievement of normal blood
glucose and GHB levels (ADA, 2000). Behavior modification strategies to decrease
high-energy high-fat food intake while encouraging healthy eating habits and regular
physical activity for the entire family should be considered (Franz et al., 2004). These
nutrition recommendations should also address co-morbidities, such as hypertension and
dyslipidemia. Behavior modification to decrease high-calorie, high fat foods while
encouraging healthy eating habits and regular exercise for the entire family should be
considered (Ferguson et al., 1999). To enhance dietary adherence, patient inclusion in

planning and regular follow-up would be an important consideration.

4. 3. 5) Weight control

Risk of Type 2 diabetes attributable to obesity is as much as 75 % (Manson and
Spelsberg, 1994). Excess body fat is perhaps the most notable modifiable risk factor for
the development of Type 2 diabetes (Edelstein et al., 1997). Weight loss is believed to

improve glycemic control by decreasing exogenous insulin requirements and increasing

45

insulin sensitivity, thereby decreasing morbidity and mortality overall (Wing 1995;
Hansen, 1988; Wing et al., 1987b). Results from the Mahno Feasibility (intervened with
reduced fat diets) study demonstrated that both weight reduction and increased fitness
were associated with reduced incidence of diabetes in a lifestyle intervention group when

compared to a control group (Eriksson and Linkgrade, 1991).

The benefit Of weight loss in adult Type 2 diabetes patients has certainly been
demonstrated even when the weight loss is modest (Wing at al., 1986; Wing et al.,
1987a). Several recent studies have demonstrated the potential for moderate, sustained
weight loss to substantially reduce the risk for Type 2 diabetes (Moore et al., 2000;
Heymsfield et al., 2000; Sjostrom et al., 1999; Pan et al., 1997; Viswanathan et al., 1997;
Eriksson et al., 1991). There is a paucity of literature showing the benefits of weight loss
for children and adolescents with Type 2 diabetes, but since the majority of the children
or adolescents with Type 2 diabetes are obese/overweight, weight loss should be one of
the key treatment strategies for this population.

Motivated patients can usually lose weight successfully during the initial dietary and
increased physical activity period, but it is important that he/she maintains a healthy
weight by losing more weight if necessary. Weight control is therefore a complex issue
that involves the integration of a number of different approaches. Approaches should
however take into consideration each patient’s individual needs, which may change,

depending on the circumstances.

46

4.3. 6) Education

Education should provide an important communication tool for the health care provider
to increase patient knowledge and skills in the management of disease. With regard to
diabetes, education has been shown to have a positive effect on diabetes control (Hasler
et al., 2000; Raz et al., 1988; Mazzuca et al., 1986). Continuous education plays a critical
role in the management of adolescents with diabetes (Pinhas-Hamiel and Zietler, 2001).
All family members should be included in the education program, since they are often
also overweight and themselves at high risk for developing Type 2 diabetes (Pinhas-
Hamiel and Zietler, 2001). Involving the entire family enables the adolescent to comply
more reliably with recommendations (Pinhas-Hamiel and Zietler, 2001). Studies
measuring changes in diabetes knowledge demonstrate improvement with education
(group sessions, individual sessions, interactive computer teaching, home-visits, teaching
based on needs), including those with follow-up of 6—12 months after the last intervention
contact (Norris et al., 2001; Campbell et al., 1996; Heller et al., 1988; Hawthorne and
Tomlinson., 1997). Regular reinforcement or repetition of the intervention has been
demonstrated to improve knowledge levels at variable lengths of follow-up: Bloomgarden
et al. (1987) conducted nine visits in 18 months, Korhonen et al. (1983) conducted one
visit every 3 months for 12 months, Campbell et a1. (1996) who demonstrated positive
results by regular reinforcement with visits and telephone calls over 12 months, and

Rettig et al. (1986) did 1 visit very month for 12 months.

Review of literature established the increasing incidence of Type 2 diabetes in US, and

demonstrated that complying with self-care behaviors such as diet, exercise, and

47

medication play a vital role in diabetes management. Hence, Phase 1 of the this study
focuses on determining the proportion of youth with Type 2 diabetes in Michigan and
Phase 2 of this study includes an interview-based study, designed to identify social and
behavioral variables that may be associated with diabetes control. The theoretical

foundation for Phase 2 is presented below.

5) Theoretical foundation for conducting in-depth interviews related to self-care

behaviors

Concepts related to diabetes control play a central role in the shaping of nutrition
education programs for families whose children have Type 2 diabetes. Although diabetes
control is often stated as a program goal, the concept lacks specificity. Past research on
nutrition education and weight control Often suffered from a failure to base programs on
theoretical models (Johnson and Johnson, 1985). There is a need for research that
includes exploration of the individual’s objectives and priorities for diabetes self-
management education and cares as they may differ fiom those of the health care team
and published standards of care (American Association of Diabetes Educators, 2002).
However, the person with diabetes has the right and responsibility to make these choices.
Building programs around self-selected goals helps to maintain participant’s interest in
the education programs and provides the necessary knowledge and skills for personal
goal attainment (American Association of Diabetes Educators, 2002). More in-depth
information is needed about an individual’s attitudes; beliefs; experiences; psychosocial

status; cultural issues, personal, metabolic, and other goals.

48

This study is grounded in the human ecology theory and employs an ecological
framework that includes Bubolz and Sontag’s (1993) human ecology theory and
McLeroy’s Social-Ecological Model for nutrition evaluation (1988). The intent is to
elicit the unique experiences and voices of children and adolescents with Type 2 diabetes
regarding expected self-care monitoring practices (monitoring blood glucose, exercising
regularly, following dietary recommendations, selecting healthy foods and eating
patterns), as well as social and institutional support and other potentially influential

aspects of daily living.

Human Ecology Theory

Human ecological theory focuses on human beings as both biological organisms and
social beings in interaction with their environment (Bubolz and Sontag, 1993). This
theory presents the individual as part of the family, which is an energy transforming
system that is interdependent with its natural, human built and socio-cultural milieu. In
addition the access, use and management of resources for human adaptation and
development are emphasized.

The ecological perspective as espoused by Bronfenbrenner (1989) provides a framework
from which multiple contextual factors affecting the management of diabetes can be
viewed. Bronfenbrenner and Ceci (1994) suggest that individual behavior and
development is a culmination of many direct and indirect influences that either facilitate
or impede individual potential. Bronfenbrenner’s framework presents contextual
influences within a 5-dimensional framework consisting of the Macro, Exo, Meso, Micro,

and Chronosystems. In a bio-ecological model, a distinction is made between the

49

concepts of the environment and process, with the proximal process in a central position
that is defined in terms of its functional relationship to both the environment and to the
characteristics of the developing person. Environmental contexts influence proximal
processes and developmental outcomes not only in terms of the resources that they
uncover, but also in the degree to which they provide stability and consistency over time
that proximal processes require for their effective functioning (Bronfenbrenner, 1999).
Bubolz and Sontag’s theory is employed as a framework to illustrate the structure and
process of supportive ecologies for children and adolescents with Type 2 diabetes (Figure
2). This theory looks at how the natural, human constructed and socio-cultural structures
in an individual’s environment contribute (inputs) and facilitate human adaptation
(throughput) that results in healthy outcomes (outputs). This process illustrates the

functioning of an individual’s ecology.

50

Figure 2: Bubolz and Sontag’s Model: Process by which Support Leads to Diabetes

Control.

 
   
 
  
 
  

Systems
Family School Church

Government Comm. Agency
Institutions

 

  
 

Inputs
Resources Values

  

 

 

 

\7

Throughput:
Adaptation

Compliance/

 

 

 

V

Outcome:
Diabetes
Control

 

 

m
Healthy Life:

Better Socio—economic
Status

51

Social-Ecological Model

This model is based on the Bronfenbemer model and provides a model that
conceptualizes the social world in five spheres, or levels, of influence (Figure 3). These
levels of influences are: social structure, policy, and systems; community;

institutional/organizational; interpersonal; and individual.

The social structure, policy, systems sphere includes local, state, and federal policies that
regulate or support organizational or individual behavior, including protection of or
attention to children and special populations. The community level includes social
networks, norms, and standards that exist formally or informally among individuals,
groups, partnerships, and organizations. Community-level theoretical models believe that
collaboration is a process of participation through which people, groups, and
organizations work together to achieve desired results. The institutional/organizational
sphere includes factors that influence organizational behavior in the private, public, and
nonprofit sectors. These include schools, churches, public agencies, and businesses. The
interpersonal level of influence includes primary groups, such as peers, family, and
friends that provide social identity; support; role delineation and interaction for the
individual. Individuals exist in a dynamic social environment in which the attitudes and
actions of others influence their behaviors. Lastly the most specific level of influence is
the individual itself. This level focuses on behavior choices, cognitive factors and
psychological factors such as knowledge, attitudes, beliefs, and personality traits. This
model is employed in this study to illustrate the ecology of families with

children/adolescents with Type 2 diabetes and the supportive systems within it. Thus, the

52

specific components of interest for children and adolescents with diagnosed Type 2

diabetes are the ecologies characteristic of the different systems at the different levels.

Figure 3: Model of supportive systems in etiologies of children and adolescents with

Type 2 diabetes.

Social Structure, Polig, & System

Interpersonal

 

Conceptual Model:

By employing a combination of Bubolz and Sontag’s (1993) human ecology theory and
McLeroy’s Social-Ecological Model for nutrition evaluation (1988), the things the
children/adolescents diagnosed with Type 2 diabetes perceive as having assisted them in
controlling diabetes and adapting to changes in lifestyle alter the diagnosis will be
characterized as the inputs into the ecology (Figure 4). In this conceptual model, the
inputs will be characterized as representing one of the following systems: family/social
support, individual themselves, and diabetes care institutions. How these inputs
contribute to the throughput (controlling diabetes after diagnosis) and thus facilitate the
outcome (good glycemic control and healthy lifestyle) are of specific interest. This
model proposes that, the family/social support (structure of the family, ethnicity, socio-
economic support, moral support of parents etc. ), the individual themselves (their own
behaviors, beliefs/values, attitudes, availability of resources), and the institutions
(diabetes centers, diabetes educators, physicians, insurance agencies, or other social
support agencies) are all inputs that influence an individual’s adapting or adhering to the
self care behaviors, and hence help in achieving better diabetes control. Based on the

conceptual map and the literature, research questions were derived.

Research Questions:
1) How do family factors facilitate or inhibit the management of diabetes?
2) How do individual’s values and behaviors influence the management of diabetes?

3) How do institutions influence the aspects of diabetes management?

54

Figure 4: Conceptual Framework adapted from Bubolz & Sontag, and McLeroy’s theory

Inputs \
/

 

 

 

 

 

 

Family/social support Individual Institutions
Structure Values/beliefs Government
Ethnic origin Behaviors Diabetes Education
SES Attitudes -physical activity
Relationship with family 'diet

 

 

W Availability of resources

 

 

Throughputs D

 

 

 

Adaptation
Adherence/
Compliance/
Selfcare /
Management

 

 

/

 

 

 

 

 

Diabetes Control

 

 

\
C Output :1
\

4/

55

CHAPTER 3

Methods

Objectives and hypotheses
The objectives of this study were:

1) To estimate the proportion of diagnosed Type 2 diabetes among children and
adolescents (6-19 years) who have either Type 1 or Type 2 diabetes at
endocrinology Specialty clinics in Michigan.

2) To determine glycemic control and associated factors (including biomedical,
socio-demographic and family factors) in this pOpulation compared to Type 1
cases.

3) To determine the ecological factors that influence glycemic control in the

population of children and adolescents with Type 2 diabetes.

Hypotheses for this study were:

1) The proportion of diagnosed Type 2 diabetes in children and adolescents aged 6-
19 years fiom endocrine specialty clinics in the state of Michigan will be
comparable to the national estimated rates of 8-45% for children and adolescents
diagnosed with either Type 1 or Type 2 diabetes.

2) Glycemic control will be comparable in Type 1 versus Type 2 diabetes patients in
this age group.

3) Data will Show that patterns of self-care adherence related behavior (dietary

practices, physical activity and home diabetes status monitoring) will differ

56

between good glycemic control (GHB <7%) and for these who have a GHB 27%

for those diagnosed with Type 2 diabetes.

Design

This was a two phase, cross sectional study, which was descriptive and exploratory in
nature. Data was collected for pediatric children with diabetes from medical chart
reviews and patient interviews. This two-phase study was conducted in pediatric and
adult endocrinology specialty clinics in Michigan. In Phase 1 of the study, data regarding
total number of youth aged 6-19 years with diabetes (Type 2 or Type 1) was obtained
from clinic data systems to estimate the percentages of diagnosed Type 2 diabetes.
Additionally, glycemic control and associated factors (type of diabetes, age, gender,
ethnicity, puberty, weight, and height) were abstracted from the charts to predict the
effect of these independent variables on glycerrric control in children with Type 1 or Type
2 diabetes. Phase 2 encompassed an in-depth interview study of a sub-sample from
Phase 1 of Type 2 diabetes cases, to identify social and behavioral variables associated

with glycemic control.

Sites

Pediatric and endocrinology clinics in the state of Michigan were selected for this study
because of the fact that they are more likely than primary care clinics to have a diagnosed
population of diabetes patients (Weatherspoon et al., 2001). Diabetes Centers with a
significant number of children and adolescents (physician diagnosed cases 25) were
considered eligible. Twelve clinics were contacted, but four were excluded due to

insufficient or no cases of children or adolescents diagnosed with Type 2 diabetes. For

57

this study, therefore eight endocrinology specialty clinics, each with over five identified
cases of Type 2 diabetes consented to data collection. The eight eligible clinics are
distributed over the state of Michigan: west central Michigan (Lansing-Sparrow Hospital,
Grand Rapids- Saint Mary’s Mercy Medical Center and DeVos Children’s Hospital);
southeast Michigan (Detroit- Henry Ford Children’s Hospital and University of Michigan
Medical Center); east central Michigan (Saginaw— Covenant Hospital and Hurley Medical
Center in Flint) and south central Michigan (J ackson-Foote Hospital). DeVos Children’s
hospital and Children’s Hospital of Michigan conducts satellite clinics in half of
Michigan (West, Central, & East) and hence provides information for half of the state’s
pediatric population diagnosed with diabetes (age = 6-19 years). The excluded diabetes
centers were from the Upper Peninsula, two clinics in Kalamazoo and one clinic in

Midland.

Target Population

Study subjects for Phases 1 and 2 were children aged 6-19 years of age, medically
diagnosed with either Type 1 or Type 2 diabetes, and treated at endocrinology clinics.
Previous studies have shown 10-19 years as the probable age range for Type 2 diabetes
cases in children and adolescents, but based on personal communications with
physicians, Type 2 diabetes cases have been reported in as young as 6 years old. Hence,
in order not to exclude these cases, the selected age range for this study was determined

as 6-19 years of age.

58

The population base for Phases 1 and 2 was selected fiom all children and adolescents
with a medical diagnosis of diabetes (Types 1 or 2) in the age group of 6-19 years, who
were “Active” cases and whose records are accessible and available from the eight sites.
“Active” was defined as having attended the clinic for at least six months prior to the
starting date for data collection at that clinic. The patient population in these clinics was
drawn from the entire state of Michigan. Six months was chosen as the criterion of active
patient eligibility because the Type 2 patients are expected for clinic visits at three
months intervals at least. The exclusion criteria were children 6-19 years old who have:
1) Physician noted maturity-onset diabetes of the young (MODY); 2) Type 2 diabetes
caused by steroid use; 3) Type 2 diabetes secondary to cystic fibrosis; and 4) Children
diagnosed with pre—diabetes (fasting blood glucose levels 2110 mg/dl and < 126 mg/dl).
These cases were excluded to obtain “true cases” of Type 2 diabetes as defined by the
American Diabetes Association (ADA, 2000). For Phase 2, a sub sample from Phase 1

was selected.

Since Phase 1 consisted only of medical record reviews and no personal identification
was used on the data abstraction form or for analyses, approval was required only from
Michigan State University Committee on Research Involving Human Subjects
(UCRHIS), the clinic directors and the Review Boards of the individual clinics. Human
subjects study approval was granted on February 13m, 2002 by expedited review from
UCRIHS. Phase 2 involved in-depth patient interviews. Therefore, additional approvals
were necessary from UCRHIS and individual informed consent was obtained from the

patients and their parents or guardians.

59

PHASE 1

Procedure for objectives 1 and 2

In Phase 1 of this study, data on the total number of youth aged 6-19 years with diabetes
(Types 1 or 2) was obtained from clinic data systems. These data were used to estimate

the proportion of diagnosed Type 2 diabetes in this population.

Diagnosed Type 2 DM
Diagnosed Type 1 + Type 2 DM

 

Estimated proportion of diagnosed cases =

Additionally, a study comparing medically diagnosed Type 1 with Type 2 diabetes
subjects in the age group of 6-19 years controlled for age and gender was also conducted.
The medical records of these youth were compared for diabetes diagnosis, risk factors,
and associated factors (demographic; biomedical-such as duration of diabetes, co-
morbidities; control and treatment variables). The purpose of the medical record review
was to estimate the prevalence of glycemic control in these populations and identify
associative risk and control factors considered in intervention. A data collection form
was used to abstract the information described above from the medical records (Appendix
B). Content validity of data collection form was established by asking 6 diabetes
professionals (2 pediatric endocrinologists, 1 nurse, 2 RD PhD’s, l Dietitian) to review
the data collection protocol sheet. Responses from 4 reviewers were obtained and the
changes requested included: re- organization of questions, re-phrasing of questions to
make them simpler, and deletion of questions which seemed irrelevant. Five trained

people including the primary researcher conducted data abstraction at all centers to

60

maintain consistency and confidentiality of records. The training for these researchers

was conducted by the primary researcher.

Variable definitions

The variables of interest in Phase 1 of the study were: diabetes diagnosis; glycosylated
hemoglobin; demographic data such as age, gender, race/ethnicity, family history,
pubertal status; anthropometric data such as weight, height, and weight at birth; and lipid
profiles as available. For the purposes of clearly understanding the parameters of

interest, all the variables are defined in the following section.

Dependent variable:
Diagnosis of diabetes- Number of those diagnosed by the physician with either Type 1 or
Type 2 was collected as noted on the patient chart or clinic records. This was used to

calculate the proportion of those diagnosed with Type 2 diabetes among this population.

Diabetes control- Although lipid profiles can also be used to objectively assess diabetes
control, glycemic control was selected because of the greater consistency of occurrence
in the medical records. GHB is a continuous variable, but for bivariate analysis, it was
recoded into a dichotomous variable (57%, >7%). The cutoff point for glycemic control
was selected from the American Diabetes Association guidelines which, defines the goal
for ideal glycemic control as being less than or equal to 7% hemoglobin Alc (American

Diabetes Association, 2000).

61

Independent variables

Age- Data was collected and entered in terms of date of birth (mm/day/yr). If we had a
day missing for some subjects, but month of birth was available, then the first day of the

month was considered as the day of birth.

Race/Ethnicity- Race/ethnicity was a self-reported categorical variable. Depending upon

the sample size in each category, categories were collapsed.

Gender- The data was coded as 0 for male and 1 for female, a dichotomous variable.

Family History- Data regarding frequency of diabetes in first or second-degree relatives
was collected. This was entered into the database as a dichotomous variable (yes=1 and

no=0).

Gestational diabetes of the mother- These data were abstracted from the charts when

available, and entered into the database as a dichotomous variable (yes=1 and no=0).

Height/weight- Height was recorded in meters and weight in kilograms, both were
continuous variables. The BMI variable was created by using the formula BMI= wt
(kg)/ht (m2). The BMI was then recoded into percentiles, where 2 85th to 95th percentile
is defined as at risk of overweight and 295th percentile as overweight (CDC, 2000). Thus

this variable was categorical.

62

Duration of diabetes- The duration of diabetes was determined from the medical record
data as the number of years fi'om the date of diagnosis, e.g., 2 years or if 6 months, then

converted to 0.5 years, as an ordinal variable.

Diabetes management- Information regarding oral medication, insulin intake, dietary
prescriptions, and exercise recommendation was recorded from medical charts as

categorical variables.

Hospitalization- Data regarding number of hospitalizations (continuous variable) in the
past year and reason for hospitalizations (categorical variable) was recorded from chart

reviews.

Co-morbidities- Co-morbidities were recorded as reported in the charts. These data were
entered into the dataset as yes (yes=1) and no (no=0) for each co-morbidity as a

categorical variable.

Weight at birth- If available, birth weight data was collected in kilograms and entered as
continuous variable. For analysis purposes birth weight was recoded into categories such

as low birth weight (<2.5 kg), normal birth weight (2.5-4.5 kg) and high birth weight (2

4.5 kg) categories.

63

Puberty- Information regarding age at onset of puberty (continuous variable), stage of
puberty at diagnosis of diabetes (ordinal variable), and current sexual maturation stage

(ordinal variable) was collected as available in the charts.

Acanthosis Nigricans- Because of its association with higher rates of Type 2 diabetes
mellitus in youth, Acanthosis Nigricans was viewed as a useful physical screening tool
for the identification of high-risk youth subjects with Type 2 diabetes mellitus. Data for
this information was recorded from medical charts and coded as a dichotomous variable:

presence of Acanthosis Nigricans (yes=1) or absence (no=0).

Lipid Profile and other biochemical variables- Data regarding total cholesterol (mg/d1),
Triglyceride (mg/d1), HDL cholesterol (mg/d1), LDL cholesterol (mg/d1), C-peptide,
Insulin, Islet Cell Antibodies, and Blood Pressure was obtained from the charts. These

were entered as continuous variables.

64

Data processing and analyses

Data from the medical record abstracting was coded for entry and analyzed with the
SPSS version 11.0 (2002). To detect incorrect, obvious raw data entry problems,
frequencies were run for all variables. Thus, contradictions and missing data could be

identified and corrected where applicable.

Descriptive statistics as well as contingency table analysis of the proportion with GHB
value 27% by race, gender group, and selected medical history variables were used to
determine bivariate relationships. Comparison of biochemical and clinical variables
between children with Type 1 and Type 2 diabetes were also conducted. Multivariate
analysis (logistic regression) was conducted to determine whether the findings from the
overall and stratified bivariate analysis persisted, when potential confounders were
adjusted for. Odds ratio were done to estimate magnitude of the association of a

characteristic with an outcome.

PHASE 2

Procedure for objective 3

Phase 2 was a triangulated qualitative study that included in-depth interviews and survey
questionnaires to assess medication intake, home blood glucose monitoring, and dietary
and physical activity patterns as well as barriers and facilitators. Triangulation refers to
combining methods or sources of data to enhance understanding of the setting and the
people being studied (Taylor and Bogden, 1998). Triangulation of data also serves to

support the scientific status of research and increase its utility to readers (Reinharz, 1992)

(Figure 1).

65

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

8332603 323m
:82 3220:: .3158 >255 .
50% 34% 898.590 Eommtfia oEqfionoQ E25 Rosco—2
. A
as... ”Sago 35530
”N 0923 J 82$

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3mm— .«0 muoufiom

 

 

 

ASE—O me moot—em 2.9.8.5. beta—awaatt

.83 mo 3238 30.5me muggy. onE J onE

66

Hence, the research strategy used for this study which included an in-depth interview
with diagnosed cases of Type 2 diabetes adolescents in conjunction with soliciting data
regarding self-care practices via a questionnaire was the most effective way to best
accomplish the goals for this Phase of the study (F etterrnan, 1989; LeCompte & Preissile,
1993; Yin, 1989). More specifically information pertaining to parental attitudes,

individual experiences, social networks and support systems was sought.

The self-care practices assessed in this study were: home-blood glucose monitoring,
medication intake, physical activity and dietary patterns. The American Association of
Diabetes Educators (2002), considers these diabetes self-care behaviors as important for
determining the effectiveness of diabetes self-management education at individual and

population levels, and each behavior is important to the overall management of diabetes.

Rationale for qualitative approach

Given the exploratory nature of the research questions, a qualitative approach was the
best fit for this study. Qualitative research develops concepts, insights and
understandings from patterns in the data rather than collecting data to assess pre-
conceived models or theories (Taylor & Bogdan, 1998). Since the experiences of
children and adolescents with Type 2 diabetes in relationship to how they deal with
diabetes diagnosis and management has not been explored in previous research,
qualitative methods provide an appropriate framework to allow data generation from

emerging themes and patterns that are exhibited.

67

Qualitative data provides descriptive data in people’s own written and spoken words and
observable behavior. A key objective is to ascertain “the meanings that people attach to
things in their lives” and is designed to ensure a close fit between the data and what

people actually say and do (Taylor & Bogden, 1995).

For this study, representing or “knowing” a patient’s living experience of diabetes is
essential because diabetes is a self-managed disease (Anderson, 2001). It is the patient’s
self-management decisions that have the greatest effect on their health and well-being,
and these decisions are influenced by the environment, society, family or any thing that
directly or indirectly influences the individual. The most faithful representation of the
patient’s experience is reporting the patient’s own story in his/her own words (Anderson,
2001). Qualitative research attempts to introduce rigor, objectivity, and analysis to story
telling, while preserving as much of phenomenological richness of the patient’s
experience as possible. As long as diabetes remains a self-managed disease, representing
a patient’s personal experience will remain a key aspect in helping health professionals
understand how to better assist patients with diabetes. Therefore the intent was for
patients’ stories to provide health professionals with necessary data to develop effective

educational, behavior change and coping strategies.

Validity
Qualitative methods are designed to ensure a close fit between the data collected/reported
and what people actually say and do. By interviewing people in their daily lives,

interviewing them about what they think of a certain topic, and looking at the documents

68

they produce, the qualitative researcher obtains firsthand knowledge of social life
unfiltered through operational definitions or rating scales (Taylor & Bogdan, 1998).
Qualitative methods provide more accurate information about subject’s experiences as
they have the potential to offer a forum for their experiences without succumbing to

power imbalances and imposed categories (Epstein J ayaratne & Stewart, 1991).

Another feature of qualitative data is their richness and holism. Data have strength for
revealing complexity and “thick descriptions” that are vivid, nested in real context and
demonstrate truth in a way that it impacts the reader (Miles & Huberman, 1994).

The use of triangulation enhanced the validity of the study (Miles & Huberman, 1994).
Triangulation permitted the capturing of a more complete, holistic and contextual picture
of subjects, in their individual contexts, by gathering both qualitative and quantitative
data (Epstein Jayaratne & Stewart, 1991). The use of mixed methods is a way to offset
disadvantages of one method with the strengths of another (J ick, 1979). A combination
of methods should result in more powerful research findings, which effectively tests

theory and is convincing as well (Epstein J ayaratne & Stewart, 1991).

This project utilized the triangulation of qualitative and quantitative data to maximize

research results. Integration of scholarly literature added further validity to this study.

Subject recruitment and eligibility
Subjects: The targeted study population was adolescents aged 14-18 years diagnosed

with Type 2 diabetes (i.e. criterion-based sampling). This age group was selected based

69

on the mean age of the sample from Phase 1 (mean age=l6). Moreover, at this age
adolescents are making more independent food choices, independently conducting blood
tests, administering insulin injections, and are not monitored by parents to the same
extent as at a younger age. All the participants were residents of Michigan. Subjects
meeting the ADA target goal for glycemic control (HbAlc <7%) as well as those who did
not (HbAlc 27%) were selected to determine whether differences in self-care behaviors
(dietary, physical activity, home blood glucose monitoring, medicine intake) exist
between the two groups. An effort was made to have equal number of subjects in both

the groups.

Sample size: In qualitative studies, determination of sample size is usually done at the
end of the research, as there is an inverse relationship between the number of informants
and the depth to which you interview each subject (Taylor and Bogden, 1998). For this
study, we anticipated based on similar qualitative studies published in the literature, that a
sample of 20 subjects would be sufficient to obtain good quality data. However, the final

number of 16 subjects was ultimately determined by data saturation.

Recruitment: Participants were recruited through fliers in physicians’ offices at
endocrinology clinics which participated in Phase 1. Participants received a $20 gift
certificate and a pedometer as tokens of appreciation for agreeing to participate. The time
and place of interviews was arranged according to the convenience of the participant.
UCRIHS approval for Phase 2 was obtained from Michigan State University before data

collection was commenced. In addition to UCRIHS approval from Michigan State

70

University, IRB from endocrinology clinics was also obtained, and all the participants

and parents/ guardians were requested to sign a consent form (Appendix C).

Data collection:

(1) Semi-structured interviews: Qualitative interviews were used to elicit in-depth
opinions and views regarding various issues such as family support, individual’s own
behavior, and influence of institutions (School, diabetes center, church) from the
participant’s perspective. Interviews lasted approximately for l to 1 1/2 hours in duration,

and were tape-recorded in their entirety and transcribed verbatim.

The interview questions were clustered around five general themes and were Open and
intentionally non-directive to trigger broad, comprehensive responses. The core clusters
included (a) experiences with diabetes prior to diagnosis (b) individual perspectives on
diabetes self-management recommendations (c) current lifestyle practices ((1) social and
institutional conditions that influence their diabetes care (e) social support (family,

fiiends). (Appendix D).

(2) Before commencing the main interview questions, there were some ‘Vvarm up” survey
questions which helped obtain data such as : ethnicity; age; education level; living status;
duration of disease; family history of diabetes; number of doctor visits per year; and type

of medications (Appendix D).

71

(3) Exercise/physical activity: The purpose of the physical activity questionnaire was to
assess the type, frequency and duration of leisure time activity. A good physical activity
regime for adults and adolescents is defined as participating in physical activity at least
three times a week, but preferably all days of the week, for 30 or more minutes (USDA,

2002; Diabetes Prevention Program Research Group, 2002).

In this study a qualitative assessment for physical activity was sought, which was
practical in terms of administration ease, time and cost for the investigator and the
participants. Adaptation of the physical activity questions which were used by the
National Longitudinal Study of Adolescent Health and Youth risk behavior survey
(CDC, 2003), were regarded as appropriate for the study (Appendix E). It was important
to establish whether subjects exercised at all, and then categorize the activities which
would most likely be selected, and assess the frequency and duration. Consistent with
other self-care variables, subjects were asked to discuss the barriers they encountered in

achieving any exercise as recommended.

(4) 24-hour dietary recalls

The purpose of this section was to obtain information regarding subjects’ usual eating
habits or patterns, which could be used in targeting goals for nutrition education. Dietary
intake and compliance can be assessed quantitatively or qualitatively via several methods.
In this study to obtain dietary information, two 24-hour recalls (one weekend and one
week day preferably) were used (Appendix F). Food recalls were conducted using the
USDA multiple pass method (Moshfegh et al., 1999) by a trained interviewer. Since,

only one person was interviewing, inter-person variability was avoided and consistency

72

with the approach to interviewing was facilitated. Specific aspects to be examined in this
study were the frequency and type of meals and dietary habits and patterns with regard to
carbohydrate intake, fat intake, fiber intake, soda and snack consumption. Other aspects
examined were: percentage kilocalorie coming from carbohydrates, carbohydrate intake,
and percentage kilocalories from fat, total consumption of soft drinks and sport drinks

consumed.

Data analysis:
A. In-depth interviews: The data was organized and analyzed in the following steps:

1) After each interview, the audiotapes were transcribed verbatim by the researcher
who was present at the interviews. All transcripts were re-read while listening to
the tape to check for accuracy and fix errors, and to help the researchers become
more familiar with the data. Two researchers (a graduate student and a senior
dietetics major student trained in qualitative studies) reviewed and discussed the
transcripts for accuracy.

2) The transcripts were individually coded by two researchers, checked, and
discussed by both the researchers until consensus was reached upon the correct
code. Units were very rarely coded twice; this was done only when consensus
could not be reached regarding which code to use. The coders met regularly
throughout the coding process to compare codes. The constant comparative
method developed by Glaser and Strauss (1967) and later modified by Lincoln
and Guba (1985), where every data unit is compared with every other data unit,

was used for analyzing the data. The team developed a preliminary list of code

73

words based on recurring themes and some pre-derived categories driven by the
theoretical model based on the major research questions (Table 1).

3) Data from transcripts was loaded into NUD*IST N6 software (N on-numerical
Unstructured Data by techniques of Indexing Searching and Theorizing, QSR,

2003) for tabulation and identification of responses by code word.

Based on the developed preliminary codes, a coding matrix was constructed. The
researcher recorded all relevant statements from each subject’s transcript on the coding

matrix.

B. Physical activity:

Descriptive statistics was conducted to determine: Average amount of time spent
exercising; types of exercises subjects were involved in; how many times per week they
exercised; and how many met the recommendation of physical activity of 30mins/day &

23x/week (USDA 2002).

C. 24-hr dietary recall data:

Dietary analysis was conducted by using Nutritionist V (First DataBank, 1999).
Descriptive statistics was conducted for percent kilocalories coming from carbohydrates,
carbohydrate consumption, percent kilocalories from fat, and amount and number of
times soda and sport drinks are consumed per day. Descriptive statistics was also
conducted to determine how many subjects consumed breakfast, lunch, dinner and

snacks, as well as how many meals were skipped per day.

74

 

5050055
00.0 505035 .m

50505505 0000006

033% a? =5

mama—0: 5 0n 2005 00800 53200500
0000005 00 20.. 05 5:5 :0» 00 555 .m
05050555 0000520 00.0

005000.. 5.5.0: 0005 05 :00: 0.555 .m

550505505 0000306

 

 

 

 

 

 

 

 

 

52555: 005008 55—0: 0002 .m :0 00000002003555 0:850» m0 .00 $0005 05 00:03.05
.00 0.0M 0050m A .00 00003.5: 050 0x8 00 30; F50— :0» 20 20:3 ._ 5250305 00 302 .m
90: £3 .0 556 $0050» 00 0.50 00.8 :0» 020: 5:3 .0
053.005 $5 55502 - 3.8.50»
£0200 E035 20m .N m0 050 mac—S 50¢ :0» 3000— 055? .m
505000055002 0062008 0% a»; $000050
00% w530=8 00 anfimzoam - .50» 05505 00 :0» .00 58.595 z fl .0
50355055002 006008 550$ 50» .23 000
a. 00:. w530=£ 00 52.55 - =0» 30: 009520 80000:. was 30: .m $000906 .00
0mmoc0xm - 33:80.20? 30: 00 :0» 00 5:3 .N 5050355 00:05.5:
030000200 005 - 0.:— »=00 00m: 50» £03200 55 m020>
£52305 503200 50505252 ._ :0 0000005 .00 80am 00m5£0 0000020 530: we: 30: ._ 300.300 00 30$ .N
«um—0: 000: :0» 00:3 20.580
20 E0: 00m ES :0» 00 50:3 0 H .v
05.85.2282 €80 - seen:
5:00:003002 0.000350 - 00>» »=E£ 50» 5 0:3 £80206
£09550 3 cocomom .v we: :0» 50 558 “we :0» 00:? .m $000530
2D :55 300505 50000050 m0 50505505
2000050 8 050098 00ch— .m 025 »=E£ .50» 5 0&0 0:0»:0 000D .N 05 0325 00 0552a
503% toaqsm .N »=E£ m0 000055: 3:53 £0000» _0_00m\»=5£
0.5095 .mmoom 050250 »:50m 4 E0050 »=50...~ 50» 0a 00 02500 :0» 00 05>» ._ 00 30: 4
503000.
03050.; 00505.25 0052:. 000500=O 300:0»:— 5030000 £05003—
meE—E 03:50:22.0 .082: 0020?»..02;

 

 

5035.0 800 :0 00000 003.200 00805-50 000 0052:. n_ 030,—.

75

Working definitions of terms:

1.

Family: Families in an inclusive sense are defined as composed not only of persons
related by blood, marriage, or adoption, but also sets of interdependent but
independent persons who share some common goals, resources, and a commitment to
each other over time (Bubolz and Sontag, 1993).

Need: Requirements of families and individuals that must be met at some level if they
are to survive and engage in adaptive behavior.

Values: Human conceptions of what is good, right, and worthwhile.

Goals: “Ends-in-view”, something one is willing to work to achieve (Gross et al.,
1980). Together with values, goals are a major motivating force in families.
Attitudes : A complex mental state involving beliefs, feelings, and values that make
one act in certain ways.

Resources: Ways by which families meet needs and adapt to changing environments
and stressors. Examples of personal resources include skills, health, knowledge, and
intelligence. Examples of interpersonal resources are commitment, cohesion, and
social integration. Some nonhuman resources include housing, clothing, money, and
the like.

Perspectives: The process by which environmental information is registered by the
senses, organized and made available for use (Melson, 1980). People respond
selectively to environmental stimuli that are then symbolically interpreted through
personal and cultural meanings.

Social support: Family, close friends, relatives who provide emotional support and

help with management of diabetes.

76

9. Institutions: Diabetes education centers, government organizations, and other non-
governmental organizations.

10. Community Support: Community agencies participating in the treatment of the
family and/or one or more of its’ members. They are professionals and agencies that
provide services to the family.

11. Individual: In this study the individual is the participant diagnosed with Type 2
diabetes in the age group of 14-18 years.

12. Adaptation: Adaptation is the process of adjusting to changes. Individuals,
regardless of their particular structure, transform information and engage in
adaptation.

13. Diabetes Control: Subjects meeting the ADA target goal for glycemic control

(HbAlc <7%)

77

CHAPTER 4

Proportion of children and adolescents with Type 2 diabetes in

Michigan

Abstract

Background: Type 2 diabetes mellitus (T2DM) in children and adolescents is a “newly
recognized” pediatric disease, nationally and in the state of Michigan. Childhood
overweight/obesity has been shown to be a strong predictor of this disease. The fact that
the prevalence of overweight/obesity in youth is a serious concern in Michigan and there
is no data on T2DM in this vulnerable age group, provided a strong justification for this
study. If not identified or poorly controlled, there is a potential for devastating
complications at an early age.

Objectives: 1) To estimate the proportion of diagnosed T2DM among children and
adolescents (6-19 years) who have either Type 1 or T2DM at endocrinology specialty
clinics in Michigan; 2) To determine the associated factors among youth with Type 2
diabetes; and 3) To assess glycemic control in youth with T2DM.

Study Design: Retrospective chart reviews of youth 6-19 yr diagnosed with diabetes
were conducted at endocrinology clinics in Michigan. In-depth data was collected for
those diagnosed with T2DM.

Results: Of a total of 2,018 subjects (6—19 yr) diagnosed with diabetes, 220 (11%) had
T2DM. Among those 10-19 yr, the proportion of children with T2DM was significantly

higher (14%). The estimated prevalence of T2DM in the lower peninsula of Michigan

78

was 11.03/ 100,000. The mean (iSD) age and body mass index (BMI) at presentation
were 13 d: 2.8 years and 35 :1: 12.5kg/m2, respectively. The BMI for 85% of the youth
was 2 95th percentile (overweight) and 83% were at 2 Tanner stage III. Ethnicity
distribution was as follows: African Americans (51%), Hispanic (15%), Caucasians
(12%), and others (22%). The male to female ratio was 1.3:], and females were
diagnosed 1 year earlier than males. The majority of the youth had Acanthosis nigricans
(73%), a positive family history of diabetes (95%), and 65% of the subjects were living in
single-family households. There was a high prevalence of metabolic risk factors in youth
with T2DM: high blood glucose HbAlc Z 7 (64%), elevated serum triglycerides Z 150
mg/dl (33%), HDL-C <40 (49%), and blood pressure 2 90th percentile (85%).
Conclusion: T2DM prevalence among children and adolescents in Michigan is high,
mimicking the national rise in Type 2 diabetes and concomitant with the increase in
childhood and adolescent obesity. While, ethnicity and obesity/overweight were
significantly associated with T2DM in youth as would be expected, of greater concern
were the metabolic aberrations. Once identified, controlling T2DM in children and
adolescents is imperative to decrease the likelihood of devastating complications at a

young age.

79

Introduction

Diabetes is clearly recognized as one of the most common and costly diseases in the
United States today, affecting more than 15 million Americans with as many as half
undiagnosed (Centers for Disease Control and Prevention (CDC), 2002). Of the two
major classes of the disease, Type 1 and Type 2, the latter is the more predominant form
of the disease (90%). The onset of Type 2 diabetes typically occurs primarily in older
adults, whereas Type 1 diabetes typically occurs in children and young adults. However,
T2DM in children and adolescents concomitant with the rising rates of
obesity/overweight as referred to in youth, has recently emerged as a “newly recognized”
pediatric epidemic in the US towards which enhanced state and national efforts need to
be directed. Among adults, numerous studies document a significant correlation between
the prevalence of T2DM and relative weight for height (Mokdad et al., 2000 & 2001;
Ford etal., 1997; Headley et al., 2004). Ford et al., (1997) demonstrated that for every 1
kg increase in measured weight the risk of diabetes increases by 4.5% in a national
sample of adults. In children the relationship of weight and height is assessed as greater
than 85th percentile (at risk of overweight) and greater than 95th percentile (overweight).
Childhood and adolescent overweight levels have been documented as steadily increasing
between the 1960s and 19908 (Gortmaker, 1987; Campaigne, 1994; Webber, 1994).
Current data from NHANES [II (1998-1994) of a nationally representative sample of
children, aged 6-11 years and adolescents, aged 12-17 years and the National
Longitudinal Study of Adolescent Health (Add Health) (NCHS 1994, Flegal et al., 2001)
indicate that approximately 14% of children and 12% of adolescents are overweight, with

an almost equal distribution among males and females. Obesity-related studies in

80

Michigan have shown that in children aged 4 to 17 years, among boys, 38% were above
the 85th percentile and 16% above the 95th percentile. Of the girls, 33% were above the

85th percentile and 13% were above the 95th percentile (Gautheir et al., 2000).

Studies have reported increasing rates of T2DM in American Indian, African American,
and Hispanic children from North America (Dean etal., 1988; Dean et al., 1992; Harris et
al., 1996; Pinhas-Hamiel et al., 1996; Pihoker et al., 1998; Fagot-Campagna et al., 2001;
Neufeld, 1998). Reported rates of prevalence and estimates vary based on ethnicity, but
CDC estimates that T2DM represents approximately 8-45% of all children and
adolescents diagnosed with diabetes in large US pediatric centers (CDC, 2002). While
the existing evidence would strongly support the conclusion that the incidence of T2DM
in children and adolescents has increased significantly during the past several decades,
the exact prevalence of the disease, both nationally and regionally, has yet to be
determined. The limited data on the prevalence and incidence of T2DM and associated
factors in children and adolescents, makes it difficult to identify and characterize the
target population and plan interventions to better control diabetes in this age group.
Associative factors such as being overweight, presence of acanthosis nigricans, and
positive family history of diabetes might help identify & characterize specific type of
diabetes in youth (Pinhas-Hamiel et al., 1996; Pihoker et al., 1998; Fagot-Campagna et
al., 2001). In addition, the precise risk and control-related factors as related to T2DM in
children and adolescents are not fully understood. Such information is critical if efforts

to facilitate the prevention or amelioration of the many debilitating complications of

81

unidentified or uncontrolled diabetes in the pediatric population are to be adequately

addressed by the health professional community.

Recently Michigan has been ranked number three in the country for obesity, and one city
Detroit, was classified as the “fattest city”, warrants the importance of this study. There
has been a national concern about increase in childhood overweight/at risk for overweight
and these data are mirrored in the state of Michigan (Youth Risk Behavior Survey, 2003).
Hence, the primary objectives of this study are: 1) To estimate the proportion of
diagnosed Type 2 diabetes among children and adolescents (6-19 years) who have either
Type 1 or Type 2 diabetes at endocrinology specialty clinics in Michigan; 2) To
determine the associated factors among youth with Type 2 diabetes; and 3) To assess

glycemic control in youth with Type 2 diabetes.

Research methods

A retrospective chart review of youth previously diagnosed as having T2DM was
undertaken at the endocrinology clinics in Michigan. Data regarding the total number of
youth 6-19 yr with diabetes (Type 2 or Type 1) was obtained fi'om clinic data systems for
each endocrinology clinic to estimate the percentages of diagnosed T2DM. Approval
from Michigan State University Committee on Research Involving Human Subjects

(U CRIHS), the clinic directors and the Review Boards of the individual clinics was
obtained before data collection could be commenced.

Sites: Pediatric and endocrinology clinics in the state of Michigan were selected for this

study, as they are more likely than primary care/ general family practice clinics to have a

82

diagnosed population of diabetes patients based on researchers previous experience at
primary care/ general family practice clinics (W eatherspoon et al., 2001). Diabetes
centers with a significant number of children and adolescents (diagnosed cases 35) were
considered eligible. Twelve clinics were contacted, but four were excluded due to
insufficient or no cases of diagnosed T2DM children and adolescents. For this study,
eight endocrinology specialty clinics meeting the eligibility criteria consented to data
collection. The eight eligible clinics were distributed over the state of Michigan: west
central Michigan (Lansing-Sparrow Hospital, Grand Rapids- Saint Mary’s Mercy
Medical Center, and DeVos Children’s Hospital); southeast Michigan (Detroit- Henry
Ford Children’s Hospital and University of Michigan Medical Center); east central
Michigan (Saginaw- Covenant Hospital and Flint Michigan) and south central Michigan
(J ackson-Foote Hospital). DeVos Children’s hospital and Children’s Hospital of
Michigan conduct satellite clinics in half of Michigan (West, Central, & East) and hence
provides information for half of the state’s pediatric population diagnosed with diabetes
(ages 6—19 years). The excluded diabetes centers were the Upper Peninsula (N orthem
Michigan), two clinics in Kalamazoo (South East) and one clinic in Midland (East

Central).

Target Population: Subjects for this study were children 6-19 yr of age, medically
diagnosed with either Type 1 or T2DM, treated at endocrinology clinics. Previous
studies have shown 10-19 years as the probable age range for T2DM cases in children
and adolescents. However, based on personal communication with physicians, T2DM

cases were reported to occur in children as young as 6 years old. Hence, in order to not

83

exclude these cases, the selected age range for this study was determined as 6-19 years of
age. The population base for this study included all children and adolescents with a
medical diagnosis of diabetes (Types 1 or 2) in the age group of 6-19 years, who were
“Active” cases and whose records were accessible and available from the eight sites.
“Active” was defined as having attended the clinic for at least six months prior to the
starting date for the study. The patient population in these clinics is drawn from the
entire state of Michigan. Six months was chosen as the criterion of active patient
eligibility because the Type 2 patients are expected for clinic visits at least at three-month
intervals. The exclusion criteria were children 6-19 yr who had: 1) physician noted
maturity-onset diabetes of the young (MODY); 2) Type 2 diabetes associated with steroid
use; 3) Type 2 diabetes secondary to cystic fibrosis; and 4) children with pre-diabetes
[whose blood glucose levels are higher than normal, but not yet high enough to be
diagnosed as diabetes; Impaired fasting glucose 2 100 mg/dl but < 126 mg/dl]. These
cases were excluded to obtain “true cases” of T2DM as defined by the American
Diabetes Association (ADA, 2000). ADA defines T2DM in youth as: Classic symptoms
of diabetes (polyuria, polydipsia, and unexplained weight loss) and casual glucose 22%
mg/dl (11.1 mmol/l) 0R Fasting plasma glucose 21% mg/dl (7.0 mmol/l) 0R 2-hour
plasma glucose 2 200 mg/dl (11.1 mmol/l) during an Oral Glucose Tolerance Test

(OGTT).

Data on the total number of youth aged 6-19 years with diabetes (Types 1 or 2) was

obtained from the clinic data systems. These data were used to estimate the proportion of

diagnosed T2DM in this population as follows:

84

Diagnosed Type 2 DM
Diagnosed Type 1+ Type 2 DM

 

Estimated proportion of diagnosed cases =

The purpose of the medical record review was to confirm the data system diagnosis and
to estimate the prevalence of glycemic control in this study population/sample and to
identify associative risk and control factors as clinical criteria and lab values (insulin &
C-peptide) are the best determinants to help correctly identify T2DM and describe the
medical condition of this vulnerable group. Therefore, medical records of youth with
T2DM were reviewed for diabetes diagnosis, risk factors, and associated factors such as
demographic data, anthropometrics data, clinical symptoms, and lab values. The
presence of the following metabolic risk factors (metabolic syndrome cut points) was
noted: elevated serum glucose (HbAlc Z7), hypertension (blood pressure 2 90th percentile
for height), elevated serum triglycerides (Z 110 mg/dL), and low HDL-C (s 40 mg/dL)
(Cook et al., 2003). A data collection form was used to abstract the information
described above from the medical records. Content validity of data collection form was
established by asking 6 diabetes professionals (2 pediatric endocrinologists, l nurse, 2
Registered Dietitians with doctoral degrees and 1 practicing Registered Dietitian working
with patients with diabetes) to review the data collection protocol sheet. Responses from
reviewers were obtained and the changes that were requested included: organization of
questions, re-phrasing questions to simplify, and deletion of perceived irrelevant
questions. Four trained people conducted data abstraction at all centers to maintain

consistency and confidentiality of records.

85

Statistical Analysis: Data was analyzed using SPSS version 11.0 (2002). Descriptive
statistics (means i standard deviation and frequency of distribution) were calculated to
describe the sample. Prevalence was estimated using census data for the year 2002 for
Michigan and proportions obtained from the chart reviews. Bivariate analysis (chi-square
analysis) was conducted to determine the differences across gender and ethnicity by
selected medical history variables to determine relevant association. Comparison of

biochemical and clinical variables across gender and ethnicity was also conducted.

86

Results

Of a total of 2,018 patients 6-19 yr with diagnosed Diabetes Mellitus (DM), 220 (11%)
had T2DM. When data was analyzed for youth in the age range of 10-19 years, the
proportion of diagnosed cases of T2DM was significantly higher (14%). The distribution
of the sample by clinic is presented in Table 1. The proportion of children with T2DM
ranged from 6.5 to 21%. The majority of the subjects (98%) were in the age group of 10-
19 years. The estimated prevalence rate of T2DM in the lower peninsula of Michigan

was calculated to be 11.03/100,000.

Characteristics of the subjects with Type 2 Diabetes

The majority of cases were diagnosed during a routine physical examination for school or
sports. Signs of polyuria, polydypsia, and polyphagia were the most frequently
mentioned symptoms noted. Table 2 presents the descriptive characteristics of the

sample.

Race, gender, and Age. Fifty one percent of the subjects were African Americans,
followed by Caucasians and Hispanics. The gender distribution indicated that the
majority of the youth with T2DM were females (56%). The overall female to male ratio
was 1.3:1.

The mean age for diagnosis of T2DM was 13.00 i 2.8 years for the total sample. Female
patients were identified approximately one year earlier than the male patients except for
the Caucasian females. Caucasian females were diagnosed much later than Caucasian
males (p=0.06). Hispanic males were diagnosed at a much later age than other males

(p<0.05) and females of other races. Puberty data were available for only 65 subjects.

87

Of these 65 subjects, 83% were in mid puberty (Tanner stage 1]] or greater) at the time of

diagnosis.

Body mass index: The mean BMI in patients with T2DM was 35.0 i 12.5 kg/m2 (Table
2). Seventy eight percent of the T2DM subjects were 2 95th %tile for BMI, 11% were 2
85th %tile, and 11% were between the 5th and 85th percentiles (Figure 2). The majority of
cases 2 95th %tile, were females (55%) and Afi‘ican Americans (50%) compared to males

and other races respectively (p<0.05).

Family History, Acanthosis Nigricans, & Living Status: Ninety-five percent of T2DM
subjects had a positive family history of diabetes. Acanthosis Nigricans was present in
73% of the subjects at the time of diagnosis. Data regarding living status of the subjects
with T2DM indicated that 65% of the subjects with T2DM were living with single

parents (Table 3).

Clinical parameters: Mean i SD of clinical parameters are reported in Table 4. Mean
glycosylated hemoglobin (HbA1C) recorded at the first visit for the total sample of Type
2 DM subjects was 9.3 i- 3.1. Both C-peptide and insulin values for these subjects were
higher than normal values. More in-depth data analysis revealed that more subjects who
had their HbAlc 2 7% also had high total cholesterol (p<0.05)and high LDL-C (p<0.05).
Subjects with BMI 2. 95‘h percentile had TG 2 150 mg/dl (p=0.09) and HDL-C s 40

mg/dl (p<0.001).

88

Discussion

This study demonstrates that the proportion of diagnosed T2DM among children and
adolescents in Michigan is very comparable to the results published by previous studies
ranging from 8-45% (Pinhas-Hamiel, 1996; Pihoker et al., 1998; Neufeld et al., 1998;
Glaser, 1998; Macalusco et al., 2002). Our study demonstrated that diagnosed T2DM
accounted for 11.1% of all children and adolescents diagnosed with diabetes in the age
group of 6-19 years, and 14% of all children and adolescents diagnosed with diabetes in
the age group of 10-19 years at the adult and pediatric clinics in the state of Michigan.
Adolescents in the age group of 10-19 years have a higher proportion of youth with
diagnosed T 2DM, similar to that of some of the previously published studies (Pinhas-
Hamiel et al., 1996; Glaser, 1998; Neufeld et al., 1998). However it is important to note
that this disease is also a problem in youth who are as young as 6 years. This makes it
important for adequate screening to be done when youth have risk factors, even if not
symptomatic at the time of clinic visit. Studies have shown inadequate screening of
youth for diabetes or diabetes risk factors (O’Brien et al., 2004; Weatherspoon et al.,

2001).

This study is a multi-clinic study and included adult and pediatric endocrinology clinics
throughout the lower peninsula of Michigan. Hence, the population of these clinics is
representative of the population of the lower peninsula of Michigan. Therefore a good
estimate of the proportion of children and adolescents in Michigan, who may have T2DM
is provided. The data indicates that the estimated prevalence of T2DM among

adolescents aged 6-19 years in the lower peninsula of Michigan is 1 1.3/ 100, 000.

89

Michigan Department of Community Health estimates that based on Blue Cross Blue
Shield (BCBS) information, 0.32% children under the age of 18 years with all types of
diabetes. However, we do need to take into consideration the fact that the data from Blue
Cross Blue Shield might not be representative of all the youth in Michigan as there are
many subjects who might not be covered by BCBS insurance, and there might also be a
higher proportion of undiagnosed cases of T2DM in Michigan similar to the prevalence

of undiagnosed trends noticed in adults.

Results from previous studies reported that T2DM accounts for 2 to 3% of all patients
with diabetes mellitus aged 0 to 19 in the United States (Dabelea et al., 1998), but the
prevalence is higher among children in populations with a relatively high prevalence of
T2DM in adults as one would expect (Glasser, 1997). In our study, there was a higher
prevalence among African Americans. Based on both the adult literature and clinic based
studies in youth with Afi'ican American patients, T2DM is clearly a noteworthy problem
in this ethnic group. However, it should be noted that the proportion of Caucasian cases
was also high suggesting that risk factors other than ethnicity may be even stronger

predictors of the disease.

Results from a study conducted in Cincinnati showed that the proportion of children (10-
19 yr) with T2DM increased from 4% in 1982-1991 to 16% in 1994 (Pinhas-Hamiel,
1996). In Tokyo, the incidence rates of T2DM in school children between 1975 and

1990 increased 1.5 fold, along with a similar increase in the prevalence of obesity

90

(Kitagawa et al., 1994). However, in our study we were not able to compare the increase

over a period of time as this was a cross sectional study.

In our clinic the mean age at diagnosis for T2DM was 13.0 i 2.8 years, which is very
similar to data from Pinhas-Hamiel et. al. (1996). Females on average were diagnosed at
least 6 months earlier than males; this was especially evident for African American
females who were diagnosed 1 year earlier than females from other ethnicities and males
on average. Among the males, Hispanic males were diagnosed at a much later age
compared to males from other ethnicities (14.57 years). The earlier onset of diabetes in
females may be attributed to onset of puberty. In females puberty starts on an average of
1 year earlier compared to males and more female subjects (54%) were pubertal when
diagnosed with T2DM. Relative insulin resistance that is characteristic of puberty may
be playing a role in this early appearance of T2DM in these adolescents. It has been
shown that between tanner stages II and IV there is 30% lower insulin-mediated glucose
disposal compared with prepubertal children in Tanner stage I and compared with young
adults (Arslanian, 2000). Since puberty is characterized by relative insulin resistance, it
may be an aggravating factor in the appearance of overt T2DM in obese adolescents.
This study also demonstrated higher levels of insulin and C-peptide in this sample, thus
emphasizing that the B-cell’s are still functioning and that insulin resistance may be an

important factor to take into consideration in this sample.

In adults, obesity has been strongly associated with T2DM. In our study population, a

similar association was noticed. For the past few years Michigan has been ranked among

91

the top 3 states with the highest obesity rates. Moreover, results from other studies
describing T2DM in youth have also demonstrated a strong association with obesity
(Pinhas-Hamiel, 1996; Glaser, 1997 ; Neufeld et al., 1998). A key physiological
implication of obesity and probable link to T2DM is the adverse effects on glucose
metabolism. For example, 55 % of the variance in insulin sensitivity among healthy
white children (i.e. without diabetic) is accounted for by total adiposity (Bogardus et al.,
1985). The amount of visceral fat in obese adolescents was directly correlated with
hyperinsulinemia and inversely related with insulin sensitivity (Tamura et al., 2000).

Therefore, it is not surprising that the T2DM-obesity association is so strong.

Data regarding family history, demonstrated that 84% had family members with diabetes.
These results of family history are in line with those published in the reported literature
(Pinhas-Hamid, 1996; Glaser, 1997; Neufeld et al., 1998). Therefore, the importance of
family history as a notable risk factor cannot be over emphasized. Practitioners
unfortunately do not always note family history of diseases such as diabetes in
children/youth (Weatherspoon, 2004). Since the onset of T2DM can be asymptomatic for
prolonged periods of time, and the age of onset also varies, the prevalence of T2DM
among family members can be much higher than reported (Glaser & Jones, 1998). On
the other hand, studies with children with Type 1 diabetes have demonstrated that only 8
to 16% have a family history of Type 1 diabetes and about 1-25% have a family history

of T2DM (Levy-Marchal et al., 1992; Pociot et al., 1993; Quataro et al., 1990).

92

An additional factor, not previously reported, was family composition. The majority of
the youth with T2DM were living in single parent families. Also, in the state of
Michigan, all children are covered by children’s special health insurance and hence lack
of medical support/access to medical services might not be a significant contributor.
Therefore, these findings demonstrated that besides genes, and/or medical/physiological

factors, social factors also play a huge role in the development/control of T2DM.

Even during the short period of follow up (mean disease duration 3.0 i 2.3), with these
patients some serious metabolic aberrations like hyperglycemia (HbAlc >7%),
hypertension, increased triglycerides, low HDL-C were already present in the majority of
these youth. If aberrations persist, these youth will likely incur severe complications at
an early age (N eufeld, 1998). Poor compliance with recommended treatment is a well
known problem among youth with Type 1 diabetes (Weissberg-Benchell et al., 1995),
and this problem is likely to be more pronounced among youth with T2DM as non-
compliance will not be likely to produce immediate symptoms (Neufeld et al., 1998).
Dean et al. (1992) stated that if poor compliance persists into adulthood, these children
with T2DM will be at a higher risk of developing macrovascular and microvascular
complications of diabetes with an impaired quality of life at a relatively young age

compared to adults who are diagnosed with the disease (Dean et al., 1992).

In conclusion, our study demonstrates that T2DM in youth in the state of Michigan is

occurring at rates similar to the published literature from other states in the US. This is

the first multi-clinic study with a representative sample of diagnosed cases with diabetes

93

in the lower peninsula of Michigan. Since no statewide data or estimates exist, this study
provides some useful baseline information about diagnosed T2DM in youth aged 6—19 yr
for Michigan. It is expected that similar to adults, there might be a large proportion of
undiagnosed cases of T2DM in youth across the nation given the obesity epidemic. In .
this sample the strong associative factors were: obesity/overweight, pubertal stage, and a
positive family history of diabetes. This study supports and strengthens the results
published by previous studies that there is a strong association between the development
of T2DM and obesity. In addition, the fact that social factors such as the challenge of
single parenting might be playing a pivotal role in disease manifestation and
management, was an interesting finding previously not reported. Hence, a second phase
of this study was designed to study the influence of social factors in management of
T2DM in this vulnerable age group. As demonstrated among adults, T2DM and it’s
complications accounts for the majority of the health costs. The early onset of this
disease will therefore have long-term public health consequences, both emotionally and
economically. Results from this study and previous studies on T2DM among children
and adolescents offer health care providers with sufficient justification to ensure that
subjects at high risk because of obesity and/or positive family history of diabetes or other
risk factors are adequately screened. A recent publication from Chicago (Drobac et al.,
2004), demonstrated that at a busy urban clinic the diabetes screening protocol proposed
by the American Diabetes Association (ADA, 2000) for youth was inconsistently being
used. Only presence of acanthosis nigricans and higher rate of documentation of
nutritional counseling were a driving factor for screening (Drobac et al., 2004). Hence,

implementing proper use of screening protocols and screening youth at high-risk of

94

developing T2DM at a younger age is essential in order to delay/prevent the deve10pment
of diabetes and diabetes related complication. Once diagnosed, careful monitoring and
diligent patient compliance with treatment protocols are essential for disease management

and a potentially longer healthier life.

95

REFERENCES

American Diabetes Association (ADA) consensus Statement: Type 2 diabetes in children
and adolescents. Diabetes Care 2000; 22(12): 381-389.

Arslanian SA. Type 2 diabetes mellitus in children: Pathophysiology and risk factors.
Journal of Pediatric Endocrinology Metabolism 2000; 13(Suppl. 6): 1358-1394.

Bogardus C, Lillioja S, Mott DM, Hollenbeck C, and Reaven G. Relationship between
degree of obesity and in vivo insulin action in man. American Journal of
Physiology 1985; 248: E286-E291.

Campaign BN, Morrison J A, Schumann BC, et al. Indexes of obesity and comparisons
with previous national survey data in 9 and 10-year old black and white girls: The
National Heart, Lung, and Blood Institute Growth and Health Study. Journal of
Pediatrics 1994; 124: 675-680.

CDC 2002. National Diabetes Fact Sheet. http://www.cdc.gov/diabetes/pubs/general.htrn

Cook S, Weitzman M, Auinger P, Nguyen M, and Dietz W. Prevalence of 3 Metabolic
Syndrome Phenotype in Adolescents. Archives of Pediatric Adolescent Medicine
2003; 157: 821-827.

Dabelea D, Hanson RL, Bennett PH, Roumain J, Knowler WC, and Pettitt DJ. Increasing
prevalence of Type 2 diabetes in American Indian children. Diabetologia 1998;
41: 904-910.

Dean H. NIDDM-Y in First Nation children in Canada. Clinical Pediatrics 1998; 39: 89-
96.

Dean HE, Mundy RLL, and Moffatt M. Non-insulin-dependent diabetes mellitus in
Indian children in Manitoba. Canadian Medical Association Journal 1992; 147 :
52-57.

Drobac S, Brickman W, Smith T, and Binns H. Evaluation of a Type 2 diabetes
screening protocol in an Urban Pediatric Clinic. Pediatrics 2004; 114: 141-148.

Fagot-Campagna A, Saaddine JB, Flegal KM, and Beckles GL. Diabetes, impaired
fasting glucose, and elevated HbAlc in US. adolescents: the Third National
Health and Nutrition Examination Survey. Diabetes Care 2001; 24(5): 834-7.

F legal KM, Ogden CL, Wei R, Kuczmarski RJ, Campbell SM, and Johnson CL.

Prevalence of overweight in US children: Comparison of US growth charts from
the Centers for Disease control and Prevention with other reference values for

96

body mass index. American Journal of Clinical Nutrition 2001; 73(6): 1086-
1093.

Ford ES, Williamson DF, and Liu S. Weight change and diabetes incidence: Findings
from a national cohort of US adults. American Journal of Epidemiology 1997;
146: 214-222.

Gauthier BM, Hickner JM, and Noel MM. High prevalence of overweight children in
Michigan primary care practices: An UPRNet study. Upper Peninsula Research
Network. Journal of Family Practice 2000, 49(1): 73-76.

Glaser NS, Jones KL. Non-insulin-dependent diabetes mellitus in Mexican-American
children. The Western Journal of Medicine 1998; 168(1): 1 1-19.

Glaser NS. Non-insulin-dependent diabetes mellitus in childhood and adolescence.
Pediatric Clinics North America 1997; 44(2): 307-37.

Gortrnaker SL, Dietz WH, Sobol AM, and Weber CA. Increasing pediatric obesity in the
United States. Arch Pediatric Adolescent Medicine 1987; 141: 535-40.

Harris SB, Perkins BA, and Whalen-Brough E. Non Insulin Dependent diabetes mellitus
among First Nations Children. New entity among First Nations people of north
western Ontario. Canadian Family Physician 1996; 42: 869-876

Kitagawa T, Owada M, Urakarni T, and Tajima N. Epidemiology of Type 1 (insulin-
dependent) and Type 2(non-insulin-dependent) diabetes mellitus in Japanese
children. Diabetes Research and Clinical Practice 1994; 24(suppl.): S7-S13.

Knowles HC Jr. Diabetes mellitus in childhood and adolescence. Medical Clinical North
America 1971; 55: 975-987.

Levy-Marchal C, Papoz L, De Beaufort C, Doutreix J, Froment V, Voirin J, Czemichow
P. Clinical and laboratory features of Type 1 diabetic children at the time of
diagnosis. Diabetics Medicine 1992; 9: 279-284.

Macaluso CJ, Bauer UE, Deeb LC, Malone JL, Chaudhari M, SilversteinJ, Eidson M,
Goldberg RB, Gaughan-Bailey, Bonnie, Brooks, Robert, Rosenbloom AL. Type 2
diabetes mellitus among Florida children and adolescents, 1994 through 1998.
Public Health Reports 2002; 117: 373-379.

Mokdad AH, Bowman BA, Ford ES, Vinicor F, Marks J S, and Koplan JP. The

continuing epidemics of obesity and diabetes in the United States. Journal of
American Medical Association 2001; Sep 12; 286(10): 1195-200.

97

Mokdad AH, Ford ES, Bowman BA, Nelson DE, Engelgau MM, Vinicor F, and Marks
J S. Diabetes Trends in the US: 1990-1998. Diabetes Care 2000; 23(9): 1278-
1283.

National Center for Health Statistics. Plan and operation of the Third National Health
and Nutrition Examination Survey, 1988-94. Series 1: Programs and collection
procedures. Vital Health Statistics 1994; 32: 1-407.

Neufeld ND, Raffel L, and Landon C. Early presentation of Type 2 diabetes in Mexican-
American youth. Diabetes Care 1998; 21(1): 80-86.

Norusis MJ (2002). SPSS 11.0 Guide to Data Analysis. NJ: Prentice Hall, Inc.

O’Brien SH, Holubkov R, and Cohen RE. Identification, Evaluation, and Management
of obesity in an academic primary care center. Pediatrics 2004. 114(2): 154-159.

Pihoker C, Scott CR, Lensing SY, Cradock MM, and Smith J. Non-insulin dependent
diabetes mellitus in African American youths of Arkansas. Clinical Pediatrics
1998; 37: 97-102.

Pinhas-Hamiel OM, Dolan LM, Daniels SR, Standiford D, Khoury PR, and Zeitler P.
Increased incidence of non-insulin dependent diabetes mellitus among
adolescents. The Journal of Pediatrics 1996; 128(5): 608-615.

Pociot F, Norgaard K, Hobolth N, Anderson 0, Nerup J, and the Danish Study Group of
Diabetes in Childhood. A nationwide population-based study of the familial
aggregation of Type 1 diabetes mellitus Denmark. Diabetologia 1993; 36: 870-
875.

Quataroa A, Consoli G, Magno M, Caretta F, Ceriello A, and Giugliano D. Analysis of
diabetic family connection in subjects with insulin-dependent diabetes mellitus.
Diabetics Metabolism 1990; 16: 449-452.

Salvage PJ, Bennett PH, Senter RG, and Miller M. High prevalence of diabetes in young
Pima Indians. Diabetes 1979; 28: 937-942.

Tamura A, Mori T, Hara Y, and Komiyama A. Preperitoneal fat thickness in childhood
obesity: association with serum insulin concentration. Pediatric International
2000; 42(2): 155-159.

Weatherspoon LJ., Handu D., Jocks J ., Hollen D., and Carolan M. Screening for risk
factors of diabetes among youth at primary care clinics. 2004; Still in publication.

Webber LS, Harsha DW, Nickles TA, and Berenson GS. Secular trends in obesity in
children. In: Filer LJ, Iuaer RM, Lurpker RV, editors. Prevention of

98

atherosceloris and hypertension beginning in youth. Philadelphia: Lea and
Febiger; 1994; 194-203.

Weissberg-Benchell J, Glasgow AM, Tynan WD, Wirtz P, Turek J, and Ward J:

Adolescent diabetes management and mismanagement. Diabetes Care 1995; 18:
77-82.

99

Table 1: Proportion of diagnosed Type 2 diabetes mellitus cases among youth diagnosed
with and treated for diabetes (6-19 yrs.).

 

 

 

 

 

 

 

 

 

 

Sites 6-19 yr 10-19 yr
%(T2DM/T2DM +T1DM) %(TZDMITZDM +T1DM)

Clinic 1 8 % (55/700) 10.5%(54/530)
Clinic 2 21% (27/ 130) 28% (27/97)
Clinic 3 6.5%(7/107) 8.5%(7/82)
Clinic4 8% (1/13) 8% (1/13)
Clinic 5 20% (82/411) 24% (82/340)
Clinic 6 14.7% (1 1/75) 17.5% (10/57)
Clinic 7 5.4% (23/435) 6.5% (23/334)
Clinic 8 10% (14/140) 11.8% (1 1/93)
Total ' 11% (220/2018) 14% (214/1556)

 

 

 

 

 

100

Table 2: Characteristics of patients with Type 2 diabetes mellitus.

 

 

 

 

 

Gender Race No. (%) Age at BMI (kg/m2) BMI percentile
diagnosis Mean i SD 2 85th %tile
(yrs) % (n/N)
All Afri American 111 (57) 12.7 :L- 3.0 35.5 i 14.9 47% (101/111)
White 33 (17) 12.6 i 2.3 33.0 i 7.1 14% (31/33)
HiSPanic 25 (14) 14.0 i 2.7 36.4 i 11.0 11% (24/24)
Others 45 (12) 12.89 i 2.8 34 i 8.8 19% (42/45)
A“ 214 13.0i2.8 35.0:125 90%(191/213)
Female Afri. American 70 12.3 i 3.1 36.0 i 17.0 54.2 % (65/69)
White 16 13.3 :r. 1.8 35.0 i 6.6 12.5% (15/16)
Hispanic 11 13.5 i- 2.1 34.7 : 14.7 83%(10/10)
Others 25 13.3 i 2.8 34.3 i 8.7 19.2% (23/25)
A“ 122 12.7 r. 2.8 35.4 i 14.2 943% (113/120)
Male Afii. American 42 13.26 i 2.8 b 34.7 i 10.6 38.7% (36/42)
White 17 12.14 i 2.3 b 30.6 i 7.8 17.3 % (16/17)
HiSPanic 14 14.57 i 3.1a 37.8 1r 8.1 140% (14/14)
Other 20 11.00 i 3.0 30.2 i 7.0 204% (19/20)
A“ 93 13.04 i 2.8 34.2 i 9.5 915% (85/93)

 

 

 

 

 

 

*p<0.05; within a column with different superscripts are significantly different at p<0.05

101

 

Table 3: Presence of Type 2 diabetes associated risk factors among diagnosed cases of

Type 2 diabetes youth by ethnicity and gender.

 

 

 

 

Gender Race Positive Presence of Living
Family Acanthosis Status(single
History of DM Nigricans parent)
(%) (%) (%)
All Afri. Amer. 56 a 55 57 a
White 14b 13 16b
Hispanic 10 b 14 8 b
Others 20 b l 8 19 b
Female Afri. Amer. 58 60 60 a
White 14 12 17 b
Hispanic 8 13 7 b
Others 20 15 16b
Male Afri. Amer. 53 48 54 a
White 15 14 14 b
Hispanic 13 16 9b
Other 19 23 23 b

 

 

 

 

 

 

 

*p<0.01; within a column with different superscripts are significantly different at
p<0.05

102

Table 4: Presence of clinical parameters among youth with Type 2 diabetes.

 

 

 

 

 

 

 

 

 

 

 

Type 2 DM cases
Hemoglobin Alc: mean iS.D. 8.76 i 2.9
(n=200) < 7 36%
Z 7 64%
C-peptide (ng/L): mean iS.D. 4.1 i 3.0
(n=66)
Insulin (aIu/L): mean iS.D. 38 i 28
(11:44)
Blood Pressure (mmHg): Systolic: mean i SD. 127 i 15
< 90th percentile 15%
2 90‘h percentile 85%
Triglyceride (mg/d1): mean i SD. 167: 195
(n=69) < 150 67%
2 150 33%
Total Cholesterol (mg/d1): mean i SD. 179 i 44
(n=130) < 170 47
2 170 53
I-IDL-C (mg/d1): mean i SD. 43 i 12
(n=68) < 40 (low) 49%
_>_ 40 51%
LDL-C (mg/d1): mean i SD. 106 i 43
(n=64) < 110 61%
2 110 39%

 

 

103

Figure 1: BMI percentile distribution of youth
with Type 2 diabetes

80-

60“

% of youth
8

   

   

, t
1 ,

Type 2 DM BMI percentiles

 

P<0.0001

El 5th-85th %tile I =>85th %tile I =>95th Vdile

104

CHAPTER 5

Comparison of glycemic control and associated factors in youth (6-19 yr) with

Type 2 or Type 1 diabetes in Michigan

Abstract

Background: Type 2 diabetes (T2DM) in youth has increased dramatically over the past
few years. Historically diabetes mellitus occurring in children was primarily Type 1
diabetes (TlDM) however, recently more cases of T2DM have been diagnosed. This
increase in youth with T2DM has been associated with the increasing rates of obesity in
this age group. The challenges of management issues in youth with TlDM, which have
been extensively studied are important references to better understand the potential
severity of this new and growing disease.

Objective: To compare the characteristics of youth (6-19 yr) with T2DM and TlDM
cases matched for age and sex.

Methods: Retrospective in-depth chart reviews of youth diagnosed with Type 2 or Type
1 diabetes were conducted to assess glycemic control and associated factors. Youth with
T2DM were compared to youth with TlDM matched for age and gender to determine if
glycemic control and associative factors of diabetes (example: lab values,
anthropometrics, socio-demographic, and self-care management behaviors) differed by
the type of diabetes in this age group.

Results: Of a total of 201 8 youth, 6-19 yr diagnosed with diabetes at endocrinology

clinics in Michigan, 220 (11%) had T2DM, whereas 14% of 10-19 year old youth had

105

T2DM. The mean age for T2DM onset was significantly higher than TlDM cases (13 yr
vs 8.7 yr) and the majority was at Tanner stage 3 or higher (83% vs 27%). Ethnic
distribution of the sample indicated that more African Americans (52% vs 22%) and
Hispanics (12% vs 1%) compared to Caucasians were diagnosed with T2DM. Based on
body mass index (BMI) percentiles, 7 8% of youth with T2DM were >95th %tile
(overweight), but for youth with TlDM, 81% were between the 5m-85th %tile (normal).
Youth with T2DM had: lower HDL-C (48%), elevated serum triglyceride (33%),
hypertension (85%), and elevated HbAlc (62%). Self-care behavior data indicated that
the majority of the youth with T2DM were not following their diet (80% vs 42%) or
exercise (64% vs 38%) recommendations compared to youth with TlDM

Conclusions: The results of this multi-clinic study show that poor glycemic control was
common among youth with either TlDM or T2DM. However, other metabolic risk
factors (low HDL-C, high TG, hypertension) were higher in youth with T2DM. Poorer
compliance of self-care behaviors for diabetes management was also more prevalent in
youth with T2DM. It is important therefore that health practitioners address these risk
factors and target self-care behaviors via both screening and intervention strategies

because of the potential long-term ramifications.

106

Introduction

There has been a dramatic rise in the incidence of Type 2 diabetes (T2DM) in youth over
the past few years. In 10-19 year old Afiican American and White children referred to a
major pediatric center in Cincinnati, Ohio, the incidence of diagnosed T2DM increased
lO-fold, from 0.7/100,000 in 1982 to 7.2/100,000 in 1994 (Pinhas-Hamiel et al., 1996).
Data from the Indian Health Service (1988 to 1996), also documented a 54% increase in
prevalence of reported diabetes in 15-19 year old adolescents (Fagot-Campagna et al.,
2002). Case studies in California, South Carolina and a few other states have shown
increasing percentages of incident pediatric cases of diagnosed diabetes, with fewer than
4% reported before 19905 and up to 45% in recent studies (Pinhas-Hamiel et al., 1996;
Willi et al., 1997; Fagot-Campagna et al., 2002). Traditionally, T2DM was known as an
adult disease, and was strongly associated with obesity, positive family history and
sedentary lifestyle (Rewers & Hamman, 1995; Simmons et al., 1995). However, the
predominant form of diabetes in youth was Type 1 diabetes (TlDM). While TlDM is
still the predominant form of the disease in youth, the recent rise in T2DM cases has lead

to the Surgeon General proclaiming it to be an epidemic in 1998.

T2DM among adults has been extensively studied. Among adults, numerous studies
document a significant positive correlation between the prevalence of T2DM and relative
weight for height (Mokdad et al., 2000 & 2001). Researchers have demonstrated an
association between obesity, insulin resistance, and a progressive transition from glucose
intolerance to being diagnosed with diabetes (Kenny et al., 1995; Scott et al., 1997;

Rewers & Hamman, 1995; Sega] et al., 1996). The typical age of onset for T2DM is

107

over 45 years. However, within the last decade, the age of onset of T2DM has decreased.
T2DM has been reported in children and adolescents worldwide, with a greater
proportion of children of color affected. More recently, several clinical reports have
published data of increasing incidences of T2DM among African American children in
Cincinnati and Arkansas (Pinhas-Hamiel et al., 1996; Pihoker et al., 1998); first nation
(American Indian) children in Manitoba (Dean et al., 1988; Dean H, 1992); American
Indian in Ontario (Hanis et al., 1996); Hispanic children in California (Fagot-Campagna
et al., 2001); and Japanese children in Tokyo (Kitagawa et al., 1994 & 1998). The
incidence rates reported in these studies ranges from 8 to 45%. In Tokyo, for example
the annual incidence of T2DM among junior high school children, increased from 7.3 per
100,000 in 1976-1980 to 12.1/100,000 in 1981-1985, and to l3.9/100,000 in 1991-1995

(Kitagawa et al., 1998 & 1994).

The ideal goal for treatment is normalization of blood glucose values and glycosylated
hemoglobin (GHB) (American Diabetes Association, 2000). The ultimate goal of
treatment is to decrease the risk of the acute and chronic complications associated with
diabetes. There is strong evidence from the UK Prospective Diabetes study (UKPDS)
that the normalization of blood glucose substantially reduces the frequency of
microvascular complications (such as retinopathy) of T2DM in adults (UKPDS Group,
1998). Similarly, the Diabetes Complications and Control Trial (DCCT) showed that in
the case of TlDM, normalization of blood glucose reduced the risk of retinopathy,
nephropathy, and neuropathy substantially (DCCT, 1993). The early age of onset of

T2DM in children may particularly increase the risk of microalbuminuria and

108

nephropathy, which are known to be directly related associated with duration of diabetes
and hyperglycemia (ADA, 2000). Prevalence of metabolic syndrome (MS) (having at
least 3 of the following: abnormal glucose, low HDL-C, elevated serum triglyceride,
abnormal waist circumference, and high blood pressure) among youth aged 12-19 years
was 4.2% (Cook et al., 2003). The authors suggest that a substantial percentage of
overweight youth may be inflicted with the MS. Hence, the goals for clinical
management of T2DM in children and adolescents should include therapies directed at
treating the underlying pathologies of diabetes, effects of chronic hyperglycemia, other
metabolic risk factors and the prevention of long-term complications. Prevention and
treatment of associated co-morbidities such as hypertension, hyperlipidemia, and obesity
are important, but the ultimate goal is to maintain blood glucose levels and reduce the
risk of end-organ damage from diabetes, which is directly related to the duration of
diabetes and level of hyperglycerrria. Similar to T2DM mellitus in adults, the first lines
of therapy in children with T2DM are diet, exercise and weight loss or maintenance,
because these therapies are directed at the underlying pathology, insulin resistance, which

is a primary associative feature of T2DM.

The main objective of this study was to assess distinguishing characteristics of youth
(age, gender, ethnicity, puberty, weight, height,) with Type 2 versus TlDM in Michigan
to determine if differentiation is clear at this vulnerable age. We were specifically also
interested in determining if diabetes/glycemic control and associated factors (self-care
management and monitoring behaviors, and other metabolic behaviors) differed by type

of diabetes in this age group.

109

Research methods

A retrospective chart review of youth (6-19 yr) previously diagnosed with Type 2 or
TlDM was undertaken at pediatric and adult endocrinology clinics in Michigan to
determine if independent variables were associated with glycenric control in children
based on type of diabetes. Youth diagnosed with T2DM were matched for age and
gender with children with TlDM for comparison purposes. If there were more than one
TlDM subject with an age similar to a T2DM subject, random matching was conducted.
Approval from Michigan State University Committee on Research Involving Human
Subjects (UCRIHS), the clinic directors and the Review Boards of the individual clinics
was obtained before data collection was commenced.

Sites: Data was collected at eight pediatric and endocrinology clinics in the state of
Michigan. The eight eligible clinics were distributed over the state of Michigan: west
central Michigan (Lansing-Sparrow Hospital, Grand Rapids- Saint Mary’s Mercy
Medical Center and DeVos Children’s Hospital); southeast Michigan (Detroit- Children’s
Hospital of Michigan and Ann Arbor- University of Michigan Medical Center); east
central Michigan (Saginaw- Covenant Hospital and Flint- Hurley Medical Center) and
south central Michigan (J ackson-F oote Hospital).

Target Population: Subjects were youth aged 6 to 19 yr, medically diagnosed with
either Type 1 or T2DM. Previous studies have shown 10-19 years as the probable age
range for T2DM cases in children and adolescents, but based on personal communication
with local physicians, T2DM cases have been reported in children as young as 6 years
old. Hence, in order not to exclude these cases, the selected age range for this study was

determined as 6-19 years of age. The population base for this study included all children

110

and adolescents with a medical diagnosis of diabetes (Type 1 or 2) who had attended the
clinic for at least six months prior to the commencement date for the study. Exclusion
criteria were children 6-19 years old who have: 1) Physician noted maturity-onset
diabetes of the young (MODY); 2) Type 2 diabetes associated with steroid use; 3) Type 2
diabetes associated with cystic fibrosis; and 4) Children with pre-diabetes (whose blood
glucose levels are higher than normal, but not yet high enough to be diagnosed as
diabetes). These cases were excluded to obtain “true cases” of T2DM as defined by the
American Diabetes Association (ADA, 2000). ADA defines T2DM in youth as: Classic
symptoms of diabetes (polyuria, polydipsia, & unexplained weight loss) and casual
glucose 2200 mg/dl (11.1 mmol/l) 0R Fasting plasma glucose 2126 mg/dl (7.0 mmol/l)

0R 2-hour plasma glucose 2 200 mg/dl (11.1 mmol/l) during an Oral Glucose Tolerance

Test (OGTT).

Estimating the proportion of diagnosed T2DM among youth 6-19 yr with diabetes
(TlDM or T2DM) in the state of Michigan was conducted by Handu et al., 2004 (Chapter
4). After confirming the proportion of T2DM cases to be higher than usually expected,
similar to other nationally reported rates, it was important to compare and contrast T2DM
and TlDM in this vulnerable age group. The purpose of the medical record review was
to firstly estimate the prevalence of glycemic control in these populations because of the
importance of good glycemic control on later quality of life. Secondly, it was important
to identify associative risk and control factors to determine if the challenges faced by

T2DM were different, and to inform health care professionals who diagnose or counsel

lll

T2DM youth on associated family and health care behaviors which might be different

between these two groups of youth.

The medical records of youth with T2DM and matched cases with TlDM were reviewed
for diabetes diagnosis, glycemic control and associated factors, and self-care behaviors
(home blood glucose monitoring, following recommendations of exercise and diet). The
presence of the following metabolic risk factors (metabolic syndrome cut points) was also
compared: elevated serum glucose, blood pressure 2 90h percentile for height, elevated
serum triglycerides 2 110 mg/dL, and low serum High Density Lipoprotein- Cholesterol
(HDL-C) s 40 mg/dL (Cook etal., 2003). Metabolic syndrome is defined as having at
least three of the before mentioned metabolic risk factors and has been reported to be
potentially associated with serious ramifications such as cardiovascular disease if present.
Typically in adults, cardiovascular disease is a leading cause of death among individuals
with T2DM (Cook et al., 2003). Diabetes mellitus is often accompanied with metabolic
aberrations; therefore it was critical to determine if these aberrations were present in
youth with T2DM. To abstract the information described above a data collection form
was used (Appendix B). Content validity of the data collection form was established by
asking 6 diabetes professionals (2 pediatric endocrinologists, l nurse, 2 registered
dietitian’s with doctorate degree and 1 dietitian who has experience working with
diabetes youth) to review the data collection protocol sheet. Responses from reviewers
were obtained and the changes requested included: organization of questions, re-phrasing

questions to simplify, and deletion of perceived irrelevant questions. Four trained people

112

conducted data abstraction at all centers to maintain consistency and confidentiality of

records.

Body mass index GBMI) and BMI percentiles for each subject was calculated by using
Epi-Info sofiware (Dean etal., 2002). Epi- Info also provided BMI and height
percentiles specific for age and sex. Height percentiles were used for calculating blood
pressure percentiles. Blood pressure percentiles were calculated based on tables
developed by the National Heart and Lung Blood Institute (NHLBI, 2004). These tables
are standardized for age and sex. Tanner stage data was noted as reported in the medical
charts. Tanner stage at diagnosis of diabetes and current tanner stage were also noted as
the literature indicates that during puberty, insulin sensitivity is. reduced and hence, it was

critical to know at what stage of puberty are youth diagnosed with diabetes.

Statistical Analysis: Data were analyzed using SPSS version 11.0 (Norusis, 2002).
Means i standard deviation and frequency distribution were calculated to describe the
sample. Bivariate analysis (chi-square analysis) was conducted to determine if
differences existed by gender and ethnicity for selected medical history, and biochemical
and clinical variables. Logistic regression models were generated to determine the odds
ratios (OR) for risk of T2DM compared to TlDM, risk of having low HDL-C, and risk of
having high triglyceride among 6-19 year old youth when controlling for gender,
ethnicity, type of diabetes, and BMI percentiles. A p-value of <0.05 was considered

statistically significant.

113

Results

Of a total of 2018 children (6-19 yr) with diagnosed diabetes (Type 1 or Type 2) at eight
endocrinology clinics in the state of Michigan, 220 (11%) had T2DM. Among subjects
10 to 19 years of age, T2DM accounted for 14% of the diagnosed cases of diabetes (Type
1 or Type 2). The gender and age distribution between the two types of diabetes was
similar because of the age and gender matching. Table 1 depicts the demographic and
age of onset comparisons. T2DM was diagnosed at a significantly higher age compared
to TlDM in youth (p<0.001). Compared to TlDM cases, significantly more African
Americans and Hispanics were diagnosed with T2DM (p<0.001). In addition, 65% of
T2DM subjects were living in single parent households compared to only 40% of
subjects with TlDM (p<0.001). Data regarding income estimates demonstrated that 41%
of T2DM subjects Were supported by government assistance insurance. For TlDM cases

this was true for only 37% of TlDM subjects.

Data regarding BMI indicated that youth with T2DM had significantly higher mean BMI
compared to youth diagnosed with TlDM (34.9 d: 12.4 vs 21.6 i 5.6, p<0.001).
Classification of subjects by BMI percentile showed that the majority of youth with
diagnosed T2DM were 2 95th percentile, whereas the majority of youth diagnosed with

TlDM had a BMI %tile between the 5th and 85th percentiles (Figure 1).
Data analysis of the other variables indicated that more of subjects with T2DM had a

positive family history of diabetes compared to TlDM subjects (85% vs 61%).

Acanthosis nigricans was present in 73% of those with T2DM compared to 6% in those

114

with TlDM (p<0.001). When pubertal status was examined, the majority of the youth
with T2DM were in Tanner stage 3 or higher at the time of diagnosis (83% vs 28%,

p<0.001) (Table 2).

Biochemical parameters measured most frequently in both groups included HbAlc and
lipid profile (Table 3). HbAlc was higher among youth with T2DM compared to TlDM,
but these results were not statistically significant. For both groups however, the mean
HbAlc was higher (>7%) than the target set by ADA for Optimum control. Mean
triglyceride (TG) values were significantly higher among T2DM subjects compared to
those with TlDM. Mean HDL-C was significantly lower among the subjects with
T2DM. When data were analyzed according to normal cut off points for each of these
parameters, T2DM subjects were more likely to have serum TG 2 150mg/dl (p<0.01),
HDL-C S 40 mg/dl (p<0.01), and TC 2 110 mg/dl than those with TlDM. Data were
also analyzed by using the metabolic syndrome cut off points (serum TG _>. 110mg /d1;
blood pressure %tile 2 90th %tile; and HDL-C s 40 mg/dl). Compared to subjects with
TlDM, T2DM subjects had higher serum TG, lower serum HDL-C, and higher blood
pressure (p<0.05). Based on the criteria for metabolic syndrome classification (Cook et
al., 2003), 57% of T2DM subjects compared to only 28% of TlDM subjects qualified as
having metabolic syndrome (p<0.001). Eighty six percent of T2DM youth had at least 2
metabolic syndrome risk factors and 59% had at least 3 metabolic syndrome risk factors.
Information regarding subject compliance with dietary and exercise recommendations,
and self-monitoring of blood glucose at home as recommended showed that a significant

percentage of T2DM subjects were not following their dietary and exercise

115

recommendations compared to subjects with TlDM (Table 4). Twenty two percent of
subjects with T2DM compared to only 6% of subjects with TlDM were not checking

their blood sugars at least 2 times per day (p<0.001).

The significant variables in the bivariate associations were tested in a logistic regression
model to assess the effect of the independent variables on risk of T2DM, risk of high
HDL-C, and risk of high TG, while controlling for each of the independent variables in
the model. Model 1 (Table 5) predicted the likelihood of Type of diabetes (Type 2 vs
Type 1) relative to gender, race, and body mass index. Odds ratios (OR’s) and 95%
confidence intervals (CI) for each of these variables are shown in Table 5. The odds of
being diagnosed with T2DM relative to TlDM was 75.0 times greater for those with a
BMI _>_ 95th percentile, compared to those with a BMI <85th percentile. Subjects with a
BMI 2 85th percentile were 3.4 times more likely to develop T2DM compared to TlDM
(p<0.001). Hispanic and Afiican American youth were 31.9 and 6.9 times respectively
more likely than Caucasian youth to be diagnosed with T2DM when gender and BMI

were controlled for or held constant (p<0.001).

Model 2 predicted the odds of serum TG 2 150 mg/dl when controlling for gender, age,
BMI percentile, and Type of diabetes (Type 1 or Type 2). The odds of serum TG 2 150
mg/dl was 2.8 times greater for those with a BMI 2 95th %tile compared to those with a
BMI <85th %tile. Subjects with T2DM had significantly higher odds of having serum TG
_>_ 150 mg/d when compared to TlDM subjects (OR= 4.0, CI: 1 1.1-17.0, p<0.05) (Table

5).

116

Model 3 determined the odds of HDL-C S 40 mg/dl while controlling for gender, age,
BMI percentile, and type of diabetes (Type 1 or Type 2). The odds of HDL-C S 40 mg/dl
was 4.1 times greater for subjects with BMI 2 95th percentile compared to those with

BMI <85th percentile, and 7.8 times greater for subjects with T2DM compared to those

with TlDM. (Table 5)

117

Discussion

This study was unique in showing that the majority of youth with T2DM were living with
single parent families compared to youth with TlDM. Further analysis showed that this
was especially true for African Americans. In fact in this ethnic group, regardless of
whether they had Type 1 or T2DM, the majority were fiom single family parents. In
addition, insurance data indicated that more of youth with T2DM were using government
assisted insurance support compared to youth with TlDM. Therefore social factors are

key factors for consideration in this population.

Key distinguishing features of T2DM among children and adolescents as presented by
this and other studies are obesity, acanthosis nigricans, and positive family history of
diabetes (Pinhas-Hamiel etal., 1996; Pihoker et al., 1998; Dean 1998). Abnormal lipid
profile and presence of metabolic syndrome were more prevalent among youth with
T2DM compared to youth with TlDM cases, indicating a clustering of cardiovascular
risk in this sample of T2DM youth. Similar to data reported by Pinhas-Hamiel et al.
(1996), African Americans were over represented among the youth with T2DM in both of
these studies. The number of Hispanic youths diagnosed with T2DM compared to
Michigan’s ethnic distribution indicates that Hispanics were at a higher odds of being
diagnosed with T2DM compared to TlDM. These results mimic the adult scenario

where populations of color are at an increased risk of developing T2DM.

The age of onset of diabetes was significantly higher among youth with T2DM compared

to youth with TlDM. However, the age of T2DM onset in this sample is significantly

118

lower than is usually predicted for the onset of this disease. Hence, this disease, which
historically was common among adults is now becoming a pediatric problem, which
needs to be addressed. Similar results have been demonstrated by Neufeld et a1. (1998)
and Pinhas-Hamiel et al. (1996). In addition, puberty data analysis indicated that more of
T2DM subjects were at Tanner stage 3 or higher compared to TlDM youth. Therefore
based on puberty information and age of onset, puberty might be a precipitating factor for
T2DM in youth in conjunction with other risk factors such as overweight or obesity. Due
to hormonal changes (growth hormone) during puberty, there is increased resistance to
the action of insulin. The increased demand for insulin during puberty may exceed beta-
cell capacity resulting in overt diabetes mellitus (Arslanian, 2000). Among normal
children and adolescents, having normal B-cell frmction, insulin resistance during puberty
is compensated by increased insulin production and secretion leading to high circulating
insulin levels. However, in youth genetically predisposed to developing diabetes or
having strong associative factors of diabetes, these physiological changes likely tip the

balance from normal to impaired glucose tolerance (Liu et al., 2004).

The strong association of family history of diabetes with the occurrence of T2DM in the
youth identified in our study was not surprising. A positive family history of T2DM in a
first degree relative is a known risk factor for T2DM. Children with T2DM have a strong
link to positive family history of diabetes (Hale, 2000; Hale & Danney, 2000). Pinhas-
Hamiel et al. (1996), demonstrated that 65% of their subjects had a positive family
history of first degree family member with T2DM and 85% had a first or second degree

relative with T2DM. A study from First Nation children in Ontario indicated that 92.9%

119

of T2DM cases had a positive family history of diabetes (Harris et al., 1996). Studies
have demonstrated that inheritance of T2DM is multigeneic and heterogeous. While
some genes have been associated with T2DM in some studies, the findings vary in
different populations (Rosenbloom et al., 1999). On the other hand, relationship between
family lifestyle and diabetes has also been shown. Pinhas-Hamiel et al. (1996), examined
the “Type 2 family”, and found that family members were more likely to have central
obesity and lifestyles characterized by high fat intake, minimal physical activity, and a
high incidence of binge eating (Pinhas-Hamiel et al., 1999; Liu et al., 2004). Therefore,

family environment rather than genetics per se might be a key factor to note as well.

Acanthosis nigricans was a key distinguishing factor in the T2DM cases compared to
TlDM. It has been estimated that acanthosis nigricans can be found in 90% of children
and adolescents with diagnosed T2DM (Dabelea et al., 1999; Callahan & Mansfield,
2000). Acanthosis nigricans is a marker of insulin resistance and is associated with many
different conditions and symptoms that include insulin resistance and compensatory
insulin secretion (Liu et al., 2004). African American youth have a 25-fold higher
prevalence than other populations (Stuart et al., 1998). In our data 61% of African
Americans had acanthosis nigricans compared to Caucasian Americans (23%). Hence,
the presence of acanthosis nigricans is a good clinical indicator, as hyperinsulinemia
correlates with the presence and severity of acanthosis nigricans, making it a useful

indicator of risk for T2DM in youth.

120

The exceptionally strong association of T2DM in youth with overweight/obesity was
similar to studies published by Scott et al. (1997), Pinhas-Hamiel et a1. (1996), Dabelea et
a1. (1999), and Macaluso et a1. (2002). Recent data from the National Health and
Examination Survey (NHANES) 1999-00 suggests a continued rise in the prevalence of
overweight in youth, with approximately 15% at risk of overweight and another 15 %
overweight (Ogden et al., 2002). Overweight prevalence over the past 20 to 30 years has
doubled for children 2-5 years old and almost tripled for those 6 to 19 years of age (Liu et
al., 2004). A key physiological implication of overweight and link to T2DM is the
adverse effects on glucose metabolism. For example, 55 % of variance in insulin
sensitivity among healthy white children (i.e. who do not have diabetes) is accounted for
by total adiposity (Bogardus et al., 1985). The amount of visceral fat in overweight
adolescents was directly correlated with hyperinsulinemia and inversely related with
insulin sensitivity (Tamura A et al., 2000). Therefore, it is not surprising that the T2DM-

obesity association is so strong.

In the present study HbAlc levels were higher but not statistically significant among
TlDM youth compared to youth with T2DM. The reason for this is not clear but perhaps
the longer duration of diabetes in the TlDM cases and/or the metabolically unstable
nature of TlDM may be a primary factor. However, for both the groups HbAlc were
higher than the normal recommendations by ADA (HbAlc <7). This was an important
biomarker of diabetes control for both TlDM and T2DM. Hence, developing programs
targeted specifically for youth to control blood glucose levels is important. Except for

the HbAlc, all other biochemical parameters measured in this study were higher among

121

T2DM youth compared to youth with TlDM. Triglycerides were significantly (p<0.05)
higher and HDL-C significantly (p<0.0001) lower among youth with T2DM compared to
youth with TlDM. Total cholesterol and LDL-C also tended to be higher among youth
with T2DM compared to youth with TlDM, but the levels were not statistically
significant. These findings are unique and not previously reported. Therefore,
controlling and testing only HbAlc in this population is not sufficient. It is imperative
that lipid profiles are also considered, because of the fact that cardiovascular disease is
the leading cause of death in people with T2DM (American Diabetes Association, 2000;
CDC, 2004). Cardiovascular disease markers are thus just as important for the

prevention or amelioration of potential complications.

Although both T2DM and TlDM are serious conditions, youth with T2DM appear to
present with more metabolic aberrations compared to TlDM youth. According to the
American Diabetes Association (2000), dyslipidernia far outweighs all other risk factors
for cardiovascular disease in adults with T2DM. Hence, the scenario is likely to be

similar and even more for youth with T2DM.

More youth with T2DM had higher blood pressure percentiles compared to TlDM youth.
According to Carla Scott (1997), high blood pressure in youth may be secondary to their
overweight rather than a complication from diabetes. Our data indicated that among
youth with T2DM who had blood pressure percentiles >90th percentile, 87% had BIVII 2
95th percentile. Many national health surveys have also demonstrated youth-onset

hypertension as associated with overweight (Gotrnaker et al., 1987). A combination of

122

poorly controlled diabetes and hypertension could predispose individuals to chronic renal
failure and ultimately dialysis. While this is already a significant problem in older
individuals with T2DM, a much earlier onset of T2DM in youth might result in these
complications occurring at a much younger age, and hence potentially lead to a low

quality of life.

The data regarding adherence to self-care behaviors among T2DM youth were
discouraging. Youth with T2DM had poorer reported adherence to recommended dietary
advice, exercise, and monitoring blood glucose levels at home as regularly as
recommended compared to TlDM youth. Anecdotal information from our clinic staff
suggested that subjects frequently missing clinic appointments had poorer glycemic
control compared to those regularly attending clinics. These findings are similar to those
presented by Neufeld et al., 1998, for a sample of 11 Mexican-American subjects. Self-
care behaviors as recommended by the Association of American Diabetes Educators
(AADE), are an important aspect of controlling/maintaining normal blood glucose levels
(AADE, 2002). Poor compliance with self-care behaviors may be a major contributor
towards development of diabetes mellitus complications in this age group. One of the
proposed reasons is that T2DM cases are at a higher risk than those with TlDM for
failing to adhere to prescribed recommendations to control their disease and prevent long
term complications (Pinhas-Hamiel & Zeitler, 1998). T2DM subjects may not perceive
any immediate benefits from following their prescribed treatment regimen because the

severity of the response might not be as clearly evident. In the case of TlDM youth, a

123

missed insulin dose would, for example, result in pronounced effects, perhaps to the

extent of being admitted to the hospital.

Our results clearly show that youth with T2DM were less likely to adhere to treatment
regimens and dietary and exercise recommendations prescribed by the physician. Even
during the short period of follow-up, data obtained from medical records demonstrated
that the majority of these youth had abnormal lipid profiles and higher than normal blood

pressure levels.

T2DM in youth is becoming a major concern because of the very young age of onset.
Hence, if they are exposed to hyperglycerrria for a longer duration compared to those who
develop diabetes in adulthood/older age. This places them at greater risk of developing
more severe complications earlier in life. This becomes a greater problem with the added
factor of poor compliance with recommended care. Poor compliance has been a well-
known problem in adolescents with TlDM (Weissberg-Benchell et al., 1995), and this
problem is likely to be aggravated in youth with T2DM because of the insidious nature of
T2DM. Hence, aggressive intervention is needed to help control/delay development of

diabetes related complications in this very vulnerable population.

124

REFERENCES

American Diabetes Association (ADA) Consensus Statement: Type 2 diabetes in children
and adolescents. Diabetes Care 2000; 22(12): 381-389.

American Diabetes Association Clinical Practice Recommendations. Diabetes Care
2000; 23(suppl 1): $32-$60.

Arslanian SA. Type 2 diabetes mellitus in children: Pathophysiology and risk factors.
Journal of Pediatric Endocrinology Metabolism 2000; 13(Suppl 6): 1358-94.

Blood Pressure Tables for Children and Adolescents. Fourth Report on the diagnosis,
evaluation, and treatment of high blood pressure in children and adolescents,
2004; httrfi/wwwnhlbi.nih.gov/guidelines/hyperterrsion/child tbl.ht1n

Bogardus C, Lillioj a S, Mott DM, Hollenbeck C, and Reaven G. Relationship between
degree of obesity and in vivo insulin action in man. American Journal of
Physiology 1985; 248: E286-E291.

Callahan ST, and Mansfield J. Type 2 diabetes mellitus in adolescents. Current Opinion
Pediatrics 2000; 12: 310-315.

Cook S, Weitzman M, Auinger P, Nguyen M, and Dietz W. Prevalence of a Metabolic
Syndrome Phenotype in Adolescents. Archives of Pediatric Adolescents
Medicine 2003; 157: 821-827.

Dabelea D, Pettitt DJ, Jones KL, and Arslanian SA. Type 2 diabetes in minority children
and adolescents: An emerging problem. Endocrinology Metabolism Clinical of
North America 1999; 28: 709-729.

Dean AG, Arner TG, Sunki GG, Friedman R, Lantinga M, Sangam S, Zubieta J C,
Sullivan KM, Brendel KA, Gao Z, Fontaine N, Shu M, and Fuller G. Epi Info, a
database and statistics program for public health professionals. Centers for
Disease Control and Prevention 2002, Atlanta: Georgia.

Dean H. NIDDM-Y in First Nation children in Canada. Clinical Pediatrics 1998; 39: 89-
96.

Dean HE, Mundy RLL, and Moffatt M. Non-insulin—dependent diabetes mellitus in
Indian children in Manitoba. Canadian Medical Association Journal 1992; 147:
52-5 7.

F agot-Campagna A, Narayan KM, and Irnperatore G. Type 2 diabetes in children.
British Medical Journal 2001; Feb 17; 322(7283): 377-8.

125

Gortrnaker SL, Dietz WH, Sobol AM, and Weber CA. Increasing pediatric obesity in the
United States. Archives of Pediatric Adolescents Medicine 1987 ; 141: 535-40.

Hale DE, and Danney KM. Non-insulin dependent diabetes in Hispanic youth (Type
2Y). Diabetes 1998;47(supp1 1): A82.

Hale DE. Type 2 diabetes: An increasing pediatric problem. Family Practice
Recertification 2000; 22: 25-38.

Harris SB, Perkins BA, and Whalen-Brough E. Non Insulin Dependent diabetes mellitus
among First Nations children. New entity among First Nations people of north
western Ontario. Canadian Family Physician 1996; 42: 869-876.

Kenny SJ, Aubert RE, and Geiss LS. Prevalence and incidence of non-insulin dependent
diabetes mellitus. In: Harris MI, ed. Diabetes in America. Washington, DC: US
Government Printing Office 1995; 37-46.

Kitagawa T, Owada M, Urakarni T, and Tajima N. Epidemiology of Type 1 (insulin-
dependent) and Type 2(non-insulin-dependent) diabetes mellitus in Japanese
children. Diabetes Research and Clinical Practice 1994; 24(suppl.): S7-S13.

Kitagawa T, Owada M, Urakarni T, and Yamauchi K. Increased incidence of non-insulin
dependent diabetes mellitus among Japanese school children correlates with an
increased intake of annual protein and fat. Clinical Pediatrics 1998; 37: 111-115.

Liu L, Hironaka K, and Pihoker C. Type 2 diabetes in youth. Current Problem in
Pediatric Adolescent Health Care, 2004; 254-272.

Macaluso CJ, Bauer UE, Deeb LC, Malone JL, Chaudhari M, Silverstein J, Eidson M,
Goldberg RB, Gaughan-Bailey, Bonnie, Brooks, Robert, and Rosenbloom AL.
Type 2 diabetes mellitus among Florida children and adolescents, 1994 through
1998. Public Health Reports 2002; 117: 373-379.

Mokdad AH, Bowman BA, Ford ES, Vinicor F, Marks J S, and Koplan JP. The
continuing epidemics of obesity and diabetes in the United States. Journal of
American Medical Association 2001; Sep 12; 286(10): 1195-200.

Mokdad AH, Ford ES, Bowman BA, Nelson DE, Engelgau MM, Vinicor F, and Marks
J S. Diabetes Trends in the US: 1990-1998. Diabetes Care 2000; 23(9): 1278-
1283.

Neufeld ND, Raffel L, and Landon C. Early presentation of Type 2 diabetes in Mexican-
American youth. Diabetes Care 1998; 21(1): 80.

Norusis MJ (2002). SPSS 11.0 Guide to Data Analysis. NJ: Prentice Hall, Inc.

126

Ogden CL, F legal KM, Carroll MD, and Clifford LJ. Prevalence and trends in
overweight among US children and adolescents. Journal of American Medical
Association 2002; 288: 1728-1732.

Pihoker C, Scott CR, Lensing SY, Cradock MM, and Smith J. Non-insulin dependent
diabetes mellitus in African American youths of Arkansas. Clinical Pediatrics
1998; 37: 97-102.

Pinhas-Hamiel O, Standford DS, Hamiel D, Dolan LM, Cohen R, and Zeitler PS. Type 2
diabetes family: A setting for development and treatment of adolescent Type 2
diabetes. Archives of Pediatrics Adolescent Medicine 1999; 153: 1063.

Pinhas-Hamiel O, and Zeitler P. Type 2 diabetes in adolescents, no longer rare.
Pediatrics Rev. 1998; 19(12): 434-5.

Pinhas-Hamiel OM, Dolan LM, Daniels SR, Standiford D, Khoury PR, and Zeitler P.
Increased incidence of non-insulin dependent diabetes mellitus among
adolescents. The Journal of Pediatrics 1996; 128(5): 608-615.

Rewers M, and Hamman RF. Risk factors for non-insulin-dependent diabetes. In: Hanis
MI, ed. Diabetes in America. Washington, DC: US Government Printing Office
1995; 179-220.

Rosenbloom AL, Joe JR, Young RS, and Winter WE. Emerging epidemic of Type 2
diabetes in youth. Diabetes Care 1999; 22: 345-354.

Scott CR, Smith JM, Cradock MM, and Pihoker C. Characteristics of youth-onset non-
insulin-independent diabetes mellitus and insulin-dependent diabetes mellitus at
diagnosis. Pediatrics 1997; 100: 84-91.

Sigal RJ, and Warram JH. The interaction between obesity and diabetes. Current
Opinion Endocrinology Diabetes 1996; 3: 3-9.

Simmons D, Gatland BA, Leakehe L, and Heming C. Frequency of diabetes in family
members of probands with non-insulin-dependent diabetes mellitus. Journal of
Internal Medicine 1995; 237: 315-321.

Stuart CA, Gilkison CR, and Smith MM. Acanthosis nigrican as a risk factor for non-
insulin dependent diabetes mellitus. Clinical Pediatrics 1998; 37 (2): 73-79.

Weissberg-Benchell J, Glasgow AM, Tynan WD, Wirtz P, Turek J, and Ward J:
Adolescent diabetes management and mismanagement. Diabetes Care 1995; 18:
77 -82.

Willi SM, Mcbumey P, Kennedy A, Wojciechowski B, Garvey T. Ketosisprone NIDDM
in African-American children [abstract]. Diabetes 1997; 46(suppl 1): A67

127

Table 1. Descriptive characteristics of youth with Type 1 or Type 2 diabetes.

 

 

 

 

 

Family

 

 

 

Type 1 Type 2
Diabetes Diabetes
Age at diagnosis**** 8.7 i 4.0 13 i 2.8
Gender : Male 92 (44%) 92 (44%)
Female 123 (56%) 123 (56%)
Ethnicity****: Afiican American 48 (22%) 114 (52%)
Caucasian 92 (43%) 33 (15%)
Hispanic 2 (1%) 25 (12%)
Others 73 (34%) 45 (21%)
Living Status****: Single parent 82 (40%) 128 (65%)

 

****p<0.0001

Mean age: Type 1: l6i2.4; Type 2: 16i2.5

128

 

Table 2. Risk factor comparisons of youth with Type 1 or Type 2 diabetes youth.

 

 

 

 

 

 

 

Type 1 (%) Type 2 (%)
Family history of DM “*2 Yes 61 85
(N=193) No 13 4
Unknown 26 11

Acanthosis Nigricans****:Yes 6 73
(N=167)
Puberty status at diagnosis****:
(N=65)

Z Tanner 3 28 83

< Tanner 3 72 17

 

****p<0.0001, ***p<0.001

129

 

Table 3. Comparison of clinical parameters of Type 1 and Type 2 diabetes cases.

 

 

 

 

 

 

 

Type 1 DM Type 2 DM
% (n/N) % (n/N)
Hemoglobin Alc (mean i SD) 9.4 i 2.1 8.76 i 2.9
2 7 92% (201/219) 62% (132/212)
Triglyceride* (mg/d1) (mean i SD) 90 i 43 127 i 97
2 150 9 % (7/77) 33 % (23/69)
Total Cholesterol (mg/d1) (mean i SD) 172 i 38 178 i 43
2 170 48% (78/163) 53% (73/139)
HDL-C**** (mg/d1) (mean :t SD) 57 i 15 43 i 12
S 40 (low) 12% (10/83) 48% (33/68)
LDL- C (mg/d1) (mean i SD) 100 i 31 106 :t 41
2 110 29% (23/78) 38.5% (28/73)
Blood Pressure****(mmHg)

Systolic/ Dystolic (mean i SD)

115i13/65i10

127i15/68.2ill

 

 

2 90th %tile 74% (136/183) 85% (152/178)
Metabolic Risk Factors
HDL-Cm (mg/d1): s 40 (10W) 12% (10/83) 48% (33/68)
Blood Pressure****(mmHg): 2 90‘h%tile 74% (136/ 183) 85% (152/178)
Triglyceride“ (mg/d1), 2 110 34% (28/82) 49% (38/78)
Metabolic Syndrome**"‘* 28% (23/80) 57% (43/75)

 

 

 

**** p<0.0001, * p<0.05;

NCEP cutoff points, NCEP 2003. Metabolic syndrome cut off points. Cook et al., 2003

130

 

Table 4. Reported adherence to recommended self-care behaviors for youth with Type 1

 

 

 

 

 

or Type 2 diabetes.
Type 1 DM Type 2 DM
% (N) % (N)
Follow Diet Rx**** Yes 58% (94) 20% (32)
No 42% (69) 80% (124)
Follow Exercise Rx*** * Yes 62% (91) 36% (52)
NO 38% (56) 64% (91)
Self Glucose Monitoring/day**** < 2x 6 % (11) 22% (31)
2 2x 94% (173) 78% (109)

 

 

 

 

****p<0.0001

131

Table 5. Risk for being diagnosed with Type 2 diabetes compared to Type 1 diabetes,

serum triglyceride 2 150 mg/dl, and serum HDL-C S 40 mg/dl.

 

 

Models Odds Ratio (CI) Significance
Model 1: risk of being diagnosed with Type 2
diabetes
Gender (females) 0.94 (0.5,1.7) 0.84
Race 0.0001
Caucasian (ref)
AA 6.9 (3.1, 15.2) 0.0001
Hispanic 31.9 (5.5, 184) 0.0001
BMI 0.0001
<85‘“ %tile (ref)
85‘“ - 95‘“ %tile 75 (35, 160) 0.0001
2 95‘“ %tile 3.4 (1.5, 7.9) 0.005

 

Model 2: risk of having TC 2 150 mg/dl
Gender (females)

Race 1.4 (0.5,3.5) 0.50
Caucasian (ref) 0.98

AA
Hispanic 0.3 (0.7, 0.99) 0.04
BMI 1.5 (0.33, 7.0) 0.60
<85‘“ %tile (ref) 0.38

85‘“ - 95‘“ %tile
2 95‘“ %tile

Type of Diabetes 2.8 (0.6, 14) 0.20
Type 1 (ref) 2.3 (0.5, 11) 0.30
Type 2

4.0 (1.1-17.0) 0.05

 

 

Model 3: risk of having HDL-C s 40 mg/d

 

 

Gender (females) 0.94 (0.5,1.7) 0.84
Race 0.003
Caucasian (ref)
AA 0.6 (0.04, 0.5) 0.002
Hispanic 6.2 (0.5, 84) 0.17
BMI 0.0001
<85‘“ %tile (ref)
85‘“ - 95‘“ %tile 4.1 (1.1, 16) 0.04
2 95‘“ %tile 3.3 (0.8, 13) 0.08
Type of Diabetes
Type 1 (ref)
Type 2 8.0 (1.9, 34) 0.005

 

Logistic regression controlled for Gender, Race, & BMI, Type of diabetes

132

 

Figure 1. BMI percentile distribution of
youth by Type 1 or Type 2 DM

100“

78

80-

60-
%
40‘

    

   

 

11

   
 

20-

  

10 11

 

9

 

Type 1 DM Type 2 DM

.5th-85th %tile -=>85th %tlle -=>951h %tlle
p<0.0001

133

CHAPTER 6

Ecological factors influencing adherence to self-care behaviors among children

and adolescents with Type 2 diabetes

Abstract

Objective: The objective of this study was to examine the beliefs and perspectives of
adolescents with Type 2 diabetes regarding important self-care disease management
behaviors.

Design: In-depth interviews explored subjects’ experiences with diabetes prior to
diagnosis, participants’ views of diabetes self-management recommendations, current
lifestyle practices, and how social and institutional conditions influence their diabetes
care. In addition, physical activity and dietary intake data were collected with a
questionnaire and 24-hr dietary recalls respectively.

Results: Adolescents reported that the most difficult behavior was to follow dietary
recommendations. Perceived barriers to achieving dietary compliance included: eating
out, fast food temptation, and eating with fiiends. F arrrily support was identified as a
facilitator for many subjects. In the case of single parent families, however, the mother’s
busy schedule and income generating capacity were substantial factors, which influenced
self-care behaviors. Friends and institutions were deemed both helpful and detrimental in
helping subjects to follow their diabetes management behavior.

Implications: Diabetes education programs should focus on eating habits, time

management, relationship with family and fiiends, and making healthy choices when

134

eating out. A family based approach rather than an individual approach to diabetes
management should be the focus of education programs. Further research is needed to

refine the model developed, based on the findings of this study.

135

Introduction

Type 2 diabetes is a serious and growing health problem affecting all segments of the
population (Bolanos et al., 1995). Traditionally, Type 2 diabetes was known as an adult
disease and was strongly associated with obesity, positive family history and sedentary
lifestyle (Rewers & Humman, 1995; Simmons et al., 1995). However, over the last
decade, the age of onset of Type 2 diabetes has decreased and Type 2 diabetes has been
reported in children and adolescents worldwide with a greater proportion of minority
children being affected. Not only does diabetes have negative health consequences but

also its impact on patients is also considerable (Mitchell, 1998).

In the last decade there has been a concerted national effort to reduce the negative impact
of diabetes through improvements in self-care behaviors that lead to improved diabetes
management. Type 2 diabetes patients require adoption and maintenance of multiple
self-care behaviors to achieve and sustain good glycemic control (DCCT, 1993; Turner et
al., 1998). Such behaviors mainly include self-monitoring of blood glucose via finger
prick tests, exercising regularly, and adhering to a recommended eating regime. The
bases for this effort are supported by the findings of the UK. Prospective Diabetes Study
(Turner et al., 1998) and the Diabetes Control and Complications Trial (DCCT, 1993).
These findings emphasize the importance of self-care behaviors being incorporated as a

part of an integrated program to maintain good blood glucose control over time.

Studies have shown that these self-care behaviors are influenced by psychosocial,

behavioral, and environmental elements (Oltersdorf et al., 1999; Nestle et al., 1998).

136

Many studies, therefore have investigated behavioral and psychosocial issues influencing
food selection and eating patterns (Oltersdorf et al., 1999; Nestle et al., 1998). A study
by Travis (1997) of adults with Type 2 diabetes focused on psychosocial variables
affecting dietary adherence and identified the variables that influenced diabetes self-care.
Other quantitative studies specific to populations of color with adult Type 2 diabetes have
suggested that factors such as culture, ethnicity, socioeconomic status, and psychosocial
factors play a significant role in explaining self-care behavior patterns and outcomes

(Fitzgerald et al., 1997; Cgipkin et al, 1998; Bell et al., 1995; Gilliland et al., 1998).

Adolescence can be challenging especially when combined with a chronic illness such as
diabetes. Hence, it poses a unique problem for several reasons including: developmental
priorities competing with the demands of health care, chronic illness interfering with
social integration or psychosocial functioning, and the shift in responsibility of care fi'om
parents to the individual, sometimes resulting in confusion and anxiety (Court, 1991). In
addition, children and adolescents spend a substantial part of their day at school and
school personnel play an integral role in their daily diabetes management (Greenhalgh et
al., 1997). Students often have to incorporate glucose monitoring, insulin/medication
intake, and meal plans into their school routines (Siminerio and Koerbel, 2000).
Numerous cultural and socioeconomic barriers interfere with implementation of dietary
changes in youth with diabetes (Rosenbloom et al., 1999). Youth may lack familiarity
with recommended food items, which also may be costly, difficult for families to obtain,
or may require special preparation (Dean, 1998; Jones, 1998). Although adolescents do

start exerting more control over their health behaviors as they enter adulthood, results

137

from studies have indicated that most adolescents do not associate unhealthy behaviors
with negative health outcomes (Radius et al., 1980). Studies in Mexican-American Type
2 diabetes youth in California (Jones, 1998), Native American youth with Type 2
diabetes in Canada (Dean, 1998), and Native American youth with Type 2 diabetes in the
US. (Watkins etal., 1998) attribute non-adherence to many factors such as denial about
their diabetes because they are asymptomatic, and peer pressure to consume high-caloric

foods especially highly sugared beverages.

Studies in adolescents with Type 1 diabetes have demonstrated that Type 1 diabetes
interferes with the achievement of developmental tasks more during adolescence than in
any other period of the life cycle because of the conflicts between developmental needs
and glucose goals (Cerreto & Travis, 1984). Smith et al., (1991) indicated that
adolescents with Type 1 diabetes, who had better diabetes control reported more conflict
about issues of becoming independent and more concerns about family relationships
(Smith et al., 1991). Thomas et al., (1997), indicated that adolescents are less adherent to

their diabetes regimen than younger children.

The Diabetes Prevention Study among adults demonstrated that lifestyle intervention
(reduction of at least 7% of initial body weight through a healthy diet and physical
activity of moderate intensity for 150 minutes/week) reduced the incidence of Type 2
diabetes by 58% as compared to the placebo group (Diabetes Prevention Program
Research Group, 2002). However, research among adults also demonstrated that

adhering to a healthy diet and increasing physical activity were the most difficult

138

components of a self-care regime (Sullivan & Joseph, 1998). People with diabetes were
reported to be more resistant to dietary change when compared to people with other

chronic diseases (Groop and Tuomi, 1997).

Qualitative research has provided additional insights into the various psychosocial factors
influencing self-care behaviors of adults with Type 2 diabetes (Anderson et al., 1996; El-
Kebbi et al., 1996; Maillet et al., 1996). Although these studies identified a number of
important socio-cultural and psychosocial influences on self-management behaviors, and
particularly dietary behaviors, it is also necessary to have information on the relative
importance of these factors and how these manifest in day-to-day living. Moreover, there
is limited information on how unique personal dimensions, behavioral requirements, and
environmental characteristics of those with Type 2 diabetes affect lifestyle factors,

especially of youth.

This study proposes to contribute to what is known about lifestyle factors related to
diabetes control by employing the ecological theory of Bubolz and Sontag (1993), and
Mcleroy’s social-ecological model for nutrition evaluation (1988), as a guide for
identifying the structure, characteristics, and function of systems that facilitate control of
diabetes specially in youth. The conceptual framework based on these two ecological
theories proposes that the farrrily/social support (structure of the family, ethnicity, socio-
economic support, moral support of parents etc. ), the individual themselves (their own
behaviors, beliefs/values, attitudes, availability of resources), and the institutions

(diabetes centers, diabetes educators, physicians, insurance agencies, or other social

139

support agencies) are all inputs that influence an individual’s adapting or adhering to
self-care behaviors and to achieving glycemic control. Based on the conceptual map and
the literature reviewed, the following research questions were derived.
1) How do family factors facilitate or inhibit the management of diabetes in youth?
2) How do individual’s values and behaviors influence the management of diabetes?

3) How do institutions influence aspects of diabetes self-care practices?

Research methods

This study is a part of larger cross sectional study of diagnosed Type 2 diabetes in youth.
This phase of the study was a triangulated qualitative study that included in-depth
interviews, as well as assessment of the following self-care behaviors: medication intake,
home blood glucose monitoring, and dietary and physical activity patterns via a
questionnaire. The American Association of Diabetes Educators (2002) considers these
diabetes self-care behaviors as measures to determine the effectiveness of diabetes self-
management education at individual and population levels. Each behavior is important

for the overall management of diabetes.

Triangulation refers to combining data collection methods or data sources to enhance the
understanding of the setting and the target population (Taylor and Bogden, 1998).
Triangulation of data also serves to support the scientific status of research and increase
its utility to readers (Reinharz, 1992). The qualitative methodology selected corresponds

to the nature of the data sought: parental attitudes, individual experiences, social

140

networks and support systems (Fetterman, 1989; LeCompte & Preissile, 1993; Yin,

1989)

Subject recruitment and eligibility:

Subjects: The targeted study population was adolescents 14-18 yr diagnosed with Type 2
diabetes (i.e. criterion-based sampling). This age group was selected because at this age
adolescents are making independent food choices, independently conducting blood tests,
administering insulin injections, and are not as closely monitored by parents as a younger
child. At this age, girls are past their growth spurt while many males are still having
grth spurts. Subjects diagnosed with Type 2 diabetes less than six months were
excluded from the study due to the less duration of experience with diabetes
management. All the participants were residents of Michigan. The difference between
subjects with good glycemic control (HbAlc < 7%) and those with poor glycemic control
(HbAlc 27%) was also determined. The 7% cut point is the target set by the American
Diabetes Association (ADA) for good control (ADA, 2004).

Sample size: In qualitative studies, determination of sample size is usually done at the
end of the research, as there is an inverse relationship between the number of informants
and the depth to which an interview was conducted with each subject (Taylor and
Bogden, 1998). Based on similar qualitative studies published in the literature, we
anticipated that a sample of 20 subjects would be sufficient to obtain good quality data.
After 16 interviews were completed it was noted that no new information was
forthcoming in the interviews. Therefore, based on data saturation, 16 subjects were

determined as an adequate sample size for analyses.

141

Recruitment: Participants were recruited through advertisements (or fliers) in physicians’
offices and diabetes education centers. Subjects received a $20 token (gift certificates)
and a pedometer to acknowledge participation, once the data was collected. The time and
place of interviews were arranged according to the convenience of the participant.

Before the commencement of data collection, approval from the Internal Research
Review Board (IRB) for Human Subject research was Obtained from Michigan State
University and the endocrinology clinics. In addition, all the participants were requested
to sign an assent form and parents/ guardians were requested to sign a consent form.

Consent from parents/ guardians was necessary as subjects were under the age of 18 yr.

Procedures:

Semi-structured interviews: Qualitative interviews by two researchers were used to
elicit in-depth opinions and views regarding various issues like family and individual’s
own behavior, and influence of institutions fiom the participant’s perspective. Each
interview was 1 to 1 1/2 hours in duration. All interviews were audio taped in their

entirety and transcribed verbatim.

The interview questions were clustered around five general themes and were open and
intentionally non-directive to trigger broad, comprehensive responses. The core clusters
included: a) experiences with diabetes prior to diagnosis; b) individual perspectives on
diabetes self-management recommendations; c) current lifestyle practices; d) social and
institutional conditions that influence their diabetes care; and e) social support (family,

fiiends).

142

Before commencing these core interview questions, several descriptive questions were
asked to obtain data such as: ethnicity; age; education level; living status; duration of
disease; family history of diabetes; number of doctor visits per year; and type of

medications.

Physical activity: The purpose of the physical activity component of the questionnaire
was to assess the type, frequency, and duration of leisure time activity. A physical
activity regime for adults and adolescents minimal to maintain health is defined as
participating in physical activity at least three times a week, but preferably all days of the
week, for 30 or more minutes based on 2002 dietary guidelines (United States

Department of Agriculture, 2002).

In this study, a qualitative assessment for physical activity was sought, which would be
practical in terms of administration ease, time and cost for both the investigator and the
participants. Adaptation of the physical activity questions which were used by National
Longitudinal Study of Adolescent Health and Youth risk behavior survey of the Centers
for Diseases Control (CDC) (CDC 2003) were regarded as appropriate for the study. It
was important to first establish whether subjects exercised at all, and then to categorize
the activities which would most likely be selected, and finally assess frequency and
duration. The analysis was conducted to assess hours spent in active sports such as:
football, basketball, soccer; playing video garnes/ watching TV; and sleeping. Consistent
with other self-care variables, subjects were also asked to discuss the barriers they

encountered in achieving physical activity as recommended.

143

24-hour dietary recalls: The purpose of this section was to obtain information regarding
subjects’ usual eating habits or patterns, which could be used in targeting goals for
nutrition education. Dietary intake and compliance can be assessed quantitatively or
qualitatively via several methods. To obtain dietary information, two 24-hour recalls
(one weekend and one week day preferably) were used. Food recalls were conducted
using the USDA multiple pass method (Moshfegh et al., 1999) by a trained interviewer (1
interview in-person and 1 over the telephone). Since, only two people were conducting
the interviews, inter-person variability was low and consistency with the approach to
interviewing was facilitated. Specific dietary aspects of interest were the frequency and
type of meals as well as dietary habits and patterns with regard to intake of carbohydrate,
fat, fiber, soda, and snacks. Beverage consumption was defined as intake of soda, juice,

and milk.

Data analysis:
The data were organized and analyzed in the following steps:

1) After each interview, the researchers present at the interviews transcribed the
audiotapes verbatim. All transcripts were re-read while listening to the tape to
check for accuracy and fix errors, and to help the researchers become more
familiar with the data.

2) The transcripts were individually coded by two researchers, checked for accuracy,
and discussed by both the researchers until consensus was reached upon the
correct code. Units were very rarely coded twice. This was done only when

consensus could not be reached regarding which code to use. The two researchers

144

developed a preliminary list of code words based on recuning themes and some
pre-derived categories driven by the theoretical model based on the major
research questions (Table l).

3) Data from transcripts was loaded into NUD*IST N6 software (Non-numerical
Unstructured Data by techniques of Indexing Searching and Theorizing, QSR,
2003) for tabulation and identification of responses by code word.

4) Based on the developed preliminary codes, a coding matrix was constructed. The
researcher recorded all relevant statements from each subject’s transcript into the

coding matrix.

Physical Activity: Descriptive statistics was used to look at: average amount of time
spent exercising; types of exercises subjects were involved in; frequency per week they
exercised; and how many subjects met the recommendation for physical activity of
30mins/day and _>_3x/week (USDA 2002).

24-hr recall data: Dietary analysis was conducted by using Nutritionist V (First
DataBank, 1999). Descriptive statistics was used to assess percent kilocalories coming
from carbohydrates, carbohydrate consumption, percent kilocalories from fat, and amount
and number of times soda and sport drinks were consumed per day. Descriptive statistics
were also conducted to demonstrate how many subjects consumed breakfast, lunch,

dinner, and snacks, as well as how many meals were skipped in a day.

145

Results

Participant characteristics: The demographic characteristics are provided in Table 1.
The mean age for the subjects were 15.1 i 2.4 years, and the majority were females
(57%), Afiican American, and came from single parent families (lived with their

mothers).

Key themes from participant narratives: The main themes that evolved from this
analysis were: the influence of family (social support); the influence of lifestyle changes
and individual’s perspectives about being diagnosed with diabetes, diet, and physical
activity; the role of institutions; and the new emerging theme was the role of friends.
Table 2 displays the themes and sub-themes that emerged. Table 3 presents a count of
responses for some themes. A description of the participants’ views of each of these

themes is provided below.

Social support (influence of family): The majority of the subjects stated that they had a
very supportive family, which mainly consisted of a mother, grandmother, and siblings.
Whenever subjects had problems with their diabetes management or other things in life,
they went to their mothers for support. Mothers represented the major part of subjects’
support systems. One subject said, for example: “I go to my mom if she 's there, but if
she ’s not there, I go to my grandmother. ” Four out of sixteen subjects also mentioned
that fiiends were an important support system.

When asked about their reaction or feelings after being diagnosed with diabetes, most

responded with sadness, fear, surprise, devastation, a sense of separation from other

146

youth, and denial. One youth stated, “I was in denial, like, no, I don ’t. You guys are like
idiots or something. ” Another subject’s reaction was, “I was devastated. I thought
everything was over. ” Parents’ reactions towards their child’s diagnosis of diabetes
were mixed. Some parents felt scared, some were surprised, but most expressed that they
would support and help their children in any way. One of the parents expressed, “You
know, getting it now, so young, that ’s why I tell her, whatever it takes, you know for her
to live, we should do. All subjects reported that somebody in their family had either
Type 1 or Type 2 diabetes. However, not all reported that it was helpful for them to have

family members with diabetes.

Influence of lifestyle changes/ individual’s perspectives: When youth were asked about
whether diagnosis of diabetes had changed their lifestyle, most (10 out of 16) stated that
their lifestyle changed tremendously. One of the subjects stated, “I got to take time...like
take time aside to test my sugar and see what that is and if I need something to eat, go get
something to eat or whatever. ” Another responded, “I can ’t eat what I used to eat, I

don ’t go out a lot. ”

Most reported that their diet had changed since being diagnosed. Subjects were
consuming diet soda more often than regular soda. Food selection for all the subjects
meant limiting carbohydrate intake and avoiding high fat foods and candy. Most felt that
they had to cut back on chips, chocolates and sweets, pizza, flied foods, regular soda, and
juice. One subject reported, “I had to st0p eating so many fried foods, chips, and

candies. ” Subjects were aware that they had to eat more fruits and vegetables. Some of

147

the responses were, “I eat healthier, not a lot of carbs, but baked foods, salads, fruits,
and vegetables, but I love fatty foods ”; “I guess the fact that I have to eat more
vegetables helps me. I don ’t like it, but it helps. ” Most youth reported that they did not
like any vegetables except salads. Most youth reported a good understanding of diet in
diabetes management, but felt that it was difficult to follow. As one of the subject said,
“I think diet is tougher to do, because you are consistently faced with diflerent fast food
commercials giving you um, discount on this big burger. ” Also, many reported that
they were tempted to consume foods that were part of their lifestyle, prior to the
diagnosis of diabetes. In summary, diet was very difficult to follow for all the subjects.
These subjects had a good understanding of what to eat and what to avoid for diabetes
management. However, they were not practicing what they knew. Also, most mentioned

that eating packaged foods, canned foods, and fast foods were routine. These eating

practices were mainly as a result of parent’s busy schedules or lack of family mealtime.

Results from 24-hr recalls indicated that the 71% of subjects received >3 0% of their total
calories from fat. Fifty-seven percent of the subjects had >10% of their fat calories fiom
saturated fat. When parents were asked about the preparation method of certain food
items, it was noted that they practiced deep-frying of chicken, leaving the skin and fat on

chicken, and not eating enough vegetables.

Responses to exercise questions indicated that all subjects had started to exercise more

regularly and frequently than prior to their diagnosis of diabetes. For example, one of the

148

subjects reported, “I walk and dance, and go to recreational center to do weights Most

of the subjects’ felt that they could exercise, but not maintain a diet as easily.

Subjects also reported some barriers and facilitators of their diabetes management (Table
3). Subjects indicated that it was difficult to follow healthy dietary patterns when
spending time with fiiends and eating out. Laziness and fear of being made firn of kept
some participants from exercising. The facilitators for diabetes management in this group
were mainly: supportive family; positive attitude; and fear of sickness as a result of

uncontrolled diabetes.

Most subjects (9 out of 16) reported a high regard for their mothers. The reason for this
admiration was mostly because of the way she handled her life and took care of the
children. Most of the subjects looked up to their mothers and wanted to have her strength
and positive attitudes when they grew up. Managing diabetes was very important to the
subjects (11 out of 16), because they feared the complications that could occur as a result
of uncontrolled Type 2 diabetes. In this respect, one of the subjects reported, “I ’d rather
take care of myself than die. ” Another responded, “I am scared of the side effects of
diabetes, that’s why managing diabetes is important. ” This reinforced the fact that
education regarding the negative impact diabetes can have in the long run is known by
this study population, yet the subjects were not able to adhere to the recommended self-
care behaviors. Also, when asked about what they valued in life, the majority (8 out of

16) reported that they valued family, followed by fiiends, church, and education.

149

Role of institutions: Only 8 out of 16 subjects reported attending formal diabetes
education programs offered by their hospitals. The other half of the subjects said that
they had received diabetes information from their doctor, dietitian, and the nurse. These
classes and sessions with doctors/dietitian helped them to understand what diabetes was,
it’s complications, foods to avoid, foods to consume and so on. Only 3 subjects
mentioned that the school was really supportive for managing their diabetes. Subjects
and their parents/ guardians also offered some ideas about how the nutrition education
programs provided by hospitals and diabetes classes could be improved. The most
frequent request made by the subj ects/parents/ guardians was for more advice on planning
healthy meals. Parents were also confused about the type of diabetes their children had
and the use of oral medications/insulin. Most of the patients and family felt that, “If I
have Type 2 diabetes why am I on insulin ”, and “Does being on insulin mean that my
diabetes state is really bad. ” Some of the subjects thought that avoiding food all together
would help them deal with diabetes and were consuming 1 or 2 meals in a day. One of
the subjects also felt that basic diabetes classes for all healthy adolescents should be
conducted to make them aware of diabetes. This subject stated, “giving talks or sessions
in school would be helpful to normal kids not just diabetics " and “younger people need
to be more aware of how important it is, and how easy it is to become a diabetic. ”
Talking with the subjects revealed that to help them successfully manage diabetes,

constant reinforcement is needed for this age group.

Role of friends: When subjects were asked whether they talked about their diabetes with

their fiiends, the majority said “no” (10 out of 16). The main reason for not discussing

150

their diabetes with friends, was that they would be teased and discriminated against. One
subject stated, “Because they would make fun of me. ” Some of the subjects revealed that
they were teased at school for being overweight and did not want to aggravate the
situation. Among subjects who informed friends about their diabetes, most specified that
it was only after a few years when they were much older. One of the subjects

summarizes this explanation as follows: "Well I did not really start telling my friends,
until I got like to middle school, junior high. ” Most of the subjects indicated that none of
their fiiends knew what diabetes was, and did not understand or care about it. Another
interesting finding in this respect was that subjects felt that if they drank diet soda or did
not eat some candy/flies, they stood out and that their friends would then tease them

about being on a diet (“why you are having that, are you on a diet ”).

Physical activity: Physical activity data indicated that subjects spent on an average 7 .8 i
5.5 hours per week in active sports while they spent 25 i 12.8 hours per week in
sedentary activities. When data for television watching/playing video games was
analyzed, it was noted that subjects spent on an average 21.2 i 11.4 hours per week on

these activities. The most often reported barriers to exercising were bad weather (36%),

laziness (36%), and feeling sick (36%).

24-hour recall results: Descriptive data for dietary data are present in Table 4. Total
calorie consumption of subjects was in the normal range that is recommended for this age
group. However, for 73% of subjects, more than 30 percent of calories came fiom fat.

Calcium consumption was low compared to the DRI’s for this age group (518 v/s 1300

151

mg). Dietary patterns indicated that only 40% of subjects had breakfast every day of the
week, 40% of the subjects had 3 meals per day, 7 out of 16 subjects had only 1 fruit in a
day, 4 out 16 had any vegetables in a day, and 9 out of 16 subjects had eaten out on their
days of 24-hour recalls. Beverage consumption data (beverage includes juice, milk and
soda) indicated that a median of 14 oz was consumed per day. Median diet soda
consumption, regular soda consumption, and juice consumption were: 8 oz, 8 oz, and 12

oz per day respectively.

Data were also analyzed to compare youth with HbAlc < 7% (n=9) and HbAlc 2 7%
(n=7). Quantitative analysis of dietary recalls and physical activity data indicated no
significant difference between the two groups. Total calories, fat, saturated fat, and % fat
of total kilocalorie intake was greater among subjects with HbAlc 2 7% compared to
subjects with HbAlc <7%, but these results were not statistically significant. A similar
trend was noticed for hours spend in active sports. Subjects with HbAlc 2 7% spent
fewer hours per week in any active sport compared to those with HbAlc < 7% (6 hrs v/s
8.3 hrs, p=0.49). Qualitative data indicated, that adjusting to diet changes after diabetes
diagnosis was better in subjects with HbAlc < 7% compared to those with HbAlc 2 7%.
The majority of the subjects with HbAlc 2 7% indicated that they did not follow dietary
recommendations. Qualitative information regarding exercise showed that a similar

pattern existed between both the groups.

152

Discussion

The key findings showed that incorporating recommended changes in lifestyles after the
diagnosis of diabetes were difficult to follow, and that family support as well as friends
and were important facilitators of diabetes management. Following dietary
recommendation was one of the most difficult behavior changes for adolescents. Many
barriers, such as eating out, not able to give up fast foods, and eating with friends were
indicated as influencing dietary choices. Family support was a facilitator for many
subjects, but single parent status added a new perspective to the support system. Role of
fiiends and institutions was both helpfirl and detrimental in helping subjects follow their
management behavior for diabetes. Figure 1 presents the model based on these research
findings and illustrates a preliminary view of how these components might relate to each

other and influence adolescents adherence to diabetes management behaviors.

Individual’s perspective: In this study, one main observation that stood out was
“difficulty in following dietary recommendations”. Observations from this study
indicated that being diagnosed with diabetes did not always result in change of eating
habits. Previous qualitative studies among adults with diabetes have indicated a positive
relationship between eating history prior to diabetes and its influence on current dietary
practices (Hampson et al., 1990; Schoenberrg et al., 1998; Hunt et al., 1998). Hence, past
eating habits need to be integrated into nutritional counseling considerations for diabetes
subjects. Most subjects in the present study demonstrated a good understanding of food
selection and meal planning in relation to their diabetes. Previous studies among adults

have indicated a positive relation between knowledge of food selection and meal

153

planning and level of subjects’ dietary adherence (Travis, 1997). Glasgow et al. (1989)
demonstrated that knowledge about food selection and portion was a better indicator of
dietary self-care behaviors than any demographic variable (Glasgow et al. 1989). In this
study, the majority of the subjects felt that they had the knowledge, but they were not

able to transfer this knowledge into maintaining a balanced diet. It is known that
adolescents spend a large amount of time outside of the home, and they do not have much
control over food purchasing and preparation. Hence, parents/ guardians need to be
included in nutrition education programs, and adolescents should be encouraged to
participate in planning family meals. F amily-based education classes should be

conducted to encourage healthy eating and meal planning.

The barriers mentioned in this study could be targeted during interventions to change a
desired behavior. For example, the noted potential barriers included social support, time
management, and attitude/self-efficacy. More specifically, the purported lack of school-
based support was particularly disturbing. Similar variables have been identified in other
diabetes self-management studies among adults and adolescents with Type 1 diabetes
(Ellison and Rayman, 1998; O’Connor et al., 1997; Hunt et al., 1998; Samuel-Hodge et

al., 2000).

Family Support: The majority of the subjects reported that they had a very supportive
family. However, the fact that so many subjects came from single parent families might
have limited the mothers’ ability and time to provide the kind of support she would have

liked. La Greca and Bearman (2002) demonstrated that among adolescents with Type 1

154

diabetes, the family support variables that were most associated with adolescents’
adherence involved daily management tasks like meals, glucose testing, and insulin
administration, rather than exercise or emotions (La Greca & Bearman, 2002). On the
other hand, a study by Anderson et al. (2001) indicated that a family’s emotional support
may help adolescents prevent or minimize feelings of depression, which were reportedly
high among individuals with diabetes (Anderson et al., 2001). These previous findings
when applied to the present study suggest that single parents with a busy schedule might

not have enough time to support their adolescents with diet, exercise, and emotions.

Influence of friends: Support from friends and influence on self-care behaviors was
identified as a major factor in this study. Subjects were not comfortable informing
friends about their diabetes. However, as subjects became older (middle school or junior
high), they shared their diabetes problem with friends. A small number of subjects also
mentioned that their friends helped them keep away from eating junk food at school,
though this attitude of fiiends bothered subjects at times. On the other hand, most
subjects felt that when in the company of friends, they were more likely to consume fatty
foods and drink regular soda. Previous studies have indicated that support from friends is
mainly oriented toward companionship and emotional support (La Greca et al., 1995;
Bearman & La Greca, 2002). This support from fiiends is typically more occasional than

daily support (La Greca et al., 1995; Bearman & La Greca, 2002).

Role of institutions: Results regarding the role of institutions provided very mixed

information about schools. Only 3 out of 16 subjects surprisingly indicated that schools

155

acted as a positive support system for them. These were the schools that had a nurse on
staff. At these schools, parents felt that the children were receiving healthy meals.
Adolescents spend on an average one-third of the day at school. Hence, school staff
plays an integral part in daily care (Clayton et al., 2002). Previous studies have suggested
that teachers are not well trained to care for students with diabetes (Ratrrer et al., 2002;
Gormanous et al., 2002; Siminerio et al., 2000), school nurses are not always available
(Brener et al., 2001), and care of students at school is restricted (Brener et al., 2001). In
the present study, parents felt that schools were offering high fat foods, drinks, and a la
carte snacks that were not healthy for their children. Previous studies indicated that
adolescent students with diabetes and their parents expressed concerns about unhealthy
school meals. They expressed a desire for a greater variety of healthy choices in the
cafeteria and vending machines (Hayes-Bohn et al., 2004). The American Diabetes
Association (ADA) and the American Association of Diabetes Educators (AADE) have
position statements regarding diabetes care at school and both state that professionals at
schools should be trained, and that schools should partner with health care providers to
develop or support individualized diabetes care plans (AADE Position Statement, 2000;

ADA position statement 2002).

Implications for practice: Nutrition education emerged as a key foundation for effective
diabetes management. Diabetes management was strongly affected by individual’s
behavior (diet and exercise). As mentioned earlier, changing eating habits/following a
diet was indicated to be the most difficult part of self-care behaviors. Although the

diagnosis of diabetes may change an individual’s personal view of life, elements of daily

156

living like family, friends, and food preferences remain the same. When planning an
intervention, an important point to keep in mind is that adolescents with Type 2 diabetes
are different from those with Type 1 diabetes. Type 2 diabetes subjects do not perceive
any immediate benefits from following their prescribed treatment regimen because lack
of adherence might not result in any serious metabolic symptoms. However, youth with
Type 1 diabetes would see pronounced effects even to the extent of being admitted to the
hospital if they missed their insulin. Hence, intervention strategies should be
individualized, explain the course of disease, and focus on all the aspects that influence
dietary behavior including the “silent effects” that might later be manifested in

irreversible physiological complications that could have been averted.

Educators can facilitate adoption of healthy eating patterns among subjects by helping
them assess their eating habits. Education programs should incorporate skill-building
activities to help develop self-efficacy, time management, and problem solving
techniques. Educators need to individualize education and help subjects develop routines
based on their lifestyle. Results from this study indicated that most of the subjects were
unsuccessfiil in transferring diabetes knowledge into practice. It is known that
adolescents spend a large amount of time outside of the home, and they do not have much
control over food purchasing and preparation. Hence, parents/ guardians need to be
included in nutrition education programs and adolescents should be encouraged to
participate in planning family meals. F arnily-based education classes should be
conducted to encourage healthy eating and meal planning. The barriers mentioned in

this study can help plan interventions providing solutions on how to deal with these

157

barriers. All adolescents should be encouraged to attend diabetes camps, or support
groups that help adolescents share their problem about diabetes or share how they deal

with diabetes (ADA 2004; CDC 2001).

Limitations of the study: Some of the limitations of this study are, firstly this was a
small sample of adolescents with Type 2 diabetes. To generalize these findings, more
ethnic representation is needed and a larger sample size fi'om different demographics is
required. In five cases, parents were present at the time of interviews and might have
influenced subject responses. It was observed that when asked about role of institutions
and how institutions could be more helpful in management of diabetes, parents were very
eager to respond. Hence, in future studies it would be beneficial to interview both
parents and youth separately to help obtain different perspectives. Additional research is
needed to confirm the proposed behaviors, barriers, and facilitators mentioned in this
study. Future research can help refine and validate the proposed model (Figure 1) for
management of diabetes. Research in the area of stages of change might provide some
idea about self-efficacy of Type 2 diabetes adolescents regarding their preparedness to
change their eating and lifestyle factors, and why transferring knowledge into practice is

a problem in this specific population.

Conclusion
In summary, this is one of the first studies that provided a glance into the lifestyles of
adolescents with diagnosed Type 2 diabetes. It provides information regarding how

adolescents feel about diabetes, the typical problems they face and even provides

158

suggestions for health care providers (examples- information about diabetes, educating
students at school about diabetes, more specific information on type of foods to
consume). Thus, diabetes education programs specific for this youth population that
seeks to help individuals reduce the barriers associated with achieving recommended

self-care behaviors is pertinent.

159

REFERENCES

American Association of Diabetes Educators. Individualization of Diabetes Self-
Management Education. Diabetes Educator 2002; 28(5): 741-749.

American Diabetes Association. Diabetes Care at Diabetes Camps. Diabetes Care 2004;
27: $129-$131.

American Diabetes Education. Available at: http://diabetesgg. Accessed October 2004.

Anderson RM, F reedland KE, Clouse RE, and Lustrnan PJ. The prevalence of comorbid
depression in adults with diabetes: A meta-analysis. Diabetes Care 2001; 24:
1069-1078.

Anderson RM, Barr PA, Edwards GJ, Funnell MM, Fitzerald J T, and Wisdom K. Using
focus groups to identify psychological issues in urban black individuals with
diabetes. Diabetes Education 1996; 22: 28-33

Bolanos E, and Sania-Santarnera A. Perspective of patients on Type 2 diabetes and their
relationship with primary care health professionals: a qualitative study. Hanis
MI. Summary. In: National Diabetes data Group, ed. Diabetes in America, 2nd
edition. NIH Publications No. 95-1468, 1995: 1-13

Bearman KI, and La Greca AM. Assessing friend support of adolescents’ diabetes care:
The diabetes social support questionnaire-friends version. Journal of Pediatric
Psychology 2002; 27(5): 417-428.

Bell RA, Summerson JH, and Konen J C. Dietary intakes by levels of glycemic control
for black and white adults with non-insulin dependent diabetes mellitus
(NIDDM). Journal of The American College of Nutrition 1995; 14: 144-154.

Bell RA, Summerson JH, and Konen J C. Racial differences in psychological variables
among adults with non-insulin-dependent diabetes mellitus. Behavioral Medicine
1995; 21: 69-73.

Bolanos E, and Sarria-Santamera A. Perspective of patients on Type 2 diabetes and their
relationship with primary care health professionals: a qualitative study. Harris
MI. Summary. In: National Diabetes data Group, ed. Diabetes in America, 2nd
edition. NIH Publications No. 95-1468, 1995: 1-13.

Brener ND, Burstein GR, Dushaw ML, Vernon MF, Wheeler L, and Robinson J. Health

services: Results from school health policies and programs study 2000. Journal
of School Health 2001; 71: 294-304.

160

Bubolz MM, and Sontag MS. (1993). Human ecology theory. In P.G. Boss, W.J.
Doherty, T LaRossa, WR Schumm, SK Steinmetz (Eds), Sourcebook of family
theories and methods: A contextual approach. (pp. 419-448). New York: Plenum
Press.

Centers for Disease Control and Prevention (CDC). (2003). National Surveys.
http://www.cdc. gov

Centers for Disease Control and Prevention (CDC). Strategies for reducing morbidity
and mortality from diabetes through health-care system interventions and diabetes
self-management education in community settings. A report on recommendations
of the Task Force on Community Preventive Services. Morbidity and Mortality
Weekly Report Recommendations and Reports 2001; 28: 1-15.

Chipkin ST, and De Groot M. Contextual variables influencing outcome measures in
minority populations with diabetes mellitus. Diabetes Spectrum 1998; 11: 149-
1 60.

Clayton BJ, Goodwin DK, and Kendrick 0. Nursing, food service, and the child with
diabetes. Journal of School Nursing 2002; 18: 1501-1516.

Cerreto MC, and Travis LB. Implications of psychological and family factors in the
treatment of diabetes. Pediatric Clinics of North America 1984; 31(3): 689-710.

Court JM. Outpatient-based transition services for youth. Pediatrician 1991; 18:150-156.

Dean H. NIDDM-Y in First Nation children in Canada. Clinical Pediatrics 1998, 39: 89-
96.

Diabetes Control and Complications Trial Research group. The effect of intensive
treatment of diabetes on the development and progression of long-term
complications in insulin-dependent diabetes mellitus. New England Journal of
Medicine 1993; 329: 977-1036.

Ellison GC, and Rayman KM. Exemplars’ experience of self-managing Type 2 diabetes.
Diabetes Educator 1998; 24: 325-330.

El-Kebbi IM, Bacha GA, Ziemer DC, Musey VC, Gallina DL, Dunbar V, and Phillips
LS. Diabetes in urban African-American. Use of discussion groups to identify
barriers to dietary therapy among low-income individuals with non-insulin-
dependent diabetic mellitus. Diabetes Educator 1996; 22: 488-492.

Fetterman, D. M. (1989). Ethnography Step by Step. Newbury Park, CA: Sage.

Fitzgerald J T, Anderson RM, Funnell MM, Arnold MS, Davis WK, Amam LC, J acober
SJ, and Grunberger G. Differences in the impact of dietary restrictions of

161

AFRICAN Americans and Caucasians with NIDDM. Diabetes Educator 1997; 23:
41-47.

First DataBank, (1999). Nutritionist V. Dietary data analysis tool.

Greenhalgh S. Improving school teachers’ knowledge of diabetes. Professional Nurse,
1997; 13: 150-156

Gilliland SS, Carter J S, Perez GE, Two Feathers J, Kenui CK, and Mau MK.
Recommendations for development and adaptation of culturally competent
community health interventions in minority populations with Type 2 diabetes
mellitus. Diabetes Spectrum 1998; 11: 166-174.

Glasgow RE, Toobert DJ, Riddle M et al. Diabetes-specific social learning variables and
self-care behaviors among persons with Type2 diabetes. Health Psychology
1989; 8: 285-303.

Gormanous M, Hunt A, Pope J, and Gerald B. Lack of knowledge of diabetes among
Arkansas public elementary teachers: Implication for dieticians. Journal of The
American Dietetic Association 2002; 102: 1136-1139.

Groop LC, and Tuomi T. Non-insulin dependent diabetes mellitus-a collision between
the thrifty gene and an affluent society. Annals of Medicine 1997; 2937-2953

Hampson SE, Glasfow RE, and Toobert DJ. Personal models of diabetes and their
relations to self-care activities. Health Psychology 1990; 9: 632-646.

Hayes-Bohn R, Neumark-Sztainer D, Melin A, and Patterson J. Adolescent and diabetes
mellitus management at school. Journal of School Health 2004; 74(5): 166-169.

Hunt LM, Pugh J A, and Valenzuela MA. How patients adapt diabetes self-care
recommendation in everyday life. Journal of Family Practice 1998; 46: 207-250.

Jones L. (1998). Wisconsin nutrition education program annual report: 1998, Madison,
WI: University of Wisconsin cooperative extension service.

La Greca AM, Auslander EF, Greco P, Spetter D, Fisher EB, and Santiago JV. I get by
with a little help from my family and friends: Adolescents’ support for diabetes
care. Journal of Pediatric Psychology 1995; 20: 449-476.

La Greca AM, and Bearman KJ. The diabetes social support questionnaire-family
version: Evaluating adolescent’s diabetes-specific support from family members.

Journal of Pediatric Psychology 2002; 27(8): 665-676.

LeCompte, MD, and Preissle, J. (1993). Ethnography and Qualitative Design in
Educational Research (2nd ed.). San Diego: Academic.

162

Maillet N, D’Eramo-Melkus G, and Spollett G. Using focus groups to characterize he
health beliefs and practices of black women with non-insulin-dependent diabetes.
Diabetes Education 1996; 22: 39-45.

McLeroy KR, Bibeau D, Steckler A, and Glanz K. An ecological perspective on health
promotion programs. Health Education Q 1988; 15: 351-377.

Mitchell GJ. Living with diabetes: How understanding expands theory for professional
practice. Canadian Journal of Diabetes Care 1998; 22: 30-7.

Moshfeg A, Borrud L, Perloff B, and Lacomb R. (1999). Improved Method for the 24-
hour Dietary recall for Use in National Surveys. FASEB J 13(4): A603.

Nestle M, Wing R, Birch L, DiSogra L, Drewnowski A, Middleton S, Sigman—Grant M,
Sobal J, and Winston M. Behavioral and social influences on food choices.
Nutrition Reviews 1998; 56: 850-874.

O’Connor PJ, Crabtree BF, and Yanoshik MK. Differences between diabetic patients
who do and do not respond to a diabetes care intervention: A qualitative analysis.
Family Medicine 1997; 29(6): 424-428.

Oltersdorf U, Schlettweing-Gsell D, and Winkler G. Assessing eating pattems-An
emerging research topic in nutritional sciences; Introduction to the symposium.
Appetite 1999; 32: 1-7.

Radius SM, Dillrnan TE, Becker MH, Rosenstock IM, and Horvah WJ. Adolescent
perspective on health and illness. Adolescence 1980; 15: 375-3 84.

Rewers M, and Hamman RF. Risk factors for non-insulin-dependent diabetes. In: Harris
MI, ed. Diabetes in America. Washington, DC: US Government Printing Office
1995; 179-220.

Rosenbloom AL, Joe JR, Young RS, and Winter WE. Emerging epidemic of Type 2
diabetes in youth. Diabetes Care 1999; 22: 345-354.

Reinharz S. (1992). Feminist methods in social research. New York: Oxford University.

Sullivan ED, and Joseph DH. Struggling with behavior changes: a special case for clients
with diabetes. Diabetes Education 1998; 24: 72-77.

Samuel-Hodge CD, Headen SW, Skelly AH, and Ingram AE. Influences on day-to-day

self-management of Type 2 diabetes among African-American women. Diabetes
Care 2000; 23(7): 928-933.

163

Savoca M, and Miller C. Food selection and eating patterns: Themes found among
people with Type 2 diabetes mellitus. Journal of Nutrition Education 2001; 33:
224-233.

Schoenberry NE, and Amey CH. Stories of meaning: Lay perspectives on the origin and
management of non-insulin dependent diabetes mellitus among older women in
the United States. Social Science and Medicine 1998; 47: 2113-2125.

Siminerio LM, Clougherty M, Gilliland A, and Kelly K. Evaluating children with
diabetes and their parent’s preparedness and involvement in diabetes care for the
school. Diabetes 2000; 49: A173.

Simmons D, Gatland BA, Leakehe L, and Heming C. Frequency of diabetes in family
members of probands with non-insulin—dependent diabetes mellitus. Journal of
Internal Medicine. 1995; 237 : 315-321.

Siminerio LM, and Koerbel G. A diabetes education program for school personnel.
Practical Diabetes International 2000; 17: 174-177.

Smith MS, Mauseth R, Pahner JP, Pecoraro R, and Wenet G. Glycosylated hemoglobin
and psychosocial adjustment in adolescents with diabetes. Adolescence 1991;
26(101): 31-40.

Sullivan ED, and Joseph DH. Struggling with behavior changes: A special case for
clients with diabetes. Diabetes Educator 1998; 24: 72-77.

Taylor SJ, and Bogdan R. (1998). Introduction to qualitative research methods: a
guidebook_and resource. (3rd ed.). New York: John Wiley and Sons.

Thomas AM, Peterson L, and Goldstein D. Problem solving and diabetes regimen
adherence by children and adolescence with IDDM in social pressure situations:
A reflection of normal development. Journal of Pediatric Psychology 1997; 22:
541 -561 .

Tuomilehto et al. NEJM 2001; 344: 1343-1350.

Travis T. Patient perceptions of factors that affect adherence to dietary regimens for
diabetes mellitus. Diabetes Educator 1997; 23: 152-156.

Turner RC, Millns H, Neil HA, Stratton IM, Manley SE, Matthews DR, and Hohnan RR.
Risk factors for coronary artery disease in non-insulin dependent diabetes
mellitus: United Kingdom prospective diabetes study (UKPDS :23). British
Medical Journal 1998, 316: 823-828.

164

US. Department of Agriculture (USDA) and US. Department of Health and human
Services (2002). Nutrition and your health: dietary guidelines for Americans.
Washington, DC: US Government Printing Office.

Watkins PB, and Whitcomb RW. Hepatic dysfunction associated with troglitazone. New
England Journal of Medicine 1998; 338: 916-917.

Yin RK. (1989). Case study research, design and methods. California: Sage

165

Table 1: Descriptive characteristics of the total sample (N=16).

 

 

 

 

Age in years (mean i SD.) 15.1 i 2.4
Gender: Females (n=9) 56%
Males (n=7) 44%
Ethnicity: African American (n=12) 75%
Hispanic (n=2) 12.5%
Caucasian (n=2) 12.5%

 

 

166

 

 

$050550 53 :0»
55.05 5 05 0505 50500 50.550500

 

005550 .50 0.0. 05 555 :0» 00 55>» .m 5550555
5050555 55509505 55550 50.5 85550
5050655 .65 505535 .m 85550 :0 02:82 55505 505 055 505 0.553 .N 50 80050.0 055
5055505 08:05.. 55505 502 .m 8050055055505 5.05:0» 50 85:55 5055555
50 505 02:0m .5 .50 85:55 050 055 05 265 55 :0» 050 0.553 ._ 00 265 .m
90: »5>? 50 45535 558:0» .50 050 055 :0» 5:05 55>» .5
5550055 $5 55052 - 555:0»
M5505 50:03 .50m .N .50 050 555 505 :0» 5005 55>» .m
5550555000.. 05055 0% m»; $05550
5_0 w526=05 05 50555505 - 50» 0555 05 :0» 50.5 55.655 5 5 .0
50500555008 05055 0055 5:0» 553 $05550
0% 550 5:26:05 05 505.85 - 50 :0» 305 005050 85550 005 265 .m .50 5050555
0505055 - «$555.55 26: 00 :0» 00 55>» .m 85:55
0550555 55 - 05: »=00 «“055 5030505 05 8:53
50:00:05 5030505 5550552 .5 :0 005550 .50 50.5w 5:0» 005050 005550 5065 85 >65 ._ $05.53 00 265 .N

 

5500505500.. 5550.5 -
55005005000. 550.35 -

$505 000: :0» 553 505500
50 505 .85 55 :0» 00 5053 0 .5. .0
2:55.05 83 550.5 50» 5 053 £05550

 

 

 

 

 

 

 

58550 05 055005 .0 005 :0» 50 00:05 555 :0» 553 .m $05550

ED 553 505505 $05550 .50 50505505 055

505550 05 0.5895 .555 .m 0>05 5555 5:0» 5 050 0:0»5 800 .N 55555 .0 0555005

505% 5055 .N 550.5 .50 85:55 5550.5 5050.5 5005555

50.55 500m 055:5 5550“— ._ 500.53 5505 5:0» 05 05 505000 :0» 00 05>? .5 00 305 .—
50508

0505055. 85055.5:m 8505a. 5058:O 300(05— 5058:O 50.5805

Haw—505.5 0055:0582? 5005.“. =0>€0.»..005,—.

 

 

555050 500 :0 00005 003.50 5505 5:m 05 005055. ”N 555—1

167

 

 

 

05055.: 0 Z a
0: \+ 55 5 .5 c 55550
$350 50 525 555 a as, 505 20 a @255 .0
-\+ 5 55550 55550 $5555
-\+ 55 50 035.635 5555 05 53
55550 05 5055005 0.55505 0 55550
55550 05 5050005 55555 c 553 005550 053 »05 055
55559 05 5055005 .0 55.5 05 552 55555 050 >63 .0

-1 N 55 .

+ 5 0550055055545 0

+ n 05055055 0

+ m 555 .

+ m 00D 0

+ m5 502 o
5055 toggm .5 5.6555. 505 0w :0» 00 5053 0 5. .5

5 555505 555 o

5 00555 o

m m5m:00\0_0=:\5:< o

m 05055055 0

a 550. .

5 00D 0

m5 502 c

05535 55505 .0 5555 .50» 505500 :0» 00 05>? .0 5550.5 .5
550555 05:50 Z 55055.:
550555 05555 50 .0 Z 5055505 05059

 

 

 

 

 

 

005555 5505 055 05 050 5:0 50 550555 ”m 0550.5.

168

coughed 8 @222 E0888 93860de 8 gamma: "0.30%“: 95mm» Z

sofa—wow 9 @828 “5888 afflict 8 338m "8:032 033mg

 

+

5825
_oonomtonomoh

omhséuaommhofioefixnmom

0838 538:8

mowfiamu 363w»: cosmos?
0288 35an 26 825»

cosmoscm
@235
.m

 

 

++++++

 

fiN‘u—aw—Iv—Iv—i

 

£25
“Swan
55mm
:22
ED
802

can?“ so» ow 0:3 6

 

d

 

3933?:
.m

 

33:08 35302 8805 2.: 8 38.3% no momcommom .m 2an

169

 

Table 4: Barriers and facilitators indicated by Type 2 diabetes youth.

 

Facilitators

Barriers

 

 

“My right attitude helps me. I take it more
seriously”

“Knowing that if you don't manage it right
you can get real sick”

“Friends support me”

“Family was supportive, they helped me in
remembering to take my tablets and test
blood sugar”

“I am more conscience of my health. And
um, I also more conscience of other diseases
that um, can effect how urn, you would
normally live. And I was not really aware of
um how much diabetes can change you life
and how much it can actually improve your
awareness of yourself and others”

“It helps me so much because it lets me lmow
where I am at were I need to go and where I
don't need to go and um, that's what helps

,,

me

“My family helps me take care of my
diabetes”

“Mostly my family. My watch helps me. Urn,
it got a timer on here and I got it set to when
I got to take my

medicine”

“My mom helps me take care of myself”

“Friends are supportive, one friend that's a
diabetic”

 

“. . ..a lot of pricking does really hurt. . .my
fingers and stuff so, that’s the only I can
really think of”

“The only thing I would say is the pain of
injections that would stop me from times
um, taking injections or a shot because of
the pain. It hurts. You know, after you
do it over and over you know a period of
time it hurts”

“Harder to stick to my diet”

“Very expensive to buy all stuff. And me
and his aunt bought it and the we tried to
keep up with the strips but their
expensive”.

“Forget to take medications, or sometimes
to not eat certain things”

“Kids making fun is not helpful at all”

“Because of my weight, I don’t get to
play”

“Giving up eating fast foods and fatty
foods is har ”

“Easier to eat fatty snacks when come
back from school”
“Can’t stop eating the favorite foods”

“When you go on school trips, it is hard to
eat things different from others”

“I don’t go out to play because people
make fun of me, because of my weight”

 

170

 

Table 5: Dietary intake (24- Hour Recall) descriptive for total sample (N=16).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

N=16
Kilocalories mean i SD. 1893 i 743
Rang 748, 3348
Protein (g) mean i SD. 68.5 i 32
Range 22, 157
Carbohydrate (g) mean i SD. 207 i 97
Range 117, 396
Fat (g) mean i SD. 83 i 49
Range 22, 195
Saturated fat (g) mean i SD. 25 i 16
Range 7, 54
Cholesterol (g) mean i SD. 205 i 154
Range 22, 660
Total sugar (g) mean i- S.D. 69 i 41
Range 26, 122
Calcium (mg) mean i SD. 518 i 257
Range 128, 1032
Sodium (mg) mean i SD. 2926 :t 1617
Range 1137, 6997
% fat >30% mean i SD. 38 i 10
of total kcal >30% 73% (1 1/16)
% sat. fat >7% 87% (13/16)
>10% 60% (9/16)

 

171

 

 

 

 

  

.2800 030:8:

  

 

 

0:4 .8 3:000 00.8.88— _—

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

        

 

 

 

E
SE .23
00030800 0.080938-
25.-
8 00080930:
:5 0% 0M5 \l HflDEOWNH—dz ] chum a «02:
todmsmnémaw- \080..:0m 0.88008 00 >55-
. 3:05
8088 :0: - 0000: 00888800 -
w:w30.=mh 02:th \ 008080514 00:00—85 5:» 0”“ wEwfiwm
000 .«0 2.00080 . . =035aac< 03832 030M008
05 @8305? 0&8 9 “0 Moan-
. \lnl 0000.8 8
00380 5&2- ,/ gnaw—8.5m. U $008-38 a: 836.
£88.08 888 8:30
9800 88¢. 0.800.
80:00? “80 80A.
was—2.8 Bwfim-
; jig flotsam
0 _ _ a :3 .
0 0.2 New 5? 82823.3.
8380 .3530- 0003mfi< mMm . .3 H
cozwozcm 0000205 80_>0s0m Ewto 085m wEwBEm
8088080 $02090030> 0.8085
2.3.585 .3328 583388.88
\l 3.5:—

 

 

 

 

//

088m 88 8 005802 8008508 00 8283 080 0805 88080 30: 885 _0008 3:800:00 ; 08wE

 

172

CHAPTER 7

Summary and conclusions

Diabetes is clearly recognized as one of the most common and costly diseases in the
United States today, affecting more than 18 million Americans with as many as half
undiagnosed (Centers for Disease Control and Prevention (CDC), 2002). Type 2 diabetes
in children and adolescents concomitant with the rising rates of obesity has recently
emerged as a “newly recognized” pediatric epidemic in the US, towards which enhanced

national and state efforts need to be directed.

Among adults, numerous studies have documented a significant correlation between the
prevalence of Type 2 diabetes and relative weight for height (Mokdad et al., 2000 &
2001). Data of a nationally representative sample from NHANES 111 (1998-1994) and
National Longitudinal Study of Adolescent Health (Add Health) (NCHS 1994, Flegal et
al., 2001) indicated that approximately 14% of children aged 6-11 years and 12% of
adolescents aged 12-17 years are overweight, with an almost equal distribution among
males and females. Obesity-related studies in Michigan have shown that among children
aged 4 to 17 years, 38% of the boys were above the 85th percentile and 16% above the
95th percentile for weight. Of the girls, 33% were above the 85th percentile and 13% were

above the 95th percentile (Gautheir et al., 2000).

173

Reported studies on prevalence/incidence of Type 2 diabetes among youth have
demonstrated a significant recent increase in the number of youth diagnosed with Type 2
diabetes. These studies have concluded that this increase was strongly associated with
obesity. The fact that Type 2 diabetes is strongly linked to obesity and Michigan was
recently ranked number three in the country for adult obesity, and one city, Detroit, was
classified as the “fattest city‘ ’, warrants the importance of this study (Michigan
Department of Community Health, 2004). Because this is a topical area of research,
there is a paucity or very limited data, both nationally and for Michigan. True prevalence
is difficult to determine since there is undoubtedly an undiagnosed population similar to
that, which exists for adults. However, the proportion of those who have been recognized
as having the disease and who are being treated at endocrinology clinics will provide

useful information.

Therefore, the purpose of this study was to estimate the number of children and
adolescents (6-19 yr), who have diagnosed Type 2 diabetes among those who have either
Type 1 or Type 2 diabetes at endocrinology specialty clinics in Michigan. Endocrinology
data was used because they were the most likely to have significant numbers of
diagnosed cases. Additional useful information was obtained for professionals who
diagnose or counsel children with Type 2 diabetes on glycemic control differences
between Type 2 and Type 1 diabetes and associated biomedical, family and health

behavior factors.

174

A two-phase study was conducted using an in—depth medical chart review and subject
interviews. In Phase 1 of this study, data on the total number of youth aged 6-19 years
with diabetes (Types 1 or 2) was obtained from clinic data systems. These data were used
to estimate the proportion of diagnosed Type 2 diabetes in this population. Additionally,
a comparison study for medically diagnosed Type 1 and Type 2 diabetes subjects in the
age group of 6-19 years controlling for age and gender was also conducted. Phase 2 of
this study, involved an in-depth qualitative interview and survey study with diagnosed
cases of Type 2 diabetes adolescents. The main aim of this phase was to determine
which factors were most likely to influence diabetes control in the population of children

and adolescents with Type 2 diabetes.

The primary finding of this multi-clinic study demonstrated that the relatively high
proportion of diagnosed Type 2 diabetes among children and adolescents in Michigan is
comparable to the results published by previous single clinic studies (Pinhas-Hamiel,
1996; Pihoker et al., 1998; Neufeld et al., 1998; Glaser, 1998; Macalusco et al., 2002).
This study demonstrated that diagnosed Type 2 diabetes accounted for 11.1% of all
children and adolescents diagnosed with diabetes in the age group of 6-19 years, and 14%
of all children and adolescents diagnosed with diabetes in the age group of 10-19 years at
8 pediatric and adult clinics in the state of Michigan. Adolescents were more likely to be
diagnosed with Type 2 diabetes than those younger than 10 yrs, similar to that of some of
the previously published studies (Pinhas, 1996; Glaser, 1995; Neufeld et a1, 1998). The
population of these clinics was representative of the population of the lower peninsula of

Michigan. Hence, extrapolations based on the results of this study and census data, it was

175

determined that in the lower peninsula of Michigan, the estimated prevalence of Type 2
diabetes was approximately 11.03/100,000. These results imply that healthcare providers
must be aware of the possibility of Type 2 diabetes in youth and be alert to identify
subjects at high risk because of the strongly associated factors such as obesity and family
history of diabetes. The need for successful treatment of Type 2 diabetes in youth is
critical give the possible onset of secondary complications from this disease at such early

ages.

Comparison of Type 2 and Type 1 diabetes cases matched for age and gender, indicated
that obesity, acanthosis nigricans, positive family history of diabetes and abnormal lipid
profile are more significantly associated with Type 2 diabetes compared to Type 1
diabetes cases. Children and adolescents, more likely to be diagnosed with Type 2
diabetes relative to Type 1 diabetes, were significantly more overweight, Afi'ican

American, or Hispanic and the age of diabetes onset was much higher.

The mean age of diagnosis for Type 2 diabetes was 13.0 i 2.8 years, which is very
similar to data from Pinhas-Hamiel et. al. (1996). Females on average were diagnosed at
least 6 months earlier than males. The earlier onset of diabetes in females may be
attributed to the onset of puberty. The age of onset of diabetes was significantly higher
among youth with Type 2 diabetes compared to youth with Type 1 diabetes (13 i 2.8 v/s
8.7 i 4). More youth with Type 2 diabetes were at Tanner stage 3 pubertal status or
higher compared to youth with Type 1 diabetes. Typically in females, puberty begins on

average, one year earlier compared to males. More female subjects (54%) were pubertal

176

when diagnosed with Type 2 diabetes. Due to hormonal changes during puberty, there is
increased resistance to the action of insulin. The increased demand for insulin during
puberty may exceed beta-cell capacity resulting in overt diabetes mellitus (Arslanian et
al., 2000). Among normal children and adolescents, in the presence of normal B-cell
function, insulin resistance during puberty is compensated by increased insulin
production and secretion leading to high circulating insulin levels. However, in youth
who are genetically predisposed to developing diabetes or have the presence of strong
associative factors for diabetes, these physiological changes can tip the balance from

normal to impaired glucose tolerance (Liu et al., 2004).

The exceptionally strong association of Type 2 diabetes in youth with overweight/obesity
are in line with similar studies published by Scott et al., 1997, Pinhas-Hamiel et al., 1996,
Dabelea et al., 1999, and Macaluso et al., 2002. Classification of subjects by BMI
percentile showed that the majority of youth with diagnosed with Type 2 diabetes were 2
95th %tile, whereas the majority of youth diagnosed with Type 1 diabetes had BMI %tile

between the 5th and 85th %tile.

Family history of diabetes was significantly higher in youth with Type 2 diabetes (84%)
compared to in youth with Type 1 diabetes (61%). The fact that family history appeared
to be a strong predictor, is not surprising given the strong association seen in previously

reported studies (Pinhas-Hamiel, 1996; Glaser, 1998; Neufeld, 1998).

177

Acanthosis nigricans was present among 73% of Type 2 diabetes cases compared to only
6% of Type 1 diabetes cases. It is estimated that acanthosis nigricans can be found in
90% of children and adolescents with diagnosed Type 2 diabetes (Dabelea et al., 1999;
Callahan et al., 2000). Acanthosis nigricans is a marker of insulin resistance and is
associated with many different conditions and symptoms that include insulin resistance

and compensatory insulin secretion (Liu et al., 2004).

Lipid profile data indicated that triglycerides were significantly higher and high density
lipoprotein —cholesterol (HDL-C) was significantly lower among youth with Type 2
diabetes compared to youth with Type 1 diabetes. Total cholesterol and low density
lipoprotein- cholesterol (LDL-C) were also higher among youth with Type 2 diabetes
compared to youth with Type 1 diabetes, but these results were not statistically
significant. These are some prominent findings, not previously reported. Of specific
relevance was the fact that contrary to what is commonly believed, controlling and testing
for HbAlc only in this population is not enough. It is imperative that lipid profiles are
also considered. Although both Type 2 and Type 1 diabetes are serious conditions, youth
with Type 2 diabetes were more likely to have metabolic aberrations compared to youth
with Type 1 diabetes. According to the American Diabetes Association (2000),
dyslipidemia far outweighs all other risk factors for cardiovascular disease in adults with
Type 2 diabetes. Hence, the same scenario might also be true for children with Type 2
diabetes. Since cardiovascular disease is the leading cause of death in people with
diabetes, it is imperative that dyslipidemia’s are carefully monitored. Risk of

microvascular complications in this Type 2 diabetes population, due to the early age of

178

onset, may be significantly higher because these complications are directly related to
duration of diabetes and hyperglycemia. In addition, significantly more youth with Type

2 diabetes had higher blood pressure percentiles compared to youth with Type 1 diabetes.

Youth with Type 2 diabetes were significantly less likely to eat, exercise, or self-monitor
blood glucose as recommended when compared to youth with Type 1 diabetes. Poor
compliance with self-care behaviors may be a major contributor towards development of
diabetes mellitus complications in this age group. One of the proposed reasons is that
Type 2 diabetes cases are at a higher risk than the Type 1 diabetes population for not
following prescribed recommendations to control their disease and prevent long term
complication (Pinhas-Hamiel, 1998). It may be that Type 2 diabetes subjects do not
perceive any immediate benefits from following their prescribed treatment regimen
because lack of adherence is not fiequently associated with any serious metabolic
symptoms. However, in the case of individual with Type 1 diabetes, the effects of poor
compliance are severe and almost immediate. An additional factor of concern is
frequency of medical/clinic visits. Subjects who miss their clinic appointments

frequently had poorer glycemic control compared to those attending clinics regularly.

Another striking finding of this study was the living status of youth. Sixty five percent of
youth with Type 2 diabetes were living with single parent families, while this was the
case for only 40% of youth with Type 1 diabetes. The in-depth interviews demonstrated
that the majority of the subjects had a very supportive family. However, in the case of

single parent families, the mother’s busy schedule and income generating capacity were

179

substantial factors, which influenced self-care behaviors. Support from friends and
influence on self-care behaviors in this study was important. It was noted that subjects
were not comfortable informing friends about their diabetes. However, as subjects
became older (middle school or junior high), they were more likely to share their diabetes
problems with friends. A small number of subjects also mentioned that friends helped
them refrain fi'om eating “junk food” at school. However by the same token, a large
number felt that when in the company of friends, they were more likely to consume fatty

foods and drink regular soft drinks such as coke.

Youth with Type 2 diabetes mentioned that, changing eating habits/following a diet was
the most difficult part of self-care behaviors. Reducing or eliminating high fat foods and
fast foods was especially difficult for these youth. The majority of the subjects felt that
they had the knowledge about food selection and food preparation in relation to diabetes,
but they were not able to transfer this knowledge into maintaining a balanced diet and
eating a variety of foods. Adolescents spend a large amount of time outside the home,

and they do not have much control over food purchase choices and preparation.

Strengths

The strengths of this study were: 1) this was the frrst reported multi-clinic study and
included adult as well as pediatric endocrinology clinics throughout the lower peninsula
of Michigan. Hence, the population of these clinics was representative of the population
of the lower peninsula of Michigan. This provided a good estimate of the proportion of

children and adolescents in lower Michigan who may have Type 2 diabetes among

180

children with either Type 1 or Type 2 diabetes. 2) The procedures for this study involved
both quantitative and qualitative methods to obtain data. Data from Phase 1, indicated
that obesity, acanthosis nigricans, positive family history of diabetes and abnormal lipid
profile are more significantly associated with Type 2 diabetes compared to Type 1
diabetes cases. Qualitative interviews in Phase 2 of the study helped provide an in-depth
picture of barriers or facilitators to achieving recommended self-care behaviors necessary
for good diabetes control. Social and institutional supports as well as subjects’ own
willingness were examined. Poor adherence to self-care behaviors have been noted
among adults with Type 2 diabetes, but this is the first reported study to demonstrate a
similar problem among youth with Type 2 diabetes. The fact that this study indicated
that the majority of youth with Type 2 diabetes were living in single parent families,
highlighted an often unrecognized factor that might be crucial in some cases to adequacy
of care and monitoring. An additional strength of the study, not often mentioned, was the
level of volunteerism. The nurses, dietitians, physicians, and office staff who volunteered
to assist with this study did so without any financial compensation, and were extremely
helpful in verifying the accuracy of data or identification of missing or difficult to find

data.

Limitations

While this study had significant strengths, it also had limitations. During Phase 1 of the
study, we would have liked to have included a clinic from the Upper Peninsula, so that
we could get a more representative sample for the entire state of Michigan. However, the

upper peninsula, did not have an established pediatric endocrinology clinic. A temporary

181

physician visits every two months instead. At the time they were contacted, the response
was that no youth with Type 2 diabetes were being attended to. Data collection over a
longer period of time (8 to 10 years) in order to assess true incidence changes over the
years would have been very helpful but was not feasible. However, this was a PhD

dissertation, and thus limited by the amount of time.

Future Directions

This study will add to the limited data that is available fi'om other states in the US, and
ultimately towards estimating national statistics. A platform for conducting a more in-
depth study with continuous data collection at the sites covered in this study was
provided. Contacts and relationships have already been established and medical staff is
willing to participate in an on-going data collection effort to better document the problem
of Type 2 diabetes in Michigan. Michigan has no registry of Type 2 diabetes for youth.
Hence this study is a stepping-stone for creating a registry. The data about self-care
behaviors and findings about barriers and facilitators from the interview phase provide
important information for designing an intervention program to help better control

diabetes.

A prospective study with youth with Type 2 diabetes will help us understand the course
of the disease in this group, and monitor the development of complications associated
with diabetes. An intensive intervention study duplicating the Diabetes Prevention
Program in adult, in order to circumvent the condition could be planned for youth at risk

for Type 2 diabetes.

182

Also, a study using the stages of change can be employed in this population to study the
self-efficacy of these youth in following dietary and exercise recommendations. Results
from Phase 2 of this study indicated that the majority of the subjects felt that they had a
very good understanding of food selection and meal planning in relation to their diabetes,
but they were not able to transfer this knowledge into maintaining a balanced diet and
eating a variety of foods. Stages of change might help us determine how many subjects
are at precontemplation, contemplation, preparation, action, and maintenance stages.
This information will help develop education program, skill-building activities to
increase self-efficacy, and problem solving techniques as suitable for an individual

person.

In summary, Type 2 diabetes among children and adolescents (6-19 years) in the state of
Michigan is as high or higher than reported studies in other states. Most of these youth
are overweight/obese, from single families, 10-19 yrs old, and demonstrate poor
compliance with diabetes management self-care behaviors. This study highlighted the
fact that besides medical/physiological factors, social factors also play a prominent role
in diabetes management. Metabolic aberrations were more prevalent among Type 2
diabetes youth compared to Type 1 diabetes youth, suggesting that the likelihood of
developing complications was high. The problem is compounded by the fact that the vast
majority has multiple risk factors. Therefore, it is important that health practitioners

address these risk factors via both screening and intervention strategies.

183

APPENDICES

184

APPENDIX A

Pharmaceutical Agents For The Treatment Of Type 2 diabetes (Evert, 2002)

 

 

 

 

 

 

 

 

 

Class Mechanism of action Name FDA approval
Sulfonylureas Promote insulin Acetohexamide, Safety and
secretion cholpropamine, effectiveness in
glimepiride, pediatric patients
glipizide, gylburide, not been
tolazamide, established
tolbutamide
Biguanides Decrease hepatic Metforrnin Safety and
glucose output, effectiveness for
enhance hepatic and treatment of Type
muscle sensitivity to 2 diabetes has
insulin, no direct on been established
beta-cell in pediatric
patients 10-16
years of age
Meglitininde, Short-term promotion Repaglinide, No studies
nataglinide of glucose-stimulated nataglinide performed in
insulin secretion pediatric patients
Alpha- Slows hydrolysis of Acarbose, miglitol Safety and
glucosidase complex effectiveness in
inhibitor carbohydrates, slows pediatric patients
carbohydrate has not been
absorption established
thiazolidenedione Improve peripheral Rosiglitazone, Safety and
insulin sensitivity pioglitazone effectiveness in
pediatrics patients
has not been
established

 

 

185

 

APPENDIX B

DATA ABSTRACTION FORM

Children and Adolescents Diagnosed with Type 2 Diabetes in Pediatric and Adult
Endocrinology Clinics in Michigan, Glycemic Control and Associated Factors.

Study Site: Date Abstracted:
Subject I.D.: Reviewer :
Supervising Physician:

Date ofBirth: __ / __/

Zip Code of Residence:

Diagnosis of Diabetes: Yes
No
Uncertain (e. g. glucose tolerance)

"If diabetes was noted on chart, then"
Type as recorded on chart- Type 1
Type 2, without insulin

 

 

 

 

 

 

Type 2, with insulin"
DM, difficult to classify
Gestational
Duration of Disease - no. of years
OR
Date of diagnosis-
Diabetes Management:
1. Oral Medication:
Yes No
Name of the drug/drugs: a- b-
c- d-
Dosage-
2. Insulin :
Insulin injections: Yes No
Type: a. b.

 

 

186

c. d.

 

 

Dosage:

 

Insulin pump: Yes
Type: a.

 

 

 

.o-srz
O

C

 

 

Dosage:

 

3. Diet:
Yes No
If Yes, diet prescription as noted

 

4. Exercise:
Yes No
frequency of exercising Type of exercise

 

 

 

 

5. Self glucose monitoring:
times per day :

 

6. Stress management: Yes No

 

Race: Afi'ican American
Caucasian American
Hispanic American/Latino American
Native American

Asian American
Other : specify

Gender: Male
Female

Medical Insurance:
None
Medicare Medicaid

 

 

 

Private- HMO PPC

Income (monthly): OR Income (yearly):

 

 

Height: feet and inches

Weight: pounds

No. of clinic visits in the past year:

 

No. of hospitalizations in the past year:

187

Reason for clinic visit:
Acute problem
Health Maintenance
Chronic Illness follow-up
Others

 

 

Comorbidities:

 

 

 

 

 

 

 

Family History of Diabetes Mellitus: Yes/No
Mother
Father
sibling(s)
Grandparent(s)
Uncle/aunts
Great grandparent(s)

Living Status:
With Mom only
with Dad only
With both parents
With grandparent/s
"Other, specify

Sibling information:
Number of siblings

Parent information:
Married
Separated
divorced
Never married
Widowed
Other, specify

188

Age of Parents:
MotherDOB: OR current age: yrs.
Father DOB: OR current age: yrs.

 

 

 

 

Parent employment:
Father: Yes NO
Mother: Yes NO

Skin pigment changes in chart ( neck, under arms, back of legs)
Yes
No

Puberty information:

1. Age at onset of puberty: age in years

2. Stage of puberty at diagnosis of DM:

3. Current sexual maturation:

 

Glycemic control indices on record:

 

 

 

 

 

 

 

 

 

 

 

 

 

Tests over Date Value Date Value
past 2 years

GHB

Lipid Profile done: Yes No

 

 

Testsover st2 ears Date Value
Totalcholestero mg/dl)

Tr cer e m /d
HDLcho stero m /d
LDLcho stero m /dl)

Total cholesterol : HDL
ratio

 

189

Others Biochemical tests:

Tests over t 2 ars Date Value
C-peptide

Insulin

Islet cell Antibodies

Microalb uminuria

Blood Pressure
Others:

190

 

Appendix C

Informed Consent Form

Participant/Guardian Consent Form
Children and Adolescents Diagnosed with Type 2 diabetes in Pediatric
and Endocrinology Clinics in Michigan, Glycemic Control and
Associated Factors.

Investigators: Lorraine Weatherspoon PhD, RD
(517) 355-8474 ext. 136

Deepa Handu MS
(517) 355-8474 ext. 164

Purpose: We invite you to participate in a research project designed to study the unique
experiences and voices of youth with Type 2 diabetes regarding monitoring blood
glucose, exercising regularly, dietary recommendations, food selection and eating
patterns, social support, institutional support and the aspects of daily living that influence
their diabetes self-management practices.

Type 2 diabetes mellitus (90-95% of all cases of diagnosed diabetes) has clearly been
identified as a serious epidemic in our society, which can be prevented or ameliorated by
self-managed lifestyle changes, especially diet and physical activity. Although the
American Diabetes Association and other similar organizations have established target
behaviors for management of the disease, the traditional medical model has been
unsuccessfirl in effectively facilitating target behaviors. There is need for research that
includes exploration of the individual’s objectives and priorities for diabetes self-
management education and care as they may differ from those of the health care team and
published standards of care. This project will ask you questions about how you deal with
diabetes management. Our purpose for this study is to learn more about your experiences
so that we can be more helpful to families who have youth with the Type 2 diabetes.

Procedure/What you will be asked to do if you participate:

Your voluntary participation in this study will involve one meeting with the researcher
which should take approximately 1- 1 V2 hours. We will be talking/discussing about
doctor and health professional recommendations that help with blood sugar control and
how easy or difficult it is to follow this advice and why. The procedures followed are: 1)
you will be asked to participate in an interview with a researcher; and 2) A 24- hour
dietary recall will be conducted by the researcher.

191

The purpose of this project is to help develop successful intervention for youth with Type
2 diabetes. Your participation in this research project is completely voluntary. You will
continue to receive diabetes center services and medical care as you usually do whether
or not you choose to participate in this research. You can refuse to answer any questions
that you do not wish to answer. The interview or discussion will be audio-taped. The
tape will be used for transcription purposes only and will be destroyed following
transcription. Your name or any identifier will not appear on the transcription and will
not be associated with the study findings in any way. You can withdraw your
participation at any time. At the end of the interview, you will receive a $25 gift card to
Meij er’s/Best Buy/ Cash in appreciation for your participation. If for any reason, you
decide to discontinue with the interview (dropout before it ends) you will only receive a
pedometer in appreciation for your participation.

RISKS AND BENEFITS: There are no risks or discomforts associated with this
research. You may feel tired during or after the evaluation. Some psychological
discomfort may be experienced from revealing personal information or thinking about
things that are related to you diabetes experiences. Keep in mind that you may take a
break at any time and you can refuse to answer any questions that make you
uncomfortable. There are no implied benefits for the participants in this study. However,
the results from this study may be beneficial to youth who have Type 2 diabetes mellitus
and their families in the fiiture. If desired, you may learn of the study results by asking
the investigators that the results be available to you when the study is completed

Confidentiality:

During and after this research, your privacy will be protected to the maximum extent of
the law. All information that refers to you, or can be identified with you will remain
confidential to the maximum extent permitted by law. If you choose to sign this consent
form, you are also giving consent to have the interview audio-taped, so that the
researchers have complete and correct information from the interview. You may request
at any time to have the taping stopped and you can refuse to be taped at all. All data,
including audio-tapes, will be kept for three years and then destroyed.

Other than this form, all data will be identified only with a code number. A list linking
your name to the code will be kept in a locked file for the duration of the study. Once all
the data are collected and analyzed, the list linking the names to the code numbers will be
destroyed.

Who to contact for answers: If there are any questions you have at any time about
this research project or your participation in it, please contact one of the investigators:

Lorraine Weatherspoon, PhD, RD OR Deepa Handu, MS

334 A GM Trout FSHN Bldg. 301 GM Trout FSHN Bldg.
Michigan State University Michigan State University
East Lansing, MI 48824 East Lansing, MI 48824

192

If you have questions or concerns regarding your rights as a study participant, or are
dissatisfied at any time with any aspect of this study, you may contact (anonymously, if
you wish) — Ashir Kumar, M.D., Chair of the University Committee on Research
Involving Human Subjects (U CRIHS) by phone: (5 17) 355-2180, fax: (517) 432-4503,
email: UCRIHS@MSU.EIE, or regular mail: 202 Olds Hall, Michigan State
University, East Lansing, MI 48824.

Your participation in this project is voluntary: Your participation in this study
is voluntary. If you wish, you may decline to participate, simply by telling the project
investigator. If you decide to participate in this study, and later decide that you do not
wish to continue, you may at any time withdraw your consent and stop participation. You
decision not to participate, or to participate and later withdraw fiom the study will not in
any way result in a penalty to you, or a loss of benefits to which you are otherwise
entitled.

Your signature below indicates your voluntary agreement to participate in this

 

 

 

 

 

 

 

study.
Print Name of the Subject:
Signature of Parent or Legal Guardian Date
Signature of the Research Participant Date
Signature of the Person obtaining consent Date

193

APPENDIX D

Interview Guide

ID number Date of Interview

 

 

 

Demographic sheet

. Date of birth

 

. Gender: Male Female

 

. Education (of child)

1. Attend school
2. Does not attend school
3. Other: home school etc.

. In what grade are you right now

. Which of these groups would you say you and most of your family belong to?

a. White b. African American

c. Hispanic (1. Asian

e. Native Hawaiian/Pacific Islander f. American Indian, Alaska Native
g. Others, specify_ h. Do not know/Not sure

i. Multiracial but preferred j. Refuse to answer

race not asked

. With whom do you live?

a. Mom only

b. Dad only

c. Both mom and dad
d. Grandparents

e. Others

194

7. Marital status (of parents)
Are you : 1. single 2. married
3. widowed 4. divorced/separated

8. Employment status (of parents)
Employed (full time)
Employed (part time)
Disabled, unable to work
Homemaker
Unemployed

Retired

Student

Other (specify)

we rm 9.0 9‘s»

9. On a scale of 1 (very poor) to 5 (very rich), how would you describe your family’s
income/ money status:

. Very less money (very poor)

Less money

Enough money

More than enough money

Lots of money (very rich)

MPPN"

10. Since when have you had diabetes?

 

i. How ofien do you visit the doctor in a year?

 

MEDICATION
ii. Do you take insulin shots?
Yes(Ol) No(02) NA(3)

13a. Do you take diabetes tablets?
Yes (01) No(02) NA(3)

13b. Do you have any problems taking diabetes tablets when you are supposed to do

so?

Yes (01) No(02) NA(3)

14c. What do you do if yes in 6b?
1. Take it later 2. Wait until the next medicine time
3. Other (specify):

15. Other Medications?

195

 

MONITORING

16. How often do you check your blood sugar at home?

 

17. Do you check it yourself? / Who helps you check your blood sugar?

 

18. What interferes with your blood sugar testing at home?

I don’t know how to do it
It hurts

I don’t like it
Other, specify

9.0 9‘?”

 

196

Interview Questions based on research questions:

1) How do family/social factors facilitate or inhibit the management of diabetes?

 

 

 

 

 

 

Content Interview questions

Structure Who do you consider to be your family?

Family history of Does anyone else in your family have

diabetes diabetes? Or was there someone in your
family who had diabetes?

Relationship with family When you first found out you had diabetes,

who in your family was helpful? Who in
your family didn’t understand? Can you
give me an example? (Prompt- were they
supportive of it? Did they help in your
diabetes management? If so, how?)

To whom do you turn for help or comfort
when you need help with taking care of
your diabetes?

 

197

 

. How do the subjects values and behaviors influence self-care practices of

diabetes?

 

Content

Interview questions

 

Behaviors

1. What has changed for you since you were diagnosed
with diabetes? (diet, exercise, lifestyle)

OR

1. How has having diabetes changed your life? (Prompt
for mainly in terms of eating, sports, fi’iends)

OR

1. How has having diabetes changed things for you?

2.How has having diabetes changed how you act with
friends?

3. What do you do differently now? (i.e. after being
diagnosed with diabetes)

 

Beliefs/values

Who do admire and what do you admire most about
them?

What one quality would you like to have to make you
“cool”?

What are some of the things important to you now and
why?

Tell me one thing you do well about managing diabetes
and Why?

Is it important for you to manage your diabetes? Why?

 

Attitudes
(barriers,
facilitators)

 

 

What do you think is the best way for you to take care
of yourself? Who in your family agree or disagree with
you?

What would you like to do to be healthy?

What keeps you from taking care of yourself?

What helps you in taking care of yourself?

 

198

 

3. How do institutions influence the aspects of diabetes self-care practices?

 

Content

Interview questions

 

Availability of resources
(Physical education,
medical assistance,
dietary education)

Where and from where did you learn how to
take care of yourself?

From what organizations or groups do you get
helpful information?

What’s been the most helpful resource or thing
for you?

 

Barriers/ facilitators

 

 

What do you do on a daily basis to take care of
yourself or your diabetes?

Prompt for: exercise, medical care, diabetes
education school.

What are some of the difficulties in managing
your diabetes?

What are some things that helped you manage
your diabetes?

What do you think the role of diabetes
centers/your doctor should be in helping you
with your diabetes?

 

199

 

APPENDIX E

PHYSICAL ACTIVITY QUESTIONNAIRE

1. During the past week, how many times did you. . ..

a)

b)

(1)

Do hobbies, such as collecting baseball cards, playing a musical instrument,
reading, or doing arts and crafts?
a. 0 — not at all

 

b. l — l or 2 times
c. 2 — 3 or 4 times
(1. 3 — 5 or > times

Duration - minutes

 

 

 

e. 8 — don’t know

 

 

 

 

 

Watch television or videos, or play video games?
i. 0 — not at all
ii. 1 — 1 or 2 times . .
. Duration - minutes
111. 2 — 3 or 4 trmes ——
iv. 3 — 5 or > times
v. 8 — don’t know

 

 

 

 

Go roller-blading, roller-skating, skate-boarding, or bicycling?
i. 0 — not at all
ii' 1 _ 1 or 2 times Duration - minutes
iii. 2 — 3 or 4 times —
iv. 3 - 5 or > times
v. 8 — don’t know

 

 

 

 

 

 

 

 

Play an active sport, such as baseball, softball, basketball, soccer, swimming, or
football?
i. 0 — not at all
ii. 1 — l or 2 times Duration _ minutes
iii. 2 - 3 or 4 times _—
iv. 3 — 5 or > times
v. 8 — don’t know
Exercise, such as jogging, walking, doing karate, jumping rope, doing gymnastics
or dancing?
i. O — not at all
ii' 1 _ 1 or 2 times Duration - minutes
iii. 2 - 3 or 4 times —--—
iv. 3 — 5 or > times
v. 8 — don’t know

200

f) In your 24 — hour day how many hours do you spend sitting or lying down?

 

Include time spent sleeping. Hours
1. Do any of the following keep you fiom exercising as you think you
should?

1=YES 2: NO NA= no applicable

i. Finding the time

i. Finding a good place____

iii. The inconvenience of going someplace and carrying equipment with me

iv. Problems with my health e. g. trouble seeing, heart condition, breathing problems

H:

v. Forgetting
vi. Feeling sick
vii. Its too complicated
viii. Its too painful
ix. Being away from home (shopping, traveling etc.)
x. Changes 1n my routine

xi. The cost
xii. Special occasions (church, weddings, holidays, etc.)
xiii. Bad weather Other

201

 

Appendix F
24-Hour Diet Recall Protocol

I Record everything a person ate in a 24-hr period
I A list of WHAT, HOW, WHEN & WHERE food was consumed

Kind of food

Way it was prepared
How it was served
Portion size

Important to Include...

I Food

I Both meals & snacks
I All beverages (even water)

I Dietary supplements or vitamins & minerals

I Include essentially everything that is eaten from a specific time period the day
before until the same time the next day.

Getting Started
I Break the ice

I Explain WHY the assessment is being done

I Reassure the subject this will be kept confidential

USDA Multiple Pass Method
I Three Main Passes

I Uninterrupted (Client talks): let them speak while you record

I Food Details Probed (Interviewer talks)

I Kind of food/beverage
I Preparation of food
I Portion size
I How served
I Review information with client; you are both talking here. Ask specific
questions based on what they told you they ate.

202

 

e. First Pass

“What was the 1St thing you ate after you got up yesterday?

I AVOID terms like breakfast or lunch
Record only foods at this time; don’t worry about portion sizes until later

Allow extra space for adding things later

Do NOT interrupt

f Second Pass
Your turn to talk

Probe w/ open ended questions (How, What, Describe)
Obtain 4 kinds of info about each food/beverage

KIND OF FOOD/BEVERAGE

I Fresh, frozen, canned

- Skim, 2%, whole

PREPARTION OF FOOD

- Fried or baked

I Ingredients added

PORTION SIZE OF FOOD

I Participant may underestimate so use models or examples
I Make sure EVERY item has some measuring unit

HOW SERVED

I Butter, gravy, or cream added?

If you are not sure about a food, ask the participant to describe it to you

I For example, Joe tells you he has a Gatorade® every morning afier breakfast
I Find out what is Gatorade®. ..

I Is it a drink?

I An energy bar?
Get details (color, ingredients, etc)

I Your mom’s BBQ is not going to be the same as his/her mom’s
Do not forget...

I Condiments

I Beverages

I Alcohol

I “Little bites” of food
Frequently missed foods

203

 

g. Final Pass
I Review the day to them

I Ask the subject to tell you the time of day each food was eaten
I Ask if there are additions or corrections

I Record dietary supplement or vitamins/minerals
I “Do you have a problem with digesting fluid milk?” Yes or No

I “Was this a normal day?” Yes or No

Remember...
I Double check name on each dietary assessment form

I Check for completeness

I Remind them that they will be contacted again after the program

204

24- HOUR RECALL SHEET

 

TIME OF
THE DAY

FOOD
ITEMS

AMOUNT/
PORTION

WHAT WERE
YOU DOING?

WHERE WERE
YOU EATING?

 

 

 

 

 

 

 

Q 1. How many times/week do you eat meals with your family?

Q2. How many times/week do you eat breakfast?

205

 

 

APPENDIX G

University Committee on Research Involving
Human Subjects (UCHRIS)
Approval Letters

206

 

 

OFFICE OF
1531511111011~
mcs AND
mnAnns

ommlttoo on
rch Involving
ran Subjects

:tate University
202 Olds Hall
st Lansing. MI

48824

517/355—2180
31 7/432-4503

iu/user/ucrihs
ihs@msu.edu

rmalii'c-arlion,
nir’y‘ rnslllulmn

MICHIGAN STATE

UNIVERSITY

 

December 18, 2003

TO: Lorraine WEATHERSPOON
334 Trout FSHN Bldg
MSU

RE: IRB# 03-829 CATEGORY: EXPEDITED 2-6. 2-7

APPROVAL DATE: December 16, 2003
EXPIRATION DATE November 16, 2004

TITLE: CHILDREN AND ADOLESCENTS DIAGNOSED, WITH TYPE 2 DIABETES IN
PEDIATRIC AND ADULT ENDOCRINOLOGY CLINICS IN MICHIGAN,
GLYCEMIC CONTROL, AND ASSOCIATED FACTORS

The University Committee on Research Involving Human Subjects‘ (UCRIHS) review of this
project is complete and I am pleased to advise that. the rights and welfare of the human
subjects appear to be adequately protected and methods to obtain informed consent are
appropriate. Therefore, the UCRIHS approved this project.

RENEWALS: UCRIHS approval is valid until the expiration date listed above. Projects
continuing beyond this date must be renewed with the renewal form. A maximum of four such
expedited renewals are possible. Investigators wishing to continue a project beyond that time
need to submit a 5-year application for a complete review.

REVISIONS: UCRIHS must review any changes in procedures involving human subjects, prior
to initiation of the change. if this is done at the time of renewal. please include a revision form
with the renewal. To revise an approved protocol at any other time during the year. send your
written request with an attached revision cover sheet to the UCRIHS Chair. requesting revised
approval and referencing the project's lRB# and title. Include in your request a description of
the change and any revised instruments. consent forms or advertisements that are applicable.
PROBLEMS/CHANGES: Should either or the following arise during the course of the wdrk,
notify UCRIHS promptly: 1) problems (unexpected side effects. complaints. etc.) involving
human subjects or 2) changes in the research environment or new information indicating

greater risk to the human subjects than existed when the protocol was previously reviewed and-

approved. .

If we can be of further assistance. please contact us at (517) 355-2180 or via email:
UCRIHS@msu.edu. Please note that all UCRIHS forms are located on the web:
httpzllwwwhumanresearch.msu.edu

Sincerely,
WK

Peter Vasilenko, Ph.D.

UCRIHS Chair
PV: rt
CC: Deepa Handu
338 GM Trout FSHN Bldg 207

 

 

 

MICHIGAN STATE

U N I V E R SIT Y
January 12, 2004

 

TO: Lorraine WEATHERSPOON
334 Trout FSHN Bldg
MSU

RE: IRB #. 02.042 CATEGORY: 2-5 EXPEDITED

RENEWAL APPROVAL DATE: January 9, 2004
EXPIRATION DATE: December 9. 2004

TITLE' CHILDREN AND ADOLESCENTS DIAGNOSED WITH TYPE 2 DIABETES IN
' PEDIATRIC AND ADULT ENDOCRINOLOGY CLINICS IN MICHIGAN. GLYCEMIC
CONTROL AND ASSOCIATED FACTORS ‘

The University Committee on Research Involving Human Subjects' (UCRIHS) review of this project
is complete and i am pleased to advise that the rights and welfare of the human subjects appear to
be adequately protected and methods to obtain informed consent are appropriate. Therefore. th
UCRIHS APPROVED THIS PROJECT'S RENEWAL. .

This letter also notes approval for the the Waiver of Consent and Waiver of
Authorization.

RENEWALS: UCRIHS approval is valid until the expiration date listed above. Projects continuing
beyond this date must be renewed with the renewal form. A maximum of four such expedited
renewals are possible. Investigators wishing to continue a project beyond that time need to submit a
5-year renewal application for complete review.
REVISIONS: UCRIHS must review any changes in procedures involving human subjects. prior to
initiation of the change. If this is done at the time of renewal, please include a revision form with the
renewal. To revise an approved protocol at any other time during the year, send your written request
with an attached revision cover sheet to the UCRIHS Chair. requesting revised approval and
. ' referencing the project's IRB# and title. Include in your request a description of the change and any
'- - ’ revised instruments. consent forms or advertisements that are applicable.
OFFICE OF PROBLEMSICHANGES: Should either of the following arise during the course of the work, notify

RESEARCH UCRIHS promptly: 1) problems (unexpected side effects, complaints, etc.) involving human subjects
ETHICS AND or 2) changes in the research environment or new information indicating greater risk to the human
STANDARDS subjects than existed when the protocol was previously reviewed and approved.

unity Committee on If we can be of further assistance, please contact us at 517 355-2180 or via email:
Research Involving UCRIHS@msu.edu.

 

Human Subjects
chigan State University Sincerely,
202 Olds Hall
East Lansing. MI W .
48824 M
517/355-2180

FAXr 517/4324503 Peter Vasilenko, Ph.D.

«.msuedu/user/ucrihs UCRIH S Chair
Vlail: ucrihs@msu.edu

PV: rt
208

,1/5 an allumalrvc-atlion,
gr. opportunity IIISIIIUIIOD,

 

 

 

Informed Consent Form -
Participant/Guardian Consent Form

Children and Adolescents Diagnosed. with Type 2 diabetes in Pediatric
and Endocrinology Clinics in Michigan,’Glycemic Control and
Associated Factors.

. Investigators: Lorraine Weatherspoon PhD, RD
‘ (517) 355-8474 ext. 136

. Deepa Honda has .
(517) SSS-8474 ext. 164

Purpose: We invite you to participate in a research project designed to‘ study the unique
experiences and voices of youth with Type 2 diabetes regarding monitoring blood
glucose, exercising regularly, dietary recommendations, food selection and eating

patterns, social support, institutional support and the aspects of daily living that influence
their diabetes self—management practices.

~ Type 2 diabetes mellitus (90-95% of all cases of diagnosed diabetes) has clearly been
identified as a serious epidemic in our society, which can be prevented or ameliorated by
" self-managed lifestyle changes, especially diet and physical activity. Although the '

- AmericanDiabetes Association and other similar organizations have established target ,
behaviors for management of the disease, the traditional medical model has been
unsuccessful 1n effectively facilitating target behaviors. There rs need for research that
includes exploratidn of the individual’s objectives and priorities for diabetes self-

management education and care as they may difl’er from those of the health care team and
- published standards of care. This project will ask you questions about how you deal with
‘diabetes management. Our purpose for this study rs to learn more about your experiences
'. so that we can be more hélpful to families who have youth with the Type 2 diabetes.

Procedure/What you will be asked to do if you participate:

Your voluntary participation in this study will involve one meeting with the researcher
which should take apprbximately 1- 1‘ V2 hours. We will be talking/discussing about
doctor and health professional recommendations that help with blood sugar control and
how easy or difficult it' rs to follow this adviceand why.- The procedures followed are: 1)
you will be asked to participate in an interview with a researcher; and 2) A 24~ hour
dietary recall will be conducted by the researcher

lof3

209

 

 

 

The purpose of this project is to help develop successful intervention for youth with Type
2 diabetes. Your participation in this research project is completely voluntary. You Will
- continue to receive diabetes center services and medical care as you usually do whether
or not you choose to participate in this research. You can refuse to answer any questions
that you do not wish to answer. The interview or discussion will be audio-taped. The "
tape will be used for transcription purposes onlyand will be destroyed following
transcription. Your naine or any identifier will not appear on the transcription and will
-not be associated with the study findings in any 'way. You can withdraw your - .
‘ participation at any time. At the end of theinterview, you will receive a $25 gifi card to
Meijer’s/Best Buy/ Cash‘in appreciation for your participation. If for any reason, you
decide to discontinue with the interview (dropout before it ends) you will only receive a
pedometer in appreciation for your participation.

 

7

RISKS AND BENEFITS: There are no risks or discomforts associated with this
research. You may feel tired during or after the evaluation. Some psychological
‘ discomfort may be experienced from revealing personal information or thinking about
things that are related to you diabetes experiences. Keep in mind that you may take a ,
break at any time and you can refuse to answer any questions that make you
. uncomfortable. There are no implied benefits for the participants in this study. However,
-. the results from this study may be beneficial to youth who have Type 2diabetes mellitus.
and their families in the future. Ifdesired, you may learn of the study results by asking
the investigators that the results be available to you when the study is completed L-

 

Confidentiality:

During and aflerthisresearch, yourprivacywillbeprotectedtothe maximum extentof
the law. All information that refers to‘you, or can be identified with you will remain

, confidential to the maximum extent permitted by law. Ifyou choose to sign this consent
form, you are also giving consent to have the interview audio-taped, so that the .
-_mearchers have complete and correct information from the interview. You may request
atanytimetohavethetapingstoppedandyoucanrefusetobetapedatall. Alldata,
including audio-tapes, will be kept for three years and then destroyed. .

- Other than this form, all data twill be identified only with a code number. A list linking

your name to the code will be kept in a locked file for the duration of the study. Once all

.the data are collected and analyzed, the list linking the names to the code numberswill be
destroyed. . '

’ZWho to contact for answers: lfthere are any questions you have at any time about
this research project or your participation in it, please contact one of the investigators: .

Lorraine Weatherspoon, PhD, RD‘ OR . Deepa Handu, MS 7 i r

334 A GM Trout FSHN Bldg. 301 GM Trout FSHN Bldg.

20f3

210

Michigan State‘University ‘ ' Michigan State University
East Lansing, MI 48824 , , . East Lansing, MI 48824

. Ifyou have questions or concerns regarding your rights as a study participant, or are
dissatisfied at any time with any aspect of this study, youmay contact (anonymously, if
you wish)- Ashir Kumar, M. D., Chair of the University Committee on Research
‘ Involving Human Subjects (UCRIHS) by phone: (517) 355-2580, fax: (517) 432-4503,
email: UQBLES @mUEDU, or regular mail: 202 Olds Hall, Michigan State
University, East Lansing, MI 48824.

Your participation in this project is voluntary: Your participation in this study
, is voluntary. Ifyou wish, you may decline to participate, simply by telling the project
investigator. If you decide to participate 1n this study, and later decide that you do not
wish to continue, you may at any time withdraw your consent and stop participation. You
decision not to participate, or to participate and later withdraw from the study will not in

. < any way result' m a penalty to you, or a loss of benefits to which you are otherwise
entitled , V

\
Your signature below indicates your voluntary agreement to participate in this

 

 

 

 

study.

Print Name of the Subject:

Signature of Parent or Legal Guardian ‘ Date
[Signature of the Research Participarh ‘ I Date .
_ Signature of the Person obtaining consent ’ . . . Date

UCRIHS APPROVAL FOR
mus moor minus:
nov‘ ‘1 s 2004“

30f3

211

 

REFERENCES

212

 

REFERENCES

Alberti G, Zimmet P, Shaw J, Bloomgarden Z, Kaufman F, and Silink M. Type 2
Diabetes in the Young: The Evolving Epidemic: The International Diabetes
Federation Consensus Workshop 2004; 27(7): 1798-1811

Alleyene SI, Morrison EY St. A, and Richards RR. Some social factors related to control
of diabetes mellitus in adult Jamaican patients. Diabetes Care 1979; 2: 401-408.

Amatruda JM (1987). The treatment of non-insulin-dependent diabetes mellitus: A
pathophysiological approach. In Bergman M (ed.), Principles of Diabetes
Mellitus. NY: Medical Examination Publishing Co.

American Association of Diabetes Educators. (2002). Position Statement- Standards for
outcome measurements of Diabetes Self-Management Education (DSME).

American Association of Diabetes Educators. Individualization of Diabetes Self-
Management Education. Diabetes Educator 2002; 28(5): 741-749.

American Association of Diabetes Educators. Individualization of Diabetes Self-
Management Education. Diabetes Educator 2002; 28(5): 741 -749.

American Diabetes Association. Diabetes Care at Diabetes Camps. Diabetes Care 2004;
27:8129-8131.

American Diabetes Association (ADA). Management of dyslipidemia in adults with
diabetes (Position Statement). Diabetes Care 2001; 24(suppl. 1): SSS—S61.

American Diabetes Association (ADA) consensus Statement: Type 2 diabetes in children
and adolescents. Diabetes Care 2000; 22(12): 381-3 89.

American Diabetes Association (ADA). Clinical Practice Recommendations 1999.
Diabetes Care 1999; 22 (suppl. 1): Sl-Sl 14.

American Diabetes Association (ADA): Nutrition recommendations and principles for
peOple with diabetes mellitus (position statement). Diabetes Care 1994; 17: 519-
522.

American Diabetes Association (ADA)’s special report: principles of nutrition and
dietary recommendations for individuals with diabetes mellitus 1971, 1979 &
1987.

American Diabetes Association Clinical Practice Recommendations. Diabetes Care
2000; 23(suppl 1): 832-860.

213

American Diabetes Education. Available at: http://diabetes.oLg. Accessed October 2004.

Anderson RM, Barr PA, Edwards GJ, Funnell MM, Fitzerald J T, and Wisdom K. Using
focus groups to identify psychological issues in urban black individuals with
diabetes. Diabetes Education 1996; 22: 28-33

Anderson RM, Freedland KE, Clouse RE, and Lustrnan PJ. The prevalence of comorbid
depression in adults with diabetes: A meta-analysis. Diabetes Care 2001; 24:
1069-1078.

Anderson BJ, Miller JP, Auslander WP, and Santiago JV. Family characteristics of
diabetic adolescents: relationship to metabolic control. Diabetes Care 1981; 4(6):
586-594.

Anderson DK, and Svardsudd K. Long-term glycemic control relates to mortality in type
II diabetes. Diabetes Care 1995; 18(12): 1534-1543.

Anderson RM. Qualitative research in diabetes: The role of stories in the culture of
science. Diabetes Educator 2001; 27(6): 798-808.

Arslanian SA, Saad R, Lewy V, Danadian K, and Janosky J. Hyperinsulinemia in
African-American children: decreased insulin clearance and increased insulin
secretion and its relationship to insulin sensitivity. Diabetes 2002; 51(10): 3014-
3019.

Arslanian SA. Type 2 diabetes mellitus in children: pathophysiology and risk factors.
J ournal of Pediatric Endocrinology Metabolism 2000; 13(Suppl 6): 1358-1394.

Bantle JP, Swanson J E, Thomas W, and Laine DC: Metabolic effects of dietary sucrose
in type 11 diabetic subjects. Diabetes Care 1993; 16: 1301—1305.

Bantle JP. The dietary treatment of diabetes mellitus. Medicine Clinics North American
1988; 72(6): 128512-99.

Basa RP, and McLeod B: Evaluation of diabetes specialty center: Structure, process and
outcome. Patient Education Counseling 1995. 25:23-29.

Bearman KJ, and La Greca AM. Assessing fiiend support of adolescents’ diabetes care:
The diabetes social support questionnaire-friends version. Journal of Pediatric
Psychology 2002; 27(5): 417-428.

Bell RA, Summerson JH, and Konen J C. Dietary intakes by levels of glycemic control
for black and white adults with non-insulin dependent diabetes mellitus
(NIDDM). Journal of American College of Nutrition 1995; 14: 144-154.

214

Bell RA, Summerson J H, and Konen J C. Racial differences in psychological variables
among adults with non-insulin-dependent diabetes mellitus. Behavior Medicine
1995; 21: 69-73.

Blanc MH, Barnett DM, Gleason RE, Dunn PJ, and Soeldner J S. GHB compared with
three conventional measures of diabetes control. Diabetes Care 1981, 4: 349-353.

Blood Pressure Tables for Children and Adolescents. Fourth Report on the diagnosis,
evaluation, and treatment of high blood pressure in children and adolescents,
2004; http://www.nhlbi.nih.gov/guidelines/hypertension/chi1d tbl.htm

Bloomgarden Z, Karmally W, Metzger M, Brothers M, Nechemias C, Bookman J,
Faierman D, Ginsberg-Fellner F, Rayfield E, and Brown W: Randomized,
controlled trial of diabetic patient education: improved knowledge without
improved metabolic status. Diabetes Care 1987; 10: 263—272.

Bogardus C, Lillioja S, Mott DM, Hollenbeck C, and Reaven G. Relationship between
degree of obesity and in vivo insulin action in man. American Journal of
Physiology 1985; 248: E286-E291.

Bolanos E, and Sarria-Santamera A. Perspective of patients on Type 2 diabetes and their
relationship with primary care health professionals: a qualitative study. Ham's
MI. Summary. In: National Diabetes data Group, ed. Diabetes in America, 2"d
edition. NIH Publications No. 95-1468, 1995: 1-13

Bolanos E, and San'ia-Santamera A. Perspective of patients on Type 2 diabetes and their
relationship with primary care health professionals: a qualitative study. Harris
MI. Summary. In: National Diabetes data Group, ed. Diabetes in America, 2nd
edition. NIH Publications No. 95-1468, 1995: 1-13.

Boule NG, Haddad E, Kenny GP, Wells GA, and Sigal RJ. Effects of exercise on
glycemic control and body mass in Type 2 diabetes mellitus: A meta analysis of
controlled clinical trials. Journal of American Medical Association 2001;
286(10): 1218-1227.

Boyle RG, O’Connor PJ, Pronk NP, et al. Stages of change in physical activity, diet, and
smoking among HMO members with chronic conditions. American Journal of
Health Promotion 1998; 12: 170-5.

Brand J C, Colagiuri S, Crossman S, Allen A, and Roberts DCK, Truswell AS: Low
glycemic index food improve long-term glycemic control in NIDDM. Diabetes
Care 1991; 14: 95—101.

Brener ND, Burstein GR, Dushaw ML, Vernon MF, Wheeler L, and Robinson J. Health

services: Results from school health policies and programs study 2000. Journal of
School Health 2001; 71: 294-304.

215

 

 

Bronfenbrenner U, and Ceci S. Nature-nurture reconceptualized in developmental
perspective: A bioecological model. Psychological Review 1994; 101: 568-586.

Bronfenbrenner U. Ecological systems theory. Annals of Child Development 1989; 6:
1 87-249.

Bronfenbrenner U. (1999). Environments in developmental perspective: Theoretical and
operational models. In S.L. Friedman, & T.D. Wachs (Eds), Measuring
environments across the life sp__an: Emerging methods and concepts. (pp. 3-28).
Washington, DC: American Psychological Association.

Bubolz MM, and Sontag MS. (1993). Human ecology theory. In P.G. Boss, W.J.
Doherty, T LaRossa, WR Schumm, SK Steinmetz (Eds.), Sourcebook of family
theories and methods: A contextual approach. (pp. 419-448). New York: Plenum
Press.

Byers T, Mestle M, McTieman, Doyle C, Currie-Williarns A, Gansler T, and Thun
Michael. American Cancer society Guidelines on Nutrition and Physical Activity
for Cancer Prevention. Cancer Journal for Clinicians 2002; 52: 92-119.

Callahan ST, and Mansfield J. Type 2 diabetes mellitus in adolescents. Curr Opinion
Pediatr 2000; 12: 310-315.

Campaigne BN, Morrison J A, Schumann BC, et al. Indexes of obesity and comparisons
with previous national survey data in 9 and 10-year old black and white girls: The
National Heart, Lung, and Blood Institute Growth and Health Study. Journal of
Pediatrics 1994; 124: 675-680.

Campbell E, Redman S, Moffrtt P, and Sanson-Fisher R: The relative effectiveness of
educational and behavioral instruction programs for patients with NIDDM: A
randomized trial. Diabetes Educator 1996; 22: 379—386.

Center for Disease Control and Prevention (CDC). (2004). National Diabetes Fact
Sheet. http://www.cdc.gov/diabetes/pubs/general.htrn

Center for Disease Control and Prevention (CDC). (2003). National Surveys.
http://www.cdc.gov

Center for Disease Control and Prevention (CDC). (2002). National Diabetes Fact
Sheet. http://www.cdc.gov/diabetes/pubs/general.htm

Center for Disease Control and Prevention (CDC). (2002). Prevalence of Overweight

Among Children and Adolescents: United States, 1999.
http://www.cdcgv/nchs/products/pubs/pubd/hestats/overwght99.htm

216

Center for Disease Control and Prevention (CDC). (2002). Initial results from the 1999
National Health and Nutrition Examination Survey (NHANES), using measured
heights and weights, indicate that an estimated 13 percent of children ages 6-11
years and 14 percent of adolescents ages 12-19 years are overweight.

Centers for Disease Control and Prevention (CDC). Strategies for reducing morbidity
and mortality from diabetes through health-care system interventions and diabetes
self-management education in community settings. A report on recommendations
of the Task Force on Community Preventive Services. Morbidity and Mortality
Weekly Report Recommendations and Reports 2001; 28: l-15.

Center for Disease Control and Prevention. (1998). The National Diabetes Education
Program, http://www.cdc.gov/nccdphp/ddt/prois/ndepfs.htm .

Cerreto MC, and Travis LB. Implications of psychological and family factors in the
treatment of diabetes. Pediatric Clinics of North America 1984; 31(3): 689-710.

Chandalia M, Garg A, Luthohann D, von Bergrnann K, Grundy SM, and Brinkley LJ.
Beneficial effects of a high dietary fiber intake in patients with Type 2 diabetes.
New England Journal of Medicine 2000; 342: 1392—1398.

Chipkin ST, and De Groot M. Contextual variables influencing outcome measures in
minority populations with diabetes mellitus. Diabetes Spectrum 1998; 11: 149-
160.

Cicinelli-Timm D and Dense S. Personal communication. Registered dietitian and
Registered Nurse, Covenant Health System 2002, Saginaw.

Clark CA, Zabrecky GP, and Henry DN. Type 2 diabetes in children and adolescents. A
report by Michigan State University and The Marcus Foundation, Atlanta,
Georgia. 2001.

Clayton BJ, Goodwin DK, and Kendrick O. Nursing, food service, and the child with
diabetes. Journal of School Nursing 2002; 18: 1501-1516.

Cook S, Weitzman M, Auinger P, Nguyen M, and Dietz W. Prevalence of a Metabolic
Syndrome Phenotype in Adolescents. Archives of Pediatric Adolescent Medicine
2003; 157: 821-827.

Court J M. Outpatient-based transition services for youth. Pediatrician 1991; 18:150-156.

Cruz ML, Weigensberg MJ, Huang TT, Ball G, Shaibi GO, and Goran MI. The

metabolic syndrome in overweight Hispanic youth and the role of insulin
sensitivity. Journal of Clinical Endocrinol Metabolism 2004; 89(1): 108-113.

217

Dabelea D, Hanson RL, Bennett PH, Roumain J, Knowler WC, Pettitt DJ. Increasing
prevalence of Type 2 diabetes in American Indian children. Diabetologia 1998;
41: 904-910.

Dabelea D, Pettitt DJ, Jones KL, Arslanian SA. Type 2 diabetes in minority children and
adolescents. An emerging problem. Endocrinology Metabolism Clinicals of
North America 1999; 28: 709-729.

Danadian K, Balasekaran G, Lewy V, Meza MP, Robertson R, and Arslanian SA. Insulin
sensitivity in African-American children with and without family history of type 2
diabetes. Diabetes Care 1999; 22(8): 1325-9.

Daniel J. Research consultant. Health Needs Assessment Survey of Senior Citizens
Living in Washington, DC. Washington DC: District of Columbia Office on
Aging 1986.

Daniel M, Rowley KG, McDermott R, Mylvaganam A, and O’Dea K. Diabetes
incidence in an Australian aboriginal population. An 8-year follow-up study.
Diabetes Care 1999; 22(12): 1993-8.

Dean AG, Amer TG, Sunki GG, Friedman R, Lantinga M, Sangam S, Zubieta J C,
Sullivan KM, Brendel KA, Gao Z, F ontaine N, Shu M, and Fuller G. Epi Info, a
database and statistics program for public health professionals. Centers for
Disease Control and Prevention 2002, Atlanta: Georgia.

Dean H. NIDDM-Y in First Nation children in Canada. Clinical Pediatrics 1998, 39: 89-
96.

Dean HE, Mundy RLL, and Moffatt M. Non-insulin-dependent diabetes mellitus in
Indian children in Manitoba. Canadian Medical Association Journal 1992, 147:
52-57.

Delahanaty LM, and Halford BN: The role of diet behaviors in achieving improved
glycemic control in intensively treated patients in the diabetes Control and
Complications Trail. Diabetes Care 1993; 16: 1453-1458.

Diabetes Control and Complications Trial Research group. The effect of intensive
treatment of diabetes on the development and progression of long-term
complications in insulin-dependent diabetes mellitus. New England Journal of
Medicine 1993; 329: 977-1036.

Diabetes Control and Complications Trial Research group. The effect of intensive
treatment of diabetes on the development and progression of long-term
complications in insulin-dependent diabetes mellitus. New England Journal of
Medicine 1993; 329: 977-1036.

218

Diabetes Prevention Program Research Group. Reduction in the incidence of Type 2
diabetes with lifestyle intervention or metformin. The New England Journal of
Medicine 2002; 346(6): 393-403.

Drobac S, Brickman W, Smith T, and Binns H. Evaluation of a Type 2 diabetes
screening protocol in an Urban Pediatric Clinic. Pediatrics 2004; 114: 141-148.

Edelstein SL, Knowler WC, Bain RP, Andres R, Barrett-Connor EL, Dowse GK, Haffner
SM, Pettitt DJ, Sorkin JD, Muller DC, Collins VR, and Hamman RF: Predictors
of progression from impaired glucose tolerance to NIDDM: an analysis of six
prospective studies. Diabetes 1997; 46: 701—710.

El-Kebbi IM, Bacha GA, Ziemer DC, Musey VC, Gallina DL, Dunbar V, and Phillips
LS. Diabetes in urban Afiican Americans: Use of discussion groups to identify

baniers to dietary therapy among low-income individuals with non-insulin-
dependent diabetes mellitus. Diabetes Educator 1996; 22:488-492.

El-Kebbi IM, Bacha GA, Ziemer DC, Musey VC, Gallina DL, Dunbar V, and Phillips
LS. Diabetes in urban Afiican-American. Use of discussion groups to identify
baniers to dietary therapy among low-income individuals with non-insulin-
dependent diabetic mellitus. Diabetes Education 1996; 22: 488-492.

Ellison GC, and Rayman KM. Exemplars’ experience of self-managing Type 2 diabetes.
Diabetes Educator 1998; 24: 325-330.

Epstein J T, and Stewart AJ. (1991). Quantitative or qualitative methods in the social
sciences: Current feminist issues and practical strategies. In M.M. Fonow & J .A.
Cook (Eds), Beyond Methodology: Feminist scholarship as lived research (pp. 85-
106). Bloomington, In: Indiana University Press.

Eriksson KF, and Lindgarde F. Prevention of Type 2(non-insulin dependent) diabetes
mellitus by diet and physical exercise: The 6-year Malmo feasibility study.
Diabetologia 1991; 34: 891—898.

Evert A. Childhood obesity and the emerging epidemic of Type 2 diabetes in youth.
Diabetes Educator 2002;

F agot-Campagna A, Narayan KM, and Irnperatore G. Type 2 diabetes in children.
British Medical Journal 2001; Feb 17; 322(7283): 377-8.

Fagot-Campagna A, Saaddine JB, F legal KM, and Beckles GL. Diabetes, impaired
fasting glucose, and elevated HbAlc in US. adolescents: the Third National
Health and Nutrition Examination Survey. Diabetes Care 2001; 24(5): 834-7.

Fagot-Campagna A, Pettitt DJ, Engelgau MM, Burrows NR, Geiss LS, Valdez R,
Beckles GL, Saaddine J, Gregg EW, Williamson DF, and Narayan KM. Type 2

219

diabetes among North American children and adolescents: an epidemiologic
review and a public health perspective. Journal of Pediatrics 2000; 136(5): 664-
672.

Fagot-Campagna A. Type 2 diabetes Mellitus Among North American Children and
Adolescents: Conducted by the Divison of Diabetes Translation. Centers for
Disease Control and Prevention. American Academy of Pediatrics. Section on
Endocrinology, Summer 1999 Newsletter, Vol.6.

F agot-Campagna A, Knowler WC, and Pettitt DJ. Type 2 diabetes in Pima Indian
children: cardiovascular risk factors at diagnosis and 10 years later. Diabetes
1998; 47(suppll): A605.

Falkner B, Hassink S, Ross J, and Gidding S. Dysmetabolic syndrome: multiple risk
factors for premature adult disease in an adolescent girl. Pediatrics 2002; 110(1
Pt 1): e14.

Ferguson MA, Gutin B, Le N-A, Karp W, Litaker M, Humphries M, Okuyama T, Riggs
S, Owens S: Effects of exercise training and its cessation on components of the
insulin resistance syndrome in obese children. Int J Obes Relat Metab Disord
1999; 23:889—895.

F etterrnan DM. (1989). Ethnography Step by Step. Newbury Park, CA: Sage.

Fitzgerald J T, Anderson RM, Funnell MM, Arnold MS, Davis WK, Amam LC, J acober
SJ, and Grunberger G. Differences in the impact of dietary restrictions of Afiican
American and Caucasians with NIDDM. Diabetes Educator 1997; 23: 41-47.

First DataBank. (1999). Nutritionist V. Dietary Data Analysis Tool.

F legal KM, Ogden CL, Wei R, kuczmarski R], Campbell SM, Johnson CL. Prevalence of
overweight in US children: comparison of US growth charts from the Centers for
Disease control and Prevention with other reference values for body mass index.
American Journal of Clinical Nutrition 2001; 73(6): 1086-93.

Fleiss J L. Statistical Methods for Rates and Proportions. 2nd edition. New York, NY:
John Wiley and Sons Inc; 1981: 112-136.

Food and Nutrition Board, National Research Council (1989): Recommended Dietary
Allowances, 10th ed, Washington, DC: National Academy Press, 285.

Ford ES, Giles WH, and Dietz WH. Prevalence of the metabolic syndrome among US

adults: findings from the third National Health and Nutrition Examination Survey.
Journal of American Medical Association 2002; 287(3): 356-359.

220

Ford ES, Williamson DF, and Liu S. Weight change and diabetes incidence: findings
fi'om a national cohort of US adults. American Journal of Epidemiology 1997;
146(3): 214-222.

Franz MJ, Bantle JP, Beebe CA, and Brunzell, JD. Evidence-based nutrition principles
and recommendations for the treatment of diabetes and related complications.
Diabetes Care 2002; 25(1): 148-198.

Franz MJ, Horton ES, Bantle JP, Beebe CA, Brunzell JD, Coulston AM, Henry AR,
Hoogwerf BJ, and Stacpoole PW: Nutrition principles for the management of
diabetes and related complications. Diabetes Care 1994; 17: 490-518.

Franz MJ, Splett PL, Monk A, Barry B, McLain K, Weaver T, Upham P, Bergenstal R,
and Mazze RS: Cost effectiveness of medical nutrition therapy provided by
dietitians for persons with non-insulin dependent diabetes mellitus. J Am Diet
assoc 95:1018-1024, 1995.

Franz MJ, Bantle JP, Beebe CA, Brunzell JD, et al. Nutrition Principles and
Recommendations in Diabetes. Diabetes Care 2004; 27: S36

Franz MJ, Bantle JP, Beebe CA, Brunzell JD, et al. Nutrition Principles and
Recommendations in Diabetes. Diabetes Care 2004; 27: S36-S46.

Freedman DS, Serdula MK, Schechtrnan KB, Ehsani AA, and Kohrt WM. Relation of
circumferences and skinfold thickness to lipid and insulin concentrations in
children and adolescents: The Bogalusa Heart Study. American J oumal of
Clinical Nutrition 1999; 69: 308-317.

Gabbay KH, Hasty K, Breslow JL, Ellison BC, Bunn HF, and Gallop PM. Glycosylated
hemoglobins and long-term blood glucose control in diabetes mellitus. Journal of
Clinical Endocrinology and metabolism 1977 ; 44: 859-864.

Gabbay KH. Glycosylated hemoglobin and diabetes mellitus. Medical Clinics of North
America 1982; 66: 1309-1314.

Galloway JA, Potvin J H, and Shuman CR. (1988). Eds Diabetes Mellitus. 9th eds.
Indianapolis, IN: Lilly corporate Center, 167-173.

Gauthier BM, Hickner J M, and Noel MM. High prevalence of overweight children in
Michigan primary care practices. An UPRNet study. Upper Peninsula Research
Network. Journal of Family Practice 2000, 49(1): 73-76.

Gilliland SS, Carter J S, Perez GE, Feathers J, Kenui CK, and Mau MK.
Recommendations for development and adaptation of culturally competent
community health interventions in minority populations with Type 2 diabetes
mellitus. Diabetes Spectrum 1998; 11: 166-174.

221

Glaser NS, and Jones KL: Non-insulin-dependent diabetes mellitus in Mexican-
American children. West J Medicine 1998; 168(I): 11.

Glaser NS. Non-insulin-dependent diabetes mellitus in childhood and adolescence.
Pediatr Clinics North American. 1997 ; 44(2): 307-37.

Glasgow RE, Toobert DJ, Riddle M et al. Diabetes-specific social learning variables and
self-care behaviors among persons with Type2 diabetes. Health Psychology
1989; 8: 285-303.

Goran MI, Bergman RN, Cruz ML, and Watanabe R. Insulin resistance and associated
compensatory responses in African-American and Hispanic children. Diabetes
Care 2002; 25(12): 2184-90.

Gormanous M, Hunt A, Pope J, and Gerald B. Lack of knowledge of diabetes among
Arkansas public elementary teachers: Implication for dieticians. Journal of
American Dietitic Association 2002; 102: 1136-1139.

Gortrnaker SL, Dietz WH, Sobol AM, and Weber CA. Increasing pediatric obesity in the
United States. Archives of Pediatric Adolescent Medicine 1987; 141: 535-540.

Greenhalgh S. Improving school teachers’ knowledge of diabetes. Professional Nurse,
1997;13:150-156

Groop LC, and Tuomi T. Non-insulin dependent diabetes mellitus-a collision between
the thrifty gene and an affluent society. Ann Medicine 1997; 2937—2953

Gu K, Cowie CC, and Harris MI. Mortality in adults with and without diabetes in a
national cohort of the US. population, 1971-1993. Diabetes Care 1998; 21 :1 138-
45.

Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, and Flegal KM.
Prevalence of overweight and obesity among US children, adolescents, and
adults, 1999-2002. Journal of American Medical Association. 2004;91(23): 2847-
50.

Hale DE, and Danney KM. Non-insulin dependent diabetes in Hispanic youth (Type
2Y). Diabetes 1998; 47(suppl 1): A82.

Hale DE. Type 2 diabetes: An increasing pediatric problem. Family Practice
Recertification 2000; 22: 25-3 8.

Hampson SE, Glasfow RE, and Toobert DJ. Personal models of diabetes and their
relations to self-care activities. Health Psychology 1990; 9: 632-646.

222

Hansen BC. Dietary considerations for obese diabetic subjects. Diabetes Care 1988; 11:
1 83-1 88.

Harris MI, Flegal KM, Cowie CC, Eberhardt MS, Goldstein DE, Little RR, Wiedmeyer
H, and Byrd-Holt DD. Prevalence of diabetes, impaired fasting glucose, and

impaired glucose tolerance in US. adults (The third national health and nutrition
examination survey, 1988-1994). Diabetes Care 1998; 21(4): 518-524.

Harris SB, Perkins BA, and Whalen-Brough E. Non Insulin Dependent diabetes mellitus
among First Nations Children. New entity among First Nations people of north
western Ontario. Canadian Family Physician 1996; 42: 869-876.

Hartz AJ, Rupley DC, Kalkhoff RD, and Rim AA. Relationship of obesity to diabetes:
influence of obesity level and body fat distribution. Preventive medicine 1983;
12: 35 1-357.

Hasler T, Fisher M, Maclnytre P, and Mutrie N. Exercise consultation and physical
activity in patients with type 1 diabetes. Pract diabetes Int 2000; 17: 44-48.

Hawthorne K, and Tomlinson S: One-to-one teaching with pictures: flashcard health
education for British Asians with diabetes. Br J Gen Pract 1997; 47: 301—304.

Hayes-Bohn R, Neumark-Sztainer D, Melin A, and Patterson J. Adolescent and diabetes
mellitus management at school. Journal of School Health 2004; 74(5): 166-169.

Heather D. Diagnostic criteria for non-insulin dependent diabetes in youth (NIDDM-Y).
Clinical Pediatrics 1998; 37 : 67-72.

Hegsted DM, Ausman LM, Johnson JA, and Dallal GE: Dietary fat and serum lipids: an
evaluation of the experimental data. [Published erratum appears in American
Journal of Clinical Nutrition. 58:245, 1993]. American Journal Clinical Nutrition
1993; 57: 875—883.

Heilbronn L, Noakes M, and Clifton P: Effect of energy restriction, weight loss, and diet
composition on plasma lipids and glucose in patients with Type 2 diabetes.
Diabetes Care 1999; 22: 889—895.

Heisler M, Bouknight RP, Hayward RA, Smith DM, Kerr EA. The Relative Importance
of Physician Communication, Participatory Decision Making, and Patient
Understanding in Diabetes Self-management. Journal of General Internal
Medicine 2002; 17(4): 243.

Heller S, Clarke P, Daly H, Davis I, McCulloch D, Allison S, and Tattersal R: Group

education for obese patients with type 2 diabetes: greater success at less cost.
Diabetes Medicine 1988; 5:552—556.

223

Henry D. 2001. Personal Communication. Pediatric Endocrinologists, Michigan State
University.

Henry D. (1998). Non-Type 1 diabetes in youth, In Mediguide to Diabetes, Whitehouse,
F.(ed.) 5(2):l-5, New York: Lawrence DellaCorte Publications, Inc.

Henry RR, Scheaffer L, and Olefsky JM. Glycemic effects of intensive caloric restriction
and isocaloric refeeding in non-insulin dependent diabetes mellitus. J oumal of
Clinical Endocrinology and Metabolism 1985; 61: 917-925.

Heymsfield SB, Segal KR, Hauptrnan J, Lucas CP, Boldrin MN, Rissanen A, Wilding JP,
and Sjostrom L: Effects of weight loss with Orlistat on glucose tolerance and
progression to Type 2 diabetes in obese adults. Archives of Intern Medicine

2000; 160: 1321—1326.

Hillier TA, and Pedula KL. Complications in young adults with early-onset type 2
diabetes: Losing the relative protection of youth. Diabetes Care 2003; 26(11):
2999.

Holmes V, and Griffiths P. Self-monitoring of glucose levels for people with type 2
diabetes. Br J Community Nurs 2002; 7(1): 41-46.

Hulka BS, Cassel J C, Kupper LL, and Burdette J A. Communication compliance and
concordance between physicians and patients with prescribed medications.
American Journal of Public Health 1976; 66: 847-853.

Hunt LM, Pugh J A, and Valenzuela MA. How patients adapt diabetes self-care
recommendation in everyday life. Journal of Family Practice 1998; 46: 207-250.

Institute of Medicine Food and Nutrition Board (1997). Dietary Reference Intakes for
Calcium, Phosphorus, Magnesium, Vitamin D, and Fluoride. Washington, DC,
National Academy Press.

Institute of Medicine Food and Nutrition Board. (1998). Dietary Reference Intakes for
Thiamine, Riboflavin, Niacin, Vitamin B5, Folate, Vitamin B12, Pantothenic Acid,
Biotin, and Choline. Washington, DC, National Academy Press.

Institute of Medicine Food and Nutrition Board. (2000). Dietary Reference Intakes for
Vitamin C, Vitamin E, Selenium, and Carotenoids. Washington, DC, National
Academy Press.

Institute of Medicine Food and Nutrition Board. (2001). Dietary Reference Intakes for
Vitamin A, Vitamin K, Arsenic, Boron, Chromium, Copper, Iodine, Iron,
Manganese, Molybdenum, Nickel, Silicon, Vanadium, and Zinc. Washington,
DC, National Academy Press.

224

Irvine AA, Saunders JT, Blank MB, and Carter WR. Validation of scale measuring
environmental barriers to diabetes regimen adherence. Diabetes Care, 1990; 13:
705-711.

Jenkins DJ, Leeds AR, Gassull MA, Wolever TMS, Goff DV, Alberti KGMM, and
Hockaday TDR. Unabsorbable carbohydrates and diabetes: Decreased
postprandial hyperglycemia. Lancet 1976; ii: 172—174.

Jenkins DJ, Wolever TM, Taylor RH, Barker H, Fielden H, Baldwin JM, Bowling AC,
Newman HC, Jenkins AL, and Goff DV. Glycemic index of foods: a
physiological basis for carbohydrate exchange. American J oumal of Clinical
Nutrition 1981; 34: 362—366.

J ewler D. Diabetes costs: up, up and away. Diabetes Forecast 1988; 41: 23-26.

J ick TD. Mixing qualitative and quantitative methods: Triangulation in action.
Administrative science quarterly, 1979; 24: 602-610.

Johnson DW, and Johnson RT. Nutrition Education: a model for effectiveness, a
synthesis of research. J Nutr Educ 1985; 17(Suppl): Sl-S44.

Jones KL. Non-insulin dependent diabetes in children and adolescents: the therapeutic
challenge. Clinical Pediatrics 1998; 37: 103-110.

Jones L (1998). Wisconsin nutrition education program annual report: 1998, Madison,
WI: University of Wisconsin cooperative extension service.

Kabedi VM. Nutritional therapy in diabetes: rationale and recommendations.
Postgraduate Medicine 1996; 79: 145-156.

Kadiki OA, Reddy MR, and Marzouk AA. Incidence of insulin-dependent diabetes
(IDDM) and non-insulin-dependent diabetes (NIDDM) (0-34 years at onset) in
Benghazi, Libya. Diabetes Research Clinical Pract 1996; 32: 165-173.

Keith SE, and Doyle EI. Using PRECEDE/PROCEED to address diabetes within the
Choctaw Nation of Oklahoma. American Journal of Health Behavior 1998; 22:
358-67.

Kenny SJ, Aubert RE, and Geiss LS. Prevalence and incidence of non-insulin dependent
diabetes mellitus. In: Harris MI, ed. Diabetes in America. Washington, DC: US
Government Printing Office 1995; 37-46.

King PZH, and Kirk SSR. The Tsuji memorial Lecture: Prevention and control of type 2
diabetes — dream or reality. Australia Academy Press 1984; 219-35.

225

Kitagawa T, Owada M, Urakarni T, and Tajima N. Epidemiology of Type 1 (insulin-
dependent) and Type 2(non-insulin-dependent) diabetes mellitus in Japanese
children. Diabetes Research and Clinical Practice 1994, 24(suppl.): S7-Sl3.

Kitagawa T, Owada M, Urakarni T, and Yamauchi K. Increased incidence of non-insulin
dependent diabetes mellitus among Japanese school children correlates with an
increased intake of annual protein and fat. Clinical Pediatrics 1998; 37: 111-115.

Knowles HC Jr. Diabetes mellitus in childhood and adolescence. Medicine Clinics
North America 1971; 55: 975-987.

Korhonen T, Huttunen J, Aro A, Hentinen M, lhalainen O, Maj ander H, Siitonen O,
Uusitupa M, and Pyorala K: A controlled trial on the effects of patient education
in the treatment of insulin-dependent diabetes. Diabetes Care 1983; 6: 256—261.

Krosnick A, and Shelmet J J . The management of non-insulin dependent diabetes
mellitus. Clinical Therapeutics 1988; 10:146-157.

Kuczmarski RJ, Fegal KM, Campbell SM, and Johnson CL. Increasing prevalence of
overweight among US. adults. J oumal of the American Medical Association
1994, 272: 205-1 1.

La Greca AM, and Bearman KJ. The diabetes social support questionnaire-farnily
version: Evaluating adolescent’s diabetes-specific support from family members.
Journal of Pediatric Psychology 2002; 27(8): 665-676.

La Greca AM, Auslander EF, Greco P, Spetter D, Fisher EB, and Santiago JV. I get by
with a little help from my family and friends: Adolescents’ support for diabetes
care. Journal of Pediatric Psychology 1995; 20: 449-476.

LeCompte, MD, and Preissle, J. (1993). Ethnoggphv and Qualitative Deggn in
Educational Research (2nd ed.). San Diego: Academic.

Lenzi S, Giampietro O, Giovanetti G, Sarnpietro T, Miccoli R, and Navalesi R. The
clinical usefulness of glycated hemoglobin in monitoring diabetes mellitus: A
long term study. Clinical Chemistry 1987, 33: 55-56.

Levy-Marchal C, Papoz L, De Beaufort C, Doutreix J, Froment V, Voirin J, Czernichow
P. Clinical and laboratory features of Type 1 diabetic children at the time of
diagnosis. Diabet Medicine 1992; 9: 279-284.

Likitrnaskul S, Kiattisathavee P, Chaichanwatanakul K, Punnakanta L, Angsusingha K,
and Tuchinda C. Increasing prevalence of type 2 diabetes mellitus in Thai
children and adolescents associated with increasing prevalence of obesity. J

Pediatr Endocrinol Metab. 2003; 16(1): 71-7.

226

Lincoln YS, and Guba EG. (1985). Naturalistic inquiry. Beverly Hills, CA: Sage.

Lindsay RS, Dabelea D, Roumain J, Hanson RL, Bennett PH, and Knowler WC. Type 2
diabetes and low birth weight: the role of paternal inheritance in the association of
low birth weight and diabetes. Diabetes 2000; 49(3): 445-9.

Liu L, Hironaka K, and Pihoker C. Type 2 diabetes in youth. Curr Probl Pediatr Adolesc
Health Care 2004; 254-272.

Ludwig DS, and Ebbeling CB. Type 2 diabetes mellitus in children: Primary care and
public health considerations. J oumal of American Medical Association 2001;
286(12): 147.

Lustrnan PJ, Griffith LS, Freedland KE, Kissel SS, and Clouse RE. Cognitive behavior
therapy for depression in type 2 diabetes mellitus. A randomized, controlled trial.
Ann Intern Medicine. 1998; 129(8): 613-21.

Macaluso CJ, Bauer UE, Deeb LC, Malone JL, Chaudhari M, SilversteinJ, Eidson M,
Goldberg RB, Gaughan-Bailey, Bonnie, Brooks, Robert, Rosenbloom AL. Type
2 diabetes mellitus among Florida children and adolescents, 1994 through 1998.
Public Health Reports 2002; 117: 373-379.

Macaluso CJ, Bauer UE, Deeb LC, Malone JL, Chaudhari M, SilversteinJ, Eidson M,
Goldberg RB, Gaughan-Bailey, Bonnie, Brooks, Robert, and Rosenbloom AL.
Type 2 diabetes mellitus among Florida children and adolescents, 1994 through
1998. Public Health Reports 2002; 117: 373-379.

Maillet N, D’Eramo-Melkus G, and Spollett G. Using focus groups to characterize he
health beliefs and practices of black women with non-insulin-dependent diabetes.
Diabetes Education 1996; 22: 39-45.

Malerbi DA, Paiva ES, Duarte AL, and Wajchenberg BL: Metabolic effects of dietary
sucrose and fructose in Type 2diabetic subjects. Diabetes Care 1996; 19: 1249—
1256.

Manson J E, and Spelsberg A: Primary prevention of non-insulin-dependent diabetes
mellitus. American Journal of Preventive Medicine 1994; 10: 172.

Mazzuca SA, Moorman NH, Wheeler ML, et al. The diabetes education study: a
controlled trial of the effects of diabetes patient education. Diabetes Care 1986; 9:
1-10.

McLeroy KR, Bibeau D, Steckler A, and Glanz K. An ecological perspective on health
promotion programs. Health Education Q 1988; 15: 351-377.

227

McMurray RG, Harrell J S, Bradley CB, Webb JP, and Goodman EM. Comparison of a
computerized physical activity recall with a tri-axail motion sensor in middle
school youth. Medicine Science of Sports and Exercise 1998; 30: 1238-1245.

Mei Z, Scanlon KS, Grurnmer-Strawn LM, Freedman DS, Yip R, and Trowbridge FL.
Increasing prevalence of overweight among US low-income preschool children:
The Center for Disease control and Prevention Pediatric Nutrition Surveillance,
1983 to 1995. Pediatrics 1998; 101: e12.

Michigan Department of Community Health. (2004). Behavioral risk Factors
surveillance survey report.

Miles, MB, and Huberman, AM. (1994). An expanded sourcebook: Qualitative data
analysis (2nd ed.). Thousand Oaks, CA: Sage.

Miller J C. Importance of glycemic index in diabetes. J Nutrition 2000; 130: 2808-2838.

Mitchell GJ. Living with diabetes: How understanding expands theory for professional
practice. Canadian Journal of Diabetes Care 1998; 22: 30-7.

Mokdad AH, Bowman BA, Ford ES, Vinicor F, Marks J S, and Koplan JP. The
continuing epidemics of obesity and diabetes in the United States. J oumal of
American Medical Association 2001; Sep 12; 286(10): 1195-200.

Mokdad AH, Ford ES, Bowman BA, Nelson DE, Engelgau MM, Vinicor F, and Marks
J S. Diabetes Trends in the US: 1990-1998. Diabetes Care 2000; 23(9): 1278-
1283.

Moore LL, Visioni AJ, Wilson PW, D’Agostino RB, Finkle WD, and Ellison RC: Can
sustained weight loss in overweight individuals reduce the risk of diabetes
mellitus? Epidemiology 2000; 3: 269—273.

Moshfeg A, Borrud L, Perloff B, and Lacomb R. (1999). Improved Method for the 24-
hour Dietary recall for Use in National Surveys. F ASEB J 13(4): A603.

Mourier A, Autier JF, De Kerviler E, et al. Mobilization of visceral adipose tissue related
to the improvement in insulin sensitivity in response to physical training in
NIDDM: Effects of branched chain amino acid supplements. Diabetes Care 1997;
20: 385-391.

National Center for Health Statistics. Plan and operation of the Third National Health
and Nutrition Examination Survey, 1988-94. Series 1: Programs and collection
procedures. Vital Health Statistics 1994; 32: 1-407.

National Center for Health Statistics. Havlik RJ, Liu BM, Kovar MG et al. Health
Statistics for older persons, US, 1986. Washington DC, US. Government

228

printing office. Vital and Health Statistics. Series 3, No. 25. DHHS Publication
no. (PHS) 87-1409; 1987.

National Cholesterol Education Program, 2004. Website
http://www.nhlbi.nih.gov/about/ncep/index.htrn accessed August 2004.

National Institute of Health Consensus Conference on diet and exercise in non-insulin
dependent diabetes mellitus. Diabetes Care 1987; 10: 639-644.

National Research Council, Commission on Life Sciences, Committee on Diet and
health, Food and Nutrition Board. Chronic Disease. (1989). An overview in diet
and health implications for reducing chronic disease risk. In Diet and Health.
Washington, DC: National Academy Press; 114.

Nestle M, Wing R, Birch L, DiSogra L, Drewnowski A, Middleton S, Sigrnan-Grant M,
Sobal J, and Winston M. Behavioral and social influences on food choices.
Nutrition Reviews 1998; 56: 850-874.

Neufeld ND, Raffel L, and Landon C. Early presentation of Type 2 diabetes in Mexican-
American youth. Diabetes Care 1998; 21(1): 80.

NIDDK/NICHHD (National Institute of Diabetes and Digestive and Kidney
Diseases/National Institute of Child Health and Human Development), 1999.
Type 2 diabetes in the pediatric population. RFA:DK—OO-OO8.
http://www.grants.nih.gov/grants/guide/rfa-files/RFA-DK-OO-OO8

Noel M, Hickner J, Ettenhofer T, and Gauthier B. The high prevalence of obesity in
Michigan primary care practices. An UPRNet study. Upper Peninsula Research
Network. Journal of Family Practice 1998; 47(1): 39-43.

Norris SL, Engelgau MM, and Narayan KM. Effectiveness of self-management training
in type 2 diabetes: a systematic review of randomized controlled trials. Diabetes
Care 2001; 24(3): 561-87.

Norusis MJ (2002). SPSS 11.0 Guide to Data Analysis. NJ: Prentice Hall, Inc.

O’Brien SH, Holubkov R, and Cohen RE. Identification, Evaluation, and Management
of obesity in an academic primary care center. Pediatrics 2004. 114(2): 154-159.

O’Connor PJ, Crabtree BF, and Yanoshik MK. Differences between diabetic patients
who do and do not respond to a diabetes care intervention: A qualitative analysis.
Family Medicine 1997; 29(6): 424-428.

O’Connor PJ, Fragneto R, Coulehan J, and Crabtree BF. Metabolic control in non—
insulin-dependent diabetes mellitus: factors associated with patient outcomes.
Diabetes Care 1987; 10: 697-701.

229

Ogden CL, Flegal KM, Carroll MD, and Clifford LJ. Prevalence and trends in
overweight among US children and adolescents. Journal of American Medical
Association 2002; 288: 1728-1732.

Ohkubo Y, Kishikawa H, Araki E, Miyata T, Isami S, Motoyoshi S, Kojima Y, Furuyoshi
N, and Shichiri M. Intensive insulin therapy prevents the progression of diabetic
microvascular complications in Japanese patients with non-insulin-dependent
diabetes mellitus: a randomized prospective 6-year study. Diabetes Research

Clinical Practice. 1995; 28(2): 103-17.

Oltersdorf U, Schhlettweing-Gsell D, and Winkler G. Assessing eating pattems-an
emerging research topic in nutritional sciences: introduction to the symposium.
Appetite 1999; 32: 1-7.

Pan XR, Li GW, Hu YH, Wang JX, Yang WY, An ZX, Hu ZX, Lin J, Xiao JZ, Cao HB,
Liu PA, J iang XG, J iang YY, Wang JP, Zheng H, Zhang H, Bennett PH, and
Howard BV. Effects of diet and exercise in preventing NIDDM in people with
impaired glucose tolerance. Diabetes Care 1997; 20:5 37—544.

Pettitt DJ, Aleck KA, Baird HR, Carraher MJ, Bennett PH, and Knowler WC. Congenital
susceptibility to NIDDM. Role of intrauterine environment. Diabetes 1988; 37(5):
622-628.

Phillips DI. Insulin resistance as a programmed response to fetal under nutrition.
Diabetologia 1996; 39(9): 1 1 19-22.

Pihoker C, Scott CR, Lensing SY, Cradock MM, and Smith J. Non-insulin dependent
diabetes mellitus in African American youths of Arkansas. Clinical Pediatrics
1998; 37: 97-102.

Pinhas OM, Dolan LM, Daniels SR, Standiford D, Khoury PR, and Zeitler P. Increased
incidence of non-insulin dependent diabetes mellitus among adolescents. The
Journal of Pediatrics 1996; 128(5): 608-615.

Pinhas-Hamiel O, and Zeitler P. Type 2 diabetes: Not just for grown ups anymore.
Contemporary Pediatrics 2001, 18: 102.

Pinhas-Hamiel O, Dolan LM, and Zeitler PS. Diabetic ketoacidosis among obese
Afiican-American adolescents with NIDDM. Diabetes Care 1997; 20(4): 484-6.

Pinhas-Hamiel O, Standford DS, Hamiel D, et al. Type 2 diabetes family: A setting for

development and treatment of adolescent Type 2 diabetes. Archives of Pediatric
Adolescent Medicine 1999; 153: 1063.

230

 

Pinhas-Hamiel O, and Zeitler P. Type 2 diabetes in adolescents, no longer rare. Pediatr
Rev. 1998; 19(12): 434-5.

Pinhas-Hamiel OM, Dolan LM, Daniels SR, Standiford D, Khoury PR, and Zeitler P.
Increased incidence of non-insulin dependent diabetes mellitus among
adolescents. The Journal of Pediatrics 1996; 128(5): 608-615.

Pociot F, Norgaard K, Hobolth N, Anderson 0, Nerup J, and the Danish Study Group of
Diabetes in Childhood. A nationwide population-based study of the familial
aggregation of Type 1 diabetes mellitus Denmark. Diabetologia 1993; 36: 870-
875.

Popkin BM, and Udry JR. Adolescent obesity increases significantly in second and third
generation U.S. immigrants: The National Longitudinal Study of Adolescent
Health. Journal of Nutrition 1998; 128 (4): 701-6.

Quataroa A, Consoli G, Magno M, Caretta F, Ceriello A, and Giugliano D. Analysis of
diabetic family connection in subjects with insulin-dependent diabetes mellitus.
Diabet Metab 1990; 16: 449-452.

Radius SM, Dillrnan TE, Becker MH, Rosenstock IM, and Horvah WJ. Adolescent
perspective on health and illness. Adolescence 1980; 15: 375-384.

Rao GM, Morghom LO, Abukhris AA, Mansori SS, Alphgih FA, and Ragale LY.
Glycosylated haemoglobin and blood glucose levels in Libyan diabetic patients.
Trop Geogr Medicine. 1986; 38(4): 391-397.

Raz I, Soskolne V, and Stein P. Influence of small group education sessions on glucose
homeostasis. Diabetes Care 1988; 11: 67-71.

Reaven GM. Effect of dietary carbohydrate in the metabolism of patients with non-
insulin dependent diabetes mellitus. Nutrition Reviews 1986; 44: 65-73.

Reinharz S. (1992). Feminist methods in social research. New York: Oxford University.

Rettig B, Shrauger D, Recker R, Gallagher T, and Wiltse H: A randomized study of the
effects of a home diabetes education program. Diabetes Care 1986; 9: 173—178.

Rewers M, and Hamman RF. Risk factors for non-insulin-dependent diabetes. In: Harris
MI, ed. Diabetes in America. Washington, DC: US Government Printing Office
1995; 179-220.

Rewers M, and Hamman RF. Risk factors for non-insulin-dependent diabetes. In: Harris

MI, ed. Diabetes in America. Washington, DC: US Government Printing Office
1995; 179-220.

231

 

Robertson RP, Olson LK, and Zhang HJ. Differentiating glucose toxicity from glucose
desensitizing: a new message from the insulin gene. Diabetes 1994; 43(9): 1085-
1089.

Robinson N, Lloyd CE, and Stevens LK. Social deprivation and mortality in adults with
diabetes mellitus. Diabet Medicine 1998 March; 15(3): 205-212.

Rosenbloom AL, Joe JR, Young RS, and Winter WE. Emerging epidemic of Type 2
diabetes in youth. Diabetes Care 1999; 22: 345-354.

Rost KM, F lavin KS, Schmidt LE, and Mcgill JB. Self-care predictors of metabolic
control in NIDDM. Diabetes Care 1990; 13: 1111-1113.

Rubin RR, Peyrot M, and Saudek CD. Effect of diabetes education on self-care,
metabolic control and emotional well being. Diabetes Care 1989; 12: 673-679.

Salmeron J, Manson J E, Stampfer MJ, Colditz GA, Wing AL, and Willet WC. Dietary
fiber, glycemic load, and risk of non-insulin —dependent diabetes mellitus in
women. Journal of American Medical Association 1997; 277: 472-477.

Savage PJ, Bennett PH, Senter RG, and Miller M. High prevalence of diabetes in young
Pima Indians. Diabetes 1979, 28: 937-942.

Samuel-Hodge CD, Headen SW, Skelly AH, and Ingram AE. Influences on day-to-day
self-management of Type 2 diabetes among Afiican-Arnerican women. Diabetes
Care 2000; 23(7): 928-933.

Savoca M, and Miller C. Food selection and eating patterns: Themes found among
people with Type 2 diabetes mellitus. J oumal of Nutrition Education 2001; 33:
224-233.

Schoenberry NE, and Amey CH. Stories of meaning: Lay perspectives on the origin and
management of non-insulin dependent diabetes mellitus among older women in
the United States. Social Science and Medicine 1998; 47: 2113-2125.

Schwab US, Ausman LM, Vogel S, Zhengling L, Larnmi-Keefe CJ, Goldin BR, Ordovas
JM, Schaefer EJ, and Lichtenstein AH: Dietary cholesterol increases the

susceptibility of low density lipoprotein to oxidative modification.
Atherosclerosis 2000; 149: 83—90.

Scott CR, Smith JM, Cradock MM, and Pihoker C. Characteristics of youth onset non
insulin dependent diabetes mellitus and insulin dependent diabetes mellitus at
diagnosis. Pediatrics 1997; 100(1):84-91.

Sellers EA, and Dean HJ. Diaberic ketoacidosis: A complication of Type 2 diabetes in
Canadian aboriginal youth. Diabetes Care 2000; 23(8): 1202-1204.

232

 

Service FJ, O’Brien PC, and Rizza RA. Measurement of glucose control. Diabetes Care
1987; 10: 225-237.

Si gal RJ, and Warram JH. The interaction between obesity and diabetes. Curr Opin
Endocrinol Diabetes 1996; 3: 3-9.

Silverstein JH, and Rosenbloom AL. Treatment of Type 2 diabetes mellitus in children
and adolescents. J oumal of Pediatric Endocrinology Metabolism 2000; 13(86):
1403-1409.

Siminerio LM, Clougherty M, Gilliland A, and Kelly K. Evaluating children with
diabetes and their parent’s preparedness and involvement in diabetes care for the
school. Diabetes 2000; 49: A173.

Simmons D, Gatland BA, Leakehe L, and Henring C. Frequency of diabetes in family
members of probands with non-insulin-dependent diabetes mellitus. J Intern
Medicine. 1995; 237: 315-321.

Sinaiko, AR, Jacobs, DR. Jr., Steinberger, J ., Moran, A. Influence of insulin resistance In
childhood on systolic blood pressure and insulin resistance syndrome in early
young adulthood. [Abstracts From the 58th Annual Fall Conference and
Scientific Sessions of the Council for High Blood Pressure Research in
association with the Council on the Kidney in Cardiovascular Disease: Oral
Presentations] Hypertension 2004; 44(4): 503.

Sjostrom CD, Lissner L, Weedel H, and Sjostrom L: Reduction in incidence of diabetes,
hypertension and lipid disturbances after intentional weight loss induced by
bariatric surgery: The SOS Intervention Study. Obes Res 1999; 5: 477—484.

Skelton CW. Use of glycosylated hemoglobins in the long-term management of diabetes.
Nurse Pract. 1986; 11(3): 42, 44, 46 passirn.

Smith MS, Mauseth R, Palmer JP, Pecoraro R, and Wenet G. Glycosylated hemoglobin
and psychosocial adjustment in adolescents with diabetes. Adolescence 1991;
26(101): 31-40.

Smucker R, Block G, Coyle L, Harvin A, and Kessler A. Dietary and risk factor
questionnaire and analysis system for personal computers. American Journal of
Epidemiology 1989; 129: 445-449.

Storm H, Thomsen C, Pedersen E, Rasmussen O, Christiansen C, and Herrnansen K.
Comparison of a carbohydrate-rich diet and diets rich in stearic or palnritic acid in
NIDDM patients. Diabetes Care 1997; 20: 1807—1813.

233

 

 

Stuart CA, Gilkison CR, and Smith MM. Acanthosis nigrican as a risk factor for non-
insulin dependent diabetes mellitus. Clinical Pediatrics 1998; 37: 80.

Stuart CA, Gilkison CR, and Smith MM. Acanthosis nigrican as a risk factor for non-
insulin dependent diabetes mellitus. Clinical Pediatrics 1998; 37 (2): 73-79.

Stuart CA, Gilkison CR, Keenan BS, and Nagamai M. Hyperinsulinemia and acanthosis
nigricans in Afiican Americans. Journal National Medical Association. 1997;
89(8): 523-527.

Stuart CA, Smith MM, Gilkison CR, Shaheb S, and Stahn RM. Acanthosis nigricans
among native Americans: an indicator of high diabetes risk. Am J Public health
1994; 84(11): 1839-1842.

Sullivan ED, and Joseph DH. Struggling with behavior changes: a special case for clients
with diabetes. Diabetes Education 1998; 24: 72-77.

Tamura A, Mori T, Hara Y, and Komiyama A. Preperitoneal fat thickness in childhood
obesity: association with serum insulin concentration. Pediatric International
2000; 42(2): 155-159.

Tan KC, Mackay IR, Zimmet PZ, Hawkins BR, and Lam KS. Metabolic and
immunological features of Chinese patients with atypical diabetes mellitus.
Diabetes Care 2000; 23(3): 335-338.

Tanaka K, Moriya T, Kanamori A, and Yajima Y. Analysis and a long term follow up of
ketosis onset Japanese NIDDM patients. Diabetes Res Clinics Pract. 1999; 44(2):
137-46.

Taylor SJ, and Bogdan R. (1998). Introduction to quzflrtive resgrch methods: a
guidebook and resource. (3lrd ed.). New York: John Wiley and Sons.

Thai AC, Ng WY, Loke KY, Lee WR, Lui KF, and Cheah J S. Anti-GAD antibodies in
Chinese patients with youth and adult onset IDDM and NIDDM. Diabetologia
1997; 40(1): 1425-30.

The Diabetes Control and Complications Trail Research Group. Intensive diabetes
treatment and complications in IDDM. New England Journal of Medicine 1993,
329: 977-986.

Thomas AM, Peterson L, and Goldstein D. Problem solving and diabetes regimen
adherence by children and adolescence with IDDM in social pressure situations:
A reflection of normal development. J oumal of Pediatric Psychology 1997; 22:
541-561.

234

 

Torre MS, Schofield DH, and Mangione RA. Glycosylated hemoglobins and diabetic
control assessment. Drug Intelligence and Clinical Pharmacy 1981; 15: 175-179.

Travis T. Patient perceptions of factors that affect adherence to dietary regimens for
diabetes mellitus. Diabetes Educator 1997; 23: 152-156.

Trioano RP, and Flegal KM. Overweight children and adolescents: Description,
Epidemiology, and Demographics. Pediatrics 1998; 101(3): 497-504.

Tubiana-Rufi N, Moret L, Czemichow P, and Chwalow J. The association of poor
adherence and acute metabolic disorders with low levels of cohesion and
adaptability in families with diabetic children. The PEDIAB Collaborative Group.
Acta Paediatr. 1998; 87(7): 741-6.

Turner RC, Millns H, Neil HA, Stratton IM, Manley SE, Matthews DR, and Hohnan RR.
Risk factors for coronary artery disease in non-insulin dependent diabetes
mellitus: United Kingdom prospective diabetes study (UKPDS :23). British
Medical Journal 1998, 316: 823-828.

US. Department of Agriculture (USDA) and US. Department of Health and human
Services. (2000). Nutrition and your health: Dietary guidelines for Americans.
Washington, DC: US Government Printing Office.

US. Department of Agriculture (USDA) and US. Department of Health and human
Services (2002). Nutrition and your health: dietary guidelines for Americans.
Washington, DC: US Government Printing Office.

UK Prospective Diabetes Study Group. Intensive blood-glucose control with
sulphonlyureas or insulin compared with conventional treatment and risk of
complications in patients with Type 2 diabetes. Lancet 1998; 352: 837-53.

Urbina EM, Gidding SS, Bao W, Elkasabany A, and Berenson GS. Association of
fasting blood sugar level, insulin level, and obesity with left ventricular mass in
healthy children and adolescents: The Bogalusa Heart Study. American Heart
Journal 1999; 138(1 Pt 1): 122-7.

Vinkin AI, and Jenkins DJA. Dietary fiber in the management of diabetes. Diabetes
Care 1988; 11: 160-173.

Viswanathan M, Snehalatha C, Viswanathan V, Vidyavathi P, Indu J, and Ramachandran
A: Reduction in body weight helps to delay the onset of diabetes even in non-

obese with strong family history of the disease. Diabetes Research in Clinical
Practice 1997; 35: 107—112.

235

Walker K, O’Dea K, Nicholson G, and Muir J. Dietary composition, body weight, and
NIDDM. Diabetes Care 1995; 18: 401—403.

Watkins PB, and Whitcomb RW. Hepatic dysfunction associated with troglitazone. New
England Journal of Medicine 1998; 338: 916-917.

Wdowik MJ, Kendall PA, Harris MA, and Auld G. Expanded Health Belief
Modelnpredicts Diabetes self-management in college students. Journal of
Nutrition Education 2001 ; 33 : 17-23.

Weathersoon LJ, Carolan M, Song W, Latty C, and Deighton, T. (2001). Risk for Type 2
diabetes and family factors.

Weatherspoon LJ, Kerver J, Carolan M, J ager K. and Song, W. (2000). Glycated
Hemoglobin concentration Associated with risk factors for Type 2 diabetes in US
children and adolescents. Abstract submitted to American Dietetic Association.

 

Webber LS, Harsha DW, Nickles TA, and Berenson GS. Secular trends in obesity in
children. In: Filer LJ, Iuaer RM, Lurpker RV, editors. Prevention of
atherosceloris and hypertension beginning in youth. Philadelphia: Lea and
Febiger; 1994; 194-203.

Weber, RP. (1990). Basic Content Analysis (2nd ed.). Thousand Oaks, CA: Sage.

Wei JN, Sung F C, Lin CC, Lin RS, Chiang CC, and Chuang LM. National surveillance
for type 2 diabetes mellitus in Taiwanese children. J oumal of American Medical
Association 2003; 290(10): 1345-50.

Weissberg-Benchell J, Glasgow AM, Tynan WD, Wirtz P, Turek J, and Ward J:
Adolescent diabetes management and mismanagement. Diabetes Care 1995; 18:
77-82.

Willi SM, Mcbumey P, Kennedy A, Wojciechowski B, Garvey T. Ketosisprone NIDDM
in African-American children [abstract]. Diabetes 1997; 46(suppl 1): A67

Wing RR, Epstein LH, Nowalk MP, Scott N, Koeska R, and Hagg S. Does self
monitoring of blood glucose levels improve dietary compliance for obese patients
with Type 2 diabetes. The American Journal of Medicine 1986; 81: 830-835.

Wing RR, Koeska R, Epstein LH, Nowalk MP, Gooding W, and Becker D. Long term
effects of modest weight loss in type II diabetic patients. Archives of Internal
Medicine 1987a; 147: 1749-1753.

Wing RR, Marcus MD, Epstein LH, and Salata R. Type 11 diabetic subjects lose less

weight than their overweight non-diabetic spouses. Diabetes Care 1987b; 10:
563-566.

236

Wing RR. Use of a very low-calorie diets in the treatment of obese persons with Type 2
diabetes mellitus. J Am diet Assoc. 1995; 95: 569-572.

World Health Organization: Diabetes Mellitus: Report of a WHO Study Group. Geneva,
World Health Org. 1985 (Tech. Rep. Ser., no. 727).

Yamada K, and Nonaka K. Diabetic ketoacidosis in young obese Japanese men.
Diabetes Care 1996; 19(6): 671.

Yamanouchi K, Shinozaki T, Chikada D, et a1. Daily walking combined with diet is a
useful means for obese Type 2 diabetes patients not only to reduce body weight
but also improve insulin sensitivity. Diabetes Care 1995; 18: 775.

Yin RK. (1989). Case study research, design and methods. California: Sage Publications.

Youth Risk Behavior Survey. 2003. www.cdc.gov Accessed January 2005.

Zimmerman BR, and Service FJ. Management of non-insulin dependent diabetes
mellitus. Medical Clinics of North America 1988; 72: 1355-1364.

237