MATERNAL AND CHILD DIET-RELATED FACTORS ASSOCIATED WITH
STUNTING AND WASTING IN CHILDREN 6-23 MONTHS OF AGE IN INDONESIA

By
Dwi Savitri Rivami

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Human Nutrition – Doctor of Philosophy
2017

ABSTRACT
MATERNAL AND CHILD DIET-RELATED FACTORS ASSOCIATED WITH STUNTING
AND WASTING IN CHILDREN 6-23 MONTHS OF AGE IN INDONESIA
By
Dwi Savitri Rivami
Background: Undernutrition among children under-five years of age is a long-term major
concern in Indonesia. Over 20 years, the prevalence of undernutrition in this target group only
decreased by 7.3% from 44.5% in 1990 to 37.2% in 2013. The most common forms of
undernutrition in Indonesian young children are stunting and wasting, strong predictors of
mortality and morbidity among young children. Inappropriate dietary intake is postulated to be
an important immediate risk factor for development of undernutrition as demonstrated in
Indonesian children by a low rate of exclusive breastfeeding and poor complementary feeding,
specifically relative to a high consumption of unhealthy snacks. Links between maternal and
child dietary intake have been well documented in other countries, but not Indonesia and few
have examined mother’s dietary intake quality and weight status as well as the association of
snacks with child nutrition status, which is critical for facilitating the efficacy of prevention and
treatment of undernutrition among Indonesian young children.
Specific aims: The two Specific Aims of this study were: 1) to examine the relationship between
mother’s dietary intake quality and weight status and risk for stunting and wasting in children 623 months of age in Indonesia, and 2) to examine the relationship between child feeding
practices, including unhealthy snack consumption, dietary quality, and risk for stunting and
wasting in children 6-23 months of age in Indonesia.
Methods: The Indonesia Demographic and Health Survey (IDHS) of 2010 was used to assess
maternal and child diet-related factors in association with stunting and wasting in children 6-23

months of age in Indonesia. The IDHS, conducted by The Ministry of Health every three years,
included a single 24-hour dietary recall and anthropometric measurements from the targeted
sample. Mothers’ weight status was determined using body mass index (BMI). Dietary quality
for the mothers was determined from the 24-hour dietary recalls using the minimum dietary
diversity (MDD) score recommended by FAO in 2014. Stunting and wasting were defined as
height-for-age z-scores (HAZ) and weight-for-height z-scores (WHZ) lower than -2 respectively.
Child dietary intake data included breastfeeding (past and current) and complementary feeding
(minimum dietary diversity score and frequency of unhealthy snack consumption) practices. Path
model analysis was conducted using Mplus software.
Results: After data cleaning, there were 2,457 mother and child dyads. Stunting and wasting
rates were 37.3% and 14.5% respectively. Mothers’ BMI had direct a positive effect on stunting
(p = 0.05). There was a significant moderating effect of mothers’ MDD on child’s unhealthy
snack consumption relative to wasting status, but not stunting. Risk for child stunting was higher
when breastfeeding was low (OR: 1.29, p-value < 0.05) and with a high consumption of
unhealthy snacks (OR: 1.13, p-value < 0.05), while risk for wasting was lower with a high
consumption of unhealthy snacks (OR: 0.80, p-value < 0.05).
Conclusion: The absence breastfeeding and a high consumption of unhealthy snacks were key
independent factors associated with stunting in Indonesian children 6-23 months of age. High
consumption of unhealthy snacks interestingly had a protective effect on wasting, while mothers’
MDD moderated the association between child high consumption of unhealthy snacks and
wasting status. Therefore, findings from the current study suggest that improving breastfeeding
and complementary feeding practices of young children can enhance their nutritional status and
have short- and long-term impacts on reducing stunting and wasting.

Copyright by
DWI SAVITRI RIVAMI
2017

ACKNOWLEDGEMENTS

First, I would like to express my sincere gratitude to my advisor, Dr. Lorraine Weatherspoon,
for the continuous support of my PhD study, for her never-ending patience, motivation, and
immense knowledge. I could not have finished this dissertation without her remarkable help.
I would like to thank the chair of my examination committee, Dr. Won Song, for her insightful
comments and encouragement in all the time of research. I am also very thankful to the rest
of my committee, Dr. Joseph Carlson and Dr. Robert Griffore for their valuable inputs and
friendly support, which enriched the overall quality of this research.

I thank the Fulbright Foreign Program, Ministry of Higher Education Republic of Indonesia
and John Harvey Kellogg Endowed Program in Human Nutrition and Health for providing
funding support for my PhD study. I would like to acknowledge the Research and
Development Agency, Ministry of Health Republic of Indonesia who gave access to the
Indonesian Demographic and Health Survey (IDHS) data.

I thank Wenjuan Ma from CSTAT who helped me through the data analysis. I thank Sumathi,
Julie, Amy, Dayeon and Sujin, who have provided great assistance for doing research and
also for their warm friendship that helped me survive freezing Michigan.

Last, but not least, I thank my family in Indonesia and special thanks to my husband David
and my children Dhiena, Dhavina and Driantama. I see the love of God through your sacrifice
in allowing me to follow my dream. I just cannot thank you enough.

v

TABLE OF CONTENTS

LIST OF TABLES

viii

LIST OF FIGURES

ix

CHAPTER 1 - INTRODUCTION
1.1 Background
1.2 Specific aims
1.3 Significance

1
1
4
5

CHAPTER 2 – REVIEW OF LITERATURE
2.1 Overview of Undernutrition in Children
2.1.1 Stunting
2.1.2 Wasting
2.1.3 Underweight
2.2 Undernutrition in Children in Indonesia
2.3 Factors Associated with Undernutrition in Children Under-five Years
2.3.1 Child Specific Factors
2.3.1.1 Dietary intake
2.3.1.1.1 Breastfeeding
2.3.1.1.2 Complementary feeding
2.3.1.1.3 Specific food group intake
2.3.1.2 Role of diseases
2.3.2 Maternal Factors
2.3.2.1 Mothers’ dietary intake
2.3.2.2 Mothers’ anthropometric measurements
2.3.2.3 Mothers’ socio-demographic characteristics
2.4 Implications of Undernutrition in Children Under-five Years
2.5 Nutrition Programming in Indonesia

6
6
9
10
11
12
16
16
16
16
19
21
22
23
23
25
26
28
30

CHAPTER 3 – METHODS
3.1 Dataset
3.1.1 Study Sample
3.1.2 Steps in Data Preparation
3.2 Variable Definition and Operationalization
3.2.1 Primary Variables of Interest
3.2.1.1 Child Nutritional Status
3.2.1.2 Maternal Nutritional Status
3.2.1.3 Maternal Dietary Intake
3.2.1.4 Child Feeding Practice
3.2.1.5 Child Dietary Quality
3.2.2 Covariates
3.3 Statistical Analysis

33
35
38
38
40
40
40
41
41
43
43
44
45

vi

CHAPTER 4 – RESULTS
4.1 Study Population
4.2 Stunting and Wasting Socio-demographic Associations
4.3 Path Analysis of Factors Associated with Stunting and Wasting
4.4 Factors Associated with Ever Being Breastfed
4.5 Factors Associated with Current Status of Breastfeeding
4.6 Path Analysis of Factors Associated with Continuous Stunting and
Wasting

48
48
56
62
66
68

CHAPTER 5 – DISCUSSION

73

CHAPTER 6 – SUMMARY AND CONCLUSIONS
79
6.1 Conclusion
6.2 Implications
6.3 Strengths and Limitations

79
80
81

70

APPENDICES
Appendix 1 – Electronic approval
Appendix 2 – Link to access the IDHS database
Appendix 3 – Indonesian Demographic and Health Survey
Questionnaire (Indonesian)
Appendix 4 – Indonesian Demographic and Healthy Survey
Questionnaire (English)

102

BIBLIOGRAPHY

139

vii

83
84
85
86

LIST OF TABLES

Table 1. Socio-demographic characteristics of children and mothers in the study

48

Table 2. Dietary and nutrition characteristics of children and mothers in the study 49
Table 3. Breastfeeding information for children 6-23 months of age in the study

51

Table 4. Complementary feeding practices for children 6-23 months of age in the
study

52

Table 5. Protein and energy intake of mothers and children in the study

52

Table 6. Adequacy of minimum dietary diversity of mothers and her children

53

Table 7. Breastfeeding practices by child age group

54

Table 8. Adequacy of minimum dietary diversity of children in the study based on
age groups

54

Table 9. Unhealthy snack consumption of children in the study based on age groups

55

Table 10. Percentage of stunting and wasting on children 6-23 months of age
in the study based on age groups

55

Table 11. Demographic characteristics of households, mothers and children
based on stunting and wasting categories

58

Table 12. Dietary characteristics of mothers and children based on stunting
and wasting categories

60

Table 13. Logistic regression model for age and history of ever being breastfed

69

Table 14. Odds ratios from logistic regression model for stunting

69

Table 15. Odds ratios from logistic regression model for wasting

70

viii

LIST OF FIGURES

Figure 1. Conceptual framework for the determinants and impacts of malnutrition

7

Figure 2. Adapted human ecological model of child nutrition status

33

Figure 3. Conceptual framework for factors that influence child nutrition status
(stunting and wasting)

34

Figure 4. Flow chart of study sampling

40

Figure 5. Path diagram of the overall model

61

Figure 6. Direct effect of mothers’ BMI relative to children stunting status

62

Figure 7. Path analysis relationships of dietary intake of mothers and children with
stunting in children

64

Figure 8. Path analysis relationship of mothers’ and children’s dietary intake to
wasting in children

65

Figure 9. Factors associated with children ever being breastfed

67

Figure 10. Factors associated with children currently being breastfed

68

Figure 11. Relationship of mothers’ and children’s dietary intake to child
Height for Age Z-scores

70

Figure 12. Relationship of mothers’ and children’s dietary intake to child
Weight for Age Z-scores

72

ix

CHAPTER 1 – INTRODUCTION

1.1 Background
The economy of Indonesia, a developing country in South East Asia, has been growing fast since
2008,1 as evidenced by a five-year Gross Domestic Product (GDP) growth above 5%. 2
Governmental efforts to address the serious problems of child and adult undernutrition in the
country have also been ongoing for over 30 years. However, undernutrition problems persist in
almost every district in Indonesia. In 1990, there were at least 44.5% children under-five years of
age with undernutrition. More than twenty years later, the government estimated that 37.2% of
children under-five years had some type of undernutrition. 3 With a population of over 24.6
million children under-five years of age, Indonesia is touted to be one of ten countries in the
world with the largest number of childhood wasting and stunting, the two indicators of severe
undernutrition. 4 In 2013, more than 37.2% of children (9.2 million) under-five years of age were
stunted, and 12.1% of children (3 million)5 from the same age group were wasted.

According to the World Health Organization (WHO), undernutrition has been recognized as
creating the highest burden of disease in the world (16% of all calculated disability-adjusted life
years). 6 Nutritional status during the first years of life is critical because of the long-term
ramifications into adulthood. The enduring effects of child undernutrition include increased risks
for lower intellectual capacity compared to well-nourished children, decreased economic
potential, and increased chronic diseases such as diabetes and cardiovascular disease in
adulthood. 7–9 One of the immediate causes of undernutrition is poor dietary intake. 10,11 Thus
assessing the quality of dietary intake and other risk factors of undernutrition of a targeted

1

population can facilitate early identification and potentially elucidate how to address problems
before the negative impacts of undernutrition occur. Although growth faltering is typically
assessed and reported primarily for children under the age of five years, this study adds insight to
this aspect of the pediatric literature in that it focuses on children 6-23 months. This period is a
critical window for growth and development during which a child is least likely to recover from
the stunting impairment experienced as a result of severe undernutrition, even if nutrition
improves after two years of age. 12 The 6-23 month age period is also the target age range for
introduction of complementary feeding in conjunction, preferably, with continued breastfeeding,
and if not appropriately implemented can have devastating implications. 13

A mother’s diet and weight status have been found to be significantly related to that of her
child’s from the pre-pregnancy period through that of caring for her young child. 14,15 It is
however interesting to note that in contrast to the stunting and wasting problem among children
under-five years in Indonesia, only 20.8% of women were chronically undernourished and
32.9% were overweight or obese in 2013. 5 To our knowledge, no study has been done in
Indonesia to assess the link between dietary intake and weight status in mothers and stunting and
wasting in their young children. The body of evidence shows that mother’s dietary quality is
usually complicated and determined by multiple factors including socio-demographic
characteristics, healthy or unhealthy behaviors and has a both under-and-over-weight
relationship with weight status. 16–19 Mother and child (6-23 months) intakes may vary
particularly for nutrient-rich foods such as fruits and vegetables as shown in Bangladesh,
Vietnam and Ethiopia. 20 In addition, measuring dietary intake for young children may be more
challenging than that for adults because of the possibility of inaccurate reports from parents as

2

they may not know what foods the child eats when with caretakers other than the parents. 21
However, it is important to understand if and how dietary quality of mothers in this vulnerable
population relates to that of their young children so that nutrition inconsistencies can be better
identified to improve child nutrition status and health.

One of the major problems believed to be related to poor dietary intake among young children in
Indonesia is poor feeding practices, which includes both poor breastfeeding and complementary
feeding practices. 22–24 Exclusive breastfeeding was practiced less than 50% by mothers for
infants below 6 months with a very high percentage (65%) also feeding their newborns unhealthy
food or drink other than breast milk (such as honey and solid food) as early as the first three days
after birth. 24 Less than 50% of children 6-23 months of age in Indonesia received
complementary food from at least four food groups out of seven as recommended by WHO in
2007 25, energy intakes were below 70% of that recommended for their age. 26 These poor
feeding practices in Indonesian young children could be related to the occurrence of stunting and
wasting. To our knowledge, there are no previous reports that specifically examined poor feeding
practices relative to stunting and wasting in Indonesian children.

Another interesting aspect of poor eating behavior among Indonesian young children is frequent
and unhealthy snacking, which includes ready-to-eat snacks sold by street vendors.24 These kinds
of snacks fulfilled, on average, 40% of the energy requirement for children 1-12 years of age in
2001 in addition to the fact that they are high in salt, fat, and sugar and can suppress the appetite
and result in refusal to eat healthy foods. 24,27 A small cross-sectional study in the rural villages
of West Java province, Indonesia that included 154 children 1-12 years of age, showed that the

3

more snacks were consumed, the lower the height-for-age z-score (HAZ) or the greater
likelihood that they were stunted. 27 This finding showed that a high consumption of snacks
might predict stunting. There were however, no studies that explored, if consumption of these
calorie dense snacks is also related to wasting. Further investigation is needed to explain the
nutritional value of these snacks and associations with stunting and wasting in children 6-23
months in Indonesia.

The goal of this project was to identify how mother’s dietary intake and weight status and child
feeding practices, specifically unhealthy snacks, are related to stunting and wasting among
Indonesian children 6-23 months of age. The findings from this study helped identify specific
aspects of diet-related predictors that could be used to promote healthy dietary practices among
Indonesian young children, and potentially reduce or ameliorate the disproportionately high rates
of stunting and wasting in this vulnerable group in Indonesia.

1.2 Specific aims
Specific aim 1: To examine the relationship between mother’s dietary intake quality and weight
status and risk for stunting and wasting in children 6-23 months of age in Indonesia.
Specific aim 2: To examine the relationship between child feeding practices, including
unhealthy snack consumption and dietary quality and risk for stunting and wasting in children 623 months of age in Indonesia.

4

1.3 Significance
Undernutrition, particularly stunting and wasting, is a major public health problem in Indonesia
primarily affecting children under-five years. 3 The high prevalence of undernutrition among
these young children, which can impair their growth and development, underscores the
importance of addressing early identification and timely prevention of this serious problem.
Currently, children at risk for undernutrition are identified using anthropometric, clinical or
biochemical assessments 28 and hence only those that already have impaired growth,
development or body function are recognized. The conceptual framework for the determinants
and impacts of undernutrition showed that inadequate intake of dietary nutrients was one of the
key factors associated with undernutrition. 10 Thus assessing dietary intake of the targeted
population is important.

The goal of this project was to identify how mother’s dietary intake and weight status, child feeding
practices, including unhealthy snack consumption, and quality of dietary intake are related to
stunting and wasting among Indonesian children 6-23 months of age. This research is important
because the findings improve our ability to identify both maternal and child diet-related factors
among children who are at risk for undernutrition, and to more accurately guide nutritional,
behavioral, and/or feeding environmental interventions for these children and their families.
Health educators and policy makers have a clearer idea of diet-specific shortcomings and needs,
which need to be addressed in interventions aimed at reducing the prevalence of undernutrition in
this vulnerable population in Indonesia.

5

CHAPTER 2 – REVIEW OF LITERATURE

2.1 Overview of Undernutrition in Children
Nutritional status of children is the best global indicator of their well-being as it is closely related
to overall standards of living and basic needs, such as access to food, housing and health care. 29
Undernutrition is defined as a condition when people do not get adequate calories, macro- and/or
micronutrients for growth and maintenance from their diet or they are unable to fully utilize the
food they eat due to illness. 30 Undernutrition occurs when intake of food overall or specific
types of food are insufficient compared to body needs and is typically characterized as being
underweight, stunted, wasted or as macro and/or micronutrient deficiencies. 12 Although factors
affecting an individual’s risk of undernutrition vary, populations with increased nutrient
requirements such as children and pregnant/lactating women are especially vulnerable to
unfavorable conditions. 12

Figure 1 shows a conceptual framework of determinants of malnutrition 31 adapted from
UNICEF. 11 As depicted in Figure 1, causes of malnutrition including undernutrition are
multifaceted, comprising an interplay among the food, social, health and living environments.
These in turn are further classified into immediate, underlying, and basic causal levels.
Immediate causes operate at the individual level, underlying causes influence households and
communities, and basic causes involve the structure and processes of societies. 31

6

Figure 1. Conceptual framework for the determinants and impacts of malnutrition31

Infec on, non-communicable
disease; increased mortality

Impaired labor produc vity; worse
pregnancy outcomes

Outcome

M
alnutri on
Malnutrition

Food
environment
(e.g. food
insecurity, food
access)

Health
Health
behaviors
behaviors
(e.g.
(e.g. intake,
intake,
ac vity)
activity)

Biological
Biological
factors
factors
(e.g. (e.g.
disease,
diseases,
gene
cs)
genetics)

Social
Social
environment
environment
(e.g. feeding
(e.g.
feeding&&
care resources,
care
resources,
working
working
prac
ces)
practices

Health
environment
(e.g. access,
preven on,
treatment)

Immediate
level

Living
environment
(e.g. WASH, built
environment)

Economic, poli cal, social systems
Economic, political, social systems
Leadership, capacity, financial resources
Leadership, capacity, financial resources
Poli cs and
and governance
Politics
governance
Knowledge
Knowledge and
and evidence
evidence

WASH: Water, Sanitation, and Hygiene

Source: (Haddad L, Cameron L, Barnett I. 2014 adapted from UNICEF 1990)31

7

Underlying
level

Basic
level

The most significant immediate causes of undernutrition are inadequate dietary intake and
disease. Infectious diseases, in particular, affect dietary intake and nutrient utilization which in
turn increase the nutrition requirements. 23 For example, diarrhea in children decreases food
intake by reducing appetite and causing nausea or vomiting. 23Alternatively, inadequate dietary
intake may enhance the susceptibility to disease especially for children with immature or
impaired immune function. Undernutrition depresses the immune system in young children and
increases risk for succumbing to infectious diseases. 32 On the underlying level, dietary
inadequacies might be caused by insufficient food supply or inadequate care for children. These
practices include child feeding, health maintenance efforts, and support during growth and
development. 33 The other underlying factors of undernutrition, health environment and living
environment, include concerns about utilization of health services; for example if the location of
service is inaccessible, and/or expensive, low or no insurance coverage, inadequate or unsafe
water supply and lack of sanitary facilities. 32,33 On the basic level, various factors such as
economic, political and social conditions can lead to underlying and immediate factors and
subsequently to undernutrition. 34 For example, in situations of civil unrest or war, food security
and accessibility to care and health services may be impaired which in turn will increase the
dietary inadequacy and disease susceptibility. 34 Given the complexity of the causes of
undernutrition, this proposed study focuses on a segment of the immediate causes specifically
adequacy and quality of dietary intake from both the maternal and child perspective for children
6 to 23 months of age.

During the early years of life, one of the stages of the life cycle when accelerated growth occurs,
an adequate intake of energy and nutrient dense foods is imperative. 24 Those individuals who

8

consume inadequate food or have infectious diseases will not be able to attain their full genetic
potential in growth and development. This is true for more than 170 million children globally
who suffer from one or more types of undernutrition conditions such as stunting and wasting. 35
Worldwide, child undernutrition is disproportionately high in Asia with the proportion for
stunting, underweight and wasting respectively reported as being 56%, 67% and 69% of all
undernourished children in the world. 36

2.1.1 Stunting
Stunting indicates a failure to attain optimal linear growth as a result of prolonged or frequent
diseases and/or undernutrition. 28,30 Stunting is one of the major factors associated with morbidity
and mortality in children under-five years of age. 37 Stunting, a hallmark of endemic poverty, is a
reflection of chronic undernutrition. The global indicator used to define stunting is height-for-age
z-score (HAZ) lower than -2. 28 Stunting may start as early as the fetal period and continue as a
result of long-term undernutrition that occurs during the growing phases. The negative impacts
of stunting are largely irreversible and often associated with intergenerational undernutrition. 9,38
A study in 2014 showed that stunting at 2 years of age negatively affects cognitive skills at age
five even when the child has corrected growth. 39 In addition, stunted mothers had an increased
risk of having stunted children. 40,41

Of all children worldwide, 27% or 171 million were stunted based on data for 2010. 42 In other
words, one in four of children in the world is impacted by long-term undernutrition. More than
80 developing countries have child stunting rates of at least 20%; among these 30 have rates of
40% or more. 43 This high level of stunting is associated with poverty and hence improvements

9

in national socioeconomic conditions are expected to decrease national stunting rates. 44 A
decline of stunting occurred in Asia from 1990 to 2010 during which time rates were cut by 13%
from 39.7% to 26.7%. 42 The decline was associated with an increase in socioeconomic
conditions and, increased access to food, schools, clean water, sanitation and basic health care. 42
However, more than 50% of all stunted children in the world are still found in Asia. 28

2.1.2 Wasting
Wasting is defined as weight-for-height z-scores (WHZ) lower than -2 while severe wasting is
WHZ lower than -3. 28 Unlike stunting, this condition is caused by acute undernutrition. In most
cases, it reflects a recent and intense process of weight loss that is frequently related to severe
food shortage and/or serious disease. 44 Wasting is reversible when the child has adequate food
intake and does not suffer from infectious diseases. 45 However, when it occurs repeatedly,
wasting may prohibit linear catch-up growth over the long-term and promote stunting. 46 Almost
8% (51 million) and 3% (17 million) of all children worldwide are wasted and severely wasted,
respectively. 28 A child with chronic undernutrition is more susceptible to acute undernutrition
than well-nourished children when there are sudden or enhanced food shortages, economic
crises, and other emergencies. 47 In infants, breastfeeding and complementary feeding can play
an important role in wasting outcomes. 24 A recent study in Northern Ghana showed that
adequate complementary feeding had a positive effect on WHZ. 48 Alternatively, breastfeeding
was associated with a lower odds of wasting than that found in non-breastfed children. 49 Several
other risk factors suggested in the literature for wasting are maternal short stature 50, presence of
infectious disease 51, low dietary diversity 52, diarrhea 53, inappropriate complementary feeding
54

, and intrauterine growth retardation (IUGR). 55 A study using demographic and health survey

10

(DHS) data across 54 countries with low to middle income showed that maternal stature was
negatively associated with offspring’s nutrition status including wasting. 50 Based on pooled
analysis involving children 1 week to 59 months of age in 10 prospective studies in Africa, Asia
and South America, it was found that infectious diseases such as respiratory tract infections and
diarrhea were risk factors for wasting. 51 Data from seven DHS from developing countries in
Africa, Latin America and Asia showed that dietary diversity was significantly associated with
child nutrition status such as wasting. 52 Seven cohort studies in Peru, Brazil, Guinea-Bissau and
Bangladesh which included 1,007 children showed that diarrhea was inversely associated with
weight of the children. 53 A thorough review on complementary feeding that included 16
randomized clinical trials in developing countries and quasi-experimental studies showed that
inappropriate complementary feeding leads to wasting. 54 As part of The Child Health Reference
Group, a pooled analysis using 14 longitudinal birth cohorts from low- and middle-income
countries such as: India, Brazil, Zimbabwe, etc, showed associations between IUGR and
subsequent stunting and wasting in children. 55

2.1.3 Underweight
A child is underweight when weight-for-age z-score (WAZ) is lower than -2. 28 As weight is a
strongly associated with any level of undernutrition, underweight can usually be corrected by
improving nutrition and health status. 43 Worldwide, about 16%, or 95 million children underfive years of age in developing countries are underweight with most of them living in Asia. 56
Globally, the proportion of children under-five years of age who were underweight declined by
11% between 1990 and 2014, from 25% to 14%. 56 This progress was made because of the
commitment to fight hunger implemented by the government across countries. 56 Underweight

11

can include stunting alone, wasting alone or a combination of both. 12 Similar to wasting and
stunting, being underweight is also a serious public health problem that has been associated with
greater risk of death and disease. 57–59

Risks for being underweight includes illness, food shortage, dry-season cultivation 60, male
gender, older age, lower maternal education, a lower household income 61, lower frequency of
complementary feeding, and diseases such as malaria and HIV. 62
A cross-sectional study in 152 households with children under 5 years of age in Rukwa region,
Tanzania, found that illness such as infectious diseases, food insecurity and dry-season
cultivation were significant risk factors for being underweight. 60 Data from a cross-sectional
study of rural areas in 10 provinces in China with a total of 84,009 children under 5 years of age
showed that boys had lower mean WAZ-scores compared with their female counterparts with the
assumption that the cause was increased bio-vulnerability of the male gender. 61 This study also
found that older children, lower maternal education, and lower household income were other risk
factors for being underweight. 61 Another study conducted in Tanga region, Tanzania among 748
children 6 months to 14 years of age found that being fed at a frequency below the
recommendation of 5 times a day and infectious diseases were other risk factors for being
underweight. 62

2.2 Undernutrition in Children in Indonesia
In 2010, the population of children under-five years of age in Indonesia was more than 20
million. 63 The national level of stunting and wasting was 35.6% and 13.3% respectively (or 8.7
million children combined), which ranked Indonesia as the fifth largest with regard to stunted

12

children in the world. 63 In a study, where the South East Asian Nutrition Survey data was used,
the researchers found that the overall prevalence of stunting in Indonesia in 2011 was 25.2% and
39.2% in urban and rural areas respectively, implying that rural locations were at greater risk for
chronic undernutrition. 26 The variation for stunting is clearly depicted as 58.4% in the rural east
in Nusa Tenggara province versus 22.5% in the western urban province of Yogyakarta. Out of a
total 33 provinces in the country in 2010 (one has since been added), 15 provinces, which are all
rural, had a prevalence of stunting higher by at least 0.5% than the national average. 3 The
number of wasted children was more than 3.2 million with prevalence rates higher than the
national average in 19 provinces 43, but the variation between provinces was not as variable as
that for stunting, e.g. 20% in Jambi in the rural western part of the country and 15.8% in the east
in Sulawesi. 3 Prevalence of child undernutrition was different across country, most of those who
had high prevalence were located in remote areas with forestry or archipelagic regions and
difficult access. 3

Indonesia is one of the underperforming countries with regard to child nutrition relative to the
national wealth. 35 Despite the rapid five year GDP growth above 5% 2, the stunting rate
increased by 0.6% in 3 years from 35.6% in 2010 to 37.2% in 2013 adding more than 147,000
new cases of stunting. 5 This may be due to problems of limited food availability and inequality
of food distribution among household members. 24 The global economic crisis in 2007-2008
resulted in increased food costs in Indonesia. 64 In 2008, the cost of protein-rich soy products
rose by 50% with subsequent reduced purchasing power. 65 Another factor is food distribution
within the home. Data from the IDHS 2010 showed unequal distribution of food between
children and other family members. Children consumed lower amounts of calories than their

13

mothers and other family members relative to the Recommended Dietary Allowance (OR 1.34;
95%CI 1.06-1.69, P = 0.011), carbohydrates (OR 1.2; 95%CI1.03-1.61, P = 0.022), protein (OR
1.3; 95%CI 1.03-1.64, P = 0.026), and fat (OR 1.3; 95%CI 1.05-1.66, P = 0.016). 66

Previous studies conducted in various regions in Indonesia found several risk factors associated
with lower HAZ. In 2004, a study in North Maluku, a rural eastern part of the country, included
2,168 children 0-59 months of age. The authors found that older age, male gender, number of
family meals per day (< 2 times), and income at the lowest tertile were risk factors for lower
HAZ. 67 Another longitudinal study in rural villages of West Java followed 318 infants from 18
weeks of gestation until at least 1 year of age. In the study, predictors of lower HAZ were low
quality of housing, neonatal length lower than expected/normal, insufficient complementary food
consumed, low maternal heights, and interestingly low fruit intake. 68

Sari et al (2010) assessed the relationship between stunting and non-grain food expenditure at the
household level using the Nutritional Surveillance System (NSS) in Indonesia that was
implemented from 1999 to 2003. 69 This study included 446,473 children 0-59 months of age
from rural and 143,807 from urban poor areas in Indonesia. They found that households in both
areas that spent a smaller proportion of food expenditure on non-grain foods, in particular foods
of animal sources were more likely to have a higher prevalence of stunted children. 69 Using the
NSS dataset, Semba et al, 2011 assessed determinants of stunting among children 6-59 months of
age. These authors found that maternal age < 24 years, low maternal education status, child
receiving deworming medication in the 6 month period prior to the survey, history of diarrhea in
7 day period prior to survey, father with smoking history, more than 4 individuals eating meals

14

from the same kitchen, and less weekly per capita household expenditure increased risk for
stunting. 70 Semba et al (2011) also reported that risk of stunting decreased with consumption of
fortified milk, consuming fortified noodles only in rural areas, older age group (24-59 months),
tall maternal height, receiving vitamin A in the 6 month period prior to the study primarily in
rural areas, improved household latrine that allows for the safe disposal of human excreta, use of
iodized salt, and greater expenditure in households on plant and animal food. 70

A cross-sectional study among children 1-5 years of ages in Cianjur rural district, a West Java
province showed that the prevalence of stunting tended to be greater for children with low
participation in Health and Nutrition Integrated Service Centers (called Posyandu) (46.4%) than
in children with high participation (39.5%). 71 Posyandu is a community-based healthcare center
which provides basic health services, such as family planning, mother and child health, nutrition
(growth monitoring, supplemental feeding, vitamin and mineral supplementation, and nutrition
education), immunization, and diarrhea disease control. Government subsidized service is
conducted every month in every village level and mainly supported by volunteers from the
surrounding villages with supervision from health providers from the sub district primary health
center. 72,73 Children with lower participation were also more likely to be wasted (14.9%) than
children with higher participation (8.4%) and the prevalence of wasting among boys tended to be
higher than among girls in both high and low participation groups. 71 This might be partly
explained by an increase of bio-vulnerability of the male gender, but the detailed mechanism
needs further investigation. 61

A study conducted with 80 children 6-60 months of age in 2 resettlement villages in the eastern

15

rural province of Nusa Tenggara showed that the WHZ improved significantly from a mean ±
SD of -1.7± 0.9 in March (wet season) to -1.3±0.9 in November (dry season) (p<0.001). There
were no significant changes in height between wet and dry seasons. Prevalence of wasting was
42% in March (dry season) and 19% in November (wet season) (p<0.001). 74 This high
prevalence of wasting in the dry season and improvement in November suggests acute
deprivation followed by an improved food supply. 74 In this rural area, the farming period is
affected by climate changes between seasons thus during the dry season with minimum or no
irrigation, farmers face challenges in planting. 74

2.3 Factors Associated with Undernutrition in Children Under-five Years
2.3.1 Child Specific Factors
2.3.1.1 Dietary intake
2.3.1.1.1 Breastfeeding
Breastfeeding is the method of feeding a baby with milk directly from the
biological mother’s or other caretaker’s breast. 13 The importance of breastfeeding
is widely known. An optimal practice of breastfeeding may reduce child mortality
by up to one million each year worldwide. 35 WHO recommends exclusive
breastfeeding –that is feeding a baby only breast milk- for the first 6 months of
life and feeding age-appropriate complementary foods with continued
breastfeeding at least up to 2 years of age. 75 Data from the previous demographic
and health survey in Indonesia (IDHS) in 2007 showed only 43.9% of Indonesian
infants were breastfed within one hour after birth with exclusive breastfeeding as
low as 32.4%. 23

16

In Indonesia, giving food or drink other than breast milk for the first three days of
life, also known as prelacteal feeding, is very common (65% of babies). 23 Most
of pre-lacteal food or drink includes formula (66.5%), and 28.6% of babies
receive honey. Additional food or drink is suggested mostly by health care
providers such as midwives and nurses (54.3%); only 16.5% mothers make
feeding choice by themselves. 24 This practice typically occurs due to the
misunderstanding of the natural progression of lactogenesis where breast milk per
se is preceded by colostrum and mothers report concern that “breast milk is not
coming out” (51.1%), baby does not stop crying (23.35%), and that breast milk is
perceived as insufficient to satisfy the baby (11.25%). 76 Most of the infants
receiving formula milk are delivered in health care facilities such as hospitals,
midwifery clinics or a maternity clinic where samples of formula milk are either
given out, free, or sold. 24

The marketing efforts by infant formula companies have hence likely contributed
to decreasing breastfeeding in Indonesia. 76 Formula milk is frequently advertised
on television and billboards as a superior food, which is nutrient dense. Health
centers welcome the sales representatives who promote formula in their facilities.
24,76

Infant formula companies also gain new customers during emergency

situations through free donations of formula following natural disasters such as
the Yogyakarta earthquake in 2006 in the Indonesian western region during which
time formula use increased (from 32% to 43%). 77

17

Giving breast milk and formula interchangeably or just feeding formula is also
very common in Indonesia (56.1%) since there is the perception that it is only
poor mothers who do not give at least some infant formula to their babies. 24
Therefore, to increase social acceptance and decrease the likelihood of being
stigmatized as “poor”, mothers feel the necessity to appear to be “trendy”.
Formula introduction may also unfortunately result in early termination of
breastfeeding. 24 Working moms also face another problem with regard to nursing
their children since the maternity leave of 3 months is not adequate to support
exclusive breastfeeding for 6 months as recommended by WHO (2015) 75, and
there is a lack of breastfeeding-friendly workplaces. 24

The Indonesian Minister of Health issued a decree on exclusive breastfeeding
through 6 months in 2004, but the implementation is still limited. 76 Most of the
breastfeeding programs are for health staff training in lactation management and
immediate breastfeeding promotion, but some resistance from the staff has
occurred with regard to implementation because of the perception that the activity
requires extra time and resources. 24 Therefore, data that indicate the need to
support breastfeeding programs will be helpful in addressing serious
breastfeeding problems, especially among low income families.

18

2.3.1.1.2 Complementary feeding
“Complementary feeding is defined as the process from when breast milk alone is
no longer sufficient to meet the nutritional requirements of infants, and therefore
other foods and liquids are needed, along with breast milk”. 13 Another definition
from WHO was all solid, semi-solid, liquid food and drink given along with
breast milk. 78 One of the primary strategies for overcoming nutrition problems,
specifically stunting, is healthy complementary feeding. 24 For children 6–23
months of age, the appropriate feeding practice is to continue breastfeeding with
semi-solid foods with adequate dietary diversity 2–4 times a day by including 4 or
more food groups. 79 Complementary feeding is crucial as breast milk is no longer
enough to meet the nutritional needs of the infant especially for iron, and could be
associated with growth impairment as well as increased risk of disease and
infection through unclean food and/or drink. 80

In Indonesia, complementary food is typically given as early as 3 months of age
24

, even though WHO recommends commencing at 6 months of age. 13 After the

milk “comes in”, mothers then breastfeed exclusively for 3 months, as this is the
length of maternity leave for working mothers mandated by Indonesian law. They
later go back to the workplace, where there is generally a lack of support for
expressing, storing, and maintaining their milk supply. 76 Typically infant
formula, regular cow’s milk, and water will be introduced at 3 months of age. 24
In addition, other complementary food is also offered at about 3 months such as

19

fruit juice, porridge, smashed fruit, and honey. 24 All these practices reduce breast
milk consumption.

Less than 50% of children 6-23 months of age in Indonesia received
complementary food from at least 4 food groups as recommended by WHO in
2007 25, and 23% of children 6-23 months of age had an energy intake below 70%
of the Indonesian Recommended Dietary Allowance (RDA) for this age group. 26
Therefore, there is likely a strong association between complementary feeding
and child nutrition status in this vulnerable age range.

Poor complementary feeding was defined as not following WHO (2007)
recommendations for complementary feeding which are: 1) Introduction of
complementary feeding at 6-8 months of age, 2) Minimum dietary diversity,
receiving foods from at least four food groups within the last 24 hours, 3)
Minimum meal frequency of complementary food at least 2 times a day for
breast-fed infants 6-8 months of age, 3 times a day for breastfed children 9-23
months of age, and 4 times a day for non-breastfed children 6-23 months of age,
4) Minimum acceptable diet - children 6-23 months of age who received a
minimum dietary diversity and minimum meal frequency during the previous day.
25

The determinants for poor complementary feeding among children 6-23 months

of age in Indonesia were deemed as older age of child, poor household, lower
education of mothers, illiterate mothers, lower likelihood of exposure to
newspapers or magazines, lower television watching, rural residence, resident in

20

the Java and Bali regions in the western and southern part of the country, mothers
who were no longer married, and female gender of baby. 25 These researchers
conducted a secondary data analysis from IDHS in 2007 to assess complementary
feeding practices and identify the potential risk factors associated with
inappropriate complementary feeding in Indonesia using individual-level,
household-level, and community-level factors.

A common complementary feeding practice in Indonesia is commercial instant
“baby food” such as cereal and snacks. As many as 45-70% of children 4-5
months of age consume this type of food, alone or in combination with other
foods such as home-made puree. 81 Sole consumption of instant baby food may
increase risk for nutrient deficiencies since this type of food often contains high
amounts of sugar, but lacks protein and micronutrients. 24 There is no regulation
to fortify “baby food” in Indonesia with micronutrients such as iron. 82 Iron in the
body stores at 6 months of age and the amount of iron in breast milk are no longer
sufficient to meet the requirements of infants when they meet 6 months of age . 35

2.3.1.1.3 Specific food group intake
Indonesian diets for children under-five years of age generally tend to be low in
terms of energy, micronutrients, fatty acids, and protein content and
bioavailability of micronutrients is often poor. 24,83 Children’s diets mostly consist
of non-fortified cereals with a small amount of vegetables and animal protein. 84

21

As few as 23% of children 6-8 months of age had sufficient iron consumption due
to a lack of variety in their intake measured by the dietary diversity score. 85
Relative to food group intake, snack foods are an interesting caveat of concern in
the diets of young children. A study was conducted on children 1-12 years of age
in a rural village of West Java in the western region of Indonesia using food recall
surveys for all meals and snack foods consumed in 7 consecutive days for each
subject. 27 In this study, snack foods were classified into: 1) modern snacks (2
kinds of salty chips made from flour), 2) Traditional snack foods (e.g., nuts or
seeds; fried chips made from cassava, banana, or seed of Gnetum gnemon; sweets
made from coconuts, sweet beans, flour or rice, and fritters), 3) candies and
desserts; and 4) soft drinks (e.g., sweetened carbonated beverages and fruit
drinks). These types of snacks often contribute to fat, salt and sugar intake, but
lack essential nutrients such as vitamin and minerals. The mean percent
contribution of snack foods was 59.6% for fat, 40.0% for energy, 20.6% for
calcium, and <10% for vitamins A and C. Frequent and unhealthy snacking habits
contributed to low diversity of children’s diets. Frequent inappropriate snacking
may suppress a child’s appetite and prevent children from being receptive to more
complete nutritious meals. 27

2.3.1.2 Role of diseases
The leading cause of illness of children under-five years of age in Indonesia is infectious
diseases such as acute respiratory infection, pneumonia, and viral gastroenteritis. 23 There
is a clear correlation between infectious diseases and undernutrition. One of the common

22

symptoms associated with gastrointestinal infectious diseases in Indonesian young
children is diarrhea which is mostly caused by rotavirus infection as a result of poor food
hygiene practices. 86,87 Diarrhea rates were highest among children 12-23 months of age,
which was 9.7% (The National Institute of Health Research and Development, 2013).
This may be attributed in part to food contamination in conjunction with complementary
feeding. 88 The most recent IDHS in 2013 combined the age groups under 6 months and
6-12 months of age when reporting diarrhea incidence. Solid food preparation definitely
increases the chance of contamination compared to breastfeeding. 88 Diarrhea affects
nutritional status in several ways: (1) reduced appetite, which leads to reduced dietary
intake; (2) increased nutrient loss via frequency of defecation; (3) decreased intestinal
transit time which leads to poor absorption of nutrients; (4) acceleration of basal
metabolic rate which leads to increased protein catabolism. 89 The risk of stunting
increases with frequent episodes of diarrhea. 90 Infectious diseases like diarrhea will
reduce the nutrient absorption of the children and when it occurs repeatedly, it may
prohibit linear catch-up growth over the long-term and result in permanent stunting. 46

2.3.2 Maternal Factors
2.3.2.1 Mothers’ dietary intake
The link between diet and nutritional status of a child and the mother is an important
consideration. Studies in developed countries suggest that maternal dietary patterns
influence children’s diets. 91–93 Researchers in the United States of America (US), in a
study among 98 low-income African-American mothers with children 6-18 months,
found that maternal food intake was a positive correlate of child’s food intake. 91 The

23

study found that the children’s intakes of fruit, vegetables and snack foods were
positively associated with maternal intake of each of these foods, respectively. 91 A
longitudinal study in the US among low-income, African American adolescent mothers
that followed children 13 months of age for 1 year of showed that maternal and toddler
fruit, vegetable, snack, meat, dairy and soda intake were positively correlated. 92
Robinson et al (2007) conducted a prospective study in the United Kingdom (UK) among
1,434 infants 6 and 12 months of age and their mothers. They found that the key
influence on the infant diet was the quality of the maternal diet. Women who complied
with dietary recommendations overall were more likely to feed their infants comparable
diets. 93 The mother’s diet independently accounted for almost a third of the variance in
the child’s dietary quality in another study, also conducted in the UK. 15

When nutrient rich foods such as fruits and vegetables are considered, the positive
association between maternal and child (6-24 months) dietary quality was not however
seen in developing nations such as Bangladesh, Vietnam and Ethiopia. 20 This multicountry study was done to examine agreement and association between maternal and
child dietary diversity and identify determinants of maternal and child dietary diversity
using mother-child dyads. A strong positive association was seen between maternal and
child dietary diversity score, however the disagreement in mother/child intake for fruit
and vegetables could be attributed to the fact that some mothers believe that vegetables
and fruit are difficult to digest and can cause stomach illness or abdominal pain. 94 Also,
lack of familiarity on alternative food preparation may lead to mothers not giving their
children some traditionally prepared vegetables that contain spices, which are assumed to

24

be too spicy for young children. 95 It is not known if this lack of association for fruits and
vegetables is also the case for Indonesia.

2.3.2.2 Mothers’ anthropometric measurements
Regarding growth of the child, maternal height is an important determinant of children’s
HAZ. 96 A study in Indonesia found that lower maternal height was a positive predictor of
lower HAZ among infants up to one year of age, 68 while higher maternal height appeared
to be protective of low HAZ in children 6-59 months of age. 70 The biologic plausibility
more likely includes genetic and non-genetic factors, and may involve nutrition-related
intergenerational effects on growth and the mechanics of a reduced space for the fetus to
grow. 40,97 There are also socio-cultural factors such as the intergenerational transmission
of poverty that influences dietary intake for both mother and child, which may be related
to anthropometric status for both. 97

Intra-uterine Growth Retardation predicts individual final height as shown in a
longitudinal study in France. 98 This study included full-term singleton subjects born with
IUGR matched with their non-IUGR counterparts. Heights were measured before and
after puberty. A significant deficit in final height was found in those who had IUGR
compared with the non-IUGR subjects ranging from -4.0 cm for males and -3.6 cm for
females.

Researchers investigated a subsample of the Early Childhood Longitudinal Study-Birth
Cohort, which was a national sample of US children born in 2001 and found that IUGR is

25

a risk for stunting at age of five years. 99 Additional risk factors included inadequate
weight gain in the mothers who smoked during pregnancy and mothers who were short.
99

A review paper reporting findings from studies in different countries (Brazil, Guatemala,
India, the Philippines and South Africa) indicated that IUGR was associated with shorter
height in the mothers. 100 Subjects were recruited before pregnancy in India, during
pregnancy in the Philippines and South Africa, and at birth in Brazil and Guatemala.
Outcomes were measured in adolescents in South Africa and in adults in the other sites.

Schmidt et al also found that maternal weight was a predictor of WHZ scores among
children 12-15 months of age. 68 The researchers followed newborn infants from 9 rural
villages in West Java, Indonesia until 12-15 months of age and found that lower maternal
weight predicted lower WHZ and vice versa. 68

2.3.2.3 Mothers’ socio-demographic characteristics
Several maternal socio-demographic factors may influence the diet and nutritional status
of children. This is true for both developed and developing countries. These include
race/ethnicity, age, educational status, and type of employment. A recent study in the US
showed that dietary patterns of children varied according to the racial, ethnic and
educational backgrounds of their mothers. 101 At 12 months, infants of mothers who had
low education or who were non-Hispanic African American mothers (compared to nonHispanic white) had a higher score on unhealthy dietary patterns. Semba et al conducted
a study in Indonesia using data from the Nutritional Surveillance System in Indonesia

26

from January 1999 to September 2003 for children 6-59 months of age. This survey was
done to monitor public health problems and guide policy decisions. They found that
maternal age < 24 years and maternal low education were risk factors for low HAZ
scores in children. 70

Researchers who conducted a community case control study in South Ethiopia among
children 24-59 months of age, found that children whose mothers worked as merchants
(Adjusted OR = 4.03, 95% CI: 1.60-10.17) were more likely to be stunted than children
whose mothers were housewives. 102

In contrast, a study in Vietnam in 2007, which used a cross-sectional survey among 607
mother-child (0-59 months) pairs found that the children of mothers who were farmers or
housewives were at greater risk for both stunting and wasting compared to when mothers
were civil servant officers. 99 In different a study in the mountainous region in Vietnam,
mother’s education of primary school or lower was a risk factor for stunting, but not
wasting when compared to mother’s education of senior high school or higher. 103

In Indonesia, the high rate of female labor force participation which was 54% of the
female population 15-64 of age from 2006 to 2015 may influence the relatively high rate
of stunting among Indonesian children under-five years of age. 104 A survey in a lowincome community in the urban part of Indonesia showed that the children of nonworking mothers had significantly higher HAZ scores than those of working (all types of
employment) mothers. 105

27

2.4 Implications of Undernutrition in Children Under-five Years
Each year, at least 2.6 million children die or more than a third of all deaths are associated with
undernutrition in the world. 35

Any degree of undernutrition contributes significantly to mortality. 106–108 Undernutrition can
depress immune systems in young children and increase their susceptibility to infections and in
many instances to death from common illnesses such as pneumonia, diarrhea and malaria. 29,35
Compared to their well-nourished counterparts, children with undernutrition are hence up to 10
times more likely to die from an easily preventable or treatable disease. 37

In addition, early life stage undernutrition, may interestingly also increase risk for overweight or
obesity as well as some types of diet-related chronic diseases such as diabetes and cardiovascular
disease at a later age. 9,109 The underlying mechanism is unknown, but it may involve links
between weight status in childhood and body composition in later life. 110 Children who were
thin at birth or early childhood, but experience a rapid weight gain after late childhood have a
predominantly increased fat mass. 111,112 Both undernutrition and overweight/obesity in utero and
early childhood have been shown to be associated with increased risk for diet-related disease
later in life. 114-116

Growth failure or more specifically stunting, during the first two years of life is irreversible and
will continue to exhibit itself in the form of a compromised height through adulthood as well as
potentially impact the birth weight of the next generation. 9,38 The biologic plausibility includes

28

genetic and non-genetic factors, involving nutrition-related intergenerational effects on growth
and the mechanics of a reduced space for the fetus to grow. 40,97 There are also socio-cultural
factors such as the intergenerational transmission of poverty that influences dietary intake for
both the mother and child. 97

Attained height in adolescence and adulthood has a potential to serve as a proxy measure for
several things including the following: an adolescent’s social skills 113, adult cognitive ability
114,115

, adult social class 116 or adult health in general. 117 Height in turn is an indicator of health

and nutrition in early childhood, which effects on cognitive development. Combined with the
childhood environment, cognitive development affects educational attainment, which can later
affect occupational choice and income 115 as shown in the conceptual framework for malnutrition
if Figure 1. 31

More specifically undernutrition during childhood is associated with lower test scores, decreased
productivity and hence also with reduced adult income. 9,118 Undernutrition has been shown to be
associated with reduced dendrite density in the hippocampus of the brain, which is responsible
for long-term memory, and likely impacts test performance. 119 From a productivity perspective,
long-term consequences of these neurological effects have been shown in adults. Adults with a
history of being undernourished as children have low scores on tests of attention, vocabulary,
non-verbal cognitive ability and working memory. 9,118,120 This likely impacts the type of
employment and hence earning capacity. An estimated 20% loss on earning occurs for adults in
developing countries who were undernourished as children compared to those who were wellnourished 35. The direct cost of child undernutrition worldwide is $20 to $30 billion per year. 105

29

2.5 Nutrition Programming in Indonesia
The Indonesian government has been engaged in nutrition intervention efforts for over 30 years
with a focus on protein energy malnutrition, vitamin A deficiency, iron deficiency anemia and
iodine deficiency disorders. 73,121 The Ministry of Health is currently undertaking a national
program called Community Management of Acute Malnutrition to Manage Wasting and
Underweight specifically for children since the national level of child undernutrition is still high.
With this program, local health centers provide 90 days of supplemental food (fortified cookies
and milk or sometimes sachets of packaged, fortified complementary food) to children diagnosed
with wasting or are underweight. Children 6-59 months of age are screened using a growth card
distributed at local community health centers. Diagnosis is made if the WHZ or WAZ scores are
below -2. 122 Another national program called MP ASI (Food Supplementing Breastfeeding) is
also being administered by the Ministry of Health to enhance nutrition in children under-five
years from poor families. For this program, all children 6-59 months of age who visit local
community health centers for monthly growth monitoring receive the food supplementation
made from local food. 122 However, the coverage of this program is low and it has not been
shown to be successful in those in greatest need. 123 The government of Indonesia also has a
program that distributes rice to poor families (RASKIN). The goal of this program is to allocate
20 kg of rice to 9 million poor households across the country per month, but this program has
also not been well delivered. 24

From the nutrition education perspective, a government program called Keluarga Sadar Gizi
(Nutritionally Aware Families) is a campaign to improve nutrition behaviors among families

30

with children. 122 The objectives include monitoring growth of children, under-five years,
promoting exclusive breastfeeding for 6 months and continuing to 2 years, encouraging
consumption of a variety of food in adequate amounts using the Indonesian food pyramid as a
guide, interesting the use of iodized salt and administering a high dose of vitamin A twice a year
for children aged 6 months to 5 years in local community health centers by nurses. The
monitoring for this program is however somewhat not clear. 122 Micronutrient programs by the
Indonesian government are twice-yearly vitamin A supplementation for children under-five years
of age at community health centers, and fortification of flour with multi-micronutrients, oil with
vitamin A, and salt with iodine. 24

Government programs which specifically promote maternal nutrition are very scarce. The only
current ongoing national programs available are supplementation of iron and folate during antenatal care and post-partum supplementation of vitamin A. These two programs however are
underutilized. 124

There are some complementary feeding promotion programs conducted by the United Nations
(UN) and non-government organizations (NGOs). Examples include CARE’s efforts to improve
breastfeeding and complementary feeding in the rural province of Nusa Tenggara Timur, and the
Mercy Corps program to raise awareness and support mothers to practice and promote exclusive
breastfeeding in the urban province of Jakarta and the rural province of Maluku. 24
Unfortunately, these programs are only local and, not national. 24

Although the Indonesian government remains committed to nutrition intervention efforts, the

31

scope and magnitude of success of nutrition programs have unfortunately been limited
warranting the need for continued and enhanced efforts. This is especially true from a maternal
perspective as well as the need to identify areas and facilitators to success. Multiple level policy
systems and environmental changes are needed. Findings from this dissertation add to the body
of literature regarding maternal and infant nutrition challenges that need to be addressed.

32

CHAPTER 3 – METHODS

The current research project is guided by the Human Ecological Model. 125 This model was
selected because it represents the multilevel depiction of factors described in the literature review
that can impact child nutrition status. The human ecological model also fits in well with the
conceptual framework for the determinants of malnutrition as shown in Figure 1 earlier by
Haddad 2014 and was adapted to reflect both (Figure 2). At the core of the model is child
nutrition status, which is first impacted by individual factors such as birth weight, health status,
psychological factors, genetics; family (parent/s and household factors); and community (e.g.
food accessibility, safety and health services). These are all in line with the Conceptual
Framework for the Determinants of Malnutrition as shown in Figure 1 earlier.

Figure 2. Adapted human ecological model of child nutrition status 31, 125

33

Figure 3 depicts a proposed model of the postulated interplay of the purported factors presented
in Figure 2, which could influence child nutrition and child nutritional status in Indonesia.

Figure 3. Conceptual framework for factors that influence child nutrition status (stunting and
wasting) 126
Household
factors
Family
Expenses
(c)

# of
household
members
(c)
Gender of
household
head (c)

Maternal factors

Individual factors
Age, sex, birth
weight(c)

Weight
status (1)

Dietary
intake (1)

Child
Stunting/
Wasting

Dietary
intake
Complementary
feeding (2)

Age,
education,
occupation(c)

Breastfeeding(2)
Unhealthy
snacks (2)

d
Residency
(c)

Legend: Arrows represent cause-and-effect relationships; the solid lines represent well-known
relationships, dotted lines represent probable relationships
C = covariates; 1= Specific Aim 1; 2= Specific Aim 2
Source: Patrick and Nicklas, 2005 126

The significant immediate factors that influence child stunting and wasting, especially for young
children, are classified as child’s dietary intake that includes complementary feeding,

34

breastfeeding and consumption of unhealthy snacks. Maternal factors including mother’s dietary
intake were hypothesized to have indirect effects on child’s dietary intake (Specific Aim 1).
Child’s dietary intake as a whole is widely known to have a direct effect on child stunting and
wasting. However the specific child dietary intake components such as breastfeeding and
complementary feeding practices (Specific Aim 2) relative to child stunting/wasting have not
been studied for this target population.

3.1 Dataset
The data used in this study was drawn from the Indonesian Demographic and Health Survey
(IDHS) in 2010. The survey was conducted by The Ministry of Health in all 33 provinces of
Indonesia, and aimed to evaluate the extent to which Indonesia was achieving the WHO
Millennium Development Goals. 3 These goals specifically include: 1) eradicating extreme
poverty and hunger, 2) achieving universal primary education, 3) promoting gender equality, 4)
reducing child mortality, 5) improving maternal health, 6) combating HIV/AIDS, malaria, and
other diseases, 7) ensuring environmental sustainability, 8) developing a global partnership for
development. Multi-stage sampling was used with the sampling frame taken from the National
Census conducted by the National Statistical Bureau in 2010. Every district/city that was
included in the sampling frame had a number of proportional census blocks representing the
number of households in a related district/city. There was total of 2,800 census blocks from 441
districts/cities. The possibility of a census block to be included in the sample within the
district/city was proportional to the number of households in a district/city (probability
proportional to size). From every chosen census block, 25 households were randomly selected.
All members in the chosen household generated the individual samples.

35

The data set provides a valuable and effective source of data for mother and child nutritional
information from a representative national household sample of 69,300 households. The data
collection was based on two main questionnaires: the Household Questionnaire and Individual
Questionnaire. Copies of both the Indonesian and English translated version of the questionnaire
are included in Appendices 3 and 4 respectively.

Although human subject approval was not required due to the fact that the IDHS data set is
viewed as public information and deemed automatically exempt, approval was electronically
obtained from the IDHS administrators (Appendix 1).

Data in the Household Questionnaire included: a) location information (11 variables), b)
household information (4 variables), c) data collector information (6 variables), d) household
member information (13 variables), e) health service facility (18 variables), f) sanitation (20
variables), g) household expenses (39 variables). Data in the Individual Questionnaire included
for each member in the household : a) subject identification (4 variables), b) history of
communicable diseases: malaria (10 variables) and lung tuberculosis (9 variables), c) knowledge
and attitudes (22 variables), d) reproductive health which consisted of: female reproductive
information (6 variables); fertility information (11 variables); family planning (8 variables);
pregnancy/delivery/post-partum period information (41 variables); abortion and unwanted
pregnancy (10 variables); sexual behavior (6 variables), e) child health information which
consisted of: infant and under-five children health information (22 variables), breastfeeding and
complementary feeding (10 variables). In addition to data from these 2 questionnaires, data
included 24-hour dietary recalls for each dyad, anthropometric measurements for each dyad, and
biomedical examination (7 variables) for a selected subsample of households. Biomedical data

36

was collected for a sub-sample from 2,800 census blocks that represented the national
population, which was 823 census blocks. For every household that was selected for biomedical
testing, each member had a blood test for malaria and all members who were 15 years or older
also had a sputum test for lung tuberculosis.

Trained data collectors interviewed the household head or other adult member in the household
who provided information for the household questionnaire. All individuals who were 15 years or
older were interviewed for the individual questionnaire. Children under 15 years of age or
unhealthy family members were represented by other household members who identified as the
primary caretaker.

Anthropometric measurements were done in accordance with WHO standard by trained data
collectors. 127 Height was measured using a measuring board (brand “Multifungsi”) which was
placed on a flat, stable surface such as a table. For all children, length was measured in the
supine position with the child’s eyes looking straight up (recumbent). For mothers, height was
measured while standing upright with eyes looking straight ahead. All measurements were done
without shoes to the nearest 0.1 cm. Weight was measured to the nearest 0.1 kg with light
clothing using a digital scale (brand “AND”), which was calibrated every day. The scale was
placed on a flat, hard, even surface such as a tile floor without carpet. Child’s weight was
measured with the mother carrying the child then subtracting the result from the mother’s weight
without the child. It was a single measurement.

37

In this IDHS, 99.1% of the 69,950 households and 251,388 individuals were successfully
interviewed, which comprised 94.3% of 266,510 eligible individuals. Eligible individuals were
all members in selected households.

3.1.1 Study Sample
Children 6-23 months of age were included if measurements of weight, height and dietary
intake were also obtained and plausible with that of their mothers. Of specific interest was
child-mother or primary caregiver dyad for the purpose of this study. All of the caregivers
were mothers when initial descriptive analyses were run. A total of 4,056 mother-child (6-23
months of age) dyads were identified; 1,599 (39.4%) were excluded when: the child was
exclusively breastfed (n = 90), since they would not have complementary feeding
information, the mothers could not be matched (n = 349), some values were implausible (n =
980) such as mother’s age was not biological possible to have children under 2 years of age,
mother’s weight or BMI were too small, mother’s energy intake was < 500 kcal or exceeded
5,000 kcal, child’s energy intake was 0 or > 2,500 kcal, child’s HAZ or WHZ <-6 or > 6
(Figure 4), and child had missing weight/height data (n = 180). The final sample size after
data cleaning was 2,457 mother-child dyads (Figure 4).

3.1.2 Steps in Data Preparation
After cleaning the data, variables were selected based on the specific aims including the
covariates. Data were then translated to English from Indonesian and assigned new variable
names with explanatory labels. Creating new variables such as: mothers’ BMI based on
mothers’ weight and height; child’s HAZ and WHZ based on child’s height and weight, child

38

was currently being breastfed or not based on the 24-hour dietary recall. Then categories of
continuous data were created including categorizing the household expenses into 3 groups of
low, medium, high, based on tertiles; number of household members into 2 groups of < 4 and
> 4 persons; mothers’ age into < 20, 20-29, 30-39, > 40 years; education into <6, 6-11, > 12
years; mothers’ occupation as stay at home or working mothers; mothers’ BMI into <18.5,
18.5-22.9, 23.0-27.4, > 27.5, child’s age into 6-11, 12-17, 18-23 months, birth weight into
very low birth weight (< 2,000 g), low birth weight (2,000-2,499 g), 2,500-2,999, 3,0003,499, > 3,500; mothers and child’s mean dietary diversity scores (MDD) into adequate
versus not adequate; mothers’ energy intake into low, medium, high based on tertiles, initial
breastfeeding into < 1 and > 1 hour; introduction of complementary feeding into < 6 and > 6
months; and consumption of unhealthy snacks into low, medium, high based on tertiles. The
weighting factor included in the dataset was activated before do the analysis.

39

Figure 4. Flow chart of study sampling
Children 6-23 months of age
(n=4,056)

Children exclusively breastfed
(n=90)
Children with missing height
(n=116) or weight data (n =64)
Children with same mothers
(n=349)

n= 3,437

Moms age > 53 yo (n=10)
Moms weight < 20 kg (n=5)
Moms BMI < 13 (n=1)
Moms energy intake < 500
(n=102) or > 5,000kkal (n=18)
Child energy intake =0 (n=2) or
>2,500 kkal (n=490)
Child HAZ or WHZ < -6 or > 6
(n=352)

n=2,457

3.2 Variable Definition and Operationalization
3.2.1 Primary Variables of Interest
3.2.1.1 Child Nutritional Status
The heights (length) and weights of each child in centimeters were transferred into
WHO Anthro Plus software version 3.2.2 (WHO, 2011). This software was used to
calculate the HAZ and WHZ scores of the study population based on WHO standards.
127

The HAZ and WHZ scores were depicted as standard deviation (SD) units from the

median of the reference population. Children with scores of < -2 SD units below the

40

median height-for-age of the reference population were considered short for their age
(stunted) and children with scores < -2SD units below the median weight-for-height of
the reference population were classified as wasted. The reference population was taken
from the WHO multicenter Growth Reference Study (MGRS) in 1997-2003. The
children in this population were healthy children living under conditions likely to
favor achievement of their full genetic growth potential and coming from different
several countries: Brazil, Ghana, India, Norway, Oman and the USA. 127

3.2.1.2 Maternal Nutritional Status
Mother’s weight status was determined by using the classification of adult weight
status for Asian populations based on WHO determined cut points for body mass
index calculated from the weights and heights reported in the database: BMI < 18.5,
18.5-22.9, 23-27.4, and > 27.5 for underweight, normal, overweight and obese
categorization respectively. 128 BMI was calculated as weight (in kilograms) divided
by height squared (in meters).

3.2.1.3 Maternal Dietary Intake
Maternal dietary intake quality was determined from single 24 hour recall data in the
IDHS. Data was coded into food groups in order to calculate minimum dietary
diversity (MDD) scores for women (MDD-W) as recommended by the Food and
Agriculture Organization (FAO) in 2014. 129 This score (MDD-W) provides a global
dietary diversity indicator for women, especially those from less developed countries
129

. The food groups were categorized as follows: 1) all starchy staple foods, 2) beans

41

and peas, 3) nuts and seeds, 4) dairy, 5) flesh foods, 6) eggs, 7) vitamin A-rich dark
green leafy vegetables, 8) other vitamin A-rich vegetables and fruits, 9) other
vegetables, 10) other fruits. This 10 food group method was chosen because it had a
stronger relationship to micronutrient adequacy than other with different groupings. 129
The response options were “consumed” (score=1) or “not consumed” (score=0). The
MDD-W was a simple sum of the scores for 10 categorized food groups and thus
ranged from 0 to 10. An adequate MDD-W is defined as mothers consuming at least 5
food groups according to FAO. 129

MDD-W was classified dichotomously as adequate versus not adequate for further
analysis. Calorie intake from the IDHS was taken into account in analyzing the
mothers intake. Chi-square tests were performed to assess the relationship between
MDD-W and calorie intake. The calorie intake is important because it is a proxy of
the household food security. 129

Mother’s weight status was determined by using the classification of adult weight
status for Asian populations based on WHO determined cut points for body mass
index calculated from the weights and heights reported in the database: BMI < 18.5,
18.5-22.9, 23-27.4, and > 27.5 for underweight, normal, overweight and obese
categorization respectively. 128 BMI was calculated as weight (in kilograms) divided
by height squared (in meters).

42

3.2.1.4 Child Feeding Practice
The child feeding practices were assessed using the latest recommendation by WHO
in 2010 which applied to children 6-23 months of age based on 24-hour recall data
and are described as follows:
1. Early initiation of breastfeeding: children born in the last 24 months who were put
to the breast within one hour of birth.
2. Introduction of solid, semi-solid or soft foods: infants who received solid, semisolid or soft foods at 6-8 months of age.
3. Children ever breastfed: children born in the last 24 months who were ever
breastfed. Breastfeeding was deemed the method of feeding a baby with milk directly
from the biologic mother’s or other care taker’s breast.13
In addition to the complementary feeding practice, the current status of breastfeeding
was also assessed, defined as children within the last of 24 hours who received any
breast milk.

3.2.1.5 Child Dietary Quality
Child dietary quality was measured as minimum dietary diversity scores (MDD) and
unhealthy snack consumption. Minimum dietary diversity (MDD) pertained to
children 6-23 months of age who received foods from four or more food groups
within the past 24 hours. Seven food groups were used in this calculation as
recommended by WHO:
a.

grains, roots, and tubers

b.

legumes and nuts

43

c.

dairy product (milk, yogurt, cheese)

d.

flesh foods (meat, fish, poultry and liver/organ meats)

e.

eggs

f.

vitamin-A rich fruits and vegetables

g.

other fruits and vegetables

The 7 food groups have been identified based on research showing the critical
importance of each in the complementary feeding diet. 78

Unhealthy snacks in the IDHS were defined as ready-to-eat snacks consumed at any
time during the specific age period. These unhealthy snacks did not include fresh fruit
and vegetables, but those which are usually high in salt, fat and sugar, while low in
micronutrient content.

Unhealthy snack food groups were Indonesia specific and classified according to
Adair and Popkin 129 and Sekiyama et al 27 to include: 1) modern snacks (e.g. stick
cheese, cheese balls); 2) traditional snacks (e.g. sweets made from coconuts, flour or
rice; and fritters); 3) candies and desserts; 4) soft drinks (sweetened carbonated
beverages and fruit drinks). Child intake of unhealthy snack food groups was
categorized into 3 groups: low, moderate, or high based on intake tertiles among
subjects.

3.2.2 Covariates
Factors that could influence stunting and wasting in children 6-23 months of age as

44

described in the literature review and provided in the dataset were included in the model as
covariates. These included: child’s age, gender, birth weight, maternal and household
factors. Maternal factors included: mother’s age, years of education, and occupation.
Mother’s age was categorized into < 20 years, 20-29 years, 30-39 years, and > 40 years to
better capture younger and older mothers. Years of education was classified as < 6 years, 611 years, and > 12 years in accordance with the education system in Indonesia that has
elementary, middle/high school then college and above. Mothers’ occupation was classified
as stay at home or employed. Household factors included socio-economic status, gender of
household head, number of all household members, and area of residency (rural versus
urban). Household socio-economic status was based on average household total expenses
per month, which was classified into 3 groups: low, medium and high based on expense
tertiles among households to better capture the difference between groups. Total number of
all household members was classified into less or equal to 4 persons and more than 4
persons based on the recommendation of having a maximum of 2 children per family by the
National Family Planning Coordinating Board in Indonesia to promote the national birth
control program. 3

3.3 Statistical Analysis
Descriptive analyses were conducted to examine the socio-demographic characteristics of the
study samples. The prevalence of child stunting and wasting categories was estimated across
different explanatory variables, and the chi-square test was used to test the statistical
significance. Participants’ characteristics were described using weighted frequency distributions
consistent with survey sampling. Weighting scores were included in the dataset as a variable.

45

Dependent variables were first treated as dichotomous thus logistic regression was used to assess
the association between child’s stunting and wasting categories to mothers MDD-W and weight
status. Multivariate linear regression was used to examine this association for all children 6-23
months of age treating child’s actual height and weight as continuous variables. Both logistic and
linear regression models controlled for covariates.

The major conceptual limitation of all regression techniques is that one can only ascertain
relationships, but never be sure about underlying causal mechanisms 131. The techniques also
require some conditions to avoid biased and/or inefficient estimates such as: 1) every variable is
measured at the interval-ratio level, each independent variable has a linear relationship with the
dependent variable, independent variables do not interact with each other and independent
variables are uncorrelated with each other. 130

As a combination between Specific Aim 1 and 2, a path model analysis was used to identify
specific factors associated with stunting and wasting in children 6-23 months of age in Indonesia
using the conceptual framework in (Figure 3). This approach was used to identify factors with
direct and indirect effects on the child stunting and wasting. Path models permit identification of
both direct effects between indicator and response variables and indirect effects that act through
mediating variables. 131 In our model building, we retained independent variables when they had
a significant (α < 0.05) direct effect on the response variable, while significant indirect effects
were also retained in the model if they were mediated through another response variable that
itself had a significant direct effect on the response variable. The total pathways are a sum of

46

direct and indirect pathways. Unstandardized coefficients were presented to examine the
significance and direction of each relationship.

Analyses, other than the path analysis were conducted using SAS software (version 9.3; SAS
Institute, Cary, NC). A P-value <0.05 was declared as statistically significant. The path analysis
was performed using maximum likelihood estimation with robust standard errors (MLR)
estimator in Mplus software (version 7.4; Muthen and Muthen, 2015), which uses a multivariate
logistic regression framework and takes the exponentials of the logistic regression coefficients
(odds ratios [OR]). Mplus integrates the statistical concepts captured by latent variables into a
general modeling framework that includes structural equation models. 132

47

CHAPTER 4 –RESULTS

4.1 Study Population
The study sample included 2,457 mother-child dyads, and represents 60.1% of all children 6-23
months of age in the IDHS survey. Characteristics of households, mothers and children in the
study are shown in Tables 1-3.

Table 1. Socio-demographic characteristics of children and mothers in the study
(N = 2,457)
Variables

n (%)1

CHILDREN
Gender
Male
Female

48.2
51.8

Age
6-11 months
12-27 months
18-23 months

31.7
34.8
33.5

MOTHERS
Education
< 12 years
> 12 years

68.1
31.9

Main occupation
Unemployed
Student
Military/Police force
Civil servant
Entrepreneur
Farmer
Fisherman
Factory worker
Other
1 Weighted percentage

55.7
0.3
0.001
5.2
11.2
13.5
0.1
3.4
10.6

48

Table 2. Dietary and nutrition status characteristics of children and mothers in the study
(N = 2,457)
Characteristics
CHILDREN
- HAZ
- WHZ
- MDD
- Frequency of snack food group intake/day
- Age (months)
- Birth weight (kg)

MOTHERS
- Age (year)
- BMI
- Height (m)
- MDD

Mean

SD

Min

Max

-1.2
-0.7
2.9
1.9
14.6
3.2

2.3
1.3
1.2
0.8
5.1
0.5

-6.0
-5.5
1
0
6
1

5.9
5.4
7
8
23
5

29.9
22.9
1.5
2.7

6.4
4.0
0.1
1.0

15
14
1.2
1

53
41.7
1.8
8

SD = standard deviation
Min = minimum, max = maximum
HAZ = height-for-age z-score
WHZ = weight-for-age z-score
MDD = minimum dietary diversity, for women according to FAO (2014) is based on intake of
10 food groups: 1) all starchy staple foods, 2) beans and peas, 3) nuts and seeds, 4) dairy, 5) flesh
foods, 6) eggs, 7) vitamin A-rich dark green leafy vegetables, 8) other vitamin A-rich vegetables
and fruits, 9) other vegetables, 10) other fruits. Adequate if > 5 groups consumed
MDD for children according to WHO (2014) is based on 7 food groups: 1) grains, roots, and
tubers, 2) legumes and nuts, 3) dairy product, 4) flesh foods (meat, fish, poultry and liver/organ
meats), 5) eggs, 6) vitamin-A rich fruits and vegetables, 7) other fruits and vegetables. Adequate
if > 4 groups consumed

As depicted in Table 1, the sample in this study included 2,457 respondents. The majority of
mothers were between the age of 20-29 years (44.3%) and 30-39 years (44.9%), with more than
two thirds having an education of less than 12 years (68.1%) and more than half, were stay at
home mothers (55.7%).

49

Children were evenly distributed across age groups of 6-11 months (31.78%), 12-17 months
(35.23%), and 18-23 months (33.5%). There were slightly more girls (51.8%) compared to boys,
but this difference was not significant.

Although data is not shown, regions of residency for the subjects were comparable between
urban (49.5%) and rural (50.5%). The majority of households examined in the present study had
a total of 4 or less household members (64.5%) with a male household head (97.4%). Mean
household monthly expenses was 2.3 million rupiahs with an SD of 2.6 million rupiahs.

Means, standard deviations (SD) and percentages for dietary, nutritional status indicators are
shown in Table 2. Means for child HAZ, WHZ, MDD and frequency of snack food group intake
per day were -1.2, -0.7, 2.9 and 1.9 respectively.

A small proportion of these children (5.1%) had low birth weight (LBW) defined as birth weight
less than 2,500g. Most of the mothers (69.9%) had a normal BMI.

Table 3 depicts the breastfeeding practices. The majority of children were ever breastfed (93.3%)
and were breastfed at the time of data collection (81.4%). Interestingly, almost one third of
babies were not fed colostrum. Despite this high proportion of breastfeeding, it was not done
exclusively as 21.9% were given complementary feeding as early as the first week of life and
65.5% were introduced to complementary feeding before the recommended age of 6 months
(Table 4). Complementary food/drink included the following: baby formula (35.4%), baby cereal
(24.2%), rice porridge (21.1%), fruit puree/juice (9.5%), regular cow milk (1.8%), water from

50

boiling rice (1.1%), and other food/drink (6.9%). Table 5 shows that both mothers and their
children had low protein intakes, which were 31.6% and 23.7% of the recommended dietary
allowance respectively. Most of the children did not have an adequate dietary diversity score
(69.3%) as defined by consumption of 4 food groups or more (Table 6). More than half of
children had consumed unhealthy snacks (58.7%). Among mothers, 96.1% did not have
recommended minimum dietary diversity scores as intake (5 food groups or more). (Mothers’
minimum dietary diversity was correlated with mothers’ BMI (p = 0.46).)

Table 3. Breastfeeding information for children 6-23 months of age in the study (N = 2,457)
Variables

%1

Ever being breastfed
Yes
No

93.3
6.7

Currently being breastfed2
Yes
No
Missing data

81.4
17.1
1.5

Mother treatment of colostrum
Given to baby
70.6
Discarded
29.4
1 Weighted percentages
2 Being breastfed within 24 hours prior to survey

51

Table 4. Complementary feeding1 practices for children 6-23 months of age in the study
(N = 2,457)
Percentage2

Variables

Age when started complementary feeding (days)
0-7
21.9
8-28
4.8
29-59
4.0
60-89
7.7
90-119
9.6
120-179
17.5
> 180
31.6
Don’t know
2.9
1 All solid, semi-solid, liquid food and drink in conjunction with breast milk according to WHO
(2014)
2 Weighted percentages

Table 5. Protein and energy intake of mothers and children in the study (N = 2,457)
Dietary intake
Child
Energy, kcal
Protein, g
Mothers
Energy, kcal
Protein, g

Mean

SD

% RDA

739.9
6.5

572.9
4.5

89.6
31.6

1,395.5
11.9

590.3
6.4

70.9
23.7

SD = standard deviation
RDA = recommended dietary allowance for Indonesian children aged < 2 years of age and
women 16-49 years of age

52

Table 6. Adequacy of minimum dietary diversity of mothers and her children1 (N = 2,457)
N

%2

Mothers
Not adequate
Adequate

2,693
109

96.1
3.9

Children
Not adequate
Adequate

1,926
855

69.3
30.7

1 MDD = minimum dietary diversity, for women according to FAO (2014) is based on intake of
10 food groups: 1) all starchy staple foods, 2) beans and peas, 3) nuts and seeds, 4) dairy, 5) flesh
foods, 6) eggs, 7) vitamin A-rich dark green leafy vegetables, 8) other vitamin A-rich vegetables
and fruits, 9) other vegetables, 10) other fruits. Adequate if > 5 groups consumed
MDD for children according to WHO (2014) is based on 7 food groups: 1) grains, roots, and
tubers, 2) legumes and nuts, 3) dairy product, 4) flesh foods (meat, fish, poultry and liver/organ
meats), 5) eggs, 6) vitamin-A rich fruits and vegetables, 7) other fruits and vegetables. Adequate
if > 4 groups consumed
2 Weighted percentages

Younger children were more likely to be breastfed (Table 7). Complementary feeding quality as
defined by the adequacy of MDD and consumption of unhealthy snacks was not significantly
different across age groups (Table 8 and 9). In this study there was a total of 914 (37.3%) stunted
and 359 (14.5%) wasted children (Table 10). Stunting by age groups of 6-11 months, 12-17
months, and 18-23 months was 38.1%, 40.3%, and 41.6% respectively. Wasting for the same age
groups was 14.9%, 13.6% and 14.5% respectively.

53

Table 7. Breastfeeding practices by child age group (N = 2,457)

Yes

No

Child age categories
6-11 mo
12-17 mo
18-23 mo
6-11 mo
12-17 mo
18-23 mo

%1
37.8
35.9
26.3

p2
<0.001

12.8
27.2
60.0

<0.001

1 Weighted percentages
2 Chi-square tests for differences on breastfeeding status by child age categories

Table 8. Adequacy of minimum dietary diversity1 of children in the study based on age groups
(N = 2,457)

Not adequate

Child age categories
6-11 mo
12-17 mo
18-23 mo

%2
32.3
34.1
33.6

Adequate

p3
0.62

6-11 mo
30.7
0.62
12-17 mo
34.4
18-23 mo
34.9
1 MDD = minimum dietary diversity, for children according to WHO (2014) consists of 7
groups: 1) grains, roots, and tubers, 2) legumes and nuts, 3) dairy product, 4) flesh foods (meat,
fish, poultry and liver/organ meats), 5) eggs, 6) vitamin-A rich fruits and vegetables, 7) other
fruits and vegetables. Adequate if > 4 food groups consumed
2 Weighted percentages
3 Chi-square tests for differences on adequacy of MDD by child age categories

54

Table 9. Unhealthy snack1 consumption of children in the study based on age groups
(N = 2,457)

Low

Medium

Child age categories
6-11 mo
12-17 mo
18-23 mo
6-11 mo
12-17 mo
18-23 mo

%2
32.9
34.3
32.8

p3
0.34

32.5
35.0
32.5

0.34

High

6-11 mo
29.8
0.34
12-17 mo
33.6
18-23 mo
36.6
1 Unhealthy snacks according to Adair and Popkin 129 and Sekiyama et al 27 which included: a)
modern snacks (e.g. stick cheese, cheese balls); b) Traditional snacks (e.g. sweets made from
coconuts, flour or rice; and fritters); c) candies and desserts; d) soft drinks (sweetened carbonated
beverages and fruit drinks)
2 Weighted percentages
3 Chi-square tests for differences of unhealthy snack consumption by child age categories

Table 10. Percentage of stunting and wasting on children 6-23 months of age in the study
based on age groups (N = 2,457)
Child age categories
2
Stunting
6-11 mo
(n=914)
12-17 mo
18-23 mo

Percentage1
38.1
40.3
41.6

Wasting3
(n=359)

6-11 mo
14.9
12-17mo
13.6
18-23 mo
14.5
1 Weighted percentages
2 Stunting is HAZ < -2 according to UNICEF
3 Wasting is WHZ <-2 according to UNICEF

55

4.2 Stunting and Wasting-Socio-demographic Associations
Table 11 shows the characteristics of the study population relative to stunting and wasting status
of the children. Location of residence, monthly expenses, number of household members, gender
of household head, maternal age, maternal education, maternal occupation, maternal BMI, child
age, child gender, and child birth weight were all significantly related to stunting and wasting
status (p<0.0001).

Children in rural areas were more likely to be stunted than those in urban areas, but there were
more wasted children in urban compared to rural areas. In terms of household monthly expenses,
there was a significant trend where the higher the monthly expenses, the lower the rate of
stunting. This was not true for wasting categories.

With regard to the number of household members, for both stunting and wasting, if there were
more than 4 members in the household, rates were lower. Stunted and wasted children were more
likely to live in households with a male head. Older women had the lowest number of stunted
children. Stay-at-home mothers had more stunted or wasted children compared to working
mothers. Mothers who were normal or overweight were more likely to have stunted or wasted
children than women who were obese or underweight.

Table 12 depicts the distribution of dietary characteristics by stunting and wasting status.
Distribution of maternal and child dietary intake significantly differed by stunting and wasting
categories (p<0.0001). Mothers with inadequate MDD scores were more likely to have stunted or

56

wasted children than those with acceptable scores. Children who had never been breastfed were
less likely to be stunted or wasted. Children who were not currently breastfed were also less
likely to be stunted or wasted. Stunting and wasting was higher among children who were
breastfed within one hour after birth as well. Children with adequate dietary diversity were less
stunted or wasted. Children who received complementary feeding earlier than the recommended
age of 6 months were more likely to be stunted or wasted.

57

Table 11. Demographic characteristics of households, mothers and children based on stunting
and wasting categories (N = 2,457)

Households (HH)
Region
Urban
Rural
Monthly expenses
Low
Medium
High
Number of HH
members
<4
>4
Gender of HHH
Male
Female

Mothers
Age
< 20
20-29
30-39
> 40
Education (y)
<6
6-11
> 12Occupation
Stay at home
Working
BMI
< 18.5
18.5-22.9
23.0-27.4
> 27.5

Stunting a
(n=914;Wt’d%=37.3%)
Wt’d %
pc
n

Wastingb
(n=359;Wt’d%=14.5%)
n
Wt’d %
pc

434
549

45.9
54.1

183
176

51.0
49.0

353
315
246

38.6
34.5
26.9

106
139
103

31.2
39.1
29.7

637
346

65.3
34.7

<0.0001

229
119

66.0
34.0

<0.0001

959
24

97.6
2.4

<0.0001

333
15

95.5
4.5

<0.0001

40
418
397
59

4.5
45.7
43.7
6.4

<0.0001

12
149
133
25

3.5
46.6
41.8
8.1

<0.0001

117
562
304

11.7
57.3
30.9

<0.0001

48
185
115

13.9
52.8
33.3

<0.0001

543
440

55.1
44.9

<0.0001

202
146

57.4
42.6

<0.0001

107
422
275
104

11.8
46.5
30.3
11.5

<0.0001

30
159
88
42

9.2
49.6
27.9
13.3

<0.0001

<0.0001

<0.0001

<0.0001

<0.0001

a Stunting is HAZ < -2 according to the UNICEF
b Wasting is WHZ < -2 according to the UNICEF
Wt’d: Based on weighted percentage
c Chi-square tests for differences in child stunting and wasting status by household, maternal and child
characteristics
Numbers may not sum up to 100.0 due to rounding
HHH= Household head
BMI = body mass index as weight (kg)/height (m)2

58

Table 11. (cont’d)

Child
Age (mo)
6-11
12-17
18-23
Sex
Male
Female
Birth weight (g)
< 2,000
2,000-2,499
2,500-2,999
3,000-3,499
> 3,500

Stunting a
(n=914;Wt’d%=37.3%)
Wt’d %
pc
n

Wastingb
(n=359;Wt’d%=14.5%)
n
Wt’d %
pc

299
345
339

30.3
35.5
34.2

<0.0001

119
120
120

33.1
33.4
33.4

<0.0001

473
510

47.9
52.0

<0.0001

160
187

46.8
53.2

<0.0001

5
35
203
338
260

0.5
4.4
24.3
39.6
31.1

<0.0001

5
15
57
126
89

1.6
5.1
20.2
43.2
29.9

<0.0001

a Stunting is HAZ < -2 according to the UNICEF
b Wasting is WHZ < -2 according to the UNICEF
Wt’d: Based on weighted percentage
c Chi-square tests for differences in child stunting and wasting status by household, maternal and child
characteristics
Numbers may not sum up to 100.0 due to rounding
HHH= Household head
BMI = body mass index as weight (kg)/height (m)2

59

Table 12. Dietary characteristics of mothers and children based on stunting and wasting
categories (N = 2,457)
Stunting a
(n=914;Wt’d%=37.3%)
Wt’d %
pc
n

Wastingb
(n=359;Wt’d%=14.5%)
n
Wt’d %
pc

Mothers
MDDd
Inadequate
Adequate

869
40

95.8
4.2

<0.0001

308
8

97.8
2.2

Energy intakee
Low
Medium
High

518
342
123

54.9
32.5
12.6

<0.0001

55
121
172

15.9
33.2
50.9

Children
Breastfeeding
Ever breastfed
Never breastfed

855
59

93.4
6.6

<0.0001

301
18

94.3
5.8

666

79.1

<0.0001

251

83.3

189

20.9

50

16.7

Initial breastfeeding (h)
< 1
> 1

435
233

65.0
35.0

<0.0001

158
88

64.2
35.8

<0.0001

Complementary feedingf
Inadequate MDD
Adequate MDD

600
308

66.9
33.1

<0.0001

241
77

97.8
2.2

<0.0001

Introduction of
complementary feeding
< 6 months
> 6 months

649
288

65.2
34.8

<0.0001

236
102

67.5
32.5

<0.0001

Consumption of unhealthy
snacksg
Low
Medium
High

385
305
293

38.1
31.3
30.6

<0.0001

159
107
82

46.2
30.6
23.2

<0.0001

Breastfeeding
currently
Not breastfeeding
currently

<0.0001

<0.0001

<0.0001

<0.0001

a
=
b
=
Wt’d =
c
=

Stunting is HAZ < -2 according to the UNICEF;
Wasting is WHZ < -2 according to the UNICEF
Based on weighted percentage
Chi-square tests for differences in child stunting and wasting status by mothers and children dietary
characteristics
d
= MDD = minimum dietary diversity, for women according to FAO (2014) is based on intake of 10 food groups: 1)
all starchy staple foods, 2) beans and peas, 3) nuts and seeds, 4) dairy, 5) flesh foods, 6) eggs, 7) vitamin A-rich
dark green leafy vegetables, 8) other vitamin A-rich vegetables and fruits, 9) other vegetables, 10) other fruits.
Adequate if > 5 groups consumed
e & g = classification based on tertiles
f
= MDD for children according to WHO (2014) consists of 7 groups: 1) grains, roots, and tubers, 2) legumes and nuts, 3)
dairy product, 4) flesh foods (meat, fish, poultry and liver/organ meats), 5) eggs, 6) vitamin-A rich fruits and vegetables,
7) other fruits and vegetables. Adequate if > 4 food groups consumed

60

Figure 5. Path diagram of the overall model

61

4.3 Path Analysis of Factors Associated with Stunting and Wasting
The path analysis summary diagram of the overall model is presented in Figure 5. It shows that
child stunting status was significantly influenced by breastfeeding currently and the consumption
of unhealthy snacks. For wasting, only mothers’ BMI had a significant positive effect.

Specific Aim 1
To examine the relationship between mother’s dietary intake and weight status and risk for
stunting and wasting in children 6-23 months of age in Indonesia.
It was hypothesized that mothers’ BMI would have a direct positive effect on children’s stunting
or wasting status, meaning that heavier mothers would be less likely to have stunted or wasted
children compared to those who had a lower weight status. The direct effect test for the
relationship of mothers’ BMI to stunting status supported both assumptions (Figure 6. The
unstandardized parameter estimate was 0.02, SE = 0.01, p = 0.05) although the significance was
borderline.

Figure 6. Direct effect of mothers’ BMI relative to children stunting status

Mothers
BMI

Stunting

0.02

BMI = body mass index as weight (kg)/height (m)2
Stunting is HAZ < -2 according to the UNICEF

62

For the direct effect of mothers’ BMI relative to wasting status in children, the result was not
statistically significant (unstandardized parameter estimate = 0.01, SE = 0.02, p = 0.78).

It was also hypothesized that mothers’ dietary intake would have an indirect effect on stunting or
wasting status in children. First, the mediating effect of mothers’ dietary intake was tested and
compared with the moderating one. The moderating model had a better fitting model with a log
likelihood value closer to zero and a lower Bayesian Information Criterion (BIC) value
compared to those for the mediating model. Therefore, the moderating model was used to
explain the relationship between mothers’ and children’s dietary intake and stunting or wasting
(Figure 7 and 8).

In the model depicting stunting (Figure 7), breastfeeding currently or the consumption of
unhealthy snacks significantly affected the child stunting status. The moderating effect of
mothers’ MDD on child complementary feeding practice (child MDD and unhealthy snack
consumption) was not significant. However, the moderating effect of mothers’ MDD relative to
unhealthy snack consumption was significant for wasting status (Figure 8. Unstandardized
parameter estimate = -0.03, SE = 0.01, p = 0.04).

63

Figure 7. Path analysis relationships of dietary intake of mothers and children with stunting in
children

Mothers
MDD

Stunting

0.07
-0.02

-0.06

-0.01
0.26*
Breastfeeding
currently

Child MDD
-0.1

Ever
breastfed
-0.14*
Child
unhealthy
snack
consumption

MDD = minimum dietary diversity
Stunting is HAZ < -2 according to UNICEF
* p < 0.05
Significant paths shown with solid line

64

Figure 8. Path analysis relationship of mothers’ and children’s dietary intake to wasting in
children

Ever
breastfed
Breastfeeding
currently

-0.01
-0.1

Mothers
BMI
Mothers
MDD

0.03
0.03

-0.03*
0.1*
Child
unhealthy
snack
consumption

MDD = minimum dietary diversity
Wasting is WHZ < -2 according to the UNICEF
* p < 0.05
Significant paths shown with solid line

65

Wasting

Specific aim 2
To examine the relationship between child feeding practices and risk for stunting and wasting in
children 6-23 months of age in Indonesia.

Data was analyzed based on breastfeeding and complementary feeding practices. Breastfeeding
practices were explained by the child ever being breastfed or if the child was currently being
breastfed as per data presented in IDHS

Figure 7 confirmed that breastfeeding was protective against stunting status (unstandardized
parameter estimate = 0.26, SE = 0.11, p = 0.02); while ever being breastfed was not significant
(unstandardized parameter estimate = 0.03, SE = 0.045, p = 0.5). For wasting status, both child
ever being breastfed and currently breastfed were not significantly related.

For stunting status, the lower the unhealthy snack consumption, the lower the stunting risk
(unstandardized parameter estimate = -0.14, SE = 0.05, p = 0.008). The child MDD was not
significantly related to stunting. For wasting status, the unhealthy snack consumption was once
again significant, showing that the more the unhealthy snack consumption the less likelihood of
wasting (unstandardized parameter estimate = 0.091, SE = 0.042, p = 0.03).

4.4 Factors Associated with Ever Being Breastfed
Figure 9 shows the determinants for history of ever being breastfed. Only the child’s age was
significant (unstandardized parameter estimate = -0.07, SE = 0.02, p < 0.001). Mothers’ age had
borderline significance (unstandardized parameter estimate = -0.02, SE = 0.01, p = 0.06)

66

Figure 9. Factors associated with children ever being breastfed

Region of
residency
-0.26a
Monthly
expenses
-0.01
Mothers
age
Mothers
education

-0.02

Ever
breastfed

-0.04
-0.16

Mothers
occupation

-0.07**

Child age

a

p = 0.06
* p < 0.05
** p < 0.001
Significant paths shown with solid line

67

4.5 Factors Associated with Current Status of Breastfeeding
Figure 10 shows the determinants for currently being breastfed. Mothers’ education was
negatively significantly related to the child being breastfed (unstandardized parameter estimate =
-0.03, SE = 0.01, p < 0.001). Child’s age was also negatively related (unstandardized parameter
estimate = -0.02, SE = 0.01, p < 0.001)

Figure 10. Factors associated with children currently being breastfed

Region of
residency1
Monthly
expenses

-0.03
-0.01

Mothers
age

0.01

Mothers
education

-0.03**

Currently
breastfed

-0.03
Mothers
occupation

-0.02**

Child age

* p < 0.05
** p < 0.001
Significant paths shown with solid line

68

Table 13 shows odds ratio for history of ever being breastfed with the younger age group used as
the reference. The older age group was less likely to be breastfed.

Table 13. Logistic regression model for age and history of ever being breastfed
Factors

Logistic
regression
coefficient

Odds ratio

Age

- 0.4

0.93

95%
Confidence
interval
Odds ratio
0.92-0.96

P-value

<0.0001

Table 14 shows the odds ratio for stunting. Children who were not currently being breastfed had a
greater risk of 1.29 for stunting while children who were fed unhealthy snack consumption had a
13% higher risk for being stunted (OR= 1.13; 95% CI= 1.12-1.19).

Table 14. Odds ratios from logistic regression model for stunting
OR (95% CI) for stunting
Currently breastfed
Yes
No

1
1.29 (1.22-1.29)**

Unhealthy snack consumption
Low
High
** = p < 0.001

1
1.13 (1.12-1.19)**

Table 15 shows the odds ratio for wasting where children who were fed unhealthy snacks were
20% less likely to be wasted.

69

Table 15. Odds ratios from logistic regression model for wasting
OR (95% CI) for wasting
Unhealthy snack consumption
Low
High
** = p < 0.001

1
0.80 (0.78-0.80)**

4.6 Path Analysis of Factors Associated with Continuous Stunting and Wasting
Path analysis findings with continuous stunting (HAZ-scores) and wasting (WHZ-scores) outcome
variables are depicted in Figures 11 and 12.

Figure 11. Relationship of mothers’ and children’s dietary intake to child Height for Age Zscores
Mothers
MDD

HAZ

0.08
-0.01
0.01

-0.1*
0.29*

0.02
Mothers
BMI

Breastfeeding
currently

Child MDD
-0.01

Ever
breastfed
-0.2*
HAZ = height-for-age z-score
MDD = minimum dietary diversity
* p < 0.05
Significant paths are shown with solid lines

Child
unhealthy
snack
consumption

70

Figure 11 depicts the relationship of mothers’ and children’s dietary intakes on child HAZ
scores. Currently breastfeeding had a significant positive effect (unstandardized parameter
estimate = 0.29, SE = 0.12, p = 0.02). Unhealthy snack consumption had a negative significant
effect on HAZ-scores (unstandardized parameter estimate = -0.2, SE = 0.06, p < 0.001). Child
MDD was also negatively significantly related to HAZ-scores (unstandardized parameter
estimate = -0.1, SE = 0.04, p < 0.05). Mothers’ MDD did not have significant moderating effects
on child complementary feeding.

With regard to the path analysis for WHZ (Figure 12), only mothers’ BMI was significantly
positively related (unstandardized parameter estimate = 0.03, SE = 0.01, p < 0.001). Heavier
mothers had children with higher WHZ scores.

71

Figure 12. Relationship of mothers’ and children’s dietary intake to child Weight for Age Zscores

Ever
breastfed
0.01

Breastfeeding
currently

0.07

Mothers
BMI

0.03**
0.03

Mothers
MDD

-0.01
-0.06
Child
unhealthy
snack

MDD = minimum dietary diversity
WHZ = weight-for-height z-score
** p < 0.01
Significant path shown with a solid line

72

WHZ

CHAPTER 5 – DISCUSSION

The MDD for children was 2.9, which is below the WHO’s recommendation intake of at least 4
food groups per day. Only a small proportion of children (30.4%) met the MDD
recommendation. This seems to be a prominent trend in developing countries. 133–136 Several
studies done in children 6-23 months of age showed that the minimum dietary diversity rates
were 46% (breastfed children) and 51.4% (non-breastfed children) in Ghana, 16% in Nigeria,
34% in Nepal, and 14% in Ethiopia. 134-137 Similarly, for mothers the MDD was 2.7 compared to
the FAO recommendation of at least 5, and even more disturbing was the fact that less than 4%
met the recommendation. Dietary diversity scores for women and children have been shown to
be good indicators of dietary quality because they are related to micronutrient adequacy of the
diet, an important element of dietary quality. 52,137–141 Indonesia has a long term history of
micronutrient deficiency, associated with low diversity in the diet. 84 Some key micronutrient
deficiencies in Indonesia were iron, iodine, and vitamin A. 121 Dietary diversity is specifically
essential for young children who require energy and micronutrients for optimal growth and
development 138, and may have been especially low among children in this study because of
unequal distribution of food between children and other family members, resulting in insufficient
energy intake relative to that recommended. 66

The mean energy intake of mothers in this study was low, and only fulfilled 71% of RDA with
protein consumption less than 25% of RDA. Generally mothers in this study were young,
uneducated; unemployed, and of normal weight. A study in Bangladesh among 2,809 women of
reproductive age showed that literacy had a significant positive impact on dietary diversity score,

73

but age did not show a significant effect. 142 Another study among pregnant women in Kenya
showed that education and employment status were positively relate to the dietary diversity
score. 143 BMI was associated only with the food variety score, the amount of food items
consumed in 24 hours, among 210 adult women in Tanzania, but not the dietary diversity score.
144

According to the IDHS 2010 report, 60% of women of reproductive age in Indonesia also had

a normal BMI.

Breastfeeding rates were high for both those who reported a history of ever breastfeeding their
children and whose children who were currently being breastfed. Despite the high rate of
breastfeeding, exclusive breastfeeding,(only breast milk until 6 months of age), was very low.
Babies were given food or drink as early as the first week of life including several ‘harmful’
foods for this young age, such as regular cow’s milk and honey. 24 This finding is in accordance
with previous studies on complementary feeding in Indonesia. 25,85,145 The main reason for these
inappropriate practices is probably mothers’ lack of knowledge. In a previous study by Blaney et
al, only 35% of mothers were aware of the recommended age for introducing complementary
feeding and 60% thought that all kinds of foods were acceptable for complementary feeding. 85

An interesting Indonesian practice, which was evident in the current study findings, was the
restriction of colostrum for the infant. Almost 30% of babies were not fed colostrum. This is a
concern because the value of colostrum from a nutrition perspective has been clearly established.
146

However, many Indonesian mothers believe that colostrum is not milk and bad for the

newborn. 146 This is also most likely the reason why babies are given complementary feeding as
early as the first week of life, since mothers wait for the ‘real’ milk to be evident before actively

74

breastfeeding. This is therefore an important misconception, which needs to be addressed by
health care professionals working in this vulnerable population.

Consumption of unhealthy snacks was high despite the young age of the children in this study. A
study in the rural western part of Indonesia showed that children 0-7 years had a similar
consumption of snacks throughout the day. 27 A multi-country study in Asia and Africa found
that more than 20% of babies 6-8 months of age consumed sugary snacks with the proportion of
children consuming sugary snack foods generally being higher than the proportion who
consumed fortified infant cereals, eggs or fruit. 147 Sugary snack food consumption was
especially common in Asia: among 6–8-month infants, 10–44% consumed sugary foods,
compared to 28–62% among those 9–11-months of age, and 42–75% among those who were 12–
23-month of age. 147

Similar findings were found in a previous study where the typical diet of Indonesians consisted
of unbalanced proportions of staple foods, vegetables, fruits and animal-based foods. 84 There
were disproportionally large amounts of staple foods, which are low in micronutrients. 84 The
protein content in the children’s diets was only one third of the RDA. The high consumption of
unhealthy snacks may contribute to the low protein content, as unhealthy snacks are typically
energy dense, but low in protein and may suppress the child’s appetite and decrease diversity in
the child’s diet. 27 Protein is essential for growth and development. 148 Therefore, it is imperative
that efforts to improve the dietary quality in the diets of young children in Indonesia, are
enhanced.

75

The percentages of stunting and wasting in this study was similar to the national average for the
same year (2010), which were 37.3% compared to 35.6% and 14.5% compared to 13.3%. These
high rates are not surprising given the poor child feeding practices demonstrated in the study.
However the reported rate of low birth weight in this study was, almost half of that of national
rate in the same year (11.1%). This may be due to fact that in this study LBW information was
collected based on mothers’ memory. Therefore, it may be under-reported.

Mothers’ BMI had a direct positive effect on stunting although the significance was borderline.
Previous studies showed that mothers’ nutritional status, in particular height and BMI, were
related to stunting in their children. 14,40,50,149 Mothers who are undernourished or stunted, may
have sub-optimal uterine conditions due to an insufficient nutrient supply for the fetus, which
leads to restricted fetal growth and promotes low birth weight and stunting in the babies. 96,150

Currently being breastfed was protective against stunting. Similar results were found in several
studies. 57,102,103,151 The current status of breastfeeding reflects breastfeeding practice beyond the
recommendation of exclusive breastfeeding until 6 months of age. This continued breastfeeding
protects against infection, particularly relative to the gastrointestinal and respiratory tracts 75,152
and provides important energy and nutrients for child growth. 153

Factors that significantly determined stunting comprised protective factors (currently breastfed
and high child MDD), as well as the negative role of high consumption of unhealthy snacks.
Higher child MDD decreased stunting, since MDD is a proxy of a high nutrient content of the
diet. 79,154–156

76

Child consumption of unhealthy snacks had a significant negative impact on the child height
status. This finding was similar to that found in a study of 154 children 1-12 years of age in a
rural village of West Java, Indonesia. 27 The study showed that the more snacks were consumed,
the lower the HAZ score among these children. 27 On the other hand, unhealthy snack
consumption protected against wasting. This may be because unhealthy snacks are energy dense,
but this does not mean that the child nutritional status is adequate because of the low nutrient
density. 24,27 This was clearly evident in the unacceptable MDD scores for both mothers and
children.

A factor that determined history of ever or currently being breastfed was child age. The younger
the child the more likely the child was to be breastfed. Another review article in Indonesia also
showed that breastfeeding practice declines with increasing age of the child. 145 Interestingly,
mothers’ education had a significant negative effect on current breastfeeding practices. The more
educated the mother, the less they breastfeed their babies. In contrast, a study in a rural area in
North Sumatra, Indonesia showed that the majority of mothers (52%) had appropriate knowledge
on child feeding practices that included duration and benefits of breastfeeding, regardless of the
level of education. 85

Mothers’ BMI had a significant positive effect on child WHZ scores in accordance with several
studies 149,157,158. These studies used a cross-sectional design in Kenya 149 and Ethiopia. 157-158
The data were collected from mothers and their children under 5 years of age. All showed
significant positive associations between the mothers’ BMI and their children WHZ scores.
149,157,158

77

The main finding of this study was that inappropriate child feeding practices were associated
with undernutrition among Indonesian children 6-23 months of age, more specifically with
stunting and wasting. The national prevalence of stunting and wasting was high, 37.3% and
14.5% respectively, showing that child undernutrition remained a main concern for Indonesia.
Factors of feeding practices that determined the child nutritional status included both
breastfeeding and complementary feeding. Being breastfed protected the children from stunting,
while having calorie-dense intake protected them from wasting.

78

CHAPTER 6 – SUMMARY AND CONCLUSIONS

6.1 Conclusion
Stunting and wasting prevalence among Indonesian young children was high and dietary intake
of these children, i.e. breastfeeding and complementary feeding, was poor. One third of the
infants were not given colostrum and introduced to complementary feeding as early as the first
week of life. Both mothers and their children had low protein intake and did not meet the
requirement for adequate dietary diversity.

Independent factors which contributed significantly to stunting among Indonesian children 6-23
months of age were current status of not breastfeeding and high consumption of unhealthy
snacks. The high consumption of unhealthy snacks interestingly had a protective effect on
wasting. Mothers’ MDD was a moderator variable that decreased the correlation of child high
consumption of unhealthy snacks and child wasting status. The logistic regression models for
assessing the association between child stunting and wasting categories and mothers MDD-W
and weight status controlled for household, maternal and individual characteristics including
region of residency, monthly expenses, mothers’ age, mothers’ education, mothers’ BMI,
mothers’ occupation, and child age.

Mother’s BMI had a borderline positive effect on stunting although mother’s dietary intake did
not have any significant effect on either stunting or wasting. Mother’s BMI had a significant
direct positive effect on WHZ-score when it was used as a continuous variable. Heavier mothers
had children with higher WHZ-scores. Child age was associated with breastfeeding status’, the

79

younger were more likely to be breastfed.. On the other hand, the more educated mothers were
less likely to breastfeed their children.

6.2 Implications

In 2013, The Lancet Series on Maternal and Child Nutrition provided evidence that nutrition is
important for optimal fetal and child growth and development. 54 Findings from the current study
suggest that improving breastfeeding and complementary feeding of young children can enhance
their nutritional status and have short-term and long-term positive impacts on stunting and
wasting. Furthermore, improvements in nutritional status will result in positive returns since
healthier children will likely become healthy and productive adults. Independent factors
associated with stunting for Indonesian children 6-23 months included current status of not being
breastfeed and a high consumption of unhealthy snacks. High consumption of unhealthy snacks
had a protective effect on wasting.

The IDHS 2010 data used in this study did not include information on infectious disease other
than malaria and tuberculosis or physical examination/current health status information.

Information on infectious diseases could have provided a clearer picture of immediate causes of
child undernutrition. . In addition, cultural barriers and facilitators to the introduction of healthy
complementary foods wasn’t assessed. This would provide critical information on if and how
Indonesian societal and cultural norms need to be considered to enhance social programs that
target health, and maintain well-being in the disadvantaged, especially young children in
Indonesia.

80

The policy implications for the Indonesian government are: 1) to determine how to implement
The Indonesian Minister of Health decree on exclusive breastfeeding more effectively, 2) to
support breastfeeding mothers who are working with regulations for adequate maternity leave,
and breastfeeding-friendly workplaces, and 3) to regulate the marketing efforts by infant formula
companies such as prohibition to advertise at health centers, in addition, donation of formula
should be allowed only during emergency situations. Implications for healthcare professionals
are to develop and implement: 1) programs to improve mothers’ knowledge and breastfeeding
practices, both for exclusive breastfeeding and continued breastfeeding from birth to2 years of
age, 2) programs to improve mothers and young children’s dietary quality, in particular mothers’
and children’s dietary diversity and reduce children’s consumption of unhealthy snacks.

6.3 Strengths and Limitations

This current study uses national data, includes mother-child dyads and combines dietary
information with household, mother, and child information. To our knowledge this is the first
that examines the relationships between unhealthy snack food consumption with stunting and
wasting in Indonesia and beyond. The large sample size in this study increases both reliability
and generalizability to other mother-young child dyads in Indonesia. Factors that may have
limited the results was that dietary intake information was derived from one 24-hour dietary
recall that may not be adequate to represent usual dietary intake of mothers and their children,
and may also contain recall bias. With regard to capturing dietary pattern information, a) food
frequency would have been better compared to 24-hour dietary recall. We also did not include
data from the fathers who potentially had some influence on the nutritional status of their

81

children. Due to the cross-sectional nature of the study design used, evidence of a causal
relationship between child feeding practices and risk for stunting and wasting cannot be
established. We tried to include all possible confounding factors in the current study, but some
unidentified and unknown confounders may have been missed. For example in the dataset, some
important information was not collected such as: actual initiation of complementary feeding per
se was not measured well, history of diseases such as congenital diseases and hospitalization
prior to data collection were not included. Other determinants of breastfeeding and
complementary feeding (e.g. the lack value for colostrum), such as: beliefs, attitudes, knowledge,
self-efficacy, misconceptions, maternal care and practices, family or social support (e.g. poor
support could result in early breastfeeding cessation), type of employment, and child care
support, were not assessed. Cultural differences and/or preferences were also not measured.
Longitudinal studies are needed to establish causal-effect relationships between dietary intake of
children and mothers and diseases over time. Future research studies should also include in-depth
qualitative methods to better understand why breastfeeding continuation after 6 months of age
was low, even though it was initiated earlier.

82

APPENDICES

83

Appendix 1 – Electronic approval
Appendix 1A - Indonesian email with approval to use the IDHS data

Appendix 1B – English Translation
Dear,
Dr. Dwi Savitri Rivami, M.Sc
With respect,
I am Arif Gunawan, from the Secretariat of Data Management Lab, R & D Agency, Ministry of
Health.
We have received your data request letter (Data Management Lab) on July 2, 2013, and now the
proposal is in a review process. To find out the results of the review process please check at
http://labmandat.litbang.depkes.go.id/home/menu-layan/status-permata-data. When the proposal
review is completed, we will inform you on how the data can be accessed.
Thank you
Best regards
Arif Gunawan
Secretariat of Data Management Laboratory
R & D Agency
Ministry of Health Republic of Indonesia

84

Appendix 2 – Link to access the IDHS data
Appendix 2A Indonesian email with link to access the IDHS data

Appendix 2B English translation
Dear,
Dr. Dwi Savitri Rivami, M.Sc
Here I submit a subset of data links that have been given by the reviewers. If any data is not
appropriate and there is a question please contact me by email, so I can refer to the reviewers.
http://labmandat.litbang.depkes.go.id:81/axs/u:c97a89a89c040644305767cef0fccef3/01.%20DW
I%20SAVITRI%20RIVAMI.rar
Thank you,
Best regards

85

Appendix 3 – Indonesian Demographic and Health Survey Questionnaire (Indonesian)

86

87

88

89

90

91

92

93

94

95

96

97

98

99

100

101

Appendix 4 – Indonesian Demographic and Health Survey Questionnaire (English)
RKD1 0.IND
BASIC HEALTH RESEARCH (RISKESDAS 2010)
CONFIDENTIAL
LOCATION IDENTIFICATION
(Quoted from Block I. LOCATION IDENTIFICATION RKD10.RT)
Prov

Reg/
City

Kec

Village/Kel

K/D

Order of
household
member
sample
sampel RT

Sample Code No.

Order
of
house
hold
memb

LABORATORY
SAMPLE 13S
1.Yes
2. No

VIII. INDIVIDUAL INFORMATION
A. RESPONDENT’S IDENTIFICATION
A01

Write name and order of Household Member /ART

Name of ART .................

A02

For ART at A01 < 15 years/ ill condition/adults needing
accompaniment /representation, write name and order of ART
who is accompanying/representing

Name of ART .................

A03

Date of data collecting

Order of ART:

□□

Order of ART:

□□

□□-□□-□□□□
B. CONTAGIOUS DISEASES

[NAME] in the questions below refers to NAME stated in question A01
QUESTIONS 1301-1310 ARE ASKED TO HOUSEHOLD MEMBERS AT ALL AGES
MALARIA

102

B01

In the past year, has [NAMA] been diagnosed to suffer from Malaria which was
confirmed with blood test by health practitioners (doctor/ nurse/ midwife)?

1. Once (1)
2. Twice(2)
3. ≥Three (3) times
4. No →B07

□

Has [NAME], also in the past 1 month, been diagnosed to suffer from Malaria which has
been tested with blood test by health practitioners (doctor/nurse/midwife)?

1. Yes
2. No →B07

□

B02

B03

B04

If the answer is Yes, where was the last test conducted?:
1. State Hospital
4. Health Clinic/ Clinic
2. Private Hospital
5. Doctor’s Practice
3. Public Health Center 6. Nurse/midwife’s Practice

7.
8.
9.

Public Health Center Supporting Unit
Village Maternity Center.
Village Health Post

Has [NAME] received treatment of artemisinin combination program medication
(ACT, see the props)?

B05

If the answer is yes, has [NAME] received medication within first 24 jam of suffering from
fever?

B06

Has [NAME] been given artemisinin combination medication (ACT) for 3 days?
1. Yes, taken completely.
2. Yes, not completely taken, give reason ................................................................

□

1. Yes
2. No→B09

□

1. Yes
2. No

□
□

CONTINUE TO B09
B07

B08

In the past month, has [NAME] ever experienced fever with the chill or gradual
temperature increase, could be accompanied by headache, sweating, nauseous, vomiting?
In the past month, has [NAME] taken anti malaria medicine even without symptoms
(fever)?

B09

Was Traditional remedy/herbal medicine used for the illness/symptoms mentioned
above?

B10

If the answer is Yes, what is the name of the Traditional remedy/herbal medicine most
often taken:

103

1.
2.

Yes →B09
No

1. Yes
2. No →B11A
1. Yes
2. No →B11A

□
□
□

...........................................

IF ART/HOUSEHOLD MEMBER IS ≥ 15 YEARS OLD→P.B11
IF ART/HOUSEHOLD MEMBER IS 10 YEARS OLD→P.C23
ART/HOUSEHOLD MEMBER IS 5-9 YEARS →OLD BLOCK IX. INDIVIDUAL CONSUMPTION
IF ART/HOUSEHOLD MEMBER IS < 5 YEARS OLD →E.TODDLERS’ HEALTH

B11A

LUNG TUBERCULOSIS (LUNG TB), ALL ART/HOUSEHOLD MEMBER AGED ≥15 YEARS OLD
B11

Has [NAME] been diagnosed to suffer from Lung TB through mucus test and/lung photo,
by health practitioners (doctor/ nurse/ midwife)?

B12

B13

B14

B15

2 . No →B17

□

In the last 12 months, has [NAME] been diagnosed to suffer from Lung TB through

1 . Yes

examination of mucus and/or lung photo, by health practitioner (doctor/ nurse/midwife)?

2 . No→B17

□

1. State Hospital 2. Private Hospital 3. Public Health Center 4. Health Centers/Clinics/ Doctor’s Practice

□

Where was [NAME] diagnosed?

After being diagnosed, where did [NAME] receive treatment?

1. State Hospital

4.

Doctor’s Practice

2. Private Hospital

5.

Health Center/ Clinic

3. Public Health Center

6.

No Treatment →B17

□

What kind of medicine does [NAME] take at present (sample of medicine is shown to the respondent):
1.

B16

1 . Yes

Combipack/FDC (Fixed Dose Combination)…..

2. Not combipack/FDC, please state if any…..

□

How long was/is [NAME] given medicine?
1. Received/s medication until the end, for 6 months or more →C01

2. Is in the process of medication < 6 months

4.

Stopped medication after 2-5 months

3. Stopped medication < 2 months

5.

Did not/ take medicine

104

□

B17

In the last 12 months, has [NAME] suffered from cough with phlegm ≥ 2 weeks
accompanied by one or more symptoms: mucus with blood/ bleeding cough, weight

1 . Yes
2. No → C01

decrease, night sweating without physical activity and fever > 1 month?
B18

□

What did/does [NAME] do to overcome the above symptoms:

1. Still continues medication of Lung TB program → C01 3. Purchased/purchases medicine at the pharmacy/drug
2. Returned/returns to health practitioner → C01

store
4. Took/takes herbal remedy/Traditional

□

5. Not treated
B19

What is the main reason that causes [NAME] with the symptoms of TB not seek treatment to health practitioners:
1. Not severe illness

3. Lack of time

5. Can be self-treated/self-healing

2. Difficult access to health facilities

4. No money

6. Others please state...............................

105

□

C. KNOWLEDGE AND BEHAVIOR (ALL HOUSEHOLD MEMBERS AGED ≥ 15 YEARS)
HIV/AIDS
C01
C02

Has [NAME] heard about HIV/AIDS

1. Yes

2. No → C07

□

Can HIV/AIDS be passed on through:
TO BE READ AND FILLED IN WITH ANSWER CODE OF 1=YES, 2=NO, OR 8=DON’T KNOW
a. Unsafe sexual contact

□
□

f. Passing on from mother to baby during pregnancy

h. Eating from the same plate with a person infected with the virus
of HIV/AIDS

d. Passing on from mother to baby
during birth

□
□

e. Passing on from mother to baby
during nursing

□

b. Use of same syringe

c. Blood transfusion

C03

C04

g. Buying fresh vegetables from farmers/sellers who are infected
HIV/AIDS

i. Through food prepared by ODHA (Sufferers of
HIV/AIDS)
j. Through mosquito bites

□
□
□
□
□

Can HIV/AIDS be prevented by :
TO BE READ AND FILLED IN WITH ANSWER CODES OF 1=YES, 2=NO , OR 8=DON’T KNOW
a. Having sexual intercourse
with only one partner who is
not at risk

□

c. Not having sexual intercourse at
all

□

e. Not using the same syringe

□

b. Having sexual intercourse
with only husband/wife

□

d. Using condom while having
sexual intercourse with
circumcision

□

f. Conducting partner who is at
risk

□

If a [NAME]’s family member suffers from HIV/AIDS, what will be done?
READ AND FILL OUT ANSWER CODE WITH 1=YES OR 2=NO OR 8=DON’T KNOW

106

a. Keep it a secret
b. Talk to family member
C05

C06

□
□

c. Counseling and treatment

e. Kept out

□
□

d. Seek alternative treatment

Does [NAME] know about the voluntary HIV/AIDS test with
counseling?

f. Willing to take care of the
house
2. No → C07

1. Yes

□
□
□

Where does one obtain the voluntary HIV/AIDS test?
[ANSWER IS NOT READ], FILL OUT ANSWER CODE WITH 1=YES, 2=NO
1. State Hospital
2. Private Hospital
3. Public Health Center/
Supporting Public Health
Center

□
□
□

4. Private Clinic

7. Midwife/ Nurse

□
□
□

5. VCT Clinic
6. Doctor’s practice

8. Others, please state

□
□

PREVENTION OF LUNG TUBERCULOSIS (LUNG TB)
C07

□

Where does [NAME] usually spit [ANSWER IS NOT READ]
3. Spits in a spitting container/can
4. Spits anywhere

1. Does not usually spit
2. Spits in the bathroom
C08
C09
C10

Does [NAME] usually open the bedroom window everyday

1. Yes

2. No

Does [NAME] sundry mattress and or pillow and or bolster of kapok regularly once a week?
1. Yes
2. No
Does [NAME] have a habit of eating and/or drinking from same plate/glass with others?
1. Yes
2. No

PREVENTION OF MALARIA

107

3. Don’t have it
3. Does not have

□
□
□

C11

What does [NAME] usually do so far to prevent malaria?
ANSWER IS NOT READ, Do probing.
FILL THE ANSWER CODE WITH 1=YES, 2=NO

□
□
□

e. house is sprayed with mosquito
repellent/insecticide
f. Taking preventive medicine when staying in
malaria endemic area

a.

Sleep with net

b.

Using coil/electric insect repellentq

c.

Window/ ventilation using mosquito net

d.

Using repellent/ ingredients for prevention of mosquito bites

g.
Others…

□
□
□

□

TOBACCO USE
C12

Has [NAME] smoked/ chewed tobacco for the last 1 month?
1. Yes, everyday
3. No, but have done so previously →C16
2. Yes, sometimes →C14
4. Have never done it at all →C18

C13

How old was [NAME] when starting to smoke/ chew tobacco “everyday” ?FILL
IN WITH ”88” IF RESPONDENTS ANSWER DON’T REMEMBER

C14

On average, how many cigarettes/ cigars/ pipes (fruit)/ tobacco (quid) that
[NAME] smoke per day?

C15

□
.................... years

.................... pieces

Does [NAME] usually smoke in the house when being with other family members?

1.Yes →C17
2. No→C17

□□
□□
□

C16

How old was [NAME] when he/she stopped/did not smoke/ chewed
tobacco at all? FILL IN WITH “88” IF RESPONDENT ANSWERS WITH
DO NOT REMEMBER

.................... years

□□

C17

How old was [NAME] when “first time” smoking/chewing
tobacco? FILL IN WITH ”88” IF RESPONDENT ANSWERS
DON’T REMEMBER

.................... years

□□

CONSUME HERBAL REMEDY/ TRADITIONAL MEDICINE

108

C18

C19
C20

Does [NAME] consume self-made herbal remedy
1. Yes
2. No →C21
If the answer is Yes, does the self-made herbal remedy made by [NAME] use ingredients: 1=YES, 2=NO
a.

Javanese ginger curcuma zanthorriza)

b. Ginger
c.
C21

Kencur (kaempferia galanga)

b. Steeped (powder)

C23

□
□
□

□

e. Noni/Indianmulberry

□
□

f.

□

d. Meniran (phyllantus niruri)

Form of herbal remedy supply which [NAME] usually consumes 1=YES, 2=NO
a. Capsule/pill/tablet

C22

□

Does [NAME] usually consume herbal remedy/ Traditional medicine?
1. Yes, everyday
3. No, but has consumed it before
2. Yes, sometimes
4. Never at all →C23

□
□

□
□

c. Boiled (sliced)
d. Liquid

Is consuming herbs/Traditional medicine beneficial for [NAME]

1.Yes

2. No

□

IF HOUSEHOLD MEMBER FEMALE AGED 10 - 59 YEARS → Da. REPRODUCTIVE HEALTH
IF HOUSEHOLD MEMBER FEMALE AGED >= 60 years →BLOCK IX. INDIVIDUALCONSUMPTION
IF HOUSEHOLD MEMBER MALE 10 – 24 Years → D101
IF HOUSEHOLD MEMBER MALE ≥ 25 Years → BLOCK IX. INDIVIDUAL CONSUMPTION
D. REPRODUCTIVE HEALTH
Da. WOMEN’S REPRODUCTIVE PERIOD (ESPECIALLY FEMALE HOUSEHOLD MEMBERS OF 10-59 YEARS)

Da01

How old was [NAME] when first got the period (menstruation)

Age :………………(year)
Not yet get period 77→ D101
Don’t know/ Forget 88

109

□□

Da02

Da03

Has [NAME] experienced irregular menstruation in the last 12
months?

□

Ya →2.Db01a
Tidak 4 Db01a
1. Yes
2. No

□
□

1. Approaching Menopause
2. Chronic pain

□

Has [NAME] experienced getting period late in the last !2 months

Da 04

Is [NAME] pregnant at the moment or has just given birth?

Da05

According to [NAME], why is she suffering from irregular
menstruation? (ANSWER ALTERNATIVES ARE NOT TO
BE READ)

Da06

1. Yes
2. No → Db01a

3. Hereditary
4. Others,.................
8. Don’t know

What does [NAME] do to treat the irregular menstruation?
(ANSWER ALTERNATIVES ARE NOT TO BE READ) 1=YES OR 2=NO
a. Take medicine to ease period

b. Take/drink herbs
c. Doctor’s medication

□
□
□

d. Hormonal injection
e. Others, please state……………..

□
□

Db. FERTILITY (ESPECIALLY FOR WOMEN WHO HAS BEEN MARRIED AGED 10-59 =YEARS)
Db01 How old was [NAME] when first got married?

Age ................ years
Don’t know ... 88

Db02 Has [NAME] been given TT immunization?

1. Yes 2. No → Db04 8. Don’t know → Db04

Db03 a. How many times has [NAME] been given TT
immunization before being married?

Number of injections ... .times

b. How many times has [NAME] been given TT
immunization after being married?

Number of injections .... times

IF NEVER WRITE “0”, IF 7 TIMES IMMUNISATION OR MORE WRITE “7”, IF DON’T KNOW WRITE “8”

110

□
□
□
□

Db04

During your lifetime.
a. Has [NAME] been pregnant?

1. Yes

2. No →Dc01

b. Has [NAME] been pregnant which ended at the period of
pregnancy<22 w or < 5 …

1. Yes

2. No

8. Don’t know

□

1. Yes

2. No 8. Don’t know

□

1. Yes

2. No

□

c. Has [NAME] been pregnant but ended at ≥22 weeks or >-5
months and the baby did not show signs of life?

d. Has [NAME] given birth to live baby (including one who did
not live long)?
Db05

Does [NAME] have son or daughter who now lives with
[NAME]?

□

1. Yes
2. No → Db07

111

□

The number of children who live with [NAME]?
a. The number of sons
b. The number of daughters
None write “00”

Db06

Db07

Db09

□□

a.

Sons in other places .....................

b.The number of daughters
none write “00”

b.

Daughters in other places .............

a.

1.
2.

b.

□
□□
□□

Yes
No → Db11

a. Sons who have passed away .........

How many sons have passed away

b. How many daughters have passed away
If none write “00”
ADD UP Db06a, Db06b, Db08a, Db08b, Db10a, Db10b AND
WRITE THE TOTAL NUMBER

Db11

b. Daughters at home.....................

The number of children who are still alive but don’t live together
with [NAME]?
a. The number of sons

Has [NAME] ever give birth to sons or daughters who was born
alive but now have passed away (including those who only lived
for a short period of time)?

Db10

□□

1. Yes
2. No → Db09

Does [NAME] have children that [NAME] delivered and
now still alive but don’t live together with [NAME]?

Db08

a. Sons at home ........................

Daughters who have passed away

TOTAL NUMBER OF
CHILDREN:..........................

□
□□
□□
□□

Dc. TYPE OF BIRTH CONTROL (SPECFICALLY FOR WOMEN WHO HAVE BEEN MARRIED AGED 10-59 YEARS)
Dc01

Does [NAME] clan partner, use birth
control/contraception to prevent pregnancy?

1. Use it now
2. Has used it/does not use it anymore → Dc06
3. Has never used it at all → Dc06

Dc02

What type of birth control/contraception is [NAME] clan partner using?
Read point a to k . FILL IN CODE 1=YES OR 2 = NO

112

□

a.

Female

Sterilization
e.
Injectionq
Dc03

□
□
□
□

e. Injection
i. Periodic
abstinence/calender q

f.

Condom

i. Periodic abstinence/calender.

□
□
□
□

j. Coitus
interruptus/withdrawal
q

k. Others (please
i. Periodic
g. Diaphragm/intravagh.
a. Is there cost spent to obtain birth control/contraception service used at present?
1. Yes
2. No → Dc04
b. Does [NAME] know the amount of rupiah paid

Rp
Dc04

Dc05

□

a. Yes
b. No→ Dc04

c. If the answer is yes, write the amount in rupiah

□
□
□

□

□.□□□.□□□

Where did [NAME] get the birth control/contraception service or care?
1. State Hospital

5. Supporting Public Health Center

9. Midwife’s Practice

2. Private Hospital

6. Clinic

10. Nurse’s Practice

c.Maternity Hospital

7. Mobile Family Planning
Team/Mobile Medical Team

11. Village Health Post/Village
Maternity Center

4. Public Health Center

8. Doctor’s Practice

12. Others, please state………..

How long has [NAME] used (birth control/contraception used at present) continuously? (Months)

□□

□□□

CONTINUE TO Dc08. Dc06-Dc07 especially for respondents not using birth control/contraception.

113

Dc06

The main reason for not using birth
control/ contraception ?
ANSWER ALTERNATIVES ARE
NOT TO BE READ

1.
2.
3.
4.
5.

6.
7.
8.
9.
10.

Not allowed by spouse/partner
Forbidden by religion
Costly
Difficult to obtain
Have no child yet

Planning to conceive
Afraid of side effects
Not willing
Does not find it necessary
Others

□
□

If the answer Dc01=2, continue to P.Dc07
If the answer Dc01=3, continue to P.Dc08
.........( month)

Dc07

How long has it been for not using birth control/contraception?

Dc08

In the last 12 months, has [NAME] done examination of vital organ to
health practitioners (Pap Smear/IVA Inspeculo Visual of vinegar acid)?

1. Yes
2. No
8. Don’t know

□□□
□

Dd. PREGNANCY, BIRTH AND EXAMINATIONS AFTER BIRTH (WOMEN HAVE BEEN MARRIED AGED 10-59
YEARS)
Dd01

Have you been pregnant and given birth, during the period of 1 January 2005
until now?

1. Yes

2. No → De01

□

Now I would like to ask about your experience during pregnancy and giving birth especially for the child born last.
a. Write [CHILD’S NAME ] and Household Member order of the
last child
(If not on the House Member list, write the code 00)

Household Member
name

b. How old was she when she gave birth to last [CHILD’S NAME]

............ years

Dd03

Order of birth [last CHILD’S NAME] from all born alive

The ……..child in the family

Dd04

Length of time between birth of the last child
[CHILD’S NAME] and the previous child [“000” if first
child)

.......months

Dd02

114

Household Member
order:

□□
□□
□□
□□

Dd05

Status of last child

1. Alive→ Dd10
2. Passed away

□

QUESTIONS Dd06-Dd09f ESPECIALLY FOR THE LAST WHO DIED
Dd06

Dd07

If already passed away, age when died:
Circle code 1, if died at < 1 month, fill in in days
Circle code 2, if died at age 1-23 months, fill in in months
Circle code 3, if died >= 2 years (over 24 months), fill in in years

Was [CHILD’S NAME] weighed when born?

1.

DAYS

2.

MONTHS

3.

YEARS

1. Yes
2. No →Dd09a
8.Don’t know→ Dd09a

Dd08

Dd09

What was the weight of [CHILD’S NAME] when born?
Note the weight from KMS/KIA Book, If Any
IF THE ANSWER IS DON’T KNOW FILL IN CODE
8888

1. Gram based on respondent’s memory
2. Gram from KMS/KIA Book

a. Who helped her when giving birth to [CHILD’S NAME]?
1. Obstetrician
5. Medicine man
2. Physician
6. Family/friend
3. Midwife
7. Others, please write
4. Nurse/paramedic
b. Where was [NAME] born
1. State Hospital
2. Private Hospital
3. Maternity Hospital/Maternity Center
4. Public Health Center

□
□□□
□
□□□

a. First Aid

□

b. Last Aid

□

05. Supporting Public Health Center 09. At home
06. Doctor’s Practice
10.Others, please state
07.Midwife Practice
08. Village Maternity Center/Village Health Post

115

□□
□□
□□

□□

c. After [CHILD’S NAME] was born, was health
check done?

1.
2.

Yes
No →Dd10
8. Don’t know → Dd10

□

d. Did [NAME] receive health service (was visited/visited) at: (READ OUT POINTS a TO d) FILL IN
WITH CODES 1=YES 2=NO 7=DOES NOT APPLY 8 = DON’T KNOW
a. 6–48 hours after being
born

b. 3–7 days after being

□

born

c. 8–28 days after being

□

born

□

d. >28 days after
being born

e. Who had [CHILD’S NAME] checked at the time?
HEALTH ATTENDANT:
1. Pediatrician
4. Midwife
2. Physician
5. Village Midwife
3. Nurse

OTHER PEOPLE:
6. Nurse-midwife
7. Others,…………….(please state)

□
□□

f. Where was the check done?

1.
2.
3.
4.

Dd10

Dd11

State Hospital
5. Integrated Service Post
9. Village Maternity
Center/Village Health Post
Private Hospital
6. Clinic/ Doctor’s Practice
10. At home
Maternity Hospital
7. Clinic / Midwife’s Practice
11. Others, please state............
Public Health
8. Nurse’s Practice
Center/
Supporting Public
Health Center
When she was being pregnant with [CHILD’S NAME], did she
1.Yes, intended later
intend to conceive at the time, intended later, or did not intend to
2. Yes, intended→ Dd12 3.Did
have (another) child at all?
not intend to have any more
children →Dd12
How long was it that she wanted before having [CHILD’S
NAME]?
IF THE ANSWER IS DON’T KNOW FILL IN THE CODE 888

□

□
□□□

116

Dd12

Dd13

1.Health Practitioner
2. Health practitioner and
traditional healer /nursemidwife
3. Traditional healer/nurse-midwife
→Dd27
Who checked her pregnancy? (Ask the people who checked the pregnancy. Answer may be more
than 1). FILL IN ANSWER CODE WITH 1=YES OR 2=NO
During pregnancy with [CHILD’S NAME] where did she
have her pregnancy checked?

□

a. Obstetrician/Gynecologist
b. Physician
Dd14

Dd15

□

d. Nurse/Mantri (paramedic)

Were you given Kartu Menuju Sehat Ibu Hamil (KMS
BUMIL)/Health Card for Pregnancy or KIA Book. If the answer is
Yes, can she show the KMS BUMIL/KIA Book?

□

e. Others

□

□

1.
2.

Yes, shown
Yes, not shown
No

3.

□

Where did she have her pregnancy checked? (READ POINTS a TO k) FILL IN ANSWER CODE WITH 1=YES OR
2=NO

□
b. Private Hospital
□
c. Maternity Hospital □
d. Public Health Center □

e. Supporting Public Health

a. State Hospital

Dd16

c. Midwife

□

□
Clinic / Doctor’s Practice □
Clinic / Midwife Practice □
Nurse Practice
□
Center

f.
g.
h.

While being pregnant with [CHILD’S NAME], how many times did
she have checks?
IF THE ANSWER IS DON’T KNOW FILL IN THE CODE 1188”

i. Village Maternity Center / Village Health
Post

j. integrated Service Post
k. Others

□
□
□

please state……..,
------ Times

117

□□

Dd17

How many months being pregnant with [CHILD’S NAME] when first
had the pregnancy checked by health practitioner?
IF THE ANSWER IS DON’T KNOW FILL IN WITH CODE 1188”

----- Months

Dd18

How many times did she have her pregnancy checked :
In the first 3 months
Between 4-6 months:
c. Between 7 months until giving birth

Number of checks:
....... times
....... times
....... times

Dd19

How many months being pregnant with [CHILD’S NAME]
When she last had her pregnancy checked?
IF THE ANSWER IS DON’T KNOW FILL IN CODE 88

............... Months

Dd20

While being pregnant with (CHILD’S NAME) did she:?
FILL IN ANSWER CODE WITH 1=YES OR 2=NO

a.
b.

Dd21

a.

Have her weight checked

b.

Have her height checked

c.

Have her blood pressure checked

□
□
□

□□
□□
□□
□□
□□

□
□

d.

have her urine checked

e.

have her blood checked

f.

have her abdomen/stomach checked (stroked)

□

During checks, was she told about the signs of danger (complications) in
pregnancy?

1. Yes
2. No→Dd23

□

8. Don’t know →Dd23
Dd22

During checks, was she told where to go to get help in times of dangers
(complications)?

1. Yes
2. No

□

8. Don’t know
Dd23

While being pregnant with (CHILD’S NAME) did she ever get injection
on the upper arm to prevent babies from tetanus or seizure after birth?

1. Yes
2. No →Dd25
8. Don’t know →Dd25

118

□

Dd24

While being pregnant with (CHILD’S NAME) how many times did she
receive the injection? ( IF THE ANSWER IS DON’T KNOW FILL IN
“88”)

............. times

Dd25

While being pregnant with (CHILD’S NAME), did she receive or buy
zinc/iron pill?

1. Yes
2. No →Dd27
8. Don’t know→Dd27

Dd26

While being pregnant with (CHILD’S NAME) how many days did she take
iron/zinc pills?

Dd27

If
the respondent’s
answer
is not
in number,
asktalk
to estimate
theabout:
number of
While
being pregnant
with
(NAME),
did she
to anyone
(FILL IN ANSWER CODE WITH 1=YES OR 2=NO)

Dd28

□□

d. cost of giving birth?

b.

e blood donation if necessary?

□
□

1. Yes
2. No→Dd31

□

Did she experience signs of dangers
(complications) during pregnancy?

8. Don’t know → Dd31
Dd29

□

a. Where did she give birth?

c.

□
Transportation to place of giving birth? □
Who will help when giving birth?
□

..................days

□□

What are the signs of danger (complications) of the pregnancy?
ANSWERS SHOULD NOT BE READ, FILL IN ANSWER CODE WITH 1=YES OR 2=NO

a. Strong pain before 9 months
b. Bleeding
c. High Fever

□
□
□

d. Seizure and fainting
e.

Others, please state

119

□
□

Dd30

What was done to overcome the problem?
ANSWERS SHOULD NOT BE READ, FILL IN ANSWER CODE WITH 1=YES, 2=NO

a. Did nothing
b. Took a rest

□
□

□

d. Take/drink herbal medicine.

e. Went to Traditional healer/nurse-midwife

□
□

h. Went to the Health Service Unit

c. Took medicine

□

g. Went to tthe doctor

f. Went to the midwife

i. Others

Was (CHILD’S NAME) born through cesarean section)?

1. Yes 2.No

Dd32

How far into the pregnancy with (CHILD’S NAME) was it when
he/she was born ?

.................. months

Dd33

When (CHILD’S NAME) was born, was he/she: very big , bigger
than average, average, smaller than average, or very small?

1.
2.
3.
4.

Dd34

Dd35

Very big
Bigger than average
Average,
Smaller than average,
5. Very small

□
□
□
□
□
□

When about to give birth to (CHILD’S NAME), did she suffer from:
FILL IN ANSWER CODE WITH 1=YES OR 2=NO or 8=DON’T KNOW
a. Strong and regular stomach pain more than a
day and night?

□

d. Seizure and/or fainting ?

□

b. Heavier bleeding than usual (more than 2
cloths)?

□

e. Discharge of amniotic fluid more than
6 before the child was born?

□

c. High body temperature and or discharge of
smelly mucus/slime?

□

f. Is there any other difficulties
complications? If any, please
state……….

□

When giving birth to (CHILD’S NAME), was she diagnosed with:
FILL IN ANSWER CODE WITH 1=YES, 2=NO OR 8=Don’t know

120

a. Bleeding
b. Preeclampsy/Eclampsy (Swelling of two legs
& high blood Pressure/seizure)

c. Rupture uteri/rupture of uterus
d. Placenta praevia

e. Early

□
□
□
□

□
□
□

f. Ectopic Pregnancy
g. Others
break of amniotic fluid

IF Dd35 POINT a to g ONE OF THEM IS ANSWERED BY “YES” THEN CONTINUE TO Dd36
IF Dd35 POINT a to g ALL ANSWER IS “NO” OR “DON’T KNOW” THEN CONTINUE TO Dd37
Dd36

Who diagnosed her to have suffered from the complication (as shown in Dd35)?
3. Midwife
5. Traditional healer/nurse midwife 7.
Others, please state:
2. Physician
4. Nurse/Mantri
6. Family/friend
........................

□

1. Obstetricians

Dd37
Dd38

Dd39

After (CHILD’S NAME) was born, did she have her health
checked?

□

1. Yes 2. No → Dd41
Day .....................

After giving birth, on what day was her health checked for
the first time? ( IF THE ANSWER IS DON’T KNOW FILL
IN “888”)

□□□

Who checked her health after giving birth ?
FILL IN ANSWER CODE WITH 1=YES OR 2=NO (ONLY ONE CHOICE)
a. Obstetrician
b. Physician

□
□

c. Midwife
d. Nurse

□
□

e. Traditional healer/nurse-midwife
f. Others, please state

121

□

□

Dd40

Where was the examination conducted?

1. State Hospital

05. Integrated Service Post 09. Village Maternity Center/Village Health

□□

Post

2. Private Hospital

06. Clinic/ Doctor’s Practice

10. At home

3. Maternity Hospital

07. Clinic / Midwife Practice

11. Others, please state..........................

4. Public Health Center/Supporting Public Health Center
Dd41

8. . Nurse Practice

After giving birth, did she experience?
FILL IN ANSWER CODE WITH 1=YES OR 2=NO 8=DON’T KNOW

a. Bleeding (more than 2 cloths)
b. Fainting

□

□ c. Seizure □
d. High Fever □

e. Pain on the breast
f. Feeling of sadness and depress
g. Others, please state ……..

122

□
□
□

IF in Dd41 POINTS a to g ONE OF THE ANSWERS IS “YES” THEN CONTINUE TO Dd42
IF in Dd41 POINTS a to g ALL ANSWERS WERE “NO” OR ”DON’T KNOW” THEN CONTINUE TO Dd43
Dd42

When experiencing the above mentioned, what was done:
FILL IN ANSWER CODE WITH 1= YES OR 2=NO

a. Did not do anything
b. Took a rest
c.

Took medicine

□ d.
□ e.
□

Took/drank herbal remedy
Saw Traditional
healer/nurse-midwife

□ g. Visited doctor’s practice
h. Went to Community Health
□ Center/ Supporting Health
Center
□ i. Went to Village Maternity

f. Went to midwife Practice

j. Center/Village Health Post
k. Others, please state

Dd43

During childbed period, did [NAME] receive vitamin A capsule pink in color.
SHOW PROP CARD

1. Yes
2. No
8. Don’t know

□
□
□
□
□
□

De. MISCARRIAGE and UNWANTED PREGNANCY(especially for women who have been married aged 10-59 years)
(PERTANYAAN LANGSUNG DITANYAKAN KEPADA RESPONDEN/ UPAYAKAN TANPA PENDAMPING)
Now I would like to give questions regarding pregnancy during the last five years (since 1 January 2005)
De01

In the last five years,
Was there pregnancy which ended at the period of pregnancy < 22
weeks (< 5 months)?

1. Yes, has experienced
2. Never→ De05

□

De02

Was there an intention to terminate the pregnancy?

1. Yes
2. No → De05

□

De03

If the answer is Yes, what was done to terminate the pregnancy? (answers can be more than one). Fill in answer
code with 1= Yes or 2 = No

123

a. Herbs
b.

Pill

□
□

c. Massage
d. Injection

□
□

e. Suction
f. Curette

□
□

g. Others, please state ...................

De04

Who helped during the miscarriage?

De05

In the last five years, was there any unwanted pregnancy?

1. Yes

2. No → De1 1

□

De06

Was there intention to terminate the pregnancy?

1. Yes

2. No → De1 1

□

De07

De08

4.By herself
5. Others, please state…

□

1.Doctor
2.Midwife
3.Traditional
healer/nursemidwife

□

If the answer is Yes, what was done to terminate the pregnancy? (answer may be more than one) with answer
code 1= Yes or 2 = No

a. Herbal remedy

□

c. Massage

□

e. Suction

□

g. Others,

b. Pills

□

d. Injection

□

f. Curette

□

Please state ..........

Did anyone help?

De09

Was the intention to terminate the
pregnancy successful?

De10

What was the reason for terminating the
pregnancy

4.
5.

1. Doctor
2. Midwife

Herself
Others, please state

3. Traditional healer/nursemidwife
1. Yes
2. No → De11

1.
2.
3.
4.

5. Economic reasons
6. Busy from work
7. 7. Others (please state…….)

Health Problems
Too many children
Too close/frequent
Age

124

□
□
□
□

De11

IF THE RESPONDENT IS MALE OR FEMALE AGED 10-24 YEARS → TO P.Df01
IF THE RESPONDENT IS MALE OR FEMALE AGED 25 YEARS AND OVER → BLOCK IX. CONSUMPTION

Df. SEXUAL BEHAVIOR (Especially for Household Member Aged10-24 years)
THIS PART MUST BE ANSWERED BY THE RESPONDENT HIM/HERSELF (MUST NOT BE ACCOMPANIED)
Now I would like to give six questions (Df01 – Df06) on sex. Please apologize if it is too personal
Has [NAME] had sexual intercourse?
1. Yes 2. No →Df06

Df01
Df02

Df03
Df04

Df05

Df06

With whom did [NAME] do sexual intercourse for
the first time DO NOT READ THE ANSWER
ALTERNATIVES

How old was [NAME] when having the sexual
intercourse
When having the first sexual intercourse, did [NAME]
or partner used contraception/birth control to
prevent pregnancy?
The use of which contraception /birth control that
[NAME] or partner choose when having first
intercourse?
DO NOT READ ANSWER ALTERNATIVES

Has [NAME] had information on reproductive
health?

□

1. Husband/ wife
2. Friend
3. Boy/girlfriend
4. Family
5. Sex Worker/prostitute
6. Others, please state...

□

Age in years ............................ years
Don’t know 88 →Df06

□

1. Yes
2. No →Df06

□

8. Don’t know/ don’t remember →Df06

1.
2.
3.
4.

Condom
Pill
Diaphragm/intravag
Coitus interruptus/withdrawal
5. Others, please state ..............................

1. Yes
2. No

□

□

125

CONTINUE TO BLOCK IX. CONSUMPTION

126

E. CHILD HEALTH
Ea. Health record of babies and children under-five years of age (Esp. household member aged 0-59 mo)
Ea01

Write name and order of biological mother [NAME]
IF BIOLOGICAL MOTHER DOES NOT LIVE IN SAMPLE
HOUSEHOLD (NOT HOUSEHOLD MEMBER) FILL IN ”00”

Biological
mother’s name
......................

Ea02

a. If biological mother is not a household member ,
is the biological mother [NAME]
b. If biological mother [NAME]
has passed away, did she die

Ea03

□□

8. Don’t know→Ea03

1. During pregnancy
4. Accident
2. While giving birth
5. Others
3. Less than 2 months after giving birth

a. Who helped in the process of giving birth (NAME)? [Fill in answer
code directly to the box]
1. Doctor
3. Other paramedics
5. Relatives/ Family
2. Midwife
4. Traditional birth attendant
6. Others, please state ....
b. Where was [NAME] born :
1. State Hospital
2. Private Hospital
3. Maternity Hospital/ Maternity Center
4. Public Health Center

Ea04

1. Still alive→Ea03
2. Has passed away

Mother’s order
in household
member:

05.
06.
07.
08

When [NAME] was born, was he/she weighed
(weight of baby within 48 hours)

a. First aid
b. Last aid

Supporting Public Health Center
09. At home
Doctor’s Practice
10. Others, ............
Midwife Practice
Village Maternity Center/Village Health Post
1. Yes
8. Don’t know → Ea07

2. No →Ea07

Ea05

If the answer is “Yes”, what was the weight of [NAME] when born
(Write in unit of gram)

Ea06

What is the source of [NAME]’s weight information when born
1. KMS/KIA Book/Health Note Book/birth notes 2. Mother/other household member’s admitting or
memory

127

................... gram

□
□
□
□
□□

□
□□□
□

Ea07

Ea08

What kind of medicine/remedy was used to treat [NAME]’s umbilical cord right after being born
1. Not given anything
3. Sprinkled medicine (powder form)
8. Don’t know
2. Betadine/ alcohol
4. Concoction / Traditional remedy
Did [NAME] get health service (was visited/visited) in: (BREAD OUT POINTS a TO d) FILL IN WITH THE
CODE 1 = YES 2 = NO 7 = DOES NOT APPLY 8 = DON’T KNOW
a. 6–48 hours after being
born

b. 3–7 days after being
born

□

c. 8–28 days after being
born

d. >28 days after being
born

□

□

IF ANSWER CODE Ea08 (a TO d) ALL OF THEM 2 OR 7 OR 8 →Ea11
Ea09

Where did [NAME] receive health service at the time?
State Hospital
6. Private Polyclinic
Private Hospital
7. Health Worker Practice
Maternity Hospital
8. At home
Public Health Center/
9. Does not
Supporting Public Health Center/
Community Public Health Center
5. Village Health Post/Integrated Service Center apply

1.
2.
3.
4.

Ea10

□

a. 6 – 48 hours after being born

□

c. 3 – 7 days after being born

□

c. 8 – 28 days after being born

□

d. > 28 days after being born

□

Type of health service received when [NAME] was 6 – 48 hours after being born: FILL IN WITH CODE 1 = YES
OR 2 = NO OR 8 = DON’T KNOW
(IF AT 6 - 48 HOURS OLD [NAME] WASNOT CHECKED, FILL IN ALL WITH CODE”2”)

a. Given Hepatitis B (HB-0)Immunization
b. Given ointment for eyes/eye drop
Ea11

□

□
□

□
d. Others, please state .................................................. □
c. Vitamin K injection

Since [NAME] was born until he/she was 28 days old, has
[NAME] been suffering from illness?

1. Yes
2. No →Ea13
8. Don’t know → Ea13

128

□

Ea12

When ill, did [NAME] see any health practitioners?

Ea13

Does [NAME] have health notes in the form of KS
1. Yes, able to show
2. Yes, is not able to show(kept by cadre/ nurse/
in Integrated Service Post/Integrated Service Post)
Does [NAME] have health note in the form of KIA Book
1. Yes, able to show
2. Yes, is not able to show(kept by cadre/ nurse/
in Integrated Service Post/Integrated Service Post)

Ea14

Ea15

1. Yes
8. Don’t know

2. No

3. Used to have one, but has lost it

□
□

4. has never owned one
3. Used to have one, but has lost it

□

4. has never owned one

Has [NAME] owned other health notes such as Child Health Note Book (Beside KMS and KIA Book)
1. Yes, able to show
3. Used to have one, but has lost it
2. Yes, was not able to show (kept in another place)
4. has never owned one

□

IF ANSWER CODE Ea13 S/D Ea15 ALL ARE CODED 2 OR 3 OR 4 →Ea18
Ea16

Ea17

1.
2.

Was there immunization notes in [NAME]’s KMS/ KIA Book/
Child Health Note Book

Yes
No →Ea18

□

Copy from KMS/KIA BOOK/CHILD HEALTH NOTE, date.. / month..../year for each type of immunization.
FILL IN 1177” IN ’DATE/MONTH/YEAR’ COLUMN, IF CHILD’S AGE IS NOT THE AGE TO BE GIVEN
IMMUNISATION YET
FILL IN 1188” IN ’DATE/MONTH/YEAR’, IF THE CARD SHOWS THAT IMMUNISATION WAS GIVEN,
BUT THE DATE/MONTH/YEAR WAS NOT STATED.
FILL IN 1199” IN THE COLUMN FOR ’DATE/MONTH/YEAR’, IF IMMUNISATION WAS NOT GIVEN
a. Hepatiitis B 0

□□/□□/□□

f. Polio 1

□□/□□/□□

b. BCG

□□/□□/□□

g. Polio 2

□□/□□/□□

c. DPT –HB Combo1

□□/□□/□□

h. Polio 3

□□/□□/□□

129

d. DPT-HB Combo 2

□□/□□/□□

i. Polio 4

□□/□□/□□

e. DPT-HB Combo 3

□□/□□/□□

j. Measles

□□/□□/□□

130

IF THE IMMUNISATION NOTE OF ART/HOUSEHOLD MEMBER IS COMPLETE, CONTINUE TO Ea19
IFIMMUNISATION OF ART/HOUSEHOLD MEMBER IS INCOMPLETE, CONTINUE TO Ea18
Ea18

Has [NAME] ever got the following immunization : (INFORMATION CAN BE OBTAINED FROM VARIOUS
SOURCES)
a. Hepatitis B-0 immunization, usually given right after the
baby is born until the baby is 7 days old, injected on the
thigh?

1. Yes
2. No →Ea18e 8. Don’t know →Ea18c

□

b. At how many days old was [NAME] given
Hepatitis B 0 immunization? IF THE ANSWER
IS DON’T KNOW FILL IN ”88” FOR DAYS
(usually HB-0 is given at 0-7 days)
c. BCG immunization which usually starts to be given at
1 day old and injected on the upper arm or thigh also
leaves a (scar) under the skin?

.........… days

1. Yes
2. No →Ea18e 8. Don’t know →Ea18e

d. At what age was [NAME] given BCG immunization?
(FILL IN DAY OR MONTH) IF THE ANSWER IS
DON’T KNOW FILL IN THE CODE ”88” FOR DAYS
AND MONTHS
e. Polio immunization, pink or white fluid which usually
starts to be given at 2 months old and dripped into the
mouth?

□

............ days
.............. months

1. Yes
2. No →Ea18h
7. Not time yet (not 2 months old yet)

□
□
□
□

→Ea18h
f. At what age was [NAME] first given polio
immunization? IF DON’T KNOW FILL IN “88”
UNTUK BULAN

8. Don’t know 4Ea18h
………. months

g. How many times was [NAME] given polio immunization?

………. times

131

□□
□

h. DPT-HB combo (Diphteria Pertusis Tetanus-Hepatitis
B immunization (combo) usually injected on the thigh
and usually starts to be given when the child is 2
months old given at the same time as polio?

1. Yes
2. No →Ea18k
7. Not time yet (not yet 2 months old)

□

→Ea18k

8. Don’t know →Ea18k
i. At what age did (NAME) first given DPT-HB Combo
immunization. ”IF DON’T KNOW FILL IN CODE “88”

………. months

j. How many times has [NAME] been given DPT-HB Combo
immunization?
k. Measles immunization which usually starts to be given at
9 months old and injected on the thigh also given one
time?
Ea19

………. times
1. Yes
2. No
7. Not time yet (not 9 months old yet)
8. Don’t know

In the last 6 months, how many times has [NAME] been
weighed? IF JIKA TIDAK PERNAH
WEIGHED, FILL IN CODE ” OR IF ”DON’T KNOW”,
FILL IN CODE ”88” →Ea21

........................... times

132

□□
□
□
□□

Ea20

Ea21

Where does [NAME] most often weighed?
1. Hospital
2. Public Health Center/Supporting
3. Village Maternity House …….

4. Posyandu (Integrated Service Post)
5. Poskesdes (Village Health Post)
6. Others, please state

Has in the last 6 months [NAME] been getting capsule
vitamin A? (USE PROP CARDS)

1. Yes
yet)
2. No

7. Not yet time (not 6 months
8. Don’t know

□
□

IF HOUSEHOLD MEMBER AGED 24 – 59 MONTHS →Ea22
IF HOUSEHOLD MEMBER AGED 0 – 23 MONTHS →Eb01

Ea22 ESPECIALLY FOR HOUSEHOLD MEMNER AGED 24 – 59 MONTHS
Ea22

Does [NAME] have anomaly/handicap : FILL IN WITH CODE 1=YES OR 2=NO
a. Blind (sight) → OBSERVATION
b. Hearing impairment (hearing) →
OBSERVATION
c. Speech impairment (speech) →
OBSERVATION
d. Mentally disabled (mental) →
OBSERVATION

□
□
□
□

e.Disabled (body) → OBSERVATION
f. Down Syndrome → USE PROP CARDS
g. Cerebral Palsy→ USE PROP CARDS
h. Others, please state .......................

□
□
□
□

CONTINUE TO BLOCK IX. CONSUMPTION
Eb. BREASTMILK AND BABY FOOD (ESPECIALLY FOR HOUSEHOLD MEMBER AGED
0 – 23 MONTHS)
1.

Yes
2. No →
Eb09

Eb01

Has [NAME] been breast-fed (given breast milk)?

Eb02

When did [NAME] started to be breast-fed by the mother for the first time, after being born?
IF LESS THAN 1 HOUR, WRITE 00;
IF LESS THAN 24 HOURS, WRITE IN HOUR;
IF 24 HOURS OR MORE WRITE IN DAY

133

□

□□

a. ............. hours

b. ...................................... days

Eb03

What did [NAME’S mother] do to the colostrum (the very first breast milk, usually watery, clear and or
yellowish in color)?
1. Given all to the baby
3. Discarded all, then breast milk was given to the baby
2. Discarded a little then breast milk was given to the baby 8. Don’t know

Eb04

Was before given breast milk for the first time or before breast
milk was available,
[NAME] given drinks (liquid) or food besides

Eb05

Eb08

8. Don’t Know →Eb06

□

e. Rice broth

□

i. Honey/ Honey + water

□

b. Non formula milk

□

f.Coconut Water

□

j. Mashed banana

□

□
□

g. Squeezed fruit/ fruit juice
h. Sweet tea

□
□

Is [NAMA] still breast-fed at present?

k. Mashed rice
l. Others, please state
1. Yes →Eb08

At how many months old was [NAME] weaned/started
not to be given breast milk anymore? If the answer is
don’t
know
write
88[NAME] only get breast milk (not given
Is in the
last 24
hours

2. No

...... month →Eb09
1. Yes

fluid/food besides breast milk)
Eb09

□

a. Formula milk

d. Sugar water

Eb07

2. No →Eb06

What drinks/food were given to [NAME] before breast milk was available?
TO BE READ AND FILL IN WITH CODE 1= YES OR 2=NO

c. Plain water

Eb06

1. Yes

□□
□

2. No

Since when (at how many days/months old) did [NAME] started to be given drinks (fluid) or food
besides breast milk:
1. 0 – 7 days
4. 2 – < 3 months
7. ≥ 6 months
2. 8 – 28 days
5. 3 – < 4 months
8. Don’t know
3. 29 days – < 2 months 6. 4 – < 6 months
9. Not given food besides breast milk yet (breast
milk)
→BLOCK IX. CONSUMPTION

134

□
□
□
□□
□
□

Eb10

What kind of drinks (fluid) or food besides breast milk were started to be given to [NAME] at
that age (According to answer Eb09)
1. Formula Milk
5. Squeezed fruit/ fruit juice
2. Non-formula Milk
6. Flour porridge/ sifted porridge
3. Rice broth
7. Rice Porridge/ steamed rice/ mashed rice
4. Mashed banana
8. Others ...

□

BLOCK IX. INDIVIDUAL FOOD CONSUMPTION - 24 HOURS AGO (All Ages)

□

1. Days of interview :
1. Monday – Friday;
2. Saturday _Sunday

Time

Menu

Food Ingredient

2.Condition during interview :
1. The usual;
2. Holding event;
3. Religious Holidays/events;
Ingredient Code

Morning

Variety

Noon

135

□
4. Fasting;
5. Ill;
6. Diet.

Household Size

Weight
(gram)

Variety

Night

3. Does it still get breast milk : 1. Yes; 2. No
day and night (24 hours ago)

□;

4. If the answer is Yes, Frequency of getting breast milk :

□□times

X. BODY HEIGHT/ LENGTH AND WEIGHT MEASUREMENTS
ALL AGES
1 a. Was household
member weighed?
2a. Was household
member measured?

1. Yes

2. No →X2a

1. Yes

2. No →XI

□
□

1

b. Body Weight (kg)

2

b. Body Height/ Body Length
(cm)

□□□
□□□

2c. ESPECIALLY FOR TODDLERS, Position of Measuring

□

BH/BL
1. Standing

136

2. Laying on Back

XI. LABORATORY EXAMINATION

Sticker
Number

STICK THE NUMBER STICKER (7 DIGITS) HERE

RDT EXAMINATION (ALL AGES)
Examination of RDT?

1

1. Yes
2. No →XI.6

□

IF THE ANSWER IS YES, ANSWERS 2a – 5 QUOTED FROM FORM M1

1.

a. Date of finger blood sampling

□□-□□-□□□□

b. Name of finger blood taker............................

3. Is /Has [NAME] :

a. Suffering from fever in the last 2 days?

1.

Yes

2. No

□
1. Yes
2. No
b. Taking medicine of ACT program in this 1 month?
□
c. Suffered from malaria before in the last 1 month?
1. Yes
2. No
□
d. Received blood transfusion in the last 1 month?
1. Yes
2. No
□
e. Stayed over out of town in the last 1 month? Please state
1. Yes
2. No
□
b. Time of reading of RDT Hour □□ Minute □□
4. a. Time of buffer drops:
Hour □□ Minute □ □
1.
2.
3.
4.

Negative
Plasmodium falcifarum (Pf)
Plasmodium vivax (Pv)
Pf and Pv (Mix)
5.Result is not valid

5.. Result of blood dipstick examination (Rapid Diagnostic Test)

THICK BLOOD SMEAR SUPPLY (ALL AGES)

137

□

6.

Was Thick Blood Smear Supply taken?

1.

Yes

□

2. No

SPUTUM (ESPECIALLY HOUSEHOLD MEMBERS AGED ≥ 15 YEARS)
7. Sputum Taking

a. At same time

1. Yes

2. No

b. Morning

1. Yes

2. No

138

□
□

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