AN ASIAN INDIAN DIETARY ACCULTURATION MEASURE: INSTRUMENT
DEVELOPMENT AND VALIDATION
By
Sumathi Venkatesh

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Human Nutrition – Doctor of Philosophy
2014

1

ABSTRACT
AN ASIAN INDIAN DIETARY ACCULTURATION MEASURE: INSTRUMENT
DEVELOPMENT AND VALIDATION
By
Sumathi Venkatesh
Background: Asian Indian adults in the U.S. (~1% of the total population) have a high
prevalence of type 2 diabetes (ranging from 17%-29%) and other diet-related problems. A key
associative factor could be unhealthy changes in dietary practices because exposure to the host
culture may potentially negatively change dietary behaviors and food preparation practices
(dietary acculturation). An assessment of dietary acculturation using an appropriate and
culturally sensitive measure is therefore critical for understanding if and how dietary changes
occur in those who relocate to another country. This will facilitate the efficacy of culturally
sensitive interventions.
Specific aims: The three specific aims of this study were: (i) to qualitatively examine the factors
influencing the dietary acculturation behaviors of Asian Indian adults in the U.S., (ii) to develop
a culturally sensitive, reliable and valid Asian Indian Dietary Acculturation Measure (AIDAM),
and (iii) to examine the relationship between AIDAM scores and the risk for type 2 diabetes
among Asian Indians.
Methods: For specific aim 1, eight audio-taped focus group discussions (2-5 members/ group)
and assessment of typical weekday and weekend 24 hour dietary recalls were conducted with 30
Asian Indian adults in Michigan. Verbatim focus group transcripts and dietary recalls were
qualitatively analyzed for generating themes. To accomplish specific aim 2, themes that evolved
from the focus group discussions were used to generate items for the AIDAM, which was revised
by 10 experts in nutrition/survey research and pre-tested with 12 Asian Indians. A web-based
ii

study was conducted with 225 Asian Indians in the U.S. to determine the reliability and validity
of AIDAM. A Rasch rating scale model was used to determine reliability and construct validity.
To achieve specific aim 3, the Finnish Diabetes Risk Score (FINDRISC), a validated tool to
determine diabetes risk in 10 years was completed with the web-survey. The associations
between AIDAM and FINDRISC scores were examined using correlations and relative risk
ratios.
Results: The key reported factors that emerged relative to modification of traditional eating
behaviors were: social independence, social network influences, increased health awareness, substandard taste and increased cost of Asian Indian foods, time constraints, and convenience
(specific aim 1). These findings were used for generating AIDAM items. The estimates from
Rasch model analysis showed the 50 item AIDAM to be a reliable and valid measure with
reliability of 0.88. The infit and outfit MNSQ statistics of the items were within the range of 0.58
– 0.61 indicating good model fit (specific aim 2). Comparison of AIDAM with FINDRISC
scores showed that adaptation to the U.S. dietary practices by Asian Indians (AIDAM scores
>2.8) increased the likelihood of developing type 2 diabetes (relative risk 1.6, confidence interval
1.02-2.51) (specific aim 3).
Conclusion: This dissertation: (i) documented dietary behaviors and influential factors of Asian
Indian adults over time in the U.S., (ii) utilized findings for the development of a validated
dietary acculturation assessment tool, and (iii) showed the association of AIDAM with type 2
diabetes risk. These findings are relevant for nutrition/health professionals to better understand
Asian Indian food choices over time and health implications.

iii

Copyright by
SUMATHI VENKATESH
2014

iv

ACKNOWLEDGEMENTS

I am very thankful to my academic advisor Dr. Lorraine Weatherspoon who was very
approachable as a mentor and was a great support for me both academically and otherwise. My
sincere thanks to my guidance committee members Dr. Lorraine Weatherspoon, Dr. Won Song,
Dr. Beth Olson, and Dr. Thomas Conner for their expert comments and inputs, which enhanced
the quality of this research. I would like to acknowledge Dr. Marsha Carolan, Dr. Shabnam
Momin, and Dr. Deepa Handu for revising the focus group guide for the qualitative piece of my
dissertation, and Dr. Sudha Raj, Dr. Karmeen Kulkarni, Ms. Moushumi Mukherjee, Ms. Parul
Shah, Ms. Rita Batheja, Dr. Ranjita Misra, Ms. Padmini Balagopal, Ms. Karen Clark, Dr. Ryan
Bowles, and Dr. Merley Mathew who were the expert reviewers of the dietary acculturation
instrument. I thank the Blue Cross Blue Shield Foundation of Michigan, the Michigan State
University Graduate School, and The Alliance for Graduate Education and the Professoriate for
providing funding support for my research. Last but not the least; I thank my family in India and
a special thanks to my husband Dr. Venkatesh Balan and my daughters Supritha and Samyuktha
for all the love and support.

v

TABLE OF CONTENTS
LIST OF TABLES ......................................................................................................................... ix
LIST OF FIGURES ....................................................................................................................... xi
CHAPTER 1 - INTRODUCTION .................................................................................................. 1
I. Background .............................................................................................................................. 1
II. Specific aims .......................................................................................................................... 3
III. Significance........................................................................................................................... 4
CHAPTER 2 - REVIEW OF LITERATURE ................................................................................. 5
I. Theoretical Model for Dietary Acculturation .......................................................................... 5
II. Dietary Patterns of Asian Indians relocated to other countries .............................................. 7
III. Measures of Acculturation for Asians and Relation to Food ................................................ 9
IV. Scales used for Asian Indians ............................................................................................. 12
V. Measures of Dietary Acculturation ...................................................................................... 13
VI. Dietary Acculturation Measure for Asian Indians .............................................................. 16
VII. Justification for a Dietary Acculturation Scale ................................................................. 18
VIII. Type 2 Diabetes Prevalence and Risk Factors ................................................................. 19
CHAPTER 3 - METHODS........................................................................................................... 25
I. Phase 1 (Qualitative) ............................................................................................................. 25
II. Phase 2 (Quantitative) .......................................................................................................... 26
CHAPTER 4 - RESULTS............................................................................................................. 30
I. Manuscript 1 (specific aim 1) ................................................................................................ 30
Abstract ................................................................................................................................. 30
Introduction ........................................................................................................................... 31
Methods................................................................................................................................. 34
Focus group guide ............................................................................................................. 36
Typical day dietary recalls ................................................................................................ 38
Data analysis ..................................................................................................................... 38
Results ................................................................................................................................... 39
Sample Characteristics ...................................................................................................... 39
Typical weekday and weekend dietary intake of participants .......................................... 40
Thematic findings ............................................................................................................. 44
Facilitators of dietary acculturation .................................................................................. 44
Facilitators of traditional food consumption ..................................................................... 55
Discussion ............................................................................................................................. 61
Social independence.......................................................................................................... 62
Social network influences for consuming non-Indian foods ............................................ 63
Increased health awareness ............................................................................................... 65
Sub-standard taste and increased cost of Asian Indian snacks/ restaurant foods ............. 66
Ability to cook Asian Indian foods, time constraints and convenience ............................ 68
Strengths and limitations................................................................................................... 69
vi

Conclusion ............................................................................................................................ 70
II. Manuscript 2 (specific aim 2)............................................................................................... 71
Abstract ................................................................................................................................. 71
Introduction ........................................................................................................................... 72
Methods................................................................................................................................. 75
Asian Indian Dietary Acculturation Measure (AIDAM) .................................................. 76
Food frequency questionnaire ........................................................................................... 80
Data analysis ..................................................................................................................... 82
Results ................................................................................................................................... 84
Sample Characteristics ...................................................................................................... 84
AIDAM: Model fit, reliability and validity ...................................................................... 85
Correlation between AIDAM and AI-FFQ and NI-FFQ scores ....................................... 91
Relationship of AIDAM with participant sociodemographic characteristics and AI-FFQ
and NI-FFQ scores ............................................................................................................ 91
Discussion ............................................................................................................................. 94
Strengths and limitations................................................................................................... 99
Conclusion .......................................................................................................................... 100
III. Manuscript 3 (specific aim 3) ........................................................................................... 101
Abstract ............................................................................................................................... 101
Introduction ......................................................................................................................... 102
Methods............................................................................................................................... 107
Asian Indian Dietary Acculturation Measure (AIDAM) ................................................ 107
The Finnish Diabetes Risk Score (FINDRISC) .............................................................. 108
Data analysis ................................................................................................................... 109
Results ................................................................................................................................. 110
Sample characteristics ..................................................................................................... 110
Participants’ FINDRISC scores ...................................................................................... 111
Relation between FINDRISC and AIDAM .................................................................... 113
Discussion ........................................................................................................................... 114
Strengths and limitations................................................................................................. 117
Conclusion .......................................................................................................................... 118
CHAPTER 5 - SUMMARY ....................................................................................................... 120
I. Main findings ....................................................................................................................... 120
II. Future Directions ................................................................................................................ 122
III. Innovation ......................................................................................................................... 123
APPENDICES ............................................................................................................................ 125
Appendix 1 - IRB approval ..................................................................................................... 126
Appendix 2 - Research flyer ................................................................................................... 127
Appendix 3 - Research participant informed consent form (A) ............................................. 128
Appendix 4 - Sociodemographic survey ................................................................................. 130
Appendix 5 - Focus group questions ...................................................................................... 131
Appendix 6 - 24-hour dietary recall ........................................................................................ 132
Appendix 7 – Expert review of focus group guide ................................................................. 133
Appendix 8 - Codebook for focus group analysis .................................................................. 134
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Appendix 9 – Expert review of Asian Indian Dietary Acculturation Measure (AIDAM) and
food frequency questions ........................................................................................................ 137
Appendix 10 – Asian Indian Dietary Acculturation Measure (AIDAM) pilot test results (n=12)
................................................................................................................................................. 139
Appendix 11 – Location of residence of web-survey participants (n=225)............................ 142
Appendix 12 – Comparison of demographic profile of Asian Indians participants and nonparticipants .............................................................................................................................. 143
Appendix 13 - Research participant informed consent form (B) ............................................ 144
Appendix 14 - Questions on demographic characteristics, diet, and general health .............. 145
Appendix 15 - Food frequency assessment ............................................................................ 149
Appendix 16 - The Finnish Diabetes Risk Score (FINDRISC) assessment ........................... 151
Appendix 17 – Validated Asian Indian Dietary Acculturation Measure (AIDAM) ............... 153
Appendix 18 – Participant responses to the food frequency questionnaire ............................ 156
BIBLIOGRAPHY ....................................................................................................................... 159

viii

LIST OF TABLES

Table 1. Focus group questions based on the PRECEDE model .................................................. 37
Table 2. Participant characteristics (n=30) ................................................................................... 39
Table 3. Participant consumption of non-Indian, common, and Asian Indian foods (n=30) ....... 42
Table 3 (cont’d)............................................................................................................................. 43
Table 4. List of Asian Indian and non-Indian foods in the Food Frequency Questionnaire......... 81
Table 5. Sample characteristics (n=191) ....................................................................................... 85
Table 6: Descriptives and Rasch fit statistics of the Asian Indian Dietary Acculturation Measure
(AIDAM) (n=191) ........................................................................................................................ 88
Table 6 (cont’d)............................................................................................................................. 89
Table 6 (cont’d)............................................................................................................................. 90
Table 7. Sociodemographic predictors of dietary acculturation as measured by Asian Indian
Dietary Acculturation Measure (AIDAM).................................................................................... 92
Table 8. Participant characteristics (n=153) ............................................................................... 110
Table 9. Finnish Diabetes Risk Score (FINDRISC) components by dietary acculturation level
(n=153)........................................................................................................................................ 112
Table 10. The association (relative risk) between Asian Indian Dietary Acculturation Measure
(AIDAM) and Finnish Diabetes Risk Score (FINDRISC) (n = 153) ......................................... 113
Table 11. Codebook for focus group analysis ............................................................................ 134
Table 11 (cont’d)......................................................................................................................... 135
Table 11 (cont’d)......................................................................................................................... 136
Table 12. Asian Indian Dietary Acculturation Measure (AIDAM) – pilot test results (n=12) ... 139
Table 13: Mean scores for the Asian Indian Dietary Acculturation Measure (AIDAM) – pilot test
results (n=12) .............................................................................................................................. 140
Table 13 (cont’d)......................................................................................................................... 141
ix

Table 14. Location of residence of web-survey participants (n=225) ........................................ 142
Table 15. Comparison of demographic profile of participants with non-participants (n=1350) 143
Table 16. Participant responses for the food frequency questionnaire ....................................... 156
Table 16 (cont’d)......................................................................................................................... 157
Table 16 (cont’d)......................................................................................................................... 158

x

LIST OF FIGURES

Figure 1. Proposed Model of Dietary Acculturation ...................................................................... 6
Figure 2. Figure showing the two phases of data collection ......................................................... 29
Figure 3. Person/item map for the 50 item Asian Indian Dietary Acculturation Measure
(AIDAM) ...................................................................................................................................... 86
Figure 4. Research flyer for focus group recruitment ................................................................. 127
Figure 5. The Finnish Diabetes Risk Score (FINDRISC) assessment ........................................ 151

xi

CHAPTER 1 - INTRODUCTION

I. Background
Diet-related health disparities exist in the United States (U.S.) as evidenced by the
disproportionately high rates of chronic diseases such as type 2 diabetes, hypertension, and
cardiovascular disease among racial/ ethnic minority populations (Cowie et al., 2009, Egan et al.,
2010, Jolly et al., 2010). Asian Indians, the second largest Asian group in the U.S., constitute
nearly 1% (3.2 million) of the U.S. population (U.S. Census Bureau, 2012). A high prevalence of
diet-related chronic diseases, especially type 2 diabetes and cardiovascular disease and their risk
factors have been documented among Asian Indians living in other countries when compared to
the host population (Anand et al., 2000, Beckles et al., 1986, Dowse et al., 1990, Kanaya et al.,
2010, Marine et al., 1969, Misra et al., 2010b, Simmons et al., 1992, Thai et al., 1987,
Venkataraman et al., 2004, Zimmet et al., 1983). Dietary acculturation could be a possible
explanation for the high prevalence of type 2 diabetes and associated complications among Asian
Indians who relocate to the U.S.

When two or more cultures come into contact, psychological and cultural changes occur at
individual and group levels termed acculturation (Berry, 2005). Dietary acculturation is the
process that reflects the extent to which members of a migrating group adopt the eating patterns/
practices of their new environment (Satia-Abouta et al., 2002). Immigration and relocation
potentially influence the acquisition of varying levels of new dietary behaviors. It is well known
that individuals who immigrate/ relocate to other countries could have an altered dietary intake
(compared to their native/ home country) by including new foods available in the host country or
exclusion of foods consumed in the home country, which could be a consequence of dietary

1

acculturation (Dixon et al., 2000, Hubert et al., 2005, Jonnalagadda and Diwan, 2002, Raj et al.,
1999). These changes may or may not be healthful. Therefore it is important to study if and how
these changes occur and whether or not they result in healthy outcomes.

Methodologies currently used in the assessment of dietary behaviors/ patterns are subject to
certain limitations. Traditionally, diet and acculturation were independently captured using
different assessments to study dietary acculturation behaviors. Dietary assessment tools generally
encompass dietary recalls, food frequency questionnaires, or food diaries. These measures will
provide information about the nutrients and types of foods commonly consumed, but may not
serve as a measure of the changes that take place after relocation to another country. Similarly,
general acculturation scales or single item proxy measures (e.g. fluency in host language or
duration in the host country) have been widely employed in nutrition research to examine the
association between host country adaptation or lifestyle changes and specific health outcomes of
interest. However, these measures are limited from a dietary behavior perspective. There is
specifically a lack of culturally sensitive measures for use with Asian Indians that are solely
designed for the purpose of assessing the dietary acculturation level.

Therefore, the primary goal of this study was to develop and validate a culturally sensitive
dietary acculturation assessment tool for Asian Indians that can assess both dietary behaviors and
acculturation as a single measure. The rationale was that although there have been dietary
assessment tools used extensively to assess dietary quality in general in previous studies; there is
an overall lack of instruments available for Asian Indian specific foods and/ or adoption of host
culture foods. An increased understanding of culturally sensitive dietary patterns/practices is
2

critical for construction of an instrument that applies to a particular ethnicity. Therefore, survey
items to determine if and how dietary changes occur after relocation to the U.S. were identified
by examining the perceptions of a sample of Asian Indian adults.

In addition, it is not currently clear if and how dietary acculturation can demonstrate diet-related
disease risk. A quantitative measure of the overall changes in dietary pattern may explain the
diet-disease link and is hence an important consideration for diet-related chronic disease risk
assessment. Although the primary goal of the research was to develop a culture-specific dietary
acculturation instrument for Asian Indians, it was also important to test the value of the tool from
a health perspective and demonstrate the potential for future use in either research or healthcare
professional assessment. Therefore, we examined the relationship between the dietary
acculturation level of Asian Indians and their risk for the development of type 2 diabetes. The
disproportionately high prevalence of type 2 diabetes among Asian Indians in the U.S. (17%29%) was the reason for choosing type 2 diabetes among other diet-related chronic diseases.

II. Specific aims
Specific aim 1: To qualitatively examine the factors influencing the dietary acculturation
behaviors of Asian Indians in the U.S.
Specific aim 2: To develop a culturally sensitive, reliable and valid Asian Indian Dietary
Acculturation Measure (AIDAM)
Specific aim 3: To examine if the dietary acculturation score is related to diet-disease risk,
specifically type 2 diabetes among participating Asian Indians.

3

III. Significance
It was expected that the three specific aims would yield the following outcomes. First this study
would provide a measure of dietary acculturation for use with Asian Indian adults in the U.S.
This tool could be used to identify the trend in the dietary behavior and the dietary changes made
due to host country environmental exposure. Second, findings would help to improve the
understanding of nutrition/ health professionals about the quality of Asian Indian food choices
and preferences. The high prevalence and risk factors for chronic diseases in conjunction with
the remarkable increase in immigration/ relocation of Asian Indians to the U.S. makes this study
timely and important. Third, the instrument was constructed in such a manner that in the future
researchers and/ or healthcare professionals can use this instrument to examine the association
between dietary acculturation and the risk factors for chronic diseases in the Asian Indian
population. Therefore, the goal of the study was to make a significant contribution to the
literature on how to assess dietary patterns of individuals who relocate to other countries. It is
important to understand the specific dietary patterns of a particular ethnicity before offering
dietary recommendations or developing intervention strategies. Such interventions are critical to
long term advancement in the nutritional/ health status of this growing population.

4

CHAPTER 2 - REVIEW OF LITERATURE

I. Theoretical Model for Dietary Acculturation
Dietary acculturation occurs when individuals who relocate to another country adopt at varying
levels, the eating patterns and food choices of their new environment (Negy and Woods, 1992).
Relocation to another country results in exposure to a new environment, which includes foods
and food supply. According to the conceptual model of dietary acculturation, exposure to the
host culture, socio-demographic (sex, age, age at relocation, duration in the host country,
education, income, employment, marital status, generational characteristics of household
members, fluency with host language, location of residence, country of origin, rural vs. urban
residence in country of origin, and voluntary vs. non-voluntary migration) and cultural factors
(religion, cultural beliefs, attitudes, and values, and residence in an ethnic enclave) could lead to
psychosocial changes, changes in taste preferences, and changes in food purchasing and
preparation (environmental changes) resulting in different patterns of dietary intake (SatiaAbouta et al., 2002) (see figure 1).

As indicated in the conceptual model, socio-demographic factors play a role in food choices
and dietary behaviors. Age has been shown to be relate to the choice of foods such as higher fruit
and vegetable consumption by older individuals versus higher fat consumption by those who are
younger (McClelland et al., 1998, Kayrooz et al., 1998). Likewise, lower education, income, and
lack of employment have been associated with increased fat intake (Eyler et al., 2004, Kayrooz
et al., 1998). Longer duration in the host country and fluency in host country’s language have
been shown to be indicators of increased dietary acculturation due to increased exposure to the
host culture (Lee et al., 1999, Raj et al., 1999, Satia-Abouta et al., 2000).

5

Figure 1. Proposed Model of Dietary Acculturation

Source: (Satia-Abouta et al., 2002)

Psychosocial factors (higher self-efficacy, belief about healthful eating, and social support from
friends and family) were shown to be associated with healthier food behaviors and nutrition
awareness such as increased consumption of fruits and vegetables, reduced fat intake and
increased nutrition knowledge (Campbell et al., 1999, McClelland et al., 1998, Satia-Abouta et
6

al., 2004, Satia-Abouta et al., 2005, Watters et al., 2007, Watters and Satia, 2009). Cultural
factors are important determinants of dietary practices. In the Asian Indian ethnic group,
religious beliefs play a vital role in food selection. Vegetarianism is followed with varying
degrees of strictness among several Asian Indian religious groups (Prashantham, 2008). Certain
types of meat are strictly prohibited such as beef by Hindus and pork by Muslims (Prashantham,
2008). Culture also determines how one perceives body image and size, which further impacts
dietary behavior and food choices. For example, the prevalence of eating disorders is less likely
in certain cultures, which may be due to acceptance of larger body sizes (Breitkopf and
Berenson, 2004, Kumanyika et al., 2005).

Lastly, environmental factors such as food availability, type of stores in the residential location,
cost of food, and social support have all been shown to influence the selection of foods by
individuals (Eyler et al., 2004, Vitolins et al., 2002). In a study by Satia-Abouta, environmental
factors such as food quality, cost, convenience, and availability of foods were the major
determinants and the most important contributors of dietary changes (Satia-Abouta et al., 2000).
Therefore, an assessment of dietary acculturation should be comprehensive enough to include the
assessment of the influence of these factors.

II. Dietary Patterns of Asian Indians relocated to other countries
Traditionally, refined carbohydrate such as dehulled white rice, semolina, and white flour have
been consumed in excess in India (Radhika et al., 2009). In southern India rice is commonly
consumed versus wheat in northern India (Malhotra, 1970, Prashantham, 2008). Practicing
vegetarianism is common among Asian Indians of Hindu descent; however, the frequency of

7

consuming a vegetarian diet and how strictly it is followed may differ among individuals within
this ethnic group (Prashantham, 2008). Food choices are to some extent determined by religion
because typically beef is prohibited in Hinduism and Muslims do not consume pork or meat that
is slaughtered inappropriately (Prashantham, 2008).

Dietary patterns and nutrient intake of Asian Indians who relocate to other countries have been
shown to differ from traditional eating patterns in India. For example, higher energy and fat
intake among Asian Indians in Britain was noted when compared to age, gender, and caste
matched Asian Indians in India (Patel et al., 2006). The two studies that focused on
acculturation/ duration of stay in the U.S. and dietary patterns of Asian Indians showed that
dietary acculturation of Asian Indians was associated with frequent selection of western foods
and replacement of traditional foods with western or other ethnic foods. Westernization of the
Asian Indian diet was characterized by increased consumption of animal and saturated fat and
convenience foods in the U.S. (Kulkarni, 2004). Increased consumption of alcohol, whole grain
foods, fish, poultry, meat, salty snacks, and desserts were also noted. Contrarily, a decline in
saturated fat and fiber content of foods and increased meat and convenience food consumption
by Asian Indians after moving to the U.S has also been shown (Jonnalagadda and Diwan, 2002,
Kulkarni, 2004).

Meal patterns of Asian Indians who relocate to western countries vary by the type of meal as
many Asian Indian families adapt to a western breakfast and lunch that consists of non-Indian
foods, but still consume an Indian dinner (Varghese and Moore-Orr, 2002). The typical foods
consumed by Asian Indians during the week and the weekends also seemed to differ (Raj et al.,

8

1999). Traditional mixed dishes made with legumes, vegetables, and cereals decreased during
the week because they require increased cooking time while the consumption of carbonated
drinks, fruit juice, snacks, fruits, margarine, and alcoholic beverages increased (Raj et al., 1999).
Jonnalagadda and Diwan examined the risk factors and nutrients of concern in the diet of Asian
Indians in the U.S., which showed the diet of Asian Indians to be directly related to their weight
status. Overweight status (BMI >25) was positively correlated with total fat intake (r=.027;
p<.05) (Jonnalagadda and Diwan, 2002).

III. Measures of Acculturation for Asians and Relation to Food
As defined earlier, acculturation refers to the psychological and cultural changes that occur at
individual and group levels when two or more cultures come into contact (Berry, 2005). Dietary
acculturation occurs when members of a migrating group adopt the eating patterns/ practices of
their new environment (Satia-Abouta et al., 2002). In studies that examined the dietary patterns
of a migrating group, diet and acculturation were assessed with separate measures. Dietary
assessment tools are generally in the form of dietary recalls, food frequency questionnaires, or
food diaries, which may not adequately capture dietary changes that take place after relocation.
On the other hand, acculturation scales or single item proxy measures (e.g. fluency in host
language or duration in the host country) have been used as acculturation measures, which are
limited from a dietary behavior perspective as they are not adequately captured. For example in a
previous study, we used the Suinn–Lew Asian Self-Identity Acculturation Scale (SL-ASIA) scale,
which had only a few items on dietary behaviors (Suinn et al., 1992, Venkatesh et al., 2013).

9

Most of the existing acculturation measures are single item ‘proxy’ measures such as language,
generation level, citizenship, or duration of stay in the host country, while other scales include a
few selected items on the assessment of food related behaviors (Cuellar et al., 1980, Griffith,
1983, Neff et al., 1987, Suinn et al., 1987). Single item measures, although easy to administer,
may not be comprehensive enough to capture all the domains of dietary acculturation as
postulated in the theoretical model of dietary acculturation. An instrument with multiple items
therefore is preferred. In a review of acculturation scales for Asians by Suinn, he broadly
classifies acculturation scales into two types: those that may be used for any culture also known
as “pan-ethnic” scales and those which focus on values and behaviors (Suinn, 2010).

Pan-ethnic Scales: Pan-ethnic scales are acculturation scales that could be modified for any
ethnic group. Examples include the Vancouver Index of Acculturation (VIA), Asian American
Multidimensional Acculturation Scale (AAMAS), the Multicultural Acculturation Scale (MAS),
and the Stephenson Multigroup Acculturation Scale (SMAS) (Chung et al., 2004, Ryder et al.,
2000, Stephenson, 2000, Wong-Rieger and Quintana, 1987). The Vancouver Index of
Acculturation (VIA) is a bidimensional instrument with twenty items. The scores range from 1
(low identification) to 9 (high identification). There are two sub-scores derived from this
measure: the heritage sub-score and the mainstream sub-score. However, this scale lack items on
dietary behavior (Ryder et al., 2000). On the other hand the other three scales included a few
items on food behavior.

The Asian American Multidimensional Acculturation Scale (AAMAS) was developed by Chung
et al., which has two items on food behavior which are (i) How much do you like the food of and

10

(ii) how often do you eat the food of (a) your own Asian culture of origin? (b) other Asian
groups in America? (c) the White mainstream groups?. The three answer options are assessed on
a scale of 1(not very well) to 6 (very well) (Chung et al., 2004). The Multicultural Acculturation
Scale (MAS) was developed for individuals from Vietnam and has three items that asks about (i)
foods eaten at home, how often (ii) Vietnamese and (iii) Anglo-American foods were cooked and
consumed at home (Wong-Rieger and Quintana, 1987). While the Stephenson Multigroup
Acculturation Scale (SMAS) has two items on food choice, which are: (i) I eat traditional foods
from my native culture and (ii) I like to eat American foods (Stephenson, 2000). As indicated,
these scales were not designed to exclusively measure dietary acculturation.

Values Scales: The two scales based on values are the Asian Values Scale, developed by Kim et
al., which has 36 items and the European American Scale for Asian Americans by Wolfe et al.
has 18 items to measure adherence to Asian cultural values by Asian Americans (Kim et al.,
1999, Wolfe et al., 2001). However, these scales were intended to measure acculturation of the
values of Asians, but not their behavior. Since dietary habits belong to lifestyle behavior
changes, assessment of changes in diet was not the focus of these scales.

Behavior Scales: Examples of the behavior scales are the Suinn–Lew Asian Self-Identity
Acculturation Scale (SL-ASIA) and the Marin Acculturation Scale (MAS) (Marin et al., 1987,
Suinn et al., 1987). The SL-ASIA is the most widely used instrument for measuring dietary
acculturation of Asians. There are two items in SL-ASIA that include food preference (i) at home
and (ii) in restaurants. Participants respond to these questions by checking any of the following
categories: (a) Exclusively Asian food, (b) Mostly Asian food, some American, (c) About

11

equally Asian and American, (d) Mostly American food, and (e) Exclusively American food.
The SL-ASIA was intended to measure the overall acculturation level of Asians and hence the
tool had only two items focused on dietary behaviors. On the other hand, the Marin
Acculturation Scale was developed and revised by Gupta et al. for Chinese Americans, and the
total scale includes 12 items on language choice and ethnic social relations. Unlike the SL-ASIA,
this scale lacks items on food behaviors (Gupta and Yick, 2001).

IV. Scales used for Asian Indians
In addition to these general Asian measures, a few studies modified existing scales for use with
Asian Indians such as the ARSMA-II by Farver et al. who investigated the influence of the
family on acculturation, ethnic identity achievement, and psychological functioning among
American-born Asian Indian adolescents (Cuellar et al., 1995, Farver et al., 2002). They
modified the scale, originally designed for Mexican Americans, by substituting the word Asian
Indian for Mexican. Both parents and adolescents completed the questionnaire and the study
found positive correlations between parent and adolescent ratings of their self-identification and
ethnic identity (Farver et al., 2002). Khairullah and colleagues used the Bicultural Involvement
Questionnaire (BIQ) (originally developed to assess the acculturation of Cubans) on 629 first
generation Asian Indians in the western New York region in the U.S. and examined its relation to
participant sociodemographic characteristics. The study showed that the scale was suitable for
use with Asian Indians to determine their acculturation level. However, out of the 24 scale items
used in this study only one was on food, which is “ I wish the food would be” and the response
categories are (a) Indian all of the time, (b) Indian most of the time, (c) Indian and American

12

equally, (d) American most of the time, and (e) American all of the time (Khairullah and
Khairullah, 1999, Szapocznik et al., 1978).

In a previous study, we modified the SL-ASIA for Asian Indians to examine the relation between
acculturation and diabetes control (Venkatesh et al., 2013). The unidimensional SL-ASIA scale
has 21 items that include items on language, identity, friendship choice, behaviors, generational
background, and attitudes. The instrument measures the degree of acculturation with Asian
culture at one end and the host culture at the other and was validated against generational
differences and duration of stay in the host country (Suinn et al., 1992). Although, these
measures have been shown to be successful in capturing the acculturation level of Asian Indians,
they were not intended for measuring dietary acculturation. Therefore, these scales are limited to
only a few items on food and dining behaviors, which may not be comprehensive enough to
capture all the factors involved in food procurement, preparation, and consumption behaviors of
the target population.

V. Measures of Dietary Acculturation
A few studies exclusively looked at dietary acculturation of ethnic groups that moved to another
country by either developing new or by using existing assessments. A food-list developed by
Yang et al was used to assess the dietary acculturation of Chinese who moved to Lincoln,
Nebraska (Yang and Fox, 1979). They assessed the current food habits, prior practices, and
changes in food consumption using a structured questionnaire. Food consumption was assessed
both quantitatively (participants reported increase or decrease in the consumption of 47 food

13

items commonly used in American and Chinese cooking) and qualitatively (recent 24-hr dietary
recall and one day typical menu).

Dietary acculturation was assessed using a Composite Adaptation Score (CAS) that was
calculated from participants’ responses to questions on whether participants liked or disliked
American foods; whether they miss Chinese foods; if they attempted to obtain ethnic foods from
specific places; participant self-evaluation of dietary changes; their interest in American cooking;
how they served the food; and the use of convenience foods. A higher score indicated increased
changes in food habits. Scores were also assigned for the information on food consumption and
the foods from the qualitative data were categorized into broader categories. The study showed a
mean CAS score of 23 out of 47 possible points. Individuals older than 36 years, those who were
fluent in English, those with American friends, and those who lived in dormitories scored higher,
which was indicative of more dietary changes. Scores were higher for women (vs. men), those
who were single (vs. married), and those with children (vs. those with none).

Satia-Abouta et al developed a western and a Chinese dietary acculturation scale, which was
administered to 244 Chinese women in selected cities in the U.S. and Canada (Satia-Abouta et
al., 2001). Qualitative in-depth interviews (n=30) and focus group discussions (n=2) were
conducted to obtain information on participants’ past and current dietary habits. Fifteen items
were developed based on this information, which were then divided into two scales with 5 items
in the Chinese and 10 items in the Western dietary acculturation scales, respectively. This scale
was used along with separate acculturation (age at relocation and media preference) and dietary
(food frequency questionnaire) measures to further examine the dietary patterns within the

14

Western and the Chinese dietary acculturation groups. The study showed that women who were
young, who had 13 years of education or more, employed outside home, and stayed longer in the
host country had higher western dietary acculturation scores. In addition western acculturation
was associated with increased fruit and vegetable intake but also a diet high in fat. It was
interesting to note that the Chinese dietary acculturation score was not associated with any of the
dietary variables.

Lv et al. examined the association between participants’ demographic characteristics and the
current the dietary practices of 399 Chinese Americans in Pennsylvania (Lv and Cason, 2003).
Length of stay in the U.S., English proficiency, and number of American friends were used as
indicators of acculturation. A food frequency questionnaire was used to collect the past year’s
dietary intake. In addition to these, 10 questions on general food habits were included. This study
documented age, gender, presence of children, and place of origin to be associated with dietary
acculturation of Chinese Americans. Bojanic et al. examined the relationship of dietary
acculturation and the dining behaviors of individuals from China, Taiwan, Hong Kong, and
Macau who were residing in the U.S. (Bojanic and Xu, 2006). The study adapted the ARSMA-II
scale for Chinese individuals to measure acculturation. Participants’ frequency of dining out
behaviors and their choice of restaurants were obtained. The study showed that the frequency of
dining out was significantly higher among those with higher levels of acculturation.

Kim and colleagues examined the dietary acculturation and diet quality of Korean Americans
and native Koreans (Kim et al., 2007). A food frequency questionnaire was used to collect
dietary information and to calculate participants’ diet quality using the revised Diet Quality

15

Index (scores ranging from 0 to 16 with a high score indicative of higher diet quality). The foods
were then categorized as Korean, American, and common foods (consumed both in Korea and
the U.S.). Although the Diet Quality Index did not differ between the groups, dietary
acculturation assessed as frequency of dining out and consumption of American foods, and fast
foods was higher among Korean Americans compared to native Koreans.

Pierce et al used confirmatory factor analysis to examine the dietary acculturation of Japanese
Americans (Pierce et al., 2007). They created two latent variables named as the Japanese and the
Western food factors (JFF and WFF, respectively). A culture specific food frequency
questionnaire was administered to 636 second and third generation Japanese Americans in
Seattle. Individuals who were second generation had higher JFF and lower WFF scores than the
third generation. However, these scales included culture specific food items that do not allow
adaptation of these measures to other ethnic groups.

VI. Dietary Acculturation Measure for Asian Indians
Varghese et al developed a measure to assess the dietary acculturation of Asian Indians who had
moved to Newfoundland (Varghese and Moore-Orr, 2002). They constructed a questionnaire that
consisted of five parts, which includes questions on sociodemographics, dietary practices,
attitudes towards food selection, nutrition knowledge, and health and nutrition needs assessment.
This study showed that Asian Indians continued to consume traditional foods for dinner while
changes after relocation were evident in breakfast, lunch, and snacks with increased consumption
of foods available in Canada. Increased consumption of meat and soft drinks were also noted.
Changes in food preparation methods include spending less time in cooking, frequent baking, use

16

of microwave, barbequing, trying international foods, and increased canned foods, meat and
cheese based dishes.

Many of the questions in the study by Varghese et al. are relevant to our study. Some of these
include, questions on vegetarianism (yes/no question), changes made in the diet within the past
one year, assessment of locally available alternate ingredients for cooking, subscales with
responses ranging from often to never to assess foods commonly consumed in India and Canada,
and statements on attitudes towards food selection for which participants responded on a four
point scale from Agree to strongly disagree. Although this instrument could be used in capturing
the dietary behaviors of Asian Indians, it lacked depth in the assessment of cultural,
psychosocial, and environmental factors that were specified in the conceptual model by SatiaAbouta et al. as potentially influencing factors that may lead to changes in food procurement,
preparation, and consumption.

Although the questionnaire used by Varghese et al. was appropriate to meet their study
objectives, adaptation of their instrument may not be comprehensive enough for the purpose of
our study, which is to develop a measure of dietary acculturation based on a grounded theory
approach. Moreover, some of the questions used in their instrument that pertained to the dietary
acculturation model were not embedded in the scale but served as separate questions. For
example information on vegetarianism was collected using a yes/ no question and changes in
food preparation methods were captured using an open ended question. Our study, however,
aims to develop a scale that can be used to calculate dietary acculturation as a single score in a
linear fashion.

17

VII. Justification for a Dietary Acculturation Scale
Dietary acculturation assessment measures are essential due to the rise in obesity and other dietrelated chronic diseases in ethnic minorities. Cultural sensitivity and appropriateness of such
measures are critical for developing dietary interventions aimed at attenuating the severity of
diet-related health/medical conditions, especially among populations of color with high risk such
as the Asian Indian. A review of literature on the instruments to measure dietary acculturation
revealed a gap related to the comprehensiveness of the measures used for assessing dietary
acculturation behaviors of Asian Indians who move to other countries, specifically the U.S.

Some of the measures used for determining acculturation did not focus on dietary acculturation
alone but included several other indicators of acculturation. Although the behavior acculturation
scales had a few items on food behavior, they did not provide any information about the factors
that influence the food behaviors. The dietary acculturation scales developed for other Asian
cultures such as the Chinese, Japanese, and Koreans contain culture specific foods that may not
be applicable for Asian Indians. The instrument developed by Varghese et al. for Asian Indians
in Canada is the closest to the scale visualized in our study of all the available measures.
However, this scale did not include the cultural, psychosocial, and environmental changes, as
specified in the Satia-Abouta dietary acculturation model, which was used as the theoretical
framework for the current study (Satia-Abouta et al., 2002).

Furthermore, the unique contribution of dietary acculturation towards the risk for diet-related
chronic disease among Asian Indians is not known yet. In order to understand if and how dietary
patterns/practices relate to acculturation and risk factors for chronic diet-related diseases, ethnic

18

specific exploration within a host country or environment is essential. The gap in the current
literature is on specific measures for the assessment of dietary acculturation for Asian Indians in
the U.S. Such measures are important to increase understanding of underlying problems
potentially related to dietary changes as a consequence of acculturation that may contribute to the
adverse health outcomes in this population, such as type 2 diabetes.

The rationale for examining the risk factors for type 2 diabetes is the high prevalence of type 2
diabetes among Asian Indians who moved to the U.S (Balasubramanyam et al., 2008, Kanaya et
al., 2010, Misra et al., 2010b, Rajpathak et al., 2010, Venkataraman et al., 2004, Wu et al., 2012).
In addition, type 2 diabetes is a serious global problem. Therefore examination of a diet-disease
link would provide an understanding of one of the environmental factors that may contribute to
increasing the risk for this disease.

VIII. Type 2 Diabetes Prevalence and Risk Factors
Type 2 diabetes, is disproportionately high among Asian Indians, one of the fastest growing
ethnic groups in the U.S. The prevalence of diabetes among Asian Indians in the U.S. was shown
to be 17.4% to as high as 29% (Balasubramanyam et al., 2008, Kanaya et al., 2010, Misra et al.,
2010b, Rajpathak et al., 2010, Venkataraman et al., 2004, Wu et al., 2012). These rates are much
higher than Native American adults (14.9%), non-Hispanic blacks (12.8%), non-Hispanic whites
(6.6%), and Hispanics (8.4%) in the NHANES 2005-2006 survey (Cowie et al., 2009, Harjo et
al., 2011). Furthermore, Asian Indians in the National Health Interview Surveys (NHIS) for 1997
– 2000/2005 had a greater likelihood (OR: 2.7, 95% CI: 1.7 to 4.1) of having diabetes than nonHispanic whites (Mohanty et al., 2005, Oza-Frank et al., 2009).

19

A higher diabetes prevalence among Asian Indians/South Asians (individuals from Pakistan, Sri
Lanka, Nepal, and Bangladesh) residing in other countries than the host populations have been
noted in countries with a considerable Asian Indian population, such as the United Kingdom,
Canada, Singapore, Mauritius, Fiji, Trinidad, and South Africa (Anand et al., 2000, Beckles et
al., 1986, Dowse et al., 1990, Marine et al., 1969, Thai et al., 1987, Zimmet et al., 1983). This
trend among Asian Indians who relocate to western countries such as the U.S. could be partly
attributed to dietary acculturation. If diabetes is not identified early or well controlled, the
propensity to develop devastating complications is greatly enhanced, and may lead to increased
medical costs and premature death.

Studies have shown that individuals with type 2 diabetes are at higher risk for stroke, heart
disease, hypertension, neuropathy, retinopathy, nephropathy, foot ulcers, dental problems,
blindness, and lower limb amputations than those without diabetes (Bunce and Wormald, 2006,
Foley and Collins, 2007, Fox et al., 2006, Johannesson et al., 2009, Klein et al., 1996, Lehto et
al., 1996, Mealey and Oates, 2006, Perneger et al., 1994, Ramsey et al., 1999, Saydah et al.,
2004, Tsai et al., 2002). Type 2 diabetes also increases the cost burden since it has been shown to
triple the medical cost compared to those without diabetes (Trogdon and Hylands, 2008).
Screening and early detection is therefore imperative to capture high risk individuals
(Groeneveld et al., 1999).

Obesity, sedentary lifestyle, race ethnicity (African American, Latino, Native American, Asian
Americans and Pacific Islanders), first-degree relatives with diabetes, hypertension, impaired
glucose tolerance/fasting glucose, abnormal lipid profiles, history of gestational diabetes or

20

delivery of macrosomic baby, polycystic ovary syndrome, hemoglobin A1c level>5.7, and other
clinical conditions associated with insulin resistance such as acanthosis nigricans are risk factors
for type 2 diabetes (American Diabetes Association, 2014). Asian Indians have additional
genetic risk factors such as high prevalence of insulin resistance, abdominal obesity, and
abnormal lipid profiles (Banerji et al., 1999, Chandalia et al., 1999, Enas et al., 2007, Misra and
Vikram, 2004, Raji et al., 2001, Ramachandran et al., 2004). These genetic risk factors increase
risk for type 2 diabetes at a relatively lower body mass index, which is in part due to their higher
body fat percentage even with smaller waist circumferences (Banerji et al., 1999, Chandalia et
al., 1999, Raji et al., 2001, Ramachandran et al., 2004).

In developing countries such as India, maternal malnutrition during the pre/postnatal stages may
also increase fetal/ infant malnutrition resulting in poor organ development such as the
pancreatic beta cells that could result in insulin resistance (Thrifty Phenotype Hypothesis) (Hales
and Barker, 2001). This was demonstrated in a study that documented increased adiposity and
circulating insulin in Asian Indian neonates compared to neonates of Caucasian origin (Yajnik et
al., 2002, Yajnik, 2004). It has also been postulated that when exposed to western lifestyles,
ethnic groups with a history of prolonged nutritional deprivation in the past may experience
gene-environment interactions that may increase their susceptibility to metabolic disorders
(Thrifty Genotype Hypothesis) (Bajaj and Banerji, 2004, Prentice et al., 2005). Lifestyle changes
upon relocation may aggravate the existing genetic risk factors or could serve as additional risk
factors.

21

Unhealthy dietary patterns and a sedentary lifestyle could also contribute to increased risk for
developing type 2 diabetes. In a prospective cohort study of U.S. men in the Health Professionals
Follow-up Study, two dietary pattern indices called the “prudent” (high intake of vegetables,
fruit, fish, poultry and whole grains) and “western” (high intake of red meat, processed meat,
French fries, high-fat dairy products, refined grains, and sweets and desserts) indices were
developed and validated (van Dam et al., 2002). At the follow-up period, after twelve years, the
study showed the western diet to be associated with increased risk of type 2 diabetes. On the
other hand the prudent dietary pattern was associated with a lower risk for the disease.

The risk of developing type 2 diabetes could be reduced by consuming a healthy diet and
engagement in increased physical activity (Lindström et al., 2003, Tuomilehto et al., 2001). The
beneficial effect of a healthy diet and physical activity for the prevention of type 2 diabetes was
documented in the Finnish Diabetes Prevention Study using a randomized control trial of 522
overweight individuals (mean age: 55+7) with impaired glucose tolerance. The intervention
group received individualized counseling to reduce body weight, total fat, saturated fat, and to
increase fiber and physical activity. A significant decrease in weight was observed after 12
months in the intervention group (mean weight loss was 4.2 Kg in the intervention vs. 0.8 in the
control group). After 4 years, the cumulative incidence of diabetes was 11% in the intervention
group, while it was double (23%) in the control group, which is a 58 percent reduced risk of
diabetes due to the intervention (Lindström et al., 2003, Tuomilehto et al., 2001).

Thus, healthy dietary behaviors play a significant role in preventing or delaying the onset of type
2 diabetes. Among individuals who relocated, cultural orientation of the diet has been shown to

22

be influential in the development of risk factors for type 2 diabetes in various ethnic groups. One
of the challenges that individuals who relocated may encounter is adjusting to the host culture
diet. Among Japanese men in Hawaii, retaining a traditional lifestyle was associated with
reduced risk for type 2 diabetes. Although carbohydrate consumption was high among those who
were low acculturated, fat and animal protein intake was lower. In addition, increased physical
activity was noted (Huang et al., 1996). In a Multi-Ethnic Study of Atherosclerosis, high
acculturation was associated with increased diabetes prevalence among non-Mexican origin
Hispanics, but the association was not evident among Mexican-origin Hispanics or Chinese
individuals (Kandula et al., 2008).

The contrary may also be possible. For example, analysis of the National Health and Nutrition
Examination Survey (NHANES) 1999–2002, showed that the likelihood of developing diabetes
increased among Hispanic adults was highest among those with low acculturation (Mainous et
al., 2006). Similarly, decreased acculturation was associated with increased risk for diabetes in
Arabs in the U.S. (Jaber et al., 2003). Furthermore, in addition to diabetes, studies conducted on
various ethnic populations have shown acculturation to the mainstream culture could result in
poor diet and ultimately other negative health outcomes such as increasing rates of obesity,
hypertension, and coronary artery disease risk (Aldrich and Variyam, 2000, Dixon et al., 2000,
Hubert et al., 2005, Kaplan et al., 2002, Marmot and Syme, 1976). Therefore, acculturation in
relation to disease risk may not be the same across different ethnicities. Moreover, these studies
did not focus on dietary acculturation and hence did not use acculturation measures that are
exclusively constructed for capturing dietary acculturation.

23

Thus, despite the increasing prevalence of diet-related chronic diseases among Asian Indians,
there is no single valid and reliable measure of dietary acculturation (Kanaya et al., 2010, Misra
et al., 2010b, Simmons et al., 1992, Venkataraman et al., 2004). This was a major focus of the
current study as well as to test the diet-disease link, specifically with regard to risk for type 2
diabetes within the context of dietary acculturation, specifically a single measure that
quantitatively determines the extent of adaptation of Asian Indians to a host country’s dietary
practices. Behavioral acculturation (e.g. adaptation of host country’s dietary behaviors) occurs
sooner than values acculturation for Asian Americans (Kim et al., 1999). Since dietary habits fall
under behavior acculturation, a behavior scale would be the appropriate approach to meet the
purpose of this study. The reliability and validity of such measures are critical for accurate
measurement of the underlying domains and for the reproducibility of results when administered
using a different sample.

24

CHAPTER 3 - METHODS
The study was approved by the Institutional Review Board of Michigan State University (MSU
IRB) (appendix 1). To accomplish the three specific aims of the study, two phases (qualitative
and quantitative) of data collection were conducted. A qualitative study consisting of focus group
discussions was conducted to accomplish specific aim 1 while specific aims 2 and 3 were
achieved through a quantitative web-based cross-sectional survey. The two phases of the study
are described in detail below.

I. Phase 1 (Qualitative)
A qualitative study was conducted to accomplish specific aim 1 of the study, which is to
qualitatively examine the factors influencing the dietary acculturation behaviors of Asian Indians
in the U.S. Participants were recruited until data saturation by sending an electronic research
flyer (appendix 2) to Asian Indian organizations in Michigan. Interested participants provided
informed consent (appendix 3) and completed a sociodemographic questionnaire in private
(appendix 4). Eight audio-taped focus group discussions guided by a structured focus group
guide (appendix 5) accompanied by two 24 hour recalls of each participant’s typical weekday
and weekend dietary intake (appendix 6) was conducted to examine the dietary behaviors of
participating Asian Indians.

The questions for the focus groups were based on the PRECEDE (Predisposing, Reinforcing, and
Enabling Constructs in Educational Diagnosis and Evaluation) model and a thorough review of
relevant literature (Green, 1999). According to this model, behavior is influenced by preceding
(attitudes, beliefs, and values), reinforcing (social support), and enabling (skills and resources)

25

factors. The focus group questions addressed these domains and were reviewed by three experts
in nutrition and/or qualitative research to determine the appropriateness of wording and content
(Appendix 7).

Focus group discussions were conducted in English in a room at a local library or in a university
classroom. A primary and an assistant moderator of Asian Indian origin conducted the
discussions and recorded notes, respectively. Within a week after the focus group discussions,
one 24 hour weekday and one weekend typical day dietary recall was conducted by phone by the
primary moderator. A $20 gift card incentive was given to participants who participated in the
focus group sessions and completed the two dietary recalls.

Participants’ socio-demographic data was analyzed for descriptive information. Qualitative data
was transcribed verbatim and individually coded by the primary and the assistant moderator. A
codebook was developed with the theoretical domians, themes, codes, rules for application and
illustrations to facilitate the coding process (appendix 8). Coding disagreements were discussed
until consensus after coding each focus group transcript. Themes were generated based on the
conceptual model of dietary acculturation (Satia-Abouta et al., 2002). Asian Indian and nonIndian foods, their preparation methods and portion sizes were determined from the dietary
recalls.

II. Phase 2 (Quantitative)
A cross-sectional study was conducted by administering a web-survey to a national sample of
225 Asian Indian adults in the U.S to accomplish specific aims 2 and 3, which were: to develop a

26

culturally sensitive Asian Indian Dietary Acculturation Measure (AIDAM) and determine the
reliability and validity by testing with a national sample of Asian Indian adults in the U.S.
(specific aim 2) and to examine the relationship between the dietary acculturation score of the
participating Asian Indians and their risk for type 2 diabetes (specific aim 3).

Items for the AIDAM were generated from the themes that emerged in our qualitative analysis
for specific aim 1. A food frequency questionnaire consisting of Asian Indian and non-Indian
foods was developed from the 24-hour dietary recall data analysis. The AIDAM and the food
frequency items were revised by 8 Asian Indians who were either registered dietitians or experts
in nutrition research, one expert in survey research, and one expert in data analysis (appendix 9).
The AIDAM was pilot tested with 12 Asian Indian adults who participated in the focus group
discussions to determine appropriateness of content. The pilot test results are shown in appendix
10. The institutional review board of Michigan State University approved the revised
instruments.

The sample size for the web-survey was calculated based on Rasch rating scale models that are
employed for attitudinal rating scales and for most purposes a sample between 108 and 243 is
recommended (Linacre, 1994). Recruitment of participants and administration of the web-survey
was performed through Qualtrics research suite (Qualtrics, 2009, Provo, Utah, USA. Version.
12,018). For Asian Indian panel recruitment, Qualtrics Research Suite used Research Now
Group, Inc (formerly known as E-Rewards, Inc, headquartered in Plano, Texas), a recognized
market research company that rewards consumer panelists for time spent taking market research
surveys. Research Now uses an incentive scale which is based on time increments and the

27

panelist profiles. The incentive amount is variable and based on the profile of the target sample.
After completing surveys participants are allowed to redeem from a large range of gift cards,
points programs, and partner products or services. For example, our study participants earned erewards currency for completing the survey. A wide net of 1408 emails were sent to Asian
Indians and 289 participants clicked on the entry link. A total of 225 participants completed the
survey, which is a response rate of 16%. The location of residence (in the U.S.) of the 225
participants is provided in appendix 11. Demographic profile of participants and non-participants
were similar, as shown in appendix 12.

Interested and eligible participants (Asian Indians > 18 years) provided informed consent
(appendix 13) and completed the following survey items: (i) participant sociodemographic, diet,
and health care questions (appendix 14), (ii) the food frequency items (appendix 15), (iii) the
Finnish Diabetes Risk Score (FINDRISC), a tool to calculate participants’ risk for developing
type 2 diabetes in ten years (appendix 16), and (iv) the AIDAM (appendix 17). A detailed
description of the assessments are provided in chapter 4 - manuscript 2.

Participants sociodemographic characteristics were analyzed for descriptive information using
Statistical Package for Social Sciences (SPSS) (version 20.0, 2011, Chicago, Illinois, SPSS Inc.).
To accomplish specific aim 2, construct validity and reliability estimations were performed
through WINSTEPS (Rasch measurement software version 3.74 Beaverton, Oregon) to
determine model fit. Validity was also determined by examining the correlations between
AIDAM (calculated using participant responses for the dietary acculturation items) and (ii) the
scores obtained for Asian Indian (AI-FFQ) and non-Indian (NI-FFQ) food frequency items

28

(participant responses provided in appendix 18). Linear regression analysis was conducted with
AI-FFQ and NI-FFQ scores as predictors and AIDAM score as the outcome by controlling for
sociodemographic variables. Association between participants’ predictive diabetes risk score
(calculated using FINDRISC assessment) and AIDAM were examined using correlations and
linear regression analysis to accomplish specific aim 3.

Figure 2. Figure showing the two phases of data collection

Sources of Data

Phase 1 - Qualitative
Focus group discussions

Phase 2 - Quantitative
Web-survey

Focus group discussions

Sociodemographic
survey

Two 24 hour typical day
dietary recalls

Dietary acculturation
assessment
Asian Indian and nonIndian food frequency
assessment
Diabetes risk score
assessment

29

CHAPTER 4 - RESULTS

I. Manuscript 1 (specific aim 1)
Factors influencing dietary acculturation of Asian Indians in the U.S.

Abstract
Background: Asian Indians, one of the fastest growing ethnic groups in the U.S. (~1% of the
total population) have a high prevalence of several diet-related diseases. Exposure to a new
culture may change taste preferences, food procurement and food preparation of individuals who
relocated, leading to changes in their dietary pattern (dietary acculturation) that could have an
impact on their health.
Objective: The objective of this study is to qualitatively examine the factors influencing the
dietary acculturation behaviors of Asian Indians in the U.S.
Methods: Thirty Asian Indian adults in a Midwestern state in the US participated in eight
audiotaped focus group discussions (2-5/ group) conducted in a public library/university. Two
Asian Indian researchers independently analyzed focus group transcripts verbatim for theme
generation. Emergent themes were analyzed using the constant comparison method.
Results: The sample (n= 16 males and 14 females) consisted of a variable group of Asian
Indians, which included members from different generations, religions, and places of origin in
India. Key reported factors that led to modification of traditional behaviors were: social
independence; social network influences; increased health awareness; sub-standard taste and
increased cost of commercial Asian Indian snacks/ restaurant foods; and time constraints and
convenience.

30

Conclusion: This study elucidated the factors that contribute to dietary acculturation of Asian
Indians. These findings were utilized for the development and validation of an Asian Indian
dietary acculturation instrument that can be used nationally and internationally, to improve the
understanding of nutrition/health professionals about Asian Indian food choices and preferences.

Introduction
Asian Indians constitute about 1% of the U.S. population and are the second largest Asian group
in the U.S. (U.S. Census Bureau, 2012). Asian Indians in the U.S. have a high prevalence of dietrelated chronic diseases, which is also higher than that of the host population, especially type 2
diabetes (17% to as high as 29% in Asian Indians vs.13.1% in non-Hispanic blacks, 8.7% in
Mexican Americans, and 7.4% non-Hispanic whites) (Kanaya et al., 2010, Misra et al., 2010b,
Selvin et al., 2014, Simmons et al., 1992, Venkataraman et al., 2004). The prevalence of type 2
diabetes among Asian Indians who relocated to the U.S. has also been shown to be higher than
the diabetes prevalence in India (7.3% urban and 3.1% rural) (Mohan et al., 2008). Although
genetic factors play an important role in the development of diet-related chronic diseases, it is
equally important to investigate the environmental risk factors. One such risk factor is unhealthy
dietary intake. In the case of individuals who relocated to another country, dietary acculturation
could be an important variable of interest. Dietary acculturation is the extent to which members
of a migrating group adopt the eating patterns/ practices of their new environment (Satia-Abouta
et al., 2002).

The traditional Asian Indian diet is predominantly carbohydrate based. More specifically there is
increased usage of refined grains such as dehulled white rice, semolina, and white flour (Radhika
31

et al., 2009). There are different patterns of dietary intake even within the Asian Indian ethnic
group, with rice as the staple in the southern India while wheat is consumed in large quantities in
the north (Malhotra, 1970, Prashantham, 2008). Upon relocation, the diets of Asian Indians
undergo changes, which may also affect the nutrient composition of the diet as well. For
example, an increased intake of energy and fat intake was documented among Asian Indians in
Britain when compared to age, gender, and caste matched individuals in India (Patel et al., 2006).

Meal preparation practices of Asian Indians differ between the week and the weekends due to the
complexity and time involved in preparing Asian Indian foods (Raj et al., 1999). Traditional
mixed dishes made with legumes, vegetables, and cereals decreased during the week because
they require increased cooking time (Raj et al., 1999). A study among Asian Indians in
Newfoundland, Canada showed that Asian Indians changed their meal preparation practices by
frequently baking, barbecuing, using a microwave, and including canned foods, which are
traditionally not frequently employed for Asian Indian meal preparation (Varghese and MooreOrr, 2002). The reasons quoted for such changes were lack of time, lack of availability of
ingredients for traditional cooking, and cooking was perceived as more interesting with the use
of modern equipment (Varghese and Moore-Orr, 2002).

In the U.S., the diet of Asian Indians has been shown to consist of frequent selection of nonIndian foods and replacement of traditional foods with other ethnic or western foods. Asian
Indians in the U.S. were shown to consume more of animal fat and saturated fat, convenience
foods, alcohol, whole grain foods, fish, poultry, meat, salty snacks, and desserts when compared
to their diet in India (Kulkarni, 2004). Contrarily, another study showed a decline in saturated fat

32

and fiber content of the foods consumed by Asian Indians after relocation to the U.S.
(Jonnalagadda and Diwan, 2002).

These changes happen because immigration and relocation results in exposure to a new
environment, which includes new foods and food sources (Satia-Abouta et al., 2002). It is well
known that individuals who relocate to western countries may have an altered dietary intake with
the inclusion or exclusion of certain foods as a consequence of dietary acculturation (Dixon et
al., 2000, Hubert et al., 2005, Jonnalagadda and Diwan, 2002, Raj et al., 1999). Along with
socio-demographic and cultural factors, exposure to a new host culture may lead to collective
changes in psychosocial factors, taste preferences, as well as food procurement and preparation
methods thereby leading to different patterns of dietary intake (Satia-Abouta et al., 2002).

According to the conceptual model of dietary acculturation proposed by Satia-Abouta, these
socio-demographic factors include: gender, age, age at relocation, duration in the host country,
education, income, employment, marital status, presence of children or seniors in the household,
fluency with host language, country of origin, rural vs. urban residence in country of origin, and
voluntary vs. non-voluntary migration. The cultural factors are religion, cultural beliefs,
attitudes, and values, and residence in an ethnic enclave. The psychosocial changes include diet
and disease related knowledge, attitude and beliefs, values ascribed to traditional eating practices
and host country assimilating patterns, and changes in taste preferences. Lastly, the
environmental contributors are: availability, accessibility, and affordability of traditional foods at
stores and restaurants, and changes in food procurement and preparation due to media influence,
time constraints, and availability of packaged and convenience foods (Satia-Abouta et al., 2002).

33

For any population of concern, nutrition assessments/ interventions should take into account
various sociodemographic, social, cultural, and environmental factors of the target audience
instead of addressing a single component. In order to understand if and how dietary
patterns/practices relate to acculturation and risk for chronic diet-related diseases, ethnic specific
exploration of dietary practices within a host country or environment is essential. This
information will be useful for interventions targeted to specific audiences of different cultures.
Therefore, we explored these concepts specifically relative to Asian Indians in the U.S.

The purpose of this study was to conduct a qualitative study to determine the factors that
contribute to dietary changes among Asian Indians in the U.S. More specifically we investigated
cultural, environmental, and psychosocial factors that can contribute to dietary acculturation in
this population. We used focus group discussion methodology because group interaction would
facilitate exchange of experiences and views and will help to gain an in-depth understanding
from the target group perspective. The goal was to determine the factors that influence dietary
acculturation behaviors of Asian Indians who relocate to other countries so that these findings
could be utilized for the development of an Asian Indian culture specific dietary acculturation
tool. This is an important step for facilitating the assessment of dietary changes of this target
group.

Methods
The study was approved by the Institutional Review Board of Michigan State University (MSU
IRB). Audio-taped focus group discussions were conducted in East Lansing, Michigan between
November 2012 and January 2013 to identify survey items that are specific for Asian Indians.
Participants for the focus group discussions were recruited from Asian Indian organizations in
34

Michigan until data saturation. Although this was a convenience sample, Michigan is composed
of a considerable proportion of Asian Indians with varying professions that is comparable to the
U.S. census data (U.S. Census Bureau, 2012). Subjects of Asian Indian descent who were > 18
years old and who were able to read and converse in English were included in the study. Since
Asian Indians are a linguistically diverse population, focus group discussions were conducted in
English for ease of understanding participant responses without an interpreter. In addition,
conducting discussions in English and audio-taping facilitated data transcription, coding
accuracy and confirmation of themes.

The focus group discussion sites were determined based on the convenience of eligible
participants. All the discussions were conducted either in the study room of a local public library
or a university classroom. The size of the focus groups ranged between two and five participants.
An Asian Indian moderator followed the focus group procedures accompanied by an assistant
moderator, also of Asian Indian descent who was present to record the discussions, take notes,
and assist with technological needs (Krueger and Casey, 2009). Both the moderators had
nutrition background. The primary moderator was trained in qualitative research and the
secondary moderator in focus group methodology.

Participants signed a consent form and self-completed a short socio-demographic questionnaire.
On the same occasion, focus group discussions guided by a structured guide were conducted for
approximately one to two hours based on the size of the group. Every participant had an
opportunity to speak and was allowed to politely agree or disagree with the other participants. At
the end of the discussion participants were encouraged to discuss any other information related to

35

their dietary practices that were not covered by the focus group questions. A total of eight focus
groups were conducted to reach saturation.

Focus group guide
A focus group guide consisting of questions based on the PRECEDE (Predisposing, Reinforcing,
and Enabling Constructs in Educational Diagnosis and Evaluation) model was developed by a
thorough review of relevant literature (table 1). The PRECEDE model (Green, 1999) has been
previously shown to be successful in dietary behavior assessment studies in various populations
such as non-Hispanic blacks, non-Hispanic whites, Hispanics, and Asians (Chang et al., 2004,
Devine et al., 2007, Satia-Abouta et al., 2000, Satia-Abouta et al., 2001, Wenrich and Cason,
2004). According to this model, behavior is influenced by preceding (attitudes, beliefs, and
values), reinforcing (social support), and enabling (skills and resources) factors. The questions
for our focus groups included these important parameters of interest. This model has also been
used to guide qualitative focus group interviews to study the dietary behaviors of Chinese
Americans for the development of a dietary acculturation scale (Satia-Abouta et al., 2000, SatiaAbouta et al., 2001). Three experts in nutrition and/or qualitative research validated the focus
group guide by determining the appropriateness of content as well as clarity of questions. Two
pilot interviews were conducted with non-native individuals (Asian Indian and Indonesian) in the
U.S. to check for interpretation and clarity of the questions.

36

Table 1. Focus group questions based on the PRECEDE model
Focus group questions
What are some of your favorite foods? Probe: They could be Asian Indian,
western, or other ethnic foods. Why are they your favorites?
What are some new foods that you started eating after coming to the U.S.?
Probe: Why?
After coming to the U.S., how have you made any changes to the types, amount
and/or the number of times you eat meals?
How do you choose the foods that you want to eat on a certain day? Probe: Who
does the cooking at home? How do you think the internet, TV, radio, or
magazines here affect what you buy or eat?
What are some changes that you made in your eating habits to suit the needs of
your family? Probe: e.g. elderly with medical conditions, school going children,
etc.
How do you decide what places to go out and eat? What are the types of foods
that you eat in restaurants?
What are some Indian foods that you wish you could get here in the U.S.? How
do you make up for those items?
What are your preferences for snack foods that you buy?
When you go grocery shopping for foods, how do you decide what you want to
buy?
What are some typical dishes that are cooked at home or purchased from the
store when you invite your American friends? Probe: How is this different when
you invite your Indian friends?
What do you typically contribute when you attend potluck social gatherings?
Probe: How does it vary between Indian and American social gatherings?
How are the foods that you eat outside your home different from what you eat at
home? Probe: e.g. workplace, school, road trips, etc.?
How do you think the types of foods in the U.S. has changed your health?
Probe: What are some things that you like or dislike about the Indian diet? What
are some things that you like or dislike about other non-Indian foods in the
U.S.?
When you were in India, what would you typically eat during the week days and
weekends?
How did your religion determine what you ate in India? How has this changed
since you came to the U.S.?
Do you want to say anything else about your eating habits in the U.S.?
Questions based on PRECEDE conceptual model (Green, 1999)

37

Theoretical
construct
Predisposing
Enabling
Enabling
Predisposing

Reinforcing

Enabling
Enabling
Enabling
Enabling
Reinforcing

Reinforcing
Predisposing
Predisposing

Enabling
Predisposing

Typical day dietary recalls
Two typical day 24 hour recalls, one representing a weekday and one a weekend, were
conducted by phone within a week of each focus group to assess the type of foods consumed,
their preparation methods, and portion sizes. The recalls were administered by the primary
moderator, who was trained to use the validated USDA multiple pass method (Conway et al.,
2003, Conway et al., 2004). Each dietary recall took approximately 15 to 20 minutes to
complete. A list of foods and beverages consumed during a typical 24 hour period was collected
with mealtime occasions, a description of preparation methods, and corresponding portion sizes.
To account for variability, dietary recalls were collected for a typical weekday and a weekend
day. All the participants completed the dietary recalls and a $20 gift card incentive was given to
participants for completing both the focus groups and the dietary recalls.

Data analysis
Participants’ socio-demographic data was analyzed using SPSS (version 20.0, Chicago, Illinois,
SPSS Inc.). Focus group discussions were transcribed verbatim and individually coded by the
two moderators. The coding process was facilitated by a codebook, which consisted of the
domains, themes, codes, rules for application, and illustrations. Coding disagreements were
discussed after coding each focus group transcript until consensus. Themes were examined by
organizing and managing the data using Nvivo (version 8.0, QSR International) software for
qualitative research. Asian Indian and non-Indian foods consumed during each meal occasion
were identified from the information obtained from the dietary recalls.

38

Results
Table 2. Participant characteristics (n=30)

Age (years)

Relocation age

Generation
Gender
Religion
Educational level
Employment

Annual household income

Marital status
Duration of stay in the US
No. members in the household

Language spoken at home

Lived in a country other than
US and India

18 - 30
31 – 50
> 50
0-3 years
3-30 years
>30 years
1st
2nd / relocated before age 3
Male
Female
Hindu
Other (Muslim, Sikh, Christian, none)
<Bachelors
>Masters
Employed full time
Other (employed part time, home maker/
unemployed/ retired)
Student
<$20,000
$20,000 - $75,000
>$76,000
Did not disclose
Single
Married
< 15 years
> 15 years
1
2
>2
Mostly Indian
Mostly English
Indian and English equally
Yes
No

n (%)
14 (46.7)
11 (36.7)
5 (16.7)
5 (16.7)
20 (66.7)
5 (16.7)
25 (83.3)
5 (16.7)
16 (53.3)
14 (46.7)
24 (80.0)
6 (20.0)
8 (26.7)
22 (73.3)
12 (40.0)
10 (33.3)
8 (26.7)
5 (16.7)
11 (36.7)
13 (43.3)
1 (3.3)
9 (30.0)
21 (70.0)
18 (60.0)
11 (40.0)
2 (6.7)
13 (43.3)
15 (50.0
12 (40.0)
6 (20.0)
12 (40.0)
4 (13.3)
26 (86.7)

Sample Characteristics
Participant demographic characteristics are depicted in table 2. There were 16 males and 14
females. About half of the participants were between 18 and 30 years (n=14). The majority were
39

married (n=21), Hindu (n=24), had a master’s degree or higher education (n=22), and were first
generation Asian Indians (immigrants and non-immigrants) or had relocated to the U.S. before
age 3 (n=25). A larger proportion of the participants were either working fulltime (n=12), or
were students (n=8) of which five students had lived in the U.S. for less than five years. Eleven
participants had lived in the U.S. for 1 to 5 years, while 13 participants and 6 participants had
been in the U.S. for 6 to 20 years and > 20 years, respectively. The majority of the participants
lived with either their friends or family members (includes spouse, children, or parents). A larger
proportion of the participants spoke mostly Indian (n=12) or both English and Indian languages
equally (n=12) at home. Four participants had lived in at least one country other than India and
the U.S., which included Japan, Taiwan, Singapore, Malaysia, Indonesia, and the U.K. for a
period of 1-5 years.

Typical weekday and weekend dietary intake of participants
Table 3 shows the Asian Indian and non-Indian foods typically consumed by participants. It was
evident from the recalls that second generation Asian Indians who were born in the U.S. or
participants who had relocated to the U.S. before age three (n=5) did not select Asian Indian
foods for most of their meals and snacks. All the participants (n=30) did not consume Asian
Indian foods for breakfast, especially during weekdays. The breakfast items mostly consisted of
milk based beverages and non-Indian breads or hot or cold breakfast cereals. However, during
the weekends a few participants (n=7) chose to eat Asian Indian foods typically consumed for
breakfast in India such as idly, dosa, upma or pongal.

40

Unlike breakfast a larger proportion of participants consumed at least one Asian Indian food for
lunch both during weekdays (n=19) and weekends (n=20). The foods that participants chose for
lunch were Asian Indian breads such as rotis/ chapatis or rice accompanied by a vegetable or
meat curry in addition to other foods such as salads, sandwiches, pasta, pizza or frozen nonIndian lunch entrees. During the weekends a few participants (n=4) consumed lunch at
restaurants or resident dining halls.

Dinner foods during weekdays and weekends consisted of predominantly Asian Indian items,
which included but were not limited to Asian Indian breads (rotis/chapattis, paratas), rice, meat
or vegetarian curry, dal, idli, dosa, upma, and mixed rice dishes. Many participants (n=16)
indicated that they would typically eat at restaurants, visit friends’ houses or invite guests for
dinner, or eat dinner at other social gatherings. Three male participants said they would typically
consume alcoholic beverages such as whisky, wine or beer during the weekends. Participants
were likely to select Asian Indian sweets and savory products for afternoon snacks when
compared to mid-morning or evening snacks. A considerable amount of breakfast breads and
cereals, dried fruits and nuts, sweet yogurt, non-Indian meals (sandwiches, pasta/spaghetti,
noodles, pizza), and non-Indian dessert consumption, and frequent dining out especially during
weekends at other ethnic restaurants was also evident from the dietary recalls.

41

Table 3. Participant consumption of non-Indian, common, and Asian Indian foods (n=30)
-

-

Non-Indian foodsa
Green tea
Cappuccino
Hot chocolate
Protein shake
Greek yogurt/ flavored yogurt
Cereal (honey oats and bran,
corn flakes, square wheat,
raisin bran, shredded wheat,
honey nut cheerios, honey
bunch of oats, cheerios)
Oatmeal (regular, flavored)
Bread (whole wheat,
multigrain, raisin bread, oat
nut, banana bread)
Pita/flat bread
Wheat bagel
Pancakes
Waffle
French toast
Cereal bar (Nature valley oats,
Granola chocolate chips)
Mac and cheese
Rolls
Sandwich
Burger
Spaghetti
Pasta
Frozen Lean Cuisine entrees
Fried rice
Brown rice
Burritos
Flour tortillas
Pizza (cheese, pepperoni,
barbeque chicken, vegetarian,
and chicken pizza)

-

Common foods
Milk (whole/reduced
fat/ fat free)
Yogurt/ homemade
yogurt
Buttermilk
Coffee
Tea (black, herbal)
Soda (mountain dew,
diet coke)
Fruit smoothie
Carrot juice
Orange juice
Cheese
Almonds
Walnuts
Mixed nuts
Peanuts
Cashew nuts
Dates
Raisins
Steamed egg whites
Scrambled eggs
Boiled eggs
Egg omelet
Vegetable salad
Lettuce
Cucumber
Baby carrots
Tomato
Olives
Apple
Berries
Banana

-

-

42

Asian Indian foodsb
Indian tea
Indian buttermilk
Lassi
Quinoa
Dosa
Idli
Upma (rice, sooji, bread)
Pongal
Chapatis/Rotis
store bought frozen
chapattis
Rice
Indian mixed rice dishes
(vegetable pulao, spinach
rice, yogurt rice, rice pulao,
meat biryani)
Stuffed paratas
Store bought frozen
chapattis, naan and paratas
Wheat dosa
Idli
Barley
Poori
Maggie noodles
Ragi dish
Sambar
Channa masala
Vegetable sabji
Indian style vegetable stir
fry
Vegetable kuruma
Store bought frozen
kuruma
Indian style meat curry
(beef, chicken, turkey, fish)

Table 3 (cont’d).
-

Non-Indian foodsa
Chicken tenders
Canned beans
Grilled salmon
Canned condensed soup
Frozen corn
Noodles
Tortilla chips
Multigrain wheatables
Cheese crackers
Wheat thins
Barbeque chips
Veggie straws
Brownies
Cheesecakes
Non-Indian cookies e.g. Oreo,
Chocolate chip
Digestive biscuits
Donuts
Fruit snacks
Dark chocolate
Sweetener
Peanut butter
Creamer
Margarine
Syrup
Salad dressing
Feta cheese
Cream cheese
Mustard
Pesto sauce
Sweet and sour sauce
Pasta sauce
Salsa
Magic whip
Jelly

-

Common foods
Pear
Orange
Grapes
Strawberries
Prunes
Apricots
Popcorn
Potato chips
Chocolates
Biscuits
Ice cream
Cupcakes
Cookies
Cake
Candy
Sugar
Brown sugar
Honey
Butter
Whisky
Wine
Beer

-

a

Asian Indian foodsb
Vegetable/and bean curries
Indian style vegetable stir
fry
Rasam
Dal (lentils)
Pulikuzhambu
Murukku
Banana chips
Spice mixture (snack)
Puffed rice
Indian sprouts
Pohas (flattened rice)
Indian savory snacks
Biscuits commonly found
in India e.g. Marie, Milk
bikkis, Parley-G
Asian Indian rusk
Indian sweets
Kheer
Carrot halwa
Chutney (coconut, peanut,
coriander, onion, tomato)
Spice powder
Herbal ginger powder
Pickles
Ghee
Papad

Dining out - Breakfast at a café on weekends, eat at cafeteria/ resident dining halls eat at
Mexican, Chinese, Thai, Italian, and Mediterranean restaurants
b
Dining out – Restaurant (Indian, Pakistani), eat at temple, eat at friends’ houses and host guests

43

Thematic findings
Eight themes evolved and were organized within the three domains of the dietary acculturation
model (Satia-Abouta et al., 2002) as follows:
(i)

psychosocial factors and taste preferences – social network, health and nutrition, media,
and taste preferences

(ii)

environmental factors – food purchasing, food preparation, and restaurants

(iii)

cultural factors – religious and cultural beliefs

Within each theme facilitators of dietary acculturation and traditional food consumption were
identified and discussed separately. Facilitators were focused on the domains specified in the
dietary acculturation model by Satia-Abouta (Satia-Abouta et al., 2002).

Facilitators of dietary acculturation
Social network (Family, friends and others, work place, and social events): Participants
specified that their spouses were influential in them trying new foods at restaurants, including
non-Indian foods when eating at home, initiating cooking and eating meat for those who were
vegetarian, controlling food portions, and altering salt or spice level. “…my husband forced me
to like he said why don’t you try? Always you are cooking at home. I mean it’s been two years
since I lived in the US and the first 6 months I never came out. I always cooked at home. I never
ate out. Then okay I should come out, started trying out and at that time…so that’s when I
started the Mexican and then the pancakes. And even now it’s not my favorite but I can survive
on that” – (303, female, age 27, relocation age 25).

44

Similarly when a family member had a medical problem (e.g. type 2 diabetes) or when a family
member in the health care field incorporated health awareness, it impacted the dietary habits of
the entire family, which led to including healthy foods, avoiding deep frying, and tweaking
recipes to make foods healthy. “But the one thing that I learned also a lot like you know it’s like
reading the label. Like thanks to name of participant’s daughter again otherwise I would never. I
would just look at the stuff whatever attracts me go and buy that. But she’ll always look at the
saturated fat, the trans-fat blah blah blah…she put it in my head too. So when I buy things I have
to read through all that labels too and buy” – (202, female, age 46, relocation age 30).

Children under eighteen years were influential in the dietary habits of parents. Many participants/
parents (n=10) mentioned that they started preparing and eating the foods that their children
preferred, which were mostly non-Indian foods. Similarly, second generation participants (n=5)
who were either born in the U.S. or had relocated to the U.S. before age three and were in
college/ graduate school and living away from their parents said that their meals were not
structured anymore and that they tended to cook simple and easy non-Indian foods since they
were alone (due to lack of an Asian Indian social network). Participants who were vegetarians
indicated that they did not impose a vegetarian diet on their children and therefore their children
were allowed to eat non-vegetarian foods. “once we had kids like I said, we started making foods
more that would, that they would also eat…so um you know just trying to have foods like peanut
butter and jelly sandwiches, which we would never buy for ourselves and never eat ourselves
once we moved from India…Mac and cheese you know those kind of things which the kids eat
was only brought into the home because of kids” – (402, female, age 51, relocation age 23).

45

In addition to family, other individuals such as friends and colleagues and a fitness trainer also
played an important role in the dietary habits of participants. Participants mentioned that they
would get recipes from their friends, try different ethnic foods with their friends or colleagues,
and eat foods cooked by non-Indian friends. They also indicated sometimes eating lunch with
friends/ colleagues at non-Indian restaurants on work days (n=6). Eight participants said that they
preferred to eat non-Indian foods at the workplace. One of the reasons given by four participants
was that the foods tended to have strong aromas. And the work place most of the time…I feel like
you know at a work place like especially when you open your lunch box and then it gives that
smell. I am not comfortable with you know, that you know that kind of a feeling. Like I just try to
you know, keep something like that is not going to like, strong in aromas and stuff like that” (202, female, age 46, relocation age 30).

When asked about social events with Asian Indians and non-Indians, it was interesting to note
that three participants perceived that food allergies were common among non-Indians, hence the
preference was to take them to restaurants rather than preparing home cooked meals from a
safety perspective. Two participants mentioned that certain foods such as fried Asian Indian
items are made only for social events. Three male participants indicated that alcohol
consumption generally increased during social events. “And of course some alcohol like beer you
know once in a week or month with friends yeah. It was there back in India but after coming
here, it’s kind of like uh but it was kind of becoming like uh you know social event I would say” –
(505, male, age 40, relocation age 35).

Health and nutrition: Greater health awareness in the U.S. was perceived as a key reason for
achieving weight control (n=5) and increasing dietary intake of healthy non-Indian foods (n=10).
46

A few participants (n=9) said that they gained weight in the U.S.; however, three said that it was
during the initial years but they later lost the weight. In this respect, reducing portion sizes and
making healthy food selections that included salads and “healthy” sandwiches were important
changes that were made gradually over a period of stay in the U.S. “my rice consumption has
gone down and also spice…I lost uh lost lot of weight…I feel okay this is good. And plus you
know of course we included like sandwiches and these kind of things especially for afternoon
lunch so that’s kind of good and now after coming here, becoming more you know, becoming
more health conscious” – (505, male, age 40, relocation age 35). Excessive salt, excessive oil,
energy dense Asian Indian party/ restaurant foods were considered as negative aspects of the
Asian Indian diet, which could have led to reduced consumption of such foods and replacement
with healthy alternatives such as salads and sandwiches. “Um uh with the Indian food…some
dishes use a lot of oil and a lot of fat. So there can be a lot of unhealthy dishes” – (701, male,
age 19, relocation age 3 months).

Overall, numerous perceived positive changes in dietary behaviors in the U.S. were mentioned
by participants. The majority of the participants (n=21) said that they had incorporated healthy
habits, which were: consuming a healthy breakfast, switching to healthy ingredients, eating more
protein, including healthy alternatives for snacks, including salads, replacing white rice with
whole wheat products, consuming a balanced meal, avoiding “junk” foods, reducing the use of
processed and packaged foods, reducing the intake of carbohydrates, reducing salt, controlling
portions, and regulating meat intake. “so we have tried to control the portion lately and have
split the meals. So it is more frequent with smaller portions. Yeah, and then we also cook

47

breakfast most of the time, yes…yeah mostly but it is a twist on the Indian food like use oats
instead of rice” – (603, female, age 29, relocation age 23).

On the other hand, participants also mentioned increased consumption of meat, rice, coffee, and
less healthy foods in the U.S. Ease of availability of energy dense desserts, a plethora of fast food
outlets, and increased availability and consumption of processed and less healthy foods were
perceived as negative aspects of the diet in the U.S. Different patterns of eating between
weekdays and weekend was also evident. Healthier choices were made during the week
compared to the weekends (n=2). “Yeah, overall the nutritional value, the content, the calorific
value is very high in American foods. That’s what I thought. Um I love pecan pie but if you look
at the saturated fat, cholesterol content, it restricts how much you can eat. Same is true with any
of the fast foods.” – (501, male, age 44, relocation age 33).

For some, increasing age and income determined food choices. For example, five participants
said that they started eating healthy and practiced portion control after a certain age. With regard
to income, healthy foods such as fruits and vegetables were perceived to be expensive in the U.S.
and hence less healthy food options (e.g. fast foods) were considered as more affordable for
those with limited income sources. This was especially true for students as expressed by a
participant who was a student as follows: “Yeah I think cost comes before health and then once
you have a little affordability, then you put health also into the equation yeah” – (603, female,
age 29, relocation age 23).

Media: The influence of media in food choices of participants was mainly in the form of either
trying out recipes or foods shown on the television or by searching the internet for recipes and
48

nutrition information. Participants said that they would do the following when asked about the
role of media in their food choices: eat foods advertised or shown on cooking channels, search
for new recipes or adapt some of the recipes to suit the Asian Indian palate, and learn about
nutrition and health information (e.g. watching Dr. Oz show). One participant said that he tried
the foods that he watched in Hollywood movies during his childhood. “Uh I had a fancy about
US when we were growing up as kids and we see a lot of Hollywood movies. So in those movies
we get to see stuff like uh some kind of western food and steak was one and there are several
other things. So probably to copy what I was dreaming of in my childhood years, I wanted to try
all these things. And then I took a liking to it naturally, that is how I would say” – (101, male,
age 39, relocation age 24).

Taste preferences: When asked about their favorite non-Indian foods, the following were
mentioned by a few participants: chicken noodles, chicken noodle soup, vegetarian patties,
chicken sandwiches, doughnuts, peanut butter, western desserts, soda, pizza, and different
cuisines such as American, Mexican, Italian, and Thai. “I like Mexican food too. It’s really easy
to make. It doesn’t take as long as like Indian food” – (703, female, age 20, 2nd generation). A
few participants mentioned reducing the amount of food or portion sizes consumed during every
meal in the U.S. compared to what they would consume in India (n=6). “In India especially like
there is no concept of portion size, I guess. Like you know like if you go out, like if you are going
out to some relative’s house, you have to take the second helping. Otherwise it’s like, even at
home if you don’t take the second helping they say like what’s happening to you, and are you
ill?...So I feel like my portion size is much under control here”- (603, female, age 29, relocation
age 23).

49

According to a few participants, consumption of the following foods increased in the U.S.:
Alcohol, meat, fish, coffee, fruits, soda, burgers, soups, chocolate, ice-cream, milk, sandwiches,
fast foods, salads, and peanut butter. “I take quite a lot of alcohol after coming here because of
access to it” – (101, male, age 39, relocation age 24). On the other hand consumption of rice,
spicy foods, sweets, and potato chips decreased over time. “I reduced the rice and because of
awareness…so reduced a little bit rice and increased the chapatti, chapatti and so lunchtime at
least three times a week we take chapattis” – (502, male, age 41, relocation age 28).

Almost all the participants indicated that breakfast is the meal that had completely changed
compared to their diet in India. Breakfast items in the U.S. included cold and hot cereals,
sandwiches, toast, and cereal bars versus traditional foods such as idli, dosa, roti, upma, etc. for
breakfast in India. “We used to eat idly, dosa and upma for breakfast in India and have a lunch
and dinner and in between one snack with tea in the evening. And after coming over here that
changed to bread and cereals in the morning but it’s healthy though” – (104, female, age 39,
relocation age 27). Similar to breakfast, many participants chose to eat non-Indian foods for
lunch, especially participants of second generation or those who relocated when they were less
than 3 years. Second generation participants also mentioned consuming non-Indian foods for
dinner. Participants did however mention both Asian Indian (e.g. murukku, sev, and Asian Indian
sweets such as burfi) and non-Indian foods (sweets such as pie, donuts and salty savories such as
cheetos, and doritos) as their preferred snacks.

Restaurants: Those who enjoyed a variety of non-Indian restaurants (n=13) said access and
availability were key motivating factors. “Yeah, I think uh you start eating different foods

50

because of the availability of the foods and um just having different options to be able to choose
from that are common options…I would say the same thing Italian, you know Mexican um Thai
food because Thai food was not very common in India at all when we moved here in the 80’s
(1980” – (402, female, age 51, relocation age 23).

While another participant with young children said he would prefer a restaurant with a play area
for children, two participants said that they would choose restaurants that served alcohol and
non-vegetarian foods. Restaurant selection was also based on special offers, recommendations/
reviews and location or mode of delivery for those who did not have transportation facilities.
During road trips most participants (n=19) said they would consume non-Indian foods most of
the time such as pizza, sandwiches, fast foods, soft drinks, beverages, and milk shakes. Three
participants said that they would try the regional specialties in the location where they travelled.
Cost of Asian Indian fast foods/ street foods was perceived to be expensive in the U.S. Seven
participants said that they disliked Asian Indian restaurants because of poor service and poor
quality of the food. The foods served at Asian Indian restaurants were considered as less healthy
and not as delicious as home cooked food. “As a family, we don’t choose Indian at all because
we think Indian food is better at home than at the restaurant…uh American restaurants are good
because my son likes to have some barbecued pork ribs…and then if we want to have some spicy
food we go to Thai” – (101, male, age 39, relocation age 24).

Food preparation: Food preparation evolved as an important determinant of non-Indian food
preference due to time, availability of ingredients and cooking ability constraints. Four
participants especially mentioned that Asian Indian foods are usually elaborate, complicated, and

51

are very time consuming to prepare. “Umm I like American food. Just cause like it’s really easy
to get. Like go to fast foods and get something. I know like Indian food there is like this entire
process, like you need pots and pans, and cooking everything. I don’t know how to do any of
that” – (702, male, age 19, relocation age 3). This was clearly evident in breakfast food choices
(oatmeal and cereal). A few modifications to Asian Indian cooking were also discussed such as:
substituting frozen in lieu of fresh vegetables, integrating chutneys in sandwiches, adding nonIndian vegetables in Asian Indian foods, and using olive oil for tempering. “Basic change I have
made is I, I have started cooking Indian food in olive oil” – (401, female, age 49, relocation age
23)

Food purchasing: The major impact of food purchasing behavior relative to non-Indian food
consumption was through cost and ease of access to non-Indian food choices e.g. meats for
vegetarians, fruit and fruit juice varieties, and frozen vs. fresh vegetables. When discussing the
availability of Asian Indian foods in the U.S., participants said that they were not able to obtain
certain Asian Indian varieties of bananas, mangoes, greens, seafood, and sweets in the store that
they shopped or in the place where they lived. Furthermore, it was deemed that the taste of fruits
differed from what they had consumed in India.

One recent Asian Indian (residing in the U.S. for less than a year) alternatively expressed a
preference for milk, eggs and bread in the U.S. compared to India. The same participant also
mentioned that he switched to western snacks and sweets since similar Asian Indian foods were
priced high and of poor quality. Participants who were students were especially concerned about
the cost of food rather than the quality. Although organic foods were considered as good quality

52

they were considered expensive and hence only participants who were wealthier chose to buy
them. “Yeah cost factor and taste both of them…in India I used to take Indian sweets and Indian
mixture type of things regularly. Here uh depending on this uh since it is more expensive and
taste is not so good, so I changed to American snacks. Yeah it’s basically donuts and uh of
course these muffins we say there in India we call them as cupcakes so I used to take those also”
– (802, male, age 48, relocation age 47).

Because some participants preferred specific stores for specific Indian items (e.g. regular
supermarkets, halal meat store, Asian store, bulk grocers, and Asian Indian stores), distance was
a limiting factor for those participants who did not have a car. Therefore, they purchased from
stores with more non-Indian choices. “So putting all the plus and minus together so whenever my
friend goes to Meijer then I have to go. And I don’t know when he’ll go again. So factor like that
are there” – (801, female, age 22, relocation age 22).

A large proportion of participants also said they were disappointed with the quality of Asian
Indian products and the freshness of ingredients in the Asian Indian grocery stores where they
regularly shopped, hence the frequent selection of non-Indian alternatives. Nutrient information
and expiration dates on package labels were especially limited. “So it’s like whenever you go to
Indian stores, as long as you are an Indian you will take it. That’s what they take it as granted.
Because I sometimes even don’t see the manufacturing date. Forget about the nutrition things” –
(201, male, age 24, relocation age 21).

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Religious and cultural beliefs: Eight participants said that they had relaxed some of their
religious beliefs in the U.S by eating non-vegetarian foods (those who were vegetarians) or foods
prohibited in their religion (e.g. beef or pork). A large proportion of participants perceived that
there were limited options for vegetarians in this country. “I am big on vegetables so but that’s
the biggest problem in this country, the variety of vegetarian you know…the vegetables in India
is like plenty. Like you have so much that you can choose from and it doesn’t have to repeat
every day but here you are stuck to this cauliflower or broccoli or green beans and carrots and
like you know the variety” – (202, female, age 46, relocation age 30). Four participants
mentioned that in the U.S. they had relaxed the practice of avoiding eating meat consumption on
religious designated days as strictly practiced by their family in India. “Yeah I grew up
vegetarian. My father in fact atheist, but you know didn’t believe in bringing any meats. But uh
coming here yes sometimes we ate hamburgers that time. Very rarely, but like just maybe, maybe
I remember 5-6 times I have eaten hamburger”- (401, female, age 49, relocation age 23).

Six participants indicated that their children influenced their decision to deviate from their
religious beliefs and cook and allow them to eat non-vegetarian foods or to eat prohibited meat
outside home. “But there is no restriction for my kids and my husband…I buy, like nonvegetarian is concerned I buy chicken, I buy goat or lamb and then I buy shrimp and fish. Fish
couple of varieties. But my, they, outside my house my daughter eats like sausage, pork…hot
dogs and whatever, whatever they. I don’t cook or anything” – (301, female, age 36, relocation
age 24).

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Facilitators of traditional food consumption
Social network (Family, friends and others, work place, and social events): A few participants
perceived exposure to Asian Indian foods important for transferring Asian Indian values to their
children. At least three participants mentioned that they reduced the spice level of foods to
encourage the children to eat home cooked Asian Indian foods. “I cook everything but I make
sure that the spice is less. If I put a little spice, I put little ghee or oil something to make them to
eat. So yeah that has changed drastically” – (301, female, age 36, relocation age 24). One
participant said that his children would take Asian Indian foods to school, while another
participant after a cycle of cooking Asian Indian and non-Indian foods for the children, switched
back to cooking Asian Indian foods to promote the Asian Indian foods. However, to include a
variety in the diet, non-Indian foods were cooked at home for children.

Young adults (mean age: 20.8+2.95) who were either born in the U.S. or had relocated to the
U.S. before age three (n=5) and also had parents in the U.S. perceived that access to traditional
foods facilitated by parents was an important factor for consumption. I go home quite a bit to eat,
but if I’m on my own I don’t eat as regularly as I should…my mom like when I was really little
we used to have Indian food almost every day…and then since I live close to home, my mom
drops off a lot of food too” – (703, female, age 20, 2nd generation). From the parent’s
perspective, however, exodus of children for college or work increased the likelihood of
consumption of more traditional food. Food purchasing was also impacted as they were no
longer purchasing the non-Indian foods that their children were fond of. “for the family, for the
dinner and all its always you know more of a Indian thing like just one sabji and one roti and
something” – (404, female, age 51, relocation age 23). A second-generation female participant

55

noted that her non-Indian friends preferred Asian Indian food. “If I had my friends from like
school over there were not Indian, they would actually prefer to have Indian food” – (703,
female, age 20, 2nd generation).

Elders (e.g. participants’ parents) from India who visited family in the U.S. for a limited period
of time were also influential in the selection of Asian Indian foods. Participants (n=6) mentioned
that Asian Indian foods were always cooked at home when seniors were present. This was true
when dining out as well even though they were limited by specific restaurant choices that are
acceptable for visitors from India. “…like when parents come we pretty much have like breakfast
like my mom prepares something like upma or something and then lunch and dinner. Then in
between some snack like samosa or pakoda…So when parents come it’s, it was different” – (504,
female, age 28, relocation age 22).

Asian Indian foods were served for both non-Indian and Asian Indian guests, which included
traditional and regional specialty Asian Indian foods, meat based spicy foods, simple and easy
foods, “can’t go wrong” type of foods, and rice based Asian Indian dishes such as pulao. The
spice level of the foods played an important role in foods consumed/ served during non-Indian
social events. “most of the American friends that I had, always loved Indian food. So and they
like spicy food too. So we didn’t have to go down on the spice levels. May be we will incorporate
some American stuff like salsa, dips and stuff but everything else is pretty Indian, yeah” – (102,
male, age 27, relocation age 21).

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Health and nutrition: While greater health awareness was perceived as a positive influence by
many, it was interesting to note that three participants were concerned that increased emphasis
on food and health may sometimes result in negative consequences such as inadequate food
consumption, being overly conscious about calories and nutrients, and increased stress about
food and health. “I think the stress level like I look at the ingredient label all the time. It is crazy
like I never looked at all of these things in India…more aware or more psychotic, it’s a little bit
crazy now” - (304, male, age 31, relocation age 24).

From a health perspective, participants were keen on preparing home cooked Asian Indian meals
as it was perceived by some to be healthy as there are many fresh produce items and ingredients
included instead of preservatives typically added in the prepackaged foods. The Asian Indian
foods were referred to as being wholesome and satisfying even though others were of a contrary
opinion. Therefore, Asian Indian foods were considered healthy since they included healthy
snack options, healthy spices, and fresh produce. More specifically, Asian Indian foods (e.g. roti
with vegetable sabji or rice with lentils) were considered healthy when consumed in moderation.

Media: The media was primarily used for learning recipes. One female participant said that she
was passionate about cooking and hence would find recipes from the internet that could also
include Asian Indian foods. “Um you know, something some that are different you can look up,
yeah on the TV and on the web. I do browse a lot on food; I really love food and cooking too…so
then I actually go buy for the recipe (Moderator: is it mostly Indian?) anything yeah”- (603,
female, age 29, relocation age 23).

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Taste preferences: Participants were asked about their food choices and dietary behaviors during
their stay in India either before relocating to the U.S. (for participants of first-generation) or
when they went on trips to India (for participants of second-generation and those who relocated
before age three). The majority of the participants ate home cooked meals most of the time when
they lived in or travelled to India although they had the opportunity to try other cuisines. In the
U.S., it is during dinner that Asian Indian foods were increasingly consumed compared to the
other meal occasions. Three participants mentioned that bland foods and salads did not suit their
Indian palate since they were not accustomed to eating such foods in India. “As far as I’m
concerned I don’t want to eat it (non-Indian foods) because it doesn’t suit my palate, as simple
as that. And I think their food is very very very very bland. Because their vegetarian is you know
poached potatoes and salad” - (302, male, age 62, relocation age 60).

Participants’ favorite Asian Indian items included Asian Indian sweets, snacks, biscuits, tea,
Asian Indian style chicken dishes, dosa, regional specialty foods, curries, meat dishes, rice
dishes, spicy vegetarian foods, potato dishes, and Asian Indian toast. When discussing the foods
that participants were not able to obtain in the U.S., the majority recollected Asian Indian street
foods/ fast foods typically known as “chats” (e.g. bhel puri, pani, puri, and vada pav), Asian
Indian sweets, beverages, breakfast items, and snacks, the varieties of greens versus spinach or
other selected greens available in the U.S., varieties of root vegetables, and festival foods. “I
kind of miss the uh chats uh Pani Puri. I kind of miss the idly, vada, but I mean I started to make
that but I really miss the chat and yeah Pani Puri, Bhel Puri, Masala Puri and stuff” – (504,
female, age 28, relocation age 22).

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Restaurants: Eight participants said that they preferred to eat at Asian Indian restaurants. It was
perceived that Asian Indian restaurants in the location where participants lived were not as good
as the ones in big cities in the U.S. Therefore, a few participants said that they would often drive
to big cities that are close by to eat at Asian Indian restaurants. One participant said that her
family would only go to restaurants that serve halal meat (meat permissible for consumption by a
Muslim) due to religious restrictions. “In our case we actually look for Halal food. Like we can’t
eat everything so that narrows down our choices again” – (504, female, age 28, relocation age
22).

The preference for traditional foods was evident in the concern expressed by ten participants,
that limited Asian Indian options were available for vegetarians in the U.S. especially when
travelling. Hence a few participants (n=12) indicated that took home cooked Asian Indian foods,
especially if they are accompanied by visitors from India. “Wherever we go, we make rice and
puliyodharai and Lays…our latest addition this time was to buy a rice cooker…you go to a hotel
and then you don’t know what to eat. So if you have a rice cooker, yogurt is available then and
you just, and for the south Indian anybody the rice and dahi (yogurt) is more than enough” (302, male, age 62, relocation age 60).

Food preparation: Participants often prepared and consumed Asian Indian foods mainly for
dinner (n=17). Participants who cooked Asian Indian foods said that they had the ability to
prepare complicated Asian Indian foods, could prepare the foods in large quantities during the
weekend and saved some for other occasions, purchased food processors that are needed to cook
Asian Indian foods, and obtained help from their relatives in India if they needed directions to
cook Asian Indian foods. “I mean you can’t keep eating, I mean you can’t keep same things for
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month’s right so you need to learn new things. I used to call my mom and used to ask the recipe
how to cook something” – (601, male, age 25, relocation age 24). Alternatively, to satisfy
traditional food preferences, purchasing frozen Asian Indian breads (naan/ rotis) and ready to eat
curries on days that they were busy also occurred.

Food purchasing: Although the variety of products were not as extensive as those available in
India, participants perceived that the availability of Asian Indian products had increased over the
past few decades and that they were able to obtain almost every Asian Indian food product in the
U.S. According to a few participants, availability of Asian Indian food products differed based
on location in the U.S. Participants who were particular about purchasing good quality Asian
Indian groceries and produce said that they would shop at another big city in the state on a
regular basis. “These days I think we are getting almost everything that we want but it is region
specific…But even here, I think from the Indian store I think we have at least 90% of the stuff
that we get in India and if you go to Detroit we get much more, many more options, California,
Texas, you have everything” – (102, male, age 27, relocation age 21).

Religious and cultural beliefs: Eleven participants said that they had maintained religious
restrictions such as being a strict vegetarian (Hindu), avoiding beef and pork (Hindus and
Muslims), and consuming only halal meat if they were Muslim. Three participants mentioned
that similar to India, they avoided eating meat on religious designated days in the U.S. Religious
dietary restrictions were also imposed on children as mentioned by one participant. “Being
religious, uh religion made a difference in introducing food to my kids. I introduced chicken to
them, fish to them, but never really meat. Beef never, never and somehow pork also”- (401,
female, age 49, relocation age 23).A few participants (n=4) who were strict vegetarians regarded
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themselves as ‘picky eaters’ since even the aroma of non-vegetarian foods was bothersome. They
mentioned that it was unacceptable for them if the same gloves were used to serve meat and
vegetarian food. “when I am eating every bite of that food it’s there like you know she put the
same hand in all those things and she made my food, which I don’t relish” – (202, female, age
46, relocation age 30).

There were other factors pertaining to religion that impacted the dietary behaviors of participants
or their families. One participant mentioned that her son avoided eating beef after attending a
religious camp. A second-generation female participant said that her husband came from a
staunch Hindu family and she strictly avoids beef after her marriage. “He (participant’s
husband) is half Hindu, so he was brought up with the idea that beef is really bad for you so he
never touches beef and he’s really strict about that. I will eat a soup if it’s a beef broth, he won’t
touch it. So I mean to that level” - (403, female, age 26, 2nd generation). A male participant who
had tried various types of meat that are uncommon (e.g. alligator meat) said that he refrained
after realizing that his parents disapproved. One male participant, who started eating steak after
coming to the U.S., mentioned that he experienced social stigma while eating with his friends
and felt guilty.

Discussion
Our study objective was to investigate the factors influencing dietary acculturation based on the
theoretical model proposed by Satia-Abouta (Satia-Abouta et al., 2002). In the three domains that
we qualitatively analyzed (cultural, psychosocial, and environmental), exposure to new foods
played a role in the following key factors that were related to dietary acculturation: (i) social
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independence, (ii) social network influences for consuming non-Indian foods, (iii) increased
health awareness, (iv) sub-standard taste and increased cost of Asian Indian snacks/ restaurant
foods, and (v) time constraints and convenience.

Social independence
Participants recollected living in a closely connected family setting with extended family
members in India. Hence a family member who was primarily responsible for meal preparation
determined their food choices. In contrast, in the U.S., participants were responsible for their
own meals. Thus the social independence along with the exposure to new food environment led
to self-determination of food choices, which in some cases happened to be preference for and
exploration of new and uncommon foods (Pettys and Balgopal, 1998).

Social independence also impacted religious beliefs of participants (Bharmal et al., 2013).
Among Asian Indians in California, religiosity was found to be lower among those with higher
dietary acculturation to the host culture (Bharmal et al., 2013). In our sample, religious
restrictions such as avoidance of certain (e.g. beef or pork) or all meat products and religious
fasting on religious designated days by eating exclusively vegetarian foods were relaxed by a
few participants upon relocation. On the other hand traditional religious dietary practices were
still rigidly practiced by some participants who were influenced either by their family or place of
worship.

The two predominant religions of India, namely Hinduism and Islam have dietary restrictions
such as avoidance of beef/all meat and pork, respectively (Eliasi and Dwyer, 2002). In addition
62

to these foods, Muslims in India also eat “halal” foods, which translates as “permissible for
consumption by a muslim”(Eliasi and Dwyer, 2002). Furthermore, abstinence of certain foods
such as animal products is practiced on religious designated days. Classifying a food as halal
depends on how the food is obtained and processed in addition to several other determining
factors (Eliasi and Dwyer, 2002). This was clearly evident by the participant who only selected
restaurants that served halal foods.

Bharmal et al (2013) analyzed information from telephone interviews with 3228 Asian Indians in
California from the 2004 California Asian Indian Tobacco Survey. Half of the Asian Indian
participants in this study were classified as highly religious. Religiosity was associated with an
increased likelihood of being overweight or obese for Hindus but not for Muslims. The authors
discussed that the different religious practices within these religions (Muslims practice fasting
and abstain from alcohol while Hindus consume foods high in saturated fat and refined sugars)
could serve as a possible explanation for this difference (Bharmal et al., 2013).

Social network influences for consuming non-Indian foods
Social network appeared to be very influential in participant food selection in our sample.
Participants tried and explored new foods for family members at home and when eating outside
and accommodated preferences of family members, which was especially true in households
with young children. It was evident from our sample that more than their parents, Asian Indian
children under 18 years had a strong preference for other ethnic foods. These findings were
consistent with a study conducted with Arabs in Canada. This study showed that Arab children
who were raised in Canada preferred other ethnic foods to traditional Arabic foods (Abou El
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Hassan and Hekmat, 2012). The same was apparent in a qualitative study with Pakistani women
in Norway, which documented increased consumption of Norwegian vs. traditional foods by
young children (Mellin-Olsen and Wandel, 2005).

Households with seniors or visitors from India were more likely to practice traditional dietary
behaviors and were hence less exposed to host country foods in the home. In contrast parents in
households with children under 18 years, were not as rigid in imposing their religious rules on
children’s dietary habits. Although parents did not consume or prepare prohibited foods at home,
children were allowed to select those foods at school or when they dined elsewhere. On the other
hand, parents with children above 18 years and who lived away from the family regularly
provided traditional home cooked foods during their visits. Those children who were all of
second generation had limited ability to cook traditional foods and hence relied mostly on other
ethnic food choices that were widely available. Thus, for families with children, age of the
children appeared to be an important determinant of the dietary habits of the entire family.

Dietary acculturation has been shown to be greater among children and adolescents (vs. adults)
and those of second/third generation (vs. first generation) (Smith and Franzen-Castle, 2012, Tam
et al., 2010, Wutso et al., 1995). In a study of Mexican American adolescents (12-19 years) in
the NHANES 1999-2004 data set, second and third generation children and adolescents had
poorer diet quality than first generation children. This was documented by significantly lower
overall HEI 2005 scores as well as the individual HEI components - total fruit, whole fruit, total
vegetables, dark green, orange vegetables and legumes, and meat and beans. On the other hand,
whole grains, saturated fat, and sodium, intake was significantly higher for second and third

64

generation children and adolescents. In addition, energy from SoFAAS and intake of sweetened
beverages was higher for third generation (Liu et al., 2012). Therefore, adaptation to host
country’s dietary practices may have a greater impact on children’s food choices and
subsequently may impact their diet quality.

In a qualitative study among Hispanic adults in South Carolina, family members were influential
in participant food choices (Chavez-Martinez et al., 2010). Second generation Asian Indians or
those who were born in India but relocated to the U.S. as children tend to choose foods that are
both traditional as well as those that are available in the host country, which they were exposed
to while growing up as adults (Koenig et al., 2012). Therefore, it is important to be aware that
they are more likely to have a dietary pattern that is different from the first generation Asian
Indians. Likewise, intake of energy dense foods increased during social gatherings in our study.
Koenig et al. argues that the guest-host relationship is a social factor in Asian Indian families
wherein the host encourages the guest to eat heartily to show affection and to facilitate rapport
(Koenig et al., 2012). This might also result in less “healthful” eating from the traditional food
perspective.

Increased health awareness
In our study, it emerged that during the initial years, first generation Asian Indians experienced
social independence, which when coupled with a new food environment facilitated intake of less
healthy foods and weight gain. However, over a period of several years, they gained nutrition
knowledge through various resources and subsequently increased their health awareness, which
may result in selection and substitution of healthy foods. In our sample, age (older vs. younger)
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and having a family member with a medical condition or in the health care field also led to
selection of what was perceived as healthy foods. These were not necessarily foods of Asian
Indian origin. A medical/ health condition could therefore be a major determinant for the
adoption of healthy dietary habits, regardless of preference for traditional or non-traditional
foods (Chavez-Martinez et al., 2010).

The majority of our study participants mentioned that they gained health awareness in the U.S.,
which was reflected in their diet and eating habits. This notion was also conceived by Arabs of
the Greater Toronto Area, and such a change was believed to occur mainly through increased
awareness of health and nutrition (Abou El Hassan and Hekmat, 2012). However, contradicting
results have also been documented in various cultures where poor dietary habits were adopted by
individuals who relocated (Pan et al., 1999). Therefore, it appears that dietary acculturation
could vary depending on the ethnic group chosen for investigation, or there may be other
participant characteristics such as income, educational level or nutrition knowledge that may
explain this difference between and within cultures. Similarly media was also perceived as a
resource for the exposure to new foods as well as to learn about food and nutrition. Television
was perceived as an important source of nutrition education/information that promoted healthy
food consumption by our study participants as well as in another study conducted among
Hispanics (Chavez-Martinez et al., 2010).

Sub-standard taste and increased cost of Asian Indian snacks/ restaurant foods
It was perceived that some of the foods sold at the Asian Indian specialty stores were expensive
and lacked product/ nutritional information compared to the ones sold in the regular grocery
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stores. Hence, they were concerned about the shelf life and taste of some of the products that
might have been in the shelves beyond the expiration date. This was particularly mentioned for
Asian Indian readymade snacks, which led to selection of non-Indian foods for snacks.

Distance and availability of ethnic products in local specialty ethnic stores could be a limiting
factor for the consumption of traditional foods. In our study, participants who had a vehicle were
able to go farther to a bigger city to purchase fresh or locally unavailable Asian Indian
ingredients and foods. Therefore, as mentioned by some participants, alternative non-traditional
foods were selected. Similarly, Hispanics in South Carolina perceived unavailability of specific
ethnic foods as a barrier to traditional eating behaviors in the U.S. (Chavez-Martinez et al.,
2010).

When dining out, some Asian Indians said they preferred to try new foods that were not
commonly found in India. Restaurants were also chosen based on special offers, reviews and
recommendations. Indian restaurants were not frequently sought after by many because
participants had a tendency to compare the authenticity of the taste to that of the food offered in
India or at home and were hence not completely satisfied. Asian Indians who were vegetarians
mentioned that they had limited non-Indian dining options (salads, vegetarian sandwiches or
cheese pizza most of the time), which resulted in initiation of meat consumption by some.

Traditional foods were considered to be expensive by some participants in our study. In a study
among Hispanics, fresh fruits and vegetables were deemed expensive in the U.S. The same study
also showed that it was a common practice during food purchasing to compare the prices of such

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foods in the U.S. with that of their home country, however, comparing prices of foods decreased
over a period of stay in the U.S. (Chavez-Martinez et al., 2010). Therefore, food purchasing
based on cost may not necessarily be a barrier for non-native individuals who have the financial
means and who have a longer duration of stay in the U.S.

Ability to cook Asian Indian foods, time constraints and convenience
Selection of non-Indian foods was more prevalent among those who did not have the time to
cook at home or had limited ability to cook any kind of food. This was especially true for second
generation Asian Indians who perceived that Indian foods take longer to cook. Similar to our
study, cooking traditional foods was perceived to be time consuming, and hence a barrier for the
frequent consumption of such foods by the Arab populations as well (Abou El Hassan and
Hekmat, 2012). Moreover, many individuals who moved to the U.S. may not be aware of
traditional cooking methods and hence lack the skills to prepare traditional foods (ChavezMartinez et al., 2010).

Consistent with other studies, breakfast items had drastically changed from what participants
typically consumed in India, while dinner consisted of predominantly Asian Indian foods
(Mellin-Olsen and Wandel, 2005). The typical weekday and weekend dietary recall data showed
an increased inclusion of non-Indian foods for breakfast, which were deemed convenient by most
participants. Lunch and snacks included both Asian Indian and non-Indian items. It was evident
that consumption of alcohol, meat, fish, soda, milk, fruits, and non-Indian foods increased in the
U.S. while rice, spicy foods, sweets, and potato chips gradually decreased over time. In
summary, according to the conceptual model of dietary acculturation, various factors within the
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three domains (religious and cultural beliefs, psychosocial changes and changes in taste
preferences, and environmental changes) influenced the dietary behavior of Asian Indians.

Strengths and limitations
Recruitment of subjects for the focus groups was facilitated by providing incentives for
participation and through advertising via Asian Indian organizations. Two researchers coded
qualitative focus group data independently and coding consensus was obtained to minimize bias.
For the focus group discussions, the primary and the assistant moderators belonged to the same
ethnicity and therefore participants were more comfortable and willing to disclose dietary and
survey information. The fact that the primary and assistant moderators were Asian Indians also
facilitated rapport with the participants during focus group discussions (Vatrapu and PerezQuinones, 2006). Since the focus group participants were located in metropolitan/ suburban areas
in Michigan, our sample was limited to one geographical region and hence may not be
representative of the dietary behaviors of Asian Indians in the other regions in the U.S. However,
a few participants had lived in the other states in the U.S. and recollected and compared their
experiences to that of the current location. This provided some insight into potential regional
variations.

Our sample consisted of a large proportion of individuals who were highly educated and had
high annual household incomes, which could be attributed to the fact that most of the first
generation Asian Indians were in the U.S. primarily for education or job opportunities. Hence,
our sample may be reflective of the characteristics of a large proportion Asian Indians in the U.S
(Whatley and Batalova, 2013). This is also evident in the U.S. census data, which depicts Asian
69

Indians to have high education and median incomes (U.S. Census Bureau, 2004) as well as a
previous study, which included in-depth interviews with Asian Indian adults with type 2 diabetes
in Michigan (Venkatesh et al., 2013, Venkatesh and Weatherspoon, 2013). In our study, only 5
participants were either second generation or relocated to the U.S. before age 3. Therefore, more
participants in this category would have allowed us to better capture the perceptions of second
generation Asian Indians in the U.S. and can be viewed a limitation.

Conclusion
This study documented the factors influencing dietary changes of Asian Indians in the U.S. The
key facilitators that emerged from our data relative to dietary acculturation were: social
independence, social network influences, increased health awareness, sub-standard taste and
increased cost of Asian Indian snacks/ restaurant foods, and time constraints and convenience.
Our study adds to the evidence that multiple factors may influence an individual’s food choices,
and that dietary acculturation can lead to both healthful and unhealthy eating patterns (Sobal and
Bisogni, 2009).

70

II. Manuscript 2 (specific aim 2)
Reliability and validity of An Asian Indian Dietary Acculturation Measure (AIDAM)

Abstract
Background: Dietary acculturation (adopting the eating patterns/ practices of the host
environment) of individuals who relocate to another country could be a risk factor for dietrelated chronic diseases. A reliable and validated measure for the assessment of dietary
acculturation may facilitate understanding if and how dietary acculturation is related to dietrelated chronic diseases in various non-native populations.
Objective: Our objective was to determine the reliability and validity of an Asian Indian Dietary
Acculturation Measure (AIDAM) for Asian Indian adults living in the U.S.
Methods: A cross-sectional web-survey was administered nationwide to 191 Asian Indian adults
in the U.S. that consisted of the AIDAM, a food frequency consisting of Asian Indian (AI-FFQ)
and non-Indian foods (NI-FFQ), and participant sociodemographic questions. Construct validity
and reliability were examined through a polytomous Rasch model. The relationship between
AIDAM and the AI-FFQ and the NI-FFQ scores were examined using correlations and linear
regression analysis.
Results: Except for one item that was excluded due to misfit, 50 items were stable. The root
mean square error was 0.08 for all the items and the item and person reliabilities were 0.98 and
0.88, respectively. AIDAM was positively related to NI-FFQ (r=.265) and negatively related to
AI-FFQ (r=.432) based on correlations and linear regressions (p<.001).
Conclusion: Our analysis showed the AIDAM to be a reliable and valid measure of dietary
acculturation when tested with Asian Indians in the U.S. This tool can be used by health
71

professionals to determine the level of dietary acculturation as well as diet quality implications
and enhance the investigation of the potential association with risk for diet-related diseases.

Introduction
Asian Indians are the second largest Asian group in the U.S. and constitute nearly 1% (3.2
million) of the U.S. population (U.S. Census Bureau, 2012). Asian Indians in the U.S. are
concentrated in California, New Jersey, Texas, New York, and Illinois, which are also areas with
high concentrations of other immigrant/ non-native populations (Camarota, 2012, Whatley and
Batalova, 2013). Dietary behaviors in such areas may be diverse with foods from different
cultures. In addition, exposure to a new environment in general could also be associated with
changes in types of foods that nonnative populations consume in a different environment when
compared to their home country.

Dietary acculturation (the adaptation of the eating patterns/ practices to the host environment by
individuals who move to a new cultural milieu) is hence highly likely (Satia-Abouta et al., 2002).
However, the extent to which these changes may be beneficial or harmful from a health
perspective is not conclusive. For example refined grains, high-fat dairy, and red meat increases
the risk for type 2 diabetes and cardiovascular risk factors while whole grains, nuts/seeds, fruits
and vegetables all have a protective effect (Nettleton et al., 2008, Stricker et al., 2013). Dietary
acculturation of Asian Indians in the U.S. has been characterized by consumption of a diet high
in fat, animal and saturated fat, cholesterol, convenience foods, alcohol, whole grain foods, fish,
poultry, meat, salty snacks, and sugar/ sweets/desserts, while a diet low in saturated fat and fiber

72

was documented by another study (Balasubramanyam et al., 2008, Jonnalagadda and Diwan,
2002, Kulkarni, 2004).

Asian Indians are genetically prone to several diet-related diseases regardless of location of
residence, which was also evident in the studies conducted with this target group in the U.S.
(Bainey and Jugdutt, 2009, Enas et al., 2007). However, it is important not to disregard
environmental risk factors, including dietary behaviors. Dietary risk factors for chronic diseases
are low consumption of fruits, vegetables, nuts and seeds, foods high in omega 3 fatty acids,
whole grains, foods rich in fiber, and consuming a diet high in sodium and processed meat (Lim
et al., 2012).

A high prevalence of diet-related chronic diseases have been documented among Asian Indians
in the U.S. such as type 2 diabetes (17.4% to 29%) and metabolic syndrome (26.9 to38.2%),
which are risk factors for cardiovascular diseases (Kanaya et al., 2010, Misra et al., 2010b,
Simmons et al., 1992, Venkataraman et al., 2004). Studies conducted in the U.S. have shown
Asian Indians to be more likely to be affected with CVD and diabetes (odds ratio >2.0 vs.
whites) than the general population (Enas et al., 1996, Kanaya et al., 2010, Lee et al., 2011,
Mohanty et al., 2005, Oza-Frank et al., 2009, Rajpathak et al., 2010).

Diet related chronic diseases can increase medical expenditure and may result in poor quality of
life, while consuming a diet consisting of healthy foods can prevent or delay the occurrence of
such complications (Frazao, 1999).When investigating diet-related disease risk factors of nonnative populations, dietary acculturation could therefore be an important avenue of interest to

73

many researchers. A culture specific measure for the assessment of dietary acculturation may be
useful in explaining the extent to which dietary changes have occurred in non-native populations,
as well as the quality. Research studies on dietary risk factors of migrants have not exclusively
focused on dietary acculturation per se but included several other indicators of acculturation
along with only one or two items on dietary behaviors.

More specifically, dietary acculturation measures referred to in the literature for Asian Indians
were not comprehensive and the likely gap noted was the lack in attitudinal scales (Raj et al.,
1999, Uusitalo et al., 2005, Varghese and Moore-Orr, 2002). In addition, the dietary
acculturation scales developed for other cultures such as the Chinese, Japanese, and Koreans
have culture specific foods, which were not deemed appropriate for Asian Indians (Bojanic and
Xu, 2006, Kim et al., 2007, Lv and Cason, 2003, Pierce et al., 2007, Satia-Abouta et al., 2001,
Sukalakamala and Brittin, 2006, Yang and Fox, 1979).

Therefore, we developed a culture specific tool called the “Asian Indian Dietary Acculturation
Measure” (AIDAM) to assess the level of dietary acculturation of Asian Indians by conducting
focus group discussions, soliciting experts input, and by reviewing relevant literature. The
validity and reliability of any tool is critical to be able to accurately measure the underlying
concept and for reproducibility. The objective of this study was to determine the reliability and
validity of an Asian Indian Dietary Acculturation Measure (AIDAM) for use with Asian Indian
adults in the U.S.

74

Methods
AIDAM was developed by conducting eight focus group discussions soliciting input from
experts (Asian Indian registered dietitians and/or researchers in nutrition/acculturation and
specialists in survey research and Rasch data analysis) and reviewing relevant literature (refer to
chapter 4 - manuscript 1). In order to conduct reliability and validity testing of the AIDAM
instrument, it was important to include a nationwide cross sectional sample of Asian Indian
adults in the U.S. This was accomplished by conducting a web-based survey, administered
through an independent organization with access to a variety of national databases of survey
participants that can be prespecified to ensure appropriateness for study purposes.

The sample size for the web-survey was calculated for Rasch polytomous models that are
employed for attitudinal rating scales. As for any other statistical analysis, a small sample size in
Rasch analysis would yield less precise estimates, less powerful fit analysis, and less robust
estimates. A sample size between 108 and 243 is recommended to have item calibrations that are
stable with +½ logit interval with a two tailed 99% confidence interval. For most purposes, the
optimum sample size recommended to achieve this is 150 (Linacre, 1994). Anticipating missing
responses, we targeted a sample of >200 to be able to have meaningful data from a larger
sample. Therefore, we collected data from 225 Asian Indian adults in the U.S. Participants who
did not complete all the items of the AIDAM were excluded resulting in a final sample consisted
of 191 participants.

Recruitment of participants and administration of the web-survey was contracted through the
Office of Survey Research (OSR) at Michigan State University via Qualtrics Research Suite, a

75

program designed to conduct web-based survey research (Qualtrics, 2009, Provo, Utah, USA.
Version. 12,018). Qualtrics Research Suite used Research Now group, Inc (formerly known as
E-Rewards, Inc, headquartered in Plano, Texas) for recruiting Asian Indians. Research Now is a
recognized market research company that rewards participants for time spent taking market
research surveys. A response rate of 16% was achieved (1408 emails sent and 225 participants
completed the survey), and participants who completed the survey were allowed to redeem gift
cards, program points, and partner products or services.

Interested and eligible participants (Asian Indians > 18 years) were provided with a link, which
provided access to an informed consent form for participation as well as the survey items, which
were: (i) the AIDAM, (ii) a food frequency questionnaire that included Asian Indian and nonIndian foods, and (iii) sociodemographic questions such as information on participant age,
gender, education level, employment status, duration of stay in the U.S., religion, marital status,
annual household income from all sources, language mostly spoken at home, and residency in
the U.S.

Asian Indian Dietary Acculturation Measure (AIDAM)
Instrument Development: The AIDAM was developed to measure the level of dietary
acculturation of Asian Indian immigrants/ non-natives in conjunction with the influence of
various underlying cultural, psychosocial and environmental factors on participant food choices.
We explored the dietary patterns/practices of Asian Indians in the U.S. to be able to construct an
instrument that specifically applies to this ethnicity by utilizing the following methods: (i) a
thorough review of the literature on measures of Asian Indian dietary acculturation behaviors,
76

(ii) applying the conceptual model of dietary acculturation proposed by Satia-Abouta (SatiaAbouta et al., 2002) to define the domains of the dietary acculturation instrument, (iii) utilizing
the themes generated from 8 focus group discussions with 30 Asian Indian adults, (iv) including
recommendations from experts in nutrition/ dietetics of Asian Indian origin and experts in
qualitative research, survey research and Rasch analytical approach, and (v) encompassing
feedback from the target population by pilot testing the dietary acculturation items with 14 Asian
Indian adults in Lansing, Michigan. This rigorous procedure resulted in 51 items on dietary
acculturation.

(i) Literature review: The literature on dietary acculturation measures for Asian Indians showed
that there was a gap in the literature related to attitudinal scales. Along with studies on Asian
Indians as well as studies on other ethnic groups, data collection procedures, and the type of
questionnaires used were examined to facilitate the process (Bojanic and Xu, 2006, Kim et al.,
2007, Lv and Cason, 2003, Pierce et al., 2007, Raj et al., 1999, Satia-Abouta et al., 2001,
Sukalakamala and Brittin, 2006, Uusitalo et al., 2005, Varghese and Moore-Orr, 2002, Yang and
Fox, 1979).

(ii) Theoretical model: Based on the theoretical model on dietary acculturation, when exposed to
a host culture, the socio-demographic and cultural factors along with psychosocial changes and
changes in the taste preferences, food procurement and preparation may result in differing
patterns of dietary intake (Satia-Abouta et al., 2002). Predetermined themes within these
domains (psychosocial factors and taste preferences, environmental factors, and cultural factors)

77

were identified based on this model. Therefore, the themes included these domains, which were
deemed crucial for comprehensive assessment.

(iii) Focus group discussions with Asian Indians: We conducted eight audio-taped focus group
discussions (2-5 participants per group) with thirty Asian Indian adults in a Midwestern state in
the US. The transcripts were independently analyzed by two researchers of Asian Indian origin
to generate themes within the perceived factors influencing dietary acculturation based on the
model proposed by Satia-Abouta (Satia-Abouta et al., 2002). The items represented the three
domains (psychosocial factors and taste preferences, environmental factors, and cultural factors)
and the eight underlying themes that were postulated as the influential factors of dietary
acculturation behaviors: social network (9 items); health and nutrition (8 items); media (2 items);
taste preferences (13 items); restaurants (3 items); food preparation (10 items); food purchasing
(3 items); and religious and cultural beliefs (4 items) (details provided in chapter 4 - manuscript
2).

(iv) Expert reviews: Content validity, was established through expert reviews and pilot testing of
the instrument. Ten professionals revised the instrument for comprehensiveness; appropriateness
of the language used in the items, relevance to Asian Indians, and provided suggestions for
instrument improvement. The experts were eight Asian Indians who are either registered
dietitians and/or researchers in nutrition/acculturation and who were knowledgeable in Asian
Indian food choices and dietary practices; a specialist in survey research who provided
suggestions for question formulation and improvement of the readability of the instrument; and a
professor with expertise in Rasch data analysis who reviewed the instrument items for data

78

analysis efficacy. Initially, there were 35 items in the AIDAM that was sent to the experts for
reviewing, 16 items suggested by the experts were then added resulting in a total of 51 items.

(v) Pilot testing: The revised instrument was approved by the Michigan State University
Institutional Review Board (MSU IRB) and was pilot tested with 12 Asian Indian adult
participants (mean age: 34.42+9.9 years) who participated in the focus group study that we had
previously conducted. The pilot survey was administered through Michigan State University
Office for Survey Research who used Qualtrics Research Suite (Qualtrics, 2009, Provo, Utah,
USA. Version. 12,018). Participants were contacted by email. A brief summary of the results of
the focus group discussion in which they had participated was provided along with a link to the
web-survey. Participation in the pilot test was entirely voluntary.

The pilot test results allowed the items that were frequently skipped or which appeared to be
incorrectly interpreted to be examined or modified. Feedback on the length of the survey was
also provided. Thus, the pilot test determined feasibility, the appropriateness of the language
used in the items and the respondent burden. The only change that was made to the web-survey
after the pilot testing was modification of the response categories of the food frequency
questionnaire. The NHANES food frequency assessment categories were used to consolidate the
food frequency response into five categories.

This rigorous instrument development procedure for the AIDAM resulted in 51 items on dietary
acculturation. The items were in the form of statements and participants evaluated each statement
and provided their level of agreement or disagreement on a five point Likert scale. The Flesh-

79

Kincaid readability score was 5.9 for the AIDAM and 8.3 for the entire web-survey, which
indicates that the instrument was constructed with fifth to sixth U.S. grade reading level. The
instrument measured the extent of dietary acculturation with traditional Asian Indian dietary
practices to western/ non-Indian practices. Five Likert ordered response levels were used with
the following format: (1) strongly agree; (2) agree; (3) neither agree nor disagree; (4) disagree;
and (5) strongly disagree. Twenty three items that represented non-Indian dietary practices were
reverse coded. Since dietary acculturation is not unidimensional, these items were included to
represent non-Indian dietary practices; however, they were reverse coded to obtain a single
dietary acculturation score. For the items with reverse coding, scores were assigned as strongly
agree=5 to strongly disagree=1. The responses for all the items were added and divided by the
number of items. The final scores also ranged from 1 to 5 with 1 indicating an Asian dietary
pattern and 5, a western/non-Indian dietary pattern.

Food frequency questionnaire
A food frequency questionnaire was developed by the primary researcher consisting of Asian
Indian and non-Indian foods (table 4). A food list was compiled based on the literature and from
two 24 hour typical weekday and weekend dietary recall data that we collected from the focus
group participants. The frequency of consumption of foods given in the food list was determined
using a scale ranging from never =0, 1-11 times a year = 1, 1-3 times a month = 2, 1-6 times a
week = 3, and every day = 4. Asian Indian (25 items) and non-Indian (25 items) foods in the
food frequency questionnaire were identified and separated to compute Asian Indian (AI-FFQ)
and non-Indian (NI-FFQ) scores that ranged from 0-100 (see table 4 for the list of Asian Indian
and non-Indian items).
80

Table 4. List of Asian Indian and non-Indian foods in the Food Frequency Questionnaire
Asian Indian
Non-Indian
1. White rice
1. Brown rice
2. Idly
2. Cous cous
3. Vermicelli
3. Quinoa
4. Dhokla
4. Pizza
5. Handvo
5. Pasta/ spaghetti
6. Dosa
6. Macaroni
7. Sambar/ Dal
7. Chinese noodles
8. Sabji
8. Tortillas/ tacos
9. Paneer dishes
9. Non-Indian sandwiches
10. Ethnic vegetables (e.g. drumstick, raw/
10. Non-Indian Salad
green banana, bitter gourd, etc.)
11. Indian tea
11. Bacon
12. Papad/ fryums
12. Roast beef
13. Indian chutney
13. Hot dogs
14. Indian pickles
14. Greek yogurt
15. Indian mixed rice dishes (e.g. biryani,
15. Flavored yogurt
lemon rice, etc)
16. Indian rice and lentil dishes (e.g. Khichdi, 16. Green tea
pongal, bisibelabath, etc.)
17. Ready to eat Indian meals (e.g. swad,
17. Cold breakfast cereals
deep brands)
18. Indian bread (e.g. chapatti, naan, paratas, 18. Hot cereals (e.g. oatmeal)
etc.)
19. Indian style simple meat or vegetable
19. Pancakes/ waffles/ bagels
curry
20. Indian style stir fried vegetables
20. Breakfast cereal bar
21. Indian style party foods (cream based/oily 21. Ready to eat non-Indian meals (e.g. lean
curries or foods)
cuisine, banquet, etc.)
22. Indian fried foods (e.g. puri, vada,
22. Non-Indian bread (e.g. multigrain, rye, pita,
samosa, pakora, etc.)
rolls, crescents, corn bread, etc.)
23. Indian fast foods (e.g. bhel puri, pani
23. Non-Indian fast foods (e.g. french fries,
puri, etc.)
burger, etc.)
24. Indian sweets/ desserts (e.g. burfi, gulab
24. Non-Indian sweets/ desserts (e.g. Donut,
jamun, kheer, etc.)
pie, brownie, cookies, tart, etc.)
25. Indian ready made salty snacks (e.g.
25. Non-Indian readymade salty snacks (e.g.
mixture, chakli/ murukku)
pretzels, tortilla chips, Chex-mix, etc.)
Scale range: never =0, 1-11 times a year = 1, 1-3 times a month = 2, 1-6 times a week = 3, and
everyday = 4.

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Scores were assigned for each category of the food frequency questions as follows: Everyday =
4, 1-6 times a week = 3, 1-3 times a month = 2, 1-11 times a year = 1, and never = 0. The scores
were calculated based on participant responses by adding the number corresponding to each
response category for each item in the food list. Thus, a higher score in the AI-FFQ or NI-FFQ
categories indicated frequent selection of corresponding foods by the participants. The AI-FFQ
or NI-FFQ scores were also used for external validation of the AIDAM by correlating with the
AIDAM.

Data analysis
Responses to the items were examined for any missing information. Only responses with
complete information for all the items of the AIDAM were included in the analysis. The
distribution of all the variables was examined for normality. Construct validity and reliability
was examined through a polytomous Rasch model using Winsteps software (Rasch measurement
software version 3.74 Beaverton, Oregon). The Rasch model is based on item response theory
and commonly used in psychometric analysis of survey data. The Rasch model was used to
determine model fit because it postulates that several items are indirect measures of a single
underlying attitude or trait (dietary acculturation behavior) that cannot be observed directly. This
approach therefore provided information on how well the items on the instrument work to
measure dietary acculturation. Based on this model, the probability of the response to a certain
item on the instrument depends on the degree to which the person possesses the trait and the
degree to which the test item measured the underlying trait, both on a linear continuum.

82

The Rasch model is based on the assumption that the data is unidimensional, the response of an
individual for one item does not affect the responses to other items (local independence),
monotonicity of the latent trait, and non-intersecting Item response functions (Iramaneerat et al.,
2007). The rationale for using the Rasch model for this particular study is to create interval
scores from the ordinal Likert scales, to eliminate items that do not fit the unidimensional
construct, and to be able to calculate the total score even when some items are incomplete
(however, in order to conduct and interpret regression analysis we eliminated missing responses
for our study). These advantages of the Rasch model enable improved scoring and interpretation
of the dietary acculturation measure.

The infit (inlier-sensitive fit) and outfit (outlier-sensitive fit) are fit statistics in the Rasch model,
which are indicative of how accurately the data fits this model. The infit and outfit are examined
using the mean square (MNSQ) and standardized fit statistics (z scores) (Linacre, 2002). A
MNSQ value of 1.0 is considered ideal since values below 1.0 or above 1.0 are considered as
either too predictable or unpredictable, respectively. An optimum MNSQ range of 0.5 – 1.5 is
suggested by Linacre for Rasch measurement models (Linacre, 2002). Similarly, standardized fit
statistics (z scores) are t-tests to confirm model fit. A negative value indicates that the data is too
predictable while a positive value is indicative of a lack of predictability (Linacre, 2002).

Besides using multiple indicators of the same construct (dietary acculturation) in one survey,
validity was also determined by using external survey data. Correlations between the dietary
acculturation (AIDAM) score, the AI-FFQ and the NI-FFQ scores were examined to determine if
there was an association between the two measures. Additionally, we conducted linear regression

83

analysis with the Rasch person score (an estimated dietary acculturation score for each person
produced by the Rasch analysis) as the outcome and the AI-FFQ and NI-FFQ scores as
predictors after controlling for sociodemographic variables.

Results
Sample Characteristics
Table 5 shows the sample characteristics. Of the 191 participants, about one-third of the
participants were from California, New Jersey, Texas, and Illinois. Participants’ age ranged from
21-89 with a mean and standard deviation of 43.46 and 14.7, respectively. The mean duration of
stay in the U.S. was 19 years (standard deviation 13.8, range 2-62 years). There were nearly
equal numbers of males and females. Three-fourths of the participants were Hindus with the
remaining participants comprised of Muslims, Christians, Sikhs, Jains, Zoroastrians and atheists.
About 60% of the sample had a master’s degree or higher and 60% worked in a fulltime job.

More than two-thirds of the sample had an annual household income equal to or above $75,000
from all sources. Eighty percent of the participants were currently married and 40% spoke an
Asian Indian language most of the time at home. About three fourths of the sample were either
U.S. citizens or had acquired permanent residency. The AIDAM score of participants ranged
from 1.52 – 4.18 (possible score range 1.0-5.0) with a mean score of 2.8 and standard deviation
of 0.37. We did not see a significant difference in the AIDAM scores between males (mean:
AIDAM 2.76+0.39) and females (mean: AIDAM 2.84+0.35). Out of a possible score between 0100, participants had scored a mean of 50.12 (standard deviation 14.98) for the Indian FFQ and
37.91 (standard deviation 13.75) for the non-Indian FFQ items.
84

Table 5. Sample characteristics (n=191)

Age (years)
Duration of stay in the US
Rasch person measure of dietary acculturation trait
AIDAM score (50 items – possible score 1-5)
AI-FFQ score (25 items – possible score: 0-100)
NI-FFQ score (25 items – possible score: 0-100)
Gender

Male
Female
Religion
Hindu
Other (Muslim, Christian, Sikh,
Jain, Zorastrian, Aethist)
Educational level
High school or bachelor’s degree
>Masters
Employment
Employed full time
Other (employed part time, home
maker/ unemployed/ selfemployed, retired, student)
Annual household <$75,000
income
>$75,000
Marital status
Currently married
Other (single, divorced, widowed,
dating, partnered)
Language spoken
Mostly Indian
at home
Indian and English equally
Mostly English
US Citizens and permanent
Residency
residents
Work/student/ dependent visa
* 3 participants did not disclose income

Mean+SD; range
43.46+14.7 (21-89)
19.06+13.8 (2-62)
-0.27+0.45 (-2.08 – 1.51)
2.8+0.37 (1.52 – 4.18)
50.12+14.98 (0-82)
37.91+13.75 (0-75)
n (%)
92 (48.2)
99 (51.8)
148 (77.5)
43 (22.5)
78 (40.8)
113 (59.2)
116 (60.7)
75 (39.3)

61 (31.9)
127 (66.5)
153 (80.1)
38 (19.9)
78 (40.8)
77 (40.3)
36 (18.8)
145 (75.9)
46 (24.1)

AIDAM: Model fit, reliability and validity
The Rasch analysis determined the spread of item difficulty and person ability estimates for the
AIDAM. In figure 3, the left side of the map shows participant data. Each # is equal to 3
participants and ‘.’ is equal to 1 participant. Participants with a lower tendency to acculturate are
located on the bottom of the map while those with an increased tendency are situated at the top.
85

Figure 3. Person/item map for the 50 item Asian Indian Dietary Acculturation Measure
(AIDAM)
<more>|<rare>
2
+
|
|
. |
|
| DA20 DA35
|T
1
+ DA01 DA07 DA22
| DA03
| DA08 DA28 DA37
. T|S DA45 DA50
.# |
.### | DA10 DA26 DA48
.#### S| DA05 DA12_R DA18 DA30 DA32 DA39 DA44_R
0 .######## +M DA09_R DA14 DA40_R DA41
############# | DA06_R DA11_R DA15 DA29_R DA47_R
.############ M| DA04_R DA16 DA24 DA43 DA46
#### | DA02_R DA13_R DA17 DA19_R DA27_R DA31_R DA34_R
.##### |S DA42_R DA51_R
.### S| DA23_R DA25_R
. | DA33_R DA38_R
-1
. + DA36_R
.## T|T DA21_R
. |
|
. |
. |
. |
-2
+
. |
|
|
|
|
|
-3
+
<less>|<frequ>

Items are denoted by DA followed by the item number on the right side. On the left the # denotes
subjects, each # represents 3 subjects and ‘.’ represents one subject. The items are placed based
on their degree of difficulty to measure dietary acculturation and the persons are placed on their
degree of ability to acculturate. Participants with lower tendency to acculturate are on the bottom
of the map. Items with more difficulty are placed on the top and those that are easy are on the
bottom. The scale is in logit units 2 to -3.
86

Similarly, the AIDAM items are depicted on the right side of the map with increasing order of
difficulty from the bottom to top. Items at the bottom are easier to achieve while those at the top
are difficult to achieve in terms of dietary acculturation. The scale is in logit units 2 to -3.

Tables 6 shows all the 50 items that comprise the AIDAM and the Rasch fit statistics for the
individual items. The root mean square error over all the items is 0.08 and the item reliability is
0.98 (item separation=7.35) indicating stability of the item estimate. Person reliability is 0.88
(person separation=2.76). Where value of 2 is recommended for person separation; our sample
showed a value greater than 2 indicating good reliability (Gothwal et al., 2009). The root mean
square error over all the persons is 0.15.

Four items are out of the 5 – 1.5 MNSQ range. However, three of those items are within MNSQ
1.6, and hence considered as important for the instrument to be comprehensive. We excluded one
item since the infit and outfit MNSQ are extremely out of range (I strictly do not eat certain
foods because they are not allowed in my religion – infit MNSQ 1.82 and ZSTD 7.5; outfit
MNSQ 1.93 and ZSTD 8.3). We repeated the analysis after excluding this item. The infit and
outfit MNSQ of the other three items (items 39, 43, and 46 in table 6) are now within 1.61. Thus,
a MNSQ range of 0.58 – 1.61 was used to finalize the AIDAM items.

87

Table 6: Descriptives and Rasch fit statistics of the Asian Indian Dietary Acculturation Measure (AIDAM) (n=191)

#

Items

Mean+sd

1
2
3
4
5
6
7
8

I/or the people who I live with eat Indian foods often
I or the people who I live with eat non-Indian foods often
I present Indian foods to social gatherings or when I invite people
I present non-Indian foods to social gatherings or when I invite people
I prefer to eat Indian foods at my school/ workplace
I prefer to eat non-Indian foods at my school/ workplace
I often eat Indian foods when I am with Indians
I like to introduce Indian foods to non-Indians
I changed my eating habits in the U.S. to eat like everyone else in the
U.S.
I consider most of the Indian foods as healthy
I consider most of the non-Indian foods as healthy
I do not eat the Indian type of diet on most of the days
I eat healthier foods in the U.S. compared to the foods I would eat if I
were in India
I eat the same size portions of food in the U.S. as I would typically eat if I
were in India
I eat the same amount of starchy foods in the U.S. as I would typically eat
if I were in India
I eat the same amount of sweet foods in the U.S. as I would typically eat
if I were in India
I eat the same amount of oily/ fried foods in the U.S. as I would typically
eat if I were in India
I try Indian foods that I see on the television and Internet

1.91+0.92
3.18+1.13
2.07+0.87
3.02+0.97
2.66+1.09
2.98+1.06
1.92+0.86
2.17+0.92
2.83+1.07

MNSQ
infit
(ZSTD)
0.89 (-1.1)
1.01 (0.1)
0.74 (-2.9)
0.74 (-3.1)
0.90 (-1.2)
0.83 (-1.9)
0.86 (-1.4)
1.08 (0.8)
0.92 (-0.9)

2.49+0.99
2.87+0.85
2.63+1.02
3.16+1.01

0.96 (-0.5)
0.81 (-2.2)
0.82 (-2.1)
1.25 (2.6)

0.98 (-0.2)
0.85 (-1.8)
0.82 (-2.1)
1.29 (2.8)

0.33 (.08)
-0.08 (.08)
0.17 (.08)
-0.40 (.08)

2.80+1.02

1.10 (1.2)

1.27 (2.8)

0.00 (.08)

2.87+0.95

0.93 (-0.7)

1.08 (0.9)

-0.08 (.08)

3.11+0.96

1.16 (1.7)

1.27 (2.8)

-0.34 (.08)

3.23+0.93

1.11 (1.2)

1.18 (1.9)

-0.48 (.08)

2.66+1.01

1.09 (1.0)

1.15 (1.6)

0.14 (.08)

9
10
11
12
13
14
15
16
17
18

88

MNSQ
outfit
(ZSTD)
0.85 (-1.5)
1.01 (0.1)
0.72 (-3.1)
0.74 (-3.1)
0.89 (-1.2)
0.84 (-1.8)
0.86 (-1.4)
1.45 (4.1)
0.94 (-0.6)

Item
Measure
(SE)
1.06 (0.09)
-0.42 (.08)
0.84 (.08)
-0.25(.08)
0.14 (.08)
-0.21 (.08)
1.05 (.09)
0.71 (.08)
-0.04 (.08)

Table 6 (cont’d).

#

Items

Mean+sd

19
20
21
22
23
24
25
26
27
28
29
30
31
32
33

I try non-Indian foods that I see on the television and Internet
I enjoy eating Indian foods
I enjoy eating non-Indian foods
I find Indian foods to be very filling and satisfying
I find non-Indian foods to be very filling and satisfying
I prefer Indian foods for breakfast most of the time
I prefer non-Indian foods for breakfast most of the time
I prefer Indian foods for lunch most of the time
I prefer non-Indian foods for lunch most of the time
I prefer Indian foods for dinner most of the time
I prefer non-Indian foods for dinner most of the time
I prefer Indian foods for a snack most of the time
I prefer non-Indian foods for a snack most of the time
I like to eat at Indian restaurants in the place where I live
I like to eat at non-Indian restaurants in the place where I live
I eat out more often in the U.S. when compared to how I would eat in
India
I/ or the people who I live with know how to cook Indian foods
I/ or the people who I live with know how to cook non-Indian foods
I/ or the people who I live with often find it easy to prepare Indian foods
at home
I/ or the people who I live with often find it easy to prepare non-Indian
foods at home

3.23+0.99
1.78+0.74
3.80+0.92
1.92+0.76
3.42+0.90
3.01+1.19
3.42+1.00
2.57+1.04
3.14+0.86
2.22+0.94
2.96+0.90
2.67+0.94
3.19+0.83
2.62+1.04
3.58+0.88
3.23+1.09

MNSQ
infit
(ZSTD)
1.04 (0.5)
0.78 (-2.2)
0.96 (-0.4)
0.72 (-3.0)
0.73 (-3.2)
1.19 (2.0)
0.96 (-0.4)
0.82 (-2.1)
0.58 (-5.5)
0.74 (-3.1)
0.64 (-4.7)
0.71 (-4.3)
0.66 (-3.9)
1.03 (0.4)
0.75 (-2.8)
1.23 (2.4)

1.81+0.85
3.69+0.96
2.13+1.00

0.93 (-0.6)
0.99 (-0.1)
0.97 (-0.2)

0.88 (-1.2)
0.97 (-0.2)
0.96 (-0.4)

1.22 (.09)
-1.02(.08)
0.76 (.08)

3.57+0.94

0.92 (-0.9)

0.90 (-1.1)

-0.87 (.08)

34
35
36
37
38

89

MNSQ
outfit
(ZSTD)
1.07 (0.8)
0.75 (-2.5)
0.94 (-0.6)
0.71 (-3.1)
0.73 (-3.2)
1.20 (2.1)
0.96 (-0.4)
0.82 (-2.0)
0.58 (-5.4)
0.73 (-3.0)
0.64 (-4.6)
0.74 (-3.2)
0.66 (-4.2)
1.04 (0.4)
0.73 (-3.0)
1.26 (2.6)

-0.48 (.08)
1.26 (.09)
-1.16 (.08)
1.04 (.09)
-0.69 (.08)
-0.24 (.08)
-0.69 (.08)
0.25 (.08)
-0.38 (.08)
0.65 (.08)
-0.18 (.08)
0.13 (.08)
-0.44 (.08)
0.19 (.07)
-0.89 (.08)
-0.47 (.08)

Item
Measure

Table 6 (cont’d).

#
39
40
41
42
43
44
45
46
47
48
49
50

Items

Mean+sd

I/ or the people who I live with make Indian foods in large quantities and
store them for later use
I/ or the people who I live with make non-Indian foods in large quantities
and store them for later use
I often pick up Indian foods from stores/ restaurants when I/or the people
who I live with do not have time to cook
I often pick up non-Indian foods from stores/ restaurants when I/or the
people who I live with do not have time to cook
I have people who can make Indian foods for me when I/or the people
who I live with do not have time to cook
I have people who can make non-Indian foods for me when I/or the
people who I live with do not have time to cook
I am able to get all the varieties of Indian foods/ produce in the store
where I shop
I often buy packaged and ready to make Indian foods
I often buy packaged and ready to make non-Indian foods
I practice all the food-related beliefs of my religion in the US
I celebrate Indian festivals by eating specialty foods for the occasion
I celebrate non-Indian festivals by eating specialty foods for the occasion

2.69+1.20

MNSQ
infit
(ZSTD)
1.50 (4.9)

2.76+1.08

1.26 (2.7)

1.29 (3.0)

0.03 (.08)

2.84+1.15

1.31 (3.2)

1.33 (3.4)

-0.05 (.08)

3.28+1.02

1.01 (0.2)

1.03 (0.3)

-0.54 (.08)

3.10+1.21

1.61 (5.7)

1.61 (5.7)

-0.33 (.08)

2.62+1.10

1.13 (1.4)

1.12 (1.3)

0.19 (.08)

2.32+1.07

1.17 (1.8)

1.17 (1.8)

0.53 (.08)

3.10+1.14
2.86+1.10
2.53+1.20
2.29+1.09
3.27+1.03

1.52 (5.0)
1.18 (1.9)
1.36 (3.7)
1.14 (1.5)
1.01 (0.1)

1.59 (5.5)
1.18 (2.0)
1.36 (3.6)
1.17 (1.7)
1.02 (0.2)

-0.33 (.08)
-0.08 (.08)
0.29 (.08)
0.56 (.08)
-0.52 (.08)

90

MNSQ
outfit
(ZSTD)
1.61 (5.8)

Item
Measure
0.11 (.08)

Correlation between AIDAM and AI-FFQ and NI-FFQ scores
AI-FFQ and NI-FFQ scores were correlated with the AIDAM scores. The dietary acculturation
score was negatively correlated with the AI-FFQ food score (r=-.432, p<.001) and positively
(r=.265, p<.001) associated with the NI-FFQ food score. Although the strength of the
correlations was mediocre, since AIDAM measured Asian Indian food practices at the lower end
and non-Indian food practices at the higher end, a negative correlation with AI-FFQ and a
positive correlation with the NI-FFQ scores provide promising evidence for the validity of the
dietary acculturation instrument.

Relationship of AIDAM with participant sociodemographic characteristics and AI-FFQ
and NI-FFQ scores
Linear regression analysis was first conducted to examine the sociodemographic predictors of
dietary acculturation in our sample with the Rasch person score as the outcome (table 7). The
predictor variables were participant age, male gender (vs. females), duration in the U.S., English
language spoken at home (vs. Asian Indian and bilingual), Hinduism (vs. other religions),
currently married (vs. single, partnered, divorced, separated, and widowed), having a master’s
degree or higher (vs. high school or bachelor’s degree), employed fulltime (vs. part-time, retired,
student, and homemaker), annual household income from all sources >$75,000 (vs. <$75,000),
and U.S. citizens or permanent residents. (vs. those with work, student or dependent visas).

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Table 7. Sociodemographic predictors of dietary acculturation as measured by Asian Indian Dietary Acculturation Measure (AIDAM)
Model 1
Model 2
Sociodemographic
Sociodemographic
predictors of dietary predictors of dietary
acculturation
acculturation with
(n=188)
Asian Indian and
non-Indian FFQ
scores (n=161)
B
-.027
-.008
-.044
.009
.226

SE
.146
.003
.069
.003
.065

p
.855
.010
.523
.011
.001

B
.058
-.007
-.015
.005
.124

SE
.140
.003
.053
.003
.050

Model 3
Sociodemographic
predictors of
dietary
acculturation with
NI-FFQ scores
(n=168)

p
B
.681 -.319
.008 -.007
.770 -.009
.070 .009
.015 .183

SE
.151
.003
.060
.003
.057

Model 4
Sociodemographic
predictors of dietary
acculturation with
AI-FFQ scores
(n=179)

p
B
.036 .386
.011 -.007
.879 -.062
.003 .004
.002 .205

SE
.168
.003
.067
.004
.063

p
.023
.029
.361
.262
.001

Constant
Age (years)
Males (vs. females)
Duration in the U.S. (years)
Mostly English or Indian and English
equally spoken at home (vs. mostly
Indian language)
Hindus (vs. others)
-.212 .076
.006 -.097 .059
.105 -.187 .066
.005 -.179 .076
.019
Currently married (vs. not married)
-.198 .080
.014 -.066 .062
.288 -.141 .070
.046 -.130 .078
.097
Education >Master’s (vs. <master’s
-.010 .064
.878 -.032 .050
.514 .007 .057
.907 -.180 .062
.769
degree)
Employed fulltime (vs. others)
.023 .073
.753 -.004 .056
.938 .021 .064
.738 .007 .071
.924
Annual household income >$75,000
.104 .071
.142
.143 .055
.010 .112 .063
.078 .108 .069
.118
(vs. <$75,000)
U.S. citizens and permanent residents
.107 .087
.220
.047 .068
.486 .026 .078
.736 .130 .084
.123
(vs. those with work, student, and
dependent visas)
NI-FFQ score
.014 .002 <.001 .007 .002 <.001
AI-FFQ score
-.014 .002 <.001
-.009 .002
<.001
.19 (p =<.001)
.45 (p =<.001)
.23 (p =<.001)
.28 (p =<.001)
Linear regression adjusted R2
Outcome: Rasch person measure, scale range: -0.27+0.45 (-2.08 – 1.51)
AI-FFQ (Asian Indian food frequency questions) and NI-FFQ (Non-Indian food frequency questions) scale range: 0-100
92

Model 1 with only the sociodemographic variables explained 19% of the variance in dietary
acculturation (p<.001). The dietary acculturation score decreased as age of the participants
increased (b=-.008, p=.010), if participants were Hindus compared to other religions (b=-.212,
p=.006) or if participants were currently married compared to those who were not married
(single, partnered, widowed or divorced) (b=-.198, p=.014). On the other hand dietary
acculturation increased with increasing duration in the U.S. (b=.009, p=.011) or if participants
spoke mostly English/an Asian Indian language and English equally compared to those who
mostly spoke an Asian Indian language at home (b=.226, p=.001).

Controlling for the sociodemographic predictors, we added the AI-FFQ and the NI-FFQ scores in
the model in an effort to perform additional external validation of the AIDAM. This model
(model 2) explained 45% of the variance in the dietary acculturation score (p<.001). However
since the AI-FFQ and NI-FFQ scores were significantly correlated (r=0.470, p<.001), we
included NI-FFQ and AI-FFQ scores separately in models 3 and 4, respectively to omit
collinearity. Model 3 with the NI-FFQ score alone explained 23% of variance in the Rasch
person scores. Participant age (b=-.007, p=.011), duration in the U.S. (b=.009, p=.003), language
spoken at home (b=.183, p=.002), religion (b=-.187, p=.005), and marital status (b=-.141,
p=.046) remained significant predictors of dietary acculturation in model 2. In addition, the NIFFQ score was positively associated (.007, p<.001) with the participant dietary acculturation
score. Those who frequently consumed non-Indian foods were more likely to have higher dietary
acculturation, which is what we would expect. These findings validate both the AIDAM as well
as the food frequency measures that were used in this study.

93

Model 4 with the AI-FFQ score explained 28% of variance in the dietary acculturation score.
Younger age (b=-.007, p=.029), speaking mostly English/an Asian Indian language and English
equally compared to those who mostly spoke an Asian Indian language at home (b=.205,
p=.001), and participants following other religions compared to Hindus (b=-.179, p=.019) were
more likely to have higher dietary acculturation scores. AI-FFQ scores were negatively
associated with higher acculturation (b=-.009, p=<.001), indicating reduced consumption of
Asian Indian foods by those with higher acculturation, once again as we would expect.

Discussion
This study was conducted to validate the 50 item AIDAM, which was generated to assess the
dietary acculturation of Asian Indians. Our analysis showed that the AIDAM is a reliable and
valid measure of dietary acculturation when tested with a national sample of Asian Indians in the
U.S. In addition, the Rasch model used to determine construct validity and person reliability of
the instrument showed a good model fit with infit and outfit MNSQ statistics within the range of
0.58-0.61. We found the item estimates to be stable as indicated by the item statistics with a
person reliability of 0.88.

As one would expect, the AIDAM score was positively correlated with the non-Indian FFQ score
and negatively correlated with the Asian Indian FFQ score. The AI-FFQ and NI-FFQ scores
were significantly associated with the Rasch person measure in the linear regression analysis,
after controlling for sociodemographic variables. In a previous study on Korean Americans, low
acculturation has been shown to be associated with traditional food consumption, while
participants with high acculturation consumed foods available in the host country (Kim and

94

Chan, 2004). Therefore, correlating the AIDAM scores with the AI-FFQ and NI-FFQ and
conducting linear regression analysis provided additional evidence to support the validity of the
AIDAM in accurately capturing dietary acculturation behaviors.

Before we added the AI-FFQ and the NI-FFQ, the sociodemographic predictors that were
significantly associated with dietary acculturation were participants’ age, marital status, religion,
duration of stay in the U.S., and language primarily spoken at home. Age, duration of stay in the
host country, fluency in the host language, family composition have all been shown to influence
dietary acculturation in the conceptual model of dietary acculturation (Satia-Abouta et al., 2002).

Some studies that focused specifically on dietary acculturation of Asian Indians support the
notion of sociodemographic characteristics as important variables that contribute to dietary
choices. For example, in a study among Punjabi Sikhs in Canada, older participants preferred
Asian Indian foods while younger participants who were born in Canada preferred locally
available foods that were common in the host environment (Chapman et al., 2011). One possible
explanation is that most of the young people are second or third generation Asian Indians who
were either born in the host country or relocated at a very young age. Therefore increased
exposure to and consumption of non-Indian foods through peers and social networks might have
been major influencing factors.

Similarly, the primary language spoken by non-native individuals is also a good indicator of
acculturation in general as well as dietary acculturation as shown in several studies. One such
study on Peurto Rican adults utilized a language based acculturation scale, by evaluating the use

95

of English in activities such as watching television, reading newspapers/books, listening to the
radio, communicating with neighbors, friends, family and at work (Van Rompay et al., 2012).
The study showed that those with lower language acculturation were more likely to consume
traditional foods such as rice, beans, and starchy vegetables, which is consistent with our study
findings (Van Rompay et al., 2012).

Married individuals in our study were less likely to have higher dietary acculturation than those
who were single, partnered, separated or widowed. Married individuals with Asian Indian
spouses might be more likely to consume traditional foods. Out of the 38 participants in the
“other” category for marital status, 21 reported that they were single and had never been married
(mean age: 30.95+7.3 years). Therefore, it is likely that part of their meals could be consumed
outside home consisting of non-Indian foods. Married respondents were also more likely to
follow a vegetarian diet in a national study among Asian Indians in the U.S. (Misra et al., 2010a).
A study conducted in Canada showed that the consumption pattern was the same between men
and women in Asian Indian households; however the types of foods consumed were different for
parents and children (Varghese and Moore-Orr, 2002). This is likely the reason why marital
status was no longer a significant predictor when AI-FFQ and NI-FFQ were added to the model.
Therefore, family composition could be an additional determinant of the types of foods selected
in versus outside the home.

The fact that longer duration in the U.S. was associated with greater dietary acculturation could
have been linked to greater health awareness of non-native individuals resulting in the perception
that traditional Asian Indian cuisine is not healthful as shown in a previous study (Venkatesh et

96

al., 2013). In a study among South Asians (from Bangladesh, India, Nepal, Pakistan and Sri
Lanka) in Canada, improved health awareness through media, increased effort to purchase
nutritious foods, and greater reading and understanding of nutritional labels was evident in 60%
of the participants (Lesser et al., 2014). Longer duration in Canada was associated with increased
stir fry/BBQ, baking/grilling, and microwaving by South Asian participants, which are not
commonly practiced food preparation techniques in their home country and perceived as
healthier (Lesser et al., 2014). More specifically, from a healthier food choice perspective, in a
study among 73 Asian Indians in New York City Washington, a significant reduction in the
consumption of ghee (clarified butter), yogurt, butter, and milk was observed among participants
who had been in the U.S. for more than ten years when compared to ten years or less (Raj et al.,
1999).

In our sample those who were Hindus were less likely to obtain a higher score for dietary
acculturation. A study among Asian Indians in Canada showed the prevalence of vegetarianism
to be significantly higher among Hindus than others (Varghese and Moore-Orr, 2002). In
Hinduism, avoidance of beef/ all meat products is practiced with varying degrees of strictness
(Eliasi and Dwyer, 2002, Prashantham, 2008). In our study nearly 92% of vegetarians were
Hindus. Therefore more than half (52%) of the participants who were Hindus followed
vegetarianism. The Asian Indian vegetarian diet predominantly consists of cereals, legumes,
fruits, vegetables, and dairy (Koenig et al., 2012) and therefore they may have a tendency to
select foods that fall within these categories.

97

Furthermore, from our qualitative focus group discussions with Asian Indians in a mid-western
state, a few participants who were vegetarians expressed the limited availability of vegetarian
foods outside their home, being a limitation to the frequency of dining out (refer to chapter 4 manuscript 1). However, the practice of vegetarianism may be subject to change over a period of
time. A study showed that as duration in Canada increased Asian Indian participants exhibited a
shift from their traditional practice of vegetarianism (Varghese and Moore-Orr, 2002).
Furthermore, among Asian Indians in the U.S. higher acculturation has been shown to be
associated with a reduction in religiosity (Bharmal et al., 2013).

In the model with both the Ai-FFQ and NI-FFQ (model 2) higher income was a significant
predictor of higher dietary acculturation. Higher income was interestingly associated with greater
dietary acculturation scores in our sample. Higher income can increase the frequency of eating
out due to a reduced cost constraint. A study among Asian (born in China, Taiwan, Hong Kong,
Japan or Korea) adults who had stayed in the U.S. for at least three months, showed that when
dining out, participants often selected foods that were not traditional items, commonly consumed
in their home country (Pan et al., 1999). Thus higher income may have increased the likelihood
of exposure and experimentation with new foods.

In our study, sociodemographic variables such as participant age, marital status, religion,
duration in the U.S., and language primarily spoken at home were significant predictors of
dietary acculturation, all of which have been postulated to influence the dietary acculturation
process (Satia-Abouta et al., 2002). Moreover, our AIDAM tool, which measured traditional
behaviors at the lower end and non-Indian dietary behaviors at the higher end was positively

98

associated with the NI-FFQ. These findings provide additional evidence for the validity
exhibited in our Rasch analysis.

Strengths and limitations
Administration of the proposed instrument via a web-based platform allowed for a national
sample and hence generalizability of the findings is enhanced. Since it was a web-based, it was
cost efficient with ease of electronic transfer of data minimizing data entry. The survey was
constructed in such a manner that the participants were prompted for missing information hence
reducing missing data. The entire web-survey was constructed at eighth to ninth grade reading
level (AIDAM constructed at fifth to sixth grade level) in the U.S. to minimize readability issues.
The dietary acculturation instrument was designed with clear instructions, the scores of which
can be calculated using simple software or even manually.

Respondents had to have access to a computer and basic computer knowledge in order to
complete the survey, potentially excluding an important segment of the population. An
alternative for future studies using this instrument could be a paper-based version for individuals
who are not comfortable with computers. Screen readers can be provided if needed or a scribe
may also be able to assist individuals with disabilities. Options for translation of the instrument
for individuals who have difficulty in reading or interpreting the items in English would
therefore also widen the scope of potential participants. There is also much diversity in the
commonly spoken major Asian Indian languages, and for some with the least amount of
acculturation, language could be a barrier.

99

Conclusion
This study was conducted to validate a tool for the assessment of dietary acculturation, which
was shown to be a reliable and valid measure when tested with Asian Indian adults. The
instrument has been designed such that it is practical with a low respondent burden. The
instrument has value as a tool for use by nutrition researchers and/or health professionals
interested in ascertaining if and how dietary changes could be linked to a health problem,
especially, where there is a role for diet.

100

III. Manuscript 3 (specific aim 3)
The relationship between dietary acculturation and type 2 diabetes risk in a sample of
Asian Indians in the U.S.

Abstract
Background: Type 2 diabetes one of several diet-related diseases that are higher in Asian
Indians (17.4% - 29%) than the general population (8.4%) in the U.S. One potential risk factor is
poor dietary quality, which may be associated with dietary acculturation.
Objective: To examine the relationship between dietary acculturation of Asian Indians in the
U.S. and their future risk for type 2 diabetes.
Methods: A validated Asian Indian Dietary Acculturation Measure (AIDAM) and the Finnish
Diabetes Risk Score (FINDRISC) were completed by 153 Asian Indians in the U.S. via a crosssectional web-survey. The AIDAM score was dichotomized as Asian Indian-oriented (AIO)
(AIDAM<2.8) and Non-Indian oriented (NIO) (AIDAM>2.8 ) using the AIDAM sample mean.
Correlations and relative risk ratios were used to examine the association between AIDAM and
FINDRISC.
Results: The mean and median AIDAM score for the sample was 2.8. AIO participants indulged
in at least 30 minutes of physical activity per day (76.5% vs. 56.5% in NIO) and reported daily
consumption of vegetables and fruits/berries (95.6% vs. 81.2% in NIO) compared to NIO
participants. A significantly larger proportion of NIO participants (44.7%) had higher
FINDRISC scores (scores 7-26) compared to the AIO group (27.9%) (p=.024), and also had
increased relative predictive risk for type 2 diabetes (relative risk ratio=1.6).

101

Conclusion: Our study showed a positive association between dietary acculturation and diabetes
risk among Asian Indians in the U.S. These findings highlight the importance of including
dietary behaviors as well as dietary acculturation in non-native groups especially Asian Indians
when investigating type 2 diabetes risk factors and treatment.

Introduction
Asian Indians constitute about 1% of the U.S. population with growing numbers (U.S. Census
Bureau, 2012). Asian Indians in the U.S. have a high prevalence of diet-related disease in
general, but especially type 2 diabetes (Balasubramanyam et al., 2008, Kanaya et al., 2010,
Misra et al., 2010b, Rajpathak et al., 2010, Venkataraman et al., 2004, Wu et al., 2012). The rate
(17.4% - 29%) was alarmingly higher than Native American adults (14.9%) (Harjo et al., 2011)
and non-Hispanic blacks (13.1%), Mexican Americans (8.7%), and non-Hispanic whites (7.4%)
based on data from the National Health and Nutrition Examination Survey (NHANES) 20052010 (Selvin et al., 2014).

Recent studies have shown the prevalence of diabetes among Asian Indians in the U.S. to range
from 17.4% to as high as 29% (Balasubramanyam et al., 2008, Kanaya et al., 2010, Misra et al.,
2010b, Rajpathak et al., 2010, Venkataraman et al., 2004, Wu et al., 2012). In addition 35% fall
in the prediabetes stage (Kanaya et al., 2010, Misra et al., 2010b). Globally India has the highest
number of individuals with diabetes (31.7 million in 2000), which is projected to more than
double by 2030 (79.4 million by 2030) (Wild et al., 2004). Therefore risk for this disease in this
vulnerable population is especially high.

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Furthermore, in studies conducted in the U.S., Asian Indians had the highest odds of type 2
diabetes than the other ethnic groups compared. Asian Indians/ South Asians were two to six
time more likely to have type 2 diabetes than whites, thrice as likely as Latinos, twice as likely
as African Americans, and two to three times more likely than Chinese (Kanaya et al., 2010, Lee
et al., 2011, Mohanty et al., 2005, Oza-Frank et al., 2009, Rajpathak et al., 2010).

Similar to the trends in U.S., a higher prevalence of type 2 diabetes than the host population has
been documented among Asian Indians/ South Asians (individuals from India, Pakistan,
Bangladesh, and Sri Lanka) in other countries such as the United Kingdom (11.0% in South
Asians 11.0% vs. 8.0% in blacks and 3.5% in whites), Canada (6.2% in South Asians vs. 2.2% in
Caucasians), Singapore (12.8% in Asian Indians vs. 6.0% in Chinese and 9.0% in Malays),
Mauritius (12.8% in Asian Indians vs. 11.5% in Creoles), Fiji (11.9% in Asian Indians vs. 5.3%
in Melanesians), Norway (20.9% in South Asians vs. 4.4% in Westerners), Trinidad (20.5% in
Asian Indians vs. 12.5% in Africans), and South Africa (10.4% in Asian Indians vs. 3.6% in
Africans) (Anand et al., 2000, Beckles et al., 1986, Dowse et al., 1990, Dreyer et al., 2009,
Marine et al., 1969, Yeo et al., 2006, Zimmet et al., 1983). Furthermore, the prevalence of type 2
diabetes among Asian Indians who relocated to these countries is also higher than the diabetes
prevalence in India (7.3% urban and 3.1% rural) (Mohan et al., 2008).

According to the American Diabetes Association, the following are deemed established risk
factors for type 2 diabetes: obesity, sedentary lifestyle, race ethnicity (African American, Latino,
Native American, Asian Americans and Pacific Islanders), first-degree relatives with diabetes,
hypertension, impaired glucose tolerance/fasting glucose, abnormal lipid profiles, history of

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gestational diabetes or delivery of macrosomic baby, polycystic ovary syndrome, hemoglobin
A1c level>5.7, and other clinical conditions associated with insulin resistance such as acanthosis
nigricans (American Diabetes Association, 2014). It is a widely accepted fact that lifestyle
changes due to urbanization and westernization are important potentially influential factors for
the rising prevalence of type 2 diabetes and other noncommunicable diseases among ethnic
groups who also have increased genetic susceptibility to type 2 diabetes, such as Asian Indians
(Misra and Khurana, 2011).

Similarly, adaptation to the host country’s practices (acculturation) can also negatively influence
lifestyle behaviors and subsequently increase the risk factors for diet related diseases (Huang et
al., 1996, Kandula et al., 2008). However, this notion may not be applicable to individuals of all
ethnic groups as retaining one’s cultural practices has been also shown to be associated with
greater risk for type 2 diabetes in studies among Arabs and Hispanics (Jaber et al., 2003,
Mainous et al., 2006).

Most of these studies did not focus specifically on dietary acculturation (adaptation to host
countries dietary practices). An important lifestyle factor that contributes to the development of
type 2 diabetes is dietary behaviors (Hu, 2011). Social and economic factors could lead to shifts
in dietary behaviors such as increased consumption of animal products, increased consumption
of refined foods, and increased accessibility and affordability to high calorie foods not often
previously consumed (Hu, 2011). In a study among 143 Asian Indian participants in Texas, more
than half of the participants consumed a diet high in fat, saturated fat, cholesterol, and sugar/
sweets (Balasubramanyam et al., 2008). A diet rich in red meat, processed meat, French fries,

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high-fat dairy products, refined grains, and sweets and desserts has been shown to be associated
with type 2 diabetes risk, while increased consumption of vegetables, fruit, fish, poultry and
whole grains tends to have a preventative effect (van Dam et al., 2002).

In the Finnish Diabetes Prevention Study, 522 overweight individuals with impaired glucose
tolerance were randomly assigned into either an intervention group that received individualized
counseling to reduce body weight, total fat, saturated fat, and to increase fiber and physical
activity, or a control group that received general oral and written information about diet and
physical activity at every visit. The intervention group achieved greater weight loss at the end of
the first year, the average of which was four times more than the control group (intervention 4.2
kg vs control 0.8 kg). The cumulative incidence of diabetes after 4 years was 11% and 23% in
the intervention and the control groups, respectively, which is a 58 percent reduced risk of
diabetes due to the intervention (Lindström et al., 2003, Tuomilehto et al., 2001).

Type 2 diabetes also increases the cost burden since it has been shown to triple the medical cost
compared to those without diabetes (Trogdon and Hylands, 2008). Screening and early detection
is therefore imperative to capture high risk individuals and those with undiagnosed diabetes
(Pratley, 2013). The National Institute for Health and Clinical Excellence (NICE) based in the
United Kingdom, recommends diabetes risk scores as the first stage for diabetes risk
identification, followed by the second stage, which is the clinical laboratory assessment
(Chatterton et al., 2012). Diabetes risk scores may not provide a perfect estimate of the future
risk for diabetes, however, they can serve as a good cost-effective prediction tool to take
preventive measures (Noble et al., 2011).

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The Finnish Diabetes Risk Score (FINDRISC) is a diabetes screening tool that predicts the risk
of developing diabetes in 10 years (Lindström and Tuomilehto, 2003). The FINDRISC is based
on anthropometric and lifestyle behaviors in addition to the symptoms exhibited and
medical/family history of subjects (Lindström and Tuomilehto, 2003). The FINDRISC is a costeffective and a globally used screener in community based studies used not only to predict the
risk for diabetes but also for insulin resistance (Lindström and Tuomilehto, 2003, Schwarz et al.,
2009b). This tool has especially been shown to be useful for those who can benefit from
intensive lifestyle interventions for type 2 diabetes (Lindström et al., 2008). The screener has a
sensitivity of 78-81% and specificity of 76-77% in the baseline and the validation cohorts
(Lindström and Tuomilehto, 2003). Sensitivity and specificity of a screening tool are critical for
the identification of true and false positives, respectively. A review of the available diabetes risk
scores conducted by Schwarz et al. concluded that the FINDRISC is the most accurate diabetes
risk prediction tool, which is widely used in primary prevention programs (Schwarz et al.,
2009a).

The high prevalence of type 2 diabetes among Asian Indians in the U.S. and the likelihood of a
possible shift in the dietary pattern upon relocation warrant investigation of the relation between
the level of dietary acculturation and future diabetes risk in this target group. Therefore, we
conducted a web-survey to collect data from a nationally representative sample of Asian Indians
in the U.S. to examine the relationship between dietary acculturation and the future risk for type
2 diabetes in this target group. The majority of the studies conducted on Asian Indians in the U.S.
is either confined to a specific region in the U.S. or are targeted to individuals who are from a

106

specific region in India. Our study targeted a nationally representative population in the U.S.
who were from various regions in India.

Methods
Prior to study commencement Institutional Review Board approval was obtained from Michigan
State University. A cross-sectional web survey was administered to a national sample of 225
Asian Indian adults in the U.S. through Michigan State University Office for Survey Research
who used Qualtrics research suite, a program designed to conduct web-based survey research
(Qualtrics, 2009, Provo, Utah, USA. Version. 12,018). Qualtrics Research Suite used Research
Now group, Inc, a recognized market research company to recruit participants. A response rate
of 16% was achieved (1408 emails sent and 225 participants completed the survey). Out of the
225 who completed the web-survey, 162 participants had all the information required to calculate
a predictive diabetes risk score as well as a dietary acculturation score. Because we were
interested in future risk for diabetes, information about known diagnosed diabetes was solicited.
Those who indicated that they had the disease (n=9) were excluded. Therefore, we limited our
analysis to a final sample of 153 participants. The web-survey consisted of an informed consent,
participant sociodemographic information, the items of the Asian Indian Dietary Acculturation
Measure (AIDAM), and the FINDRISC predictive diabetes risk score items.

Asian Indian Dietary Acculturation Measure (AIDAM)
The 50 item AIDAM used in this study is a tool that was specifically developed for the
assessment of dietary acculturation of Asian Indians (refer to chapter 4 - manuscript 2). The
AIDAM was based on the conceptual model of dietary acculturation proposed by Satia-About a

107

(Satia-Abouta et al., 2002) and was developed from the themes generated using eight focus
group discussions with Asian Indian adults in a Midwestern state in the U.S. and a thorough
review of literature on measures of acculturation/ dietary acculturation.

The AIDAM was revised by ten registered dietitians/experts in nutrition or survey research,
pretested with 14 participants of Asian Indian origin, and validated with a national sample of 191
Asian Indian adults in the U.S. The item and person reliabilities obtained using the Rasch rating
scale model were 0.98 and 0.88, respectively. The items measured eight underlying themes that
may influence dietary acculturation behaviors, which are: social network (9 items); health and
nutrition (8 items); media (2 item); taste preferences (12 items); restaurants (3 items); food
preparation (10 items); food purchasing (3 items); and religious and cultural beliefs (3 items).

The AIDAM items are in the form of statements for which participants provided their level of
agreement on a five point Likert scale (1=strongly agree…5=strongly disagree). Dietary
acculturation is measured with traditional Asian Indian dietary practices at one end and western/
non-Indian practices on the other. The responses for all the items are added and divided by the
number of items to get a final score ranging from 1 to 5, where 1 indicates Asian Indian dietary
practices and 5 is indicative of non-Indian dietary practices.

The Finnish Diabetes Risk Score (FINDRISC)
The web-based survey requested information required to calculate total diabetes risk score of the
participants. Information included participants’ age, self-reported weight and height to calculate
Body Mass Index, self-reported waist circumference, physical activity, consumption of fruits and

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vegetables, history of antihypertensive medications, history of hyperglycemia, and presence of
family members with type 1 or type 2 diabetes. The eight items of the screener have different
scores contributing to the total risk score. The total diabetes risk scores could range from 0 to 26.
Scores are broadly categorized into the following five categories: lower than 7 (low risk – 1 in
100 will develop the disease), 7-11 (slightly elevated risk – 1 in 25 will develop the disease), 1214 (moderate risk – 1 in 6 will develop the disease), 15-20 (high risk – 1 in 3 will develop the
disease), and higher than 20 (very high risk – 1 in 2 will develop the disease).

Data analysis
All statistical analysis was conducted using the Statistical Package for Social Sciences (SPSS)
software (version 20.0, 2011, Chicago, Illinois, SPSS Inc.). After examining the descriptives, all
the variables were deemed normal. AIDAM and FINDRISC scores, which are continuous
variables, were correlated to examine the relationship in our sample. We dichotomized the
AIDAM score as Asian Indian-oriented (AIO) (AIDAM<2.8) and Non-Indian oriented (NIO)
(AIDAM>2.8 ). A cut point of 2.8 was chosen since it was both the mean and the median value
for the 153 participants. Similarly FINDRISC scores were dichotomized as low risk (scores 0-6)
and some risk (scores 7-26 - includes slightly elevated risk, moderate risk, high risk, and very
high risk). Chi square analysis was used to compare participants’ socio-demographic information
and their predictive diabetes risk score between AIO and NIO participants. Relative risk ratio
was used to examine the association between AIDAM and FINDRISC scores of participants.

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Results
Table 8. Participant characteristics (n=153)
AIO
(n=68)

NIO
(n=85)

p

Mean+SD
Age (years)
41.82+12.9 41.89+14.9 .08
No. members in the household
2.91+1.3
2.79+1.3
.96
Duration in the U.S. (years)
15.21+12.4 20.94+14.0 .08
FINDRISC score
5.51+4.5
7.11+4.8
.04
N(%)
Gender
Male
35 (51.5)
37 (43.5)
.21
Female
33 (48.5)
48 (56.5)
Language spoken at
Mostly English
5 (7.4)
21 (24.7)
.004
home
Indian and English
28 (41.2)
38 (44.7)
Equally
Mostly Indian
35 (51.5)
26 (30.6)
Religion
Hindu
59 (86.8)
62 (72.9)
.03
a
Other
9 (13.2)
23 (27.1)
Marital status
Currently married
59 (86.8)
64 (75.3)
.06
Currently not married
9 (13.2)
21 (24.7)
Employment
Employed full time
43 (63.2)
52 (61.2)
.46
b
Other
25 (36.8)
33 (38.8)
c
Annual household
<$75,000
18 (26.5)
28 (33.3)
.23
income
>$75,000
50 (73.5)
56 (66.7)
Residency
Citizens and permanent 43 (63.2)
70 (82.4)
residents
d
Other
25 (36.8)
15 (17.6)
.01
AIO: Asian Indian Oriented (AIDAM<2.8), NIO: Non-Indian Oriented (AIDAM>2.8)
a
Other = Christian, Muslim, Jain, and Sikh
b
Other=employed part time, homemaker, unemployed, retired, student, and self-employed
c
One participant did not disclose income
a
Other = work visa, student visa, and dependent visa

Sample characteristics
The sample characteristics of the 153 studied subjects are presented in Table 8. The sample
included 72 men and 81 women between 21 and 80 years. The mean dietary acculturation score
was 2.8+0.38 (range: 1.52 – 4.18). There were 68 and 85 participants in the AIO and NIO
groups, respectively. Mean age of the participants was 42 in both the groups. The mean duration

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in the U.S. was 15 years and 21 years in the AIO and NIO groups, respectively. Participants in
the AIO group were more likely to speak an Indian Language at home most of the time (p=.004).
The majority (n=123) of the participants were currently married of which fifty five participants
had one or more children under 18 years. A significantly larger proportion of AIO participants
were Hindus (86.8% vs. 72.9% in the NIO group) (p=.03). About two-thirds of the participants
were employed full time and had an annual household income >$75,000 from all sources. A
significantly larger proportion (82.4%) of NIO individuals were U.S. citizens or had acquired
permanent residency in the U.S. (p=.01). The mean FINDRISC scores were significantly lower
for the AIO (mean 5.5±4.5) than the NIO group (mean 7.11+4.8) (p=.04).

Participants’ FINDRISC scores
Table 9 shows the scores for the eight individual components of the FINDRISC that are
compared between AIO and NIO participants. The FINDRISC scores ranged from 0-22 with a
mean of 6.4±4.7 for the overall sample. More than one-third of the sample was overweight or
obese. The prevalence of overweight/obesity was 48.6% in men and 34.5% in women. However,
when taking into account the cut points for waist circumference, about two-thirds of participants
in both the groups were in the lowest category (64.7% in AIO and 65.9% in NIO). Asian Indians
in the AIO group were more likely to engage in at least 30 minutes of physical activity per day at
work, and/or during leisure time than NIO group (56.5%) (p=.008). Similarly 95.6% of the AIO
participants reported daily consumption of vegetables and fruits/berries compared to 81.2% in
the NIO group (p=.006). However, the fact that there were only three participants in the AIO
group who reported that they did not consume fruits and vegetables every day, is an important
consideration when interpreting the findings.

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Table 9. Finnish Diabetes Risk Score (FINDRISC) components by dietary acculturation level (n=153)

Age

<45 years (0 point)
45-54 years (2 points)
55-64 years (3 points)
>64 years (4 points)
Body Mass Index
<25 kg/m2 (0 point)
25-30 kg/m2 (1 point)
>30 kg/m2 (3 points)
Waist circumference
<94 cm (men); <80 cm (women) (0 point)
94-102 cm (men); 80-88 cm (women) (3 points)
>102 cm (men); >88 cm (women) (4 points)
At least 30 minutes of
Yes (0 point)
physical activity/ day
No (2 points)
Frequency of consumption of Every day (0 point)
vegetables, fruits or berries
Not every day (1 point)
Taken regular medications
No (0 point)
for high blood pressure
Yes (2 points)
Ever found to have high
No (0 point)
blood glucose
Yes (5 points)
Family/ relatives with
No (0 point)
diagnosed with diabetes
Yes: grandparent, aunt, uncle or first cousin (3 points)
Yes: parent, brother, sister or own child (5 points)
FINDRISC score
Low risk (scores 0-6)
Slightly elevated risk – very high risk (scores 7-26)
Chi-square analysis
AIO: Asian Indian Oriented (AIDAM<2.8), NIO: Non-Indian Oriented (AIDAM>2.8)

112

AIO
(n=68)
48 (70.6)
7 (10.3)
7 (10.3)
6 (8.8)
43 (63.2)
18 (26.5)
7 (10.3)
44 (64.7)
14 (20.6)
10 (14.7)
52 (76.5)
16 (23.5)
65 (95.6)
3 (4.4)
58 (85.3)
10 (14.7)
64 (94.1)
4 (5.9)
38 (55.9)
15 (22.1)
15 (22.1)
49 (72.1)
19 (27.9)

NIO
(n=85)
55 (64.7)
12 (14.1)
8 (9.4)
10 (11.8)
47 (55.3)
26 (30.6)
12 (14.1)
56 (65.9)
20 (23.5)
9 (10.6)
48 (56.5)
37 (43.5)
69 (81.2)
16 (18.8)
70 (82.4)
15 (17.6)
74 (87.1)
11 (12.9)
42 (49.4)
16 (18.8)
27 (31.8)
47 (55.3)
38 (44.7)

Total
(n=153)
103 (67.3)
19 (12.4)
15 (9.8)
16 (10.5)
90 (58.8)
44 (28.8)
19 (12.4)
100 (65.4)
34 (22.2)
19 (12.4)
100 (65.4)
53 (34.6)
134 (87.6)
19 (12.4)
128 (83.7)
25 (16.3)
138 (90.2)
15 (9.8)
80 (52.3)
31 (20.3)
42 (27.5)
96 (62.7)
57 (37.3)

p
.81

.59

.72

.008
.006
.40
.12
.41

.024

Nearly 16% of the participants were taking medications for high blood pressure on a regular
basis and about 10% denoted that they had a history of high blood glucose levels, either in a
health examination, during an illness, or during pregnancy for females. About half of the sample
had family members with diabetes, with 27.5% of the sample reporting an immediate family
member such as a parent, sibling, or child. A significantly larger proportion of AIO participants
(72% vs. 55% in NIO) had a low type 2 diabetes predictive risk score (p=.024). About one-fifth
of the overall sample had slightly elevated risk and 16.3% had moderate to very high risk.

Relation between FINDRISC and AIDAM
We looked at the bivariate correlation between dietary acculturation score and FINDRISC
diabetes risk score. Although a significant correlation was observed between the dietary
acculturation score and the FINDRISC diabetes risk score, the strength of the correlation was not
strong (r=.160; p=.048). However, on further analysis, the relative risk for type 2 diabetes was
1.6 times greater in the NIO group, which indicates a 60% increased disease risk in the NIO
relative to AIO group (table 10).

Table 10. The association (relative risk) between Asian Indian Dietary Acculturation Measure
(AIDAM) and Finnish Diabetes Risk Score (FINDRISC) (n = 153)

NIO

RR
1.600

95% CI
1.021 to 2.507

AIO

0.767

0.603 to 0.977

AIO: Asian Indian Oriented (AIDAM<2.8), NIO: Non-Indian Oriented (AIDAM>2.8)
FINDRISC scores: low risk 0-6, high risk 7-26
RR: relative risk, CI: confidence interval

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Discussion
The goal was to examine the relationship between dietary acculturation of Asian Indians and
their future risk for type 2 diabetes. A dietary acculturation tool (AIDAM) that was developed
and validated using a national sample of Asian Indian adults was used (refer to chapter 4 manuscript 2). In our sample, AIO individuals were more likely to be Hindu, speak in their
native language at home, to engage in at least 30 minutes of physical activity daily, to consume
vegetables and fruits/berries daily, and have lower FINDRISC scores. On the other hand, NIO
participants were more likely to be U.S. Citizens or permanent residents. Our study showed that
a larger proportion of NIO participants had an increased risk for type 2 diabetes. Furthermore,
the relative risk for developing type 2 diabetes was greater for NIO than AIO participants.
Therefore increased dietary acculturation appeared to be a risk factor for developing type 2
diabetes in the future.

Although our sample did not show a very high prevalence of hypertension and high blood
glucose concentration, other studies have shown these risk factors to be high among Asian
Indians in the U.S. (Baweja et al., 2004, Kanaya et al., 2010, Misra et al., 2010b, Venkataraman
et al., 2004). In a study among patients with prediabetes, participants with hypertension were
more likely to progress to type 2 diabetes in less than a year, which was associated with
increased health care utilization and associated cost (Francis et al., 2011).

Similarly, family history of diabetes is a major risk factor in the Asian Indian ethnic group as it
has been shown to be an independent predictor of type 2 diabetes. Among Asian Indians in the
U.S., nearly one in two members with type 2 diabetes have a family member affected by the

114

disease (Venkataraman et al., 2004). This association was supported in our findings given that
half of our sample had a family member with diagnosed type 2 diabetes. We also found that a
larger proportion of participants who had a family member with diabetes were also in the high
risk category for FINDRISC, which was significantly higher if it was an immediate family
member (71.4% vs. 16.2% if none in the family had diabetes) (p<.01). Besides the genetic risk
factors of Asian Indians for type 2 diabetes, the modifiable risk factors such as dietary intake and
physical activity should not be ignored, and should definitely include dietary acculturation.
Dietary behaviors have been shown to contribute to the development of type 2 diabetes, more
specifically consuming a diet rich in red meat, processed meat, high-fat dairy products, refined
grains, and sweets (van Dam et al., 2002).

The two components of the FINDRISC that were significantly different between AIO and NIO
groups were physical activity and fruit and vegetable consumption on a daily basis. In our
sample, consumption of fruit and vegetables on a daily basis was reported by 95% and 81% of
the participants in the AIO and NIO groups, respectively. It is encouraging to note that the
majority of participants in both the groups consumed fruits and vegetables every day. However,
the prevalence of fruit and vegetable consumption was higher among AIO participants. One
possible reason for this difference could be the presence of a significantly larger proportion of
Hindus in the AIO group.

In some or many cases, Hindus practice vegetarianism, which includes consumption of a plantbased diet that predominantly consists of fruits, vegetables, legumes and dairy products (Koenig
et al., 2012). In our study 79% of participants who were vegetarians were Hindus. The Asian

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Indian vegetarian diet may include foods that are cereals, legumes, fruits, vegetables, and dairy
(Gadgil et al., 2014). Consumption of a diet high in fruits and vegetables has been shown to be
protective of type 2 diabetes, and therefore adequacy of fruit and vegetable intake should be a
strong consideration for this target group (van Dam et al., 2002). Along with genetic
susceptibility to type 2 diabetes, behavioral risk factors such as a poor diet and physical
inactivity are equally important. Therefore positive dietary behavioral changes should be
emphasized more in research and practice settings (Bhopal, 2013, Mozaffarian et al., 2008).

In addition to fruit and vegetable consumption, the physical activity component of the
FINDRISC was also significantly different between the two AIDAM groups. The proportion of
participants who engaged in regular physical activity for at least 30 minutes a day at work,
and/or during leisure time was significantly higher among those in the AIO than NIO group. Our
data was supported by the fact that it has been shown that acculturation to the mainstream culture
could impact physical activity levels of individuals both positively and negatively (ChavezMartinez et al., 2010, Daniel and Wilbur, 2011).

Although about two-thirds of our study sample reported at least 30 minutes of daily physical
activity, a few studies conducted with Asian Indians in the U.S. have documented low levels of
physical activity in this target group (Misra et al., 2005, Balasubramanyam et al., 2008).
Furthermore, Asian Indians were less likely to engage in moderate/ vigorous physical activity
compared to non-Hispanic whites in the California Men’s Health Cohort Study (Ghai et al.,
2012). In a study conducted among 56 Asian Indians in the Bay area, a higher prevalence of
metabolic syndrome was documented among those with lower physical activity (Misra et al.,

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2005). It is therefore suggested that Asian Indians should engage in physical activity as a
preventive measure (Misra and Khurana, 2011).

Strengths and limitations
The indicators used in the FINDRISC tool have been shown to be a good predictor of type 2
diabetes among Asian Indians (Das et al., 2012). These indicators could also be used for the risk
prediction of other conditions such as metabolic syndrome and cardiovascular disease because
these conditions share similar risk factors such as age, gender, body mass index, waist
circumference, hypertension, and high blood glucose concentration. Therefore administration of
this single tool can be utilized for the risk prediction of a cluster of metabolic disorders. The high
sensitivity and specificity of the FINDRISC screener demonstrates its ability to capture
individuals who are truly at risk for diabetes and the exclusion of low-risk individuals.

For the calculation of FINDRISC scores, participants provided a self-report of their height,
weight, and waist circumference. Self-reported measures may not be as accurate as measured by
researchers trained in anthropometric measures. Moreover, estimates of Body Mass Index
obtained through self-reported measures could potentially be lower than that calculated from
measured height and weight. This could be due to participants underestimating or overestimating
their weight and height, respectively (Gorber et al., 2007). Therefore, it could be possible that the
participants’ BMI may have been higher if measured heights and weights were used for the
calculation. Our study also requested self-reported fruit and vegetable intake. It is possible that
over-reporting could be a factor. In the California Men’s Health Study Cohort, only one-third of
the Asian Indian participants consumed five servings of fruits and vegetables per day (Ghai et

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al., 2012). Therefore, these limitations should be a consideration when interpreting the findings
of this study.

In our study a large proportion of the sample had lower predictive risk for type 2 diabetes.
Although we calculated a predictive risk score, which is indicative of the risk for development of
type 2 diabetes in ten years, we expected the risk estimates to be consistent with type 2 diabetes
prevalence rates. A high prevalence of type 2 diabetes has been documented among Asian
Indians in the U.S. (17-29%) (Misra et al., 2010b, Kanaya et al., 2010, Venkataraman et al.,
2004). Asian Indians have strong genetic and other risk factors, not necessarily captured
comprehensively in FINDRISC. We had a relatively young sample (mean age 40 years), which
could have impacted our findings. The mean age of Asian Indians in most of the other studies
that investigated type 2 diabetes prevalence in the U.S. was over 50 years, which is a relatively
higher age group than our study (Balasubramanyam et al., 2008, Kanaya et al., 2010, Misra et al.,
2010b, Rajpathak et al., 2010, Venkataraman et al., 2004, Wu et al., 2012). In addition,
weighting of the risk factors in FINDRISC might be variable in different cultures. It is plausible
that although FINDRISC has merit in large community based studies, our findings may have
differed if used in conjunction with objective assessments in this vulnerable target group.

Conclusion
In our study higher dietary acculturation was associated with increased FINDRISC scores, which
is indicative of increased risk for type 2 diabetes in ten years. Furthermore, participants with
lower dietary acculturation were more likely to consume vegetables and fruits/berries and engage
in at least thirty minutes of physical activity on a daily basis. Health professionals could use this

118

information to advise Asian Indian individuals on preventive measures based on their current
risk factors and to educate them about healthy lifestyle behaviors.

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CHAPTER 5 - SUMMARY

I. Main findings
One primary area by which health status of those who move to another country is impacted is
nutrition. A major consideration is obtaining information about dietary changes, the quality of
the research instrument and its fit for the target population. The goal of this project was to
develop a culturally appropriate dietary change measurement instrument for use with Asian
Indians in the U.S. and potentially other countries to which Asian Indians relocate. The
qualitative findings from our focus group discussions provided important information relevant to
dietary changes of Asian Indians who relocate to the U.S. These factors collectively influenced
food selection and dining behaviors, and were linked to improved health awareness as well as
determining if, why and how non-Indian foods were included in the diet. These findings were
utilized for the development and validation of an Asian Indian dietary acculturation instrument.

The major outcome of this study was a quantitative measure of dietary acculturation that was
tested and determined to be reliable and valid for use with Asian Indians. Acculturation is an
underlying latent trait (unobservable) and hence attitudinal rating scales are appropriate measures
that can be employed (Yates, 2005). The psychometric analysis of the instrument showed that the
survey measure is practical to use, has the ability to produce reproducible results and accurately
measure the underlying construct (validity) when administered to the target population (item and
person reliabilities were 0.98 and 0.88, respectively).

Although cultural sensitivity of the instrument is the main focus, the instrument can also be a
common standardized measurement tool that can be used for comparisons with Asian Indians in

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India or adapted for other ethnic groups. Comparison of the dietary acculturation score with
participants’ diabetes risk score showed that adaptation of host country’s dietary practices by
Asian Indians may increase the likelihood of developing type 2 diabetes.

There are a limited number of reliable instruments for the evaluation of nutrition interventions,
that measure dietary acculturation behaviors specific for this population (Varghese and MooreOrr, 2002, Raj et al., 1999). This research was timely because such instruments are critically
needed in order to adequately assess dietary habits by integrating cultural preferences and for
developing and implementing strategies that promote the nutritional health of Asian Indians to
decrease the risk of diet-related chronic diseases.

The dietary acculturation instrument developed and validated in this study can be used in many
settings to improve the understanding of nutrition/health professionals about Asian Indian food
choices and preferences. Specifically, the use of this measure will allow health care/ nutrition
professionals to evaluate the dietary changes that Asian Indians may undergo in conjunction with
a change in the living environment. This measure will aid in the creation of new or tailoring of
existing intervention strategies to promote healthy dietary practices among Asian Indians and to
identify potential trends in the dietary patterns that could be used in supporting the establishment
of healthy dietary behaviors within Asian Indians.

Researchers should be aware of the regional differences in the dietary behaviors within India. A
study conducted in India showed that the cardiovascular mortality rate in India was correlated
with dietary intake in addition to the several genetic risk factors (Gupta et al., 2006). The overall

121

prevalence of overweight/ obesity (body mass index >25 kg/m2) was 12.7% with the highest
rates in Delhi and Punjab (>30%). This study showed huge variations in the types of foods
consumed and the nutrient composition of the diet among individuals in different states in India
(Gupta et al., 2006). Another study compared dietary intake of individuals from Delhi,
Trivandrum, and Mumbai, three cities in the north, south, and western regions in India,
respectively. The study showed that the primary and the secondary food patterns in Delhi were
“fruit-dairy” and “vegetable-pulses”; in Trivandrum was “pulses-rice” and “sweets-snacks”; and
in Mumbai was “fruit-vegetables” and “snacks-meat” (Daniel et al., 2011). Thus, this could be a
built-in limitation for studies investigating dietary behaviors/ patterns of Asian Indians
collectively from different regions.

Furthermore, it is important not to disregard the rapid westernization of the Asian Indian diet in
India due to lifestyle changes. Hence some of the shift in the diet that is observed among Asian
Indians in other countries could also happen among Asian Indians in India (Hu, 2011). Dietary
acculturation patterns among non-native individuals could therefore be a temporal topic since the
diets are constantly changing in both the native country as well as the host country. These facts
are key considerations when designing, implementing, and interpreting dietary acculturation
studies.

II. Future Directions
Collectively, the findings related to the specific aims of this research will make a significant
contribution to the literature by adding a validated dietary acculturation assessment tool and by
documenting factors associated with dietary acculturation from the perception of Asian Indians.

122

These findings will inform health professionals about Asian Indian food practices and will
provide a measure of the degree of dietary acculturation of Asian Indians.

Based on this work, a culturally competent intervention program targeted to Asian Indians can be
designed and tested to promote healthy nutrition in this population. When providing dietary
counseling for Asian Indians, health professionals should be aware of the cultural complexities,
dietary concerns, and trends in the Asian Indian diet and provide individualized care. Such
awareness can be achieved by the information obtained through our focus group study and using
a measure of dietary acculturation that is specific for Asian Indians. The dietary acculturation
instrument developed through this research can be administered as a web-based tool, and used
for large scale population-based studies and has the capacity to calculate scores using simple
software or even manually. This measure will allow future studies to compare and contrast risk
factors for chronic diseases based on degree of dietary acculturation of Asian Indians to host
country’s dietary practices, which would further clarify the role of dietary acculturation in the
prevalence of diet-related chronic diseases among Asian Indians.

III. Innovation
Traditional approaches to dealing with diet-related chronic diseases have focused on examination
of the association between the diet quality and the health outcome of interest. These methods
have however failed to capture the changes in the dietary behavior that occur as a result of a
change in the host environment. General acculturation measures that determine adaptation to a
new environment are also not comprehensive enough to evaluate the dietary change effects,
which might have health implications.

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This project is innovative because it combined the extent of adaptation to the host country and
the cultural, environmental, and psychosocial influences on dietary behaviors into a single
quantitative measure for dietary assessment in the Asian Indian population. Determination of the
initial psychometric properties of the instrument using the target population ensures reliable and
valid results when administered by future studies on Asian Indian population. The instrument
could be used in interventions aimed at reducing the severity and high prevalence of type 2
diabetes and other diet-related chronic diseases and subsequently improve the quality of life in
this population, which could produce savings in the cost of medical expenses.

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APPENDICES

125

Appendix 1 - IRB approval

126

Appendix 2 - Research flyer
Figure 4. Research flyer for focus group recruitment

127

Appendix 3 - Research participant informed consent form (A)
You are being asked to participate in a research project. Researchers are required to provide a consent
form to inform you about the study, to convey that participation is voluntary, to explain risks and benefits
of participation, and to empower you to make an informed decision. You should feel free to ask the
researchers any questions you may have.
Study title:

Assessment of Dietary Acculturation of Asian Indians: Instrument
Development and Validation

Researchers and
Titles:

Lorraine Weatherspoon PhD, RD
Associate Professor in Human Nutrition and Director,
Didactic Program in Dietetics
Sumathi Venkatesh M.S.
Doctoral Student in Human Nutrition

Department and
Institution:

Department of Food Science and Human Nutrition
Michigan State University

Contact Information
for L. Weatherspoon:

334 GM Trout Food Science Building
Michigan State University, East Lansing Michigan 48824-1224
Tel: 517-355-8474 ext 136
Email: weathe43@msu.edu

PURPOSE OF RESEARCH:
You are being asked to participate in a research study that will help us understand the dietary patterns,
food procurement, and food preparation of Asian Indian immigrants to the United States. You have been
selected as a possible participant in this study because you contacted the researcher and indicated interest
in participation in this research project. The investigators hope to learn how living in the United States of
America and other factors are related to the dietary patterns of Asian Indian adults. Your participation in
this entire study will take about 2 to 2.5 hours.
WHAT YOU WILL DO:
This study consists of three parts. First, you will complete a few general survey questions. This part will
take about 10 minutes. The second part will consist of an audio-recorded group discussion with 6 to 8
other Asian Indian participants, lasting about an hour. We will ask questions about how living in the
United States of America has influenced your dietary intake, food purchasing and food preparation
methods. This interview will include questions, which will help us to better understand how living in the
United States has influenced your eating habits. Thirdly, we will also need to call you on a different
occasion later in the week agreed upon with you, if you do not mind giving us your phone number, to ask
you questions about the typical foods that you eat for a 24-hr period during the week and weekend. This
will take another 20 minutes, which will give us a clearer idea about how you eat both during the week
and weekends.
POTENTIAL BENEFITS:
Your participation in this study may help you better understand your dietary habits in the United States. It
may also benefit you indirectly and Indians in the United States of America by enabling the health care
professional to understand about the special considerations for helping Indians, especially those with dietrelated chronic diseases from the information we collect.

128

POTENTIAL RISKS:
There are no physical procedures to your body expected of this research. Therefore, you should
experience no physical risks or discomforts. However, you may feel embarrassed or shy about answering
some of the questions. You are not obligated to answer anything that you would prefer not to. There will
be no penalty, if this is the case.
PRIVACY AND CONFIDENTIALITY:
The focus groups will be conducted in a convenient place for you and the other participants. All data will
only have identification numbers with no personal identifiers. Log sheets and data will be kept in separate
locked filing cabinets. However, complete confidentiality of the information that you provided cannot be
guaranteed because participants in the group discussion with you may share what was said in the group
with others outside the focus group discussion. The results of this study may be published or presented at
professional meetings, but the identities of all research participants will remain anonymous.
YOUR RIGHTS TO PARTICIPATE, SAY NO, OR WITHDRAW:
Participation in this research project is completely voluntary. However, the audio taped focus group
section is very important. So, if you do not want the discussions to be audio taped, you will not be able to
participate in this study. You may choose not to answer specific questions or to stop participating at any
time. If you withdraw from this project without completing all the three steps listed above, you will not be
eligible for the $20 gift card.
COSTS AND COMPENSATION FOR BEING IN THE STUDY:
There are no costs associated with participation in this study. Upon completion of the general survey
questions, the focus group discussion and the two 24 hr food recalls, you will receive a $20 gift card to
Meijers as a token of appreciation for your participation.
CONTACT INFORMATION FOR QUESTIONS AND CONCERNS:
If you have concerns or questions about this study or to report an injury, please contact the primary
investigator:
Dr. Lorraine Weatherspoon PhD, RD
Associate Professor in Human Nutrition and
Director, Didactic Program in Dietetics
334 GM Trout Food Science Building
Michigan State University, East Lansing Michigan 48824-1224
Tel: 517-355-8474 ext 136
Email: weathe43@msu.edu
DOCUMENTATION OF INFORMED CONSENT
Your signature below means that you voluntarily agree to participate in this research study and agree to
audio-tape the focus group discussion.
Printed name of the Participant: ______________________________________________
_________________________________
Signature

___________________________
Date

129

Appendix 4 - Sociodemographic survey
Participant ID _____________

Date of Interview______________

1) Age ______________
7) Marital status
Single
Married
Widowed
Separated/Divorced
Other (specify)____________

2) Gender
Male
Female
3) Religion
Hindu
Christian
Muslim
Other (specify) ___________

8) With whom do you live? (check all that
apply)
Alone
With friends
With spouse
With children
With parents
Other (specify) ___________

4) Educational level
Less than high school
High School
Bachelors
Masters
Ph. D or MD

9) No. of members in Household________
Adults______________
Children (<18 years) ______

5) Employment status
Employed (full time)
Employed (part time)
Homemaker
Unemployed
Disabled/Unable to work
Retired
Student
Other (specify) ___________

10) What language do you speak at home?
Mostly Indian
Mostly English
Indian and English equally
Other (specify) ____________
11) How would you describe the place in India
where you spent the majority of your time
before relocating to the U.S.?
Big City
Small City
Small Town
Village

6) Approximate annual household income
<$20,000
20,000 to 50,000
51,000 to 75,000
76,000 to 100,000
>$100,000
Other (specify) ____________

12) At which age did you move to the U.S.? _____________
13) How many years have you continuously lived in the US? ___________ (years)
14) Have you lived in a country other than US? If yes, specify country ______________for how many
years? _______

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Appendix 5 - Focus group questions
1. What are some of your favorite foods? Probe: They could be Asian Indian, western, or other ethnic
foods. Why are they your favorites?
2. What are some new foods that you started eating after coming to the U.S.? Probe: Why?
3. After coming to the U.S., how have you made any changes to the types, amount and/or the number of
times you eat meals?
4. How do you choose the foods that you want to eat on a certain day? Probe: Who does the cooking at
home? How do you think the internet, TV, radio, or magazines here affect what you buy or eat?
5. What are some changes that you made in your eating habits to suit the needs of your family? Probe:
e.g. elderly with medical conditions, school going children, etc.
6. How do you decide what places to go out and eat? What are the types of foods that you eat in
restaurants?
7. What are some Indian foods that you wish you could get here in the U.S.? How do you make up for
those items?
8. What are your preferences for snack foods that you buy?
9. When you go grocery shopping for foods, how do you decide what you want to buy?
10. What are some typical dishes that are cooked at home or purchased from the store when you invite
your American friends? Probe: How is this different when you invite your Indian friends?
11. What do you typically contribute when you attend potluck social gatherings? Probe: How does it vary
between Indian and American social gatherings?
12. How are the foods that you eat outside your home different from what you eat at home? Probe: e.g.
workplace, school, road trips, etc.?
13. How do you think the types of foods in the U.S. has changed your health? Probe: What are some
things that you like or dislike about the Indian diet? What are some things that you like or dislike
about other non-Indian foods in the U.S.?
14. When you were in India, what would you typically eat during the week days and weekends?
15. How did your religion determine what you ate in India? How has this changed since you came to the
U.S.?
16. Do you want to say anything else about your eating habits in the U.S.?

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Appendix 6 - 24-hour dietary recall
ID: ____________

Time of
the day

Date: _______________

Foods / beverages

Day of the week ________________________________

Method of preparation
(baked, fried, boiled, canned, etc.)

“Do you take vitamin or mineral supplements” yes or no If yes specify:

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Amount/portion

Appendix 7 – Expert review of focus group guide
Reviewers
Marsha Carolan, PhD
Associate Professor
Marriage and Family Therapy
Michigan State University, East Lansing, Michigan
Deepa Handu, PhD, RD, LDN
Director, Dietetic Internship
Edward Hines Jr. VA Hospital, Hines, Illinois
Shabnam Riyazali Momin, PhD
Dissertation on acculturation and dietary behaviors of Asian Indians in the U.S.
Michigan State University, East Lansing, Michigan
Revisions made to the focus group guide
There were 29 questions in the focus group guide before revision. The experts suggested
reducing the number of questions. After incorporating the expert suggestions, the revised guide
consisted of 16 questions. The questions were rearranged such that the least sensitive questions
were asked at ask at the beginning while sensitive questions (e.g. religious beliefs and health)
were asked at the end. Questions that were wordy were simplified. Probes were suggested for
questions to facilitate participant responses. Directive questions were identified and reworded
(for example: what are some foods that you think are good for your health? was modified to how
you think the type of foods in the U.S. has changed your health? Probe: What are some things
that you like or dislike about the Indian diet? What are some things that you like or dislike about
other non-Indian foods in the U.S.?). To avoid redundancy, questions on the type of foods
consumed for each meal occasion were removed since they were obtained using the 24 hour
dietary recalls.

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Appendix 8 - Codebook for focus group analysis
Table 11. Codebook for focus group analysis
Domain
Psychosocial

Theme
Social
Network

Code
Family

Psychosocial

Social
Network

Friends and
Others

Psychosocial

Social
Network

Social
Events

Psychosocial

Social
Network

Work Place

Psychosocial

Health and
Nutrition

Health and
Nutrition

Definition
Participant dietary
behaviors and
food choices
influenced by
family
Participant dietary
behaviors and
food choices
influenced by
friends, neighbors,
and others
Participant dietary
behaviors and
food choices
influenced by
social events and
gatherings
Participant dietary
behaviors and
food choices
influenced by
colleagues and
work environment
Food choices and
dietary behaviors
related to
participants’
health

Rule for Application
Applied when reference
to food choices made
for or influenced by
family members
Applied when reference
to food choices made
for or influenced by
friends, neighbors, and
others
Applied when reference
to food choices made
for or influenced by
social events and
gatherings
Applied when reference
to food choices made
for or influenced by
colleagues and work
environment
Applied when reference
to views and
experiences about diet
and food related to
health

134

Example
“When parents come…like my mom prepares
something like upma or something and then lunch
and dinner. Then in between some snack like
samosa or pakoda…so when parents come it’s, it
was different, so yeah, that’s it.”
“I have changed my habit because of my
roommate. Yeah, he likes to eat lot of healthy
things so I switched from white rice to brown
rice…he drinks lots of fruit juice so I have reduced
my soft drink consumption.”
“Usually it would be the same kind of food with
Indians and non-Indians. Like it’d just be milder
for non-Indians I guess and usually if there are kids
that are coming with non-Indians then we’d make
like pasta or something like that so they can just eat
that, order pizza or something yeah.”
“I feel like you know at a work place like
especially when you open your lunch box and then
it gives that smell, I am not comfortable with you
know that kind of a feeling. Like I just try to you
know keep something like that is not going to like,
strong in aromas and stuff like that.”
“food items which are fried in oil, they say that
many times they reuse it and uh it gives rise to bad
fats so which are very dangerous to heart health.
But here they say the oil they don’t reuse it…they
follow the regulations…so we are bit confident in
taking any items”

Table 11 (cont’d).
Domain
Psychosocial

Theme
Media

Code
Media

Definition
Food choices and
dietary behaviors
influenced by
media

Changes in
taste
preferences

Taste
Preferences

Favorite
foods

Participants’
preferred foods
and cuisines

Changes in
taste
preferences

Taste
Preferences

Diet in the
U.S.

Food choices and
dietary behaviors
in the U.S.

Changes in
taste
preferences

Taste
Preferences

Diet in
India

Food choices and
dietary behaviors
in India

Rule for Application
Applied when reference
to the influence of
internet, television,
radio, magazines, etc.
in their food choices
and dietary behaviors
Applied when reference
to favorite foods,
cuisines, and
ingredients. Applied
when reference to
Asian Indian foods that
participant miss in the
U.S.
Applied when reference
to the types of foods
consumed and typical
dietary behaviors in the
U.S.

Applied when reference
to the types of foods
consumed and typical
dietary behaviors when
participant lived in or
visited India

135

Example
“I do browse a lot on food; I really love food and
cooking too. So I do browse and then if I can
understand the recipe, I wanted to try it. So then I
actually go buy for the recipe.”
“…some of the things I miss would be, on a rainy
day hot tea and samosa, or the vada from a road
side stand. Something like that and um and the
Chinese food in India is totally different from the
Chinese food here. So that is something I would
miss as prepared food. Um for ingredients or raw
stuff I miss the varieties of bananas we used to get”
“um the amount I think um probably kind of stayed
the same but the quality of food uh deteriorated
because it’s not home cooked food with you know
all the different ingredients. It’s almost always easy
to make food or easy to buy food like pizzas and
burritos and stuff like that, which are probably not
healthy options.”
“So weekdays mostly it’s what she (mother) cooks
and it’s going to be like morning it will…any tiffin
and a cup of coffee and afternoon it was the meal
and evening she used to make those appam,
karappam…night it will be either a tiffin or
rice…um most of the weekends I went out with my
friends for a movie. So we used to go to the food
court.”

Table 11 (cont’d).
Domain
Environmental

Theme
Restaurants

Code
Restaurants

Environmental

Food
Preparation

Food
Preparation

Environmental

Food
Purchasing

Food
Purchasing

Cultural

Religious
and Cultural
Beliefs

Religious
and
Cultural
Beliefs

Definition
Choice of
restaurants and
types of foods
selected when
dining out

Rule for Application
Applied when reference
to views/ experiences
about eating out.
Reasons that determine
the places participants
choose to dine and the
type of foods selected
at restaurants
Participant
Applied when reference
perceptions of
to experiences
meals cooked at
pertaining to types of
home
foods cooked at home,
factors influencing
meal preparation, and
participants’ cooking
ability
Purchasing
Applied when reference
behavior and the
to views and
types of foods
experiences related to
purchased in
food purchasing, which
stores
includes planning,
preparation, selection
of stores, and types of
foods purchased
Religious and
Applied when
cultural influences participant references
on participant food to religious and cultural
choices and
factors that determines
dietary behaviors
dietary restrictions and
the types of foods
selected/ avoided

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Example
“I eat out when um when I am really busy and
don’t have time to or also when nothing sounds
good at my house so…I usually eat out with one of
my roommates or just whoever I am with and um
yeah I like Menna’s too and I like jimmy johns
because like if I am really busy and don’t have time
to go anywhere they deliver really fast and they’re
pretty cheap.”
“Well for me it’s uh more what I think over the
weekend because that’s when I cook. I sit in the
weekend and cook for the week. And uh…yeah, I
cook it and box it so I don’t spend time during the
week to cook…I wasn’t cooking in India, I was a
pampered kid. Um so, so now it’s that’s what I do
it gets really frustrating for me during the week to
sit and cook. Um so that’s one change."
“I have been trying some packed (Indian) food
also...if one or two people want to eat, there is this
small quantity they pack…now they are available
in regular grocery stores too. Indians of course sell
it in Indian grocery stores…yeah but uh the thing is
that normal American grocery stores are starting to
store, keep them also so it’s just becoming more
universal food.”
“Yeah my parents don’t eat (non-vegetarian foods).
They don’t even eat cake because it has eggs. Um
so the next generation like me, my cousins, my
brother we all, we all binge a lot on meat.”

Appendix 9 – Expert review of Asian Indian Dietary Acculturation Measure (AIDAM)
and food frequency questions
Reviewers
Sudha Raj, PhD, RD
Assistant Professor in Nutrition Science and Dietetics
Syracuse University, Syracuse, New York
Moushumi Mukherjee, MS, RD
Hospital and Health Care
Lansing, Michigan
Parul shah, RD/LD
Consultant Dietitian and Nutrition educator
Atlanta, Georgia
Rita Batheja,MS RD CDN
Private Practice
New York
Ranjita Misra, PhD, CHES, FASHA
Professor and Director, Public Health Practice Program
West Virginia University, Morgantown, West Virginia
Padmini Balagopal, MS, B.Ed, RD, CDE, IBCLC
Principal investigator, nutrition consultant, and adjunct faculty
Manor College, Jenkintown, PA
Marly Mathew, Ph.D
Psychology Post-Doctoral Fellow
Dissertation on acculturation of Asian Indians in the U.S.
Oklahoma City, Oklahoma
Karmeen kulkarni, MS, RD, BC-ADM, CDE
Vice President of Health Care and Education for the American Diabetes Association
Director, Scientific Affairs at Abbott Diabetes Care
Salt Lake City, Utah
Karen Clark
Senior Project Manager - Web Survey Unit
Office for Survey Research
Institute for Public Policy and Social Research
Michigan State University, East Lansing, Michigan
137

Ryan P. Bowles
Assistant Professor
Department of Human Development and Family Studies
Michigan State University, East Lansing, Michigan
Revisions made to the Asian Indian Dietary Acculturation Measure
Before revision, the Asian Indian Dietary Acculturation Measure and the food frequency
questionnaire had 35 and 41 items, respectively. The five point Likert scale used in AIDAM that
ranged from strongly agree to strongly agree was considered as appropriate for the instrument
items. Some experts completed the questionnaires themselves to examine cultural
appropriateness and attached the responses along with their suggestions. These responses were
examined to study the interpretation of the items. The experts corrected typographical errors if
any and provided suggestions to revise the tool. It was recommended by the experts that the
focus of the dietary acculturation measure should be on the assessment of the level of dietary
acculturation and not to identify the reasons for dietary acculturation. Another important
suggestion was to include items that represented non-Indian dietary behaviors. Furthermore, the
experts provided illustrations to reword the items and suggestions for new items. For example,
based on expert suggestion, items on Asian Indian and non-Indian foods not made at home but
ordered from outside were included. Similarly, foods cooked in bulk at home and frozen for later
consumption was suggested as important to include in the instrument. For the food frequency
questionnaire, inclusion of Asian Indian fasting foods such as kichidi, dhokla, and handvo, Asian
Indian party appetizers and north Indian fatty gravies, frequency of consumption of sodas,
alcohol, and energy drinks, and different varieties of yogurt such as Greek yogurt and flavored
yogurt were added as suggested by the experts.

138

Appendix 10 – Asian Indian Dietary Acculturation Measure (AIDAM) pilot test results
(n=12)
Table 12. Asian Indian Dietary Acculturation Measure (AIDAM) – pilot test results (n=12)

Age (years)
Duration of stay in the US
Gender

Male
Female
Religion
Hindu
Muslim
Educational level High school or bachelor’s degree
>Masters
Employment
Employed full time
Other (employed part time, home
maker, student)
Annual household <$75,000
income
>$75,000
Marital status
Currently married
Other (single, divorced, widowed,
dating, partnered)
Language spoken Mostly Indian
at home
Indian and English equally/
Mostly English
US Citizens and permanent
Residency
residents
Work/student/ dependent visa

139

Mean+SD (range)
34.42+9.9 (21-52)
11.88 (2.5-30)
N (%)
6 (50.0)
6 (50.0)
11 (91.7)
1 (8.3)
4 (33.4)
8 (66.6)
7 (58.3)
5 (41.7)
6 (50.0)
6 (50.0)
8 (66.7)
4 (33.3)
5 (41.7)
7 (58.4)
7 (58.3)
5 (41.7)

Table 13: Mean scores for the Asian Indian Dietary Acculturation Measure (AIDAM) – pilot test
results (n=12)
#
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33

Items
I/or the people who I live with eat Indian foods often
I or the people who I live with eat non-Indian foods often
I present Indian foods to social gatherings or when I invite people
I present non-Indian foods to social gatherings or when I invite people
I prefer to eat Indian foods at my school/ workplace
I prefer to eat non-Indian foods at my school/ workplace
I often eat Indian foods when I am with Indians
I like to introduce Indian foods to non-Indians
I changed my eating habits in the U.S. to eat like everyone else in the U.S.
I consider most of the Indian foods as healthy
I consider most of the non-Indian foods as healthy
I do not eat the Indian type of diet on most of the days
I eat healthier foods in the U.S. compared to the foods I would eat if I were
in India
I eat the same size portions of food in the U.S. as I would typically eat if I
were in India
I eat the same amount of starchy foods in the U.S. as I would typically eat if
I were in India
I eat the same amount of sweet foods in the U.S. as I would typically eat if I
were in India
I eat the same amount of oily/ fried foods in the U.S. as I would typically eat
if I were in India
I try Indian foods that I see on the television and Internet
I try non-Indian foods that I see on the television and Internet
I enjoy eating Indian foods
I enjoy eating non-Indian foods
I find Indian foods to be very filling and satisfying
I find non-Indian foods to be very filling and satisfying
I prefer Indian foods for breakfast most of the time
I prefer non-Indian foods for breakfast most of the time
I prefer Indian foods for lunch most of the time
I prefer non-Indian foods for lunch most of the time
I prefer Indian foods for dinner most of the time
I prefer non-Indian foods for dinner most of the time
I prefer Indian foods for a snack most of the time
I prefer non-Indian foods for a snack most of the time
I like to eat at Indian restaurants in the place where I live
I like to eat at non-Indian restaurants in the place where I live

140

Mean+sd
1.83+0.58
3.33+0.65
2.08+0.90
3.18+0.87
3.08+0.79
3.33+0.89
2.00+0.60
2.08+0.52
2.73+1.01
2.17+0.84
2.92+0.79
3.00+1.21
3.08+0.79
2.75+0.97
2.92+1.00
3.17+0.94
3.08+0.90
2.75+0.97
3.50+0.67
1.75+0.62
4.17+0.58
1.92+0.67
3.67+0.49
3.17+0.94
3.67+0.78
2.92+1.00
3.42+0.67
2.08+0.79
3.17+1.03
3.08+1.00
3.58+0.90
2.83+1.19
3.92+0.90

Table 13 (cont’d).
#
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51

Items
I eat out more often in the U.S. when compared to how I would eat in India
I/ or the people who I live with know how to cook Indian foods
I/ or the people who I live with know how to cook non-Indian foods
I/ or the people who I live with often find it easy to prepare Indian foods at
home
I/ or the people who I live with often find it easy to prepare non-Indian foods
at home
I/ or the people who I live with make Indian foods in large quantities and
store them for later use
I/ or the people who I live with make non-Indian foods in large quantities
and store them for later use
I often pick up Indian foods from stores/ restaurants when I/or the people
who I live with do not have time to cook
I often pick up non-Indian foods from stores/ restaurants when I/or the
people who I live with do not have time to cook
I have people who can make Indian foods for me when I/or the people who I
live with do not have time to cook
I have people who can make non-Indian foods for me when I/or the people
who I live with do not have time to cook
I am able to get all the varieties of Indian foods/ produce in the store where I
shop
I often buy packaged and ready to make Indian foods
I often buy packaged and ready to make non-Indian foods
I practice all the food-related beliefs of my religion in the US
I strictly do not eat certain foods because they are not allowed in my religion
I celebrate Indian festivals by eating specialty foods for the occasion
I celebrate non-Indian festivals by eating specialty foods for the occasion

141

Mean+sd
3.92+1.17
1.67+0.49
3.83+0.72
2.50+0.91
3.50+0.67
2.25+0.91
3.00+1.04
3.33+1.16
3.33+0.99
3.08+1.17
2.75+1.06
2.58+0.79
3.25+1.06
3.25+0.87
3.00+1.04
3.17+1.59
2.17+0.84
3.33+0.78

Appendix 11 – Location of residence of web-survey participants (n=225)
Table 14. Location of residence of web-survey participants (n=225)

California
New Jersey
Texas
Illinois
Georgia, Ohio
New York, North Carolina
Florida, Maryland
Massachusetts, Michigan, Minnesota
Pennsylvania
Washington
Tennessee, Virginia
Indiana, Wisconsin
Connecticut, Iowa, Louisiana, Missouri, Utah
Alabama, Arizona, Idaho, Kentucky, Mississippi,
Nebraska, Oklahoma, Oregon, Rhode Island, South
Carolina, Vermont, West Virginia
Total
15 participants did not report their location of residence

142

No.
Total
Participants participants
from each
state
30 (13.3)
30 (13.3)
23 (10.2)
23 (10.2)
14 (6.2)
14 (6.2)
13 (5.8)
13 (5.8)
12 (5.3)
24 (10.6)
11 (4.9)
22 (9.8)
8 (3.6)
16 (7.2)
7 (3.1)
21 (9.3)
6 (2.7)
6 (2.7)
5 (2.2)
5 (2.2)
4 (1.8)
8 (3.6)
3 (1.3)
6 (2.6)
2 (0.9)
10 (4.5)
1 (0.4)
12 (4.8)

210 (93.3)

Appendix 12 – Comparison of demographic profile of Asian Indians participants and
non-participants
Table 15. Comparison of demographic profile of participants with non-participants (n=1350)

Gender

Male
Female
Education
Graduate school
College or technical school
graduate
< Some college/ technical school
Prefer not to answer
Income
>$100,000
$75,000 - $99,999
$50,000 - $74,999
<$50,000
Prefer not to answer
Employment status Full-time
Other
Not available
Not applicable
Religion
Hindu
Other
Not available
Prefer not to answer

Participants
(n=199)
92 (46.2)
107 (53.8)
131 (65.8)
47 (23.6)

Non-participants
(n=1151)
500 (43.4)
651 (56.6)
749 (65.1)
294 (25.5)

21 (10.5)
0 (0.0)
64 (32.2)
46 (23.1)
30 (15.1)
33 (16.6)
26 (13.1)
41 (20.6)
41 (20.6)
106 (53.3)
11 (5.5)
118 (59.3)
57 (28.6)
6 (3.0)
18 (9.0)

106 (9.2)
2 (0.2)
403 (35.0)
235 (20.4)
247 (21.5)
163 (14.2)
103 (8.9)
264 (22.9)
152 (13.2)
668 (58.0)
67 (5.8)
631 (54.8)
392 (34.1)
26 (2.3)
102 (8.9)

The demographic profile comparison from Qualtrics Research Suite was available only for 1350
participants. A total of 1408 emails were sent to Asian Indians in the U.S., of which 289
individuals clicked on the entry link and 225 participants submitted their response.

143

Appendix 13 - Research participant informed consent form (B)
Asian Indian Dietary Acculturation Research Study
Thank you for participating in this survey. This study is in partial fulfillment for a PhD in Human
Nutrition. The purpose of this research is to study the changes in dietary patterns of Asian Indians in the
U.S. The investigators hope to learn how living in the United States of America and other factors are
related to the dietary patterns of Asian Indian adults. Participation in this survey will require
approximately 15-20 minutes of your time depending on your answers and the level of detail you wish to
provide. The survey will include questions on your ethnic background, dietary habits, food frequency
questions, questions on diabetes risk factors, and general survey questions. Your participation in this
research is voluntary. You can discontinue this survey anytime without penalty. You do not have to
answer any question that you do not wish to answer. The survey is anonymous and does not ask for any
information that would identify you. Data collected from this survey will be kept confidential. Data will
be grouped and your comments will not be individually identifiable. Filling out this survey indicates that
you are an Asian Indian at least 18 years old and are giving your informed consent to be a participant in
this study. Should you have any questions, please contact one of the Investigators:
Lorraine Weatherspoon, PhD, RD
Dept. Food Science and Human Nutrition
Michigan State University
Sumathi Venkatesh, MS, PhD Candidate
Dept. Food Science and Human Nutrition
Michigan State University
If you have any questions or concerns about your rights as a participant, you may contact the Michigan
State University’s Human Research Protection Program: phone 517-355-2180, fax 517-432-4503, email
irb@msu.edu or regular mail 207 Olds Hall, MSU, East Lansing, MI48824.
By proceeding to the survey I acknowledge that I have read the above statements and voluntarily agree to
participate in this research study.



Agree
Decline

144

Appendix 14 - Questions on demographic characteristics, diet, and general health
1) Age:
2) Gender:
□ Male
□ Female
3) How many years have you been in the U.S.? _____________
4) Have you lived in a country other than US and India?
□ No
□ Yes (how many years?) ____________________
5) Please indicate in which country you, your parents, and your grandparents were born.
U.S.
You
Father
Mother
Maternal grandfather
Paternal grandfather
Maternal grandmother
Paternal grandmother

□
□
□
□
□
□
□

India

Other Country

□
□
□
□
□
□
□

□
□
□
□
□
□
□

Answer if you were born in India
6) At which age did you immigrate to the U.S.?
Answer if you were born in the U.S or other country
7) Have you ever lived in or visited India?
□ No
□ Yes
Answer if you marked yes to question 7
8) How many times have you visited India, and on average how long in months was your visit?
□ Number of Times Visited: __________
□ Average Length of Stay (please specify years or months): ________________
9) When you lived in India or when you last visited India, was it a . . .
□ Big city
□ Small city
□ Small town
□ Village

145

10) What language do you speak at home?
□ Mostly Indian
□ Mostly English
□ Indian and English equally
□ Other- please specify ____________________
11) What is your religion?
□ Hindu
□ Christian
□ Muslim
□ Other - please specify ____________________
12) Are you currently . . .
□ Single, never been married
□ Married
□ Divorced
□ Widowed
□ Separated
□ Dating
□ Member of an unmarried couple
13) With whom do you currently live? (check all that apply)
□ Alone
□ With friends
□ With spouse
□ With children
□ With parents
□ Other - please specify ____________________
14) Please indicate the number of members in your household including yourself that are:
□ Adults >18 years ___________
□ Children ______________
15) What is the highest level of education that you have achieved?
□ Less than high school
□ High school
□ Bachelor’s degree
□ Master’s degree
□ PhD
□ Other degree - please specify____________________
16) What is your current employment status? (check all that apply)
□ Employed full time
□ Employed part time
□ Homemaker
□ Unemployed
□ Disabled/ unable to work
□ Retired
□ Student
□ Other - please specify ____________________

146

17) What is your approximate total annual household income from all sources?
□ Under $20,000
□ $20,000 to $49,999
□ $50,000 to $74,999
□ $75,000 to $99,999
□ Over $100,000
18) What is your status in the U.S.?
□ US Citizen
□ Green card
□ Work visa
□ Student visa
□ Other - please specify ____________________
19) In what state in the U.S. do you currently live? _______________
20) If you do not eat Indian foods often (at home, work/school, social gatherings or restaurants) what are
the reasons for not eating those type of foods? - Please list as many reasons as possible
____________________________________________________
21) If you do not eat non-Indian foods often (at home, work/school, social gatherings or restaurants)
what are the reasons for not eating those type of foods? - Please list as many reasons as possible
____________________________________________________
22) Are you a vegetarian?
□ Yes
□ No
23) For each of the following foods, please indicate which ones you never eat or drink, then in the space
below each that you never eat or drink, please indicate the main reason why you do not eat or drink
that food.
□ Milk ____________________
□ Eggs ____________________
□ Chicken ____________________
□ Mutton / lamb ____________________
□ Beef ____________________
□ Pork ____________________
□ Seafood ____________________
□ Alcohol ____________________
□ Other ____________________
□ No dietary restrictions

147

24) Do you have any of the following medical problems?
□ High blood pressure
□ Heart disease
□ Kidney problems
□ Diabetes
□ Overweight
□ High cholesterol
□ Other ____________________
□ No medical problems
25) Please provide the following information:
□ Your height in feet and inches: _________
□ Your Weight in pounds: _________
□ Your waist circumference in inches: _________
26) Thank you for taking the survey. Please provide any feedback you have about the survey or any
comments about your food choices, your diet or your health.
________________________

148

Appendix 15 - Food frequency assessment
Choose the option that best describes your typical meals.

1.
2.
3.
4.
5.
6.
7.
8.

How
How
How
How
How
How
How
How

often
often
often
often
often
often
often
often

do
do
do
do
do
do
do
do

you
you
you
you
you
you
you
you

eat
eat
eat
eat
eat
eat
eat
eat

traditional Indian
traditional Indian
traditional Indian
traditional Indian
non-Indian foods
non-Indian foods
non-Indian foods
non-Indian foods

Every
day

1-6
1-3
1-11 Never
times/ times/ times/
week month year

Every
day

1-6
1-3
1-11 Never
times/ times/ times/
week month year

foods for breakfast?
foods for lunch?
foods for dinner?
foods for snacks?
for breakfast?
for lunch?
for dinner?
for snacks?

Choose the option that best describes your typical meals.
How often do you typically eat the following foods?

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.

White rice
Brown rice
Idly
Vermicelli
Cous cous
Quinoa
Dhokla
Handvo
Dosa
Pizza
Pasta/ spaghetti
Macaroni
Chinese noodles
Tortillas/ tacos
Non-Indian sandwiches
Non-Indian Salad
Bacon
Roast beef
Hot dogs
Sambar/ Dal
Sabji
Paneer dishes
Ethnic vegetables (e.g. drumstick, raw/ green banana, bitter
gourd, etc.)
Greek yogurt
Flavored yogurt
Green tea
Indian tea

149

Every
day

28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.

Cold breakfast cereals
Hot cereals (e.g. oatmeal)
Pancakes/ waffles/ bagels
Breakfast cereal bar
Biscuits commonly found in India (e.g. Marie, rusk, etc.)
Papad/ fryums
Indian chutney
Indian pickles
Alcohol
Soda/ pop or cold drinks
Indian mixed rice dishes (e.g. biryani, lemon rice, etc)
Indian rice and lentil dishes (e.g. Khichdi, pongal, bisibelabath,
etc.)
Ready to eat Indian meals (e.g. swad, deep brands)
Ready to eat non-Indian meals (e.g. lean cuisine, banquet, etc.)
Indian bread (e.g. chapatti, naan, paratas, etc.)
Non-Indian bread (e.g. multigrain, rye, pita, rolls, crescents,
corn bread, etc.)
Indian style simple meat or vegetable curry
Indian style stir fried vegetables
Indian style party foods (cream based/oily curries or foods)
Indian fried foods (e.g. puri, vada, samosa, pakora, etc.)
Indian fast foods (e.g. bhel puri, pani puri, etc.)
Non-Indian fast foods (e.g. french fries, burger, etc.)
Indian sweets/ desserts (e.g. burfi, gulab jamun, kheer, etc.)
Non-Indian sweets/ desserts (e.g. Donut, pie, brownie, cookies,
tart, etc.)
Indian ready made salty snacks (e.g. mixture, chakli/ murukku)
Non-Indian ready made salty snacks (e.g. pretzels, tortilla chips,
Chex-mix, etc.)

150

1-6
1-3
1-11 Never
times/ times/ times/
week month year

Appendix 16 - The Finnish Diabetes Risk Score (FINDRISC) assessment
Figure 5. The Finnish Diabetes Risk Score (FINDRISC) assessment

151

Figure 5 (cont’d)

152

Appendix 17 – Validated Asian Indian Dietary Acculturation Measure (AIDAM)
The purpose of this instrument is to measure the level of dietary acculturation of Asian Indians
through the assessment of the influence of various underlying cultural, psychosocial and
environmental factors on participant food choices. We explored the dietary patterns/practices of
Asian Indians to be able to construct an instrument that specifically applies to Asian Indians. The
instrument items were finalized by (i) conducting a thorough review of literature on measures for
Asian Indian dietary acculturation behaviors, (ii) utilizing the conceptual model of dietary to define
the domains of the instrument, (iii) utilizing the themes generated from 8 focus group discussions
with 30 Asian Indian adults in a mid-western state in the U.S., (iv) obtaining opinion from experts in
nutrition/ dietetics of Asian Indian origin and experts in qualitative research, survey research, and
Rasch analytical approach, and (v) obtaining feedback from the target population by conducting a
pilot test of the dietary acculturation items with 12 Asian Indian adults. This rigorous procedure
along with psychometric analysis of the tool resulted in 50 items on dietary acculturation.
The items are in the form of statements and participants will evaluate each statement and their level
of agreement or disagreement is measured on a five point Likert scale. The items measure 8
underlying concepts that may influence dietary acculturation behaviors, which are given as follows:
social network (9 items – item numbers 1-9); health and nutrition (8 items – item numbers 10-17);
media (2 items – item numbers 18-19); taste preferences (13 items – item numbers 20-31);
restaurants (3 items – item numbers 32-34); food preparation (10 items – item numbers 35-44);
food purchasing (3 items – item numbers 45-47); and religious and cultural beliefs (3 items – item
numbers 48-50)
The instrument measures dietary acculturation with traditional Asian Indian dietary practices at oneend and non-Indian practices at the other. Each item has five possible Likert responses, ranging
from 1 – 5. Five ordered response levels were used, the format of which is: (1) strongly agree; (2)
agree; (3) neither agree nor disagree; (4) disagree; and (5) strongly disagree. Items that represent
non-Indian dietary practices are reverse coded with strongly agree as 5 to strongly disagree as 1
(refer to the table below for the specific items). The responses for all the items are added and
divided by the number of items. The final scores also range from 1 to 5, where 1 indicates Asian
Indian dietary practices and 5 is indicative of non-Indian dietary pattern.
Coding
Direct coded items
(represents Asian
Indian practices):

Items
1, 3, 5, 7, 8, 10, 14, 15, 16,
17, 18, 20, 22, 24, 26, 28,
30, 32, 35, 37, 39, 41, 43,
45, 46, 48, 49

Reverse coded items
(represents nonIndian practices):

2, 4, 6, 9, 11, 12, 13, 19,
21, 23, 25, 27, 29, 31, 33,
34, 36, 38, 40, 42, 44, 47,
50

153

1
2
3
4
5
5
4
3
2
1

Scoring
= Strongly agree
= agree
= neither agree nor disagree
= disagree
= strongly disagree
= Strongly agree
= agree
= neither agree nor disagree
= disagree
= strongly disagree

ASIAN INDIAN DIETARY ACCULTURATION MEASURE
Since living in the U.S., you might have changed some of your cultural dietary habits. For each
statement below please check the box on the right that best describes you.
Strongly
Agree

1. I/or the people who I live with eat Indian foods often
2. I or the people who I live with eat non-Indian foods
often
3. I present Indian foods to social gatherings or when I
invite people
4. I present non-Indian foods to social gatherings or when
I invite people
5. I prefer to eat Indian foods at my school/ workplace
6. I prefer to eat non-Indian foods at my school/ workplace
7. I often eat Indian foods when I am with Indians
8. I like to introduce Indian foods to non-Indians
9. I changed my eating habits in the U.S. to eat like
everyone else in the U.S.
10. I consider most of the Indian foods as healthy
11. I consider most of the non-Indian foods as healthy
12. I do not eat the Indian type of diet on most of the days
13. I eat healthier foods in the U.S. compared to the foods I
would eat if I were in India
14. I eat the same size portions of food in the U.S. as I
would typically eat if I were in India
15. I eat the same amount of starchy foods in the U.S. as I
would typically eat if I were in India
16. I eat the same amount of sweet foods in the U.S. as I
would typically eat if I were in India
17. I eat the same amount of oily/ fried foods in the U.S. as
I would typically eat if I were in India
18. I try Indian foods that I see on the television and
Internet
19. I try non-Indian foods that I see on the television and
Internet
20. I enjoy eating Indian foods
21. I enjoy eating non-Indian foods
22. I find Indian foods to be very filling and satisfying
23. I find non-Indian foods to be very filling and satisfying
24. I prefer Indian foods for breakfast most of the time
25. I prefer non-Indian foods for breakfast most of the time
26. I prefer Indian foods for lunch most of the time
27. I prefer non-Indian foods for lunch most of the time
28. I prefer Indian foods for dinner most of the time

154

Agree

Neither Disagree Strongly
agree nor
disagree
disagree

Strongly
Agree

29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.

I prefer non-Indian foods for dinner most of the time
I prefer Indian foods for a snack most of the time
I prefer non-Indian foods for a snack most of the time
I like to eat at Indian restaurants in the place where I
live
I like to eat at non-Indian restaurants in the place where
I live
I eat out more often in the U.S. when compared to how
I would eat in India
I/ or the people who I live with know how to cook Indian
foods
I/ or the people who I live with know how to cook nonIndian foods
I/ or the people who I live with often find it easy to
prepare Indian foods at home
I/ or the people who I live with often find it easy to
prepare non-Indian foods at home
I/ or the people who I live with make Indian foods in
large quantities and store them for later use
I/ or the people who I live with make non-Indian foods
in large quantities and store them for later use
I often pick up Indian foods from stores/ restaurants
when I/or the people who I live with do not have time to
cook
I often pick up non-Indian foods from stores/
restaurants when I/or the people who I live with do not
have time to cook
I have people who can make Indian foods for me when
I/or the people who I live with do not have time to cook
I have people who can make non-Indian foods for me
when I/or the people who I live with do not have time to
cook
I am able to get all the varieties of Indian foods/
produce in the store where I shop
I often buy packaged and ready to make Indian foods
I often buy packaged and ready to make non-Indian
foods
I practice all the food-related beliefs of my religion in the
US
I celebrate Indian festivals by eating specialty foods for
the occasion
I celebrate non-Indian festivals by eating specialty foods
for the occasion

155

Agree

Neither Disagree Strongly
agree nor
disagree
disagree

Appendix 18 – Participant responses to the food frequency questionnaire
Table 16. Participant responses for the food frequency questionnaire
#

Question

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22

White rice
Brown rice
Idly
Vermicelli
Cous cous
Quinoa
Dhokla
Handvo
Dosa
Pizza
Pasta/ spaghetti
Macaroni
Chinese noodles
Tortillas/ tacos
Non-Indian sandwiches
Non-Indian Salad
Bacon
Roast beef
Hot dogs
Sambar/ dal
Sabji
Paneer dishes
Ethnic vegetables (e.g. drumstick, raw/green banana,
bitter gourd, etc.)
Greek yogurt
Flavored yogurt

23
24
25

6 (3.2)
56 (30.8)
21 (11.1)
38 (20.0)
100 (52.9)
99 (52.1)
54 (28.6)
102 (54.3)
9 (4.7)
4 (2.1)
13 (6.8)
50 (26.5)
35 (18.5)
18 (9.6)
19 (10.0)
23 (12.1)
124 (65.3)
126 (66.3)
122 (64.6)
7 (3.7)
7 (3.7)
18 (9.5)

1-11 times/
year
10 (5.3)
29 (15.9)
59 (31.2)
65 (34.2)
41 (21.7)
26 (13.7)
74 (39.2)
37 (19.7)
72 (37.9)
53 (27.9)
50 (26.2)
57 (30.2)
66 (34.9)
52 (27.7)
29 (15.3)
28 (14.7)
23 (12.0)
30 (15.8)
35 (18.5)
38 (20.0)
21 (11.1)
57 (30.0)

1-3 times/
month
43 (22.8)
56 (30.8)
79 (41.8)
60 (31.6)
34 (18.0)
37 (19.5)
44 (23.0)
37 (19.7)
63 (33.2)
106 (55.8)
94 (49.2)
65 (34.4)
72 (38.1)
93 (49.5)
87 (45.8)
79 (41.6)
31 (16.3)
26 (13.7)
26 (13.8)
49 (25.8)
28 (14.7)
76 (40.0)

1-6 times/
week
88 (46.6)
34 (18.7)
27 (14.3)
25 (13.2)
11 (5.8)
26 (13.7)
17 (8.9)
11 (5.9)
41 (21.5)
26 (13.7)
33 (17.3)
17 (9.0)
15 (7.9)
25 (13.3)
51 (26.8)
51 (26.8)
10 (5.3)
8 (4.2)
6 (3.2)
70 (36.8)
80 (42.1)
37 (19.5)

13 (6.8)

33 (17.4)

55 (28.9)

45 (23.8)
42 (22.3)

44 (23.3)
49 (26.1)

40 (21.2)
43 (22.9)

Never

156

Everyday

n

42 (22.2)
7 (3.7)
3 (1.6)
2 (1.1)
3 (1.6)
2 (1.1)
0 (0.0)
1 (0.5)
5 (2.6)
1 (0.5)
1 (0.5)
0 (0.0)
1 (0.5)
0 (0.0)
4 (2.1)
9 (4.7)
2 (1.1)
0 (0.0)
0 (0.0)
26 (13.7)
54 (28.4
2 (1.1)

189
182
189
190
189
190
189
188
190
190
191
189
189
188
190
190
190
190
189
191
190
190

73 (38.4)

16 (8.4)

190

44 (23.3)
45 (23.9)

16 (8.5)
9 (4.8)

191
191

Table 16 (cont’d).

55 (28.9)
13 (6.8)
22 (11.6)
27 (14.2)
14 (7.4)
43 (22.8)

1-11 times/
year
38 (20.0)
26 (13.7)
21 (11.1)
33 (17.4)
63 (33.2)
51 (27.0)

1-3 times/
month
40 (21.1)
27 (14.2)
52 (27.5)
60 (31.6)
78 (41.1)
59 (31.2)

1-6 times/
week
38 (20.0)
35 (18.4)
67 (35.4)
41 (21.6)
31 (16.3)
26 (13.8)

25 (13.2)

46 (24.2)

48 (25.3)

17 (8.9)
9 (4.7)
13 (6.8)
73 (38.4)
24 (12.8)
9 (4.7)

46 (24.2)
35 (18.4)
32 (16.8)
44 (23.2)
59 (31.4)
29 (15.2)

8 (4.2)

#

Question

Never

26
27
28
29
30
31

Green tea
Indian tea
Cold breakfast cereals
Hot cereals (e.g. oatmeal)
Pancakes/ waffles/ bagels
Breakfast cereal bar
Biscuits commonly found in India (e.g. Marie, rusk,
etc.)
Papads/ fryums
Indian chutney
Indian pickles
Alcohol
Soda/ pop or cold drinks
Indian mixed rice dishes (e.g. biryani, lemon rice, etc.)
Indian rice and lentil dishes (e.g. khichdi, pongal,
bisibelabath, etc.)
Ready to eat Indian meals (e.g. Swad, Deep brands)
Ready to eat non-Indian meals (e.g. Lean cuisine,
Banquet, etc.)
Indian bread (e.g. chapatti, naan, paratas, etc.)
Non-Indian bread (e.g. multigrain, rye, pita, rolls,
crescents, corn bread, etc.)
Indian style simple meat or vegetable curry
Indian style stir fried vegetables
Indian style party foods (cream based/ oily curries or
foods)
Indian fried foods (e.g. puri, vada, samosa, pakora,
etc.)

32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47

Everyday

n

19 (10.0)
89 (46.8)
27 (14.3)
29 (15.3)
4 (2.1)
10 (5.3)

191
190
189
190
190
189

53 (27.9)

18 (9.5)

190

78 (41.1)
74 (38.9)
57 (30.0)
44 (23.2)
54 (28.7)
93 (48.9)

42 (22.1)
60 (31.6)
69 (36.3)
23 (12.1)
39 (20.7)
52 (27.4)

7 (3.7)
12 (6.3)
19 (10.0)
6 (3.2)
12 (6.4)
7 (3.7)

190
190
190
190
188
190

28 (14.7)

81 (42.6)

59 (31.1)

14 (7.4)

190

47 (24.9)

49 (25.9)

62 (32.8)

26 (13.8)

5 (2.6)

189

78 (41.3)

42 (22.2)

50 (26.5)

18 (9.5)

1 (0.5)

189

6 (3.2)

19 (10.0)

49 (25.8)

71 (37.4)

45 (23.7)

190

16 (8.4)

37 (19.5)

64 (33.7)

60 (31.6)

13 (6.8)

190

25 (13.2)
13 (6.8)

15 (7.9)
23 (12.1)

49 (25.8)
49 (25.8)

68 (35.8)
76 (40.0)

33 (17.4)
29 (15.3)

190
190

14 (7.4)

56 (29.5)

85 (44.7)

31 (16.3)

4 (2.1)

190

8 (4.2)

59 (31.2)

95 (50.3)

26 (13.8)

1 (0.5)

189

157

Table 16 (cont’d)
#

Question

48
49

Indian fast foods (e.g. bhel puri, pani puri, etc.)
Non-Indian fast foods (e.g. French fries, burger, etc.)
Indian sweets/ desserts (e.g. burfi, gulab jamun, kheer,
etc.)
Non-Indian sweets/ desserts (e.g. donut, pie, brownie,
cookies, tart, etc.)
Indian readymade salty snacks (e.g. spice mixture,
chakli/ murukku, etc.)
Non-Indian readymade salty snacks (e.g. pretzels,
tortilla chips, Chex-mix, etc.)

50
51
52
53

1-11 times/
year
16 (8.4)
70 (36.8)
18 (9.5)
59 (31.1)

Never

1-3 times/
month
83 (43.7)
86 (45.3)

1-6 times/
week
20 (10.5)
27 (14.2)

Everyday

n

1 (0.5)
0 (0.0)

190
190

9 (4.7)

72 (37.9)

83 (43.7)

25 (13.2)

1 (0.5)

190

12 (6.4)

62 (33.0)

84 (44.7)

25 (13.3)

5 (2.7)

188

17 (9.0)

46 (24.3)

73 (38.6)

48 (25.4)

5 (2.6)

189

12 (6.3)

42 (22.1)

91 (47.9)

38 (20.0)

7 (3.7)

190

158

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