Food Choices in the Context of Globalizing Food Options among Adolescents in Rural Southern India

Abstract

Changes in food choice often accompany globalization and economic growth. These changes have not been well documented in rural settings and among young people. To advance research on food choice, we demonstrate adolescents’ selection of local vs.non-local foods in a rural area of India where globalization is just reaching. A representative sample of 237 school-going adolescents in a village in Southern India completed a survey in 2019 to understand how adolescents decide among foods traditional to the area and foods arriving from other parts of the country and the world. Adolescents most frequently consumed local foods but also occasionally consumed non-local items. In hypothetical scenarios, 81% of the adolescents reported being most interested in substituting local foods with non-local foods if they were to have more money. Among the few who currently consumed non-local snacks and drinks, very few would be willing to replace them with local alternatives, particularly if they were to have more money (snacks: 10% and drinks: 5% respectively). Overall, adolescents were most interested in switching to non-local items when considering fruits, vegetables and snacks. As India faces the dual burden of undernutrition and overnutrition, understanding the changing food environment may help inform efforts to improve nutrition.

Intoduction

Globalization can lead to dietary shifts away from diets high in fiber and cereals, towards diets high in sugar, refined carbohydrates, fat and animal products.^{1, 2} Frequently, these shifts include increasing consumption of processed foods and foods eaten outside the home.^{3, 4} Changes in food supplies occurring with globalization and economic expansion can offer new means of addressing malnutrition in the form of under-nutrition, but may also promote malnutrition in the form of obesity.^{2, 5–10}

Food supplies are changing even in remote parts of the world, introducing new foods in places that have largely relied on locally grown foods until recently. The integration of new foods into local diets is a complex and uneven process. Foreign consumer goods and lifestyles do not outright supplant local practices, because new ideas and products are not uncritically adopted by passive consumers; they are interpreted and modified according to local norms and local history.^11–13 Globalization and localization are twinned processes, such that the inclusion of global foodstuffs into communities may foster “self-conscious difference,” whereby people emphasize their local cuisine as a counterpoint to the perceived uniformity and banality of western diets.¹⁴

After its independence in 1947, India was a socialist country, largely insulated from globalization. Food supplies in India began to change in 1991 with trade liberalization. India’s subsequent experience of the nutrition transition has been well documented,^{15, 16} with particular attention to increased food availability, accessibility, and preferences in globally connected urban centers. Despite India’s increasing integration into the global economy, local customs and norms continue to guide everyday life, making India an opportune setting in which to study how global and local forces may converge into global chains with a local twist. For example, multinational food chains in India make pizzas with paneer (homemade Indian cheese) and tikka sauce (a spicy tomato-based sauce common in North Indian dishes), and burgers are spicy chicken or potato patties.

Across India, processed and packaged foods are emerging as convenient and fast, but expensive alternatives to items from fresh markets. However, consumption of these foods is still low in remote areas.¹⁷ Still, food outlets, including roadside eateries and hotel restaurants, have increased in remote areas recently.^{17, 18} Non-local fast foods are also abundant through small shops and street vendors¹⁹ and are eaten out or brought home for family meals.^{20, 21} Recent research has documented awareness and consumption of “global” foods among adolescents in urban Southern India.^{17, 22} By examining food choice in rural areas, we can gain new perspectives into the process of dietary change and changing food environments.

An important step in understanding how changing food environments can impact nutritional intake is by learning how food choices are made. Food decisions are complex, and may be guided by external cues, including dietary recommendations, marketing, price, ease of preparation, packaging, and product placement,^{23, 24} as well as internal cues, such as taste preference for sugar and fat.^{25, 26} In this study, we examined food choice among adolescents in a remote rural Indian community. To contribute to the understanding of globalizing food choices, we have developed a classification of foods as local, national and global. Local items include flatbreads made of sorghum or pearl millet, seasonal and year-round fruits, sweet dishes and items across food groups that have historically been a part of the regional diet. Fried savory snacks, grains, and fruits and vegetables that are not local to Southern India, or “national foods”, are increasingly easy to find due to internal migration and improved transportation. Items from outside of India, or “global foods”, often include energy-dense and nutrient-poor foods, especially snacks such as pizza and noodles, but also include fruits and vegetables such as berries and broccoli. This classification recognizes the spectrum of market integration and adds needed nuance to our understanding of global food markets.

This study aims to help us understand the process by which non-local items become integrated into the process of dietary change and changing food environments. First, we describe adolescents’ familiarity with food items and which items (local, non-local, national and global) are most frequently consumed across the major food groups: fruits & vegetables; cereals & pulses; snacks; animal products; oils, sweeteners & condiments; and drinks. Next, we characterize adolescents’ interest in switching from local to national and/or global foods under different scenarios. These scenarios include if they had more money, time constraints, or considerations about healthiness, taste, or hunger. Finally, we evaluate how adolescent choices change in different scenarios.

Materials & Methods

Study Setting

The study is set in a remote village in the northern region of the state of Karnataka in India. The region, Vijayapura district, has a population of over 2 million people.²⁷ Farming and agriculture-related businesses are the main occupations in the district, which produces primarily sorghum, pearl millet, pigeon pea (toor dal) and maize, largely dependent on the monsoon.²⁷ The village is situated 25 km from Vijayapura, the district capital city, and has a population of approximately 8,519 individuals in 1,759 households (as of 2011). The major occupation in the village is farm labour. The village and its surroundings benefit from two well-established health centers.²⁷

Typical meals in the region consist of flatbreads – roti, made from sorghum or pearl millet, and chapatis, made from wheat, accompanying pulses/lentils often eaten with vegetable curries. Yogurt, or curd, is frequently eaten with meals, as are dry peanut or flax seed chutneys.²⁸ Banana, papaya and sapota are fruit available throughout the year; seasonal fruits are Indian plum (ber), grapes, pomegranate, mango, and melons. About half of the population is vegetarian;^{27, 29} others eat eggs, chicken, mutton and fish once or a few times per week. Rice is not central to local diets, though, given its easy and cheap availability through the Public Distribution System, India’s massive hunger prevention program, it has recently become incorporated into regular meals.³⁰ The major beverages consumed are tea or coffee prepared with sugar and milk; sugar cane juice and fresh fruit juices made from seasonal fruits are made at home and also sold by road-side vendors. Local sweet dishes are holige/pooran poli (gram and jaggery mixture stuffed into wheat dough), sweet porridge/sheera made form semolina (wheat) and laddos (peanut-jaggery-gram flour balls). A half-dozen street vendors sell national street foods like vada pav (bread with potato samosa), panipuri, Indo-Chinese fast foods like gobi manchurian, egg fried rice and chicken 65 near the bus stop and near schools. These vendors move around the village in the afternoon and provide savory chaats (snacks) to children and women in front of their homes. Small traditional convenience shops called Kiraana sell candy, chips, and unbranded snack items like crackers and soda. A weekly farmers’ market on Thursday sells fresh vegetables, fruits and other groceries.

Instrument Development

We developed bespoke quantitative survey instruments. These instruments were pre-tested, pilot-tested, and adapted before fielding. A socio-economic module included questions on the households, its assets, religion, caste, and demographic characteristics of each household member answered by the head of the household or his spouse. A food choice module consisted of 25 questions and made use of picture cards from a food database of foods and drinks available in the district, which we created and maintained since 2012 and was answered by the adolescent. From this food database, we designed picture cards with 72 food and drink items grouped into food groups. The picture cards were categorized into six food groups: 1) fruits & vegetables; 2) cereals & pulses; 3) snacks; 4) animal products; 5) oils, sweeteners & condiments; 6) drinks. Within each food group was were 3 photos designated as local, national, and global, based on research.^{17, 31} See Appendix A.1 for details on the food group classification and specific food cards. A review of all photos was done by authors and fieldworkers to ensure correct categorization of local, national and global.

To reduce interview time we employed two levels of randomization for the food choice module. Each adolescent was first randomized to answer questions about three of the six food groups (Appendix A.2). As a second level of randomization, within each food group respondents were randomized to one specific food card for local, one specific food card for national, and one specific food card for global. There were four local food cards, four national food cards, and four global food cards available for each food group. Respondents were shown three photos from a food group all at one time: one card showing a local item from that group, one card showing a national item, and one card showing a global item. They were asked a series of questions about each of the three items: whether they had ever seen it; if so, where; whether they had ever consumed it. Then, they were asked to point to the one they eat most frequently. Respondents were then presented with a series of hypothetical scenarios, and for each, were asked to point to the item, (one local, one national, one global) they would: “Of the 3 foods, which one would you buy if you had an additional Rs. 250 to spend?”; “… if you want something that tastes good?”; “… if you were very hungry?”; “ which one would you eat for health reasons?” “… if you had very little time to make ready to eat?” Since adolescents are not always the one making their food, we also probed with “…if there is no time for your caretaker to prepare food?” The questions were repeated for the two other randomized food groups.

Data

All adolescents ages 10 to 18 years from the rosters of all seven schools serving the village and surrounding communities were invited to participate in the study. Across the 254 adolescents selected through representative sampling, there were 237 adolescents interviewed between Januaryand April 2019. Adolescents were excluded if they lived in a different village (n=5) or were not present at school on the days of data collection (n=12). The study was approved by our Institutional Review Boards and by the Indian Council of Medical Research (ICMR). In each school, prior permission was taken from school authorities and teachers to conduct the study. Consent and assent were taken from parents and adolescents, respectively. Adolescents were pulled from class individually during school hours and taken to a quiet separate space in a classroom or school courtyard, where the interview was conducted by a trained interviewer. Interviews lasted 45–60 minutes and were conducted in Kannada, the local language. In addition to the school-based data collection, interviewers also visited each adolescent’s home and enrolled one adult male and one adult female per household. These interviews were scheduled by appointment, lasted two hours and were conducted after each respondent was informed about the study and granted informed consent.

Outcome Measures

To describe familiarity with foods and which items are most frequently consumed, we created a binary variable of ever seen based on whether adolescents confirmed they had seen a specific food item (yes; no). We created a binary variable of ever consumed based on whether adolescents confirmed they had consumed a specific food item (yes; no). We created a 3-category variable based off of adolescents being asked which food item they ate most frequently within each food group with the categories local, national and global (most frequent). Based on lower frequency in some food groups, we also created a 2-category variable of local and non-local which combined national and global for which foods adolescents reported eating most frequently within a food group (most frequent- condensed).

For each of the 6 food groups, we calculated the proportion of respondents who chose a local item as the most frequently consumed and then chose a non-local item in a hypothetical choice scenario compared to choosing local food items in both instances. We similarly calculated the proportion of respondents who chose a non-local item as their most frequently consumed item and then chose a local item compared to choosing non-local food items both times. These two variables indicated a change from local to non-local and change from non-local to local with both reference groups being a maintenance in preference with a local or non-local item.

As a parallel measure incorporating both changes, we looked across all individuals no matter the most frequently consumed choice (local or non-local) and determined if individuals switched when given different scenarios. We calculated the proportion of respondents who chose a local or non-local item as their most frequently consumed item and then switched to the other category for a hypothetical choice scenario compared to choosing the same category of item both times. This variable indicated those who switch categories and is coded as 1 for non-local to local change or local to non-local change and 0 for those who maintained their preference with a local or non-local item across scenarios.

Covariates

Adolescents’ gender (boys; girls) was taken from the school rosters and they were asked about their age (continuous). Height and weight was objectively measured by trained interviewers. Weight was measured by trained research staff in kilograms to the nearest 0.1 kg using the average of two measures from a digital scale. Height was measured in meters to the nearest 0.1 cm, using the average of two measures from a portable stadiometer (SECA company). Each device was standardized everyday using standard protocols. We calculated age- (in months) and sex-specific body mass index (BMI) z scores (kg/m²) for adolescents based on height and weight measures. We created BMI categories: underweight, normal-weight, overweight and obese using World Health Organization (WHO) growth reference for school-aged children (5–19 years).³²

A number of other household characteristics were collected frorm the adolescent’s primary caregiver. Caste was categorized as General Caste, Other Backward Caste (OBC), Scheduled Tribe (ST) and Scheduled Caste (SC). OBC, SC and ST are terms used by the Government of India to classify socially and educationally disadvantaged sections of the population. religion (Hindu; Muslim), household size (continuous), monthly household income (less than Rs. 5,000/-; Between Rs. 5,000 to 10,000/-; Between 10,001 to 20,000/-; Between Rs. 20,001 to 30,000/-; More than Rs. 30,000/-), household member owns house (yes; no), household member owns land (yes; no), house has a separate water supply (yes; no). For descriptive purposes, mother’s and father’s occupations were categorized as 1) Cultivation, herdsman, agricultural labor, 2) Non-agricultural wage labor, 3) Craftsman, small business, large business, 4) salaried employees, professional, and 5) Other. For modeling purposes, we created a combined household agricultural occupation variable where, if either or both parents worked in cultivation, animal husbandry or agricultural labor, the variable was coded as yes, otherwise no because of sample size considerations. Age, gender, and household occupation were used as covariates for regression models.

Analysis

We conducted univariate analyses of each variable, assessed normality of distributions for continuous variables, and checked for outliers and influential observations. Bivariate analyses of outcomes and covariates were performed to assess unadjusted significance and linearity of each association. We estimated a logistic regression model for the odds of changing from local to non-local food items for each choice scenario, adjusting for gender, age, household occupation, and food group dummy variables. Logistic regression was also used to examine whether individuals who reported consuming local food item most frequently had higher odds of switching to a non-local item compared to those who reported consuming non-local food items most frequently. The model was implemented for each of the 5 hypothetical choice scanrios and the variables included were age, gender, household occupation, and local/non-local most frequently consumed. All analyses were conducted using STATA 16. We used a Bonferroni correction for multiple comparisons. Weights were not necessary because all adolescents were sampled from a pooled sampling frame of all schools in the village. The findings are generalizable to adolescents in a rural village in Southern India.

Statement of Ethics

The study protocol was approved by the Emory Institutional Review Boarrd and the BLDE (Deemed to be) Institutional Review Board in India. Informed consent was obtained from the parents of the study subjects.

Results

Sample Characteristics

The majority of adolescents were normal weight (73%), 21% were underweight, 5% were overweight and 0.9% were obese (Table 1). The majority of households were OBC (62%), 23% belonged to a SC or ST, 14% belonged to a General caste indicating our sample is socially disadvantaged. The majority of households were primarily Hindu (71%) and consisted, on average, of 6 people. Approximately half (49%) of households had an income of less than 5,000 INR per month (~69 USD). The current poverty line in rural areas of India is 1059 INR per month. The large majority owned the house they lived in (94%), had a separate water supply (80%), and owned land (65%).

Table 1.

Sociodemographic characteristics of adolescents in a rural village, Vijayapura district, India

Characteristic	% or mean value
ADOLSECENT CHARACTERISTICS
Age (years)	13.5
Gender
Male	52.3%
Female	47.7%
Caste
General	14.4%
Other backward class	62.0%
Scheduled caste	23.2%
Scheduled tribe	0.4%
Religion
Hindu	71.3%
Muslim	28.7%
BMI Categories
Underweight	21.2%
Normal Weight	73.3%
Overweight	4.7%
Obese	0.9%
HOUSEHOLD CHARACTERISTICS
Household size	6.0
Father’s Occupation
Cultivaion, herdsman, agricultural labor	32.4%
Non-agricultural wage labor	14.2%
Craftsman, small business, large bus	47.0%
Salaried employees, professional	3.7%
Other	2.7%
Moher’s Occupation
Cultivaion, herdsman, agricultural labor	15.7%
Non-agricultural wage labor	4.8%
Craftsman, small business, large bus	41.1%
Salaried employees, professional	1.3%
Housewife	37.1%
Monthly household income (INR)
Less than Rs. 5000/-	29.5%
Between Rs. 5000 to 10000/-	49.8%
Between Rs. 10001 to 20000/-	15.6%
Between Rs. 20001 to 30000/-	3.4%
More than Rs. 30000/-	1.7%
Household member owns house	93.7%
Household member owns land	65.0%
Separate water supply	79.8%

^aBMI= Body Mass Index; WHO 2007 age- and sex-specific z scores

^bINR = Indian Rupees

^cN = 237

Adolescents’ Familiarity with and Consumption of Local, National, and Global Items

Table 2 shows the percentage of adolescents who had ever-seen, ever-consumed, and most frequently eaten food items from each food group, separately by local, national, and global foods. All adolescents had seen local food items from every food group and the large majority had seen national food items from all food groups (73% for animal products to 99% for fruits & vegetables). For global foods, adolescents were mostly familiar with non-perishable items: only 19% had ever seen global fruits & vegetables, but 88% had seen global snack items; 3.5% had eaten global fruits or vegetables, but 59% had eaten global snacks.

Table 2.

Familiarity and consumption of local, national, and global food items among adolescents in a rural village, Vijayapura, India

	Fruits & Vegetables (%)	Cereals & Pulses (%)	Snacks (%)	Animal Products (%)	Oils, Sweeteners, Condiments (%)	Drinks (%)
Ever Seen
Local/Traditional	100.0	100.0	100.0	100.0	100.0	100.0
National/Mixed	99.2	79.4	84.6	72.6	93.8	93.7
Global/Modern	18.8	78.4	88.0	63.8	36.5	47.6
Ever Consumed
Local/Traditional	99.2	100.0	98.4	95.3	100.0	97.2
National/Mixed	96.6	61.9	78.1	46.7	78.4	81.7
Global/Modern	3.5	41.5	58.4	44.8	10.4	11.9
Most Frequently Eaten
Local/Traditional	71.8	87.2	75.2	70.2	83.3	72.0
National/Mixed	28.2	7.2	18.4	21.2	16.7	25.2
Global/Modern	0.0	5.6	6.4	8.7	0.0	2.8
Sample Size	n 117	n 125	n 125	n 105	n 97	n 142

^aSample size for each food group based on those randomized to each food group.

^bN = 23

Adolescents most frequently ate local foods across the food groups: among animal products, 70% reported most frequently eating the local items; among cereals & pulses, 87% had reported most frequently eating the local items. A few adolescents eating national items more frequently than local or global items: 7% for cereals & pulses and 28% for fruits & vegetables. No adolescents had most frequently eaten global fruits, vegetables, oils, sweeteners, or condiments, but 9% reported most frequently eating a global animal product. Food familiarity and consumption patterns were fairly similar between boys and girls (Appendix Table A.3).

Adolescents’ Choice in Different Scenarios

For the next set of results, we condensed national and global into non-local due to infrequent choice of global items. Across food groups, the proportion of respondents who reported most frequently consuming a local item but preferred a non-local food item when given additional money ranged from 43% (animal products) to 69% (fruits & vegetables) (Table 3). In comparison, the proportion of respondents reported most frequently consuming a non-local item but preferred a local item when given additional money ranged from 4% for animal products to 47% for cereals & pulses. When considering animal products, a lower proportion of respondents changed from local to non-local for all 5 hypothetical choice scenarios. Across choice scenarios and food groups, a higher proportion of respondents changed from local to non-local than respondents changing from non-local to local, with a few exceptions.

Table 3.

Change from a local to non-local foods and non-local to local foods by different hypothetical choice scenarios

Characteristic	Fruits & Vegetables (%)	Cereals & Pulses (%)	Snacks (%)	Animal Products (%)	Oils, Sweeteners, Condiments (%)	Drinks (%)
Situation: if …
… had an additional Rs. 250
changed from local to non-local	68.8%	68.0%	65.6%	42.9%	44.2%	64.7%
changed from non-local to local	30.3%	46.7%	10.3%	3.6%	20.0%	5.1%
… wanted something tasty
changed from local to non-local	65.5%	40.7%	40.4%	37.0%	40.3%	33.3%
changed from non-local to local	15.2%	25.0%	22.6%	16.7%	31.3%	25.0%
… wanted something healthy
changed from local to non-local	41.7%	31.2%	26.7%	16.4%	41.6%	46.1%
changed from non-local to local	50.0%	50.0%	77.4%	54.8%	56.3%	17.5%
… very hungry
changed from local to non-local	51.2%	33.0%	29.8%	26.4%	44.9%	26.7%
changed from non-local to local	34.4%	31.3.%	51.6%	25.8%	31.3%	47.5%
… had little time to prepare
changed from local to non-local	63.9%	53.2%	41.5%	19.4%	50.0%	14.9%
changed from non-local to local	41.9%	37.5%	33.3%	41.4%	18.8%	60.0%
Sample Size	n 117	n 125	n 125	n 105	n 97	n 142

^aChanged from local to non-local: Respondents first reported most frequently eating a local item then changed to a non-local item when given a specific scenario.

^bChanged from non-local to local: Respondents first reported most frequently eating a national or global item then changed to a local item when given a specific scenario.

^cN = 237

^dEach % represents those who had selected either selected a local item first and then had the chance to switching.

Note that, from Table 2, we identified that adolescents had seen and consumed non-local foods less frequently in the food categories of fruits & vegetables and condiments. But, for other food groups, the vast majority had seen and consumed these items. Thus, the switch to non-local is tied to the food items that adolescents identified as being familiar to them (ever seen & ever consumed variables).

Factors Associated with Interest in Changing from Local to Non-Local Foods

Table 4 reports the odds of changing from local to non-local in different hypothetical scenarios of budget, time constraints or preferences compared to staying with a local choice across food groups, adjusted for age, gender and family occupation. The sample size for these models is 237 because every repondents reported most frequently consuming a local item for at least one food group. The six food groups are used as dummy predictors in the regression models with cereals and pulses as the reference category and for those respondents who were not asked that food group they are kept at 0 but still included in the model. Adolescents were most likely to change the item selected within the food group if they had more money (scenario offered was comparable to $3.41 in USD): 81% changed for at least one food group. Between 55%−64% of adolescents changed from a local item to a non-local item in at least one food group for all other choice scenarios. Between 6% (fruits & vegetables) and 27% (animal products) never switched from local to non-local no matter what the scenario was. Between 0.1% (snacks) and 9% (drinks) switched from non-local to local across scenarios.

Table 4.

Odds of changing from local foods to non-local foods by hypothetical choice scenarios among adolescents in a rural village, Vijayapura, India

Situations	…had an additional Rs. 250	… wanted something tasty	…wanted something healthy	…very hungry	… had little time to prepare
DESCRIPTIVES
Chose a Local Item and Stayed with a Local Item	19.4%	41.8%	45.2%	42.6%	36.3%
Chose a Local Item and Switched to a Non-Local Item	80.6%	58.2%	54.9%	57.4%	63.7%
MODELS	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)
Food Groups (Ref: Cereals & Pulses)
Fruit & Vegetables	1.49 (0.57,3.94)	3.33 (1.51,7.33) **	0.94 (0.45,1.95)	1.69 (0.80,3.57)	1.62 (0.75,3.53)
Snacks	0.67 (0.26,1.72)	1.27 (0.69,2.71)	0.48 (0.23,0.99) **	0.89 (0.43,1.85)	0.61 (0.28,1.31)
Animal Products	1.06 (0.45,2.50)	2.13 (1.04,4.39) **	0.57 (0.29,1.10) *	1.33 (0.67,2.61)	0.78 (0.39,1.59)
Oils, Sweeteners, Condiments	0.42 (0.18,0.99) **	1.20 (0.59,2.45)	0.77 (0.39,1.51)	0.87 (0.44,1.72)	0.55 (0.27,1.13)
Drinks	0.71 (0.29,1.73)	0.48 (0.24,0.99) **	0.55 (0.28,1.10) *	0.71 (0.35,1.42)	0.49 (0.24,1.03) *
Gender (Ref: Female)
Male	0.78 (0.39,1.55)	0.72 (0.41,1.26)	0.92 (0.54,1.57)	1.16 (0.67,1.99)	0.74 (0.42,1.31)
Age (years)	1.30 (1.09,1.56) **	1.10 (0.95,1.27)	1.04 (0.91,1.19)	1.17 (1.02,1.34) **	1.16 (1.01,1.35) **
Household Occupation (Ref: Other)
Agriculturally based	0.77 (0.37,1.58)	1.57 (0.86,2.87)	0.90 (0.52,1.59)	1.24 (0.70,2.21)	1.73 (0.93,3.21) *

^a**p < 0.01; * p < 0.05

^bChose a Local Item and Stayed with a Local Item: Most frequently reported a local food and across all food groups reported choosing a local food when given different scenarios

^cChose a Local Item and Switched to a Non-Local Item: Most frequently reported a local food and changed to a non-local food item in at least one food group when given different scenarios

^dEach column is its own logistic regression model

^eEach model includes the full sample (n 237)

^fMain Predictors are dummy-coded food groups with cereals and pulses as the reference; covariates include gender, age, and family occupation

^gN = 237

Adolescents were more likely to change from local to non-local foods based on wanting something tasty for fruits & vegetables and animal products. Adolescents were less likely to change from local to non-local foods when thinking about healthy items for snacks, animal products, and drinks. Under the choice of being hungry, adolescents did not change from local to non-local foods no matter the food group being considered.

Factors Associated with Switching versus Maintaining Preferences for Local or Non-Local Foods

Table 5 reports the odds of switching (local to non-local or non-local to local compared to maintaining) by different hypothetical scenarios. The primary predictor in these models is whether the respondent reported most frequently consuming a local or non-local (national or global) food item. Each model is also adjusted for age, gender, and family occupation. No matter if an adolescent reported most frequently consuming a local or non-local item, adolescents were most likely to switch when asked about fruits & vegetables or snacks. Across all food groups, imagining that they had additional money, adolescents who most frequently consumed a local item had higher odds of switching compared to adolescents who most frequently consumed a non-local item. Given a scenario of having little time to prepare food, adolescents who most frequently consumed a local item had higher odds of switching to a non-local item compared to adolescents who most frequently consumed a non-local item switching to a local item when considering fruits & vegetables [2.5 (1.04,5.83)] and oils, sweeteners & condiments [4.4 (1.14,17.17)]. Given a situation of wanting something tasty, adolescents who most frequently consumed a local item had higher odds of switching to a non-local item compared to adolescents who most frequently consumed a non-local item switching to a local item when considering fruits & vegetables [10.3 (3.57, 29.68)], snacks [2.3 (0.86,5.91)], and animal products [3.1 (1.02,9.45)].

Table 5.

The Odds of switching from local to non-local or non-local to local by food group based on different hypothetical choice scenarios

	Fruits & Vegetables (%)	Cereals & Pulses (%)	Snacks (%)	Animal Products (%)	Oils, Sweeteners, Condiments (%)	Drinks (%)
	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)
	n 117	n 125	n 125	n 105	n 97	n 142
	Odds of Switching
	from local to non-local or non-local to local (REF: staying local or staying non-local)
Situation: if …
… had an additional Rs. 250
Most Frequently Eaten (Ref: Non-Local)
Local	6.2 (2.44,15.88) **	2.7 (0.86,8.50) *	16.1 (4.39,58.76) **	20.4 (2.50,166.94) **	3.3 (0.83,12.69) *	34.7 (7.84,153.42) **
… had little time to prepare
Most Frequently Eaten (Ref: Non-Local)
Local	2.5 (1.04,5.83) **	1.7 (0.56,5.29)	1.2 (0.51,3.02)	0.3 (0.09,0.71) **	4.4 (1.14,17.17) **	0.1 (0.05,0.26) **
… wanted something tasty
Most Frequently Eaten (Ref: Non-Local)
Local	10.3 (3.58,29.68) **	2.2 (0.66, 7.59)	2.3 (0.86,5.91) *	3.1 (1.02,9.45) **	1.5 (0.48,4.94)	1.6 (0.68,3.59)
… wanted something healthy
Most Frequently Eaten (Ref: Non-Local)
Local	0.7 (0.32,1.73)	0.5 (0.15,1.35)	0.1 (0.04,0.29) **	0.2 (0.06,0.46) **	0.6 (0.18,1.68)	4.0 (1.62,10.03) **
… very hungry
Most Frequently Eaten (Ref: Non-Local)
Local	2.2 (0.94,5.32) *	0.9 (0.27,2.76)	0.4 (0.16,0.88) **	1.0 (0.38,2.76)	1.8 (0.54,5.73)	0.4 (0.18,0.85) **

^a**p < 0.01; * p < 0.05

^bSwitchers: Most Frequently reported eating a local food item and then switched to a non-local food item by food group and situation of purchase OR most frequently reported eating a non-local food item and then switched to a local food item by food group and situation of purchase.

^cStayers: Most frequently reported eating a local or non-local food item and stayed with their choice by food group and situation of purchase.

^dLocal Predictor: Most Frequently ate a local item (1) compared to respondents who most frequently reported ate a non-local item

^eEach cell is its own logistic regression model

^fEach model includes the full sample in its designated column (Ex: All fruits and vegetables models have a sample size of 117).

^gCovariates include gender, age, and household occupation

^hN = 237

Discussion

An important step in understanding how changing food environments can impact nutritional intake is by learning how food choices are made. To contribute to the understanding of globalizing food choices, the present study investigated adolescents’ food choices in a remote village in Southern India and contextualized foods and beverages in three main categories: local, national and global foods. Overall, local and national foods were more frequently seen and consumed than global foods among these adolescents. However, global foods were recognizable and consumed, particularly global cereals, snacks and animal products. Important patterns of food choices were also present under different hypothetical choice scenarios. These findings suggest that in the absence of monetary constraints, rural adolescents would prefer non-local foods. Non-local foods were also perceived to be tastier than local foods, especially for fruits & vegetables and animal products (which included dairy products).

We first evaluated what adolescents ate by looking at items ever seen and ever consumed. Local food items were familiar to respondents and were the most frequently eaten item across food groups. This is consistent with adults from the same region as well as adolescents from a neighboring urban city.^{17, 33} National food items are consistently recognized and consumed. Global items are not consistently seen or consumed. When global items are more frequently chosen, it is within unhealthy food groups (i.e., snacks). The use of a food choice questionnaire helped to identify that food choices differ based on the food group being considered. The results are also consistent with the nutrition transition literature in demonstrating that global energy dense foods like snacks are the global food groups more frequently chosen than other global healthier food groups such as fruits and vegetables.^{34, 35} However, findings also demonstrated that when presented with the scenario of having additional money, 69% of adolescents who reported most frequently consuming a local fruit & vegetable wanted to switch to a non-local fruit and/or vegetable. This may suggest an interest for non-local fruits and vegetables.

These findings underscore that the nutrition transition is no longer solely an urban phenomenon in developing countries and may be shifting to more interior regions of society.^{17, 36} Studies from ten years ago demonstrated that school-going adolescents from higher socio-economic families in the urban cities of Bengaluru,³⁷ Hyderabad,³⁸ and Baroda³⁹ had more global foods, specifically processed foods, fast foods and carbonated beverages in their diets, while rural adolescents across nine states of India had more traditional diets including grains, pulses, and green leafy vegetables.⁴⁰ Although the study doesn’t measure food and nutrient intake of rural adolescents, it identifies access and consumption of global foods. Unhealthy dietary practices and eating habits among adolescents in other areas of the world often involve low consumption of fruits and vegetables,^41–43 high consumption of snacking,⁴⁴ frequent consumption of sugar-sweetened beverages (SSB)^{41, 45} and tendency to skip breakfast^{42, 43, 46–48}, which have exposed adolescents globally to a higher likelihood of adverse health outcomes in their ensuing adulthood.^49–51

Our findings also shed light on what factors may motivate a shift away from local foods among adolescents in rural areas. We know urban adolescents from the same district specifically aspired to try novel foods and, more generally, adolescents are often at the forefront of social change and global trends.⁵² We see parallel findings from a literature review of young consumers (aged 20–40) in urban India with regard to taste and preferences for non-local foods.⁵³ The lack of time to prepare food is also a consistent theme in qualitative interviews about food choices in India. Women 20–35 years old in Delhi highlighted four primary themes that influence food choices for the household: family influence, cultural perceptions, convenience, and habit.⁵⁴ Convenience led to eating out or purchasing more premade foods. These findings outline that lack of time was a reason adolescents who most frequently consumed local food items gave for switching to non-local fruits & vegetables and oils.

Besides the scenario of additional money, we find that the odds of changing to a non-local item depends on what food group is being considered and on the scenario adolescents are presented with. This study demonstrates that the hypothetical choice of non-local food items among adolescents varies by food group, specific external cues and availability of those non-local foods in their place. Beyond the fact that adolescents who most frequently consumed local items have higher odds of switching to a non-local food, adolescents chose to change more often when considering food groups that are often the unhealthy foods (animal products, snacks, and drinks). Note that switching from a local to a nonlocal food item within a food category is dependent on how familiar (ever seen) that adolescent was about that food item. This contributes to our understanding of globalizing food choices.

This study is subject to several limitations. First, we were unable to measure the adolescents’ dietary intake to compare with the food choice measures. While the measures used to assess food choices were developed using formative research in this population, they were exploratory and may not capture all consumption. The choice scenarios used were hypothetical, this study did not observe actual choices made under real life scenarios. The monetary choice scenario was 250 rupees ($3.41 in USD). This amount was chosen for a larger study including an urban site. To provide context, 250 Indian Rupees (INR) in this village is a considerable amount for buying local snacks, fruits, and some beverages for several family members and is the miminum that would be required when purchasing global food items. For example, local bananas cost at 30 INR/kg, local Indian sweets such as laddu are 50 INR / 250 gm compared to a global fruit- kiwi priced at 150 INRfor four kiwis and 30 INR for 1 slice of pizza (prices available upon request). These results are generalizable to a rural village’s population of school-going adolescents in Karnataka state but even so, have larger implications for the nutrition transition literature and the incorporation of global products in more rural areas. Finally, the study was cross-sectional and causal inference is not possible.

Conclusion

There is an awareness and consumption of global foods even among rural adolescents in South India. Specific food choices are complex and are likely influenced by a range of factors, including money, time, tastes, and perceptions. Findings suggest that globalization can also introduce global healthy foods, such as fruits and vegetables, into the diets of adolescents in rural area. Future research should dive deeper into how globalization is impacting the food landscape and diet quality in rural areas.

Appendix

Figure A.2.

Description of Randomization and Survey Questions in the Food Choice Questionnaire

*Specific food item cards shown in Table A.1

Table A.1.

Grid of food items by food groups and categories

Food Groups by Local, National, and Global
FOOD CATEGORIES	A. LOCAL FOOD ITEMS		NATIONAL FOOD ITEMS		GLOBAL FOOD ITEMS
1. FRUITS AND VEGETABLES	BANANA		CORN		DRAGON FRUITS
	BER		POTATO		KIWI
	GREEN LEAFY VEGETABLES (SPINACH/FENUGREEK)		APPLE		BROCCOLI
	LADIES FINGER		ORANGE		RED AND YELLOW BELL PEPPER
2. CEREALS & PULSES	RICE		MULTIGRANE FLOUR		BREAKFAST CEREALS
	MILLETS (BAJRA/JOWAR)		RAJMA		OATS/MASALA OATS
	PEANUTS		CHICKPEAS		BUNS/BREADS
	DAL		OTHER NUTS(ALMOND/PISTA)		PASTA
3. SNACKS	INDIAN SWEETS (LADDU/BARFI/PEDA)		CHIPS		PIZZA/BURGER
	CHAKLI		WADAPAV		PASTRIES
	POHA		CHATS (BHELPURI/PAANIPURI)		NOODLES
	CHIWDA		INDIAN SWEETS (RASMALI/RASAGULLA)		CHOCOLATES
4. ANIMAL PRODUCTS	MILK		KULFI		ICE CREAM
	CURD		CHICKEN/MEAT/SEA FOOD		FLAVORED MILK
	BUTTER / GHEE		CHEESE		FROZEN CHICKEN NUGGETS/PRAWNS
	EGGS		PANEER		CREAM/MILK POWDER
5. OILS, SWEETENERS & CONDIMENTS	SALT		SAUCE		CHILLI SAUCE/DARK SOY SAUCE
	CHATNEY/PICKLES		FRUIT JAM		MAYONAISE
	OILS		MASALA PACKETS		PEANUT BUTTER
	SUGAR JAGGERY		HONEY		SUGAR FREE SWEETNERS
6. DRINKS	TEA/COFFEE		LASSI		ICED COFFEE
	NIMBHU PANI		SOFT DRINKS		DIET SOFT DRINKS
	SUGAR CANE JUICE		COCONUT WATER		ENERGY SPORT DRINKS
	BUTTER MILK		MILK SHAKE		GREEN TEA

Table A.3.

Familiarity and consumption of local, national, and global food items among adolescents in a rural village, Vijayapura, India by gender (n 237)

	Fruits & Vegetables (%)		Cereals & Pulses (%)		Snacks (%)		Animal Products (%)		Oils, Sweeteners, Condiments (%)		Drinks (%)
By Gender	B	G	B	G	B	G	B	G	B	G	B	G
	n 59	n 58	n 58	n 67	n 67	n 58	n 60	n 45	n 55	n 42	n 73	n 69
Ever Seen
Local/Traditional	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0
National/Mixed	100.0	98.3	78.0	80.6	89.4	79.0	75.0	70.0	96.4	90.5	98.6	88.4**
Global/Modern	20.3	17.2	77.6	79.1	86.6	89.7	61.7	66.7	44.0	26.2**	48.7	46.4
Ever Consumed
Local/Traditional	98.3	100.0	100.0	100.0	97.0	100.0	100.0	89.1**	100.0	100.0	100.0	94.2**
National/Mixed	96.6	96.6	64.4	59.7	83.3	71.9	53.3	37.8	80.0	76.2	86.3	76.8
Global/Modern	5.1	1.8	37.9	44.6	56.7	60.3	43.3	46.7	13.0	7.1	12.2	11.6
Most Frequently Eaten
Local/Traditional	72.9	70.7	87.9	86.6	70.2	81.0**	65.0	77.3**	83.3	83.3	70.3	73.9
National/Mixed	27.1	29.3	6.9	7.5	23.9	12.1**	25.0	15.9**	16.7	16.7	27.0	23.2
Global/Modern	0.0	0.0	5.2	6.0	6.0	6.9	10.0	6.8	0.0	0.0	2.7	2.9

^aB – Boys; G – Girls

^b** p < 0.05

Table A.4.

Odds of changing from local to non-local foods by individual factors among adolescents in a rural village, Vijayapura, India, by food group and different hypothetical choice scenarios

Characteristic	Fruits & Vegetables	Cereals & Pulses	Snacks	Animal Products	Oils, Sweeteners, Condiments	Drinks
	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)
Situation: if …
… had an additional Rs. 250
	n 80	n 103	n 93	n 70	n 77	n 102
Sex (Ref: Female)
Male	0.62 (0.22,1.73)	0.39 (0.16,0.95)**	0.43 (0.17,1.06) *	0.61 (0.21,1.77)	1.19 (0.47,3.03)	0.94 (0.41,2.16)
Age (years)	1.33 (1.02,1.73)**	0.89 (0.70,1.12)	1.25 (0.999,1.56)	0.99 (0.76,1.30)	1.04 (0.82,1.31)	1.25 (1.004,1.55)**
Family Occupation (Ref: Other)
Agriculturally based	0.67 (0.24,1.85)	1.07 (0.40,2.90)	0.97 (0.39,2.40)	3.85 (1.33,11.11)**	0.82 (0.31,2.14)	1.29 (0.53,3.13)
… had little time to prepare
	n 83	n 109	n 94	n 72	n 70	n 101
Sex (Ref: Female)
Male	2.77 (1.05,7.34) **	0.42 (0.18,0.94) **	0.59 (0.25,1.38)	0.14 (0.03,0.64) **	0.89 (0.33,2.36)	1.21 (0.40,3.66)
Age (years)	1.03 (0.82,1.31)	1.25 (1.003,1.56) **	1.19 (0.97,1.46) *	1.55 (1.04,2.32) **	0.97 (0.77,1.22)	1.05 (0.80,1.38)
Family Occupation (Ref: Other)
Agriculturally based	2.07 (0.75,5.69)	1.12 (0.46,2.76)	1.28 (0.54,3.02)	2.13 (0.55,8.20)	0.89 (0.33,2.42)	1.70 (0.56,5.19)
… wanted something tasty
	n 84	n 108	n 94	n 73	n 77	n 102
Sex (Ref: Female)
Male	1.21 (0.48,3.08)	0.87 (0.39,1.95)	1.39 (0.60,3.21)	0.82 (0.29,2.25)	0.90 (0.34,2.35)	1.74 (0.75,4.03)
Age (years)	1.03 (0.83,1.30)	0.84 (0.68,1.04)	1.07 (0.88,1.31)	0.92 (0.71,1.19)	1.17 (0.92,1.48)	0.94 (0.77,1.17)
Family Occupation (Ref: Other)
Agriculturally based	1.22 (0.47,3.18)	1.78 (0.73,4.37)	1.72 (0.73,4.03)	2.48 (0.90,6.88)*	0.49 (0.18,1.37)	1.04 (0.44,2.50)
… wanted something healthy
	n 84	n 109	n 90	n 73	n 77	n 102
Sex (Ref: Female)
Male	0.48 (0.19,1.20)	0.80 (0.35,1.85)	3.53 (1.24,10.04) **	1.89 (0.49,7.29)	1.07 (0.42,2.77)	0.61 (0.27,1.37)
Age (years)	1.01 (0.81,1.26)	1.02 (0.82,1.28)	0.80 (0.63,1.03) *	0.66 (0.45,0.97) **	1.06 (0.85,1.34)	1.16 (0.95,1.43)
Family Occupation (Ref: Other)
Agriculturally based	1.35 (0.54,3.41)	0.67 (0.26,1.76)	0.62 (0.22,1.73)	0.45 (0.10,2.03)	0.55 (0.20,1.53)	0.48 (0.20,1.13) *
… very hungry
	n 84	n 109	n 94	n 72	n 69	n 101
Sex (Ref: Female)
Male	1.23 (0.50,3.06)	0.66 (0.28,1.58)	0.97 (0.40,2.37)	0.73 (0.24,2.19)	1.13 (0.41,3.09)	1.69 (0.69,4.17)
Age (years)	1.27 (1.01,1.59) **	1.15 (0.91,1.45)	1.11 (0.90,1.37)	1.08 (0.81,1.43)	1.07 (0.84,1.36)	1.11 (0.88,1.39)
Family Occupation (Ref: Other)
Agriculturally based	0.87 (0.34,2.21)	2.86 (1.15,7.09) **	0.82 (0.33,2.06)	0.81 (0.26,2.51)	0.63 (0.22,1.79)	1.33 (0.53,3.35)

^**p< 0.05

^*p < 0.1

Family Occupation: Either mother or father reported occupation as cultivation, herdsman or agricultural labor, other refers to if both mother and father reported working in other occupations.

Table A.5.

Odds of changing from non-global foods to global foods by hypothetical choice scenarios among adolescents in a rural village, Vijayapura, India (n 237)

Situations	…had an additional Rs. 250	… wanted something tasty	…wanted something healthy	…very hungry	… had little time to prepare
DESCRIPTIVES
Stayed Non-Global	58.2%	73.4%	85.2%	79.3%	68.4%
Changed to Global	41.8%	26.6%	14.8%	20.7%	31.7%
MODELS	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)
Food Groups (Ref: Cereals & Pulses)
Fruit & Vegetables	0.62 (0.28,1.37)	1.10 (0.47,2.61)	1.90 (0.64,5.64)	1.09 (0.44,2.69)	0.66 (0.30,1.47)
Snacks	0.79 (0.37,1.69)	1.28 (0.55,2.94)	1.24 (0.44,3.47)	0.52 (0.21,1.30)	0.39 (0.18,0.88)**
Animal Products	1.08 (0.54,2.17)	1.51 (0.71,3.21)	1.75 (0.67,4.57)	0.70 (0.30,1.59)	0.56 (0.27,1.17)
Oils, Sweeteners, Condiments	0.21 (0.09,0.46)**	0.54 (0.24,1.22)	2.22 (0.84,5.86)	0.51 (0.21,1.23)	0.31 (0.14,0.68)**
Drinks	0.27 (0.13,0.57)**	0.46 (0.21,1.003)*	1.03 (0.40,2.68)	0.56 (0.24,1.29)	0.36 (0.17,0.76)**
Gender (Ref: Female)
Male	0.63 (0.36,1.11)	0.65 (0.35,1.20)	1.71 (0.79,3.70)	0.85 (0.44,1.63)	0.54 (0.30,0.97)**
Age (years)	0.97 (0.84,1.13)	0.92 (0.79,1.08)	0.80 (0.65,0.98)**	1.01 (0.86,1.20)	1.12 (0.97,1.31)
Family Occupation (Ref: Other)
Agriculturally based	1.30 (0.71,2.37)	1.20 (0.63,2.28)	0.57 (0.24,1.37)	1.58 (0.80,3.10)	1.08 (0.58,2.02)

^**p < 0.05;

^*p<0.1

^aStayed Non-Global: Most frequently reported a local or national food and across all food groups reported choosing a local or national food when given different scenarios

^bChanged to Global: Most frequently reported a local or national food and changed to a global food item in at least one food group when given different scenarios

^cEach column is its own logistic regression model

^dEach model includes the full sample (n 237)

^eMain Predictors are dummy-coded food groups with cereals and pulses as the reference; covariates include gender, age, and family occupation

Data Availability Statement:

Data available in the Harvard Dataverse within the Drivers of Food Choice (DFC) Dataverse entitled “DFC in the Context of Nutrition Transition in Indian Households- Vijayapura, India.