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Abstract

Designing effective interventions for achieving desired dietary behavior changes requires an in-depth study of people’s behaviors situated in sociocultural and interpersonal contexts. Guided by the Social Ecological Model, we explored the individual, family, and social-structural-level influences on dietary behaviors related to consumption of fat, sugar, salt, fruits, and vegetables among urban adults in India. We conducted 10 focus groups with a sample of men and women in diverse socioeconomic groups. Data were explored using framework analysis. Social Ecological Model helped in identifying multilevel influences that facilitated or hindered healthy dietary behaviors: Individual-level influences—awareness of dietary recommendations, self-efficacy, risk perception, and perceived benefits and costs; Family-level influences—family members’ preferences, family norms, family support, and the home environment; and Social-structural influences—societal norms, culture, media, cost, availability and accessibility of fruits and vegetables, and government policies. Overall, the findings indicated the need for a range of multilevel interventions that are more likely to promote and sustain healthy dietary behaviors—for example, improving awareness about dietary recommendations (individual level), promoting positive family norms through involvement of family members (family level), and restricting the use of fat, sugar, and salt in packaged food, and supportive policies for promoting consumption of fruits and vegetables (structural level).

Keywords

qualitative research focus group discussion framework analysis thematic analysis noncommunicable diseases (NCDs)dietary behavior intervention development India

Background

Rapid industrialization and urbanization have contributed to dietary changes across the globe (Popkin, 2006), with overconsumption of certain nutrients and underconsumption of certain others. People often fail to meet recommended levels of dietary intake and consume a diet high in fat, sugar, and salt, and low in fruits and vegetables (Hall et al., 2009; Johnson, Praveen et al., 2017; Micha et al., 2014; Sachdeva et al., 2013). This imbalance in nutrient intake is a major risk factor for chronic noncommunicable diseases (NCDs) including cardiovascular diseases, diabetes, and certain cancers (World Health Organization, 2004), which are responsible for more than 70% of the global disease burden (Naghavi et al., 2017).

Globally, the prevalence of risk factors to chronic diseases, like obesity, has grown three fold between 1975 and 2016, at a faster rate in low- and middle-income countries (LMICs) than in high-income countries (HICs) (World Health Organization, 2018). Similar global pattern has been observed for high blood pressure, another major risk factor for NCDs (Zhou et al., 2017).

India is facing a triple burden of malnutrition—that is, coexistence of undernutrition, overnutrition, and micronutrient deficiencies (International Institute for Population Sciences and ICF, 2017; Kshatriya & Acharya, 2016; Meenakshi, 2016; Parternships and Opportunities to Strengthen and Harmonize Actions for Nutrition in India and International Food Policy Research Institute, 2017). Among urban men and women, the prevalence of hypertension is 31% and 26%, respectively, and that of diabetes is 22% and 19% (National Institute of Nutrition, India, 2017). About 5.8 million people, that is, 1 in 4 die every year, from chronic diseases before the age of 70 (Deepti, M., & Ritu, 2015).

Available evidence supports that most chronic diseases are preventable through dietary behavior modifications (World Health Organization, 2011). The Global Strategy on Diet, Physical Activity, and Health (DPAS) emphasized the need to limit consumption of salt, saturated fats, trans fatty acids and sugars, and to increase consumption of fruits and vegetables (World Health Organization, 2004). However, most Indians do not meet the national dietary recommendations for fat, sugar, salt, and fruits/vegetables. Despite decades of nutrition education, the prevalence of unhealthy dietary behaviors is still high (Hall et al., 2009; Johnson, Praveen et al., 2017; Micha et al., 2014; Sachdeva et al., 2013). Therefore, understanding what influences dietary behaviors is paramount for developing effective nutrition education interventions that can lead to sustainable behavior change.

Theoretical models help in understanding determinants of dietary behaviors and increase the likelihood of an intervention to be more effective (Davis et al., 2015; Painter et al., 2008). Trans-theoretical model (TTM) is the most widely used theory, followed by Theory of Planned Behavior (TPB), Social Cognitive Theory (SCT), Health Belief Model (HBM), Self-determination Theory (SDT), and Health Action Process Approach (HAPA) (Davis et al., 2015). However, there is seldom a “one size fits all” solution and no single theory can account for all the complexities of dietary behavior change (Darnton, 2008). Furthermost, most of these theories focus on individual behavior and therefore are difficult to be applied in settings where dietary decision making takes place at the family level (Daivadanam et al., 2015; Wilson, 2010), especially in collectivistic cultures like India. However, the use of theories related to family or community such as the Social Ecological Model that attempts to explain behavior in terms of interactions of influences at various levels (Bronfenbrenner, 1977) seems limited (Painter et al., 2008).

Previous studies from both developed and developing countries identified multilevel influences on dietary behaviors related to consumption of salt, and fruits and vegetables: Structural level (salt reduction public policy, availability and accessibility of fruits and vegetables), Community level (culture, media, and food environment), Interpersonal level (family, friends, and social networks peers), and Individual level (nutrition knowledge & skills, attitudes, self-efficacy, misconceptions, taste preferences, habits, age, health status, occupation, place of living, and socioeconomic status) (Li et al., 2016; Robinson, 2008). Limited literature from rural South India indicates that awareness, attitude, risk perception, decisional balance, societal norms, and accessibility are important factors in influencing dietary behavior (Daivadanam et al., 2014). However, there is a dearth of studies on multilevel influences on dietary behaviors in India. Qualtative research is well suited to have a nuanced understanding of such multilevel influences. Given that this is one among the first few studies on understanding multilevel influences on fat, sugar, salt, fruits, and vegetables consumption among North Indian adults, we conducted a qualitative formative study to explore diverse experiences and perspectives (Brink & Wood, 1998). The findings of this formative research were intended to inform the designing of a culturally acceptable nutrition education intervention for improving dietary behaviors of people between the ages 35 and 70 years who participated in a randomized controlled trial (RCT) called “SMART Eating,” carried out in Chandigarh, a Union Territory in North India (Kaur et al., 2018).

Methods

Design and Sampling Procedure

Using qualitative exploratory design, 12 focus group discussions (FGDs) in three socioeconomic groups (i.e., four FGDs per socioeconomic group) in Chandigarh, a North Indian city, were planned based on a commonly cited guideline for estimating sample size requirement in focus groups (Guest et al., 2016). We used the type of housing assigned by the Chandigarh city administration (LIG: low-income group, MIG: middle-income group and HIG: high-income group) as a proxy for socioeconomic status. To have homogeneous focus groups, we further stratified the socioeconomic groups by age and gender to explore age- and gender-specific influencers. Therefore, we planned FGDs with adult men and women separately in two age groups, that is, 35 to 60 years and above 60 years. The study participants for FGDs were recruited with the help of influential people in the local communities. FGD participants from the HIG community were recruited with the help of President of Residents’ Welfare Association, and volunteers from Senior Citizens’ Council. And FGD participants from the LIG and MIG communities were recruited with the help of three Auxiliary Nurse Midwives (ANMs) from the dispensary, and eight Anganwadi workers of Integrated Child Development Services (ICDS) Program, who take care of the nutritional status of children under 6 years of age and their mothers.

Data Collection

The FGDs were conducted between July and November 2014. Although we planned 12 FGDs we could only conduct 10 FGDs as presented in Table 1. All FGDs, except one, were homogeneous in terms of the age group and gender. As the first author used to draft notes from the FGDs on the same day of conducting FGDs, it was realized that no new information was forthcoming after 10 FGDs. Therefore, considering the redundant information (Saunders et al., 2018) and resource constraints, we stopped data collection.

Table 1.

FGDs Conducted in Different Subgroups.

Subgroups	FGDs (N = 10)
Socioeconomic status
Low-income group (LIG)	4
Middle-income group (MIG)	4
High-income group (HIG)	2
Age groups
35–60 years	5
>60–80 years	5
Gender
Men	4
Women	5
Men and women	1

Note. FGDs = focus group discussions.

Of the total 10 FGDs, four FGDs were held at the residences of participants, two in parks, two in public meeting places, one in an anganwadi (a government-supported child-care center), and one in a religious place (Sikh Temple). A total of 53 participants participated in all FGDs (Table 2), with five to seven individuals in each FGD. The FGDs were conducted by the first author and two other trained investigators. The duration of FGDs ranged from 30 minutes to 1 hour. A semistructured FGD guide (Supplementary File 1) was used to explore potential multilevel influences on dietary behaviors such as knowledge, awareness, perceptions, self-efficacy related to dietary consumption; and to identify barriers to and facilitators of desirable behavior change. FGDs were audio-recorded after obtaining written consent and a note-taker took detailed notes simultaneously.

Table 2.

Socio-Demographic Profile of FGD Participants.

Characteristics	N = 53n (%)
Age group
35–60 years	25 (47)
60 and above	28 (53)
Gender
Men	23 (43)
Women	30 (57)
Education
Illiterate	8 (15)
Primary (1st–4th)	7 (13)
Secondary school (5th–8th)	5 (9)
Higher secondary School (9th–12th)	12 (23)
University degree and above	21 (40)
Occupation
Govt. employees	5 (9)
Business	6 (11)
Homemaker	30 (57)
Retired	12 (23)
Type of housing
Low-income group (LIG)	23 (43)
Middle-income group (MIG)	20 (38)
High-income group (HIG)	10 (19)

Note. FGD = focus group discussion.

Data Analysis

The audio recordings were transcribed in Hindi (local language) and translated into English before data analysis. Based on the Social Ecological Model (Bronfenbrenner, 1977) and previous research about dietary consumption behaviors (Daivadanam et al., 2014; Li et al., 2016; Robinson, 2008), we anticipated that influences on dietary behaviors related to consumption of fat, sugar, salt, fruits, and vegetables might occur at individual, family, and social-structural levels. Data were analyzed using narrative thematic analysis (Riessman, 2008) informed by framework analysis approach (Pope et al., 2000; Ritchie & Lewis, 2003) and techniques derived from grounded theory approach (Holton, 2010). Guided by the Social Ecological Model, a coding framework was developed based on “a priori” codes derived from the topic guide and empirical literature (Daivadanam et al., 2014; Engbers et al., 2006; Henry et al., 2006; Nakamura et al., 2017; Prochaska & Velicer, 1997). Then, as the focus group data were explored, new data-driven codes (emergent codes) were identified and added to the list of predetermined coding framework, and both “a priori” and emergent codes were used for further coding. Two analysts, one with several years of experience in qualitative data analysis in nutrition and another analyst with 3 years of qualitative research experience, checked and discussed the final coding framework. Differences in coding were resolved by discussion and consensus. After coding all the translated text, a spreadsheet was used to prepare data matrix to facilitate constant comparison of influences across subgroups and within subgroups (age, gender, and socioeconomic status). For the purpose of referring to the quotes while presenting findings, the age stratification of <60 years and >60 years is used instead of 35 to 60 years and above 60 years.

Results

Sociodemographic Characteristics of FGD Participants

The mean age of participants was 56 years (age range: 35–80 years). About 40% of participants had completed a university degree and 15% were illiterate. All women participants were homemakers and almost half of the men (n = 12) were retired and others were employed or engaged in business (Table 2).

Influences on Dietary Behavior

Given that the Social Ecological Model served as the framework for analysis, findings are summarized at three levels—individual, family, and social-structural-level influences on individual, and family and social-structural-level influences on dietary behaviors (Robinson, 2008).

Individual-Level Influences

We found that individuals’ knowledge and awareness influence their self-efficacy and perception about benefits and costs of engaging in a particular behavior change. In addition, behavior seemed to be moderated by personal characteristics such as age, gender, socioeconomic status, and health status.

Awareness about dietary recommendations

Across all the focus groups, participants were not aware of the recommended amount of fat, sugar, salt, fruits, and vegetables to be consumed per day. Most women attributed this lack of knowledge to the lack of exposure to information and stereotyped roles of women being homemakers in Indian society; however, lack of exposure to information was expressed by men as well:

“We do not know how much is actually required” (FGD1, LIG-W, >60 years); “As we people stay at home, we have neither been told nor taught [by others-health workers] about how much [oil, sugar, salt] is to be taken” (FGD8, MIG-W, <60 years); “We don’t have any idea, neither we were told nor we asked anybody” (FGD5, HIG-M, >60 years).

Across all the focus groups, none of the participants reported measuring the oil, sugar, or salt being used and consumed, though they used spoon for sugar and bottle for oils and could have estimate for sugar and oil but for salt it was for taste and they keep on adding till it satisfies them:

We never measure the quantity, so we don’t have any idea of how much we use, we just go by the estimate. We directly pour oil from the bottle into the pan for cooking. (FGD5, HIG-W, >60 years)

Not knowing about dietary recommendations and not measuring the quantity of fat, sugar, and salt seemed to have contributed to participants’ uncertainty about the adequacy of their dietary intakes; none were sure whether their fat, sugar, and salt intakes were low, high, adequate or just right:

“It is not that we measure to eat, we just eat by estimate . . . it is adequate” (FGD2, LIG-M, >60 years); “All have their own idea, we don’t know” (FGD3, MIG-W, >60 years); “More fat . . . more salt . . . less sugar (FGD4, MIG-M, >60 years); “Normal fat . . . sugar . . . salt” (FGD9, MIG-M, <60 years); “We use less fat . . . less sugar . . . less salt” (FGD10, HIG-W, <60 years).

In contrast to their uncertainty in the adequacy of intake of fat, sugar, and salt, the majority of the LIG and MIG participants perceived their fruit and vegetable intake as low, and HIG participants perceived it as adequate or high. Similarly, men compared to women perceived their intake as high. Furthermore, the perception about adequate intake was apparently based on their taste preferences and habits:

“I like sugar/sweets . . . I do take more”; “I like adding salt on fruit, so I do take salt” (FGD3, MIG-W, >60 years); “We take salt as per our taste” (FGD9, MIG-M, <60 years); “We eat limited fruit . . . actually we are not habitual of eating fruit” (FGD4, MIG-M, >60 years).

Attitude toward packaged food and eating out

Packaged food was perceived as “not good” for consumption and “harmful” for health because of the presence of preservatives, made of fine refined wheat flour containing starchy part of the grain, and the quality of oil being used during preparation. Only one participant expressed that packaged food contain more amount of salt:

“They [packaged food] contain lot many preservatives like [brand name] . . . chips . . . namkeen are not good”; “They are made of ‘maida’ [refined wheat flour]” (FGD8, MIG-W, <60 years); “They are most harmful, we don’t know about the quality of oil being used in them” (FGD9, MIG-M, <60 years); “They are high in calories” (FGD1, LIG-W, >60 years); “The salt content in Chips [brand name of an Indian packaged snack] is very high” (FGD4, MIG-M, >60 years).

As packaged food was perceived as “harmful” some people restricted its consumption to special occasions only: “We eat such items only occasionally like when we visit someone” (FGD9, MIG-M, <60 years); “It sometimes happens during festive days like Diwali [Indian festival] when people exchange biscuits [gift packs]” (FGD1, LIG-W, >60 years).

On the other hand, the perception of indigenous food as “not harmful” was responsible for high intake of salty and fried foods: “Mathi [deep fried Indian snacks item] contains less amount of oil, there is no harm in consuming such things” (FGD4, MIG-W, >60 years).

Similarly, eating out was also perceived as “undesirable” and “unhealthy” because of the perception that road-side and certain restaurants’ food being unhygienic and high in salt, oil, and spices:

“It [food] is fried”; “It is unhygienic, spicy and heavy” (FGD1, LIG-W, >60 years); “We don’t like it [eating out] as it is spicy, we don’t know what all is used in them” (FGD2, LIG-M, >60 years); “It contains more spices and oil . . . they add extra for enhancing the taste” (FGD8, MIG-W, <60 years); “It [food] is usually high in salt . . . the quality of spices used is also not known . . . the amount used is also not clear. It tastes good but not healthy” (FGD10, HIG-W, <60 years).

The perception of eating out being “unhealthy” contributed to healthy dietary behaviors:

“We rarely eat out . . . it [food] is too spicy” (FGD7, LIG-M, <60 years); “Even if I have to travel, I carry home-made food along with me. I never prefer eating at any dhabha [food outlet]”; “Everybody has his/her own ways. We all are senior citizens, all have fixed diet, eat less, sometimes go to the hotel, prefer eating dal [pulses] in dinner . . . ignore eating out.” (FGD4, MIG-M, >60 years).

Some people reported eating out frequently but preferred healthier choices over unhealthy ones:

We do eat-out frequently, almost twice a week . . . I always like grilled food, avoid fried and we take soup . . . corn or chicken soup. We ask for simple food . . . pulses with chapatti or ask them [waiter] to bring boiled food . . . prefer very low salt food . . . if we want to have chicken . . . then grilled only. (FGD10, HIG-W, <60 years)

Eating out, despite being perceived as “not healthy,” was frequently reported because of certain reasons such as the need to attend social events and being perceived as time saving activity:

“I am working in hotel and take meals there” (FGD2, LIG-M, >60 years); “I always eat out on regular basis . . . even always having lunch from outside during office work days” (FGD7, LIG-M, <60 years); “I have to keep going out for office affairs, so it is almost 10-12 days in a month” (FGD9 MIG-M, <60 years); “Those who are working, they bring [food] from outside and it saves their time” (FGD 10, HIG-W, <60); “In wedding functions we have to eat whatever is there. We have been eating food in wedding functions too frequently for the last month” (FGD2, LIG-M, >60 years).

Self-efficacy in adapting healthy dietary behaviors

Habits die hard and temptations seemed to have greater influence on one’s self-efficacy. Furthermore, personal preferences were also found to be responsible for low-self-efficacy:

“We are habitual of eating these things [snacks] since childhood; it is very difficult to change these habits. Even if we do so, we would do it hardly for 1-2 days and will stop by third day”; “We follow diet chart provided by the doctor for 5-7 days, then again return to same level” (FGD4, MIG-M, >60 years); “All in our family are habitual of taking snacks with tea” (FGD3, MIG-W, >60 years); “Our children like eating parantha [fried layers of dough] in routine, we can’t stop them and they should be allowed to eat” (FGD1, LIG-W, >60 years).

Low self-efficacy in adapting healthy dietary behaviors could be related to the lack of awareness about the dietary recommendations and lack of skills in measuring the amount of fat, sugar, and salt used in food. Self-efficacy also depends on the availability of time to engage in healthy behaviors. Urbanization, modernisation, and busy lifestyle seemed to have influenced one’s ability to concentrate on healthful activities:

We don’t have time to eat fruit as we leave early and come back late in the evening. (FGD8, MIG-F, <60 years)

Risk perception

Health status affects the risk perception, which differs on the presence or absence of lifestyle diseases such as heart disease, hypertension, and diabetes. For example, those suffering from diabetes restricted intake of certain food, including fruits, which they perceived as having high sugar content: “We take limited fruit, as with fruit my sugar level goes up so I don’t take fruit”; “I don’t eat fruit as I have sugar [diabetes]” (FGD4, MIG-M, >60 years); “I have sugar [diabetes], so I don’t take sugar” (FGD3, MIG-W, >60 years).

Although the perception of increased susceptibility or risk is linked to healthy behaviors; however, it does not always happen. For example, a younger participant said: “I am diabetic but at times take something sweet” (FGD9, MIG-M, <60 years). On the contrary, irrespective of the age, gender, and socioeconomic status, those not suffering from such diseases did not limit their intake of fat, sugar, and salt:

“We take a lot of sugar, do not pose any restrictions, by God’s grace my blood sugar level is ok” (FGD5, HIG-M, >60 years); “I am 60 years old, take every sweet thing, also take more sugar, I don’t bother about it, it doesn’t harm me, everything is alright, I am healthy, neither diabetic nor suffering from any other disease” (FGD7, LIG-M, <60 years); “All in our family think different . . . say that I am not suffering from any disease . . . why should I change” (FGD10, HIG-W, <60 years).

Perceived benefits and costs

For some people of lower socioeconomic status, meeting the basic need of food (meals) was the priority; and they could not afford adequate amount of fruits and vegetables in diet:

“We are not like rich people who consume [fruit] unlimited”; “How would poor people manage . . . when the potato is also 50 rupees per kg . . . government is not paying any attention to ever increasing price of fruits and vegetables . . . many people go to bed empty stomach every night . . . who cares for them?”; “If someone has 10 members to feed and single breadwinner . . . he would think a lot [for vegetables and fruits]” (FGD6, LIG-W, <60 years); “Vegetables are prepared at least once daily . . . fruit is bought only when pocket allows . . . although we know fruits should be consumed” (FGD2, LIG-M, >60 years).

In contrast, other participants from low socioeconomic background had different opinion. They considered that reducing fat, sugar, salt consumption, and increasing fruit and vegetable consumption would be beneficial for them in preventing certain diseases: “Yes it’s good, we poor people comparatively tend to suffer from diseases more frequently than rich people, it would be useful for us” (FGD6, LIG-W, <60 years).

In contrast to LIG participants, majority of the MIG and HIG participants reported no issues in increasing the consumption of fruits and vegetables:

“No, we don’t have any problem in increasing the consumption of fruits and vegetables . . . whether expensive or cheap, if we have to eat we have to, cost doesn’t matter” (FGD3, MIG-W, >60 years); “Yes, no problem in doing so” (FGD4, MIG-M, >60 years); “We eat vegetables liberally; vegetables are prepared daily” (FGD5, HIG-M & W, >60 years).

However, like LIG, some of the MIG and HIG participants also attributed high cost of fruits and vegetables as a barrier for improving consumption:

“Fruits are too expensive to be consumed, same is the scenario for vegetables”; “The price of fruits is too high, how to take the adequate amount?” (FGD9, MIG-M, <60 years); “At least seasonal fruits can be eaten . . . they are cheaper” (FGD8, MIG-W, <60 years; “It depends on our pocket . . . also depends on market rate [of fruit and vegetables], if cheaper then we consume more” (FGD5, HIG-W, >60 years).

Family-Level Influences

At family level, family norms, preferences of family members, support from family members, and home environment play a very important role in shaping dietary behaviors.

Family norms

It seemed that the prevalent family norm is not to proactively restrict fat and sugar intake:

“We take more sugar without any restriction” (FGD5, HIG-M, >60 years); “We take ‘Ghee’ without control as much as we wish” (FGD2, LIG-M, >60 years).

In general, the norm in the study area is to take more “Desi Ghee” (clarified butter), and it has always been considered good for health as it is seen as “desi” (indigenous).

Preferences of family members

Personal preferences especially of children were reflected in routinely consumed food that is high in fat, sugar, and salt such as snacks, fast food, and pickles:

“It is very difficult to convince children . . . they don’t like food low in salt . . . they are also very fond of sugary food” (FGD3, MIG-W, >60 years); “Now-a-days kids are very fond of pizza or similar type of food” (FGD8, MIG-W, <60 years); “Children usually consume chips [brand name of an Indian packaged snack]” (FGD9, MIG-M, <60 years); “We take biscuits and namkeen [savoury snacks] with tea every morning (FGD5, HIG-W, >60 years).

Taste was commonly reported to influence the choice of food, across all focus groups:

“Each one in the family has his/her own taste . . . some prefer more and some prefer less, if salt is less in the vegetable . . . they [children] don’t eat” (FGD3, MIG-W, >60 years); “Food low in salt and sugar does not taste good” (FGD7, LIG-M, <60 years); “We take pickle with meals regularly, at-least once in the morning” (FGD6, LIG-W, <60 years).

Support from family members

It seemed that family members have an important role in shaping dietary behavior of each other through motivation for adapting healthy behaviors: “My wife adds ghee while taking [her] meals, I always tell her not to take more” (FGD5, HIG-M, >60 years); As well as imposing restrictions on unhealthy behaviors: “My husband is fond of sweet items but we don’t allow him to take more” (FGD5, HIG-W, >60 years).

On the contrary, lack of support from the family members was perceived as a major barrier to initiating healthy dietary behaviors:

“Now-a-days nobody listens to anyone in the family . . . everyone eats according to their own wish . . . (FGD4, MIG-M, >60 years); “In our family, if we say no for anything, our daughter-in-law doesn’t like it . . . she feels like as if we are doing it deliberately for the sake of money . . . she doesn’t listen, what we can do? . . . it’s really very difficult to motivate children [daughter-in-law] . . . they would say about me that neither she eats nor lets us eat” (FGD1, LIG-W, >60 years).

Some of the older people expressed the need for support from family members in reminding them of what to eat and when to eat: “Taking medicines is difficult; controlling diet becomes even more difficult. There should be an assistant who can tell us that you have to eat this thing now” (FGD4, MIG-M, >60 years). However, a younger participant desired the company of others for initiating healthy eating habits: “I don’t like eating [fruit] alone” (FGD6, LIG-W, <60 years).

Home environment

Availability of healthy food in the house also influenced healthy eating behavior: “If available at home [fruit] . . . we tend to eat . . . if not, nobody would ask” (FGD2, LIG-M, >60 years); “If available at home we eat [fruit]”; “Not in routine . . . if kept on the table, we take one or two pieces” (FGD5, HIG-W, >60 years).

Social-Structural Influences

Societal norms

Women being “main chef” of the family were perceived to have both power and responsibility in deciding or sustaining healthy behaviors, was a common theme among all the focus groups in relation to behavior change at family level:

“Women are responsible for cooking in the family, because they work at home, all this [fat, sugar, salt] can be reduced, they can use less while cooking” (FGD2, LIG-M, >60 years); “Information should be given to females . . . they are the ones who cook food” (FGD3, MIG-W, >60 years); “Wife is responsible for everything . . .” (FGD5, HIG-M, >60 years); “Those who have to cook food, should be made aware” (FGD10, HIG-W, <60 years); “Ladies should be made aware . . . they work in the kitchen” (FGD9, MIG-M, <60 years).

Religious norms also play an important role: “As I go to Gurudwara sahib [Sikh temple] daily I take ‘Halwa’ [Indian fried sweet-dish with high fat content] daily” (FGD7, LIG-M, <60 years).

Culture

Participants reported eating more during festivals, social functions, and while attending to guests: “During festival days and wedding season quantity [fat, sugar, salt] gets increased considerably” (FGD4, MIG-M, >60 years). While attending to guests efforts are to serve multiple snacks and dishes often high in fat, sugar, and salt: “If guests are there at home then also we tend to consume more of these things [fat, sugar, salt]” (FGD9, MIG-M, <60 years).

Social and cultural symbolism seemed to be another important influencer. For some people among MIG and HIG, consuming more “Desi ghee” was viewed as a status symbol:

“Theory of ‘Desi Ghee’ among Punjabi people is that Punjabi people can’t do without ‘Desi ghee’ [clarified butter]”; “We can demonstrate drinking milk with ghee added to it” (FGD4, MIG-M, >60 years); “We are very fond of consuming ghee with meals I can demonstrate drinking ‘Desi ghee” (FGD5, HIG-M, > 60 years).

Majority tends to consume more fried and sweet food items during winter season: “We like eating parantha and the season will start now in the winters” (FGD8, MIG-F, <60 years).

Influence of media

Social media seemed to have an important bearing on dietary habits. Packaged, ready-to-eat food products are often portrayed by the media as useful in terms of being tasty:

These days, media is affecting our thinking very badly. Advertisements are showing usefulness of ready-to-eat food products, not even a single advertisement tells how harmful are they? So children also don’t listen to us, they also like chips, kurkure [junk food] and similar kind of things. (FGD9, MIG-M, >60 years)

Perceived need for policies that facilitate healthy food production and healthy eating behaviors

Concerns about unrestricted use of pesticides and insecticides, and the use of harmful injections to increase the size of fruits and vegetables, seemed to have influenced some participants to avoid consuming fruits and vegetables:

“What can we eat these days when everything is adulterated with harmful injections? Be it injection or fertilizer . . . it is not like old days when everything was pure . . . nothing can be consumed raw now-a-days” (FGD4, MIG-M, >60 years); “We are always in a doubt that vegetables are all sprayed with pesticides and insecticides . . . even the cauliflower which we purchase from vegetable market tastes bitter” (FGD8, MIG-W, <60 years); “Injections are used to grow vegetables, all contain urea . . . we are scared of eating them” (FGD 2, LIG M >60 years).

Some participants demanded the need of having restrictive policies to limit the use of fertilizers, insecticides, and pesticides. They expressed that their concern should be conveyed to the government:

“Government should do something . . . vegetables are grown with medicines . . . ghiya [gourd] is grown to 1 kg with injection . . . this is all wrong . . . it is happening everywhere across the globe . . . corrective measures should be taken . . .” (FGD2, LIG-M, >60 years); “Can you convey our message to the government that food adulteration and use of fertilizers should be reduced” (FGD9, MIG-M, >60 years).

Many LIG participants demanded supportive policies for improving the consumption of fruits and vegetables. They expressed that fruits and vegetables should be made available to them at subsidized rates:

“Fruits are too expensive to be consumed; same is the scenario for vegetables. Government should open such stores where poor people get commodities [fruits and vegetables] at subsidized rates” (FGD2, LIG-M, >60 years).

Availability and accessibility

Fruits and vegetables were available in the study areas through street vendors and local vegetable markets. These were quite accessible to the participants:

“Yes, we do get these [fruits and vegetables] at our doorsteps through vendors” (FGD1, LIG-W, >60 years); “Yes, vendors do come to our streets on routine basis, we also have local vegetable markets on fixed days, and availability is not at all a problem” (FGD8, MIG-W, <60 years); “Fruits and vegetables are easily available from grain market” (FGD5, HIG-M, >60 years).

Availability of fruits and vegetables in the area close to their living place thus seemed to facilitate adequate consumption.

Discussion

In this qualitative study among urban Indian adults, we identified several interconnected individual, family, and social-structural-level influences on dietary behaviors (Figure 1). These findings indicate that individuals alone may not be able to adapt healthy dietary behaviors without family support given that food cooked at home is consumed by all members of the family. Similarly, family food habits were found to be strongly influenced by the prevalent social norms and cultural practices regarding food consumption. Thus, this conceptual model derived from this study, informed by the Social Ecological Model, seems to be useful in understanding the complex interplay of multilevel influences on dietary behaviors among urban Indian population. Given that studies have predominantly reported individual-level influences on dietary behaviors, this study contributes to the limited literature on the family and social-structural-level influences on dietary behaviors to develop context-specific interventions. Only one qualitative study conducted in a rural South Indian setting has reported several factors that influence dietary behaviors, although they did not explicitly state the levels of influence of those factors (Daivadanam et al., 2014). In contrast, this study, using Social Ecological Model, explicitly identified multilevel influences on dietary behaviors in an urban North Indian setting.

Figure 1.

A conceptual model of the multilevel influences on dietary behaviors.

Of the identified socio ecological influences—some are common across the subgroups and some are subgroup-specific. The common influences on dietary behaviors, irrespective of age, gender, and socioeconomic differences are as follows: lack of knowledge about dietary recommendations; lack of measurement of the amount of fat, sugar, and salt used in cooking; frequent consumption of packaged food; frequent reporting of eating out; use of insecticides, pesticides and harmful injections on fruits and vegetables; and the role of women being “main chef” of the family.

We also found some differences in the reported influences on the basis of age group, gender, and socioeconomic status. The need for family support, a family-level influence, was expressed by older adults. High cost of fruits and vegetables was a major concern for those from LIG, when compared to those from MIG and HIG. Perceptions about the adequacy of dietary intakes too differed by age, gender, and socioeconomic status.

Lack of adequate knowledge about recommended dietary intakes of fat, sugar, salt, fruits, and vegetables was found to be a key individual-level influence. None of the participants in this study, even those who are educated and from middle- and high-socioeconomic classes, were aware of the recommended amount of fat, sugar, salt, fruits, and vegetables, which is consistent with the findings from a qualitative study from rural South India (Daivadanam et al., 2014) and quantitative studies from Western countries where more than 80% of participants reported nescience about maximum salt limit (Wicaksana, 2017). In contrast to the findings of this study, knowledge about recommended salt intake was higher in quantitative studies both from India (Johnson, Mohan, et al., 2017) and Western countries (Webster et al., 2016). None of the participants in this study reported measuring the amount of fat, sugar, and salt being used in cooking, a finding not reported before from India.

Like other studies, participants in our study attributed taste preferences and habits developed over the years for consuming higher amount of salt, sugar, and oily food (Pesantes et al., 2017). Similarly, working people attributed lack of time for not eating fruits and vegetables as they spend whole day out at work. In contrast, previous studies did mention that time consuming vegetable and fruit preparation are often avoided (Daivadanam et al., 2015).

This formative research confirmed that food decision making occurs at family level and all family members consume the food already prepared at home (Daivadanam et al., 2014). Like other studies, our findings demonstrated the importance of context in which food is consumed and emphasized that it is not feasible for an individual to bring change in his or her dietary behavior alone (Foster et al., 1994). Importance of support from family members was quite evident. If any member in the family was suffering from lifestyle diseases, then other family members were more careful in reminding them of healthy eating (Daivadanam et al., 2014; Li et al., 2016). Although desire for the company of others for initiating healthy dietary behaviors came from only one young participant, it could be true for all other subgroups, considering the collectivistic culture in India (Sinha et al., 2004). We also noted that key family members influenced the dietary behaviors across subgroups. Consistent with other studies, participants of this study highlighted the difficulty in asking children to avoid eating unhealthy food (snacks and junk food) and to take more fruits and vegetables which influenced their self-efficacy (Daivadanam et al., 2014; Li et al., 2016). Like other studies, home environment, for example, the presence of fruits and vegetables at home, was found to have influence on healthy food consumption (Springvloet et al., 2014).

Given that Chandigarh has people from several nearby states of India, the influence of diverse cultural practices in India on dietary behaviors was well reflected in this study findings. Diets that are rich in fat, sugar, and salt (samosa, namkeen, and processed food including biscuits) are consumed on a routine basis. Similarly, pickles are consumed with regular meals. These findings are in agreement with those reported by other researchers (Dhemla & Varma, 2015; Li et al., 2016). Taste preferences and collectivistic culture influence dietary behavior at the family level.

Social norms regarding the role of women are well documented in literature. Women are often portrayed as responsible for both food purchase and preparation (Rolnick et al., 2009). We noted that even in HIG where there were domestic helps/cooks, the cooking was instructed and supervised by the family member in-charge of food decision making; thus, women being the “main chef” of the family could be a key facilitator for dietary behavior change of the entire family. Easy availability of fruits and vegetables in local markets and through street vendors, and accessibility to markets were other facilitators in this study; inaccessibility to markets was noted as a barrier for health dietary behaviors in rural south Indian setting (Daivadanam et al., 2014).

Cost and affordability have great influence on decisional balance making healthier choices. This study indicated that fruits and vegetables are perceived to be expensive. All participants irrespective of their age, gender, and socioeconomic status held this view. In addition to cost, use of insecticides, pesticides, and harmful injections to increase the production of fruits and vegetables was a major concern highlighted by study participants for adapting healthy dietary behaviors. Such concerns have influence on home environment making healthy food unavailable. Another important barrier to engage in healthful activities was winter season. In winters, irrespective of their disease condition, people want to overindulge in food rich in fat often high in salt and sugar—given the general belief reflected by many cultures that fried foods, oil, butter, ghee, honey, coffee, tea, beef, mutton, chicken, and organ meat are hot foods (Inam et al., 2003).

Implications for Practice and Policy

Effective nutrition education for reducing dietary intake of fat, sugar, and salt, and improving fruit and vegetable intake needs careful understanding of the multilevel influences on these behaviors. Findings suggested that efforts should be made to translate written documents of dietary guidelines into practical applications for increasing awareness about recommended dietary intakes of fat, sugar, salt, fruits, and vegetables. The interventions should focus on increasing awareness about the benefits of adapting healthy dietary behaviors; on improving risk perception related to chronic diseases; developing food measurement skills; and enhancing self-efficacy on healthy food consumption. Present study findings also indicated the need of involving family members, especially children and identifying the target audience for intervention implementation—a person from the family responsible for cooking. All of these key components identified from this formative research were useful in the development of a comprehensive “SMART Eating” health promotion intervention (Kaur et al., 2018). Our findings highlighted the need to focus on reduction of fat, sugar, and salt, activities that do not involve money and thus feasible and acceptable to be implemented even among LIGs.

Demand for supportive policies was particularly relevant to fruit and vegetable consumption particularly among the underprivileged. Such concerns raised the need for supportive policies by the government which could include policies on food pricing, portion size, and explicit labeling of contents of packaged food items, and policies that support farmers to produce organic fruits and vegetables, and to promote kitchen gardening in earthen pots or in front lawns, wherever possible.

So far, a majority of the interventions from other countries had focused on individual-level behavior change and only one study in India implemented intervention at the household level (Daivadanam et al., 2013). However, individuals need family support for adapting healthy dietary behaviors, which was evident from the preferences reported by family members toward unhealthy food.

National salt reduction programs are being implemented in most of the countries toward achieving the global targets of a 30% reduction in mean population salt intake and a 25% reduction in the prevalence of raised blood pressure by 2025 (Trieu et al., 2015), against a baseline in 2010 (World Health Organization, 2013). National salt reduction program is being finalized in India (Johnson et al., 2014). Separate national programs on reducing sugar and fat, and increasing fruit and vegetable consumption have not been conceived or initiated as yet in India. Therefore, the study may have implications for development of separate or integrated programs on improving the intake of fat, sugar, salt, fruits, and vegetables. A nationwide implementation of such a program could have a large impact on reducing population fat, sugar, and salt intake, and increasing fruit and vegetable intake—thereby reducing the health burden due to NCDs and micronutrient deficiencies.

Limitations and Strengths

The use of qualitative methods and purposive sampling limits the generalizability of the study findings, an inherent limitation of qualitative research. Despite this, the concepts identified from this study could be transferred to other similar settings in urban North India. Thus, the findings have transferability or analytical generalizability. In-depth data on experiences and perspectives of the participants as well as the use of Social Ecological Model helped in developing a feasible, culturally acceptable multilevel intervention to adapt health dietary behaviors. It is possible that social desirability bias may be present resulting in underreporting of sensitive behaviors. However, the candid and detailed responses obtained in this study that could be seen in the illustrative quotes reported here indicate that underreporting of unhealthy behaviors is less likely. Given the Department of Community Medicine, PGIMER, Chandigarh, has been working in the study area to strengthen health care services, the strong rapport developed by the department over several years could have resulted in openness in responses.

All women participants in our study were homemakers. Working women did not agree to participate even when we proposed to conduct the FGD after their working hours, that is, evening or on Sunday, because of their family responsibilities; Sunday being the only off day during the week when they can attend to their pending household chores. Out of the 10 FGDs, the participation of men was lower than women in the HIG group of younger age (35–60 years) as most of the young males in these communities were working and due to their work commitments, they did not participate; thus, there is higher percentage of women in the HIG FGD sample of younger age group. We tried our level best to conduct the FGD for HIG males as per the time and venue suggested by the participants in younger age group as per their own convenience, we could not get adequate number of participants. During the first time only one participant reported for the FGD, and in the second time, two participants reported. Considering the inconvenience (waiting time) caused to those HIG males who reported for the FGD, we did not try further for increasing the number of male participants. Despite these issues, we believe that data saturation is probably achieved due to three reasons: first, the number of FGDs conducted per subgroup was adequate (Guest et al., 2016); second, informational redundancy was evident from similar/same responses obtained across the subgroups (Saunders et al., 2018); and third, no new information was forthcoming after 10 FGDs. However, we agree that in another study site there may be more heterogeneity and larger number of FGDs may be required to achieve saturation. We have mentioned this point under the discussion.

Conclusions

The findings of this study highlight the importance of formative research to identify multilevel socioecological influences dietary behaviors prior to intervention development. At the individual level—lack of knowledge about dietary recommendations, and low self-efficacy in adapting healthy food habits; at the family level—preferences of family members, and home environment; and at the social-structural level—culture, and the cost of fruits and vegetables, were found to influence intake of fat, sugar, salt, fruits, and vegetables. These findings pointed toward the need of identifying strategies to improve awareness about dietary recommendations for altering misperceptions about dietary intake, and benefits of “SMART Eating” (individual-level influences); and involving family members, especially children in intervention implementation (family-level influences). The cost largely remains unaddressed, for which strong policy measures are needed (structural level). However, the intervention strategies might focus on emphasizing consumption of locally available fruits and vegetables—at least during seasons when they are available at low cost. The conceptual framework developed from this study, based on the Social Ecological Model, is helpful in understanding the interconnections between multilevel influences and also contributed to the development of a culturally acceptable health promotion intervention to bring about desired dietary changes.

Supplemental Material

Supplementary_file_1_-_FGD_guide – Supplemental material for Multilevel Influences on Fat, Sugar, Salt, Fruit, and Vegetable Consumption Behaviors Among Urban Indians: Application of the Social Ecological Model

Supplemental material, Supplementary_file_1_-_FGD_guide for Multilevel Influences on Fat, Sugar, Salt, Fruit, and Vegetable Consumption Behaviors Among Urban Indians: Application of the Social Ecological Model by Jasvir Kaur, Manmeet Kaur, Venkatesan Chakrapani and Rajesh Kumar in SAGE Open

Footnotes

Acknowledgements

The authors are thankful to Dr. N. Nakkeeran for his valuable suggestions. They also thank Ms. Supriya Thapar and Ms. Simmi. B. Sumbria who assisted them in conducting focus group discussions. Dr. V. Chakrapani’s involvement in this manuscript was supported by the Wellcome Trust/DBT India Alliance Senior Fellowship (IA/CPHS/16/1/502667).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funding was received from Postgraduate Institute of Medical Education and Research, Chandigarh (No. 71/8-Edu-15/1619, Ledger No. 521), only for the purpose of intervention material development. This qualitative formative research was not funded by any external funding agency. Available resources of the institution (e.g., voice recorders) were used.

ORCID iDs

Jasvir Kaur

Manmeet Kaur

Supplementary Materials

Supplemental material for this article is available online.

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Supplementary Material

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Multilevel Influences on Fat,Sugar,Salt,Fruit,and Vegetable Consumption Behaviors Among Urban Indians: Application of the Social Ecological Model

Abstract

Keywords

Background

Methods

Design and Sampling Procedure

Data Collection

Data Analysis

Results

Sociodemographic Characteristics of FGD Participants

Influences on Dietary Behavior

Individual-Level Influences

Awareness about dietary recommendations

Attitude toward packaged food and eating out

Self-efficacy in adapting healthy dietary behaviors

Risk perception

Perceived benefits and costs

Family-Level Influences

Family norms

Preferences of family members

Support from family members

Home environment

Social-Structural Influences

Societal norms

Culture

Influence of media

Perceived need for policies that facilitate healthy food production and healthy eating behaviors

Availability and accessibility

Discussion

Implications for Practice and Policy

Limitations and Strengths

Conclusions

Supplemental Material

Supplementary_file_1_-_FGD_guide – Supplemental material for Multilevel Influences on Fat, Sugar, Salt, Fruit, and Vegetable Consumption Behaviors Among Urban Indians: Application of the Social Ecological Model

Footnotes

Acknowledgements

Declaration of Conflicting Interests

Funding

ORCID iDs

Supplementary Materials

References

Supplementary Material