In each of the study regions two dietary patterns emerged and varied associations with cardio-metabolic risk factors were observed. In cross-sectional analyses adjusted for key demographic and lifestyle confounders, diets across all regions characterized by dairy, fried snacks, and sweets appeared to be positively asssociated with abdominal adiposity. Conversly, dietary patterns in Trivandrum and Mumbai, characterized by intake of vegetables and pulses, were inversely related to diabetes and hypertension.
South Asians in India, and throughout the world, are an important population to study due to their greatly elevated risk of diabetes and cardiovascular disease [38, 39]. However, compared to the breadth of studies on Western-style dietary patterns and chronic disease etiology [14, 40], few studies have examined food patterns in the high-risk Indian population [13, 16, 18, 41–43] or collected biological samples. Compared to Caucasian populations, South Asians typically develop metabolic syndromes at lower BMIs, and are known to have increased visceral fat and insulin resistance [3, 44]. Abdominal adiposity, impaired glucose and lipid levels, as well as hypertension in a high-proportion of study participants corresponds with the high-risk "Asian Indian phenotype" that may be a product of genetic adaptations to food insecurity, fetal or early childhood malnutrition, as well as more recent environmental exposures including adult diet [2, 18, 44–49].
High fat intake (~40% of total energy intake), particularly in Delhi and Mumbai, was one indication that components of the Indian diet may be contributing to a high-risk diet and health profile. However, we found little evidence of Westernization of the diet  through food items, such as red meat, sweetened beverages, and processed or fast foods, but did observe other characteristics such as sugary and high-fat foods perhaps reflecting a transitional diet arising from access to cheap oils and sweeteners . Top loading food items for the dietary patterns included fruit, vegetables, chutneys, and tea, as well as traditional Indian fried snacks and desserts. Across all regions, dietary patterns frequently contained traditional mixed dishes composed mainly of vegetables, pulses, cereals and/or potato, but there were regional differences in the types of cereals (e.g., fermented rice, plain rice, wheat products) and potential protein sources such as pulses, dairy, and eggs. A study conducted in the 1970's among Indian physicians [51, 52], reported a very low-fat, rice and pulse-based diet in the South. This contrasted with a high-fat, wheat-based diet in the North with frequent consumption of vegetables cooked in ghee, milk, and yogurt. More recently, dietary data collected in India from women in the National Family Health Survey (NFHS-2) also found that intake of animal foods (eggs, dairy, fish, and meat) varied across the different regions . Compared to China and other Asian countries, high amounts of sugar are consumed in India . Our analysis suggests a continued preference for the traditional Indian sweets, as opposed to Western desserts (cake, pies, candy, etc.) which may be more easily recognized as unhealthy . In addition to sugar, many of these Indian sweets are often prepared with a substantial amount of saturated fat from ghee or coconut components.
Previous studies have reported that cardiovascular disease risk in India is likely to be inversely associated with intake of fruits, vegetables, and mustard oil [12, 43]; and positively associated with intake of refined carbohydrates and unhealthy fats (reviewed in [18, 54]). In Trivandrum we found that the more traditional pulses and rice pattern was inversely associated with diabetes. Similarly, the more prudent-appearing fruit and vegetable pattern in Mumbai was inversely associated with hypertension. Secondary patterns in both of these regions, characterized by intake of fried snacks and sweets, appeared to be positively associated with abdominal adiposity. In Delhi, the northern-most region, where dietary patterns appeared to reflect access to a greater variety of foods, the predominant fruit and dairy pattern was positively associated with both abdominal adiposity and hypertension. Although one may not typically consider fruit part of a high-risk diet, higher concordance with this pattern was more common among participants of higher socio-economic status and lower physical activity and may also reflect dietary choices or substitutions to manage a chronic condition. Unlike Trivandrum and Mumbai, the vegetables and pulses pattern in Delhi, was not associated with any chronic conditions and we found no associations for dietary patterns and dyslipidemia.
The relationship between diet and chronic disease risk is certainly complex and we are likely to encounter unfamiliar challenges in the Indian diet. The type, as well as the cooking, of vegetables (green leafy, starchy, stir-fried, stewed, boiled, etc.) in traditional Indian mixed dishes may alter some of their preventive properties [12, 55–57] and may also contribute substantially to added fat [51, 58]. The contrasting correlations we observed between intakes of iron, calcium, and retinol and the more traditional patterns in Trivandrum versus Mumbai, suggest that the nutrient quality of these regional diets vary considerably. Other cross-sectional studies in South Asian populations, living in India and abroad, have suggested that characteristically high fruit and vegetable intake may be associated with lower LDL and total cholesterol , but that high-carbohydrate diets, overall, may be associated with higher triglycerides and lower HDL cholesterol [59, 60], as well as hyperinsulinemia  in South Asians. Unraveling the nutrient composition of specific Indian foods , particularly the fatty acid, sodium, and glycemic composition , as well as the complex relationship between diet, socio-economic status, obesity, and chronic disease risk  is likely to be of great relevance for India.
Major strengths of our study were the use of interviewer-administered questionnaires developed specifically for the study, collection of fasting blood, and measurement of anthropometry and blood pressure by trained medical staff. Fasting blood and blood pressure measurements, along with medication use, were invaluable in classifying diabetes and hypertension status, as self-reports were clearly an underestimate of the prevalence in this population. However, the external validity of our findings may be limited in this lower to upper middle class sample with very high rates of abdominal adiposity and obesity. As with many developing countries, a moderate improvement in socio-economic status is likely to increase access to both over-nutrition and a sedentary lifestyle; thus, affluence may serve as a key risk factor for obesity, diabetes, and other related conditions . Other large cross-sectional studies have observed a double burden of under- and over-weight [17, 64–66] and throughout India, nutritional status and chronic disease risk profiles vary substantially by intra-and inter-state socio-economic extremes [67–69]. The prevalence of cardio-metabolic risk factors we observed more closely resembled studies of middle-aged adults residing in metropolitan areas of India [70, 71] and that of South Asians residing in the U.S. . However, it also plausible that recruitment of IHS participants from households may have resulted in a clustering of risk factors .
We recognize the limitations of the cross-sectional study design to make strong conclusions regarding causality and chronic disease etiology. Dietary patterns identified by factor analysis are intended to represent the actual eating patterns that arose from the study sample, but do not necessarily capture optimal diets or unhealthy extremes that one may want to specifically target for intervention or prevention. Factor analysis also involves some level of subjectivity in selecting and grouping food items. However, in our case, a trained nutritionist in India grouped all the food items collected in the DH into meaningful subgroups prior to the patterns analysis. In addition to the number and composition of the food items, various statistical options and methods for factor analysis, as well as the selection of the number of factors to retain in the final analysis, may also affect the overall explained factor variance . Although we used standard methods and a priori grouped food items, the detailed DH and large number of food items collected  may have limited variation explained by the dietary patterns (8-12% within each region), as well as overall interpretability. Although our variance estimates exceeded those from analyses in similarly underserved populations , some larger U.S. cohort studies achieved total explained variance levels as high as 20 to 30% [35, 77]. Dietary patterns analysis conducted in some Western cohorts may also have benefitted from a larger sample size, as well as a more cohesive population with regard to ethnicity, education, and economic access to a variety of foods to meet nutritional needs and preferences.