Open Access Open Badges Research

A cross-sectional investigation of regional patterns of diet and cardio-metabolic risk in India

Carrie R Daniel1*, Dorairaj Prabhakaran2, Kavita Kapur3, Barry I Graubard1, Niveditha Devasenapathy2, Lakshmy Ramakrishnan4, Preethi S George5, Hemali Shetty6, Leah M Ferrucci1, Susan Yurgalevitch7, Nilanjan Chatterjee1, KS Reddy4, Tanuja Rastogi8, Prakash C Gupta6, Aleyamma Mathew5 and Rashmi Sinha1

Author Affiliations

1 Division of Cancer Epidemiology and Genetics, National Cancer Institute, (6120 Executive Blvd), Rockville, MD, (20852), USA

2 Centre for Chronic Disease Control, (C1/52, Safdarjung Development Area), New Delhi, (110 016), India

3 Steno Diabetes Center, (Niels Steensens vej 8), Gentofte, (DK 2820), Denmark

4 Department of Cardiac Biochemistry, All India Institute of Medical Sciences, (Ansari Nagar), New Delhi, (110029), India

5 Regional Cancer Center, (Medical College Campus), Trivandrum, Kerala (695011), India

6 Healis Sekhsaria Institute for Public Health, (Thane, Sector 11, CBD Belapur), Navi Mumbai, (400 614), India

7 Westat, (1600 Research Blvd), Rockville, MD, (20850), USA

8 UN World Food Programme, (Via Cesare Giulio Viola, 68), Rome, (00148), Italy

For all author emails, please log on.

Nutrition Journal 2011, 10:12  doi:10.1186/1475-2891-10-12

Published: 28 January 2011



The role of diet in India's rapidly progressing chronic disease epidemic is unclear; moreover, diet may vary considerably across North-South regions.


The India Health Study was a multicenter study of men and women aged 35-69, who provided diet, lifestyle, and medical histories, as well as blood pressure, fasting blood, urine, and anthropometric measurements. In each region (Delhi, n = 824; Mumbai, n = 743; Trivandrum, n = 2,247), we identified two dietary patterns with factor analysis. In multiple logistic regression models adjusted for age, gender, education, income, marital status, religion, physical activity, tobacco, alcohol, and total energy intake, we investigated associations between regional dietary patterns and abdominal adiposity, hypertension, diabetes, and dyslipidemia.


Across the regions, more than 80% of the participants met the criteria for abdominal adiposity and 10 to 28% of participants were considered diabetic. In Delhi, the "fruit and dairy" dietary pattern was positively associated with abdominal adiposity [highest versus lowest tertile, multivariate-adjusted OR and 95% CI: 2.32 (1.03-5.23); Ptrend = 0.008] and hypertension [2.20 (1.47-3.31); Ptrend < 0.0001]. In Trivandrum, the "pulses and rice" pattern was inversely related to diabetes [0.70 (0.51-0.95); Ptrend = 0.03] and the "snacks and sweets" pattern was positively associated with abdominal adiposity [2.05 (1.34-3.14); Ptrend = 0.03]. In Mumbai, the "fruit and vegetable" pattern was inversely associated with hypertension [0.63 (0.40-0.99); Ptrend = 0.05] and the "snack and meat" pattern appeared to be positively associated with abdominal adiposity.


Cardio-metabolic risk factors were highly prevalent in this population. Across all regions, we found little evidence of a Westernized diet; however, dietary patterns characterized by animal products, fried snacks, or sweets appeared to be positively associated with abdominal adiposity. Conversely, more traditional diets in the Southern regions were inversely related to diabetes and hypertension. Continued investigation of diet, as well as other environmental and biological factors, will be needed to better understand the risk profile in this population and potential means of prevention.