Undernutrition and non-communicable disease (NCD) are important public health issues in India, yet their relationship with dietary patterns is poorly understood. The current study identified distinct dietary patterns and their association with micronutrient undernutrition (Ca, Fe, Zn) and NCD risk factors (underweight, obesity, waist:hip ratio, hypertension, total:HDL cholesterol, diabetes).

Data were from the cross-sectional Indian Migration Study, including semi-quantitative FFQ. Distinct dietary patterns were identified using finite mixture modelling; associations with NCD risk factors were assessed using mixed-effects logistic regression models.

India.

Migrant factory workers, their rural-dwelling siblings and urban non-migrants. Participants (7067 adults) resided mainly in Karnataka, Andhra Pradesh, Maharashtra and Uttar Pradesh.

Five distinct, regionally distributed, dietary patterns were identified, with rice-based patterns in the south and wheat-based patterns in the north-west. A rice-based pattern characterised by low energy consumption and dietary diversity (‘Rice & low diversity’) was consumed predominantly by adults with little formal education in rural settings, while a rice-based pattern with high fruit consumption (‘Rice & fruit’) was consumed by more educated adults in urban settings. Dietary patterns met WHO macronutrient recommendations, but some had low micronutrient contents. Dietary pattern membership was associated with several NCD risk factors.

Five distinct dietary patterns were identified, supporting sub-national assessments of the implications of dietary patterns for various health, food system or environment outcomes.

Obesity is a growing problem in India, the dietary determinants of which have been studied using an ‘individual food/nutrient’ approach. Examining dietary patterns may provide more coherent findings, but few studies in developing countries have adopted this approach. The present study aimed to identify dietary patterns in an Indian population and assess their relationship with anthropometric risk factors.

FFQ data from the cross-sectional sib-pair Indian Migration Study (IMS; n 7067) were used to identify dietary patterns using principal component analysis. Mixed-effects logistic regression was used to examine associations with obesity and central obesity.

The IMS was conducted at four factory locations across India: Lucknow, Nagpur, Hyderabad and Bangalore.

The participants were rural-to-urban migrant and urban non-migrant factory workers, their rural and urban resident siblings, and their co-resident spouses.

Three dietary patterns were identified: ‘cereals–savoury foods’ (cooked grains, rice/rice-based dishes, snacks, condiments, soups, nuts), ‘fruit–veg–sweets–snacks’ (Western cereals, vegetables, fruit, fruit juices, cooked milk products, snacks, sugars, sweets) and ‘animal-food’ (red meat, poultry, fish/seafood, eggs). In adjusted analysis, positive graded associations were found between the ‘animal-food’ pattern and both anthropometric risk factors. Moderate intake of the ‘cereals–savoury foods’ pattern was associated with reduced odds of obesity and central obesity.

Distinct dietary patterns were identified in a large Indian sample, which were different from those identified in previous literature. A clear ‘plant food-based/animal food-based pattern’ dichotomy emerged, with the latter being associated with higher odds of anthropometric risk factors. Longitudinal studies are needed to further clarify this relationship in India.