Dietary patterns and non-communicable disease risk in Indian adults: secondary analysis of Indian Migration Study data.

Auteur(s) :
Bowen L., Kinra S., Green R., Dangour AD., Macdiarmid JI., Agrawal S., Joy EJ., Aleksandrowicz L., Haines A.
Date :
Août, 2017
Source(s) :
Public health nutrition. #20:11 p1963-72
Adresse :
Department of Population Health,London School of Hygiene & Tropical Medicine,London WC1E 7HT,UK.

Sommaire de l'article

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.


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.

Source : Pubmed