Trial reportEuropean journal of clinical nutrition2026
Associations between socio-demographic factors and diet patterns among Indian women in a low-income urban setting.
Trial report in European journal of clinical nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Does getting online help low-income adults eat better? Digital access and BMI-based nutritional imbalance in China.Frontiers in nutrition · 2026Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
objectivesImproving the diets of women of reproductive age living in Mumbai slums may benefit their own health and that of their children. Our objective was to identify diet patterns in this population group. SUBJECTS/
methodsParticipants were married women (n = 6513) aged <40 years enroled in a randomised controlled trial of a food-based intervention. We collected dietary data at the time of enrolment using a 212-item food frequency questionnaire. We used principal component analysis and cluster analysis to identify dietary patterns and explored socio-demographic correlates of the patterns using multivariate linear regression models.
resultsWe identified 2 interpretable patterns. The first, named the 'Snack, Fruit and Sweet' pattern was characterised by vegetable curry, fried snacks, salad, fruit, sweets and sweetened beverages and explained 9.3% of the variance. Scores on this pattern were independently associated with the women not working versus being employed (0.13, CI: 0.06, 0.19, p < 0.001) and with standard of living index score (0.03, CI: 0.02, 0.04, p < 0.001). The second pattern was named 'Non-vegetarian' and was characterised by meat and biriyani and rice and noodle dishes, with low intakes of lentils, legumes, nuts and seeds. This pattern was associated with being Muslim and was negatively associated with age (-0.02, CI: -0.03, -0.02, p < 0.001) and standard of living index (-0.01, CI: -0.01, 0.00, p < 0.001). It explained 6.7% of the variance.
conclusionsWe identified two interpretable patterns that can be used to better understand dietary habits in Mumbai slums. This knowledge can be used to target interventions aimed at improving diet quality in these communities.
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