Evidence map›Paper›PMID 40851907›Full record

ArticleFrontiers in nutrition2025

From counsel to consumption: examining sociocultural influences on perinatal nutrition in rural India.

Faiz A Hashmi, Cristine H Legare

Abstract read
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Article in Frontiers in nutrition, 2025. 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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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Faiz A HashmiCenter for Applied Cognitive Science, The University of Texas at Austin, Austin, TX, United States.
Cristine H LegareCenter for Applied Cognitive Science, The University of Texas at Austin, Austin, TX, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Perinatal nutrition is vital for better maternal and child health outcomes. Biomedical guidelines recommend increasing caloric intake, avoiding toxins, and consuming a diverse, nutritious diet during pregnancy and postpartum. Yet, a significant gap persists between nutritional recommendations and actual practices in resource-limited settings. This gap is further complicated by cultural beliefs and traditional practices surrounding food and nutrition, which influence dietary habits. This study examines perinatal dietary practices in rural Bihar, India. We focused on three key areas: caloric adequacy, micronutrient consumption, and food avoidance patterns. We investigated how education and other social determinants influence these dietary choices. We compare dietary behaviors between recent mothers and Accredited Social Health Activists (ASHAs). ASHAs counsel rural mothers on nutrition throughout India and serve as natural benchmarks for assessing whether biomedical recommendations are translated into personal practice. We employed a mixed-methods approach combining qualitative and quantitative methods. Qualitative data included 8 focus group discussions involving 40 young mothers and 38 mothers-in-law, key informant interviews across 6 health influencer categories, and ethnographic observations of 13 ASHAs and 7 households. We conducted a quantitative survey of 400 ASHAs and 1,200 mothers across multiple districts in Bihar. Data were analyzed using descriptive statistics, generalized linear models, and thematic analysis. A significant gap exists between guidelines and actual practices; 85% of mothers and 75% of ASHAs did not increase dietary intake during pregnancy. Education emerged as the strongest predictor of dietary behaviors; women with 14-17 years of education were three times more likely to adopt healthier diets during pregnancy than women with less education. Rice-ghee combinations and milk represented cultural consensus items, while micronutrient-rich foods faced variable acceptance. Notably, more educated women increased overall dietary intake and avoided specific foods, indicating nuanced dietary decision-making rather than simple restriction reduction. Interventions must leverage culturally endorsed foods while promoting incremental modifications to restrictive practices. Educational interventions show promise, given the gradient effect of education on dietary practices. ASHAs serve as crucial cultural brokers but require structural support to overcome community barriers. Addressing maternal undernutrition requires engaging cultural dietary beliefs while enhancing educational opportunities to empower women's informed dietary choices.

Indexed as

Accredited Social Health Activist (ASHA)community health workerscultural dietary beliefsfood tabooshealth behavior changeIndiamaternal nutritionmixed methods research

Identifiers

PMID40851907
PMCPMC12367784

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.