Evidence map›Paper›PMID 40535440›Full record

ArticleFrontiers in public health2025

Measured and perceived food environment influences on women's nutritional health in marginalized areas of northern Mexico: a structural equation modeling analysis.

Zahid García, Juan Martín Preciado Rodríguez, Gloria Elena Portillo Abril, Alma Delia Contreras Paniagua, María Isabel Ortega-Vélez

Abstract read
In one paragraph

Article in Frontiers in public health, 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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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Zahid GarcíaDepartament of Public Nutrition and Health, Centro de Investigación en Alimentación y Desarrollo (CIAD), Hermosillo, Sonora, Mexico.
Juan Martín Preciado RodríguezDepartment of Industrial Engineering, University of Sonora, Hermosillo, Sonora, Mexico.
Gloria Elena Portillo AbrilDepartament of Public Nutrition and Health, Centro de Investigación en Alimentación y Desarrollo (CIAD), Hermosillo, Sonora, Mexico.
Alma Delia Contreras PaniaguaDepartament of Public Nutrition and Health, Centro de Investigación en Alimentación y Desarrollo (CIAD), Hermosillo, Sonora, Mexico.
María Isabel Ortega-VélezDepartament of Public Nutrition and Health, Centro de Investigación en Alimentación y Desarrollo (CIAD), Hermosillo, Sonora, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Obesity is a growing global public health problem and a risk factor for developing non-communicable diseases (NCDs). The food environment is crucial in shaping nutritional behaviors and health outcomes. However, how food environment indicators interrelate and impact the population's health in middle- and low-income countries is unclear. This study examined the association between the food environment and indicators of obesity and NCDs in adult women from medium and high-marginalization areas in Hermosillo, Northwest Mexico. Methods: A randomized sample of 104 adult women and 80 food retail stores participated in this cross-sectional study. Data on diet, anthropometric measurements, and NCD diagnoses were collected. We assessed the food environment's personal (perceived) and external (measured) dimensions. Personal dimensions included perceived accessibility, affordability, convenience, and desirability of foods, while external dimensions comprised the variety, prices, density of food establishments, and advertising presence in participants' neighborhoods. Data were collected via questionnaires and inventories and analyzed using geospatial and structural equation modeling (SEM) techniques to explore the relationships between food environment indicators and health outcomes. Results: The participants, with an average age of 47.6 years, exhibited an average BMI of 31.0 kg/m Conclusion: Our findings contribute to the empirical evidence that food environments influence the nutritional health of vulnerable populations. The results suggest that public policies should focus on improving the food environment by enhancing the availability and affordability of healthy foods.

Indexed as

Food SupplyWomen's HealthAdultCross-Sectional StudiesFemaleHumansLatent Class AnalysisMexicoMiddle AgedNutritional StatusObesitySurveys and Questionnairesfood environmenthealthmarginalizationnorthern Mexicoobesitystructural equation modeling

Identifiers

PMID40535440
PMCPMC12176064

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LicenceCC BY
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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.