Literature DB >> 29361993

The Flint Food Store Survey: combining spatial analysis with a modified Nutrition Environment Measures Survey in Stores (NEMS-S) to measure the community and consumer nutrition environments.

Erika R Shaver1, Richard C Sadler2, Alex B Hill3, Kendall Bell2, Myah Ray2, Jennifer Choy-Shin2, Joy Lerner2, Teresa Soldner2, Andrew D Jones1.   

Abstract

OBJECTIVE: The goal of the present study was to use a methodology that accurately and reliably describes the availability, price and quality of healthy foods at both the store and community levels using the Nutrition Environment Measures Survey in Stores (NEMS-S), to propose a spatial methodology for integrating these store and community data into measures for defining objective food access.
SETTING: Two hundred and sixty-five retail food stores in and within 2 miles (3·2 km) of Flint, Michigan, USA, were mapped using ArcGIS mapping software.
DESIGN: A survey based on the validated NEMS-S was conducted at each retail food store. Scores were assigned to each store based on a modified version of the NEMS-S scoring system and linked to the mapped locations of stores. Neighbourhood characteristics (race and socio-economic distress) were appended to each store. Finally, spatial and kernel density analyses were run on the mapped store scores to obtain healthy food density metrics.
RESULTS: Regression analyses revealed that neighbourhoods with higher socio-economic distress had significantly lower dairy sub-scores compared with their lower-distress counterparts (β coefficient=-1·3; P=0·04). Additionally, supermarkets were present only in neighbourhoods with <60 % African-American population and low socio-economic distress. Two areas in Flint had an overall NEMS-S score of 0.
CONCLUSIONS: By identifying areas with poor access to healthy foods via a validated metric, this research can be used help local government and organizations target interventions to high-need areas. Furthermore, the methodology used for the survey and the mapping exercise can be replicated in other cities to provide comparable results.

Entities:  

Keywords:  Geographic information systems; NEMS-S; Nutrition environment; Spatial analysis

Mesh:

Year:  2018        PMID: 29361993      PMCID: PMC6941423          DOI: 10.1017/S1368980017003950

Source DB:  PubMed          Journal:  Public Health Nutr        ISSN: 1368-9800            Impact factor:   4.022


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