1Department of Nutritional Sciences,University of Michigan School of Public Health,Ann Arbor,MI,USA.
2Department of Family Medicine,Michigan State University College of Human Medicine,200 East 1st Street,Flint,MI 48502,USA.
Public Health Nutr. 2018 Jun;21(8):1474-1485. doi: 10.1017/S1368980017003950. Epub 2018 Jan 24.
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.
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.
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.
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.
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.
本研究旨在使用一种方法,该方法使用商店中的营养环境测量工具调查(NEMS-S)准确可靠地描述商店和社区层面健康食品的供应、价格和质量,并提出一种将这些商店和社区数据整合到客观食物获取测量中的空间方法。
在美国密歇根州弗林特市及其 2 英里(3.2 公里)范围内的 265 家零售食品店使用 ArcGIS 制图软件进行了制图。
在每个零售食品店都进行了基于经过验证的 NEMS-S 的调查。根据 NEMS-S 评分系统的修改版本为每个商店分配分数,并将其与商店的映射位置相关联。为每个商店附加了邻里特征(种族和社会经济贫困)。最后,对映射的商店分数进行空间和核密度分析,以获得健康食品密度指标。
回归分析显示,社会经济贫困程度较高的社区的奶制品分项得分明显低于贫困程度较低的社区(β系数=-1.3;P=0.04)。此外,仅在非裔美国人比例<60%且社会经济贫困程度较低的社区中存在超市。弗林特的两个地区的 NEMS-S 总分为 0。
通过使用经过验证的指标确定获得健康食品机会较差的区域,本研究可以帮助当地政府和组织针对高需求区域开展干预措施。此外,还可以在其他城市复制用于调查和制图的方法,以提供可比的结果。