Neighborhood Racial and Socioeconomic Disparities in the Food and Alcohol Environment: Are There Differences by Commercial Data Sources?
Neighborhood Racial and Socioeconomic Disparities in the Food and Alcohol Environment: Are There Differences by Commercial Data Sources?
复制标题
食品和酒精环境中的邻里种族和社会经济差异：商业数据来源是否存在差异？
DOI：
10.1007/s40615-015-0120-0
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发表时间：
2016
影响因子：
3.9
通讯作者：
Fabio,Anthony
中科院分区：
文献类型：
--
作者：
Mendez,DaraD;Kim,KevinH;Hardaway,CecilyR;Fabio,Anthony
目的这项研究调查了邻近地区的种族和社会经济差异以及食品和酒精场所的密度。我们还检验了这些差异是否因数据来源而不同。方法本研究包括宾夕法尼亚州阿勒格尼县416个人口普查区域2003年和2009年来自InfoUSA和Dun and BradStreet(D&B)的商业数据。食品和酒类设施的密度是根据2000年美国人口普查的面积和人口数据计算出来的。用相关分析和双向混合方差分析(ANOVA)检验InfoUSA和D&B在不同社区种族和社会经济特征的食物和酒精密度之间的差异。结果不同数据来源的社区种族和社会经济特征与食品/酒精场所密度之间的相关性存在差异。在D&B数据中，杂货店/超市密度与黑人比例、贫困比例和无车比例呈正相关，但在InfoUSA并非如此。对于这两个数据来源，酒精销售点密度随着社区贫困程度的增加而增加，但在贫困程度为25%-50%的社区中，InfoUSA和D&B之间的酒精销售点密度的平均差异最大(Cohen‘s d−0.49p<； 0.001)，而不是贫困程度较低或更高的社区(2003年数据)。平均杂货店密度随着贫困百分比的增加而增加，但仅限于D&B(2009年数据)。结论商业数据在食品和酒类场所的位置和计数方面的差异与社区种族和社会经济特征有关，并可能导致关于社区食品和酒精环境、种族和社会经济差异以及健康的偏见。
ObjectivesThis study examined neighborhood racial and socioeconomic disparities and the density of food and alcohol establishments. We also examined whether these disparities differed by data source.MethodsThis study included commercial data for 2003 and 2009 from InfoUSA and Dun and Bradstreet (D&B) in 416 census tracts in Allegheny County, PA. Food and alcohol establishment densities were calculated by using area and population data from the 2000 US census. Differences between InfoUSA and D&B of food and alcohol densities across neighborhood racial and socioeconomic characteristics were tested using correlations and two-way mixed analysis of variance (ANOVA).ResultsThere were differences by data source in the association between neighborhood racial and socioeconomic characteristics and food/alcohol establishment density. There was a positive correlation between grocery store/supermarket density and percentage black, poverty, and percentage without a car among D&B data but not in InfoUSA. Alcohol outlet density (AOD) increased as neighborhood poverty increased for both data sources, but the mean difference in AOD between InfoUSA and D&B was highest among neighborhoods with 25–50 % poverty (Cohen’s d −0.49,p< 0.001) compared to neighborhoods with lower or higher poverty (2003 data). Mean grocery store density increased as percentage poverty increased, but only among D&B (2009 data).ConclusionsDifferences in commercial data in the location and numeration of food and alcohol establishments are associated with neighborhood racial and socioeconomic characteristics and may introduce biases concerning neighborhood food and alcohol environments, racial and socioeconomic disparities, and health.