Suppr超能文献

利用地理信息系统技术,追踪不同社会经济地位和人口统计学特征人群可获得的零售设施中的关键卫生法规违规行为。

Use of geographic information systems technology to track critical health code violations in retail facilities available to populations of different socioeconomic status and demographics.

机构信息

Department of Nutrition Sciences, College of Nursing and Health Professions, Drexel University, Philadelphia, Pennsylvania 19104, USA.

出版信息

J Food Prot. 2011 Sep;74(9):1524-30. doi: 10.4315/0362-028X.JFP-11-101.

Abstract

Research shows that community socioeconomic status (SES) predicts, based on food service types available, whether a population has access to healthy food. It is not known, however, if a relationship exists between SES and risk for foodborne illness (FBI) at the community level. Geographic information systems (GIS) give researchers the ability to pinpoint health indicators to specific geographic locations and detect resulting environmental gradients. It has been used extensively to characterize the food environment, with respect to access to healthy foods. This research investigated the utility of GIS in determining whether community SES and/or demographics relate to access to safe food, as measured by food service critical health code violations (CHV) as a proxy for risk for FBI. Health inspection records documenting CHV for 10,859 food service facilities collected between 2005 and 2008 in Philadelphia, PA, were accessed. Using an overlay analysis through GIS, CHV were plotted over census tracts of the corresponding area. Census tracts (n = 368) were categorized into quintiles, based on poverty level. Overall, food service facilities in higher poverty areas had a greater number of facilities (with at least one CHV) and had more frequent inspections than facilities in lower poverty areas. The facilities in lower poverty areas, however, had a higher average number of CHV per inspection. Analysis of CHV rates in census tracts with high concentrations of minority populations found Hispanic facilities had more CHV than other demographics, and Hispanic and African American facilities had fewer days between inspections. This research demonstrates the potential for utilization of GIS mapping for tracking risks for FBI. Conversely, it sheds light on the subjective nature of health inspections, and indicates that underlying factors might be affecting inspection frequency and identification of CHV, such that CHV might not be a true proxy for risk for FBI.

摘要

研究表明,根据现有餐饮类型,社区社会经济地位(SES)可预测一个人群是否能获得健康食品。然而,目前尚不清楚社区 SES 是否与食源性疾病(FBI)风险之间存在关联。地理信息系统(GIS)使研究人员能够将健康指标精确到特定地理位置,并检测到相应的环境梯度。GIS 已广泛用于描述食品环境,以评估获得健康食品的机会。本研究通过 GIS 来确定社区 SES 和/或人口统计学是否与食品安全相关,以食品安全关键卫生法规违规(CHV)作为 FBI 风险的替代指标。研究中获取了 2005 年至 2008 年间在宾夕法尼亚州费城收集的 10859 家餐饮服务设施的卫生检查记录,以评估食品安全关键卫生法规违规(CHV)。通过 GIS 的叠加分析,将 CHV 绘制在相应区域的普查区上。将普查区(n = 368)按贫困水平分为五分位数。总体而言,贫困程度较高地区的餐饮服务设施数量更多(至少有一个 CHV),且检查频率更高;而贫困程度较低地区的设施则每检查一次平均违规次数更多。对少数族裔人口高度集中的普查区的 CHV 率进行分析发现,西班牙裔设施的违规数量多于其他族裔,而西班牙裔和非裔美国人设施的检查间隔天数较少。本研究证明了利用 GIS 制图跟踪 FBI 风险的潜力。此外,这也揭示了卫生检查的主观性,并表明潜在因素可能会影响检查频率和 CHV 的识别,因此 CHV 可能不是 FBI 风险的真实替代指标。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验