Use of Geographic Information Systems Technology to Track Critical Health Code Violations in Retail Facilities Available to Populations of Different Socioeconomic Status and Demographics

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.

Evaluating area-level spatial clustering of SalmonellaEnteritidis infections and their socioeconomic determinants in the greater Toronto area, Ontario, Canada (2007 – 2009): a retrospective population-based ecological study

“…The pathogenicity and source attribution of Salmonella serotypes can differ [20,46,47], which might have led to non serotype-specific associations in the US study that are not representative of S. Enteritidis infections. Additionally, the higher rates of infection from low income areas in our study might be explained by poorer microbial quality of foods consumed [48], or by more frequent retail food safety violations [49,50] that could increase residents’ risk of foodborne diseases, including S. Enteritidis infections. Future research should consider public health inspection violations in different retail settings (e.g.…”

Foodborne Illness Incidence Rates and Food Safety Risks for Populations of Low Socioeconomic Status and Minority Race/Ethnicity: A Review of the Literature

“…These findings would all imply the likelihood that small independent markets would have more critical and non-critical code violations. Darcey and Quinlan [32] used GIS technology to map publically available critical health code violations (CHV) in retail facilities across a range of population demographics in Philadelphia, Pennsylvania. Overall, it was found that 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 areas with lower poverty.…”

“…Additionally, CHV rates in census tracts with high Hispanic populations were greater than for CHV rates in tracts of any other population demographic. However, it was also seen that facilities in lower poverty areas had the highest average number of CHV per inspection, but a greater number of days between inspections, which is counterintuitive to what would be expected if facilities in low poverty areas had more CHVs [32]. These results indicate that while GIS technology may have potential applications to exploring relative safety and sanitation of retail facilities, the technology is dependent on health inspection data to be completely objective and not influenced by potential inspector bias [73].…”

“…This concept has been recognized and defined by the U.S. Department of Agriculture as “Food Deserts” where there is a lack of large supermarkets and tends to be an abundance of smaller grocers, convenience and fast food retailers [27,28]. A small body of research has begun to attempt to assess the food safety risks of food deserts and the small independent retailers they are made up of through a combination of survey at the retail level as well as use of inspection violation rates as a proxy for safety [29,30,31,32,33]. …”

The State of Food Mapping

“…The Midwest followed with a total of seven studies (Chen and Clark 2013;Franzen and Smith 2010;Eckert and Shetty 2011;Taylor and Lovell 2012;Kremer and DeLiberty 2011;Hirsch and Hillier 2013;Darcey and Quinlank 2011). Interestingly, there were no studies examining southwestern geographies to review.…”