302593
Examining systematic biases in secondary commercial data sources of food and alcohol environments: Differences across neighborhood racial and socioeconomic characteristics
Methods: This study included two commercial datasets for 2003 and 2009 in Allegheny County, PA. Food and alcohol establishment densities were calculated by census tract (416 census tracts). Differences between the two commercial data sources of the food and alcohol environment across levels of neighborhood racial and socioeconomic characteristics were tested using correlations and two-way mixed analysis of variance (ANOVA).
Results: There 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 commercial data source #1 but not in data source #2. Alcohol outlet density (AOD) increased as neighborhood poverty increased for both data sources, but the mean difference in AOD between the two commercial data sources 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 commercial data source #1 (2009 data).
Discussion: The location, numeration, and density of food and alcohol establishments are differentially associated with neighborhood racial and socioeconomic characteristics and may introduce systematic biases. Using multiple data sources may be important for addressing systematic biases and data limitations.
Learning Areas:
Environmental health sciencesEpidemiology
Public health or related research
Learning Objectives:
Identify key commercial data sources used to capture the food and alcohol environment.
Describe these commercial data sources and the differences in the relationship with other neighborhood characteristics such as neighborhood income or racial composition.
Keyword(s): Built Environment, Geographic Information Systems (GIS)
Qualified on the content I am responsible for because: I have been the PI or co-PI of several studies investigating the influences of the neighborhood environment and its contribution to health disparities. I also have postdoctoral training and junior scholar training specific to the area of research presented in this paper.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.