Spatial clustering of emergency department visits by asthmatic children in an urban area: south-western Detroit, Michigan

Abstract

Objective This ecological study evaluates the correlation of asthma clusters with outdoor air pollution, race, and household income in South-western Detroit, Michigan. Design To attain this objective (1) a geographic information aystem (GIS) is utilized to evaluate the relationships between rates of emergency department (ED) admissions for asthma, race, and socio-economic status at the neighborhood block group level of analysis; (2) cluster statistical analyses are performed using Geomed software; and (3) the asthma risk from industrial air pollution was evaluated with windrose data and Screen3 air pollution model. Sample Data from five major hospitals with ED admissions of asthma patients (code 493), aged 0–15 years, are used to select a region of analysis with good geographical representation based on the catchment areas of hospitals in the study. A total of 2067 of the reported cases between 1 January 1993 and 30 June 1998, are successfully geocoded to a map, generating a no-match rate of 8.4%. Data on racial characteristics, population density, and household income levels are obtained from neighborhood block groups in the 1990 census report. Locations of major polluting industries within the study area are obtained from the Toxics Release Inventory. Results Spatial analysis identified a local asthma cluster roughly 2 km east (the predominant downwind direction) of the second and third largest air polluters (in terms of tonnage) in Wayne County. Evaluation of the industrial pollution with a focused cluster test, Screen3 air pollution model, and windrose figures, displayed weak association between ED asthma admissions and estimated levels of outdoor air pollution from these two facilities. The neighborhood block groups in the local asthma cluster are more closely correlated with high proportions of African Americans and low median household income. Implications for practice This study illustrates the strengths and weaknesses of GIS in the public health arena. It highlights the difficulty of disentangling the effects of exposure to outdoor air pollutants and socio-economic factors on ED asthmatics (reflecting asthma severity) among an urban population. This study also illustrates the need for population-based, as opposed to hospital-based, asthma data, and the need for block-groups, as opposed to zip codes, as a spatial unit of analysis in the evaluation and analysis of asthma-related risk factors.