Potential selection bias associated with using geocoded birth records for epidemiologic research

Abstract Purpose There is an increasing use of geocoded birth registry data in environmental epidemiology research. Ungeocoded records are routinely excluded. Methods We used classification and regression tree analysis and logistic regression to investigate potential selection bias associated with this exclusion among all singleton Florida births in 2009 ( n = 210,285). Results The rate of unsuccessful geocoding was 11.5% ( n = 24,171). This ranged between 0% and 100% across zip codes. Living in a rural zip code was the strongest predictor of being ungeocoded. Other predictors for geocoding status varied with urbanity status. In urban areas, maternal race (adjusted odds ratio [aOR] ranging between 1.08 for Hispanic and 1.18 for black compared to white), maternal age [aOR: 1.16 (1.10–1.23) for ages 20–34 compared to