Anne M Jurek1, Sander Greenland. 1. Center for Healthcare Research & Innovation, Allina Health, Minneapolis, MN 55407, USA. jure0007@umn.edu
Abstract
PURPOSE: Birth certificates are a convenient source of population data for epidemiologic studies. It is well documented, however, that birth certificate data can be highly inaccurate. Nonetheless, studies based on birth certificates are routinely analyzed without accounting for sources of data errors. We focused on the association between maternal cigarette smoking and cleft lip and palate based on birth certificate data. METHODS: We adjusted odds ratio estimates simultaneously for exposure and outcome misclassification. We also calculated odds ratios adjusted for exposure misclassification only and outcome misclassification only. RESULTS: Adjustment for both maternal smoking during pregnancy and clefting resulted in adjusted odds ratios that ranged from less than 1.0 to much greater than the unadjusted estimate of 1.16, with most adjusted estimates outside of the 95% confidence limits (1.01, 1.33). CONCLUSIONS: Because of the potentially large impact of birth certificate classification errors, we suggest that inferences from these or similar records employ quantitative methods for incorporating uncertainties caused by data errors.
PURPOSE: Birth certificates are a convenient source of population data for epidemiologic studies. It is well documented, however, that birth certificate data can be highly inaccurate. Nonetheless, studies based on birth certificates are routinely analyzed without accounting for sources of data errors. We focused on the association between maternal cigarette smoking and cleft lip and palate based on birth certificate data. METHODS: We adjusted odds ratio estimates simultaneously for exposure and outcome misclassification. We also calculated odds ratios adjusted for exposure misclassification only and outcome misclassification only. RESULTS: Adjustment for both maternal smoking during pregnancy and clefting resulted in adjusted odds ratios that ranged from less than 1.0 to much greater than the unadjusted estimate of 1.16, with most adjusted estimates outside of the 95% confidence limits (1.01, 1.33). CONCLUSIONS: Because of the potentially large impact of birth certificate classification errors, we suggest that inferences from these or similar records employ quantitative methods for incorporating uncertainties caused by data errors.