BACKGROUND: The propensity score method has been underused in research concerning asthma epidemiology, which is useful for addressing covariate imbalance in observational studies. OBJECTIVE: To examine the impact of neighborhood environment on asthma incidence by applying the propensity score method. METHODS: The study was designed as a retrospective cohort study. Study subjects were all children born in Rochester, Minn, between 1976 and 1979. Asthma status was previously determined by applying predetermined criteria. We applied the propensity score method to match children who lived in census tracts facing or not facing intersections with major highways or railroads. The propensity score of children living in a census tract facing intersections was formulated from a logistic regression model with 16 variables that may not be balanced between comparison groups. The Cox proportional hazard models were used in the matched samples to estimate hazard ratios of neighborhood environment and some other variables of interest and their corresponding 95% CIs. RESULTS: After matching with propensity scores, we found that children who lived in census tracts facing intersections with major highways or railroads had a higher risk of asthma (hazard ratios, 1.385-1.669 depending on the matching methods) compared with the matched counterparts who lived in census tracts not facing intersections with major highways or railroads. CONCLUSION: Neighborhood environment may be an important risk factor in understanding the development of pediatric asthma. The propensity score method is a useful tool in addressing covariate imbalance and exploring for causal effect in studying asthma epidemiology. Copyright (c) 2010 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.
BACKGROUND: The propensity score method has been underused in research concerning asthma epidemiology, which is useful for addressing covariate imbalance in observational studies. OBJECTIVE: To examine the impact of neighborhood environment on asthma incidence by applying the propensity score method. METHODS: The study was designed as a retrospective cohort study. Study subjects were all children born in Rochester, Minn, between 1976 and 1979. Asthma status was previously determined by applying predetermined criteria. We applied the propensity score method to match children who lived in census tracts facing or not facing intersections with major highways or railroads. The propensity score of children living in a census tract facing intersections was formulated from a logistic regression model with 16 variables that may not be balanced between comparison groups. The Cox proportional hazard models were used in the matched samples to estimate hazard ratios of neighborhood environment and some other variables of interest and their corresponding 95% CIs. RESULTS: After matching with propensity scores, we found that children who lived in census tracts facing intersections with major highways or railroads had a higher risk of asthma (hazard ratios, 1.385-1.669 depending on the matching methods) compared with the matched counterparts who lived in census tracts not facing intersections with major highways or railroads. CONCLUSION: Neighborhood environment may be an important risk factor in understanding the development of pediatric asthma. The propensity score method is a useful tool in addressing covariate imbalance and exploring for causal effect in studying asthma epidemiology. Copyright (c) 2010 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.
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