A Comparison of Two Statistical Models for Analyzing the Association Between Pm10 and Hospital Admissions for Chronic Obstructive Pulmonary Disease

Abstract

Two statistical regression models-the autoregressive integrated moving average (ARIMA) and the generalized additive model (GAM)-were compared in terms of their ability to assess the association between ambient particulate air pollution concentrations (PM10) and daily hospital admissions for chronic obstructive pulmonary disease (COPD) in Reno-Sparks, Nevada, during the period 1990 to 1994. The study involved 3115 admissions for COPD. The daily average concentration of ambient PM10 was 36.55 μg/m3. After being adjusted for the effects of weather, day of the week, season, and time trend, both the ARIMA and the GAM methods consistently found that PM10 is a statistically significant predictor of daily hospital admissions for COPD. The percentage increase in hospital admissions for COPD for an interquartile increase (26.6 μg/m3) of the 24-h average of PM10 on the 14 prior days is 4.29% (95% CI 1.22∼7.36%) with ARIMA analysis and 5.62% (95% CI 2.16∼9.08%) with GAM analysis. The percentage increase in hospital a...