Temperature and mortality among the elderly in the United States: a comparison of epidemiologic methods

Time-series analyses have been used for decades to investigate time-varying environmental exposures. Recently, the case-crossover design has been applied to assess acute effects of air pollution. Our objective was to compare time-series and case-crossover analyses using varying referent periods (ie, unidirectional, ambidirectional, and time-stratified).

We examined the association between temperature and cardiorespiratory mortality among the elderly population in the 20 largest metropolitan areas of the United States. Risks were estimated by season and geographic region in 1992. We obtained weather data from the National Climatic Data Center and mortality data from the Division of Vital Statistics. Conditional logistic regression (case-crossover) and Poisson regression (time-series) were used to estimate the increased risk of cardiorespiratory mortality associated with a 10 degrees F increase in daily temperature, accounting for dew-point temperature and other potential confounding factors.

In the time-stratified case-crossover analysis, the strongest associations were found in the summer; in the Southwest, Southeast, Northwest, Northeast, and Midwest, the odds ratios were 1.15 (95% confidence interval=1.07-1.24), 1.10 (0.96-1.27), 1.08 (0.92-1.26), 1.08 (1.02-1.15), and 1.01 (0.92-1.11), respectively. Mostly null or negative associations were found in the winter, spring, and fall. The ambidirectional case-crossover and the time-series analyses produced quantitatively similar results to those from the time-stratified analysis. The unidirectional analysis produced conflicting results.

Inferences from studies of weather and mortality using the ambidirectional or time-stratified case-crossover approaches and the time-series analyses are comparable and provide consistent findings in this study.