摘要：We carried out time-series analyses in 12 U.S. cities to estimate both the acute effects and the lagged influence of weather on respiratory and cardiovascular disease (CVD) deaths. We fit generalized additive Poisson regressions for each city using nonparametric smooth functions to control for long time trend, season, and barometric pressure. We also controlled for day of the week. We estimated the effect and the lag structure of both temperature and humidity based on a distributed lag model. In cold cities, both high and low temperatures were associated with increased CVD deaths. In general, the effect of cold temperatures persisted for days, whereas the effect of high temperatures was restricted to the day of the death or the day before. For myocardial infarctions (MI), the effect of hot days was twice as large as the cold-day effect, whereas for all CVD deaths the hot-day effect was five times smaller than the cold-day effect. The effect of hot days included some harvesting, because we observed a deficit of deaths a few days later, which we did not observe for the cold-day effect. In hot cities, neither hot nor cold temperatures had much effect on CVD or pneumonia deaths. However, for MI and chronic obstructive pulmonary disease deaths, we observed lagged effects of hot temperatures (lags 4-6 and lags 3 and 4, respectively). We saw no clear pattern for the effect of humidity. In hierarchical models, greater variance of summer and winter temperature was associated with larger effects for hot and cold days, respectively, on respiratory deaths.
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