Rossi G, Vigotti M A, Zanobetti A, Repetto F, Gianelle V, Schwartz J
Istituto d Fisiologia Clinica, Consiglio Nazionale delle Ricerche, Pisa, Italy.
Arch Environ Health. 1999 May-Jun;54(3):158-64. doi: 10.1080/00039899909602254.
In several studies, investigators have reported associations among air pollution, weather, and daily deaths, usually from all causes. In the current study, we focused on the difference in lag time between exposure to total suspended particulates or extreme weather and cause-specific mortality in an effort to understand the potential underlying mechanism. We used a robust Poisson regression in a generalized additive model to investigate the association between air pollution and daily mortality. We used a loess smooth function to model season, weather, and humidity; indicator variables for hot days were also used. To examine the relationship in a currently meaningful range, we excluded all days with a total suspended particulate concentration higher than 200 microg/m3. We found a significant association on the concurrent day, both for respiratory infection deaths (11% increase/100 microg/m3 increase in total suspended particulate; 95% confidence interval = 5, 17) and for heart-failure deaths (7% increase; 95% confidence interval = 3, 11). The associations with myocardial infarction (i.e., 10% increase; 95% confidence interval = 3, 18) and chronic obstructive pulmonary disease (12% increase, 95% confidence interval = 6, 17) were found for the means of 3 and 4 d prior to death. We observed an effect of cold weather at lag 1 for respiratory infections and an effect of hot weather at lag 0 for heart failure and myocardial infarctions. The association for all causes and cause-specific deaths was almost identical to that noted previously in Philadelphia, Pennsylvania. Smoothed functions of total suspended particulates suggested a higher slope at lower concentrations, and this finding may account for differences noted between European and U.S. studies. Given that both the dependence between weather and daily mortality and the lag between exposure and death varies by cause of death, analyses by specific causes of death would be very useful in the future.
在多项研究中,研究人员报告了空气污染、天气与每日死亡人数之间的关联,这些死亡通常是各种原因导致的。在当前研究中,我们聚焦于总悬浮颗粒物暴露或极端天气与特定病因死亡率之间的滞后时间差异,以试图理解潜在的机制。我们在广义相加模型中使用稳健的泊松回归来研究空气污染与每日死亡率之间的关联。我们使用局部加权回归平滑函数对季节、天气和湿度进行建模;还使用了炎热日的指示变量。为了在当前有意义的范围内检验这种关系,我们排除了所有总悬浮颗粒物浓度高于200微克/立方米的日子。我们发现,在同一天,呼吸道感染死亡(总悬浮颗粒物每增加100微克/立方米,死亡人数增加11%;95%置信区间为5%,17%)和心力衰竭死亡(增加7%;95%置信区间为3%,11%)均存在显著关联。在死亡前3天和4天的均值上,发现与心肌梗死(即增加10%;95%置信区间为3%,18%)和慢性阻塞性肺疾病(增加12%,95%置信区间为6%,17%)存在关联。我们观察到,对于呼吸道感染,滞后1天有寒冷天气的影响;对于心力衰竭和心肌梗死,滞后0天有炎热天气的影响。所有原因和特定病因死亡的关联与之前在宾夕法尼亚州费城所记录的几乎相同。总悬浮颗粒物的平滑函数表明,在较低浓度时斜率更高,这一发现可能解释了欧洲和美国研究之间所指出的差异。鉴于天气与每日死亡率之间的相关性以及暴露与死亡之间的滞后因死亡原因而异,未来按特定死亡原因进行分析将非常有用。