Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan 610041, China.
Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong 511430, China.
Sci Total Environ. 2019 May 10;664:99-106. doi: 10.1016/j.scitotenv.2019.02.018. Epub 2019 Feb 2.
Acute mortality effects of air pollution have been recognized in plenty of environmental epidemiologic studies. However, existing studies usually assume a universal lag association across sites and seasons. Such a strategy ignores the heterogeneity of lag structures and may lead to bias in the estimation of effects.
A Bayesian hierarchical model with flexible lag structures was applied to estimate the impact of particulate matter less than 10 μm (PM) on mortality and determine whether the lag structure varied by season and location. Data from nine US communities, obtained from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), was used to examine the lagged associations between PM and daily mortality. The estimates obtained from the flexible lag approaches were compared with those from the universal lag approach.
Of potential varying lag structures, a 10-μg/m increase in PM was associated with 0.32% (95% credible interval: 0.16, 0.45) and 0.36% (0.18, 0.52) increases in mortality from nonaccidental and cardiovascular-respiratory death. The community-specific estimates of PM mortality effects were distinct between the flexible and the universal lag approaches, with relative change of the effects ranged from -7.21% to 9.25% for nonaccidental morality, and from -5.78% to 4.16% for cardiovascular-respiratory morality. Moreover, the lag structure varied by location and season. For instance, the nonaccidental mortality effect of PM attributable to the current and previous day was 29.8% in El Paso while 55.0% in Chicago; the overall effect attributable to the previous two to five days were 60.6%, 51.9%, 59.5%, and 59.3% in winter, spring, summer, and fall, respectively.
The results indicated that a universal lag association across sites and seasons may bias the mortality effect of air pollution. The varying lag structures should be considered in studies of short-term environmental exposures to get a more precise effect estimate.
大量环境流行病学研究已经认识到空气污染的急性死亡率影响。然而，现有研究通常假设站点和季节之间存在普遍的滞后关联。这种策略忽略了滞后结构的异质性，可能导致效应估计的偏差。
应用具有灵活滞后结构的贝叶斯层次模型来估计小于 10μm 的颗粒物（PM）对死亡率的影响，并确定滞后结构是否因季节和地点而异。使用来自美国九个社区的数据，这些数据来自国家发病率、死亡率和空气污染研究（NMMAPS），以检验 PM 与每日死亡率之间的滞后关联。从灵活滞后方法中获得的估计值与从通用滞后方法中获得的估计值进行了比较。
在潜在的变化滞后结构中，PM 每增加 10μg/m，非意外和心血管-呼吸系统死亡的死亡率分别增加 0.32%（95%可信区间：0.16，0.45）和 0.36%（0.18，0.52）。PM 死亡率效应的社区特异性估计在灵活和通用滞后方法之间存在明显差异，效应的相对变化范围为非意外死亡率的-7.21%至 9.25%，心血管-呼吸系统死亡率的-5.78%至 4.16%。此外，滞后结构因地点和季节而异。例如，PM 对埃尔帕索非意外死亡率的当前和前一天的归因效应为 29.8%，而在芝加哥为 55.0%；前两到五天的总归因效应分别为 60.6%、51.9%、59.5%和 59.3%，分别在冬季、春季、夏季和秋季。
结果表明，站点和季节之间的普遍滞后关联可能会使空气污染的死亡率效应产生偏差。在研究短期环境暴露时，应考虑变化的滞后结构，以获得更精确的效应估计。
