Schwartz J
Harvard School of Public Health, Exposure, Epidemiology, and Risk Program, 401 Park Drive, Suite 415 West, Boston, MA 02215, USA.
Occup Environ Med. 2004 Dec;61(12):956-61. doi: 10.1136/oem.2003.008250.
Numerous studies have reported that day-to-day changes in particulate air pollution are associated with day-to-day changes in deaths. Recently, several reports have indicated that the software used to control for season and weather in some of these studies had deficiencies.
To investigate the use of the case-crossover design as an alternative.
This approach compares the exposure of each case to their exposure on a nearby day, when they did not die. Hence it controls for seasonal patterns and for all slowly varying covariates (age, smoking, etc) by matching rather than complex modelling. A key feature is that temperature can also be controlled by matching. This approach was applied to a study of 14 US cities. Weather and day of the week were controlled for in the regression.
A 10 microg/m3 increase in PM10 was associated with a 0.36% increase in daily deaths from internal causes (95% CI 0.22% to 0.50%). Results were little changed if, instead of symmetrical sampling of control days the time stratified method was applied, when control days were matched on temperature, or when more lags of winter time temperatures were used. Similar results were found using a Poisson regression, but the case-crossover method has the advantage of simplicity in modelling, and of combining matched strata across multiple locations in a single stage analysis.
Despite the considerable differences in analytical design, the previously reported associations of particles with mortality persisted in this study. The association appeared quite linear. Case-crossover designs represent an attractive method to control for season and weather by matching.
大量研究报告称，空气中颗粒物污染的每日变化与死亡人数的每日变化相关。最近，有几份报告指出，其中一些研究中用于控制季节和天气的软件存在缺陷。
研究采用病例交叉设计作为替代方法。
该方法将每个病例的暴露情况与其在未死亡的附近日期的暴露情况进行比较。因此，它通过匹配而非复杂建模来控制季节模式和所有缓慢变化的协变量（年龄、吸烟等）。一个关键特征是温度也可以通过匹配来控制。该方法应用于对美国14个城市的研究。在回归分析中控制了天气和星期几。
PM10每增加10微克/立方米，内部原因导致的每日死亡人数增加0.36%（95%可信区间为0.22%至0.50%）。如果采用时间分层法而非对称抽样控制日，在控制日匹配温度，或使用更多冬季时间温度滞后值，结果变化不大。使用泊松回归也得到了类似结果，但病例交叉法在建模上具有简单的优势，并且在单阶段分析中能将多个地点的匹配层合并。
尽管分析设计存在相当大的差异，但本研究中先前报告的颗粒物与死亡率的关联仍然存在。这种关联看起来相当呈线性。病例交叉设计是一种通过匹配来控制季节和天气的有吸引力的方法。
