Kumar Naresh
Department of Epidemiology and Public Health, University of Miami, Miami, FL - 33136.
Atmos Environ (1994). 2012 Mar 1;49:171-179. doi: 10.1016/j.atmosenv.2011.12.001.
Using the data on all live births (~400,000) and criteria pollutants from the Chicago Metropolitan Statistical Area (MSA) between 2000 and 2004, this paper empirically demonstrates how mismatches in the spatiotemporal scales of health and air pollution data can result in inconsistency and uncertainty in the linkages between air pollution and birth outcomes. This paper suggests that the risks of low birth weight associated with air pollution exposure changes significantly as the distance interval (around the monitoring stations) used for exposure estimation changes. For example, when the analysis was restricted within 3 miles distance of the monitoring stations the odds of LBW (births < 2500g) increased by a factor of 1.045 (±0.0285 95% CI) with a unit increase in the average daily exposure to PM(10) (in μg/m(3)) during the gestation period; the value dropped to 1.028 when the analysis was restricted within 6 miles distance of air pollution monitoring stations. The effect of PM(10) exposure on LBW became null when controlled for confounders. But PM(2.5) exposure showed a significant association with low birth weight when controlled for confounders. These results must be interpreted with caution, because the distance to monitoring station does not influence the risks of adverse birth outcomes, but uncertainty in exposure increases with the increase in distance from the monitoring stations, especially for coarse particles such as PM(10) that settle with gravity within short distance and time interval. The results of this paper have important implications for the research design of environmental epidemiological studies, and the way air pollution (and potentially other environmental) and health data are collocated to compute exposure. The paper also calls for time-space resolved estimate of air pollution to minimize uncertainty in exposure estimation.
利用2000年至2004年芝加哥大都市统计区(MSA)所有活产(约400,000例)和标准污染物的数据,本文通过实证证明了健康与空气污染数据时空尺度的不匹配如何导致空气污染与出生结局之间联系的不一致和不确定性。本文表明,随着用于暴露估计的距离间隔(围绕监测站)的变化,与空气污染暴露相关的低出生体重风险会发生显著变化。例如,当分析限制在监测站3英里范围内时,妊娠期平均每日PM(10)暴露量(以μg/m(3)为单位)每增加一个单位,低出生体重(出生体重<2500g)的几率增加1.045倍(±0.0285,95%置信区间);当分析限制在空气污染监测站6英里范围内时,该值降至1.028。在控制混杂因素后,PM(10)暴露对低出生体重的影响变得不显著。但在控制混杂因素后,PM(2.5)暴露与低出生体重显示出显著关联。这些结果必须谨慎解释,因为到监测站的距离并不影响不良出生结局的风险,但暴露的不确定性会随着与监测站距离的增加而增加,特别是对于像PM(10)这样在短距离和短时间间隔内靠重力沉降的粗颗粒。本文的结果对环境流行病学研究的设计以及空气污染(可能还有其他环境因素)与健康数据的配置方式以计算暴露具有重要意义。本文还呼吁对空气污染进行时空分辨估计,以尽量减少暴露估计中的不确定性。