空气污染指标分析,同时确定易受影响的孕期低出生体重。

ISRN obstetrics and gynecology Pub Date : 2013-01-01 Epub Date: 2013-01-30 DOI:10.1155/2013/387452
Joshua L Warren, Montserrat Fuentes, Amy H Herring, Peter H Langlois
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引用次数: 26

摘要

除了标准的空气质量系统(AQS)污染监测数据外,还有多种表征空气污染的指标可用于环境健康分析。这些指标具有完整的时空覆盖范围,因此对于计算没有AQS监测仪的地理区域的污染暴露至关重要。我们研究了确定性化学模型(CMAQ)和结合AQS和CMAQ (DS)信息的时空下尺度统计模型(downscaler statistical model)的两个指标对风险评估的影响。使用每个指标,我们利用贝叶斯时间概率回归模型分析了环境臭氧对低出生体重的影响。对2001-2004年德克萨斯州某子域所有新生儿的每周易感性窗口进行了识别和分析,并对不同污染指标的结果进行了比较。根据DS标准,妊娠20-23周暴露量增加与低出生体重有关。单独使用CMAQ输出会导致最终风险评估估计的变异性增加,而通过使用DS度量来校准CMAQ会提供更接近于AQS的结果。在可用的情况下,AQS数据仍然是首选。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Air pollution metric analysis while determining susceptible periods of pregnancy for low birth weight.

Air pollution metric analysis while determining susceptible periods of pregnancy for low birth weight.

Air pollution metric analysis while determining susceptible periods of pregnancy for low birth weight.

Air pollution metric analysis while determining susceptible periods of pregnancy for low birth weight.

Multiple metrics to characterize air pollution are available for use in environmental health analyses in addition to the standard Air Quality System (AQS) pollution monitoring data. These metrics have complete spatial-temporal coverage across a domain and are therefore crucial in calculating pollution exposures in geographic areas where AQS monitors are not present. We investigate the impact that two of these metrics, output from a deterministic chemistry model (CMAQ) and from a spatial-temporal downscaler statistical model which combines information from AQS and CMAQ (DS), have on risk assessment. Using each metric, we analyze ambient ozone's effect on low birth weight utilizing a Bayesian temporal probit regression model. Weekly windows of susceptibility are identified and analyzed jointly for all births in a subdomain of Texas, 2001-2004, and results from the different pollution metrics are compared. Increased exposures during weeks 20-23 of the pregnancy are identified as being associated with low birth weight by the DS metric. Use of the CMAQ output alone results in increased variability of the final risk assessment estimates, while calibrating the CMAQ through use of the DS metric provides results more closely resembling those of the AQS. The AQS data are still preferred when available.

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