Single-pollutant models have linked prenatal PM exposure to lower birthweight. However, analyzing air pollutant mixtures better captures pollutant interactions and total effects. Unfortunately, strong correlations between pollutants restrict traditional methods. We explored the association between exposure to a mixture of air pollutants during different gestational age windows of pregnancy and birthweight. We included 4,635 mother-infant dyads from a New York State birth cohort born 2008–2010. Air pollution data were sourced from the EPA’s Community Multiscale Air Quality model and matched to the census tract centroid of each maternal home address. Birthweight and gestational age were extracted from vital records. We applied linear regression to study the association between prenatal exposure to PM, PM, NO, SO, and CO and birthweight during six sensitive windows. We then utilized Bayesian kernel machine regression to examine the non-linear effects and interactions within this five-pollutant mixture. Final models adjusted for maternal socio-demographics, infant characteristics, and seasonality. Single-pollutant linear regression models indicated that most pollutants were associated with a decrement in birthweight, specifically during the two-week window before birth. An interquartile range increase in PM exposure (IQR: 3.3 µg/m) from the median during this window correlated with a 34 g decrement in birthweight (95 % CI: −54, −14), followed by SO (IQR: 2.0 ppb; β: −31), PM (IQR: 4.6 µg/m; β: −29), CO (IQR: 60.8 ppb; β: −27), and NO (IQR: 7.9 ppb; β: −26). Multi-pollutant BKMR models revealed that PM, NO, and CO exposure were negatively and non-linearly linked with birthweight. As the five-pollutant mixture increased, birthweight decreased until the median level of exposure. Prenatal exposure to air pollutants, notably PM, during the final two weeks of pregnancy may negatively impact birthweight. The non-linear relationships between air pollution and birthweight highlight the importance of studying pollutant mixtures and their interactions.

中文翻译：

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北部儿童队列中空气污染物混合物的产前暴露和出生体重


单一污染物模型将产前 PM 暴露与较低的出生体重联系起来。然而，分析空气污染物混合物可以更好地捕捉污染物的相互作用和总体影响。不幸的是，污染物之间的强相关性限制了传统方法。我们探讨了不同孕龄窗口期间暴露于空气污染物混合物与出生体重之间的关联。我们纳入了来自 2008 年至 2010 年出生的纽约州出生队列的 4,635 名母婴组合。空气污染数据来自 EPA 的社区多尺度空气质量模型，并与每个母亲家庭住址的人口普查区质心相匹配。从生命记录中提取出生体重和胎龄。我们应用线性回归来研究六个敏感窗口期间产前接触 PM、PM、NO、SO 和 CO 与出生体重之间的关联。然后，我们利用贝叶斯核机器回归来检查这种五种污染物混合物中的非线性效应和相互作用。最终模型根据母亲的社会人口统计、婴儿特征和季节性进行了调整。单污染物线性回归模型表明，大多数污染物与出生体重的下降有关，特别是在出生前两周的时间内。在此窗口期间，PM 暴露量（IQR：3.3 µg/m）相对于中位数的四分位数范围增加与出生体重下降 34 g 相关（95% CI：-54，-14），其次是 SO（IQR：2.0 ppb； β：-31)、PM（IQR：4.6 µg/m；β：-29）、CO（IQR：60.8 ppb；β：-27）和 NO（IQR：7.9 ppb；β：-26）。多污染物 BKMR 模型显示，PM、NO 和 CO 暴露与出生体重呈负非线性关系。 随着五种污染物混合物的增加，出生体重下降，直至达到中位暴露水平。在怀孕的最后两周内，产前接触空气污染物，尤其是 PM，可能会对出生体重产生负面影响。空气污染与出生体重之间的非线性关系凸显了研究污染物混合物及其相互作用的重要性。