Erickson Anders C, Ostry Aleck, Chan Laurie H M, Arbour Laura
Division of Medical Sciences, University of Victoria, Medical Science Bld. Rm-104, PO Box 1700 STN CSC, Victoria, V8W 2Y2, BC, Canada.
Department of Geography, University of Victoria, David Turpin Bldg. Rm-B203, PO Box 1700 STN CSC, Victoria, V8W 2Y2, BC, Canada.
Environ Health. 2016 Apr 14;15:51. doi: 10.1186/s12940-016-0133-0.
The purpose of this research was to determine the relationship between modeled particulate matter (PM2.5) exposure and birth weight, including the potential modification by maternal risk factors and indicators of socioeconomic status (SES).
Birth records from 2001 to 2006 (N = 231,929) were linked to modeled PM2.5 data from a national land-use regression model along with neighbourhood-level SES and socio-demographic data using 6-digit residential postal codes. Multilevel random coefficient models were used to estimate the effects of PM2.5, SES and other individual and neighbourhood-level covariates on continuous birth weight and test interactions. Gestational age was modeled with a random slope to assess potential neighbourhood-level differences of its effect on birth weight and whether any between-neighbourhood variability can be explained by cross-level interactions.
Models adjusted for individual and neighbourhood-level covariates showed a significant non-linear negative association between PM2.5 and birth weight explaining 8.5 % of the between-neighbourhood differences in mean birth weight. A significant interaction between SES and PM2.5 was observed, revealing a more pronounced negative effect of PM2.5 on birth weight in lower SES neighbourhoods. Further positive and negative modification of the PM2.5 effect was observed with maternal smoking, maternal age, gestational diabetes, and suspected maternal drug or alcohol use. The random intercept variance indicating between-neighbourhood birth weight differences was reduced by 75 % in the final model, while the random slope variance for between-neighbourhood gestational age effects remained virtually unchanged.
We provide evidence that neighbourhood-level SES variables and PM2.5 have both independent and interacting associations with birth weight, and together account for 49 % of the between-neighbourhood differences in birth weight. Evidence of effect modification of PM2.5 on birth weight across various maternal and neighbourhood-level factors suggests that certain sub-populations may be more or less vulnerable to relatively low doses PM2.5 exposure.
本研究的目的是确定模拟颗粒物（PM2.5）暴露与出生体重之间的关系，包括孕产妇风险因素和社会经济地位（SES）指标的潜在影响。
2001年至2006年的出生记录（N = 231,929）与来自国家土地利用回归模型的模拟PM2.5数据以及使用6位数字住宅邮政编码的社区层面的SES和社会人口数据相关联。采用多层次随机系数模型来估计PM2.5、SES以及其他个体和社区层面协变量对连续出生体重的影响，并检验相互作用。对孕周采用随机斜率模型来评估其对出生体重影响的潜在社区层面差异，以及社区间的变异性是否可通过跨层次相互作用来解释。
针对个体和社区层面协变量进行调整后的模型显示，PM2.5与出生体重之间存在显著的非线性负相关，解释了社区间平均出生体重差异的8.5%。观察到SES与PM2.5之间存在显著的相互作用，表明在较低SES社区中，PM2.5对出生体重的负面影响更为明显。随着孕产妇吸烟、孕产妇年龄、妊娠期糖尿病以及疑似孕产妇药物或酒精使用情况的变化，还观察到了PM2.5效应的进一步正向和负向改变。最终模型中，表明社区间出生体重差异的随机截距方差减少了75%，而社区间孕周效应的随机斜率方差几乎保持不变。
我们提供的证据表明，社区层面的SES变量和PM2.5与出生体重既有独立关联又有相互作用，共同解释了社区间出生体重差异的49%。关于PM2.5对出生体重在各种孕产妇和社区层面因素上的效应修正证据表明，某些亚人群可能对相对低剂量的PM2.5暴露更易或更不易受到影响。
