Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, Berkeley, 1995 University Avenue, Berkeley, CA 94704, USA.
Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Hwy, Atlanta, GA 30341, USA.
Sci Total Environ. 2020 Jul 10;725:138418. doi: 10.1016/j.scitotenv.2020.138418. Epub 2020 Apr 3.
Chemicals found in personal care products and plastics have been associated with asthma, allergies, and lung function, but methods to address real life exposure to mixtures of these chemicals have not been applied to these associations.
We quantified urinary concentrations of eleven phthalate metabolites, four parabens, and five other phenols in mothers twice during pregnancy and assessed probable asthma, aeroallergies, and lung function in their age seven children. We implemented Bayesian Profile Regression (BPR) to cluster women by their exposures to these chemicals and tested the clusters for differences in outcome measurements. We used Bayesian Kernel Machine Regression (BKMR) to fit biomarkers into one model as joint independent variables.
BPR clustered women into seven groups characterized by patterns of personal care product and plastic use, though there were no significant differences in outcomes across clusters. BKMR showed that monocarboxyisooctyl phthalate and 2,4-dichlorophenol were associated with probable asthma (predicted probability of probable asthma per IQR of biomarker z-score (standard deviation) = 0.08 (0.09) and 0.11 (0.12), respectively) and poorer lung function (predicted probability per IQR = -0.07 (0.05) and -0.07 (0.06), respectively), and that mono(3-carboxypropyl) phthalate and bisphenol A were associated with aeroallergies (predicted probability per IQR = 0.13 (0.09) and 0.11 (0.08), respectively). Several biomarkers demonstrated positive additive effects on other associations.
BPR and BKMR are useful tools to evaluate associations of biomarker concentrations within a mixture of exposure and should supplement single-chemical regression models when data allow.
个人护理产品和塑料中所含的化学物质与哮喘、过敏和肺功能有关，但尚未将这些化学物质混合物的实际暴露方法应用于这些关联。
我们在两次怀孕期间测量了母亲尿液中 11 种邻苯二甲酸代谢物、4 种对羟基苯甲酸酯和 5 种其他酚类物质的浓度，并评估了其 7 岁儿童的疑似哮喘、过敏性气道疾病和肺功能。我们采用贝叶斯轮廓回归（BPR）按这些化学物质的暴露情况对女性进行聚类，并对聚类结果进行了分析。我们使用贝叶斯核机器回归（BKMR）将生物标志物纳入一个模型中作为联合独立变量。
BPR 按个人护理产品和塑料使用模式将女性聚类为七个群组，尽管在群组之间没有观察到结果的显著差异。BKMR 表明，单羧基异辛基邻苯二甲酸和 2,4-二氯苯酚与疑似哮喘（生物标志物 z 分数（标准差）的 IQR 每单位预测的疑似哮喘概率分别为 0.08（0.09）和 0.11（0.12））和较差的肺功能（IQR 每单位预测的概率分别为 -0.07（0.05）和 -0.07（0.06））有关，单（3-羧丙基）邻苯二甲酸和双酚 A 与过敏性气道疾病有关（IQR 每单位预测的概率分别为 0.13（0.09）和 0.11（0.08））。几种生物标志物对其他关联表现出正的相加效应。
BPR 和 BKMR 是评估混合物中暴露与生物标志物浓度之间关联的有用工具，当数据允许时，应补充单一化学物质回归模型。
