PDF(Pubmed)
Abstract：
Air pollution exposure is associated with adverse respiratory health outcomes. Evidence from occupational and community-based studies also suggests agricultural pesticides have negative health impacts on respiratory health. Although populations are exposed to multiple inhalation hazards simultaneously, multidomain mixtures (e.g. environmental and chemical pollutants of different classes) are rarely studied. We investigated the association of ambient air pollution-pesticide exposure mixtures with urinary leukotriene E4 (LTE4), a respiratory inflammation biomarker, for 75 participants in four Central California communities over two seasons. Exposures included three criteria air pollutants estimated via the Community Multiscale Air Quality model (fine particulate matter, ozone, and nitrogen dioxide) and urinary metabolites of organophosphate (OP) pesticides (total dialkyl phosphates (DAPs), total diethyl phosphates (DE), and total dimethyl phosphates (DM)). We implemented multiple linear regression models to examine associations in single pollutant models adjusted for age, sex, asthma status, occupational status, household member occupational status, temperature, and relative humidity, and evaluated whether associations changed seasonally. We then implemented Bayesian kernel machine regression (BKMR) to analyse these criteria air pollutants, DE, and DM as a mixture. Our multiple linear regression models indicated an interquartile range (IQR) increase in total DAPs was associated with an increase in urinary LTE4 in winter (β: 0.04, 95% CI: [0.01, 0.07]). Similarly, an IQR increase in total DM was associated with an increase in urinary LTE4 in winter (β:0.03, 95% CI: [0.004, 0.06]). Confidence intervals for all criteria air pollutant effect estimates included the null value. BKMR analysis revealed potential non-linear interactions between exposures in our air pollution-pesticide mixture, but all confidence intervals contained the null value. Our analysis demonstrated a positive association between OP pesticide metabolites and urinary LTE4 in a low asthma prevalence population and adds to the limited research on the joint effects of ambient air pollution and pesticides mixtures on respiratory health.
摘要：
空气污染暴露与不良呼吸道健康结果相关。来自职业和社区研究的证据也表明，农业杀虫剂对呼吸系统健康有负面影响。尽管人群同时暴露于多种吸入危害，多域混合物（例如不同类别的环境和化学污染物）很少被研究。我们调查了环境空气污染-农药暴露混合物与尿白三烯E4（LTE4）的关联，呼吸道炎症生物标志物，在两个季节中，加利福尼亚中部四个社区的75名参与者。暴露包括通过社区多尺度空气质量模型估计的三个标准空气污染物(细颗粒物，臭氧,和二氧化氮）和有机磷酸酯（OP）农药的尿代谢物（总磷酸二烷基酯（DAP），总磷酸二乙酯（DE），和总磷酸二甲酯(DM))。我们实施了多元线性回归模型，以检查根据年龄调整后的单污染物模型中的关联，性别,哮喘状态，职业状况,家庭成员的职业状况，温度,和相对湿度，并评估了协会是否季节性变化。然后，我们实施了贝叶斯核机回归(BKMR)来分析这些标准空气污染物，DE,和DM作为混合物。我们的多元线性回归模型表明，总DAP的四分位数间距（IQR）增加与冬季尿LTE4的增加有关（β：0.04，95％CI：[0.01，0.07]）。同样，总DM的IQR增加与冬季尿LTE4的增加相关(β:0.03,95%CI:[0.004,0.06])。所有标准空气污染物效应估计的置信区间包括零值。BKMR分析揭示了我们的空气污染-农药混合物中暴露之间的潜在非线性相互作用，但所有置信区间都包含空值。我们的分析表明，在低哮喘患病率人群中，OP农药代谢物与尿LTE4之间存在正相关，并且增加了对环境空气污染和农药混合物对呼吸道健康的联合影响的有限研究。
