Relative Contributions of Agricultural Drift, Para-Occupational, and Residential Use Exposure Pathways to House Dust Pesticide Concentrations: Meta-Regression of Published Data.
Relative Contributions of Agricultural Drift, Para-Occupational, and Residential Use Exposure Pathways to House Dust Pesticide Concentrations: Meta-Regression of Published Data.
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DOI：
10.1289/ehp426
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发表时间：
2017-03
影响因子：
10.4
通讯作者：
Friesen MC
中科院分区：
文献类型：
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作者：
Deziel NC;Freeman LE;Graubard BI;Jones RR;Hoppin JA;Thomas K;Hines CJ;Blair A;Sandler DP;Chen H;Lubin JH;Andreotti G;Alavanja MC;Friesen MC
农业地区室内粉尘中农药浓度的增加可归因于几种接触途径，包括农业飘流、准职业和住宅使用。为了指导未来的暴露评估工作，我们使用已发表的粉尘农药浓度数据的元回归模型量化了这些途径的相对贡献。从1995年至2015年在北美农业区发表的研究中，我们提取了汇总统计报告的粉尘农药浓度[例如几何均值（GM）]。我们使用混合效应元回归模型对这些数据进行分析，该模型通过其逆方差对每个汇总统计量进行加权。因变量要么是对数变换的GM（漂移），要么是两组（准职业、住宅使用）GM的对数变换比率。对于漂移路径，根据来自7项研究的52项统计数据，预测的GMs急剧非线性下降，距离农田250米的家庭GMs比距离农田23米的家庭低64%（已发表数据的四分位数范围）。对于准职业途径，GMs高出2.3倍[95%置信区间（CI）： 1.5, 3.3；15项统计数据，5项研究]在最近或频繁使用农药的农民家中与最近或频繁使用农药的农民家中进行对比。对于住宅使用途径，当农药用于害虫治疗的概率分别为1-19%和≥20%时，处理过的家庭的gmms比未处理的家庭高1.3倍（95% CI: 1.1, 1.4）和1.5倍（95% CI: 1.2, 1.9）（88项统计，5项研究）。我们对农药暴露途径在农业人群中的相对贡献的量化可以改善流行病学研究中的暴露评估。当有额外的数据可用时，可以更新元回归模型。Deziel NC, Beane Freeman LE, Graubard BI, Jones RR, Hoppin JA, Thomas K, Hines CJ, Blair A, Sandler DP, Chen H, Lubin JH, Andreotti G, Alavanja MC, Friesen MC。2017。农业飘流、准职业和住宅使用暴露途径对室内粉尘农药浓度的相对贡献：已发表数据的元回归。环境健康展望125:296-305；http://dx.doi.org/10.1289/EHP426
Increased pesticide concentrations in house dust in agricultural areas have been attributed to several exposure pathways, including agricultural drift, para-occupational, and residential use. To guide future exposure assessment efforts, we quantified relative contributions of these pathways using meta-regression models of published data on dust pesticide concentrations. From studies in North American agricultural areas published from 1995 to 2015, we abstracted dust pesticide concentrations reported as summary statistics [e.g., geometric means (GM)]. We analyzed these data using mixed-effects meta-regression models that weighted each summary statistic by its inverse variance. Dependent variables were either the log-transformed GM (drift) or the log-transformed ratio of GMs from two groups (para-occupational, residential use). For the drift pathway, predicted GMs decreased sharply and nonlinearly, with GMs 64% lower in homes 250 m versus 23 m from fields (interquartile range of published data) based on 52 statistics from seven studies. For the para-occupational pathway, GMs were 2.3 times higher [95% confidence interval (CI): 1.5, 3.3; 15 statistics, five studies] in homes of farmers who applied pesticides more recently or frequently versus less recently or frequently. For the residential use pathway, GMs were 1.3 (95% CI: 1.1, 1.4) and 1.5 (95% CI: 1.2, 1.9) times higher in treated versus untreated homes, when the probability that a pesticide was used for the pest treatment was 1–19% and ≥ 20%, respectively (88 statistics, five studies). Our quantification of the relative contributions of pesticide exposure pathways in agricultural populations could improve exposure assessments in epidemiologic studies. The meta-regression models can be updated when additional data become available. Deziel NC, Beane Freeman LE, Graubard BI, Jones RR, Hoppin JA, Thomas K, Hines CJ, Blair A, Sandler DP, Chen H, Lubin JH, Andreotti G, Alavanja MC, Friesen MC. 2017. Relative contributions of agricultural drift, para-occupational, and residential use exposure pathways to house dust pesticide concentrations: meta-regression of published data. Environ Health Perspect 125:296–305; http://dx.doi.org/10.1289/EHP426