Characterization of Urinary Phthalate Metabolites Among Custodians.

Characterization of Urinary Phthalate Metabolites Among Custodians.
复制标题

监护人尿液邻苯二甲酸盐代谢物的表征。

DOI:
10.1093/annhyg/mev050
复制
发表时间:
2015
期刊:
The Annals of occupational hygiene
影响因子:
--
通讯作者:
Cherniack,Martin
Cherniack,Martin
中科院分区:
--
文献类型:
--
作者:
Cavallari,JenniferM;Simcox,NancyJ;Wakai,Sara;Lu,Chensheng;Garza,JenniferL;Cherniack,Martin

文献摘要

相似文献

邻苯二甲酸盐是一种普遍存在于消费者、个人护理和清洁产品中的化学物质,它会对健康产生不利影响。我们的目标是表征尿邻苯二甲酸盐代谢物浓度,并确定使用传统清洁化学品和“绿色”或环保产品(EPP)的保管人的工作和非工作来源。68名保管员在工作日(第一次换班、换班前、换班结束和就寝前)提供4份尿液样本,训练有素的观察员在轮班期间每小时记录一次清洁任务和使用的产品类型(传统、EPP或消毒剂)。使用问卷来评估个人护理产品的使用情况。采用液相色谱质谱法对四种不同的邻苯二甲酸酯代谢物[邻苯二甲酸一乙酯(MEP)、邻苯二甲酸一甲酯(MMP)、邻苯二甲酸一(2-乙基己基)酯(MEHP)和邻苯二甲酸一苯二酯(MBzP)]进行了定量分析。计算肌酐调整后尿邻苯二甲酸盐浓度的几何平均值(GM)和95%置信区间(95% CI)。混合效应单变量和多变量建模,对每个个体使用随机截距,以确定邻苯二甲酸酯代谢物的预测因子,包括人口统计学,工作场所因素和个人护理产品使用。肌酐调整的MEP、MMP、MEHP和MBzP尿浓度[GM (95% CI)]分别为107(91.0-126)、2.69(2.18-3.30)、6.93(6.00-7.99)、8.79(7.84-9.86)µg g−1。邻苯二甲酸盐浓度从轮班前到轮班后没有上升趋势。在调整了人口统计学、工作场所因素和个人护理产品使用的潜在混淆因素后,多变量模型中,肌酐调整后的尿MEP与传统清洁化学强度的频率显著相关。虽然许多人口统计、工作场所因素和个人护理产品是MMP、MEHP和MBzP的统计显著单变量预测因子,但在多变量模型中很少存在关联。总之,在这些看护人中,我们确定了邻苯二甲酸盐暴露的职业和非职业预测因素。在清洁化学品和消费品中确定邻苯二甲酸盐成分将使工人和消费者避免接触邻苯二甲酸盐。
Phthalates, a ubiquitous class of chemicals found in consumer, personal care, and cleaning products, have been linked to adverse health effects. Our goal was to characterize urinary phthalate metabolite concentrations and to identify work and nonwork sources among custodians using traditional cleaning chemicals and ‘green’ or environmentally preferable products (EPP). Sixty-eight custodians provided four urine samples on a workday (first void, before shift, end of shift, and before bedtime) and trained observers recorded cleaning tasks and types of products used (traditional, EPP, or disinfectant) hourly over the work shifts. Questionnaires were used to assess personal care product use. Four different phthalate metabolites [monoethyl phthalate (MEP), monomethyl phthalate (MMP), mono (2-ethylhexyl) phthalate (MEHP), and monobenzyl phthalate (MBzP)] were quantified using liquid chromatography mass spectrometry. Geometric means (GM) and 95% confidence intervals (95% CI) were calculated for creatinine-adjusted urinary phthalate concentrations. Mixed effects univariate and multivariate modeling, using a random intercept for each individual, was performed to identify predictors of phthalate metabolites including demographics, workplace factors, and personal care product use. Creatinine-adjusted urinary concentrations [GM (95% CI)] of MEP, MMP, MEHP, and MBzP were 107 (91.0–126), 2.69 (2.18–3.30), 6.93 (6.00–7.99), 8.79 (7.84–9.86) µg g−1, respectively. An increasing trend in phthalate concentrations from before to after shift was not observed. Creatinine-adjusted urinary MEP was significantly associated with frequency of traditional cleaning chemical intensity in the multivariate model after adjusting for potential confounding by demographics, workplace factors, and personal care product use. While numerous demographics, workplace factors, and personal care products were statistically significant univariate predictors of MMP, MEHP, and MBzP, few associations persisted in multivariate models. In summary, among this population of custodians, we identified both occupational and nonoccupational predictors of phthalate exposures. Identification of phthalates as ingredients in cleaning chemicals and consumer products would allow workers and consumers to avoid phthalate exposure.