Johns Hopkins University, Bloomberg School of Public Health, Department of Environmental Health & Engineering, Baltimore, MD, USA.
Maryland Institute of Applied Environmental Health, School of Public Health, University of Maryland, College Park, MD, USA.
Int J Hyg Environ Health. 2021 May;234:113739. doi: 10.1016/j.ijheh.2021.113739. Epub 2021 Apr 6.
Phthalates are endocrine disrupting compounds linked to various adverse health effects. U.S. national biomonitoring data indicate that select minority subgroups may suffer disparate exposures to phthalates. Still, exposures and their respective determinants among these subgroups are not well characterized.
We sought to examine determinants of phthalate exposure in a subsample of US-based Latino adults.
We conducted a cross-sectional study on 94 Latino immigrant adults in Maryland. Participants were >18 years of age and working in a service-based industry. We administered an interviewer-administered questionnaire to capture information on potential exposure determinants (e.g., demographic characteristics, consumer product use, and workplace exposures and behaviors) and using HPLC/MS-MS we quantified concentrations of 9 urinary phthalate metabolites: monoethyl phthalate (MEP, diethyl phthalate metabolite); mono-n-butyl phthalate (MBP, di-n-butyl phthalate metabolite); mono-isobutyl phthalate (MiBP, di-isobutyl phthalate metabolite; monobenzyl phthalate (MBzP, benzylbutyl phthalate metabolite); molar sum of di-2-ethylhexyl phthalate or DEHP metabolites [mono-2-ethylhexyl phthalate (MEHP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono-(2-ethyl-5-carboxypentyl) phthalate (MECCP)]; and mono(3-carboxypropyl) phthalate (MCPP, a non-specific metabolite of several phthalates including di-n-butyl phthalate and di-n-octyl phthalate). DEHP was analyzed as the molar sum of four metabolites (ΣDEHP = MEHP + MEHHP + MECPP + MEOHP). Spearman correlations, Wilcoxon-Mann-Whitney, and Kruskal-Wallis tests were conducted to assess bivariate associations between metabolite concentrations and potential exposure determinants. Covariates associated with metabolites at p < 0.10 in bivariate analyses were included in multivariable linear regression models to assess the independent effects of predictors on metabolite concentrations.
Uncorrected median phthalate metabolite concentrations were lower in our study population (<LOD-12.8 μg/L) compared to those reported in the US general population (1.0-28.8 μg/L) and adult populations in other countries. Geometric mean specific gravity-corrected concentrations for metabolites detected in >50% of samples ranged between 1.4 and 23.6 μg/L. While we observed some significant associations with select predictors in our bivariate analysis, select associations were attenuated in multivariable regression models. In our final multivariable linear regression models, we found that use of bleach (β = 1.15, 95%CI:0.30, 2.00) and consumption pasta/rice/noodles (β = 0.87, 95%CI: 0.27, 1.46) was positively associated with MBzP concentrations. MEP concentrations were inversely associated with use of furniture polish (β = -1.17, 95%CI: 2.21, -0.12) and use of scented dryer sheets (β = -1.08, 95%CI: 2.01, -0.14). Lastly, ΣDEHP concentrations were inversely associated with use of degreaser (ß = -0.65, 95%CI: 1.25, -0.05).
In this predominantly U.S.-based Central American subsample of adults, we observed lower metabolite concentrations than those previously reported in other U.S. studies and other countries. Our findings could be due, in part, to temporal trends in phthalate exposures and cultural differences related to exposure-related behaviors. While some exposure determinants were identified in our bivariate analyses, results from multivariable regression models did not provide clear results as many associations were attenuated. Environmental exposures may vary within minority subgroups and should be explored further in future studies to further inform exposure mitigation strategies.
邻苯二甲酸酯是与各种不良健康影响相关的内分泌干扰化合物。美国国家生物监测数据表明,某些少数族裔亚群可能面临不同的邻苯二甲酸酯暴露。然而,这些亚群中的暴露及其各自的决定因素仍未得到很好的描述。
我们旨在研究美国拉丁裔成年人亚群中邻苯二甲酸酯暴露的决定因素。
我们在马里兰州对 94 名拉丁裔移民成年人进行了一项横断面研究。参与者年龄大于 18 岁,从事服务业。我们通过访谈者管理的问卷来获取潜在暴露决定因素的信息(例如,人口统计学特征、消费产品使用以及工作场所暴露和行为),并使用高效液相色谱/串联质谱法(HPLC/MS-MS)定量 9 种尿邻苯二甲酸酯代谢物的浓度:单乙基邻苯二甲酸酯(MEP,邻苯二甲酸二乙酯代谢物);单正丁基邻苯二甲酸酯(MBP,邻苯二甲酸二正丁酯代谢物);单异丁基邻苯二甲酸酯(MiBP,邻苯二甲酸二异丁酯代谢物);单苄基邻苯二甲酸酯(MBzP,邻苯二甲酸丁基苄基酯代谢物);二-2-乙基己基邻苯二甲酸酯或 DEHP 代谢物的摩尔总和(单-2-乙基己基邻苯二甲酸酯(MEHP)、单-(2-乙基-5-羟基己基)邻苯二甲酸酯(MEHHP)、单-(2-乙基-5-氧代己基)邻苯二甲酸酯(MEOHP)和单-(2-乙基-5-羧基戊基)邻苯二甲酸酯(MECCP));以及单(3-羧丙基)邻苯二甲酸酯(MCPP,包括邻苯二甲酸二正丁酯和邻苯二甲酸二辛酯在内的几种邻苯二甲酸酯的非特异性代谢物)。DEHP 作为四种代谢物(ΣDEHP=MEHP+MEHHP+MECCP+MEOHP)的摩尔总和进行分析。采用 Spearman 相关分析、Wilcoxon-Mann-Whitney 和 Kruskal-Wallis 检验评估代谢物浓度与潜在暴露决定因素之间的双变量关联。在双变量分析中与代谢物相关的 p<0.10 的协变量被纳入多变量线性回归模型,以评估预测因子对代谢物浓度的独立影响。
与美国一般人群(1.0-28.8μg/L)和其他国家的成人人群(1.0-28.8μg/L)相比,我们研究人群中未经校正的邻苯二甲酸酯代谢物浓度中位数较低(<LOD-12.8μg/L)。在>50%样本中检测到的特定代谢物的几何平均特异性比重校正浓度在 1.4 至 23.6μg/L 之间。虽然我们在双变量分析中观察到一些与特定预测因子的显著关联,但在多变量回归模型中,一些关联被削弱。在我们最终的多变量线性回归模型中,我们发现使用漂白剂(β=1.15,95%CI:0.30,2.00)和食用面食/米饭/面条(β=0.87,95%CI:0.27,1.46)与 MBzP 浓度呈正相关。MEP 浓度与使用家具上光剂(β=-1.17,95%CI:2.21,-0.12)和使用有香味的干衣纸(β=-1.08,95%CI:2.01,-0.14)呈负相关。最后,ΣDEHP 浓度与使用脱脂剂(ß=-0.65,95%CI:1.25,-0.05)呈负相关。
在这个主要基于美国的中美洲成年人亚群中,我们观察到的代谢物浓度低于其他美国研究和其他国家的先前报告。我们的发现部分可能是由于邻苯二甲酸酯暴露的时间趋势和与暴露相关行为有关的文化差异。虽然在双变量分析中确定了一些暴露决定因素,但多变量回归模型的结果并没有提供明确的结果,因为许多关联被削弱。少数族裔亚群中的环境暴露可能存在差异,应在未来的研究中进一步探讨,以进一步为暴露缓解策略提供信息。