The US PFAS exposure burden calculator for 2017-2018: Application to the HOME Study, with comparison of epidemiological findings from NHANES

被引:4
|
作者
Liu, Shelley H. [1 ]
Chen, Yitong [1 ]
Feuerstahler, Leah [2 ]
Chen, Aimin [3 ]
Starling, Anne [4 ]
Dabelea, Dana [5 ]
Wang, Xiaobin [6 ]
Cecil, Kim [7 ]
Lanphear, Bruce [8 ]
Yolton, Kimberly [9 ]
Braun, Joseph M. [10 ]
Buckley, Jessie P. [11 ]
机构
[1] Icahn Sch Med Mt Sinai, Dept Populat Hlth Sci & Policy, New York, NY 10029 USA
[2] Fordham Univ, Dept Psychol, Bronx, NY USA
[3] Univ Penn, Perelman Sch Med, Dept Biostat Epidemiol & Informat, Philadelphia, PA USA
[4] Univ North Carolina Chapel Hill, Gillings Sch Global Publ Hlth, Dept Epidemiol, Chapel Hill, NC USA
[5] Univ Colorado, Colorado Sch Publ Hlth, Dept Epidemiol, Anschutz Med Campus, Aurora, CO USA
[6] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Populat Family & Reprod Hlth, Hlth Sch Publ Hlth, Baltimore, MD USA
[7] Univ Cincinnati, Dept Radiol, Cincinnati, OH 45267 USA
[8] Simon Fraser Univ, Dept Hlth Sci, Burnaby, BC, Canada
[9] Univ Cincinnati, Cincinnati Childrens Hosp, Coll Med, Dept Pediat,Med Ctr, Cincinnati, OH USA
[10] Brown Univ, Sch Publ Hlth, Dept Epidemiol, Providence, RI USA
[11] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Environm Hlth & Engn, Baltimore, MD USA
关键词
PFAS; Chemical mixtures; Cardiometabolic; Item response theory; Psychometrics; Latent variable models; POLYFLUOROALKYL SUBSTANCES; PERFLUOROALKYL CHEMICALS; SERUM-LIPIDS; ASSOCIATION; HOMEOSTASIS; CHILDREN; GLUCOSE; ACIDS;
D O I
10.1016/j.ntt.2024.107321
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Background: The 2017-2018 U.S. PFAS exposure burden calculator was designed to provide a summary exposure score for per- and polyfluoroalkyl substances (PFAS) mixtures using targeted PFAS analyte data. Its aim was to place PFAS burden score estimates onto a common scale based on nationally representative U.S. reference ranges from 2017 to 2018, enabling comparisons of overall PFAS burden scores across studies even if they did not measure the same set of PFAS analytes. Objective: To use the U.S. PFAS exposure burden calculator for comparing the same mixture of PFAS compounds in similarly aged adolescents and their associations with cardiometabolic outcomes in the HOME Study and NHANES between 2015 and 2018. Methods: We applied the PFAS burden calculator to 8 PFAS analytes measured in the serum of adolescents from the HOME Study (Cincinnati, Ohio; age range 11-14 years; years: 2016-2019; n = 207) and NHANES (US; age range 12-14 years; years 2015-2018; n = 245). We used the non -parametric Mann -Whitney U test and chisquared test to compare the two study samples. In both studies, we examined associations of PFAS burden scores with the same cardiometabolic outcomes, adjusted for the same core set of covariates using regression analyses. We conducted sensitivity analyses to verify robustness of exposure -outcome associations, by accounting for measurement error of PFAS burden scores. Results: PFAS burden scores were significantly different (p = 0.004) between the HOME Study (median: 0.00, interquartile range - 0.37, 0.34) and the NHANES samples (median: 0.04, IQR -0.11, 0.54), while no significant difference was found for PFAS summed concentrations (p = 0.661). In the HOME Study, an interquartile (IQR) increase in PFAS burden score was associated with higher total cholesterol [7.0 mg/dL, 95% CI: 0.6, 13.4]; HDL [2.8 mg/dL, 95% CI: 0.4, 5.2]; LDL [5.9 mg/dL, 95% CI: 0.5, 11.3], insulin [0.1 log(mIU/L), 95% CI: 0.01, 0.2], and HOMA-IR [0.1, 95% CI: 0.01, 0.2]. In NHANES, an IQR increase in PFAS burden score was associated with higher diastolic blood pressure [2.4 mmHg, 95% CI: 0.4, 4.4] but not with other outcomes. Sensitivity analyses in the HOME Study and NHANES were consistent with the main findings. Conclusions: Performance of the U.S. PFAS exposure burden calculator was similar in a local versus national sample of adolescents, and may be a useful tool for the assessment of PFAS mixtures across studies.
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页数:10
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