Nan Li1, Yun Liu2, George D Papandonatos3, Antonia M Calafat4, Charles B Eaton5, Karl T Kelsey6, Kim M Cecil7, Heidi J Kalkwarf8, Kimberly Yolton9, Bruce P Lanphear10, Aimin Chen11, Joseph M Braun12. 1. Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island, United States. Electronic address: nan_li1@brown.edu. 2. Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island, United States. Electronic address: yun_liu@brown.edu. 3. Department of Biostatistics, School of Public Health, Brown University, Providence, Rhode Island, United States. Electronic address: gdp@stat.brown.edu. 4. National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, United States. Electronic address: aic7@cdc.gov. 5. Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island, United States; Department of Family Medicine, Warren Alpert Medical School of Brown University, Providence, Rhode Island, United States; Kent Memorial Hospital, Warwick, Rhode Island, United States. Electronic address: charles_eaton@brown.edu. 6. Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island, United States; Department of Pathology and Laboratory Medicine, Brown University, Providence, Rhode Island, United States. Electronic address: karl_kelsey@brown.edu. 7. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States; Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, United States. Electronic address: Kim.Cecil@cchmc.org. 8. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States; Department of Pediatrics, Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States. Electronic address: heidi.kalkwarf@cchmc.org. 9. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States; Department of Pediatrics, Division of General and Community Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, United States. Electronic address: kimberly.yolton@cchmc.org. 10. Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada. Electronic address: bpl3@sfu.ca. 11. Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States. Electronic address: aimin.chen@pennmedicine.upenn.edu. 12. Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island, United States. Electronic address: joseph_braun_1@brown.edu.
Abstract
BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) may adversely influence cardiometabolic risk. However, few studies have examined if the timing of early life PFAS exposure modifies their relation to cardiometabolic risk. We examined the influence of gestational and childhood PFAS exposure on adolescents' cardiometabolic risk. METHODS: We quantified concentrations of four PFAS (perfluorooctanoate [PFOA], perfluorooctane sulfonate [PFOS], perfluorononanoate [PFNA], and perfluorohexane sulfonate [PFHxS]) in sera collected during pregnancy, at birth, and at ages 3, 8, and 12 years from 221 mother-child pairs in the HOME Study (enrolled 2003-06, Cincinnati, Ohio). We measured cardiometabolic risk factors using physical examinations, fasting serum biomarkers, and dual-energy X-ray absorptiometry scans at age 12 years. Cardiometabolic risk summary scores were calculated by summing age- and sex-standardized z-scores for individual cardiometabolic risk factors. We used multiple informant models to estimate covariate-adjusted associations of serum PFAS concentrations (log2-transformed) at each visit with cardiometabolic risk scores and their individual components, and tested for differences in associations across visits. RESULTS: The associations of serum PFOA concentrations with cardiometabolic risk scores differed across visits (P for heterogeneity = 0.03). Gestational and cord serum PFOA concentrations were positively associated with cardiometabolic risk scores (βs and 95% confidence intervals [95% CIs]: gestational 0.8 [0.0, 1.6]; cord 0.9 [-0.1, 1.9] per interquartile range increase). These positive associations were primarily driven by homeostatic model assessment for insulin resistance index (β = 0.3 [0.1, 0.5]) and adiponectin to leptin ratio (β = -0.5 [-1.0, 0.0]). Other individual cardiometabolic risk factors associated with gestational PFOA included insulin and waist circumference. Gestational and cord PFHxS were also associated with higher cardiometabolic risk scores (βs: gestational 0.9 [0.2, 1.6]; cord 0.9 [0.1, 1.7]). CONCLUSION: In this cohort of children with higher gestational PFOA exposure, fetal exposure to PFOA and PFHxS was associated with unfavorable cardiometabolic risk in adolescence.
BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) may adversely influence cardiometabolic risk. However, few studies have examined if the timing of early life PFAS exposure modifies their relation to cardiometabolic risk. We examined the influence of gestational and childhood PFAS exposure on adolescents' cardiometabolic risk. METHODS: We quantified concentrations of four PFAS (perfluorooctanoate [PFOA], perfluorooctane sulfonate [PFOS], perfluorononanoate [PFNA], and perfluorohexane sulfonate [PFHxS]) in sera collected during pregnancy, at birth, and at ages 3, 8, and 12 years from 221 mother-child pairs in the HOME Study (enrolled 2003-06, Cincinnati, Ohio). We measured cardiometabolic risk factors using physical examinations, fasting serum biomarkers, and dual-energy X-ray absorptiometry scans at age 12 years. Cardiometabolic risk summary scores were calculated by summing age- and sex-standardized z-scores for individual cardiometabolic risk factors. We used multiple informant models to estimate covariate-adjusted associations of serum PFAS concentrations (log2-transformed) at each visit with cardiometabolic risk scores and their individual components, and tested for differences in associations across visits. RESULTS: The associations of serum PFOA concentrations with cardiometabolic risk scores differed across visits (P for heterogeneity = 0.03). Gestational and cord serum PFOA concentrations were positively associated with cardiometabolic risk scores (βs and 95% confidence intervals [95% CIs]: gestational 0.8 [0.0, 1.6]; cord 0.9 [-0.1, 1.9] per interquartile range increase). These positive associations were primarily driven by homeostatic model assessment for insulin resistance index (β = 0.3 [0.1, 0.5]) and adiponectin to leptin ratio (β = -0.5 [-1.0, 0.0]). Other individual cardiometabolic risk factors associated with gestational PFOA included insulin and waist circumference. Gestational and cord PFHxS were also associated with higher cardiometabolic risk scores (βs: gestational 0.9 [0.2, 1.6]; cord 0.9 [0.1, 1.7]). CONCLUSION: In this cohort of children with higher gestational PFOA exposure, fetal exposure to PFOA and PFHxS was associated with unfavorable cardiometabolic risk in adolescence.
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