Navdep Kaur1, Anne P Starling2, Antonia M Calafat3, Andreas Sjodin3, Noemie Clouet-Foraison4, Lawrence M Dolan5, Giuseppina Imperatore6, Elizabeth T Jensen7, Jean M Lawrence8, Maria Ospina3, Catherine Pihoker9, Kyla W Taylor10, Christine Turley11, Dana Dabelea2, Lindsay M Jaacks12. 1. Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 2. Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA. 3. Division of Laboratory Sciences, Centers for Disease Control and Prevention, Atlanta, GA, USA. 4. Northwest Lipid Metabolism and Diabetes Research Laboratory, Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, University of Washington, Seattle, WA, USA. 5. Division of Endocrinology, Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, OH, USA. 6. Division of Diabetes Translation, Centers for Disease Control and Prevention (CDC), National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA, USA. 7. Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC, USA. 8. Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA. 9. Department of Pediatrics, University of Washington, Seattle, WA, USA. 10. Office of Health Assessment and Translation, National Toxicology Program, National Institute of Environmental Health Sciences, Durham, NC, USA. 11. Department of Pediatrics, University of South Carolina School of Medicine, Columbia, SC, USA. 12. Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: jaacks@hsph.harvard.edu.
Abstract
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death among individuals with diabetes, but little is known about the role of exposures to environmental chemicals such as pesticides in the early development of CVD risk in this population. OBJECTIVES: To describe changes over time in concentrations of pesticide biomarkers among youth with diabetes in the United States and to estimate the longitudinal association between these concentrations and established risk factors for CVD. METHODS: Pesticide biomarkers were quantified in urine and serum samples from 87 youth with diabetes participating in the multi-center SEARCH cohort study. Samples were obtained around the time of diagnosis (baseline visit, between 2006 and 2010) and, on average, 5.4 years later (follow-up visit, between 2012 and 2015). We calculated geometric mean (95% CI) pesticide biomarker concentrations. Eight CVD risk factors were measured at these two time points: body mass index (BMI) z-score, HbA1c, insulin sensitivity, fasting C-peptide (FCP), LDL cholesterol, HDL cholesterol, total cholesterol, and triglycerides. Linear regression models were used to estimate the associations between each pesticide biomarker at baseline and each CVD risk factor at follow-up, adjusting for baseline health outcome, elapsed time between baseline and follow up, sex, age, race/ethnicity, and diabetes type. RESULTS: Participants were, on average, 14.2 years old at their baseline visit, and most were diagnosed with type 1 diabetes (57.5%). 4-nitrophenol, 3-phenoxybenzoic acid, 2,4-dichlorophenoxyacetic acid (2,4-D), 3,5,6-trichloro-2-pyridinol, 2,2-bis(4-chlorophenyl)-1,1-dichloroethene, and hexachlorobenzene were detected in a majority of participants at both time points. Participants in the highest quartile of 2,4-D and 4-nitrophenol at baseline had HbA1c levels at follow-up that were 1.05 percentage points (95% CI: -0.40, 2.51) and 1.27 percentage points (0.22, 2.75) higher, respectively, than participants in the lowest quartile of these pesticide biomarkers at baseline. These participants also had lower log FCP levels (indicating reduced beta-cell function) compared to participants in the lowest quartile at baseline: beta (95% CI) for log FCP of -0.64 (-1.17, -0.11) for 2,4-D and -0.39 (-0.96, 0.18) for 4-nitrophenol. In other words, participants in the highest quartile of 2,4-D had a 47.3% lower FCP level compared to participants in the lowest quartile, and those in the highest quartile of 4-nitrophenol had a 32.3% lower FCP level than those in the lowest quartile. Participants with trans-nonachlor concentrations in the highest quartile at baseline had HbA1c levels that were 1.45 percentage points (-0.11, 3.01) higher and log FCP levels that were -0.28 (-0.84, 0.28) lower than participants in the lowest quartile at baseline, that is to say, participants in the highest quartile of trans-nonachlor had a 24.4% lower FCP level than those in the lowest quartile. While not all of these results were statistically significant, potentially due to the small same size, clinically, there appears to be quantitative differences. No associations were observed between any pesticide biomarker at baseline with BMI z-score or insulin sensitivity at follow-up. CONCLUSIONS: Exposure to select pesticides may be associated with impaired beta-cell function and poorer glycemic control among youth with diabetes.
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death among individuals with diabetes, but little is known about the role of exposures to environmental chemicals such as pesticides in the early development of CVD risk in this population. OBJECTIVES: To describe changes over time in concentrations of pesticide biomarkers among youth with diabetes in the United States and to estimate the longitudinal association between these concentrations and established risk factors for CVD. METHODS: Pesticide biomarkers were quantified in urine and serum samples from 87 youth with diabetes participating in the multi-center SEARCH cohort study. Samples were obtained around the time of diagnosis (baseline visit, between 2006 and 2010) and, on average, 5.4 years later (follow-up visit, between 2012 and 2015). We calculated geometric mean (95% CI) pesticide biomarker concentrations. Eight CVD risk factors were measured at these two time points: body mass index (BMI) z-score, HbA1c, insulin sensitivity, fasting C-peptide (FCP), LDL cholesterol, HDL cholesterol, total cholesterol, and triglycerides. Linear regression models were used to estimate the associations between each pesticide biomarker at baseline and each CVD risk factor at follow-up, adjusting for baseline health outcome, elapsed time between baseline and follow up, sex, age, race/ethnicity, and diabetes type. RESULTS: Participants were, on average, 14.2 years old at their baseline visit, and most were diagnosed with type 1 diabetes (57.5%). 4-nitrophenol, 3-phenoxybenzoic acid, 2,4-dichlorophenoxyacetic acid (2,4-D), 3,5,6-trichloro-2-pyridinol, 2,2-bis(4-chlorophenyl)-1,1-dichloroethene, and hexachlorobenzene were detected in a majority of participants at both time points. Participants in the highest quartile of 2,4-D and 4-nitrophenol at baseline had HbA1c levels at follow-up that were 1.05 percentage points (95% CI: -0.40, 2.51) and 1.27 percentage points (0.22, 2.75) higher, respectively, than participants in the lowest quartile of these pesticide biomarkers at baseline. These participants also had lower log FCP levels (indicating reduced beta-cell function) compared to participants in the lowest quartile at baseline: beta (95% CI) for log FCP of -0.64 (-1.17, -0.11) for 2,4-D and -0.39 (-0.96, 0.18) for 4-nitrophenol. In other words, participants in the highest quartile of 2,4-D had a 47.3% lower FCP level compared to participants in the lowest quartile, and those in the highest quartile of 4-nitrophenol had a 32.3% lower FCP level than those in the lowest quartile. Participants with trans-nonachlor concentrations in the highest quartile at baseline had HbA1c levels that were 1.45 percentage points (-0.11, 3.01) higher and log FCP levels that were -0.28 (-0.84, 0.28) lower than participants in the lowest quartile at baseline, that is to say, participants in the highest quartile of trans-nonachlor had a 24.4% lower FCP level than those in the lowest quartile. While not all of these results were statistically significant, potentially due to the small same size, clinically, there appears to be quantitative differences. No associations were observed between any pesticide biomarker at baseline with BMI z-score or insulin sensitivity at follow-up. CONCLUSIONS: Exposure to select pesticides may be associated with impaired beta-cell function and poorer glycemic control among youth with diabetes.
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