Sex-specific, non-linear and congener-specific association between mixed exposure to polychlorinated biphenyls (PCBs) and diabetes in U.S. adults
Background: Whether and to what extent the impact of exposure to various polychlorinated biphenyls (PCBs) congeners on diabetes, as well as the important contributors, have remained unclear. Objective: We aimed to investigate the association patterns between PCBs mixture and diabetes, identify the c...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | Ecotoxicology and Environmental Safety |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0147651324001660 |
| _version_ | 1827345411494379520 |
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| author | Keyu Pan Huixun Jia Renjie Chen Chang Su Huijun Wang Tao Zhang Zhenyu Wu |
| author_facet | Keyu Pan Huixun Jia Renjie Chen Chang Su Huijun Wang Tao Zhang Zhenyu Wu |
| author_sort | Keyu Pan |
| collection | DOAJ |
| description | Background: Whether and to what extent the impact of exposure to various polychlorinated biphenyls (PCBs) congeners on diabetes, as well as the important contributors, have remained unclear. Objective: We aimed to investigate the association patterns between PCBs mixture and diabetes, identify the critical congeners, and explore the potential modifiers. Methods: The present study included 5900 U.S. adults from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2016. Weighted logistic regression, restricted cubic spline regression, weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were applied to estimate the linear and non-linear associations of single and mixed PCB exposure with diabetes. Subgroup analyses were also conducted to explore potential sex differences. Results: In the weighted logistic regression model, total PCBs were positively associated with diabetes (OR = 1.33, P < 0.025), and significant non-linear associations were observed using RCS analyses. The non-linear positive association between PCBs mixed exposure and diabetes was likewise found in the WQS and BKMR results. PCB180, PCB194, PCB196, and PCB167 were with the highest weights in the WQS, and PCB209 and PCB66 were with the highest posterior inclusion probabilities in the BKMR. Additionally, exposure to total PCBs and most of individual PCB congeners were significantly associated with elevated risk of in females (OR = 1.74; P for trend < 0.001), while fewer significant associations were observed in males. Conclusion: The present study highlighted the importance of the long-term surveillance of PCBs and the need to enhance protective measures against them. Notably, these associations were non-linear, congener-specific, and significantly stronger in females than males, especially at relatively high levels of PCBs exposure. Further prospective and mechanistic studies were warranted to ascertain the causal effects between PCBs mixture and diabetes. |
| first_indexed | 2024-03-07T23:07:19Z |
| format | Article |
| id | doaj.art-a16fabd75f9e4072bd349af7a5b932d9 |
| institution | Directory Open Access Journal |
| issn | 0147-6513 |
| language | English |
| last_indexed | 2024-03-07T23:07:19Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecotoxicology and Environmental Safety |
| spelling | doaj.art-a16fabd75f9e4072bd349af7a5b932d92024-02-22T04:51:38ZengElsevierEcotoxicology and Environmental Safety0147-65132024-03-01272116091Sex-specific, non-linear and congener-specific association between mixed exposure to polychlorinated biphenyls (PCBs) and diabetes in U.S. adultsKeyu Pan0Huixun Jia1Renjie Chen2Chang Su3Huijun Wang4Tao Zhang5Zhenyu Wu6Department of Biostatistics, School of Public Health, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.; Institute for Medical Dataology, Shandong University, Jinan 250012, ChinaNational Clinical Research Center for Ophthalmic Diseases; Department of Ophthalmology, Shanghai General Hospital (Shanghai First People’s Hospital), Shanghai Jiao Tong University, School of Medicine, Shanghai, China; Shanghai Key Laboratory of Fundus Diseases, Shanghai, China; School of Public Health, Fudan University, Shanghai 200032, ChinaSchool of Public Health, Fudan University, Shanghai 200032, ChinaNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, ChinaNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China; Correspondence to: Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, 155 Changba Road, Beijing 100050, China.Department of Biostatistics, School of Public Health, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.; Institute for Medical Dataology, Shandong University, Jinan 250012, China; Clinical Research Center of Shandong University, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, China; Correspondence to: Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, PO Box 100, 44 Wenhuaxi Road, Jinan 250012, China.School of Public Health, Fudan University, Shanghai 200032, China; Correspondence to: Department of Biostatistics, School of Public Health, Key Laboratory of Public Health Safety and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai 200032, China.Background: Whether and to what extent the impact of exposure to various polychlorinated biphenyls (PCBs) congeners on diabetes, as well as the important contributors, have remained unclear. Objective: We aimed to investigate the association patterns between PCBs mixture and diabetes, identify the critical congeners, and explore the potential modifiers. Methods: The present study included 5900 U.S. adults from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2016. Weighted logistic regression, restricted cubic spline regression, weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were applied to estimate the linear and non-linear associations of single and mixed PCB exposure with diabetes. Subgroup analyses were also conducted to explore potential sex differences. Results: In the weighted logistic regression model, total PCBs were positively associated with diabetes (OR = 1.33, P < 0.025), and significant non-linear associations were observed using RCS analyses. The non-linear positive association between PCBs mixed exposure and diabetes was likewise found in the WQS and BKMR results. PCB180, PCB194, PCB196, and PCB167 were with the highest weights in the WQS, and PCB209 and PCB66 were with the highest posterior inclusion probabilities in the BKMR. Additionally, exposure to total PCBs and most of individual PCB congeners were significantly associated with elevated risk of in females (OR = 1.74; P for trend < 0.001), while fewer significant associations were observed in males. Conclusion: The present study highlighted the importance of the long-term surveillance of PCBs and the need to enhance protective measures against them. Notably, these associations were non-linear, congener-specific, and significantly stronger in females than males, especially at relatively high levels of PCBs exposure. Further prospective and mechanistic studies were warranted to ascertain the causal effects between PCBs mixture and diabetes.http://www.sciencedirect.com/science/article/pii/S0147651324001660Polychlorinated biphenylsDiabetesRestricted cubic splineWeighted quantile sum regressionBayesian kernel machine regression |
| spellingShingle | Keyu Pan Huixun Jia Renjie Chen Chang Su Huijun Wang Tao Zhang Zhenyu Wu Sex-specific, non-linear and congener-specific association between mixed exposure to polychlorinated biphenyls (PCBs) and diabetes in U.S. adults Ecotoxicology and Environmental Safety Polychlorinated biphenyls Diabetes Restricted cubic spline Weighted quantile sum regression Bayesian kernel machine regression |
| title | Sex-specific, non-linear and congener-specific association between mixed exposure to polychlorinated biphenyls (PCBs) and diabetes in U.S. adults |
| title_full | Sex-specific, non-linear and congener-specific association between mixed exposure to polychlorinated biphenyls (PCBs) and diabetes in U.S. adults |
| title_fullStr | Sex-specific, non-linear and congener-specific association between mixed exposure to polychlorinated biphenyls (PCBs) and diabetes in U.S. adults |
| title_full_unstemmed | Sex-specific, non-linear and congener-specific association between mixed exposure to polychlorinated biphenyls (PCBs) and diabetes in U.S. adults |
| title_short | Sex-specific, non-linear and congener-specific association between mixed exposure to polychlorinated biphenyls (PCBs) and diabetes in U.S. adults |
| title_sort | sex specific non linear and congener specific association between mixed exposure to polychlorinated biphenyls pcbs and diabetes in u s adults |
| topic | Polychlorinated biphenyls Diabetes Restricted cubic spline Weighted quantile sum regression Bayesian kernel machine regression |
| url | http://www.sciencedirect.com/science/article/pii/S0147651324001660 |
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