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ORIGINAL RESEARCH article

Front. Public Health
Sec. Environmental Health and Exposome
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1474994

Exploring the Impact of Polychlorinated Biphenyls on Comorbidity and Potential Mitigation Strategies

Provisionally accepted
Ying Gao Ying Gao 1Han Lu Han Lu 2Huan ZHOU Huan ZHOU 1Jiaxing Tan Jiaxing Tan 1*
  • 1 West China Hospital, Sichuan University, Chengdu, China
  • 2 Sichuan University, Chengdu, Sichuan Province, China

The final, formatted version of the article will be published soon.

    Polychlorinated Biphenyls (PCBs) persist in the environment and accumulate in humans. Currently, there is a lack of understanding about the overall impact of PCBs on human health, and effective interventions for exposed populations are insufficient.Our study aimed to assess the impact of PCBs on various diseases and mortality risks using data from the National Health and Nutrition Examination Survey, while proposing lifestyle adjustments, particularly dietary modifications, to mitigate mortality risk. Statistical analyses employed principal component analysis, multifactorial logistic regression, multifactorial Cox regression, comorbidity network analysis, and machine learning prediction models. Results indicated significant associations between 7 types of PCBs and 12 diseases (p < 0.05), with 6 diseases showing significant positive correlations (OR > 1, p < 0.05), along with listing the 25 most relevant diseases, such as asthma and chronic bronchitis (OR [95% CI] = 5.85 [4.37, 7.83], p < 0.0001), arthritis and osteoporosis (OR [95% CI] = 6.27 [5.23, 7.55], p < 0.0001). This suggested that PCBs may be intimately involved in the development and progression of multiple diseases. By constructing multidimensional machine learning models and conducting multiple iterations for precision and error measurement, PCBs may have the potential to become specific biomarkers for certain diseases in the future. Building upon this, we further suggested that controlling dietary intake to reduce dietary inflammatory index (DII) could lower mortality and disease risks. While PCBs were independent risk factors for mortality, substantial evidence suggested that adjusting DII might mitigate the adverse effects of PCBs to some extent. Further physiological mechanisms require deeper exploration through additional research.

    Keywords: Polychlorinated Biphenyls, machine learning, Mortality, comorbidities, DiI

    Received: 02 Aug 2024; Accepted: 14 Oct 2024.

    Copyright: © 2024 Gao, Lu, ZHOU and Tan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Jiaxing Tan, West China Hospital, Sichuan University, Chengdu, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.