Your browser doesn't support javascript.
loading
Potential lethality of organochlorine pesticides: Inducing fatality through inflammatory responses in the organism.
Tan, Jiaxing; Ma, Mengkai; Shen, Xinyue; Xia, Yuanlin; Qin, Wei.
Afiliação
  • Tan J; Division of Nephrology, Department of Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Pediatrics, Pennsylvania State University College of Medicine, Hershey, PA, USA. Electronic address: xingest@foxmail.com.
  • Ma M; West China School of Medicine, Sichuan University, Chengdu, Sichuan, China. Electronic address: mengkaima0403@163.com.
  • Shen X; College of Information and Engineering, Wenzhou Medical University, Wenzhou, Zhejiang, China. Electronic address: 2793829554@qq.com.
  • Xia Y; School of Mechanical Engineering, Sichuan University, Chengdu, China. Electronic address: yuanlin.xia@scu.edu.cn.
  • Qin W; Division of Nephrology, Department of Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China. Electronic address: qinweihx@scu.edu.cn.
Ecotoxicol Environ Saf ; 279: 116508, 2024 Jul 01.
Article em En | MEDLINE | ID: mdl-38815449
ABSTRACT

BACKGROUND:

Organochlorine pesticides, with their environmental persistence and bioaccumulation potential, have gained significant attention. This study explores the impact of organochlorine pesticides on mortality and chronic diseases, investigates their link to inflammatory states, and examines the role of anti-inflammatory diets in mitigating adverse reactions to these pesticides.

METHODS:

This study, with 2,847 participants, used gas chromatography and mass spectrometry to measure organochlorine pesticide exposure in NHANES data. Conventional statistical methodologies, encompassing survival curves, Cox proportional hazards regression, regression analysis, and restricted quadratic spline analysis, were employed to investigate the association between pesticides and mortality, chronic ailments, and inflammation. Furthermore, machine learning techniques, comprising RF, AdaBoost, Extra-Trees, LightGBM, and BPNN, were leveraged to evaluate the impact of pesticides on chronic disease and mortality prognostication.

RESULTS:

Organochlorine pesticides were significantly and positively correlated with increased mortality (p<0.05). Additionally, these pollutants were linked to the incidence of chronic diseases such as chronic kidney disease, diabetes, and hypertension (p< 0.05). Our study, utilizing various machine learning models, also showed a notable increase in the Area Under the Curve when incorporating organochlorine pesticide indicators into the model as opposed to excluding them. Furthermore, strong correlations were observed between serum c-reactive protein (CRP) and CRP to serum albumin ratio (CAR) concentrations with these substances, demonstrating their pro-inflammatory effects at specific concentrations. Interestingly, cutting down on dietary inflammation through changes in diet effectively reduced the risk of death at high organochlorine pesticide exposure levels, but the effect was less noticeable at low to moderate exposure levels.

CONCLUSIONS:

Exposure to organochlorine pesticides was linked to a higher risk of mortality, likely due to an increased prevalence of chronic diseases. In this context, inflammation played a crucial role, and adopting an anti-inflammatory diet significantly reduced the mortality risk associated with these pesticides.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Praguicidas / Exposição Ambiental / Hidrocarbonetos Clorados / Inflamação Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Ecotoxicol Environ Saf Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Praguicidas / Exposição Ambiental / Hidrocarbonetos Clorados / Inflamação Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Ecotoxicol Environ Saf Ano de publicação: 2024 Tipo de documento: Article