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已发表论文
高分辨率LC-MS/MS检测的环境暴露对肥胖的影响：通过统计建模研究累积效应
Authors Liu Y, Ma F, Zhong Z, Liu X , Liu M, Lou K
Received 27 August 2025
Accepted for publication 8 January 2026
Published 23 January 2026 Volume 2026:19 558970
DOI https://doi.org/10.2147/DMSO.S558970
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Prof. Dr. Liang Wang
Ying Liu,1,* Fenfen Ma,1,* Zhifang Zhong,1,* Xuekui Liu,2 Min Liu,1 Kexin Lou1
1Department of Ultrasonography, Xuzhou Central Hospital, Southeast University, Xuzhou, Jiangsu, People’s Republic of China; 2Department of Endocrinology, Xuzhou Central Hospital, Southeast University, Xuzhou, Jiangsu, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Kexin Lou, Email kxlou@jsnu.edu.cn Min Liu, Email 24187358@qq.com
Background: Obesity is a major and escalating public health challenge worldwide. Growing evidence implicates environmental chemicals, especially organophosphate flame retardants (OFRs) and per- and polyfluoroalkyl substances (PFAS), as potential obesogens due to their ability to disrupt endocrine function and lipid metabolism. However, data on the association between these chemical mixtures and overweight in Chinese populations—particularly in industrialized regions—are scarce, representing a critical knowledge gap.
Methods: We conducted a matched case–control study of 214 adults from northern China, including 107 overweight individuals (body mass index [BMI] ≥ 24 kg/m2) and 107 normal-weight controls (BMI < 24 kg/m2), pair-matched by age and sex. Using high-resolution liquid chromatography–tandem mass spectrometry (LC-MS/MS), we quantified serum concentrations of 202 environmental exposures. Multivariable logistic regression, Weighted Quantile Sum (WQS) regression, and Bayesian Kernel Machine Regression (BKMR) models were employed to assess individual and cumulative associations with overweight, adjusting for key metabolic covariates (eg, blood pressure, lipids, and fasting glucose).
Results: Thirteen chemicals showed significant differences between groups (|log2 fold change| ≥ 1). Ten were elevated in the overweight group, most notably tris(2-butoxyethyl) phosphate (TBOEP; adjusted odds ratio [OR] = 2.40, 95% confidence interval [CI]: 1.79– 3.33), 1,3,5-triazine-2,4,6-trione tris(2,3-dibromopropyl) ester (TBC), perfluorooctanoic acid (PFOA), and perfluorobutane sulfonic acid (PFBS). The WQS index reflecting the combined effect of these 13 chemicals was strongly associated with higher odds of overweight (OR = 2.33, 95% CI: 1.77– 3.07). BKMR analysis further revealed a non-linear cumulative exposure–response relationship, with maximal risk observed at moderate exposure levels.
Conclusion: This study provides robust epidemiological evidence that circulating levels of specific environmental pollutants—particularly TBOEP, PFOA, PFBS, and TBC—are significantly associated with increased likelihood of overweight in a northern Chinese adult population. Our findings highlight the potential contribution of complex chemical mixtures to obesity etiology in rapidly industrializing settings and underscore the need for targeted environmental health interventions.
Keywords: obesity, environmental exposures, overweight
1Department of Ultrasonography, Xuzhou Central Hospital, Southeast University, Xuzhou, Jiangsu, People’s Republic of China; 2Department of Endocrinology, Xuzhou Central Hospital, Southeast University, Xuzhou, Jiangsu, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Kexin Lou, Email kxlou@jsnu.edu.cn Min Liu, Email 24187358@qq.com
Background: Obesity is a major and escalating public health challenge worldwide. Growing evidence implicates environmental chemicals, especially organophosphate flame retardants (OFRs) and per- and polyfluoroalkyl substances (PFAS), as potential obesogens due to their ability to disrupt endocrine function and lipid metabolism. However, data on the association between these chemical mixtures and overweight in Chinese populations—particularly in industrialized regions—are scarce, representing a critical knowledge gap.
Methods: We conducted a matched case–control study of 214 adults from northern China, including 107 overweight individuals (body mass index [BMI] ≥ 24 kg/m2) and 107 normal-weight controls (BMI < 24 kg/m2), pair-matched by age and sex. Using high-resolution liquid chromatography–tandem mass spectrometry (LC-MS/MS), we quantified serum concentrations of 202 environmental exposures. Multivariable logistic regression, Weighted Quantile Sum (WQS) regression, and Bayesian Kernel Machine Regression (BKMR) models were employed to assess individual and cumulative associations with overweight, adjusting for key metabolic covariates (eg, blood pressure, lipids, and fasting glucose).
Results: Thirteen chemicals showed significant differences between groups (|log2 fold change| ≥ 1). Ten were elevated in the overweight group, most notably tris(2-butoxyethyl) phosphate (TBOEP; adjusted odds ratio [OR] = 2.40, 95% confidence interval [CI]: 1.79– 3.33), 1,3,5-triazine-2,4,6-trione tris(2,3-dibromopropyl) ester (TBC), perfluorooctanoic acid (PFOA), and perfluorobutane sulfonic acid (PFBS). The WQS index reflecting the combined effect of these 13 chemicals was strongly associated with higher odds of overweight (OR = 2.33, 95% CI: 1.77– 3.07). BKMR analysis further revealed a non-linear cumulative exposure–response relationship, with maximal risk observed at moderate exposure levels.
Conclusion: This study provides robust epidemiological evidence that circulating levels of specific environmental pollutants—particularly TBOEP, PFOA, PFBS, and TBC—are significantly associated with increased likelihood of overweight in a northern Chinese adult population. Our findings highlight the potential contribution of complex chemical mixtures to obesity etiology in rapidly industrializing settings and underscore the need for targeted environmental health interventions.
Keywords: obesity, environmental exposures, overweight