Authors
Xiaoru Dai, Peng Sun, Mingxian Fu, Lei Han, Lizhuang Xie, Yuan Zhao, Long Miao, Baoli Zhu, Boshen Wang
Published in
Environmental research. Pages 125983. Oct 19, 2026. Epub Oct 19, 2026.
Abstract
Evidence linking occupational noise to hypertension remains inconsistent, and potential metabolic pathways are insufficiently characterised.
We conducted a cross-sectional analysis of 70,759 workers in Jiangsu Province and a retrospective five-year cohort analysis of 2,188 workers. We combined multivariable regression, machine-learning prediction, mediation analysis, and longitudinal modelling to examine associations and potential pathways.
Hypertension prevalence was 28.19%. Compared with unexposed workers, noise exposure of 70-< 85 dB(A) and 85-< 90 dB(A) was associated with higher hypertension odds (OR = 1.16 and 1.21, p < 0.001), whereas the association at ≥ 90 dB(A) was not significant after adjustment. XGBoost achieved the best predictive performance (AUC=0.84), with metabolic indicators including triglycerides, glucose, and γ-glutamyl transferase ranking among the important predictors, while noise exposure also contributed to prediction. Mediation analyses identified potential indirect pathways involving γ-glutamyl transferase, glucose, and low-density lipoprotein cholesterol in the association between occupational noise exposure and systolic blood pressure. Longitudinal analyses showed delayed divergence in metabolic markers and larger systolic blood pressure differences during the later follow-up period.
Occupational noise exposure was associated with elevated blood pressure even at levels below the Chinese occupational noise exposure limit of 85 dB(A) for an 8-hour working day, which is primarily intended to prevent noise-induced hearing loss. The findings are consistent with a potential role of oxidative stress-related glucose and lipid metabolic dysregulation in this association. Future occupational health strategies should incorporate longitudinal metabolic surveillance to mitigate noise-induced risks in exposed populations.
PMID:
42896799
Bibliographic data and abstract were imported from PubMed on 20 Oct 2026.
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