Chen Jiaqi, Zhao Ziqi, Zheng Yizhan, Hu Jiaqi, Zhu Hongmin, Wang Huan, Luo Zhenghao, Xuan Xiaoqing, Liu Mingyue, Wang Nan, Chen Xinyang, Li Zheng, Zhang Shangmingzhu, Zhang Haoruo, Li Xiaoming, Wu Jianhui, Xue Ling
Department of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, 063210, China; Hebei Key Laboratory of Coal Health and Safety, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, 063210, China.
Public Health. 2025 Feb;239:15-21. doi: 10.1016/j.puhe.2024.12.006. Epub 2024 Dec 24.
This study aimed to use a stable and predictive method: Lasso regression model to analyze hypertension's influencing factors and explore the interactions between occupational exposures.
This has been a nested case-control study.
The case group consisted of 959 patients with high blood pressure found during the study. 959 hypertensive patients, matched 1:1 from the cohort based on the age ±2 years and same gender distribution, served as the control group. Logistic regression has been performed to analyze the relationship between occupational exposures and hypertension after the variables were screened by the Lasso regression model and to explore the interactions between the various occupational exposures.
The incidence rate of hypertension among steelworkers was 33.95 %. Noise, dust, high temperature, carbon monoxide (CO), and shift work have been found to be significantly associated with the risk of hypertension, which is 1.329, 1.370, 1.900, 1.309, and 1.427 times higher than that of the control group, respectively. In addition, a multiplicative interaction between dust and noise has been found (P = 0.038).
The study suggested that exposure to dust, high temperature, CO, noise, and shift work increases the risk of hypertension among steelworkers and that the risk of hypertension is more pronounced among workers exposed to both dust and noise.
本研究旨在运用一种稳定且具有预测性的方法——套索回归模型，分析高血压的影响因素，并探究职业暴露之间的相互作用。
这是一项巢式病例对照研究。
病例组由研究期间发现的959例高血压患者组成。959例高血压患者根据年龄±2岁且性别分布相同，从队列中1:1匹配作为对照组。在通过套索回归模型筛选变量后，进行逻辑回归分析职业暴露与高血压之间的关系，并探究各种职业暴露之间的相互作用。
钢铁工人高血压发病率为33.95%。发现噪声、粉尘、高温、一氧化碳（CO）和轮班工作与高血压风险显著相关，分别比对照组高1.329倍、1.370倍、1.900倍、1.309倍和1.427倍。此外，还发现粉尘和噪声之间存在相乘交互作用（P = 0.038）。
该研究表明，接触粉尘、高温、CO、噪声和轮班工作会增加钢铁工人患高血压的风险，且同时接触粉尘和噪声的工人患高血压的风险更为明显。
