Association between lifestyle and cardiovascular-metabolic risk factor aggregation in a young and middle-aged male occupational population
- VernacularTitle:中青年男性职业人群生活方式与心血管代谢危险因素聚集的关联性研究
- Author:
Baoyi LIANG
1
;
Lyurong LI
1
;
Yingjun CHEN
1
;
Lingxiang XIE
1
;
Gaisheng LIU
2
;
Liuquan JIANG
2
;
Lu YU
3
,
4
;
Qingsong CHEN
3
,
5
Author Information
- Publication Type:Selectedarticle
- Keywords: working population; lifestyle; healthy lifestyle adherence; cardiometabolic risk factor aggregation; cross-sectional study
- From: Journal of Environmental and Occupational Medicine 2025;42(4):385-391
- CountryChina
- Language:Chinese
-
Abstract:
Background Unhealthy lifestyle behaviors may be associated with an increased risk of cardiometabolic risk factor aggregation (CMRF≥ 2), and few studies have focused on the correlation between the two in occupational populations. Objective To investigate the current status of CMRF≥2 and the compliance of healthy lifestyle in male occupational personnel, explore the effect of lifestyle on cardiometabolic risk, and provide reference for formulating healthy behavior promotion strategies and reducing cardiometabolic risk in occupational populations. Methods The study subjects were selected from male workers who completed occupational health examinations at an occupational disease prevention and control hospital in Shanxi Province from May to December 2023, and
15125 study subjects aged 18−60 years were finally included according to pre-determined inclusion and exclusion criteria. All subjects received a series of assessments including questionnaires (basic information, lifestyle habits, and occupational factors), physical examination, laboratory tests, and six cardiometabolic risk factors (central obesity, hypertension, type 2 diabetes, hypertriglyceridemia, low-density lipoprotein cholesterolemia, and hyperuricemia). A healthy lifestyle score was calculated based on six behavioral factors (smoking, drinking, physical activity, diet, sleep, sedentary behavior) and 1 point for one positive healthy behavior. The enrolled workers were then divided into three groups according to their total scores: 0−1 points (poor group), 2−3 points (moderate group), and 4−6 points (good group). Logistic regression models were used to analyze the statistical associations between lifestyle and CMRF≥2. Results The median age of the15125 male study participants was 40 years, and the positive rate of CMRF≥2 was 53.5%. Adherence to moderate alcohol consumption was the most compliant healthy behavior (79.4%), followed by current non-smoking (41.7%), while adherence to adequate sedentary behavior (23.6%) and healthy eating (21.1%) were relatively low, and only 17.4% were able to adhere to four or more healthy lifestyle behaviors. After adjusting for confounders, when compared with the poor group high lifestyle score was found to be a protective factor for CMRF≥2 (moderate group: OR=0.70, 95%CI: 0.63, 0.77; good group: OR=0.66, 95%CI: 0.58, 0.75). In stratified analyses across different job types (coal miners, auxiliary workers, ground workers, and others), occupational stress (with or without), shift patterns (day shift, night shift, or rotating shift), dust exposure (with or without), and noise exposure (with or without), individuals with higher lifestyle scores exhibited a consistently lower risk of CMRF≥2. There was an interaction between shift pattern and lifestyle on CMRF≥2 (Pinteraction<0.05). Conclusion This occupational group has a high positive rate of CMRF≥2 and a high prevalence of poor lifestyles with low adherence to some healthy behaviors. High healthy lifestyle scores are associated with a lower risk of aggregation of cardiometabolic risk factors, which may be reduced through lifestyle interventions.
