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

Association between lifestyle and cardiovascular-metabolic risk factor aggregation in a young and middle-aged male occupational population

  • 摘要:
    背景 不良生活方式可能会导致心血管代谢危险因素聚集(CMRF≥2)风险增加,鲜有研究关注职业人群中上述二者间的相关性。
    目的 研究旨在调查男性职业人员CMRF≥2现状和健康生活方式依从情况,并探究生活方式对心血管代谢风险的影响,为职业人群制定健康行为促进策略以及降低心血管代谢风险提供参考依据。
    方法 研究对象选取自2023年5—12月在山西省某职业病防治院完成职业健康检查的男性在职职工,根据纳入排除标准最终纳入15125名18~60岁的研究对象。对所有受试者进行一系列评估,包括问卷调查(基本情况、生活习惯和职业因素)、体格检查、实验室检测以及CMRF评估。CMRF≥2的评估关注六项心血管代谢风险因素(中心性肥胖、高血压、2型糖尿病、高甘油三酯血症、低高密度脂蛋白胆固醇血症和高尿酸血症)。基于六个行为因素(吸烟、饮酒、身体活动、饮食、睡眠、静坐)计算健康生活方式得分,具有其中1项健康行为记1分,根据总得分划分为三个组别:0~1分(不良组)、2~3分(中等组)和4~6分(良好组)。采用logistic回归模型分析生活方式与CMRF≥2的关联。
    结果 15125名男性研究对象的年龄中位数为40岁,CMRF≥2的阳性率为53.5%。适量饮酒的健康生活方式依从性最为理想(79.4%),其次是当前不吸烟(41.7%),而适量静坐(23.6%)和健康饮食(21.1%)的依从性相对较低,仅17.4%能够同时坚持4种及以上健康生活行为。经调整混杂因素后发现,相较于不良组,高生活方式得分是CMRF≥2的保护因素中等组比值比(OR)=0.70,95%置信区间(95%CI):0.63~0.77;良好组OR=0.66,95%CI:0.58~0.75。在不同工种(采煤工、辅助工、地面工、其他)、职业紧张状态(有或无)、轮班模式(白班、夜班或轮班)、粉尘暴露(有或无)以及噪声暴露(有或无)的分层分析中,生活方式得分较高者CMRF≥2的风险均较低。轮班模式与生活方式对CMRF≥2的发生存在交互作用(P交互<0.05)。
    结论 该职业群体CMRF≥2的阳性率较高,且不良生活方式普遍存在,部分健康行为依从性低。健康生活方式得分高者与较低的CMRF≥2风险有关,通过干预生活方式可以降低心血管代谢风险。

     

    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 the 15125 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.

     

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