2009-2018年中国九省不同职业类型人群心血管代谢危险因素趋势OA
Cardiometabolic risk factor trends across different occupational groups in nine provinces of China,2009-2018
[背景]随着我国社会经济的发展,职业人群的生活方式发生很大的转变,心血管代谢性危险因素也随之改变,但目前我国职业人群的心血管代谢性危险因素变化趋势研究还较少. [目的]分析 2009-2018年中国九省职业人群心血管代谢性危险因素的流行趋势,并探讨不同职业类型与危险因素及其聚集的关联,为开展职业人群针对性防控提供依据. [方法]基于中国健康与营养调查(CHNS)2009、2015、2018年数据,选取 13 274名 18~59岁具有完整血液检测与体格测量数据的职业人群为研究对象.使用Joinpoint回归模型计算各危险因素检出率的平均年度变化百分比(AAPC),分析其时间趋势.采用无序logistic及logis-tic回归模型,分析 2018年不同职业类型(职员类、农民类、工人类、服务业人员、其他类)对九项心血管代谢性危险因素及其聚集(≥2项)的影响. [结果]共纳入 8 451名研究对象.2009-2018年间,职业人群超重、肥胖、中心性肥胖、甘油三酯(TG)边缘升高、总胆固醇(TC)边缘升高与升高、低密度脂蛋白胆固醇(LDL-C)边缘升高、血压升高和高血压、糖尿病的检出率均呈上升趋势(AAPC>0,P<0.05),其中肥胖(AAPC=6.07%,95%CI:3.42%~8.88%)、高血压(AAPC=4.10%,95%CI:0.62%~7.77%)和中心性肥胖(AAPC=3.27%,95%CI:1.24%~5.36%)增长较快.危险因素聚集率从2009年的62.3%上升至2018年的 73.2%(AAPC=1.87%,95%CI:1.02%~2.73%).2018年的横断面分析结果显示,在调整混杂因素后,与职员类相比,工人类发生超重(OR=0.67,95%CI:0.48~0.95)、中心性肥胖(OR=0.65,95%CI:0.45~0.92)和TG边缘升高(OR=0.54,95%CI:0.35~0.82)的风险更低;而农民类患高血压的风险更高(OR=1.76,95%CI:1.14~2.72). [结论]2009-2015年间,中国职业人群多数心血管代谢性危险因素负担显著加重,至 2018年增长趋缓.不同职业类型间的风险存在差异,工人群体某些风险因素流行水平较低.建议针对增长迅速的危险因素及高风险职业群体采取精准的干预措施.
[Background]With China's socioeconomic development,significant lifestyle changes have oc-curred among occupational groups,leading to alterations in cardiovascular metabolic risk fac-tors.However,few studies have examined the secular trends of these risk factors in China's working population. [Objective]To analyze the trends in cardiovascular metabolic risk factors among the occupational population in nine provinces of China from 2009 to 2018,and to explore the associations between different occupational types and these risk factors,along with their clustering patterns,thereby providing evidence for targeted interventions. [Methods]This study utilized data from the China Health and Nutrition Survey(CHNS)in 2009,2015,and 2018.The dataset covered 13 274 employed individuals aged 18-59 years.Only participants with complete blood test results and physical measurement data were included in the final analysis.The average annual percentage change(AAPC)in the positive rates of risk factors was calculated using Joinpoint re-gression to analyze temporal trends.Multinomial logistic regression and binary logistic regression models were employed to examine the cross-sectional associations between occupational types(categorized as white-collar workers,agricultural workers,blue-collar workers,service workers,and others)and nine cardiovascular metabolic risk factors and their clustering(defined as having≥2 risk factors)in 2018. [Results]A total of 8 451 participants were included.From 2009 to 2018,significant increasing trends(AAPC>0,P<0.05)were observed for overweight,obesity,central obesity,borderline elevated triglycerides(TG),borderline elevated to elevated total cholesterol(TC),bor-derline elevated low-density lipoprotein cholesterol(LDL-C),elevated blood pressure and hypertension,diabetes.The most rapid increases were found for obesity(AAPC=6.07%,95%CI:3.42%,8.88%),hypertension(AAPC=4.10%,95%CI:0.62%,7.77%),and central obesity(AAPC=3.27%,95%CI:1.24%,5.36%).The clustering rate of risk factors increased from 62.3%in 2009 to 73.2%in 2018(AAPC=1.87%,95%CI:1.02%,2.73%).The cross-sectional analysis in 2018,after adjusting for confounders,showed that compared with white-collar workers,blue-collar workers had a significantly lower risk of overweight(OR=0.67,95%CI:0.48,0.95),central obesity(OR=0.65,95%CI:0.45,0.92),and borderline high TG(OR=0.54,95%CI:0.35,0.82).In contrast,agricultural workers had a higher risk of hypertension(OR=1.76,95%CI:1.14,2.72). [Conclusion]Between 2009 and 2015,the burden of most cardiometabolic risk factors increases significantly among the Chinese occupa-tional population,with the rate of increase slowing by 2018.Risks vary across occupational types,among which blue-collar workers report lower target outcomes.Targeted interventions focusing on the rapidly increasing risk factors and high-risk occupational groups are rec-ommended.
吴宇;张兵;陈黎黎;丁钢强;姜红如;郝丽鑫;王柳森;李惟怡;王邵顺子;王子健;王志宏;王惠君
中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050中国疾病预防控制中心营养与健康所,北京 100050||国家卫生健康委公共营养与健康重点实验室,北京 100050
医药卫生
职业人群心血管代谢性危险因素变化趋势Joinpoint回归分析危险因素聚集
occupational groupcardiovascular metabolic risk factorsecular trendJoinpoint regression analysisclustering of risk factors
《环境与职业医学》 2026 (2)
153-159,7
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