文章摘要
郭伟,徐洋,刘婷,贾淯媛,李璐,俞琼.吉林省成年居民心血管代谢性共病的患病情况及影响因素分析[J].中华流行病学杂志,2025,46(11):1952-1957
吉林省成年居民心血管代谢性共病的患病情况及影响因素分析
Analysis on prevalence of cardiometabolic multimorbidity and influencing factors in adults in Jilin Province
收稿日期:2025-03-25  出版日期:2025-11-13
DOI:10.3760/cma.j.cn112338-20250325-00189
中文关键词: 心血管代谢性共病|患病率|影响因素
英文关键词: Cardiometabolic multimorbidity|Prevalence|Influencing factors
基金项目:吉林省卫生健康科技能力提升项目(2023GW010);吉林省卫生健康科技能力提升计划(2024A171)
作者单位E-mail
郭伟 吉林省疾病预防控制中心慢性非传染性疾病预防控制所, 长春 130062 ydgw1558@163.com 
徐洋 吉林大学公共卫生学院流行病与卫生统计学教研室, 长春 130021  
刘婷 吉林省疾病预防控制中心慢性非传染性疾病预防控制所, 长春 130062  
贾淯媛 吉林省疾病预防控制中心慢性非传染性疾病预防控制所, 长春 130062  
李璐 吉林省疾病预防控制中心慢性非传染性疾病预防控制所, 长春 130062  
俞琼 吉林大学公共卫生学院流行病与卫生统计学教研室, 长春 130021  
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中文摘要:
      目的 了解吉林省成年居民心血管代谢性共病(CMM)的患病情况及其影响因素,为制定慢性病防控策略和措施提供数据支持与理论依据。方法 于2023年采用多阶段分层整群随机抽样方法,抽取吉林省8个监测点中≥18岁的常住居民作为研究对象。组间比较采用χ2检验,采用多因素logistic回归模型分析CMM的影响因素。结果 4 717名研究对象中,吉林省成年居民CMM的加权患病率为34.56%。多因素logistic回归分析结果显示,45~59岁(aOR=1.87,95%CI1.50~2.32)、≥60岁(aOR=3.38,95%CI2.71~4.20)、男性(aOR=1.31,95%CI1.13~1.52)、已婚/同居(aOR=1.74,95%CI1.05~2.87)、丧偶/离异/分居(aOR=1.94,95%CI1.12~3.36)、存在睡眠问题(aOR=1.67,95%CI1.45~1.93)、体力活动不足(aOR=1.26,95%CI1.11~1.44)、超重/肥胖(aOR=2.10,95%CI1.79~2.46)、中心性肥胖(aOR=1.85,95%CI1.61~2.14)、存在抑郁症状(aOR=1.52,95%CI1.23~1.87)以及文化程度低(小学及初中:aOR=0.81,95%CI:0.67~0.99;高中:aOR=0.68,95%CI:0.53~0.86;大专及以上:aOR=0.67,95%CI:0.51~0.87)是吉林省成年居民患CMM的危险因素。结论 吉林省正面临日益严峻的CMM疾病负担挑战,未来应重点关注中老年群体、男性、已婚/同居或丧偶/离异/分居者、存在睡眠问题或体力活动不足等不良健康行为者、超重/肥胖及中心性肥胖等代谢异常人群、存在抑郁症状者以及低文化程度人群,通过实施精准化、分级化的防控策略,有效降低CMM带来的健康风险和社会负担。
英文摘要:
      Objective To understand the prevalence of cardiometabolic multimorbidity (CMM) and influencing factors in adults in Jilin Province, and provide data support and theoretical basis for the development of chronic disease prevention and control strategies and measures. Methods In 2023, a multi-stage stratified cluster random sampling was conducted to select local residents aged ≥18 years from 8 surveillance areas in Jilin as the study participants. Intergroup comparisons were conducted by using χ2 test, and multivariate logistic regression models were employed to analyze the influencing factors of CMM. Results In 4 717 study participants, the weighted prevalence of CMM was 34.56%. Multivariate logistic regression analysis revealed that the risk factors of CMM included being aged 45-59 years (aOR=1.87, 95%CI: 1.50-2.32), being aged ≥60 years (aOR=3.38, 95%CI: 2.71-4.20), being man (aOR=1.31, 95%CI: 1.13-1.52), being married/cohabiting (aOR=1.74, 95%CI: 1.05-2.87), being widowed/divorced/separated (aOR=1.94, 95%CI: 1.12-3.36), having sleep problems (aOR=1.67, 95%CI: 1.45-1.93), physical inactivity (aOR=1.26, 95%CI: 1.11-1.44), being overweight/obese (aOR=2.10, 95%CI: 1.79-2.46), suffering from central obesity (aOR=1.85, 95%CI: 1.61-2.14), having depressive symptoms (aOR=1.52, 95%CI: 1.23-1.87), and having lower education levels (primary/junior high school: aOR=0.81, 95%CI: 0.67-0.99; senior high school: aOR=0.68, 95%CI: 0.53-0.86; college/university or above: aOR=0.67, 95%CI: 0.51-0.87). Conclusions The challenge of CMM is serious in Jilin. In the future, special attention should be paid to the following high-risk groups: middle-aged and elderly populations, men, those who are married/cohabiting or widowed/divorced/separated, individuals with unhealthy behaviors such as sleep problems or physical inactivity, populations with metabolic disorders, including overweight/obesity and central obesity, individuals with depressive symptoms, and those with low education levels. By implementing precise and stratified prevention and control strategies, it is expected to effectively reduce the health risks and social burden caused by CMM.
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