中国全科医学 ›› 2023, Vol. 26 ›› Issue (14): 1703-1708.DOI: 10.12114/j.issn.1007-9572.2022.0658

• 论著 • 上一篇    下一篇

基于十年随访的心血管代谢性危险因素聚集与社区≥55岁人群全因死亡风险关系的队列研究

马万瑞1, 马乾凤2, 吴竞捷3, 王立群4, 王志忠1,5,*()   

  1. 1.523710 广东省东莞市,广东医科大学附属东莞第一医院老年医学科
    2.750004 宁夏回族自治区银川市,宁夏医科大学总医院超声科
    3.523808 广东省东莞市松山湖社区卫生服务中心预防保健科
    4.750004 宁夏回族自治区银川市,宁夏医科大学公共卫生与管理学院流行病与卫生统计学系
    5.523808 广东省东莞市,广东医科大学公共卫生学院流行病与卫生统计学系
  • 收稿日期:2022-09-11 修回日期:2022-12-25 出版日期:2023-05-15 发布日期:2023-02-02
  • 通讯作者: 王志忠

  • 作者贡献:马万瑞、王志忠进行文章的构思与设计、数据分析、文章的撰写;马乾凤、王立群负责数据的整理与核查;吴竞捷负责文献资料的收集与整理;王志忠负责文章的质量控制及审校,对文章整体负责。
  • 基金资助:
    国家自然科学基金资助项目(81860599)

A Ten-year Cohort Study of the Association between Cardiometabolic Risk Factor Cluster and All-cause Mortality Risk among Community-dwelling Aged 55 and Over Adults

MA Wanrui1, MA Qianfeng2, WU Jingjie3, WANG Liqun4, WANG Zhizhong1,5,*()   

  1. 1. Department of Geriatrics, the First Dongguan Affiliated Hospital of Guangdong Medical University, Dongguan 523710, China
    2. Department of Ultrasound, General Hospital of Ningxia Medical University, Yinchuan 750004, China
    3. Preventive and Healthcare Department, Songshanhu Community Health Center, Dongguan 523808, China
    4. Department of Epidemiology and Health Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750004, China
    5. Department of Epidemiology and Health Statistics, School of Public Health, Guangdong Medical University, Dongguan 523808, China
  • Received:2022-09-11 Revised:2022-12-25 Published:2023-05-15 Online:2023-02-02
  • Contact: WANG Zhizhong

摘要: 背景 心血管代谢性危险因素聚集(CRFC)是老年人常见的健康问题,目前相关研究主要集中在流行病学分布特征的描述,有关CRFC与人群全因死亡风险的研究鲜有报道。目的 探讨CRFC与社区≥55岁人群全因死亡风险的关系,为开展≥55岁人群社区保健提供参考。方法 于2011年9—11月采用典型抽样法选取宁夏回族自治区吴忠市和银川市5个社区的1 046名≥55岁人群作为研究对象,对其开展一般情况问卷调查、体格检查、超声检查、实验室检查和CRFC评价〔纳入中心性肥胖、高胆固醇血症、高三酰甘油血症、高低密度脂蛋白血症、低高密度脂蛋白血症、高血压、糖尿病、高尿酸血症、非酒精性脂肪性肝病(NAFLD)共计9项心血管代谢性危险因素后,控制一般情况变量,通过构建多因素Cox比例风险回归模型,估计各个心血管代谢性危险因素的回归系数β,以回归系数β为权重将所有心血管代谢性危险因素的评分相加得出心血管代谢危险因素危险总评分〕,将心血管代谢危险因素危险总评分按照四分位数分为三组:<P50组,P50~P75组,>P75组;分别于2017年,2019年和2021年通过面访和死因监测系统搜索的方式完成随访。采用Kaplan-Meier法绘制<P50组,P50~P75组,>P75组社区老年人全因死亡的生存曲线,生存曲线比较采用Log-rank检验;采用多因素Cox比例风险回归分析一般情况、各心血管代谢性危险因素、心血管代谢危险因素危险总评分、心血管代谢危险因素危险总评分分组、年龄组分层与社区≥55岁人群全因死亡风险的关系。结果 研究对象年龄55~88岁,平均年龄(66.4±6.6)岁。共观察到106例死亡案例,10年累计死亡率为10.13%。随着危险评分的增加,个体预期中位生存时间显著缩短,>P75组累积生存率低于P50~P75组和<P50组;多因素Cox比例风险回归分析结果显示,年龄、性别、独居、文化程度可能是社区老年人全因死亡风险的影响因素(P<0.05);控制一般情况后,多因素Cox比例风险回归分析结果显示,心血管代谢危险因素危险总评分是社区≥55岁人群全因死亡风险的影响因素〔HR=3.04,95%CI(1.55,5.97),P=0.001〕,且心血管代谢危险因素总评分越高死亡风险亦越高,>P75组全因死亡风险高于<P50组〔HR=2.02,95%CI(1.16,3.50),P=0.013〕;以年龄组分层多因素Cox比例风险回归分析结果显示,≥65岁年龄组心血管代谢危险因素总评分与社区≥55岁人群全因死亡风险显著关联〔HR=2.79,95%CI(1.36,5.74),P=0.005〕;>P75组全因死亡风险高于<P50组〔HR=1.83,95%CI(1.02,3.28),P=0.042〕。结论 CRFC与社区≥55岁人群全因死亡风险显著关联,其聚集程度越高全因死亡风险越高,提示早期评价CRFC并给予干预可能对提高社区≥55岁人群保健效果、降低死亡风险具有一定意义。

关键词: 代谢综合征, 代谢性心血管综合征, 心血管代谢风险因素, 死亡原因, 心血管代谢性危险因素聚集, 全因死亡风险, 老年人, 队列研究, 随访研究

Abstract:

Background

Cardiometabolic risk factor cluster (CRFC) is a common health issue among aged 55 and over adults. Available studies mainly focus on the distribution of its epidemiological characteristics, but rarely assess the association between CRFC and all-cause mortality risk.

Objective

To explore the association between CRFC and all-cause mortality risk among community-dwelling aged 55 and over adults, to provide evidence for developing healthcare interventional programs for this group.

Methods

By use of typical sampling, this study selected 1 046 community-dwelling aged 55 and over adults from five urban communities in Wuzhong and Yinchuan cities of Ningxia Hui Autonomous Region during September to November 2011. And sociodemographic questionnaire survey, health check-up, ultrasonic examination, laboratory test and CRFC assessment 〔nine cardiometabolic risk factors, including central obesity, hypercholesterolemia, hypertriglyceridemia, elevated LDL-cholesterol, decreased HDL-cholesterol, hypertension, diabetes, hyperuricemia, and nonalcoholic fatty liver disease (NAFLD) 〕, were included in the multivariate Cox regression model to calculate the regression coefficient β of them after adjusting for confounders, then the coefficient of each factor was used as the weight to calculate the total risk score by adding them together were finished at baseline. The participants were followed up in 2017, 2019, and 2021 by face-to-face interview coupled with searching the national death surveillance system. Log-rank test was used to compare the survival curves for all-cause mortality plotted using the Kaplan-Meier method for tertile groups of the total cardiometabolic risk score (<P50, P50-P75, and >P75) . The Cox regression model was employed to assess the association of all-cause mortality risk with sociodemographics, cardiometabolic risk factors, the total cardiometabolic risk score, the level of the total cardiometabolic risk score, and age.

Results

The participants had an average age of (66.4±6.6) years (range: 55-88) at baseline. One hundred and six death cases were identified with a ten-year accumulated mortality rate of 10.13%. The individuals in >P75 group had much lower accumulated mortality rate than the other two groups, indicating that the median survival time decreased with the increase in the total cardiometabolic risk score. Multivariate Cox regression analysis showed that age, sex, living alone and education level may be associated with all-cause mortality risk (P<0.05) . After adjusting for sociodemographic variables, the multivariate Cox regression model revealed that the cardiometabolic risk factor cluster was associated with increased risk of all-cause mortality〔HR=3.04, 95%CI (1.55, 5.97) , P=0.001〕, and a dose-response effect was found that higher score was associated with an increased risk of death〔HR=2.02, 95%CI (1.16, 3.50) , P=0.013〕for > P75 when compared with risk score lower than P50) . When stratified by age group, the association only persisted among those aged 65 and over〔HR=2.79, 95%CI (1.36, 5.74) , P=0.005〕; >P75 group had higher risk of death than P50 group〔HR=1.83, 95%CI (1.02, 3.28) , P=0.042〕.

Conclusion

The CRFC was positively associated with all-cause mortality risk among community-dwelling aged 55 and over adults, and higher level of clustering was associated with higher all-cause mortality risk. The findings indicate that early assessment and intervention of CRFC may play a role in improving the healthcare and reducing the risk of death in this population .

Key words: Metabolic syndrome, Metabolic cardiovascular syndrome, Cardiometabolic risk factors, Cause of death, Cardiometabolic risk factor cluster, All-cause risk of death, Aged, Cohort studies, Follow-up studies