Wang Y F, Wang Z W, Zheng C Y, Wang X, Tian Y X, Cao X, Feng R H
Institute of Medical Information/Medical Library, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100020, China.
Department of Prevention and Community Health, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China.
Zhonghua Xin Xue Guan Bing Za Zhi. 2025 Jul 24;53(7):792-798. doi: 10.3760/cma.j.cn112148-20240509-00247.
To investigate the prevalence, comorbidity patterns, and associated factors of cardiometabolic multimorbidity (CMM) in China. From 2012 to 2015, a total of 34 994 residents aged ≥35 years were enrolled using a stratified multistage random sampling method across 31 provinces, autonomous regions, and municipalities in China. Data were collected through questionnaires, covering demographic characteristics, behavioral and lifestyle factors, and self-reported history of cardiometabolic diseases. CMM was defined as the coexistence of two or more cardiometabolic diseases in the same individual. Association rule analysis using the Apriori algorithm from the arules package was employed to identify strong CMM patterns. Multivariable logistic regression was employed to explore factors associated with CMM. The mean age of the participants was 55.6 years. Among them, 15 926 were male (45.51%). The prevalence of cardiometabolic multimorbidity (CMM) was 11.25% (3 937/34 994). A total of 35 distinct CMM combinations (each with a frequency ≥10) were identified. The most prevalent dyad, triad, and tetrad comorbidity patterns were hypertension+hyperlipidemia (1 036 cases), hypertension+hyperlipidemia+diabetes (352 cases), and hypertension+stroke+hyperlipidemia+diabetes (54 cases), respectively. Nine strong CMM patterns were identified using the Apriori association rule algorithm. Multivariable logistic regression analysis showed that older age (≥70 years: =17.39,95% 13.92-21.71,<0.01), junior high school education (=1.31, 95% 1.17-1.48, <0.01), senior high school or above education (=1.45, 95% 1.27-1.65, <0.01), retirement (=3.09, 95% 2.76-3.46, <0.01), unemployment or being laid-off (=1.16, 95% 1.06-1.28, <0.01), a family history of cardiometabolic disease (=4.37, 95% 4.04-4.72, <0.01), regular smoking (=1.38, 95% 1.24-1.53, <0.05), and occasional smoking (=1.21, 95% 1.00-1.49, <0.01) were significantly associated with an increased risk of CMM. The prevalence of cardiometabolic multimorbidity in China is relatively high, with the most common comorbidity patterns involving combinations of hypertension and hyperlipidemia, often accompanied by diabetes and stroke. Older age, retirement status, smoking, and a family history of cardiovascular disease are associated with an increased risk of both single and multiple cardiometabolic conditions. Greater attention should be paid to individuals with a single cardiometabolic disorder due to their elevated risk of developing multimorbidity.
为调查中国心脏代谢性多种疾病共病（CMM）的患病率、共病模式及相关因素。2012年至2015年，采用分层多阶段随机抽样方法，在中国31个省、自治区和直辖市共纳入了34994名年龄≥35岁的居民。通过问卷调查收集数据，内容涵盖人口统计学特征、行为和生活方式因素以及自我报告的心脏代谢性疾病史。CMM被定义为同一个体中存在两种或更多种心脏代谢性疾病。使用来自arules包的Apriori算法进行关联规则分析，以识别强烈的CMM模式。采用多变量逻辑回归来探索与CMM相关的因素。参与者的平均年龄为55.6岁。其中，男性有15926名（45.51%）。心脏代谢性多种疾病共病（CMM）的患病率为11.25%（3937/34994）。共识别出35种不同的CMM组合（每种组合的频率≥10）。最常见的二元、三元和四元共病模式分别是高血压+高脂血症（1036例）、高血压+高脂血症+糖尿病（352例）和高血压+中风+高脂血症+糖尿病（54例）。使用Apriori关联规则算法识别出9种强烈的CMM模式。多变量逻辑回归分析显示，年龄较大（≥70岁：比值比=17.39，95%置信区间13.92 - 21.71，P<0.01）、初中文化程度（比值比=1.31，95%置信区间1.17 - 1.48，P<0.01）、高中及以上文化程度（比值比=1.45，95%置信区间1.27 - 1.65，P<0.01）、退休（比值比=3.09，95%置信区间2.76 - 3.46，P<0.01）、失业或下岗（比值比=1.16，95%置信区间1.06 - 1.28，P<0.01）、心脏代谢性疾病家族史（比值比=4.37，95%置信区间4.04 - 4.72，P<0.01）、经常吸烟（比值比=1.38，95%置信区间1.24 - 1.53，P<0.05）和偶尔吸烟（比值比=1.21，95%置信区间1.00 - 1.49，P<0.01）与CMM风险增加显著相关。中国心脏代谢性多种疾病共病的患病率相对较高，最常见的共病模式涉及高血压和高脂血症的组合，常伴有糖尿病和中风。年龄较大、退休状态、吸烟以及心血管疾病家族史与单一和多种心脏代谢性疾病的风险增加相关。由于单一心脏代谢性疾病患者发生多种疾病共病的风险升高，因此应给予更多关注。
