1.南方医科大学卫生管理学院,广东 广州510515
2.广州公共卫生服务体系建设研究基地,广东 广州510515
3.广东省医学会,广东 广州510180
4.广东省医学学术交流中心,广东 广州510180
5.新南威尔士大学乔治全球健康研究院,澳大利亚 悉尼2050
6.墨尔本大学人口与全球健康学院,澳大利亚 墨尔本3010
张露文,博士,讲师,研究方向:老年健康管理、卫生服务,E-mail:067094@smu.edu.cn
纸质出版日期:2023-01-20,
收稿日期:2022-09-20,
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张露文,陆翘楚,赵洋.中国中老年人慢病共病组合及其健康结局差异[J].中山大学学报(医学科学版),2023,44(01):159-168.
ZHANG Lu-wen,LU Qiao-chu,ZHAO Yang.Association of Multimorbidity with Health Outcomes in the Chinese Middle-aged and Elderly Population[J].Journal of Sun Yat-sen University(Medical Sciences),2023,44(01):159-168.
张露文,陆翘楚,赵洋.中国中老年人慢病共病组合及其健康结局差异[J].中山大学学报(医学科学版),2023,44(01):159-168. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).20221215.001.
ZHANG Lu-wen,LU Qiao-chu,ZHAO Yang.Association of Multimorbidity with Health Outcomes in the Chinese Middle-aged and Elderly Population[J].Journal of Sun Yat-sen University(Medical Sciences),2023,44(01):159-168. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).20221215.001.
目的
2
对中国50岁以上中老年人的慢性病共病组合进行分析,研究主要共病组合的患病率、地区分布及其与健康相关结局的关系。
方法
2
采用中国健康与养老追踪调查(CHARLS)2018年第四次全国追访数据,纳入28个省份50岁及以上受访者13 774名。统计14项患者报告医生诊断的慢性病及共病组合,报告患病率、疾病构成比与地区分布情况。使用卡方检验和logistic回归分析高发病组间的健康损失与危险因素差异。
结果
2
中国中老年人群共病患病率为57.3%。患病率高的单病种包括关节炎/风湿病(6.47%)、高血压(5.41%)、胃与消化系统疾病(4.17%);二元共病组合为关节炎+消化病(3.06%),关节炎+高血压(2.61%),高血压+高血脂(1.39%);三元组合高血压+消化病+关节病(1.00%)。省间共病患病率差异较大,呈现“西高东低、北高南低”的特点。不同共病组合相关的健康损失存在显著差异,关节炎共病组合造成的ADL损失(28.51%)和抑郁(77.68%)最高(
P
<
0.01)。慢病数量(OR=6.71,
P
<
0.01)、年龄(OR=1.96,
P
<
0.01)、大量饮酒是身心健康的共性风险因素,运动(OR=0.44,
P
<
0.01)和睡眠(OR=0.89,
P
<
0.01)是身心健康的保护因素,戒烟(OR=0.76,
P
<
0.01)有助于缓解焦虑。
结论
2
中老年人群中共病组合的患病率存在高度聚类现象,主要慢病组合引起的健康损失差异较大,相关健康干预策略应优先关注慢病共病并开展针对性的疾病管理和康复服务。
Objective
2
To analyze the multimorbidity and comorbid disease patterns among middle-aged and older adults aged 50 years and above in China and to study the prevalence, regional distribution, and relationship with health-related outcomes of major comorbid disease patterns.
Methods
2
The fourth national follow-up data of the China Health and Retirement Longitudinal Study (CHARLS) 2018 was used, including 13 774 respondents aged 50 years and older from 28 provincial units. We analyzed 14 patient-reported physician-diagnosed chronic diseases and multimorbidity combinations, reported prevalence, composition ratio, and regional distribution. Differences in health loss and risk factors between high morbidity groups were analyzed using chi-square tests and logistic regression.
Results
2
The prevalence of multimorbidities among participants was 57.3%. The single disease with high prevalence included arthritis/rheumatism (6.47%), hypertension (5.41%), and gastric and digestive disorders (4.17%); the binary multimorbidity combinations were arthritis + digestive disorders (3.06%), arthritis + hypertension (2.61%), and hypertension + hyperlipidemia (1.39%); the triadic combinations were hypertension + digestive disorders + joint disorders (1.00%). The prevalence of multimorbidity varied greatly between provinces, showing the characteristics of high in the west and north but low in the east and south China. Significant differences in the health loss caused by different multimorbidity combinations were noted, with the highest ADL loss (28.51%) and depression (77.68%) caused by the arthritis multimorbidity combinations (
P
<
0.01). The number of chronic diseases (OR=6.71,
P
<
0.01), age (OR=1.96,
P
<
0.01), and heavy alcohol consumption were comorbid risk factors for physical and mental health; exercise (OR=0.44,
P
<
0.01) and sleep (OR=0.89,
P
<
0.01) were protective factors for physical and mental health, and smoking cessation (OR=0.76,
P
<
0.01) contributed to the relief of anxiety.
Conclusions
2
The prevalence of comorbid patterns showed a high clustering trend, and the health loss caused by major patterns varied greatly. Relevant health intervention strategies should prioritize the major multimorbidity combinations for targeted disease management and rehabilitation services.
慢性病共病疾病组合地理信息系统健康损失
chronic diseasemultimorbiditycomorbid disease patternGIShealth loss
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