As population ageing accelerates and life expectancy increases, multimorbidity and disability pose challenges to health and social care systems worldwide. Although multimorbidity is closely related to disability, there is still a lack of research on the impact of multimorbidity on disability in rural middle-aged and elderly people.

To evaluate the influence of multimorbidity on disability in rural middle-aged and elderly people using the propensity-score matching (PSM) , providing a reference for formulating strategies for the management of multimorbidity and disability in this population.

The data of 11 088 rural middle-aged and elderly people (≥45 years old) were collected from the 2018 China Health and Retirement Longitudinal Study in March 2022, including demographics, chronic disease prevalence, and disability measured by activities of daily living (ADLs) , and instrumental activities of daily living (IADLs) . Participants were divided into multimorbidity and non-multimorbidity groups by the prevalence of multimorbidity (defined as having ≥2 chronic conditions) , and then matched using PSM with a 1∶1 ratio. Conditional Logistic regression model for paired binary data was used to assess the impact of multimorbidity on ADL disability and IADL disability.

Of 11 088 ural middle-aged and elderly people with chronic diseases, 2 711 (24.45%) had ADL disability, 4 216 (38.02%) had IADL disability, and 7 673 (69.20%) were multimorbidity patients. The prevalence of ADL disability or IADL disability differed significantly by gender, age, marital status, education level, sleep duration, smoking, drinking, disability status, participation in social activities, and prevalence of multimorbidity (P<0.05) . There were statistically significant differences in gender, age, marital status, education level, sleep duration, smoking, drinking, disability status, and participation in social activities between the two groups before matching (P<0.05) . A total of 3 391 pairs were derived after PSM with matched covariates. Logistic regression analysis showed that multimorbidity prevalence increased the risk of ADL disability by a factor of 2.25〔OR (95%CI) =2.25 (1.96, 2.59) , P<0.001〕 and elevated the risk of IADL disability by a factor of 1.52〔OR (95%CI) =1.52 (1.36, 1.71) , P<0.001〕.

PSM is beneficial for reducing confounding bias in study groups. Multimorbidity would increase the risk of disability in rural middle-aged and elderly people. It is suggested to value the government input on resources and policies to strengthen the prevention and management of multimorbidity and disability in this group of people.

随着人口老龄化的加速和预期寿命的延长，慢性病共病和失能对全球卫生和社会保健系统带来重大挑战。慢性病共病与失能之间关联紧密，目前尚缺乏关注农村中老年人群体慢性病共病对失能影响的研究。

探讨农村中老年人慢性病共病对失能的影响，为制订农村中老年人慢性病共病和失能的管理策略提供参考依据。

2022年3月，提取2018年中国健康与养老追踪调查（CHARLS）数据库中11 088例≥45岁农村中老年慢性病患者的数据资料，包括基本情况、患慢性病情况、日常生活自理能力（ADL）与工具性日常生活自理能力（IADL）失能情况。依据慢性病患者所患慢性病是否≥2种将其分为共病组和非共病组。采用倾向性得分匹配（PSM）法将共病组与非共病组以1∶1比例进行基本情况匹配，应用二元条件Logistic回归分析慢性病共病对ADL失能和IADL失能的影响。

11 088例农村中老年慢性病患者中，2 711例（24.45%）ADL失能，4 216例（38.02%）IADL失能，7 673例（69.20%）为慢性病共病患者。不同性别、年龄、婚姻状况、受教育程度、睡眠时间、吸烟史、饮酒史、残疾情况、参加社交活动情况、慢性病共病情况的受访者ADL失能率和IADL失能率比较，差异均有统计学意义（P<0.05）。PSM前，共病组和非共病组的性别、年龄、婚姻状况、受教育程度、睡眠时间、吸烟史、饮酒史、残疾情况、参加社交活动情况比较，差异均有统计学意义（P<0.05），PSM后共有3 391对匹配成功，匹配后两组协变量达到均衡。二元条件Logistic回归分析结果显示，共病组农村中老年人ADL失能风险是非共病组的2.25倍〔95%CI（1.96，2.59），P<0.001〕，共病组农村中老年人IADL失能风险是非共病组的1.52倍〔95%CI（1.36，1.71），P<0.001〕。

PSM可有效控制研究组间的混杂偏倚；在农村，中老年人慢性病共病会增加失能的风险，政府应重视农村地区资源和政策投入，加强对农村地区中老年人慢性病共病和失能的预防与管理。