Background the aim of this study was to examine the cross-sectional and longitudinal associations of different multimorbidity patterns with physical frailty in older adults. Methods we used data from the Swedish National study on Aging and Care in Kungsholmen to generate a physical frailty measure, and clusters of participants with similar multimorbidity patterns were identified through fuzzy c-means cluster analyses. The cross-sectional association (n = 2,534) between multimorbidity clusters and physical frailty was measured through logistic regression analyses. Six- (n = 2,122) and 12-year (n = 2,140) longitudinal associations were determined through multinomial logistic regression analyses. Results six multimorbidity patterns were identified at baseline: psychiatric diseases; cardiovascular diseases, anaemia and dementia; sensory impairments and cancer; metabolic and sleep disorders; musculoskeletal, respiratory and gastrointestinal diseases; and an unspecific pattern lacking any overrepresented diseases. Cross-sectionally, each pattern was associated with physical frailty compared with the unspecific pattern. Over 6 years, the psychiatric diseases (relative risk ratio [RRR]: 3.04; 95% confidence intervals [CI]: 1.59–5.79); cardiovascular diseases, anaemia and dementia (RRR 2.25; 95% CI: 1.13–4.49) and metabolic and sleep disorders (RRR 1.99; 95% CI: 1.25–3.16) patterns were associated with incident physical frailty. The cardiovascular diseases, anaemia and dementia (RRR: 4.81; 95% CI: 1.59–14.60); psychiatric diseases (RRR 2.62; 95% CI: 1.45–4.72) and sensory impairments and cancer (RRR 1.87; 95% CI: 1.05–3.35) patterns were more associated with physical frailty, compared with the unspecific pattern, over 12 years. Conclusions we found that older adults with multimorbidity characterised by cardiovascular and neuropsychiatric disease patterns are most susceptible to developing physical frailty.

中文翻译：

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居住在社区的老年人的多发病模式和虚弱风险：一项基于人群的队列研究

背景 本研究的目的是检查不同的多发病模式与老年人身体虚弱的横断面和纵向关联。方法 我们使用瑞典国家关于 Kungsholmen 的老龄化和护理研究的数据来生成身体虚弱测量，并通过模糊 c 均值聚类分析确定具有相似多发病模式的参与者集群。通过逻辑回归分析测量多发病群和身体虚弱之间的横截面关联（n = 2,534）。通过多项逻辑回归分析确定六年（n = 2,122）和 12 年（n = 2,140）纵向关联。结果 在基线时确定了六种多发病模式：精神疾病；心血管疾病、贫血和痴呆；感觉障碍和癌症；代谢和睡眠障碍；肌肉骨骼、呼吸系统和胃肠道疾病；以及缺乏任何过度代表疾病的非特异性模式。从横截面来看，与非特异性模式相比，每种模式都与身体虚弱有关。超过 6 年的精神疾病（相对风险比 [RRR]：3.04；95% 置信区间 [CI]：1.59–5.79）；心血管疾病、贫血和痴呆（RRR 2.25；95% CI：1.13-4.49）以及代谢和睡眠障碍（RRR 1.99；95% CI：1.25-3.16）模式与身体虚弱相关。心血管疾病、贫血和痴呆（RRR：4.81；95% CI：1.59–14.60）；精神疾病（RRR 2.62；95% CI：1.45-4.72）和感觉障碍和癌症（RRR 1.87；95% CI：1.05-3.35）模式与身体虚弱更相关，与非特异性模式相比，超过 12 年。结论 我们发现，以心血管和神经精神疾病模式为特征的患有多种疾病的老年人最容易出现身体虚弱。