School of Public Health, LKS Faculty of Medicine, University of Hong Kong, Hong Kong 999077, China.
Global Health Research Center, Duke Kunshan University, Kunshan 215316, China.
Age Ageing. 2022 Aug 2;51(8). doi: 10.1093/ageing/afac177.
to identify multimorbidity patterns among middle-aged and older adults in China and examine how these patterns are associated with incident disability and recovery of independence.
data were from The China Health and Retirement Longitudinal Study. We included 14,613 persons aged ≥45 years. Latent class analysis (LCA) was conducted to identify multimorbidity patterns with clinical meaningfulness. Multinomial logistic models were used to determine the adjusted association between multimorbidity patterns and incident disability and recovery of independence.
we identified four multimorbidity patterns: 'low morbidity' (67.91% of the sample), 'pulmonary-digestive-rheumatic' (17.28%), 'cardiovascular-metabolic-neuro' (10.77%) and 'high morbidity' (4.04%). Compared to the 'low morbidity' group, 'high morbidity' (OR = 2.63, 95% CI = 1.97-3.51), 'pulmonary-digestive-rheumatic' (OR = 1.89, 95% CI = 1.63-2.21) and 'cardiovascular-metabolic-neuro' pattern (OR = 1.61, 95% CI = 1.31-1.97) had higher odds of incident disability in adjusted multinomial logistic models. The 'cardiovascular-metabolic-neuro' (OR = 0.60, 95% CI = 0.44-0.81), 'high morbidity' (OR = 0.68, 95% CI = 0.47-0.98) and 'pulmonary-digestive-rheumatic' group (OR = 0.75, 95% CI = 0.60-0.95) had lower odds of recovery from disability than the 'low morbidity' group. Among people without disability, the 'cardiovascular-endocrine-neuro' pattern was associated with the highest 2-year mortality (OR = 2.42, 95% CI = 1.56-3.72).
multimorbidity is complex and heterogeneous, but our study demonstrates that clinically meaningful patterns can be obtained using LCA. We highlight four multimorbidity patterns with differential effects on incident disability and recovery from disability. These studies suggest that targeted prevention and treatment approaches are needed for people with multimorbidity.
识别中国中老年人群的多病共存模式,并探讨这些模式与残疾发生和独立性恢复的关系。
数据来自中国健康与退休纵向研究。共纳入 14613 名年龄≥45 岁的人群。采用潜在类别分析(LCA)识别具有临床意义的多病共存模式。采用多分类逻辑回归模型确定多病共存模式与残疾发生和独立性恢复之间的调整关联。
我们确定了四种多病共存模式:“低患病”(样本的 67.91%)、“肺部-消化系统-风湿病”(17.28%)、“心血管-代谢-神经”(10.77%)和“高患病”(4.04%)。与“低患病”组相比,“高患病”(OR=2.63,95%CI=1.97-3.51)、“肺部-消化系统-风湿病”(OR=1.89,95%CI=1.63-2.21)和“心血管-代谢-神经”模式(OR=1.61,95%CI=1.31-1.97)发生残疾的调整后多分类逻辑回归模型的比值比更高。“心血管-代谢-神经”(OR=0.60,95%CI=0.44-0.81)、“高患病”(OR=0.68,95%CI=0.47-0.98)和“肺部-消化系统-风湿病”组(OR=0.75,95%CI=0.60-0.95)发生残疾的恢复的比值比低于“低患病”组。在无残疾人群中,“心血管-内分泌-神经”模式与最高的 2 年死亡率相关(OR=2.42,95%CI=1.56-3.72)。
多病共存是复杂和异质的,但本研究表明,使用 LCA 可以获得具有临床意义的模式。我们强调了四种对残疾发生和残疾恢复具有不同影响的多病共存模式。这些研究表明,需要针对多病共存人群采取有针对性的预防和治疗措施。