Background: Multimorbidity has become a prominent problem worldwide; however, few population-based studies have been conducted among older Chinese with multimorbidity. This study aimed to examine the prevalence of multimorbidity and explore its common patterns among a nationally representative sample of older Chinese. Methods: This study used data from the China Health and Retirement Longitudinal Study and included 19,841 participants aged at least 50 years. The prevalence of individual chronic diseases and multimorbidity during 2011–2015 were evaluated among the entire cohort and according to residential regions and gender. The relationships between participants’ demographic characteristics and multimorbidity were examined using logistic regression model. Patterns of multimorbidity were explored using hierarchical cluster analysis and association rule mining. Results: Multimorbidity occurred in 42.4% of the participants. The prevalence of multimorbidity was higher among women (odds ratio [OR] = 1.31, 95% confidence interval [CI]: 1.13–1.51) and urban residents (OR = 1.14, 95% CI: 1.02–1.27) than their respective counterparts after accounting for potential confounders of age, education, smoking, and alcohol consumption. Hierarchical cluster analysis revealed four common multimorbidity patterns: the vascular-metabolic cluster, the stomach-arthritis cluster, the cognitive-emotional cluster, and the hepatorenal cluster. Regional differences were found in the distributions of stroke and memory-related disease. Most combinations of conditions and urban–rural difference in multimorbidity patterns from hierarchical cluster analysis were also observed in association rule mining. Conclusion: The prevalence and patterns of multimorbidity vary by gender and residential regions among older Chinese. Women and urban residents are more vulnerable to multimorbidity. Future studies are needed to understand the mechanisms underlying the identified multimorbidity patterns and their policy and interventional implications.

Background. The course of cognitive aging has demonstrated substantial heterogeneity. This study attempted to identify distinctive cognitive trajectories and examine their relationship with burdens of disability, hospitalization, and nursing home admission. Methods. Seven hundred and fifty-four community-living persons aged 70 years or older in the Yale Precipitating Events Project were assessed with the Mini-Mental State Examination every 18 months for up to 108 months. A group-based trajectory model was used to determine cognitive aging trajectories while adjusting for age, sex, and education. Cumulative burden of disabilities, hospitalizations, and nursing home admissions over 141 months associated with the cognitive trajectories were evaluated using a generalized estimating equation Poisson model. Results. Five distinct cognitive trajectories were identified, with about a third of participants starting with high baseline cognitive function and demonstrating No decline during the follow-up period. The remaining participants diverged with Minimal (prevalence 41%), Moderate (16%), Progressive (8%), and Rapid (3%) cognitive decline. Participants with No decline incurred the lowest incidence rates (per 1,000 person-months) of disability in activities of daily living (ADL; 75, 95% confidence intervals: 60–95) and instrumental ADL (492, 453–535), hospitalization (29, 26–33) and nursing home admission (18, 12–27), whereas participants on the Rapid trajectory experienced the greatest burden of ADL disability (612, 595–758) and those on the Progressive trajectory had the highest nursing home admission (363, 292–451). Conclusions. Community-living older persons follow distinct cognitive aging trajectories and experience increasing burdens of disability, hospitalization, and nursing home placement as they age, with greater burdens for those on a declining cognitive trajectory.

To explore the multimorbidity prevalence and patterns among middle-aged and older adults from China. Data on thirteen chronic diseases were collected from 2,097,150 participants aged over 45 years between January 1st 2011 and December 31st 2015 from Beijing Medical Claim Data for Employees. Association rule mining and hierarchical cluster analysis were applied to assess multimorbidity patterns. Multimorbidity prevalence was 51.6% and 81.3% in the middle-aged and older groups, respectively. The most prevalent disease pair was that of osteoarthritis and rheumatoid arthritis (OARA) with hypertension (HT) (middle-aged: 22.5%; older: 41.8%). Ischaemic heart disease (IHD), HT, and OARA constituted the most common triad combination (middle-aged: 11.0%; older: 31.2%). Among the middle-aged group, the strongest associations were found in a combination of cerebrovascular disease (CBD), OARA, and HT with IHD in males (lift = 3.49), and CBD, OARA, and COPD with IHD in females (lift = 3.24). Among older patients, glaucoma and cataracts in females (lift = 2.95), and IHD, OARA, and glaucoma combined with cataracts in males (lift = 2.45) were observed. Visual impairment clusters, a mixed cluster of OARA, IHD, COPD, and cardiometabolic clusters were detected. Multimorbidity is prevalent among middle-aged and older Chinese individuals. The observations of multimorbidity patterns have implications for improving preventive care and developing appropriate guidelines for morbidity treatment.

Background: Evidence on the association between physical performance and multimorbidity is scarce in Asia. This study aimed to identify multimorbidity patterns and their association with physical performance among older Chinese adults. Methods: Individuals aged ≥60 years from the China Health and Retirement Longitudinal Study 2011–2015 (N = 10,112) were included. Physical performance was measured by maximum grip strength (kg) and average gait speed (m/s) categorized as fast (>0.8 m/s), median (>0.6–0.8 m/s), and slow (≤0.6 m/s). Multimorbidity patterns were explored using exploratory factor analysis. Generalized estimating equation was conducted. Results: Four multimorbidity patterns were identified: cardio–metabolic, respiratory, mental–sensory, and visceral–arthritic. An increased number of chronic conditions was associated with decreased normalized grip strength (NGS). Additionally, the highest quartile of factor scores for cardio–metabolic (β = −0.06; 95% Confidence interval (CI) = −0.07, −0.05), respiratory (β = −0.03; 95% CI = −0.05, −0.02), mental–sensory (β = −0.04; 95% CI = −0.05, −0.03), and visceral–arthritic (β = −0.04; 95% CI = −0.05, −0.02) patterns were associated with lower NGS compared with the lowest quartile. Participants with ≥4 chronic conditions were 2.06 times more likely to have a slow gait speed. Furthermore, the odds ratios for the highest quartile of factor scores of four patterns with slow gait speed compared with the lowest quartile ranged from 1.26–2.01. Conclusion: Multimorbidity was related to worse physical performance, and multimorbidity patterns were differentially associated with physical performance. A shift of focus from single conditions to the requirements of a complex multimorbid population was needed for research, clinical guidelines, and health-care services. Grip strength and gait speed could be targeted to routinely measure clinical performance among older adults with multimorbidity, especially mental–sensory disorders, in clinical settings.