Comparing a new multimorbidity index with other multimorbidity measures for predicting disability trajectories.

BACKGROUND: The optimal multimorbidity measures for predicting disability trajectories are not universally agreed upon. We developed a multimorbidity index among middle-aged and older community-dwelling Chinese adults and compare its predictive ability of disability trajectories with other multimorbidity measures. METHODS: This study included 17,649 participants aged ≥50 years from the China Health and Retirement Longitudinal Survey 2011-2018. Two disability trajectory groups were estimated using the total disability score differences calculated between each follow-up visit and baseline. A weighted index was constructed using logistic regression models for disability trajectories based on the training set (70 %). The index and the condition count were used, along with the pattern identified by the latent class analysis to measure multimorbidity at baseline. Logistic regression models were used in the training set to examine associations between each multimorbidity measure and disability trajectories. C-statistics, integrated discrimination improvements, and net reclassification indices were applied to compare the performance of different multimorbidity measures in predicting disability trajectories in the testing set (30 %). RESULTS: In the newly developed multimorbidity index, the weights of the chronic conditions varied from 1.04 to 2.55. The multimorbidity index had a higher predictive performance than the condition count. The condition count performed better than the multimorbidity pattern in predicting disability trajectories. LIMITATION: Self-reported chronic conditions. CONCLUSIONS: The multimorbidity index may be considered an ideal measurement in predicting disability trajectories among middle-aged and older community-dwelling Chinese adults. The condition count is also suggested due to its simplicity and superior predictive performance.

The association between vision impairment and cognitive outcomes in older adults: a systematic review and meta-analysis.

OBJECTIVES: To provide a quantitative synthesis of studies on the relationship between vision impairment (VI) and cognitive outcomes in older adults. METHOD: A systematic search was undertaken of relevant databases for original articles published before April 2020. Random effect models were used to obtain pooled estimates of the associations between VI and cognitive outcomes (cognitive impairment and dementia) with subgroup analyses of VI measures, cross-sectional associations of VI with cognitive impairment, and longitudinal associations of baseline VI with incident cognitive impairment and dementia. Potential sources of heterogeneity were explored by meta-regression. Publication bias was evaluated with Egger's test. RESULTS: Sixteen studies including 76,373 participants were included in this meta-analysis, with five cross-sectional studies and eleven longitudinal studies. There was a significantly increased risk of cognitive outcomes with VI identified by subjective measures (odds ratio (OR)=1.63; 95% confidence interval (CI): 1.26-1.99) and objective measures (OR = 1.59; 95% CI: 1.40-1.78). The odds of baseline cognitive impairment were 137% higher in older adults with VI compared with those without VI (OR = 2.37, 95% CI: 1.84-3.03) at baseline. Compared with older adults without VI at baseline, those with baseline VI had a higher relative risk (RR) of incident cognitive impairment (RR = 1.41; 95% CI: 1.31-1.51) and dementia (RR = 1.44, 95% CI: 1.19-1.75). CONCLUSIONS: VI was associated with increased risks of cognitive impairment and dementia across cross-sectional and longitudinal studies. Additional research and randomized clinical trials are warranted to examine the implications of treatment for VI, such as wearing glasses and cataract surgery, to avoid cognitive impairment and dementia.

Multimorbidity measures differentially predicted mortality among older Chinese adults.

OBJECTIVES: This study aimed to examine and compare the associations between different multimorbidity measures and mortality among older Chinese adults. STUDY DESIGN AND SETTING: Using the Chinese Longitudinal Healthy Longevity Survey 2002-2018, data on fourteen chronic conditions from 13,144 participants aged ≥65 years were collected. Multimorbidity measures included condition counts, multimorbidity patterns (examined by exploratory factor analysis), and multimorbidity trajectories (examined by a group-based trajectory model). Mortality risk associated with different multimorbidity measures was each analyzed using Cox regression. C-statistic, the Integrated Discrimination Improvement (IDI), and the Net Reclassification Index (NRI) were used to compare the performance of different multimorbidity measures. RESULTS: Participants with multimorbidity, regardless of measurements, had a higher risk of death compared with people without multimorbidity. Compared with the mortality prediction model using age and sex, C-statistics showed added discrimination (over 0.77, all P < .05) for models with multimorbidity measures. Multimorbidity trajectory showed integrated discrimination and net reclassification improvement for mortality prediction compared to condition count (IDI = 0.042, NRI = 0.033) and multimorbidity pattern (IDI = 0.041, NRI = 0.069). CONCLUSION: Adding multimorbidity measures significantly improved the performance of a mortality prediction model using age and sex as predictors. Trajectory-based measures of multimorbidity performed better than count- and pattern-based measures for mortality prediction.

Patterns of cardiometabolic multimorbidity and the risk of depressive symptoms in a longitudinal cohort of middle-aged and older Chinese.

BACKGROUND: Cardiometabolic diseases (CMDs) are associated with depression. However, it is unclear whether coexisting CMDs may increase the risk of depression. We examined associations between cardiometabolic multimorbidity and depressive symptoms among middle-aged and older Chinese. METHODS: Participants aged ≥45 years were enrolled from the China Health and Retirement Longitudinal Study 2011-2018 (N = 18,002). Cardiometabolic multimorbidity was defined as the coexistence of ≥2 CMDs, including stroke, heart disease, diabetes, hypertension, and dyslipidemia. Depressive symptoms were assessed by the Center for Epidemiological Studies Depression Scale. We used generalized estimating equation models to examine associations between cardiometabolic multimorbidity and depressive symptoms, including the dose effect of disease count and prevalent disease combinations, as well as individual and additive effects of specific CMDs. RESULTS: The prevalence of cardiometabolic multimorbidity was 24.5%. A higher number of CMDs had an additive dose effect on depressive symptoms that persisted consistently in specific CMDs. Stroke only, heart disease only, and diabetes only were each associated with a higher risk of depressive symptoms compared with no CMDs. CMD combinations involving stroke, heart disease, or diabetes were each associated with an increased risk of depressive symptoms compared with the absence of stroke, heart disease, or diabetes. LIMITATION: Self-reported chronic conditions. CONCLUSION: Stroke, heart disease, and diabetes showed individual and additive effects on CMD combinations, whereas hypertension and dyslipidemia only showed associations with depressive symptoms in combinations with other CMDs. These results suggest person-centered healthcare of mental health prevention and treatment for middle-aged and older adults with individual or multiple CMDs.

Associations between Multimorbidity and Physical Performance in Older Chinese Adults.

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 (ß = -0.06; 95% Confidence interval (CI) = -0.07, -0.05), respiratory (ß = -0.03; 95% CI = -0.05, -0.02), mental-sensory (ß = -0.04; 95% CI = -0.05, -0.03), and visceral-arthritic (ß = -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.

Associations Between Somatic Multimorbidity Patterns and Depression in a Longitudinal Cohort of Middle-Aged and Older Chinese.

OBJECTIVES: Depressive symptoms are commonly seen among patients with multiple chronic somatic conditions, or somatic multimorbidity (SMM); however, little is known about the relationships between depressive symptoms and different SMM combinations. Our study aimed to delineate the patterns of SMM and their longitudinal associations with depressive symptoms among a nationally representative sample of middle-aged and older Chinese adults. DESIGN: We employed a longitudinal design. SETTING AND PARTICIPANTS: Older adults (N = 10,084) aged ≥45 years from the China Health and Retirement Longitudinal Study 2011-2015 participated (mean age = 57.7 years at baseline; 53.3% men). METHODS: Sixteen chronic somatic conditions were ascertained at baseline via questionnaires. Depression was assessed with the Center for Epidemiological Studies Depression Scale at baseline and during follow-up. Patterns of SMM were identified via exploratory factor analyses. Generalized estimating equations were used to evaluate the longitudinal associations between patterns of SMM and the presence of depressive symptoms at follow-up. RESULTS: Compared with participants with no somatic condition, those with 1, 2, and 3 or more somatic conditions had a 21%, 66%, and 111% greater risk, respectively, for the presence of depressive symptoms. Increased factor scores for 4 patterns identified, cardio-metabolic pattern [adjusted odds ratio (AOR) 1.12, 95% confidence interval (CI) 1.06, 1.20], respiratory pattern (AOR 1.25, 95% CI 1.17, 1.33), arthritic-digestive-visual pattern (AOR 1.29, 95% CI 1.22, 1.37), and hepatic-renal-skeletal pattern (AOR 1.09, 95% CI 1.02, 1.16), were all associated with a higher risk of having depressive symptoms. CONCLUSIONS AND IMPLICATIONS: All SMM patterns were independently associated with depression among middle-aged and older Chinese adults, with greater odds for people with comorbid arthritic-digestive-visual conditions and respiratory conditions. Clinical practitioners should treat the middle-aged and older population under a multiple-condition framework combining SMM and mental disorders.