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.

Trends in the prevalence of vision impairment among the oldest-old Chinese population from 1998 to 2018.

Background: Vision impairment has become a prominent public health issue worldwide. However, little is known about vision impairment prevalence trends among the oldest-old adults in China. This study aimed to examine 20-year trends in the prevalence of vision impairment among the oldest-old Chinese adults and explore the contributions of sociodemographic variables, health behaviours, and chronic conditions to the trends. Methods: This retrospective longitudinal study used data from the Chinese Longitudinal Healthy Longevity Survey during 1998-2018. A total of 45 849 participants aged ≥80 years at study entry were included. Vision impairment was assessed by an adapted Landolt-C chart at each wave. We examined unadjusted and adjusted nonlinear trends using generalized estimating equation models incorporating a natural cubic spline. We conducted linear regression models to estimate absolute annual prevalence changes and determine the contributions of sociodemographic variables, health behaviours, and chronic conditions to the trends. Results: The fully adjusted prevalence doubled from 5.5% (95% confidence interval (CI) = 5.1%-6.0%) in 1998 to 10.7% (95% CI = 9.9%-11.5%) in 2011 and slightly increased to 11.1% (95% CI = 10.3%-12.0%) in 2018 among the oldest-old Chinese population. Glaucoma, cataracts, cognitive impairment, hearing impairment, and urban residence were significant contributors to changes in vision impairment prevalence during 1998-2018. Differences in vision impairment prevalence associated with glaucoma and cataracts narrowed since 2005. Disparities in the trends among cognitively impaired and unimpaired older adults remained unchanged over time. Similar results were observed in older people with and without hearing impairment. Conclusions: Vision impairment prevalence among the oldest-old Chinese population increased from 1998 to 2011 and remained stable from 2011 to 2018. Future work is needed to improve the prevention and management of chronic diseases associated with vision impairment to reduce its prevalence.

Development and Validation of a Multimorbidity Index Predicting Mortality Among Older Chinese Adults.

Objective: This study aimed to develop and validate a multimorbidity index using self-reported chronic conditions for predicting 5-year mortality risk. Methods: We analyzed data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and included 11,853 community-dwelling older adults aged 65-84 years. Restrictive association rule mining (ARM) was used to identify disease combinations associated with mortality based on 13 chronic conditions. Data were randomly split into the training (N = 8,298) and validation (N = 3,555) sets. Two multimorbidity indices with individual diseases only (MI) and disease combinations (MIDC) were developed using hazard ratios (HRs) for 5-year morality in the training set. We compared the predictive performance in the validation set between the models using condition count, MI, and MIDC by the concordance (C) statistic, the Integrated Discrimination Improvement (IDI), and the Net Reclassification Index (NRI). Results: A total of 13 disease combinations were identified. Compared with condition count (C-statistic: 0.710), MIDC (C-statistic: 0.713) showed significantly better discriminative ability (C-statistic: p = 0.016; IDI: 0.005, p < 0.001; NRI: 0.038, p = 0.478). Compared with MI (C-statistic: 0.711), the C-statistic of the model using MIDC was significantly higher (p = 0.031), while the IDI was more than 0 but not statistically significant (IDI: 0.003, p = 0.090). Conclusion: Although current multimorbidity status is commonly defined by individual chronic conditions, this study found that the multimorbidity index incorporating disease combinations showed supreme performance in predicting mortality among community-dwelling older adults. These findings suggest a need to consider significant disease combinations when measuring multimorbidity in medical research and clinical practice.

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.

A Method for Detecting and Analyzing Facial Features of People with Drug Use Disorders.

Drug use disorders caused by illicit drug use are significant contributors to the global burden of disease, and it is vital to conduct early detection of people with drug use disorders (PDUD). However, the primary care clinics and emergency departments lack simple and effective tools for screening PDUD. This study proposes a novel method to detect PDUD using facial images. Various experiments are designed to obtain the convolutional neural network (CNN) model by transfer learning based on a large-scale dataset (9870 images from PDUD and 19,567 images from GP (the general population)). Our results show that the model achieved 84.68%, 87.93%, and 83.01% in accuracy, sensitivity, and specificity in the dataset, respectively. To verify its effectiveness, the model is evaluated on external datasets based on real scenarios, and we found it still achieved high performance (accuracy > 83.69%, specificity > 90.10%, sensitivity > 80.00%). Our results also show differences between PDUD and GP in different facial areas. Compared with GP, the facial features of PDUD were mainly concentrated in the left cheek, right cheek, and nose areas (p < 0.001), which also reveals the potential relationship between mechanisms of drugs action and changes in facial tissues. This is the first study to apply the CNN model to screen PDUD in clinical practice and is also the first attempt to quantitatively analyze the facial features of PDUD. This model could be quickly integrated into the existing clinical workflow and medical care to provide capabilities.

Adherence of HIV Self-Testing Among Men Who Have Sex With Men in China: Longitudinal Study.

BACKGROUND: The World Health Organization recommended HIV self-testing (HIVST) for individuals practicing unsafe sexual behaviors; however, the adherence to HIV testing has not been reported. OBJECTIVE: In this study, we attempted to determine the adherence to HIVST among men who have sex with men (MSM), as well as the impact factors and potential effects of their adherence. METHODS: We conducted a longitudinal study among MSM in Harbin, Heilongjiang province, China from July 1, 2017 to June 30, 2018. A mobile app system was used to provide the "Mailing rapid test reagent kit" for the HIVST service. The proportion of those who adhered to HIV testing every 3 months was calculated. Logistic regression was used to explore the impact factors related to adherence to HIVST. Rates of HIV infection between MSM who adhered to HIVST and those who did not were compared using Cox proportional hazards regression. Changes of condom use behaviors between the two groups were also compared using the chi-square test. RESULTS: A total of 1315 MSM who received the HIVST service through the app were included in the study. Overall, 10% of the MSM adhered to HIVST, and the proportion of adhering tests was only 34.9%. Adherence of HIVST was associated with marital status (adjusted odds ratio [OR]unmarried vs married 2.31, 95% CI 1.13-4.71) and the number of HIV tests they received (adjusted OR3 times vs 2 times or below 3.36, 95% CI 2.01-5.63; adjusted OR4 times or above vs 2 times or below 7.30, 95% CI 4.67-11.42). Twenty HIV seroconversions were observed during 1-year follow up. The rate of HIV infection in the adherence group (17.10 per 100 person years, 95% CI 8.80-30.84) was significantly higher than that in the nonadherence group (4.80 per 100 person years, 95% CI 2.77-7.88; adjusted hazard ratio 3.33, 95% CI 1.35-8.20). Those who adhered to HIV testing were more likely to improve condom use behaviors, although the difference was not statistically significant. CONCLUSIONS: Regular HIV testing is necessary for early detection of HIV infection among MSM. Given the poor adherence, a new internet-based management paradigm for MSM is needed to raise their health awareness to optimize the implementation of HIVST.

Protect MSM from HIV and other sexually transmitted diseases by providing mobile health services of partner notification: protocol for a pragmatic stepped wedge cluster randomized controlled trial.

BACKGROUND: Recently, more and more men who have sex with men (MSM) look for casual partners through online dating platforms in China. However, most are unable to know their partners' HIV and other sexually transmitted diseases (STD) statuses, leading to the rapid increase in HIV infection among Chinese MSM. Effective partner notification is urgently needed to increase the risk awareness of MSM and prevent HIV and other STDs transmission. However, the traditional intervention mainly targets to the HIV-positive MSM and the effect is not promising. Our study aims to provide Internet-based partner notification, along with a series of health services for HIV-negative MSM to protect them from HIV and other STDs. METHODS: A pragmatic stepped wedge cluster randomized controlled trial design is used to evaluate the effectiveness of a new intervention paradigm, which aims to reduce HIV and other STDs incidences among MSM in China. Through integrating a mobile health (mHealth) service application (app) to the current HIV and other STDs prevention and control methods, the new paradigm provides partner notification of HIV, syphilis, hepatitis B, and hepatitis C statuses. A total of 6172 MSM in 16 districts of Beijing, China will be recruited and randomized to sequentially receive partner notification intervention through the app at 6-month intervals. The primary outcomes are HIV incidence and the additional cost of the intervention. The secondary outcomes include incidences of syphilis, hepatitis B, and hepatitis C, disease transmission social networks, testing adherence, knowledge of HIV and STDs control, health self-responsibility awareness, changes of high risk behaviors and other related outcomes. The generalized linear mixed models (GLMM) will be used to analyze the differences of outcomes in the control period and in the intervention period. DISCUSSION: We expect that the HIV incidence will be significantly lower and the secondary outcomes will also be improved with providing health service of partner notification through mhealth intervention. The feasible and affordable public health intervention paradigm will have implications for HIV and STDs prevention and control among MSM and other key populations. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04349748 . Registered on 16 April 2020.

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.