Multimorbidity, the presence of two or more mental or physical chronic non-communicable diseases, is a major challenge for the health system in China, which faces unprecedented ageing of its population. Here we examined the distribution of physical multimorbidity in relation to socioeconomic status; the association between physical multimorbidity, health-care service use, and catastrophic health expenditures; and whether these associations varied by socioeconomic group and social health insurance schemes. In this population-based, panel data analysis, we used data from three waves of the nationally representative China Health and Retirement Longitudinal Study (CHARLS) for 2011, 2013, and 2015. We included participants aged 50 years and older in 2015, who had complete follow-up for the three waves. We used 11 physical non-communicable diseases to measure physical multimorbidity and annual per-capita household consumption spending as a proxy for socioeconomic status. Of 17 708 participants in CHARLS, 11 817 were eligible for inclusion in our analysis. The median age of participants was 62 years (IQR 56-69) in 2015, and 5766 (48·8%) participants were male. 7320 (61·9%) eligible participants had physical multimorbidity in China in 2015. The prevalence of physical multimorbidity was increased with older age (odds ratio 2·93, 95% CI 2·71-3·15), among women (2·70, 2·04-3·57), within a higher socioeconomic group (for quartile 4 [highest group] 1·50, 1·24-1·82), and higher educational level (5·17, 3·02-8·83); however, physical multimorbidity was more common in poorer regions than in the more affluent regions. An additional chronic non-communicable disease was associated with an increase in the number of outpatient visits (incidence rate ratio 1·29, 95% CI 1·27-1·31), and number of days spent in hospital as an inpatient (1·38, 1·35-1·41). We saw similar effects in health service use of an additional chronic non-communicable disease in different socioeconomic groups and among those covered by different social health insurance programmes. Overall, physical multimorbidity was associated with a significantly increased likelihood of catastrophic health expenditure (for the overall population: odds ratio 1·29, 95% CI 1·26-1·32, adjusted for sociodemographic variables). The effect of physical multimorbidity on catastrophic health expenditures persisted even among the higher socioeconomic groups and across all health insurance programmes. Concerted efforts are needed to reduce health inequalities that are due to physical multimorbidity, and its adverse economic effect in population groups in China. Social health insurance reforms must place emphasis on reducing out-of-pocket spending for patients with multimorbidity to provide greater financial risk protection. None.

Loss of muscle mass and muscle strength are natural consequences of the aging process, accompanied by an increased prevalence of chronic health conditions. Research suggests that in the elderly, the presence of comorbidities may impact the muscle mass/strength relationship. The objectives of this study were to characterize the muscle mass/strength relationship in older adults in the USA and to examine the impact of a variety of comorbidities on this relationship. Data were obtained from the National Health and Nutrition Examination Survey 1999–2002 databases. Subjects aged 50 years and older were included in the present study. Muscle mass was assessed by height-adjusted appendicular skeleton muscle mass (aASM) in kg/m2, as measured by dual-energy x-ray absorptiometry. Muscle strength was assessed via isokinetic quadriceps strength (IQS) in newton as measured by a dynamometer. The relationship between aASM and IQS was assessed adjusting for age and gender. The effects of a variety of comorbidities on IQS and/or on the relationship between IQS and aASM were assessed using multiple regression models. This study included 2,647 individuals, with a mean age of 62.6 years and 52.9% of whom were female. The mean (SE) aASM (kg/m2) was 7.3 (0.04), and the mean (SE) IQS (newton) was 365.0 (3.00). After adjusting for age and gender, the correlation coefficient between aASM and IQS was 0.365 (P < 0.001). Diabetes, coronary heart disease/congestive heart failure (CHD/CHF), and vision problems were significant predictors of lower muscle strength (P < 0.05) in the multiple regression models that adjusted for age, gender, and aASM, and obesity significantly modified the relationship between aASM and IQS (P < 0.05). Among individuals aged 50 and older in the US, muscle mass and muscle strength are positively correlated, independent of the associations of age and gender with muscle mass and strength. A variety of comorbid medical conditions serve as independent predictors of lower muscle strength (e.g., diabetes, CHD/CHF, vision problems) and/or modify the relationship between muscle mass and muscle strength (e.g., obesity).

Alzheimer's disease (AD) is a neurodegenerative disorder incurring significant social and economic costs. This study uses a US administrative claims database to evaluate the effect of AD on direct healthcare costs and utilization, and to identify the most common reasons for AD patients' emergency room (ER) visits and inpatient admissions.

Background: The epidemiology of stroke is evolving in China as the population undergoes demographic, lifestyle, and economic transitions. An updated review is pertinent to providing feedback on current, and in planning future, prevention and management strategies. Aims: To identify high-quality epidemiological studies for quantifying the prevalence, incidence, mortality, and case fatality for stroke in China. Methods: A search was undertaken across a range of bibliographic databases on 30 November 2021 without time limitation. Assessments were made of the risk of bias of the included studies. The outcomes were synthesized using a random-effects model. Subgroup analysis and meta-regression models were used to define the source of heterogeneity. Results: Of 9407 identified records, 26 population-based studies were included. Due to significant heterogeneity across the studies, the original range for crude rates of indices was wide. The pooled annual prevalence was 1329.5/100,000 (95% confidence interval (CI) 713.6–2131.9, p < 0.001), incidence 442.1/100,000 (327.6–573.8, p < 0.001), mortality 154.1/100,000 (52.6–308.8, I² = 100%, p < 0.001), and case fatality 35.8% (26.1% to 46.1%, I² = 97%, p < 0.001). The prevalence and incidence of stroke have increased, but stroke-related case fatality has declined in China over recent decades. There are significant regional and rural-urban differences in incidence rates. Conclusion: Despite improved public health policies and healthcare delivery, the burden of stroke remains high in China. Further coordinated efforts are required in prevention and community care to offset the likelihood of further expansion in the absolute number of stroke cases in this large population.

Background: Preventing chronic disease is important in health policy in countries with significantly ageing populations. This study aims to examine the prevalence of chronic disease multimorbidity and its association with physical activity and sleep duration; and to understand whether physical activity modifies associations between sleep duration and multimorbidity. Methods: We utilized longitudinal data of a nationally-representative sample from the China Health and Retirement Longitudinal Study (in year 2011 and 2015; N = 5321; 54.7% female; age ≥ 45 years old). Fourteen chronic diseases were used to measure multimorbidity (ten self-reported, and four by blood test). Participants were grouped into high, moderate, and low level based on self-reported frequencies and durations of physical activity with different intensities for at least 10 min at a time in a usual week. Poor and good sleepers were categorized according to average hours of actual sleep at each night during the past month. Panel data method of random-effects logistic regression model was applied to estimate the association of physical activity and sleep with multimorbidity, adjusting for social-demographic and behavioural confounders. Results: From 2011 to 2015, the prevalence of multimorbidity increased from 52.2 to 62.8%. In 2015, the proportion of participants engaging in high, moderate, and low level of physical activity was 30.3, 24.4 and 45.3%, respectively, and 63.6% of adults had good sleep. For both genders, compared with good sleep, poor sleep was associated with higher odds of multimorbidity (OR = 1.527, 95% CI: 1.277, 1.825). Compared to the high-level group, participants with a low level of physical activity were significantly more likely to have multimorbidity (OR = 1.457, 95% CI: 1.277, 1.825), but associations were stronger among women. The relative excess risk due to interaction between poor sleep and moderate or low physical activity was positive but non-significant on multimorbidity. Conclusions: The burden of multimorbidity was high in China. Low physical activity and poor sleep was independently and significantly associated with a higher likelihood of multimorbidity in women and both genders, separately. Physical activity could modify the association between sleep and multimorbidity.

Objectives To examine non-communicable diseases (NCDs) multimorbidity level and its relation to households’ socioeconomic characteristics, health service use, catastrophic health expenditures and productivity loss. Design This study used panel data of the Indonesian Family Life Survey conducted in 2007 (Wave 4) and 2014 (Wave 5). Setting The original sampling frame was based on 13 out of 27 provinces in 1993, representing 83% of the Indonesian population. Participants We included respondents aged 50 years and above in 2007, excluding those who did not participate in both Waves 4 and 5. The total number of participants in this study are 3678 respondents. Primary outcome measures We examined three main outcomes; health service use (outpatient and inpatient care), financial burden (catastrophic health expenditure) and productivity loss (labour participation, days primary activity missed, days confined in bed). We applied multilevel mixed-effects regression models to assess the associations between NCD multimorbidity and outcome variables, Results Women were more likely to have NCD multimorbidity than men and the prevalence of NCD multimorbidity increased with higher socioeconomic status. NCD multimorbidity was associated with a higher number of outpatient visits (compared with those without NCD, incidence rate ratio (IRR) 4.25, 95% CI 3.33 to 5.42 for individuals with >3 NCDs) and inpatient visits (IRR 3.68, 95% CI 2.21 to 6.12 for individuals with >3 NCDs). NCD multimorbidity was also associated with a greater likelihood of experiencing catastrophic health expenditure (for >3 NCDs, adjusted OR (aOR) 1.69, 95% CI 1.02 to 2.81) and lower participation in the labour force (aOR 0.23, 95% CI 0.16 to 0.33) compared with no NCD. Conclusions NCD multimorbidity is associated with substantial direct and indirect costs to individuals, households and the wider society. Our study highlights the importance of preparing health systems for addressing the burden of multimorbidity in low-income and middle-income countries.