ObjectivesTo examine non-communicable diseases (NCDs) multimorbidity level and its relation to households’ socioeconomic characteristics, health service use, catastrophic health expenditures and productivity loss.DesignThis study used panel data of the Indonesian Family Life Survey conducted in 2007 (Wave 4) and 2014 (Wave 5).SettingThe original sampling frame was based on 13 out of 27 provinces in 1993, representing 83% of the Indonesian population.ParticipantsWe 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 measuresWe 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,ResultsWomen 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.ConclusionsNCD 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.

Background Multimorbidity (the presence of two or more non-communicable diseases) is a major growing challenge for many low-income and middle-income countries (LMICs). Yet, its effects on health care costs and financial burden for patients have not been adequately studied. This study investigates the effect of multimorbidity across the different percentiles of healthcare utilisation and out-of-pocket expenditure (OOPE). Methods We conducted a secondary data analysis of the 2014/2015 Indonesian Family Life Survey (IFLS-5), which included 13,798 respondents aged ≥40 years. Poisson regression was used to assess the association between sociodemographic characteristics and the total number of non-communicable diseases (NCDs), while multivariate logistic regression and quantile regression analysis was used to estimate the associations between multimorbidity, health service use and OOPE. Results Overall, 20.8% of total participants had two or more NCDs in 2014/2015. The number of NCDs was associated with higher healthcare utilisation (coefficient 0.11, 95% CI 0.07–0.14 for outpatient care and coefficient 0.09 (95% CI 0.02–0.16 for inpatient care) and higher four-weekly OOPE (coefficient 27.0, 95% CI 11.4–42.7). The quantile regression results indicated that the marginal effect of having three or more NCDs on the absolute amount of four-weekly OOPE was smaller for the lower percentiles (at the 25th percentile, coefficient 1.0, 95% CI 0.5–1.5) but more pronounced for the higher percentile of out-of-pocket spending distribution (at the 90th percentile, coefficient 31.0, 95% CI 15.9–46.2). Conclusion Multimorbidity is positively correlated with health service utilisation and OOPE and has a significant effect, especially among those in the upper tail of the utilisation/costs distribution. Health financing strategies are urgently required to meet the needs of patients with multimorbidity, particularly for vulnerable groups that have a higher level of health care utilisation.

ObjectiveMultimorbidity is a growing challenge in low-income and middle-income countries. This study investigates the effects of multimorbidity on annual medical costs and the out-of-pocket expenditures (OOPEs) along the cost distribution.MethodsData from the nationally representative China Health and Retirement Longitudinal Study (CHARLS 2015), including 10 592 participants aged ≥45 years and 15 physical and mental chronic diseases, were used for this nationally representative cross-sectional study. Quantile multivariable regressions were employed to understand variations in the association of chronic disease multimorbidity with medical cost and OOPE.ResultsOverall, 69.5% of middle-aged and elderly Chinese had multimorbidity in 2015. Increased number of chronic diseases was significantly associated with greater health expenditures across every cost quantile groups. The effect of chronic diseases on total medical cost was found to be larger among the upper tail than those in the lower tail of the cost distributions (coefficients 12, 95% CI 6 to 17 for 10th percentile; coefficients 296, 95% CI 71 to 522 for 90th percentile). Annual OOPE also increased with chronic diseases from the 10th percentile to the 90th percentile. Multimorbidity had larger effects on OOPE and was more pronounced at the upper tail of the health expenditure distribution (regression coefficients of 8 and 84 at the 10th percentile and 75th percentile, respectively).ConclusionMultimorbidity is associated with escalating healthcare costs in China. Further research is required to understand the impact of multimorbidity across different population groups.

Background The co-occurrence of mental and physical chronic conditions (mental-physical multimorbidity) is a growing and largely unaddressed challenge for health systems and wider economies in low-and middle-income countries. This study investigated the independent and combined (additive or synergistic) effects of mental and physical chronic conditions on disability, work productivity, and social participation in China. Methods Panel data study design utilised two waves of the China Health and Retirement Longitudinal Study (2011, 2015), including 5616 participants aged ≥45 years, 12 physical chronic conditions and depression. We used a panel data approach of random-effects regression models to assess the relationships between mental-physical multimorbidity and outcomes. Results After adjusting for socio-economic and demographic factors, an increased number of physical chronic conditions was independently associated with a higher likelihood of disability (Adjusted odds ratio (AOR) = 1.39; 95% CI: 1.33, 1.45), early retirement (AOR = 1.37 [1.26, 1.49]) and increased sick leave days (1.25 days [1.16, 1.35]). Depression was independently associated with disability (AOR = 3.78 [3.30, 4.34]), increased sick leave days (2.18 days [1.72, 2.77]) and a lower likelihood of social participation (AOR = 0.57 [0.47, 0.70]), but not with early retirement (AOR = 1.24 [0.97, 1.58]). There were small and statistically insignificant interactions between physical chronic conditions and mental health on disability, work productivity and social participation, suggesting an additive effect of mental-physical multimorbidity on productivity loss. Conclusion Mental-physical multimorbidity poses substantial negative health and economic effects on individuals, health systems, and societies. More research that addresses the challenges of mental-physical multimorbidity is needed to inform the development of interventions that can be applied to the workplace and the wider community in China.

Objective: Schizophrenia, a complex psychiatric disorder, is often associated with cognitive, neurological and neuroimaging abnormalities. The processes underlying these abnormalities, and whether a subset of people with schizophrenia have a neuroprogressive or neurodegenerative component to schizophrenia, remain largely unknown. Examining fluid biomarkers of diverse types of neuronal damage could increase our understanding of these processes, as well as potentially provide clinically useful biomarkers, for example with assisting with differentiation from progressive neurodegenerative disorders such as Alzheimer and frontotemporal dementias. Methods: This study measured plasma neurofilament light chain protein (NfL) using ultrasensitive Simoa technology, to investigate the degree of neuronal injury in a well-characterised cohort of people with treatment-resistant schizophrenia on clozapine ( n = 82), compared to first-degree relatives (an at-risk group, n = 37), people with schizophrenia not treated with clozapine ( n = 13), and age- and sex-matched controls ( n = 59). Results: We found no differences in NfL levels between treatment-resistant schizophrenia (mean NfL, M = 6.3 pg/mL, 95% confidence interval: [5.5, 7.2]), first-degree relatives (siblings, M = 6.7 pg/mL, 95% confidence interval: [5.2, 8.2]; parents, M after adjusting for age = 6.7 pg/mL, 95% confidence interval: [4.7, 8.8]), controls (M = 5.8 pg/mL, 95% confidence interval: [5.3, 6.3]) and not treated with clozapine (M = 4.9 pg/mL, 95% confidence interval: [4.0, 5.8]). Exploratory, hypothesis-generating analyses found weak correlations in treatment-resistant schizophrenia, between NfL and clozapine levels (Spearman’s r = 0.258, 95% confidence interval: [0.034, 0.457]), dyslipidaemia ( r = 0.280, 95% confidence interval: [0.064, 0.470]) and a negative correlation with weight ( r = −0.305, 95% confidence interval: [−0.504, −0.076]). Conclusion: Treatment-resistant schizophrenia does not appear to be associated with neuronal, particularly axonal degeneration. Further studies are warranted to investigate the utility of NfL to differentiate treatment-resistant schizophrenia from neurodegenerative disorders such as behavioural variant frontotemporal dementia, and to explore NfL in other stages of schizophrenia such as the prodome and first episode.