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Introduction: Using nationally representative survey data from China and India, this study examined 1) the distribution and patterns of multimorbidity in relation to socioeconomic status 2) association between multimorbidity and out-of-pocket expenditure (OOPE) for medicines by socioeconomic groups. Methods: Secondary data analysis of adult population aged 45 years and older from WHO Study on Global Ageing and Adult Health (SAGE) India 2015 (n=7397) and China Health and Retirement Longitudinal Study (CHARLS) 2015 (n=11570). Log-linear, two-parts, zero-inflated and quantile regression models were performed to assess the association between multimorbidity and OOPE for medicines in both countries. Quantile regression was adopted to assess the observed relationship across OOPE distributions. Results: Based on 14 (11 self-reported) and 9 (8 self-reported) long-term conditions in the CHARLS and SAGE datasets respectively, the prevalence of multimorbidity in the adult population aged 45 and older was found to be 63.4% in China and 42.2% in India. Of those with any long-term health condition, 38.6% in China and 20.9% in India had complex multimorbidity. Multimorbidity was significantly associated with higher OOPE for medicines in both countries (P

Nikoline Lund Jensen,1,2 Henrik Søndergaard Pedersen,1 Mogens Vestergaard,1,2 Stewart W Mercer,3 Charlotte Glümer,4 Anders Prior,1,2 1Research Unit for General Practice, 2Section for General Medical Practice, Department of Public Health, Aarhus University, Aarhus, Denmark; 3General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow, Scotland; 4Research Centre for Prevention and Health, The Capital Region of Denmark, Glostrup, Denmark Objective: Multimorbidity (MM) is more prevalent among people of lower socioeconomic status (SES), and both MM and SES are associated with higher mortality rates. However, little is known about the relationship between SES, MM, and mortality. This study investigates the association between educational level and mortality, and to what extent MM modifies this association. Methods: We followed 239,547 individuals invited to participate in the Danish National Health Survey 2010 (mean follow-up time: 3.8 years). MM was assessed by using information on drug prescriptions and diagnoses for 39 long-term conditions. Data on educational level were provided by Statistics Denmark. Date of death was obtained from the Civil Registration System. Information on lifestyle factors and quality of life was collected from the survey. The main outcomes were overall and premature mortality (death before the age of 75). Results: Of a total of 12,480 deaths, 6,607 (9.5%) were of people with low educational level (LEL) and 1,272 (2.3%) were of people with high educational level (HEL). The mortality rate was higher among people with LEL compared with HEL in groups of people with 0–1 disease (hazard ratio: 2.26, 95% confidence interval: 2.00–2.55) and ≥4 diseases (hazard ratio: 1.14, 95% confidence interval: 1.04–1.24), respectively (adjusted model). The absolute number of deaths was six times higher among people with LEL than those with HEL in those with ≥4 diseases. The 1-year cumulative mortality proportions for overall death in those with ≥4 diseases was 5.59% for people with HEL versus 7.27% for people with LEL, and 1-year cumulative mortality proportions for premature death was 2.93% for people with HEL versus 4.04% for people with LEL. Adjusting for potential mediating factors such as lifestyle and quality of life eliminated the statistical association between educational level and mortality in people with MM. Conclusion: Our study suggests that LEL is associated with higher overall and premature mortality and that the association is affected by MM, lifestyle factors, and quality of life. Keywords: multimorbidity, socioeconomic status, social epidemiology, inequality in health, mortality, population-based cohort study

Background: Knowledge about prevalent and deadly combinations of multimorbidity is needed. Objective: To determine the nationwide prevalence of multimorbidity and estimate mortality for the most prevalent combinations of one to five diagnosis groups. Furthermore, to assess the excess mortality of the combination of two groups compared to the product of mortality associated with the single groups. Design: A prospective cohort study using Danish registries and including 3.986.209 people aged ≥18 years on 1 January, 2000. Multimorbidity was defined as having diagnoses from at least 2 of 10 diagnosis groups: lung, musculoskeletal, endocrine, mental, cancer, neurological, gastrointestinal, cardiovascular, kidney, and sensory organs. Logistic regression (odds ratios, ORs) and ratio of ORs (ROR) were used to study mortality and excess mortality. Results: Prevalence of multimorbidity was 7.1% in the Danish population. The most prevalent combination was the musculoskeletal–cardiovascular (0.4%), which had double the mortality (OR, 2.03) compared to persons not belonging to any of the diagnosis groups but showed no excess mortality (ROR, 0.97). The neurological–cancer combination had the highest mortality (OR, 6.35), was less prevalent (0.07%), and had no excess mortality (ROR, 0.94). Cardiovascular–lung was moderately prevalent (0.2%), had high mortality (OR, 5.75), and had excess mortality (ROR, 1.18). Endocrine–kidney had high excess mortality (ROR, 1.81) and cancer–mental had low excess mortality (ROR, 0.66). Mortality increased with the number of groups. Conclusions: All combinations had increased mortality risk with some of them having up to a six-fold increased risk. Mortality increased with the number of diagnosis groups. Most combinations did not increase mortality above that expected, that is, were additive rather than synergistic.