Chronic diseases contribute a large share of disease burden in low- and middle-income countries (LMICs). Chronic diseases have a tendency to occur simultaneously and where there are two or more such conditions, this is termed as ‘multimorbidity’. Multimorbidity is associated with adverse health outcomes, but limited research has been undertaken in LMICs. Therefore, this study examines the prevalence and correlates of multimorbidity as well as the associations between multimorbidity and self-rated health, activities of daily living (ADLs), quality of life, and depression across six LMICs. Data was obtained from the WHO’s Study on global AGEing and adult health (SAGE) Wave-1 (2007/10). This was a cross-sectional population based survey performed in LMICs, namely China, Ghana, India, Mexico, Russia, and South Africa, including 42,236 adults aged 18 years and older. Multimorbidity was measured as the simultaneous presence of two or more of eight chronic conditions including angina pectoris, arthritis, asthma, chronic lung disease, diabetes mellitus, hypertension, stroke, and vision impairment. Associations with four health outcomes were examined, namely ADL limitation, self-rated health, depression, and a quality of life index. Random-intercept multilevel regression models were used on pooled data from the six countries. The prevalence of morbidity and multimorbidity was 54.2 % and 21.9 %, respectively, in the pooled sample of six countries. Russia had the highest prevalence of multimorbidity (34.7 %) whereas China had the lowest (20.3 %). The likelihood of multimorbidity was higher in older age groups and was lower in those with higher socioeconomic status. In the pooled sample, the prevalence of 1+ ADL limitation was 14 %, depression 5.7 %, self-rated poor health 11.6 %, and mean quality of life score was 54.4. Substantial cross-country variations were seen in the four health outcome measures. The prevalence of 1+ ADL limitation, poor self-rated health, and depression increased whereas quality of life declined markedly with an increase in number of diseases. Findings highlight the challenge of multimorbidity in LMICs, particularly among the lower socioeconomic groups, and the pressing need for reorientation of health care resources considering the distribution of multimorbidity and its adverse effect on health outcomes.

Objective To systematically review the studies of prevalence, patterns and consequences of multimorbidity reported from South Asia. Design Systematic review. Setting South Asia. Data sources Articles were retrieved from two electronic databases (PubMed and Embase) and from the relevant references lists. Methodical data extraction according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines was followed. English-language studies published between 2000 and March 2015 were included. Eligibility criteria Studies addressing prevalence, consequences and patterns of multimorbidity in South Asia. Articles documenting presence of two or more chronic conditions were included in the review. The quality and risk of bias were assessed using STROBE criteria. Data selection Two reviewers independently assessed studies for eligibility, extracted data and assessed study quality. Due to heterogeneity in methodologies among reported studies, only narrative synthesis of the results was carried out. Results Of 11 132, 61 abstracts were selected and 13 were included for final data synthesis. The number of health conditions analysed per study varied from 7 to 22, with prevalence of multimorbidity from 4.5% to 83%. The leading chronic conditions were hypertension, arthritis, diabetes, cardiac problems and skin diseases. The most frequently reported outcomes were increased healthcare utilisation, lowered physical functioning and quality of life, and psychological distress. Conclusions Our study, a comprehensive mapping of multimorbidity research in South Asia, reveals the insufficient volume of work carried out in this domain. The published studies are inadequate to provide an indication of the magnitude of multimorbidity in these countries. Research into clinical and epidemiological aspects of multimorbidity is warranted to build up scientific evidence in this geographic region. The wide heterogeneity observed in the present review calls for greater methodological rigour while conducting these epidemiological studies. Trial registration number CRD42013005456.

Non communicable disease (NCD) multimorbidity is increasingly becoming common in high income settings but little is known about its epidemiology and associated impacts on citizens and health systems in low and middle-income countries (LMICs). We aim to examine the socio-demographic distribution of NCD multimorbidity (≥2 diseases) and its implications for health care utilization and out-of-pocket expenditure (OOPE) in India. We analyzed cross-sectional nationally representative data from the World Health Organisaion Study on Global Ageing and Adult Health (WHO-SAGE), conducted in India during 2007. Multiple logistic regression was used to determine socio-demographic predictors of self-reported multimorbidity. A two part model was used to assess the relationship between number of NCDs and health care utilization including OOPE. 28.5% of the sample population had at least one NCD and 8.9% had NCD multimorbidity. The prevalence of multimorbidity increased from 1.3% in 18–29 year olds to 30.6% in those aged 70 years and above. Mean outpatient visits in the preceding 12 months increased from 2.2 to 6.2 and the percentage reporting an overnight hospital stay in the past 3 years increased from 9% to 29% in those with no NCD and ≥2 NCDs respectively (p <0.001). OOPE incurred during the last outpatient visit increased from INR 272.1 (95% CI = 249.0-295.2) in respondents with no NCDs to INR 454.1 (95% CI = 407.8-500.4) in respondents with ≥2 NCDs. However, we did not find an increase in OOPE during the last inpatient visit with number of NCDs (7865.9 INR for those with zero NCDs compared with 7301.3 for those with ≥2 NCDs). For both outpatient and inpatient OOPE, medicine constitutes the largest proportion of spending (70.7% for outpatient, 53.6% for inpatient visit), followed by spending for health care provider (14.0% for outpatient, 12.2% for inpatient visit). NCD multimorbidity is common in the Indian adult population and is associated with substantially higher healthcare utilization and OOPE. Strategies to address the growing burden of NCDs in LMICs should include efforts to improve the management of patients with multimorbidity and reduce associated financial burden to individuals and households.

Background & objectives: The National Prevalence Survey of India (2019-2021) estimated 31 per cent tuberculosis infection (TBI) burden among individuals above 15 years of age. However, so far little is known about the TBI burden among the different risk groups in India. Thus, this systematic review and meta-analysis, aimed to estimate the prevalence of TBI in India based on geographies, sociodemographic profile, and risk groups. Methods: To identify the prevalence of TBI in India, data sources such as MEDLINE, EMBASE, CINAHL, and Scopus were searched for articles reporting data between 2013-2022, irrespective of the language and study setting. TBI data were extracted from 77 publications and pooled prevalence was estimated from the 15 community-based cohort studies. Articles were reviewed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines and were sourced using a predefined search strategy from different databases. Results: Out of 10,521 records, 77 studies (46 cross-sectional and 31 cohort studies) were included. The pooled TBI prevalence for India based on the community-based cohort studies was estimated as 41 per cent [95% confidence interval (CI) 29.5-52.6%] irrespective of the risk of acquiring it, while the estimation was 36 per cent (95% CI 28-45%) prevalence observed among the general population excluding high-risk groups. Regions with high active TB burden were found to have a high TBI prevalence such as Delhi and Tamil Nadu. An increasing trend of TBI was observed with increasing age in India. Interpretation & conclusions: This review demonstrated a high prevalence of TBI in India. The burden of TBI was commensurate with active TB prevalence suggesting possible conversion of TBI to active TB. A high burden was recorded among people residing in the northern and southern regions of the country. Such local epidemiologic variation need to be considered to reprioritize and implement-tailored strategies for managing TBI in India.

Multimorbidity, the coexistence of two or more chronic conditions is increasingly prevalent in primary care populations. Despite reports on its adverse impact on health outcomes, functioning and well-being, it’s association with quality of life is not well known in low and middle income countries. We assessed the health-related quality of life (HRQoL) of primary care patients with multimorbidity and identified the influencing factors. This cross-sectional study was done across 20 public and 20 private primary care facilities in Odisha, India. Data were collected from 1649 adult out-patients using a structured multimorbidity assessment questionnaire for primary care (MAQ-PC). HRQoL was assessed by the 12-item short-form health survey (SF-12). Both physical (PCS) and mental components scores (MCS) were calculated. Multiple regression analysis was performed to determine the association of HRQoL with socio-demographics, number, severity and typology of chronic conditions. Around 28.3% [95% CI: 25.9–30.7] of patients had multimorbidity. Mean physical component scope (PCS) and mental component score (MCS) of QoL in the study population was 43.56 [95% CI: 43.26–43.86] and 43.69 [95% CI: 43.22–44.16], respectively. Patients with multimorbidity reported poorer mean PCS [43.23, 95% CI: 42.62–43.84] and MCS [41.58, 95% CI: 40.74–42.43] compared to those without. After adjusting for other variables, morbidity severity burden score was found to be negatively associated with MCS [adjusted coefficient: -0.24, 95% CI − 0.41 to − 0.08], whereas no significant association was seen with PCS. Hypertension and diabetes with arthritis and acid peptic diseases were found to be negatively related with MCS. Within multimorbidity, lower education was inversely associated with mental QoL and positively associated with physical QoL score after adjusting for other variables. Our findings demonstrate the diverse negative effects of multimorbidity on HRQoL and reveal that apart from count of chronic conditions, severity and pattern also influence HRQoL negatively. Health care providers should consider severity as an outcome measure to improve QoL especially in individuals with physical multimorbidity. Given the differences observed between age groups, it is important to identify specific care needs for each group. Musculoskeletal clusters need prioritised attention while designing clinical guidelines for multimorbidity.