Prevalence and outcomes of multimorbidity in South Asia: a systematic review

Abstract

ObjectiveTo systematically review the studies of prevalence, patterns and consequences of multimorbidity reported from South Asia.DesignSystematic review.SettingSouth Asia.Data sourcesArticles 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 criteriaStudies 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 selectionTwo 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.ResultsOf 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.ConclusionsOur 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 numberCRD42013005456.

Multimorbidity Frameworks Impact Prevalence and Relationships with Patient‐Important Outcomes

“…23 Several factors influence prevalence estimates among studies of multimorbidity, including differing geographic settings, recruitment methods, and data collection methods, and the operational definition of multimorbidity. 9,18,[24][25][26][27] In this study, we found that including risk factors has the largest impact on prevalence estimates. Compared to most diseases and symptoms, risk factors are generally based on objective, rather than subjective, measures; are easy to quantify; and are often collected as part of routine examinations (eg, blood pressure and BMI).…”

Multimorbidity among middle‐aged and older persons in urban China: Prevalence, characteristics and health service utilization

“…A more recent cross‐country comparison showed a high prevalence of multimorbidity in older people, suggesting that levels in LMIC were gradually approaching those of high‐income countries . Pati et al found the prevalence of multimorbidity in South Asia varied widely, mostly lower than those reported in high‐income countries, but most studies were based on small samples . We searched both Chinese and English language databases for studies of multimorbidity prevalence in China and found extremely divergent reports; for example, the proportion of older people reported with more than one chronic disease ranged from 6.4% to 90.5% …”

“…4 Pati et al found the prevalence of multimorbidity in South Asia varied widely, mostly lower than those reported in high-income countries, but most studies were based on small samples. 11 We searched both Chinese and English language databases for studies of multimorbidity prevalence in China and found extremely divergent reports; for example, the proportion of older people reported with more than one chronic disease ranged from 6.4% to 90.5%. 8,[12][13][14][15] The prevalence of multimorbidity in LMIC seems lower than that in high-income countries; 2,4,10,11 however, in both LMIC and high-income countries, a negative relationship exists between socioeconomic status and the prevalence of multimorbidity.…”

Risk Factors for Chronic Diseases and Multimorbidity in a Primary Care Context of Central Argentina: A Web-Based Interactive and Cross-Sectional Study

“…Considering the health burden of chronic diseases for South America and the Caribbean, new research on multimorbidity in these areas of the world is warranted [29]. Although studies have shown that proper epidemiological characterization of multimorbidity is of great importance, it has been little explored, with few references in the literature for this region of the world.…”