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      Prevalence of multimorbidity in community settings: A systematic review and meta-analysis of observational studies

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          Abstract

          Background:

          With ageing world populations, multimorbidity (presence of two or more chronic diseases in the same individual) becomes a major concern in public health. Although multimorbidity is associated with age, its prevalence varies. This systematic review aimed to summarise and meta-analyse the prevalence of multimorbidity in high, low- and middle-income countries (HICs and LMICs).

          Methods:

          Studies were identified by searching electronic databases (Medline, Embase, PsycINFO, Global Health, Web of Science and Cochrane Library). The term ‘multimorbidity’ and its various spellings were used, alongside ‘prevalence’ or ‘epidemiology’. Quality assessment employed the Newcastle-Ottawa scale. Overall and stratified analyses according to multimorbidity operational definitions, HICs/LMICs status, gender and age were performed. A random-effects model for meta-analysis was used.

          Results:

          Seventy community-based studies (conducted in 18 HICs and 31 LMICs) were included in the final sample. Sample sizes ranged from 264 to 162,464. The overall pooled prevalence of multimorbidity was 33.1% (95% confidence interval (CI): 30.0–36.3%). There was a considerable difference in the pooled estimates between HICs and LMICs, with prevalence being 37.9% (95% CI: 32.5–43.4%) and 29.7% (26.4–33.0%), respectively. Heterogeneity across studies was high for both overall and stratified analyses ( I 2 > 99%). A sensitivity analysis showed that none of the reviewed studies skewed the overall pooled estimates.

          Conclusion:

          A large proportion of the global population, especially those aged 65+, is affected by multimorbidity. To allow accurate estimations of disease burden, and effective disease management and resources distribution, a standardised operationalisation of multimorbidity is needed.

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          Most cited references78

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          Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice

          Objectives Prevalence estimates of multimorbidity vary widely due to inconsistent definitions and measurement methods. This study examines the independent effects on prevalence estimates of how ‘disease entity’ is defined—as a single chronic condition or chapters/domains in the International Classification of Primary Care (V.2; ICPC-2), International Classification of Disease (10th revision; ICD-10) or the Cumulative Illness Rating Scale (CIRS), the number of disease entities required for multimorbidity, and the number of chronic conditions studied. Design National prospective cross-sectional study. Setting Australian general practice. Participants 8707 random consenting deidentified patient encounters with 290 randomly selected general practitioners. Main outcome measures Prevalence estimates of multimorbidity using different definitions. Results Data classified to ICPC-2 chapters, ICD-10 chapters or CIRS domains produce similar multimorbidity prevalence estimates. When multimorbidity was defined as two or more (2+) disease entities: counting individual chronic conditions and groups of chronic conditions produced similar estimates; the 12 most prevalent chronic conditions identified about 80% of those identified using all chronic conditions. When multimorbidity was defined as 3+ disease entities: counting individual chronic conditions produced significantly higher estimates than counting groups of chronic conditions; the 12 most prevalent chronic conditions identified only two-thirds of patients identified using all chronic conditions. Conclusions Multimorbidity defined as 2+ disease entities can be measured using different definitions of disease entity with as few as 12 prevalent chronic conditions, but lacks specificity to be useful, especially in older people. Multimorbidity, defined as 3+, requires more measurement conformity and inclusion of all chronic conditions, but provides greater specificity than the 2+ definition. The proposed concept of “complex multimorbidity”, the co-occurrence of three or more chronic conditions affecting three or more different body systems within one person without defining an index chronic condition, may be useful in identifying high-need individuals.
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            Socioeconomic status and multimorbidity: a systematic review and meta-analysis

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              Multimorbidity and the inequalities of global ageing: a cross-sectional study of 28 countries using the World Health Surveys

              Background Multimorbidity defined as the “the coexistence of two or more chronic diseases” in one individual, is increasing in prevalence globally. The aim of this study is to compare the prevalence of multimorbidity across low and middle-income countries (LMICs), and to investigate patterns by age and education, as a proxy for socio-economic status (SES). Methods Chronic disease data from 28 countries of the World Health Survey (2003) were extracted and inter-country socio-economic differences were examined by gross domestic product (GDP). Regression analyses were applied to examine associations of education with multimorbidity by region adjusted for age and sex distributions. Results The mean world standardized multimorbidity prevalence for LMICs was 7.8 % (95 % CI, 7.79 % - 7.83 %). In all countries, multimorbidity increased significantly with age. A positive but non–linear relationship was found between country GDP and multimorbidity prevalence. Trend analyses of multimorbidity by education suggest that there are intergenerational differences, with a more inverse education gradient for younger adults compared to older adults. Higher education was significantly associated with a decreased risk of multimorbidity in the all-region analyses. Conclusions Multimorbidity is a global phenomenon, not just affecting older adults in HICs. Policy makers worldwide need to address these health inequalities, and support the complex service needs of a growing multimorbid population. Electronic supplementary material The online version of this article (doi:10.1186/s12889-015-2008-7) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                J Comorb
                J Comorb
                COB
                spcob
                Journal of Comorbidity
                SAGE Publications (Sage UK: London, England )
                2235-042X
                22 August 2019
                Jan-Dec 2019
                : 9
                : 2235042X19870934
                Affiliations
                [1-2235042X19870934]Institute of Psychiatry, Psychology and Neuroscience, Health Service and Population Research Department, King’s College London, London, UK
                Author notes
                [*]Hai Nguyen, Institute of Psychiatry, Psychology and Neuroscience, Health Service and Population Research Department, King’s College London, PO36, David Goldberg Centre, De Crespigny Park, London SE5 8AF, UK. Email: hai.nguyen@ 123456kcl.ac.uk
                Author information
                https://orcid.org/0000-0003-2171-1955
                Article
                10.1177_2235042X19870934
                10.1177/2235042X19870934
                6710708
                31489279
                7477da0d-d1f2-496b-bafe-7edc6c49fe0e
                © The Author(s) 2019

                This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 7 March 2019
                : 30 July 2019
                Funding
                Funded by: The European Union's Horizon 2020 Research and Innovation Programme;
                Award ID: 635316
                Categories
                Review Article
                Custom metadata
                January-December 2019

                multimorbidity,prevalence,hics,lmics
                multimorbidity, prevalence, hics, lmics

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