ObjectivesTo identify and summarise existing indices for measuring multimorbidity beyond disease counts, to establish which indices include mental health comorbidities or outcomes, and to develop recommendations based on applicability, performance, and usage. DesignSystematic review. Data sOurcesSeven medical research databases (Medline, Web of Science Core Collection, Cochrane Library, Embase, PsycINFO, Scopus, and CINAHL Plus) from inception to October 2018 and bibliographies and citations of relevant papers. Searches were limited to English language publications. eligibility criteria fOr stuDy selectiOn Original articles describing a new multimorbidity index including more information than disease counts and not focusing on comorbidity associated with one specific disease. Studies were of adults based in the community or at population level. resultsAmong 7128 search results, 5560 unique titles were identified. After screening against eligibility criteria the review finally included 35 papers. As index components, 25 indices used conditions (weighted or in combination with other parameters), five used diagnostic categories, four used drug use, and one used physiological measures. Predicted outcomes included mortality (18 indices), healthcare use or costs (13), hospital admission (13), and health related quality of life (7). 29 indices considered some aspect of mental health, with most including it as a comorbidity. 12 indices are recommended for use.cOnclusiOns 35 multimorbidity indices are available, with differing components and outcomes. Researchers and clinicians should examine existing indices for suitability before creating new ones.systematic review registratiOn PROSPERO CRD42017074211. cite this as: BMJ 2020;368:m127 http://dx.
Background: There is increasing international concern about the persistent under-representation of ethnic minority patients in research.
Background Identification of those who are most at risk of developing specific patterns of disease across different populations is required for directing public health policy. Here, we contrast prevalence and patterns of cross-national disease incidence, co-occurrence and related risk factors across population samples from the U.S., Canada, England and Ireland. Methods Participants (n = 62,111) were drawn from the US Health and Retirement Study (n = 10,858); the Canadian Longitudinal Study on Ageing (n = 36,647); the English Longitudinal Study of Ageing (n = 7938) and The Irish Longitudinal Study on Ageing (n = 6668). Self-reported lifetime prevalence of 10 medical conditions, predominant clusters of multimorbidity and their specific risk factors were compared across countries using latent class analysis. Results The U.S. had significantly higher prevalence of multimorbid disease patterns and nearly all diseases when compared to the three other countries, even after adjusting for age, sex, BMI, income, employment status, education, alcohol consumption and smoking history. For the U.S. the most at-risk group were younger on average compared to Canada, England and Ireland. Socioeconomic gradients for specific disease combinations were more pronounced for the U.S., Canada and England than they were for Ireland. The rates of obesity trends over the last 50 years align with the prevalence of eight of the 10 diseases examined. While patterns of disease clusters and the risk factors related to each of the disease clusters were similar, the probabilities of the diseases within each cluster differed across countries. Conclusions This information can be used to better understand the complex nature of multimorbidity and identify appropriate prevention and management strategies for treating multimorbidity across countries.
Background The Lothian Birth Cohort 1936 (LBC1936) is a longitudinal study of ageing with well-characterised assessments, but until now, it has relied on self-report or proxies for dementia such as cognitive tests. Our aims were twofold: a) to describe a framework for identifying dementia in a cohort study. b) to report the age-specific incidence and prevalence of all-cause dementia and dementia subtypes in 865 individuals in the LBC1936. Methods Electronic Health Records (EHR) of all participants were reviewed, and relevant information was extracted to form case vignettes for everyone with any record of cognitive dysfunction. The EHR data sources include hospital and clinic letters, general practitioner and hospital referrals, prescribed medications, imaging and laboratory results. Death certificate data were obtained separately. Clinician assessments were performed when there was concern about a participant's cognition. A diagnosis of probable dementia, possible dementia, or no dementia was agreed upon by a consensus diagnostic review board, comprised of a multidisciplinary team of clinical dementia experts who reviewed case vignettes and clinician assessment letters. For those with probable dementia, a subtype was also determined, where possible. We compared the agreement between our newly ascertained dementia diagnoses with the existing self-reported dementia diagnoses. Results Self-reported dementia diagnoses were positive in only 17.8% of ascertained dementia diagnoses. The EHR review identified 163/865 (18.8%) individuals as having cognitive dysfunction. At the consensus diagnostic review board, 118/163 were diagnosed with probable all-cause dementia, a prevalence of 13.6%. Age-specific dementia prevalence increased with age from 0.8% (65–74.9 years) to 9.93% (85–89.9 years). Prevalence rates for women were higher in nearly all age groups. The most common subtype was dementia due to Alzheimer disease (49.2%), followed by mixed Alzheimer and cerebrovascular disease (17.0%), dementia of unknown or unspecified cause (16.1%), and dementia due to vascular disease (8.5%). Conclusions We present a robust systematic framework and guide for other cohort teams wanting to ascertain dementia diagnoses. The newly ascertained dementia diagnosis provides vital data for further analyses of LBC1936 to allow exploration of lifecourse predictors of dementia.
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