cad a22 4500 467973830 20181103044556.0 cr unu---uuuuu 170328s2017 xx s 000 0 eng 10.5167/uzh-136438 doi 10.1186/s12963-017-0126-4 doi (ZORA)oai:www.zora.uzh.ch:136438 610 ddc 28270157 pmid Evidence-based design recommendations for prevalence studies on multimorbidity: improving comparability of estimates [Elektronische Daten] [Barbara M Holzer, Klarissa Siebenhuener, Matthias Bopp, Christoph E Minder] openAccess eu-repo Background: In aging populations, multimorbidity causes a disease burden of growing importance and cost. However, estimates of the prevalence of multimorbidity (prevMM) vary widely across studies, impeding valid comparisons and interpretation of differences. With this study we pursued two research objectives: (1) to identify a set of study design and demographic factors related to prevMM, and (2) based on (1), to formulate design recommendations for future studies with improved comparability of prevalence estimates. Methods: Study data were obtained through systematic review of the literature. UsingPubMed/MEDLINE, Embase, CINAHL, Web of Science, BIOSIS, and Google Scholar, we looked for articles with the terms "multimorbidity,” "comorbidity,” "polymorbidity,” and variations of these published in English or German in the years 1990 to 2011. We selected quantitative studies of the prevalence of multimorbidity (two or more chronic medical conditions) with a minimum sample size of 50 and a study population with a majority of Caucasians. Our database consisted of prevalence estimates in 108 age groups taken from 45 studies. To assess the effects of study design variables, we used meta regression models. Results: In 58% of the studies, there was only one age group, i.e., no stratification by age. The number of persons per age group ranged from 136 to 5.6 million. Our analyses identified the following variables as highly significant: "mean age,” "number of age groups”, and "data reporting quality” (all p < 0.0001). "Setting,” "disease classification,” and "number of diseases in the classification” were significant (0.01 < p ≤ 0.03), and "data collection period” and "data source” were non-significant. A separate analysis showed that prevMM was significantly higher in women than men (sign test, p = 0.0015). Conclusions: Comparable prevalence estimates are urgently needed for realistic description of the magnitude of the problem of multimorbidity. Based on the results of our analyses of variables affecting prevMM, we make some design recommendations. Our suggestions were guided by a pragmatic approach and aimed at facilitating the implementation of a uniform methodology. This should aid progress towards a more uniform operationalization of multimorbidity. Keywords: Age, Gender, Study design variables, Multiple chronic conditions, Systematic review Clinic and Policlinic for Internal Medicine zora Epidemiology, Biostatistics and Prevention Institute (EBPI) zora Center of Competence Multimorbidity zora Dynamics of Healthy Aging zora Holzer Barbara M. joint author Siebenhuener Klarissa joint author Bopp Matthias joint author Minder Christoph E. joint author Population Health Metrics 15(1):9 https://www.zora.uzh.ch/id/eprint/136438/1/Holzer_Evidence-based_design_recommendations_in_MM_2017.pdf text/html WWW-Backlink auf das Repository 1 Journal Article PeerReviewed zora ZORA 856 40 https://www.zora.uzh.ch/id/eprint/136438/1/Holzer_Evidence-based_design_recommendations_in_MM_2017.pdf text/html WWW-Backlink auf das Repository ZORA 700 1- Holzer Barbara M. joint author ZORA 700 1- Siebenhuener Klarissa joint author ZORA 700 1- Bopp Matthias joint author ZORA 700 1- Minder Christoph E. joint author ZORA 773 0- Population Health Metrics 15(1):9 BK010053 XK010053 XK010000 ZORA ZORA ZORA Journal Article openAccess