Dataset Information

Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review.

ABSTRACT:

Background

Multimorbidity presents a key challenge to healthcare systems globally. However, heterogeneity in the definition of multimorbidity and design of epidemiological studies results in difficulty in comparing multimorbidity studies. This scoping review aimed to describe multimorbidity prevalence in studies using large datasets and report the differences in multimorbidity definition and study design.

Methods

We conducted a systematic search of MEDLINE, EMBASE, and CINAHL databases to identify large epidemiological studies on multimorbidity. We used the Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension for Scoping Reviews (PRISMA-ScR) protocol for reporting the results.

Results

Twenty articles were identified. We found two key definitions of multimorbidity: at least two (MM2+) or at least three (MM3+) chronic conditions. The prevalence of multimorbidity MM2+ ranged from 15.3% to 93.1%, and 11.8% to 89.7% in MM3+. The number of chronic conditions used by the articles ranged from 15 to 147, which were organized into 21 body system categories. There were seventeen cross-sectional studies and three retrospective cohort studies, and four diagnosis coding systems were used.

Conclusions

We found a wide range in reported prevalence, definition, and conduct of multimorbidity studies. Obtaining consensus in these areas will facilitate better understanding of the magnitude and epidemiology of multimorbidity.

SUBMITTER: Chua YP

PROVIDER: S-EPMC7916224 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review.

Chua Ying Pin YP Xie Ying Y Lee Poay Sian Sabrina PSS Lee Eng Sing ES

International journal of environmental research and public health 20210209 4

<h4>Background</h4>Multimorbidity presents a key challenge to healthcare systems globally. However, heterogeneity in the definition of multimorbidity and design of epidemiological studies results in difficulty in comparing multimorbidity studies. This scoping review aimed to describe multimorbidity prevalence in studies using large datasets and report the differences in multimorbidity definition and study design.<h4>Methods</h4>We conducted a systematic search of MEDLINE, EMBASE, and CINAHL data ...[more]

PMID: 33572441

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Project description:Background:Non-communicable diseases (NCDs) cause a large and growing burden of morbidity and mortality in sub-Saharan Africa. Prospective cohort studies are key to study multiple risk factors and chronic diseases and are crucial to our understanding of the burden, aetiology and prognosis of NCDs in SSA. We aimed to identify the level of research output on NCDs and their risk factors collected by cohorts in SSA. Methods:We conducted a scoping review to map the extent of current NCDs research in SSA by identifying studies published after the year 2000 using prospectively collected cohort data on any of the six NCDs (cardiovascular diseases, diabetes, obesity, chronic kidney disease, chronic respiratory diseases, and cancers), ≥1 major risk factor (other than age and sex), set only within SSA, enrolled ≥500 participants, and ≥12 months of follow-up with ≥2 data collection points (or with plans to). We performed a systematic search of databases, a manual search of references lists from included articles and the INDEPTH network website, and study investigators from SSA were contacted for further articles. Results:We identified 30 cohort studies from the 101 included articles. Eighteen countries distributed in West, Central, East and Southern Africa, were represented. The majority (27%) set in South Africa. There were three studies including children, twenty with adults, and seven with both. 53% of cohorts were sampled in general populations, 47% in clinical populations, and 1 occupational cohort study. Hypertension (n = 23) was most commonly reported, followed by obesity (n = 16), diabetes (n = 15), CKD (n = 6), COPD (n = 2), cervical cancer (n = 3), and breast cancer (n = 1). The majority (n = 22) reported data on at least one demographic/environmental, lifestyle, or physiological risk factor but these data varied greatly. Conclusions:Most studies collected data on a combination of hypertension, diabetes, and obesity and few studies collected data on respiratory diseases and cancer. Although most collected data on different risk factors the methodologies varied greatly. Several methodological limitations were found including low recruitment rate, low retention rate, and lack of validated and standardized data collection. Our results could guide potential collaborations and maximize impact to improve our global understanding of NCDs (and their risk factors) in SSA and also to inform future research, as well as policies.

Project description:IntroductionMultimorbidity is a major concern in primary care. Nevertheless, evidence of prevalence and patterns of multimorbidity, and their determinants, are scarce. The aim of this study is to systematically review studies of the prevalence, patterns and determinants of multimorbidity in primary care.MethodsSystematic review of literature published between 1961 and 2013 and indexed in Ovid (CINAHL, PsychINFO, Medline and Embase) and Web of Knowledge. Studies were selected according to eligibility criteria of addressing prevalence, determinants, and patterns of multimorbidity and using a pretested proforma in primary care. The quality and risk of bias were assessed using STROBE criteria. Two researchers assessed the eligibility of studies for inclusion (Kappa=?0.86).ResultsWe identified 39 eligible publications describing studies that included a total of 70,057,611 patients in 12 countries. The number of health conditions analysed per study ranged from 5 to 335, with multimorbidity prevalence ranging from 12.9% to 95.1%. All studies observed a significant positive association between multimorbidity and age (odds ratio [OR], 1.26 to 227.46), and lower socioeconomic status (OR, 1.20 to 1.91). Positive associations with female gender and mental disorders were also observed. The most frequent patterns of multimorbidity included osteoarthritis together with cardiovascular and/or metabolic conditions.ConclusionsWell-established determinants of multimorbidity include age, lower socioeconomic status and gender. The most prevalent conditions shape the patterns of multimorbidity. However, the limitations of the current evidence base means that further and better designed studies are needed to inform policy, research and clinical practice, with the goal of improving health-related quality of life for patients with multimorbidity. Standardization of the definition and assessment of multimorbidity is essential in order to better understand this phenomenon, and is a necessary immediate step.

Project description:BackgroundMultimorbidity is common among general practice patients and increases a general practitioner's (GP's) workload. But the extent of multimorbidity may depend on its definition and whether a time delimiter is included in the definition or not.AimsThe aims of the study were (1) to compare practice prevalence rates yielded by different models of multimorbidity, (2) to determine how a time delimiter influences the prevalence rates and (3) to assess the effects of multimorbidity on the number of direct and indirect patient contacts as an indicator of doctors' workload.MethodsThis retrospective observational study used electronic medical records from 142 German general practices, covering 13 years from 1994 to 2007. The four models of multimorbidity ranged from a simple definition, requiring only two diseases, to an advanced definition requiring at least three chronic conditions. We also included a time delimiter for the definition of multimorbidity. Descriptive statistics, such as means and correlation coefficients, were applied.FindingsThe annual percentage of multimorbid primary care patients ranged between 84% (simple model) and 16% (advanced model) and between 74% and 13% if a time delimiter was included. Multimorbid patients had about twice as many contacts annually than the remainder. The number of contacts were different for each model, but the ratio remained similar. The number of contacts correlated moderately with patient age (r = 0.35). The correlation between age and multimorbidity increased from model to model up to 0.28 while the correlations between contacts and multimorbidity varied around 0.2 in all four models.ConclusionMultimorbidity seems to be less prevalent in primary care practices than usually estimated if advanced definitions of multimorbidity and a temporal delimiter are applied. Although multimorbidity increases in any model a doctor's workload, it is especially the older person with multiple chronic diseases who is a challenge for the GP.

Dataset Information

Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review.

Background

Methods

Results

Conclusions

Publications

Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review.

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