Evidence map›Paper›PMID 35978384›Full record

ArticleBMC research notes2022

A systematic method for comparing multimorbidity in national surveys.

Rifqah Abeeda Roomaney, Brian van Wyk, Victoria Pillay-van Wyk

Abstract read
In one paragraph

Article in BMC research notes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Multimorbidity in South Africa: Is the health system ready?Journal of multimorbidity and comorbidity
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Rifqah Abeeda RoomaneyBurden of Disease Research Unit, South African Medical Research Council, Francie van Zyl Drive, Cape Town, South Africa. Rifqah.roomaney@mrc.ac.za.ORCID http://orcid.org/0000-0003-3267-8484
Brian van WykSchool of Public Health, University of the Western Cape, Robert Sobukwe Drive, Bellville, Cape Town, South Africa.
Victoria Pillay-van WykBurden of Disease Research Unit, South African Medical Research Council, Francie van Zyl Drive, Cape Town, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDue to gaps in the literature, we developed a systematic method to assess multimorbidity using national surveys. The objectives of this study were thus to identify methods used to define and measure multimorbidity, to create a pre-defined list of disease conditions, to identify potential national surveys to include, to select disease conditions for each survey, and to analyse and compare the survey findings.

resultsWe used the count method to define multimorbidity. We created a pre-defined list of disease conditions by examining international literature and using local data on the burden of disease. We assessed national surveys, reporting on more than one disease condition in people 15 years and older, for inclusion. For each survey, the prevalence of multimorbidity was calculated, the disease patterns among the multimorbid population were assessed using a latent class analysis and logistic regression was used to identify sociodemographic and behavioural factors associated with multimorbidity. The prevalence of multimorbidity varied for each survey from 2.7 to 20.7%. We used a systematic and transparent method to interrogate multimorbidity in national surveys. While the prevalence in each survey differs, they collectively indicate that multimorbidity increases in older age groups and tends to be higher among women.

Indexed as

Health ServicesMultimorbidityAgedChronic DiseaseCross-Sectional StudiesFemaleHumansPrevalenceDisease patternsLatent class analysisMultimorbidityPrevalenceSouth Africa

Identifiers

PMID35978384
PMCPMC9387001

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.