ArticleBMC research notes2022
A systematic method for comparing multimorbidity in national surveys.
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.
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.
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.
Who cites it
1 citing paper in PubMed.
- Multimorbidity in South Africa: Is the health system ready?Journal of multimorbidity and comorbidityArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
Registered trials
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.