Evidence map›Paper›PMID 25084825›Full record

ArticleBMC public health2014

Overcoming cut-off restrictions in multimorbidity prevalence estimates.

Barbara M Holzer, Klarissa Siebenhuener, Matthias Bopp, Christoph E Minder

Abstract read
In one paragraph

Article in BMC public health, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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  7. Beyond the grey tsunami: a cross-sectional population-based study of multimorbidity in Ontario.Canadian journal of public health = Revue canadienne de sante publique · 2018
    Article
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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

4 authors.

Barbara M HolzerDivision of Internal Medicine, University Hospital Zurich, Zurich, Switzerland. barbara.holzer@usz.ch.
Klarissa Siebenhuener
Matthias Bopp
Christoph E Minder

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPresently, there is no consensus on how to define multimorbidity. In this paper we investigate the connection between prevalence estimates for two or more and three or more chronic conditions to improve comparability of multimorbidity studies with different cut-offs.

methodsIn a systematic review of the literature published between January, 1990 and December, 2011, we found 52 suitable studies, many providing prevalence estimates for several age groups. A total of 31 studies reported both the prevalence for multimorbidity based on two or more chronic conditions and three or more chronic conditions, which were analysed in this study. Our research question was whether there is a systematic interrelation between these two prevalence estimates, and how this could be used to improve the comparability of studies on the burden of multimorbidity.

resultsActually, we found a tight relationship between the prevalence of two or more and three or more chronic conditions. Moreover, each of these estimates can be predicted from the other. I.e. the cut-offs of two or three for the number of chronic conditions produce essentially the same information on prevalence.

conclusionsOur study shows a way to enhance and improve the comparability of prevalence estimates from different multimorbidity studies.

Indexed as

Chronic DiseaseComorbidityResearch DesignFemaleHumansMalePrevalenceReference Values

Identifiers

PMID25084825
PMCPMC4133617

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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.