Evidence map›Paper›PMID 31060532›Full record

ArticleBMC public health2019

Calculating incidence rates and prevalence proportions: not as simple as it seems.

Inge Spronk, Joke C Korevaar, René Poos, Rodrigo Davids, Henk Hilderink, François G Schellevis, Robert A Verheij, Mark M J Nielen

Abstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed, 10 pooled it
–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

75 citing papers in PubMed, 10 syntheses or guidelines pooled it.

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  3. Safety profiles of bone-conduction hearing implants revisited: A meta-analytic comparison adjusted for follow-up time.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2025
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15 more citing papers are in PubMed but not listed here.

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

8 authors.

Inge SpronkNivel, Netherlands Institute for Health Services Research, P.O. Box 1568, 3500BN, Utrecht, The Netherlands. i.spronk@nivel.nl.ORCID http://orcid.org/0000-0001-9571-576X
Joke C KorevaarNivel, Netherlands Institute for Health Services Research, P.O. Box 1568, 3500BN, Utrecht, The Netherlands.
René PoosCentre for Health and Society, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
Rodrigo DavidsNivel, Netherlands Institute for Health Services Research, P.O. Box 1568, 3500BN, Utrecht, The Netherlands.
Henk HilderinkCentre for Health and Society, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
François G SchellevisNivel, Netherlands Institute for Health Services Research, P.O. Box 1568, 3500BN, Utrecht, The Netherlands.
Robert A VerheijNivel, Netherlands Institute for Health Services Research, P.O. Box 1568, 3500BN, Utrecht, The Netherlands.
Mark M J NielenNivel, Netherlands Institute for Health Services Research, P.O. Box 1568, 3500BN, Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIncidence rates and prevalence proportions are commonly used to express the populations health status. Since there are several methods used to calculate these epidemiological measures, good comparison between studies and countries is difficult. This study investigates the impact of different operational definitions of numerators and denominators on incidence rates and prevalence proportions.

methodsData from routine electronic health records of general practices contributing to NIVEL Primary Care Database was used. Incidence rates were calculated using different denominators (person-years at-risk, person-years and midterm population). Three different prevalence proportions were determined: 1 year period prevalence proportions, point-prevalence proportions and contact prevalence proportions.

resultsOne year period prevalence proportions were substantially higher than point-prevalence (58.3 - 206.6%) for long-lasting diseases, and one year period prevalence proportions were higher than contact prevalence proportions (26.2 - 79.7%). For incidence rates, the use of different denominators resulted in small differences between the different calculation methods (-1.3 - 14.8%). Using person-years at-risk or a midterm population resulted in higher rates compared to using person-years.

conclusionsAll different operational definitions affect incidence rates and prevalence proportions to some extent. Therefore, it is important that the terminology and methodology is well described by sources reporting these epidemiological measures. When comparing incidence rates and prevalence proportions from different sources, it is important to be aware of the operational definitions applied and their impact.

Indexed as

Epidemiologic MethodsIncidencePrevalenceAdolescentAdultAgedAged, 80 and overChildChild, PreschoolDatabases, FactualElectronic Health RecordsFemaleHumansInfantInfant, NewbornMaleElectronic health recordGeneral practiceIncidence ratePrevalence proportion

Identifiers

PMID31060532
PMCPMC6501456

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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.