Evidence map›Paper›PMID 34271890›Full record

ArticleBMC public health2021

The prevalence of multimorbidity in primary care: a comparison of two definitions of multimorbidity with two different lists of chronic conditions in Singapore.

Eng Sing Lee, Poay Sian Sabrina Lee, Ying Xie, Bridget L Ryan, Martin Fortin, Moira Stewart

Abstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  15. Sociodemographic and Health-Related Factors Influencing Drug Intake among the Elderly Population.International journal of environmental research and public health · 2022
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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

6 authors.

Eng Sing LeeClinical Research Unit, National Healthcare Group Polyclinics, Singapore, Singapore. eng_sing_lee@nhgp.com.sg.ORCID 0000-0003-4963-535X
Poay Sian Sabrina LeeClinical Research Unit, National Healthcare Group Polyclinics, Singapore, Singapore.
Ying XieClinical Research Unit, National Healthcare Group Polyclinics, Singapore, Singapore.
Bridget L RyanDepartment of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, Western University, 1151 Richmond St, London, ON, N6A 5C1, Canada.
Martin FortinDepartment of Family Medicine, Centre de Santé et de Services Sociaux de Chicoutimi, Unité de médecine de famille, University of Sherbrooke, 305, rue St-Vallier, Chicoutimi, QC, G7H 5H6, Canada.
Moira StewartDepartment of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, Western University, 1151 Richmond St, London, ON, N6A 5C1, Canada.

Funding

national medical research council NMRC/CG/C019/2017
6 · The paper itself

Abstract

backgroundThe prevalence of multimorbidity varies widely due to the lack of consensus in defining multimorbidity. This study aimed to measure the prevalence of multimorbidity in a primary care setting using two definitions of multimorbidity with two different lists of chronic conditions.

methodsWe conducted a cross-sectional study of 787,446 patients, aged 0 to 99 years, who consulted a family physician between July 2015 to June 2016. Multimorbidity was defined as 'two or more' (MM2+) or 'three or more' (MM3+) chronic conditions using the Fortin list and Chronic Disease Management Program (CDMP) list of chronic conditions. Crude and standardised prevalence rates were reported, and the corresponding age, sex or ethnic-stratified standardised prevalence rates were adjusted to the local population census.

resultsThe number of patients with multimorbidity increased with age. Age-sex-ethnicity standardised prevalence rates of multimorbidity using MM2+ and MM3+ for Fortin list (25.9, 17.2%) were higher than those for CDMP list (22.0%; 12.4%). Sex-stratified, age-ethnicity standardised prevalence rates for MM2+ and MM3+ were consistently higher in males compared to females for both lists. Chinese and Indians have the highest standardised prevalence rates among the four ethnicities using MM2+ and MM3+ respectively.

conclusionsMM3+ was better at identifying a smaller number of patients with multimorbidity requiring higher needs compared to MM2+. Using the Fortin list seemed more appropriate than the CDMP list because the chronic conditions in Fortin's list were more commonly seen in primary care. A consistent definition of multimorbidity will help researchers and clinicians to understand the epidemiology of multimorbidity better.

Indexed as

MultimorbidityPrimary Health CareChronic DiseaseComorbidityCross-Sectional StudiesFemaleHumansMalePrevalenceSingaporeAgeEthnicityMultimorbidityPrevalencePrimary careSex

Identifiers

PMID34271890
PMCPMC8283957

What OpenQuestion holds

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LicenceCC BY
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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.