Evidence map›Paper›PMID 39773733›Full record

ArticleBMC medicine2025

Multimorbidity clusters and their associations with health-related quality of life in two UK cohorts.

Lewis Steell, Stefanie J Krauth, Sayem Ahmed, Grace O Dibben, Emma McIntosh, Peter Hanlon, Jim Lewsey, Barbara I Nicholl, David A McAllister, Susan M Smith and 16 more

Abstract read
In one paragraph

Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

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

  1. Pooled it
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  9. Quality of life among women of reproductive age during the accumulation of multiple chronic conditions.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
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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

26 authors.

Lewis SteellGeneral Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Stefanie J KrauthGeneral Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Sayem AhmedHealth Economics and Health Technology Assessment, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Grace O DibbenMRC/CSO Social & Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Emma McIntoshHealth Economics and Health Technology Assessment, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Peter HanlonGeneral Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Jim LewseyHealth Economics and Health Technology Assessment, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Barbara I NichollGeneral Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
David A McAllisterHealth Economics and Health Technology Assessment, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Susan M SmithDiscipline of Public Health and Primary Care, Trinity College Dublin, Dublin, Ireland.
Rachael EvansDepartment of Respiratory Sciences, University of Leicester, Leicester, UK.
Zahira AhmedDepartment of Respiratory Sciences, University of Leicester, Leicester, UK.
Sarah DeanUniversity of Exeter Medical School, Exeter, UK.
Colin GreavesSchool of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, UK.
Shaun BarberClinical Trials Unit, University of Leicester, Leicester, UK.
Patrick DohertyDepartment of Health Science, University of York, York, UK.
Nikki GardinerDepartment of Cardiopulmonary Rehabilitation, University Hospitals of Leicester NHS Trust, Leicester, UK.
Tracy IbbotsonGeneral Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Kate JollyInstitute of Applied Health Research, University of Birmingham, Birmingham, UK.
Paula OrmandySchool of Health and Society, University of Salford, Manchester, UK.
Sharon A SimpsonMRC/CSO Social & Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Rod S TaylorMRC/CSO Social & Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Sally J SinghDiscipline of Public Health and Primary Care, Trinity College Dublin, Dublin, Ireland.
Frances S Mair *General Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Bhautesh D Jani *General Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK. Bhautesh.Jani@glasgow.ac.uk.ORCID 0000-0001-7348-514X
PERFORM research team

Funding

National Institute for Health and Care Research NIHR202020
6 · The paper itself

Abstract

backgroundIdentifying clusters of multiple long-term conditions (MLTCs), also known as multimorbidity, and their associated burden may facilitate the development of effective and cost-effective targeted healthcare strategies. This study aimed to identify clusters of MLTCs and their associations with long-term health-related quality of life (HRQoL) in two UK population-based cohorts.

methodsAge-stratified clusters of MLTCs were identified at baseline in UK Biobank (n = 502,363, 54.6% female) and UKHLS (n = 49,186, 54.8% female) using latent class analysis (LCA). LCA was applied to people who self-reported ≥ 2 LTCs (from n = 43 LTCs [UK Biobank], n = 13 LTCs [UKHLS]) at baseline, across four age-strata: 18-36, 37-54, 55-73, and 74 + years. Associations between MLTC clusters and HRQoL were investigated using tobit regression and compared to associations between MLTC counts and HRQoL. For HRQoL, we extracted EQ-5D index data from UK Biobank. In UKHLS, SF-12 data were extracted and mapped to EQ-5D index scores using a standard preference-based algorithm. HRQoL data were collected at median 5 (UKHLS) and 10 (UK Biobank) years follow-up. Analyses were adjusted for available sociodemographic and lifestyle covariates.

resultsLCA identified 9 MLTC clusters in UK Biobank and 15 MLTC clusters in UKHLS. Clusters centred around pulmonary and cardiometabolic LTCs were common across all age groups. Hypertension was prominent across clusters in all ages, while depression featured in younger groups and painful conditions/arthritis were common in clusters from middle-age onwards. MLTC clusters showed different associations with HRQoL. In UK Biobank, clusters with high prevalence of painful conditions were consistently associated with the largest deficits in HRQoL. In UKHLS, clusters of cardiometabolic disease had the lowest HRQoL. Notably, negative associations between MLTC clusters containing painful conditions and HRQoL remained significant even after adjusting for number of LTCs.

conclusionsWhile higher LTC counts remain important, we have shown that MLTC cluster types also have an impact on HRQoL. Health service delivery planning and future intervention design and risk assessment of people with MLTCs should consider both LTC counts and MLTC clusters to better meet the needs of specific populations.

Indexed as

MultimorbidityQuality of LifeAdolescentAdultAgedCohort StudiesFemaleHumansMaleMiddle AgedUnited KingdomYoung AdultLatent class analysisMultimorbidityQuality of lifeUK Biobank

Identifiers

PMID39773733
PMCPMC11708164

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.