Evidence mapPaperPMID 42483003Full record

ArticleBMJ public health2026

Effects of household and neighbourhood attributes on four definitions of multimorbidity: a comparative multilevel analysis of linked clinical and census data of Wales.

Eleojo Oluwaseun Abubakar, Clare MacRae, Chunyu Zheng, Laurence Rowley-Abel, Bruce Guthrie, Chris Dibben, Jamie Pearce, Alan Marshall

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Article in BMJ public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Eleojo Oluwaseun AbubakarDepartment of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK.ORCID https://orcid.org/0000-0001-5528-2357
Clare MacRaeUsher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.
Chunyu ZhengSchool of GeoSciences, The University of Edinburgh, Edinburgh, UK.
Laurence Rowley-AbelSocial Policy, The University of Edinburgh, Edinburgh, UK.
Bruce GuthrieAdvanced Care Research Centre, University of Edinburgh, Edinburgh, UK.
Chris DibbenSchool of GeoSciences, The University of Edinburgh, Edinburgh, UK.
Jamie PearceSchool of GeoSciences, The University of Edinburgh, Edinburgh, UK.
Alan MarshallSocial Policy, The University of Edinburgh, Edinburgh, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: To compare the influence of household and neighbourhood factors on the risk of four definitions of multimorbidity (MM), namely (1) patients with two or more long-term conditions (LTCs) (2+MM), (2) patients with three or more LTCs and (3) patients with three or more LTCs from three or more International Classification of Diseases (10th Revision) body systems and (4) 2+MM patients with at least one mental LTC and one physical LTC. Methods: We used individual-level census data of Wales and health episode records from the Secured Anonymised Information Linkage databank. The cohort was all living people registered with a Welsh general practice on the 2011 census date (27 March) (n=1 676 432). Three-level multilevel logistic regression models with individuals in households in neighbourhoods were applied to each MM definition. Results: Markers of socioeconomic disadvantage at the household (eg, tenure of dwelling) and neighbourhood (eg, neighbourhood deprivation) levels were associated with higher risks of MM across all definitions. Relative to urban cities and towns, rural village settings were associated with lower odds of all MM definitions in the fully adjusted models. Our partitioning of the variance in MM risk into level-wise components revealed more variance in households (between 23% and 12%) than in neighbourhoods (approximately 3%) and a sensitivity of the results to the definition of MM used. Household attributes accounted for a greater proportion of R Conclusions: Pertinent household and neighbourhood factors should be prioritised for targeted public interventions, and optimal strategies might vary according to definitions of MM employed, with mental-physical MM showing a different pattern from the other definitions, which have a similar pattern.

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DemographyEpidemiologyPublic Health

Identifiers

PMID42483003
PMCPMC13386087

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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 Socratic graph.