Evidence map›Paper›PMID 34380465›Full record

ArticleBMC public health2021

Prevalence and patterns of multimorbidity in Australian baby boomers: the Busselton healthy ageing study.

Michael L Hunter, Matthew W Knuiman, Bill A W Musk, Jennie Hui, Kevin Murray, John P Beilby, David R Hillman, Joseph Hung, Robert U Newton, Romola S Bucks and 8 more

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 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Exercise improves quality of life, mental health and pain in people living with osteoporosis: a systematic review and meta-analysis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026
    Pooled it
  2. Pooled it
  3. Genetic discovery using deep learning-derived optic nerve integrity phenotypes.medRxiv : the preprint server for health sciences · 2026
    Article
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  5. Review
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  9. Patterns and Determinants of Multimorbidity in Older Adults: Study in Health-Ecological Perspective.International journal of environmental research and public health · 2022
    Article
  10. 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

18 authors.

Michael L HunterBusselton Population Medical Research Institute Inc, Nedlands, WA, 6009, Australia. michael.hunter@uwa.edu.au.ORCID 0000-0001-6704-4815
Matthew W KnuimanSchool of Population and Global Health, The University of Western Australia, Crawley, WA, 6009, Australia.ORCID 0000-0001-8874-2305
Bill A W MuskBusselton Population Medical Research Institute Inc, Nedlands, WA, 6009, Australia.ORCID 0000-0003-4730-4645
Jennie HuiBusselton Population Medical Research Institute Inc, Nedlands, WA, 6009, Australia.ORCID 0000-0002-1653-2496
Kevin MurraySchool of Population and Global Health, The University of Western Australia, Crawley, WA, 6009, Australia.ORCID 0000-0002-8856-6046
John P BeilbyBusselton Population Medical Research Institute Inc, Nedlands, WA, 6009, Australia.ORCID 0000-0002-4915-2254
David R HillmanDepartment of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia.ORCID 0000-0001-9987-539X
Joseph HungBusselton Population Medical Research Institute Inc, Nedlands, WA, 6009, Australia.ORCID 0000-0002-4468-6097
Robert U NewtonExercise Medicine Research Institute, Edith Cowan University, Joondalup, WA, 6027, Australia.ORCID 0000-0003-0302-6129
Romola S BucksSchool of Psychological Science, University of Western Australia, Perth, WA, 6083, Australia.ORCID 0000-0002-4207-4724
Leon StrakerSchool of Physiotherapy and Exercise Science, Curtin University, Bentley, WA, 6845, Australia.ORCID 0000-0002-7786-4128
John P WalshFaculty of Health and Medical Sciences, Medical School, University of Western Australia, Crawley, 6009, Australia.ORCID 0000-0002-1766-2612
Kun ZhuFaculty of Health and Medical Sciences, Medical School, University of Western Australia, Crawley, 6009, Australia.ORCID 0000-0002-8723-7574
David G BruceFaculty of Health and Medical Sciences, Medical School, University of Western Australia, Crawley, 6009, Australia.ORCID 0000-0002-9979-6867
Robert H EikelboomEar Science Institute Australia, Subiaco, WA, 6008, Australia.ORCID 0000-0003-2911-5381
Timothy M E DavisMedical School, University of Western Australia, Fremantle Hospital, Fremantle, WA, 6959, Australia.ORCID 0000-0003-0749-7411
David A MackeyCentre for Ophthalmology and Visual Science, University of Western Australia, Lions Eye Institute, Perth, Australia.ORCID 0000-0001-7914-4709
Alan L JamesBusselton Population Medical Research Institute Inc, Nedlands, WA, 6009, Australia.ORCID 0000-0002-6018-0547

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveChronic medical conditions accumulate within individuals with age. However, knowledge concerning the trends, patterns and determinants of multimorbidity remains limited. This study assessed the prevalence and patterns of multimorbidity using extensive individual phenotyping in a general population of Australian middle-aged adults.

methodsParticipants (n = 5029, 55% female), born between 1946 and 1964 and attending the cross-sectional phase of the Busselton Healthy Ageing Study (BHAS) between 2010 and 2015, were studied. Prevalence of 21 chronic conditions was estimated using clinical measurement, validated instrument scores and/or self-reported doctor-diagnosis. Non-random patterns of multimorbidity were explored using observed/expected (O/E) prevalence ratios and latent class analysis (LCA). Variables associated with numbers of conditions and class of multimorbidity were investigated.

resultsThe individual prevalence of 21 chronic conditions ranged from 2 to 54% and multimorbidity was common with 73% of the cohort having 2 or more chronic conditions. (mean ± SD 2.75 ± 1.84, median = 2.00, range 0-13). The prevalence of multimorbidity increased with age, obesity, physical inactivity, tobacco smoking and family history of asthma, diabetes, myocardial infarct or cancer. There were 13 pairs and 27 triplets of conditions identified with a prevalence > 1.5% and O/E > 1.5. Of the triplets, arthritis (> 50%), bowel disease (> 33%) and depression-anxiety (> 33%) were observed most commonly. LCA modelling identified 4 statistically and clinically distinct classes of multimorbidity labelled as: 1) "Healthy" (70%) with average of 1.95 conditions; 2) "Respiratory and Atopy" (11%, 3.65 conditions); 3) "Non-cardiometabolic" (14%, 4.77 conditions), and 4) "Cardiometabolic" (5%, 6.32 conditions). Predictors of multimorbidity class membership differed between classes and differed from predictors of number of co-occurring conditions.

conclusionMultimorbidity is common among middle-aged adults from a general population. Some conditions associated with ageing such as arthritis, bowel disease and depression-anxiety co-occur in clinically distinct patterns and at higher prevalence than expected by chance. These findings may inform further studies into shared biological and environmental causes of co-occurring conditions of ageing. Recognition of distinct patterns of multimorbidity may aid in a holistic approach to care management in individuals presenting with multiple chronic conditions, while also guiding health resource allocation in ageing populations.

Indexed as

Healthy AgingMultimorbidityAdultAustraliaChronic DiseaseComorbidityCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalenceAgeingChronic diseaseCo-morbiditiesMiddle-agedMultimorbidity

Identifiers

PMID34380465
PMCPMC8359115

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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.