Evidence map›Paper›PMID 39757194›Full record

ArticleBMC medicine2025

Multimorbidity latent classes in relation to 11-year mortality, risk factors and health-related quality of life in Malaysia: a prospective health and demographic surveillance system study.

Michelle M C Tan, Charlotte Hanlon, Graciela Muniz-Terrera, Tatiana Benaglia, Roshidi Ismail, Devi Mohan, Ann Breeze Joseph Konkoth, Daniel Reidpath, Pedro José M Rebello Pinho, Pascale Allotey and 3 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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. 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
    Article
  4. Article
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

13 authors.

Michelle M C TanDepartment of Health Service and Population Research, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, De Crespigny Park, London, UK. tan_mun.chieng@kcl.ac.uk.
Charlotte HanlonDivision of Psychiatry, Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, Scotland, UK.
Graciela Muniz-TerreraEdinburgh Dementia Prevention, The University of Edinburgh and Western General Hospital, Edinburgh, Scotland, UK.
Tatiana BenagliaDepartment of Statistics, Institute of Mathematics, Statistics and Scientific Computing, Universidade Estadual de Campinas (UNICAMP), Campinas, São Paulo, Brazil.
Roshidi IsmailSouth East Asia Community Observatory (SEACO), Monash University Malaysia, Subang Jaya, Sunway City, Selangor, Malaysia.
Devi MohanGlobal Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Sunway City, Selangor, Malaysia.
Ann Breeze Joseph KonkothBiostatistics Research Group, Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK.
Daniel ReidpathGlobal Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Sunway City, Selangor, Malaysia.
Pedro José M Rebello PinhoPsychogeriatric Unit, Department of Psychiatry, Medical School, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.
Pascale AlloteyDepartment of Sexual and Reproductive Health and Research, World Health Organization (WHO), Geneva, Switzerland.
Zaid KassimDistrict Health Office Segamat, Ministry of Health Malaysia, Segamat, Johor, Malaysia.
Matthew Prina *Department of Health Service and Population Research, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, De Crespigny Park, London, UK. matthew.prina@ncl.ac.uk.
Tin Tin Su *Global Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Sunway City, Selangor, Malaysia. TinTin.Su@monash.edu.

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundWe aimed to identify specific multimorbidity latent classes among multi-ethnic community-dwelling adults aged ≥ 18 years in Malaysia. We further explored the risk factors associated with these patterns and examined the relationships between the multimorbidity patterns and 11-year all-cause mortality risk, as well as health-related quality of life (HRQoL).

methodsUsing data from 18,101 individuals (aged 18-97 years) from the baseline Census 2012, Health Round 2013, and Verbal Autopsies 2012-2023 of the South East Asia Community Observatory (SEACO) health and demographic surveillance system, latent class analysis was performed on 13 chronic health conditions to identify statistically and clinically meaningful groups. Multinomial logistic regression and Cox proportional hazards regression models were conducted to investigate the adjusted association of multimorbidity patterns with the risk factors and mortality, respectively. HRQoL was analyzed by linear contrasts in conjunction with ANCOVA adjusted for baseline confounders.

resultsFour distinct multimorbidity latent classes were identified: (1) relatively healthy (n = 10,640); (2) cardiometabolic diseases (n = 2428); (3) musculoskeletal, mobility and sensory disorders (n = 2391); and (4) complex multimorbidity (a group with more severe multimorbidity with combined profiles of classes 2 and 3) (n = 699). Significant variations in associations between socio-demographic characteristics and multimorbidity patterns were discovered, including age, sex, ethnicity, education level, marital status, household monthly income and employment status. The complex multimorbidity group had the lowest HRQoL across all domains compared to other groups (p < 0.001), including physical health, psychological, social relationships and environment. This group also exhibited the highest mortality risk over 11 years even after adjustment of confounders (age, sex, ethnicity, education and employment status), with a hazard of death of 1.83 (95% CI 1.44-2.33), followed by the cardiometabolic group (HR 1.42, 95% CI 1.18-1.70) and the musculoskeletal, mobility and sensory disorders group (HR 1.29, 95% CI 1.04-1.59).

conclusionsOur study advances the understanding of the complexity of multimorbidity and its implications for health outcomes and healthcare delivery. The findings suggest the need for integrated healthcare approaches that account for the clusters of multiple conditions and prioritize the complex multimorbidity cohort. Further longitudinal studies are warranted to explore the underlying mechanisms and evolution of multimorbidity patterns.

Indexed as

MultimorbidityQuality of LifeAdolescentAdultAgedAged, 80 and overChronic DiseaseFemaleHumansMalaysiaMaleMiddle AgedMortalityProspective StudiesRisk FactorsYoung AdultHealth and demographic surveillance systemHealth-related quality of lifeLatent classesMortalityMultimorbidityRisk factors

Identifiers

PMID39757194
PMCPMC11702131

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.