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ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2026

Multimorbidity profiles and global quality of life: a population-based latent class and structural equation modeling study.

Diego Manríquez-Robles, Scarlett Roa-Castillo, Melisa Aedo, Felipe Henríquez-Valenzuela, Rubén Alvarado

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Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 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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5 · Who and what money

Authors and funding

5 authors.

Diego Manríquez-RoblesDepartamento de Psicología, Universidad de La Frontera, Temuco, Chile. dmanriquezrobles@gmail.com.ORCID https://orcid.org/0000-0002-6394-7854
Scarlett Roa-CastilloDepartment of Health and Kinesiology, University of Illinois Urbana-Champaign, Urbana, USA.
Melisa AedoDepartamento de Psicología, Universidad Católica de Temuco, Temuco, Chile.
Felipe Henríquez-ValenzuelaDepartamento de Salud, Universidad de Los Lagos, Osorno, Chile.
Rubén AlvaradoDepartamento de Salud Pública, Universidad de Valparaíso, Valparaíso, Chile.

Funding

Agencia Nacional de Investigación y Desarrollo , Chile 56220079
6 · The paper itself

Abstract

purposeTo examine whether clustered configurations of multimorbidity, functional limitation, physical activity, formal social participation, and alcohol risk are associated with global quality of life (QoL), and to evaluate the hierarchical structure of the World Health Organization Quality of Life-BREF (WHOQOL-BREF) using data from anationally representative Chilean survey.

methodsCross-sectional data were drawn from the 2023-2024 Chilean National Survey on Quality of Life and Health. Latent class analysis identified health-functional profiles using five categorical indicators (n = 16,469). Confirmatory factor analysis evaluated correlated four-factor and hierarchical second-order representations of the WHOQOL-BREF (n = 13,451). Structural equation modeling examined associations between profile membership, sociodemographic characteristics, and global QoL (n = 13,016). Analyses incorporated calibrated sampling weights, with design-basedinference accounting for the stratified and clustered survey design.

resultsA three-class solution comprising lower-burden, intermediate-burden, and higher-burden profiles was retained. Profiles were most clearly differentiated by multimorbidity and functional limitation, whereas physical activity, social participation, and alcohol risk showed weaker or nonmonotonic differentiation. The hierarchical WHOQOL-BREF model showed comparable approximate fit to the correlated four-factor model, with strong secondorder loadings across all four QoL domains. Relative to the lower-burden profile, global QoL was lower in theintermediate-burden profile (β = -.132, p < .001) and substantially lower in the higher-burden profile (β = -.341, p < .001). Posterior pseudo-class sensitivity analyses preserved the direction and ordering of these associations. Educational attainment (β = .142, p < .001) and household income (β = .139, p < .001) were positively associated with global QoL.

conclusionGlobal QoL was associated with graded health-functional burden and socioeconomic position. Combining person-centered health profiles with a hierarchical representation of QoL may provide a useful framework for characterizing population heterogeneity in health, functioning, and subjective quality of life.

Indexed as

MultimorbidityQuality of LifeAdolescentAdultAgedChileCross-Sectional StudiesExerciseFactor Analysis, StatisticalFemaleHumansLatent Class AnalysisMaleMiddle AgedSocial ParticipationSocioeconomic FactorsHealth inequalitiesLatent class analysisMultimorbidityQuality of lifeStructural equation modelingWHOQOL-BREF

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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.