Multimorbidity clusters and their contribution to well-being among the oldest old: Results based on a nationally representative sample in Germany

dc.contributor.authorHajek A.
dc.contributor.authorGyasi R.M.
dc.contributor.authorKostev K.
dc.contributor.authorSoysal P.
dc.contributor.authorVeronese N.
dc.contributor.authorSmith L.
dc.contributor.authorJacob L.
dc.contributor.authorOh H.
dc.contributor.authorPengpid S.
dc.contributor.authorPeltzer K.
dc.contributor.authorKönig H.H.
dc.contributor.correspondenceHajek A.
dc.contributor.otherMahidol University
dc.date.accessioned2025-01-23T18:38:47Z
dc.date.available2025-01-23T18:38:47Z
dc.date.issued2025-03-01
dc.description.abstractAim: Our aim was to identify multimorbidity clusters and, in particular, to examine their contribution to well-being outcomes among the oldest old in Germany. Methods: Data were taken from the large nationally representative D80+ study including community-dwelling and institutionalized individuals aged 80 years and over residing in Germany (n = 8,773). The mean age was 85.6 years (SD: 4.1). Based on 21 chronic conditions, latent class analysis was carried out to explore multimorbidity (≥2 chronic conditions) clusters. Widely used tools were applied to quantify well-being outcomes. Results: Approximately nine out of ten people aged 80 and over living in Germany were multimorbid. Four multimorbidity clusters were identified: relatively healthy class (30.2 %), musculoskeletal class (44.8 %), mental illness class (8.6 %), and high morbidity class (16.4 %). Being part of the mental disorders cluster was consistently linked to reduced well-being (in terms of low life satisfaction, high loneliness and lower odds of meaning in life), followed by membership in the high morbidity cluster. Conclusions: Four multimorbidity clusters were detected among the oldest old in Germany. Particularly belonging to the mental disorders cluster is consistently associated with low well-being, followed by belonging to the high morbidity cluster. This stresses the need for efforts to target such vulnerable groups, pending future longitudinal research.
dc.identifier.citationArchives of Gerontology and Geriatrics Vol.130 (2025)
dc.identifier.doi10.1016/j.archger.2024.105726
dc.identifier.eissn18726976
dc.identifier.issn01674943
dc.identifier.pmid39700712
dc.identifier.scopus2-s2.0-85212322818
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/102852
dc.rights.holderSCOPUS
dc.subjectNursing
dc.subjectBiochemistry, Genetics and Molecular Biology
dc.subjectMedicine
dc.subjectSocial Sciences
dc.titleMultimorbidity clusters and their contribution to well-being among the oldest old: Results based on a nationally representative sample in Germany
dc.typeArticle
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85212322818&origin=inward
oaire.citation.titleArchives of Gerontology and Geriatrics
oaire.citation.volume130
oairecerif.author.affiliationParc Sanitari Sant Joan de Déu
oairecerif.author.affiliationCollege of Medical and Health Science
oairecerif.author.affiliationCentre de Recherche Epidémiologiques et Bio Statistiques de Sorbonne Paris Cité (CRESS)
oairecerif.author.affiliationBezmiâlem Vakıf Üniversitesi
oairecerif.author.affiliationAfrican Population and Health Research Center
oairecerif.author.affiliationUniversity of Southern California
oairecerif.author.affiliationHôpital Fernand-Widal
oairecerif.author.affiliationUniversità degli Studi di Palermo, Scuola di Medicina e Chirurgia
oairecerif.author.affiliationUniversity of the Free State
oairecerif.author.affiliationSefako Makgatho Health Sciences University (SMU)
oairecerif.author.affiliationMahidol University
oairecerif.author.affiliationSouthern Cross University
oairecerif.author.affiliationUniversitätsklinikum Hamburg-Eppendorf
oairecerif.author.affiliationUniversitätsklinikum Gießen und Marburg, Standort Marburg
oairecerif.author.affiliationAnglia Ruskin University

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