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

André Hajek*, Razak M. Gyasi, Karel Kostev, Pinar Soysal, Nicola Veronese, Lee Smith, Louis Jacob, Hans Oh, Supa Pengpid, Karl Peltzer, Hans Helmut König

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Aim: 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.

Original languageEnglish
Article number105726
JournalArchives of Gerontology and Geriatrics
Volume130
DOIs
Publication statusPublished - Mar 2025
Externally publishedYes

Keywords

  • Depression
  • High morbidity
  • Latent class analysis
  • Life satisfaction
  • Loneliness
  • Mental health
  • Mental illness
  • Multimorbidity clusters
  • Multimorbidity patterns
  • Multiple chronic conditions
  • Oldest old

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