TY - JOUR
T1 - Multimorbidity clusters and their contribution to well-being among the oldest old
T2 - Results based on a nationally representative sample in Germany
AU - Hajek, André
AU - Gyasi, Razak M.
AU - Kostev, Karel
AU - Soysal, Pinar
AU - Veronese, Nicola
AU - Smith, Lee
AU - Jacob, Louis
AU - Oh, Hans
AU - Pengpid, Supa
AU - Peltzer, Karl
AU - König, Hans Helmut
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2025/3
Y1 - 2025/3
N2 - 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.
AB - 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.
KW - Depression
KW - High morbidity
KW - Latent class analysis
KW - Life satisfaction
KW - Loneliness
KW - Mental health
KW - Mental illness
KW - Multimorbidity clusters
KW - Multimorbidity patterns
KW - Multiple chronic conditions
KW - Oldest old
UR - http://www.scopus.com/inward/record.url?scp=85212322818&partnerID=8YFLogxK
U2 - 10.1016/j.archger.2024.105726
DO - 10.1016/j.archger.2024.105726
M3 - Article
C2 - 39700712
AN - SCOPUS:85212322818
SN - 0167-4943
VL - 130
JO - Archives of Gerontology and Geriatrics
JF - Archives of Gerontology and Geriatrics
M1 - 105726
ER -