André Hajek, Razak M Gyasi, Karel Kostev, Pinar Soysal, Nicola Veronese, Lee Smith, Louis Jacob, Hans Oh, Supa Pengpid, Karl Peltzer, Hans-Helmut König
{"title":"多病集群及其对老年人福祉的贡献:基于德国全国代表性样本的结果。","authors":"André Hajek, Razak M Gyasi, Karel Kostev, Pinar Soysal, Nicola Veronese, Lee Smith, Louis Jacob, Hans Oh, Supa Pengpid, Karl Peltzer, Hans-Helmut König","doi":"10.1016/j.archger.2024.105726","DOIUrl":null,"url":null,"abstract":"<p><strong>Aim: </strong>Our aim was to identify multimorbidity clusters and, in particular, to examine their contribution to well-being outcomes among the oldest old in Germany.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":93880,"journal":{"name":"Archives of gerontology and geriatrics","volume":"130 ","pages":"105726"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multimorbidity clusters and their contribution to well-being among the oldest old: Results based on a nationally representative sample in Germany.\",\"authors\":\"André Hajek, Razak M Gyasi, Karel Kostev, Pinar Soysal, Nicola Veronese, Lee Smith, Louis Jacob, Hans Oh, Supa Pengpid, Karl Peltzer, Hans-Helmut König\",\"doi\":\"10.1016/j.archger.2024.105726\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aim: </strong>Our aim was to identify multimorbidity clusters and, in particular, to examine their contribution to well-being outcomes among the oldest old in Germany.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":93880,\"journal\":{\"name\":\"Archives of gerontology and geriatrics\",\"volume\":\"130 \",\"pages\":\"105726\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of gerontology and geriatrics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.archger.2024.105726\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/12/15 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of gerontology and geriatrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.archger.2024.105726","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/15 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Multimorbidity clusters and their contribution to well-being among the oldest old: Results based on a nationally representative sample in Germany.
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.