Assessing the relationship between multimorbidity, NCD configurations, frailty phenotypes, and mortality risk in older adults.

Clusters Frailty Mortality Multimorbidity Older adults Patterns

Journal

BMC geriatrics
ISSN: 1471-2318
Titre abrégé: BMC Geriatr
Pays: England
ID NLM: 100968548

Informations de publication

Date de publication:
22 Apr 2024
Historique:
received: 14 08 2023
accepted: 04 04 2024
medline: 23 4 2024
pubmed: 23 4 2024
entrez: 22 4 2024
Statut: epublish

Résumé

Older adults are increasingly susceptible to prolonged illness, multiple chronic diseases, and disabilities, which can lead to the coexistence of multimorbidity and frailty. Multimorbidity may result in various noncommunicable disease (NCD) patterns or configurations that could be associated with frailty and death. Mortality risk may vary depending on the presence of specific chronic diseases configurations or frailty. The aim was to examine the impact of NCD configurations on mortality risk among older adults with distinct frailty phenotypes. The population was analyzed from the Costa Rican Longevity and Healthy Aging Study Cohort (CRELES). A total of 2,662 adults aged 60 or older were included and followed for 5 years. Exploratory factor analysis and various clustering techniques were utilized to identify NCD configurations. The frequency of NCD accumulation was also assessed for a multimorbidity definition. Frailty phenotypes were set according to Fried et al. criteria. Kaplan‒Meier survival analyses, mortality rates, and Cox proportional hazards models were estimated. Four different types of patterns were identified: 'Neuro-psychiatric', 'Metabolic', 'Cardiovascular', and 'Mixt' configurations. These configurations showed a higher mortality risk than the mere accumulation of NCDs [Cardiovascular HR:1.65 (1.07-2.57); 'Mixt' HR:1.49 (1.00-2.22); ≥3 NCDs HR:1.31 (1.09-1.58)]. Frailty exhibited a high and constant mortality risk, irrespective of the presence of any NCD configuration or multimorbidity definition. However, HRs decreased and lost statistical significance when phenotypes were considered in the Cox models [frailty + 'Cardiovascular' HR:1.56 (1.00-2.42); frailty + 'Mixt':1.42 (0.95-2.11); and frailty + ≥ 3 NCDs HR:1.23 (1.02-1.49)]. Frailty accompanying multimorbidity emerges as a more crucial indicator of mortality risk than multimorbidity alone. Therefore, studying NCD configurations is worthwhile as they may offer improved risk profiles for mortality as alternatives to straightforward counts.

Sections du résumé

BACKGROUND BACKGROUND
Older adults are increasingly susceptible to prolonged illness, multiple chronic diseases, and disabilities, which can lead to the coexistence of multimorbidity and frailty. Multimorbidity may result in various noncommunicable disease (NCD) patterns or configurations that could be associated with frailty and death. Mortality risk may vary depending on the presence of specific chronic diseases configurations or frailty.
METHODS METHODS
The aim was to examine the impact of NCD configurations on mortality risk among older adults with distinct frailty phenotypes. The population was analyzed from the Costa Rican Longevity and Healthy Aging Study Cohort (CRELES). A total of 2,662 adults aged 60 or older were included and followed for 5 years. Exploratory factor analysis and various clustering techniques were utilized to identify NCD configurations. The frequency of NCD accumulation was also assessed for a multimorbidity definition. Frailty phenotypes were set according to Fried et al. criteria. Kaplan‒Meier survival analyses, mortality rates, and Cox proportional hazards models were estimated.
RESULTS RESULTS
Four different types of patterns were identified: 'Neuro-psychiatric', 'Metabolic', 'Cardiovascular', and 'Mixt' configurations. These configurations showed a higher mortality risk than the mere accumulation of NCDs [Cardiovascular HR:1.65 (1.07-2.57); 'Mixt' HR:1.49 (1.00-2.22); ≥3 NCDs HR:1.31 (1.09-1.58)]. Frailty exhibited a high and constant mortality risk, irrespective of the presence of any NCD configuration or multimorbidity definition. However, HRs decreased and lost statistical significance when phenotypes were considered in the Cox models [frailty + 'Cardiovascular' HR:1.56 (1.00-2.42); frailty + 'Mixt':1.42 (0.95-2.11); and frailty + ≥ 3 NCDs HR:1.23 (1.02-1.49)].
CONCLUSIONS CONCLUSIONS
Frailty accompanying multimorbidity emerges as a more crucial indicator of mortality risk than multimorbidity alone. Therefore, studying NCD configurations is worthwhile as they may offer improved risk profiles for mortality as alternatives to straightforward counts.

Identifiants

pubmed: 38649809
doi: 10.1186/s12877-024-04948-9
pii: 10.1186/s12877-024-04948-9
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

355

Informations de copyright

© 2024. The Author(s).

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Auteurs

Rafael Ogaz-González (R)

Department of Public Health, Faculty of Medicine, National Autonomous University of México, Sixth Floor, Building B, 411A Circuito Escolar, Copilco Universidad, Mexico City, Coyoacán, 04360, Mexico.
Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

Eva Corpeleijn (E)

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

Rosa Estela García-Chanes (RE)

Dirección de Investigación, Instituto Nacional de Geriatría, Ciudad de México, Mexico.

Luis Miguel Gutierréz-Robledo (LM)

Dirección de Investigación, Instituto Nacional de Geriatría, Ciudad de México, Mexico.

Ricardo Antonio Escamilla-Santiago (RA)

Department of Public Health, Faculty of Medicine, National Autonomous University of México, Sixth Floor, Building B, 411A Circuito Escolar, Copilco Universidad, Mexico City, Coyoacán, 04360, Mexico.

Malaquías López-Cervantes (M)

Department of Public Health, Faculty of Medicine, National Autonomous University of México, Sixth Floor, Building B, 411A Circuito Escolar, Copilco Universidad, Mexico City, Coyoacán, 04360, Mexico. mlopezcervantes@unam.mx.

Classifications MeSH