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Which Factors Contribute to Frailty among the Oldest Old? Results of the Multicentre Prospective AgeCoDe and AgeQualiDe Study
- Source :
- Gerontology 66(5), 460-466 (2020). doi:10.1159/000508723
- Publication Year :
- 2020
- Publisher :
- Karger, 2020.
-
Abstract
- Introduction: There is a lack of studies investigating the link between time-varying factors associated with changes in frailty scores in very old age longitudinally. This is important because the level of frailty is associated with subsequent morbidity and mortality. Objective: To examine time-dependent predictors of frailty among the oldest old using a longitudinal approach. Methods: Longitudinal data were drawn from the multicentre prospective cohort study “Study on Needs, health service use, costs and health-related quality of life in a large sample of oldest-old primary care patients (85+)” (AgeQualiDe), covering primary care patients aged 85 years and over. Three waves were used (from follow-up, FU, wave 7 to FU wave 9 [with 10 months between each wave]; 1,301 observations in the analytical sample). Frailty was assessed using the Canadian Study of Health and Aging (CSHA) Clinical Frailty Scale (CFS). As explanatory variables, we included sociodemographic factors (marital status and age), social isolation as well as health-related variables (depression, dementia, and chronic diseases) in a regression analysis. Results: In total, 18.9% of the individuals were mildly frail, 12.4% of the individuals were moderately frail, and 0.4% of the individuals were severely frail at FU wave 7. Fixed effects regressions revealed that increases in frailty were associated with increases in age (β = 0.23, p < 0.001), and dementia (β = 0.84, p < 0.01), as well as increases in chronic conditions (β = 0.03, p = 0.058). Conclusion: The study findings particularly emphasize the importance of changes in age, probably chronic conditions as well as dementia for frailty. Future research is required to elucidate the underlying mechanisms. Furthermore, future longitudinal studies based on panel regression models are required to confirm our findings.
- Subjects :
- Gerontology
Male
Aging
Longitudinal study
Chronic conditions
Canada
Frail Elderly
Comorbidity
Chronic illness
statistics & numerical data [Frail Elderly]
Oldest old
Cohort Studies
Quality of life
epidemiology [Canada]
Activities of Daily Living
Medicine
Dementia
Humans
Longitudinal Studies
Prospective Studies
ddc:610
Social isolation
Prospective cohort study
Depression (differential diagnoses)
Aged, 80 and over
Frailty
Primary Health Care
business.industry
Depression
Physical illness
medicine.disease
epidemiology [Frailty]
Quality of Life
Frailty, Depression, Dementia, Oldest old, Longitudinal study, Chronic conditions, Chronic illness, Comorbidity, Physical illness
Marital status
statistics & numerical data [Primary Health Care]
Female
Geriatrics and Gerontology
medicine.symptom
business
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Gerontology 66(5), 460-466 (2020). doi:10.1159/000508723
- Accession number :
- edsair.doi.dedup.....88672a62017d3265b5325b0cef3c7c7d
- Full Text :
- https://doi.org/10.1159/000508723