Cargando…

Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition

BACKGROUND: Information about frailty status and its transition is important to inform clinical decisions. Predicting frailty transition is beneficial for its prevention. While Indonesia is the 4th largest geriatric population in Asia, data about frailty transition is limited. This study aimed to ob...

Descripción completa

Detalles Bibliográficos
Autores principales: Setiati, Siti, Laksmi, Purwita Wijaya, Aryana, I.G.P. Suka, Sunarti, Sri, Widajanti, Novira, Dwipa, Lazuardhi, Seto, Euphemia, Istanti, Rahmi, Ardian, Laurentius Johan, Chotimah, Sabrina Chusnul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609407/
https://www.ncbi.nlm.nih.gov/pubmed/31269921
http://dx.doi.org/10.1186/s12877-019-1198-8
_version_ 1783432312183062528
author Setiati, Siti
Laksmi, Purwita Wijaya
Aryana, I.G.P. Suka
Sunarti, Sri
Widajanti, Novira
Dwipa, Lazuardhi
Seto, Euphemia
Istanti, Rahmi
Ardian, Laurentius Johan
Chotimah, Sabrina Chusnul
author_facet Setiati, Siti
Laksmi, Purwita Wijaya
Aryana, I.G.P. Suka
Sunarti, Sri
Widajanti, Novira
Dwipa, Lazuardhi
Seto, Euphemia
Istanti, Rahmi
Ardian, Laurentius Johan
Chotimah, Sabrina Chusnul
author_sort Setiati, Siti
collection PubMed
description BACKGROUND: Information about frailty status and its transition is important to inform clinical decisions. Predicting frailty transition is beneficial for its prevention. While Indonesia is the 4th largest geriatric population in Asia, data about frailty transition is limited. This study aimed to obtain data on prevalence of frailty, its risk factors, frailty state transition and its prognostic factors, as well as to develop prognostic score for frailty state transition. METHODS: Multicenter study on subjects aged ≥60 years old was done to obtain the prevalence of frailty status and to identify risk factors of frailty. Prospective cohort over 12 months was done to obtain data on frailty state transition. Multiple logistic regression analysis was performed to identify its prognostic factors from several clinical data, which then were utilized to develop prognostic score for frailty state worsening. RESULTS: Cross-sectional data from 448 subjects showed that 25.2% of the subjects were frail based on Frailty index-40 items. Risk factors of frailty were age (OR 2.72; 95% CI 1.58–4.76), functional status (OR 2.89; 95% CI 1.79–4.67), and nutritional status (OR 3.75; 95% CI 2.29–6.13). Data from the 162 subjects who completed the cohort showed 27.2% of the cohort had frailty state worsening. Prognostic factors for frailty state worsening were being 70 years or older (OR 3.9; 95% CI 1.2–12.3, p < 0.05), negative QoL, i.e., fair and poor QoL (OR 2.5; 95% CI 1.1–5.9, p < 0.05), and slow gait speed (OR 2.8; 95% CI 1.3–6.4, p < 0.05). The internal validation of the prognostic score consisted of those three variables showed good performance. CONCLUSION: The prevalence of frailty in this study among Indonesian elderly in outpatient setting was 25.2%. The risk factors of frailty were age, functional status and nutritional status. The prognostic factors for frailty state worsening were being 70 years old or older, negative QoL (fair or poor quality of life), and slow gait speed. A prognostic score to predict frailty state worsening in 12 months had been developed.
format Online
Article
Text
id pubmed-6609407
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-66094072019-07-16 Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition Setiati, Siti Laksmi, Purwita Wijaya Aryana, I.G.P. Suka Sunarti, Sri Widajanti, Novira Dwipa, Lazuardhi Seto, Euphemia Istanti, Rahmi Ardian, Laurentius Johan Chotimah, Sabrina Chusnul BMC Geriatr Research Article BACKGROUND: Information about frailty status and its transition is important to inform clinical decisions. Predicting frailty transition is beneficial for its prevention. While Indonesia is the 4th largest geriatric population in Asia, data about frailty transition is limited. This study aimed to obtain data on prevalence of frailty, its risk factors, frailty state transition and its prognostic factors, as well as to develop prognostic score for frailty state transition. METHODS: Multicenter study on subjects aged ≥60 years old was done to obtain the prevalence of frailty status and to identify risk factors of frailty. Prospective cohort over 12 months was done to obtain data on frailty state transition. Multiple logistic regression analysis was performed to identify its prognostic factors from several clinical data, which then were utilized to develop prognostic score for frailty state worsening. RESULTS: Cross-sectional data from 448 subjects showed that 25.2% of the subjects were frail based on Frailty index-40 items. Risk factors of frailty were age (OR 2.72; 95% CI 1.58–4.76), functional status (OR 2.89; 95% CI 1.79–4.67), and nutritional status (OR 3.75; 95% CI 2.29–6.13). Data from the 162 subjects who completed the cohort showed 27.2% of the cohort had frailty state worsening. Prognostic factors for frailty state worsening were being 70 years or older (OR 3.9; 95% CI 1.2–12.3, p < 0.05), negative QoL, i.e., fair and poor QoL (OR 2.5; 95% CI 1.1–5.9, p < 0.05), and slow gait speed (OR 2.8; 95% CI 1.3–6.4, p < 0.05). The internal validation of the prognostic score consisted of those three variables showed good performance. CONCLUSION: The prevalence of frailty in this study among Indonesian elderly in outpatient setting was 25.2%. The risk factors of frailty were age, functional status and nutritional status. The prognostic factors for frailty state worsening were being 70 years old or older, negative QoL (fair or poor quality of life), and slow gait speed. A prognostic score to predict frailty state worsening in 12 months had been developed. BioMed Central 2019-07-03 /pmc/articles/PMC6609407/ /pubmed/31269921 http://dx.doi.org/10.1186/s12877-019-1198-8 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Setiati, Siti
Laksmi, Purwita Wijaya
Aryana, I.G.P. Suka
Sunarti, Sri
Widajanti, Novira
Dwipa, Lazuardhi
Seto, Euphemia
Istanti, Rahmi
Ardian, Laurentius Johan
Chotimah, Sabrina Chusnul
Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition
title Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition
title_full Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition
title_fullStr Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition
title_full_unstemmed Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition
title_short Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition
title_sort frailty state among indonesian elderly: prevalence, associated factors, and frailty state transition
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609407/
https://www.ncbi.nlm.nih.gov/pubmed/31269921
http://dx.doi.org/10.1186/s12877-019-1198-8
work_keys_str_mv AT setiatisiti frailtystateamongindonesianelderlyprevalenceassociatedfactorsandfrailtystatetransition
AT laksmipurwitawijaya frailtystateamongindonesianelderlyprevalenceassociatedfactorsandfrailtystatetransition
AT aryanaigpsuka frailtystateamongindonesianelderlyprevalenceassociatedfactorsandfrailtystatetransition
AT sunartisri frailtystateamongindonesianelderlyprevalenceassociatedfactorsandfrailtystatetransition
AT widajantinovira frailtystateamongindonesianelderlyprevalenceassociatedfactorsandfrailtystatetransition
AT dwipalazuardhi frailtystateamongindonesianelderlyprevalenceassociatedfactorsandfrailtystatetransition
AT setoeuphemia frailtystateamongindonesianelderlyprevalenceassociatedfactorsandfrailtystatetransition
AT istantirahmi frailtystateamongindonesianelderlyprevalenceassociatedfactorsandfrailtystatetransition
AT ardianlaurentiusjohan frailtystateamongindonesianelderlyprevalenceassociatedfactorsandfrailtystatetransition
AT chotimahsabrinachusnul frailtystateamongindonesianelderlyprevalenceassociatedfactorsandfrailtystatetransition