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...
Autores principales: | , , , , , , , , , |
---|---|
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 |