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Frailty and the prediction of dependence and mortality in low- and middle-income countries: a 10/66 population-based cohort study

BACKGROUND: In countries with high incomes, frailty indicators predict adverse outcomes in older people, despite a lack of consensus on definition or measurement. We tested the predictive validity of physical and multidimensional frailty phenotypes in settings in Latin America, India, and China. MET...

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Autores principales: AT, Jotheeswaran, Bryce, Renata, Prina, Matthew, Acosta, Daisy, Ferri, Cleusa P, Guerra, Mariella, Huang, Yueqin, Rodriguez, Juan J. Llibre, Salas, Aquiles, Sosa, Ana Luisa, Williams, Joseph D., Dewey, Michael E., Acosta, Isaac, Liu, Zhaorui, Beard, John, Prince, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481121/
https://www.ncbi.nlm.nih.gov/pubmed/26063168
http://dx.doi.org/10.1186/s12916-015-0378-4
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author AT, Jotheeswaran
Bryce, Renata
Prina, Matthew
Acosta, Daisy
Ferri, Cleusa P
Guerra, Mariella
Huang, Yueqin
Rodriguez, Juan J. Llibre
Salas, Aquiles
Sosa, Ana Luisa
Williams, Joseph D.
Dewey, Michael E.
Acosta, Isaac
Liu, Zhaorui
Beard, John
Prince, Martin
author_facet AT, Jotheeswaran
Bryce, Renata
Prina, Matthew
Acosta, Daisy
Ferri, Cleusa P
Guerra, Mariella
Huang, Yueqin
Rodriguez, Juan J. Llibre
Salas, Aquiles
Sosa, Ana Luisa
Williams, Joseph D.
Dewey, Michael E.
Acosta, Isaac
Liu, Zhaorui
Beard, John
Prince, Martin
author_sort AT, Jotheeswaran
collection PubMed
description BACKGROUND: In countries with high incomes, frailty indicators predict adverse outcomes in older people, despite a lack of consensus on definition or measurement. We tested the predictive validity of physical and multidimensional frailty phenotypes in settings in Latin America, India, and China. METHODS: Population-based cohort studies were conducted in catchment area sites in Cuba, Dominican Republic, Venezuela, Mexico, Peru, India, and China. Seven frailty indicators, namely gait speed, self-reported exhaustion, weight loss, low energy expenditure, undernutrition, cognitive, and sensory impairment were assessed to estimate frailty phenotypes. Mortality and onset of dependence were ascertained after a median of 3.9 years. RESULTS: Overall, 13,924 older people were assessed at baseline, with 47,438 person-years follow-up for mortality and 30,689 for dependence. Both frailty phenotypes predicted the onset of dependence and mortality, even adjusting for chronic diseases and disability, with little heterogeneity of effect among sites. However, population attributable fractions (PAF) summarising etiologic force were highest for the aggregate effect of the individual indicators, as opposed to either the number of indicators or the dichotomised frailty phenotypes. The aggregate of all seven indicators provided the best overall prediction (weighted mean PAF 41.8 % for dependence and 38.3 % for mortality). While weight loss, underactivity, slow walking speed, and cognitive impairment predicted both outcomes, whereas undernutrition predicted only mortality and sensory impairment only dependence. Exhaustion predicted neither outcome. CONCLUSIONS: Simply assessed frailty indicators identify older people at risk of dependence and mortality, beyond information provided by chronic disease diagnoses and disability. Frailty is likely to be multidimensional. A better understanding of the construct and pathways to adverse outcomes could inform multidimensional assessment and intervention to prevent or manage dependence in frail older people, with potential to add life to years, and years to life.
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spelling pubmed-44811212015-06-27 Frailty and the prediction of dependence and mortality in low- and middle-income countries: a 10/66 population-based cohort study AT, Jotheeswaran Bryce, Renata Prina, Matthew Acosta, Daisy Ferri, Cleusa P Guerra, Mariella Huang, Yueqin Rodriguez, Juan J. Llibre Salas, Aquiles Sosa, Ana Luisa Williams, Joseph D. Dewey, Michael E. Acosta, Isaac Liu, Zhaorui Beard, John Prince, Martin BMC Med Research Article BACKGROUND: In countries with high incomes, frailty indicators predict adverse outcomes in older people, despite a lack of consensus on definition or measurement. We tested the predictive validity of physical and multidimensional frailty phenotypes in settings in Latin America, India, and China. METHODS: Population-based cohort studies were conducted in catchment area sites in Cuba, Dominican Republic, Venezuela, Mexico, Peru, India, and China. Seven frailty indicators, namely gait speed, self-reported exhaustion, weight loss, low energy expenditure, undernutrition, cognitive, and sensory impairment were assessed to estimate frailty phenotypes. Mortality and onset of dependence were ascertained after a median of 3.9 years. RESULTS: Overall, 13,924 older people were assessed at baseline, with 47,438 person-years follow-up for mortality and 30,689 for dependence. Both frailty phenotypes predicted the onset of dependence and mortality, even adjusting for chronic diseases and disability, with little heterogeneity of effect among sites. However, population attributable fractions (PAF) summarising etiologic force were highest for the aggregate effect of the individual indicators, as opposed to either the number of indicators or the dichotomised frailty phenotypes. The aggregate of all seven indicators provided the best overall prediction (weighted mean PAF 41.8 % for dependence and 38.3 % for mortality). While weight loss, underactivity, slow walking speed, and cognitive impairment predicted both outcomes, whereas undernutrition predicted only mortality and sensory impairment only dependence. Exhaustion predicted neither outcome. CONCLUSIONS: Simply assessed frailty indicators identify older people at risk of dependence and mortality, beyond information provided by chronic disease diagnoses and disability. Frailty is likely to be multidimensional. A better understanding of the construct and pathways to adverse outcomes could inform multidimensional assessment and intervention to prevent or manage dependence in frail older people, with potential to add life to years, and years to life. BioMed Central 2015-06-10 /pmc/articles/PMC4481121/ /pubmed/26063168 http://dx.doi.org/10.1186/s12916-015-0378-4 Text en © AT et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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
AT, Jotheeswaran
Bryce, Renata
Prina, Matthew
Acosta, Daisy
Ferri, Cleusa P
Guerra, Mariella
Huang, Yueqin
Rodriguez, Juan J. Llibre
Salas, Aquiles
Sosa, Ana Luisa
Williams, Joseph D.
Dewey, Michael E.
Acosta, Isaac
Liu, Zhaorui
Beard, John
Prince, Martin
Frailty and the prediction of dependence and mortality in low- and middle-income countries: a 10/66 population-based cohort study
title Frailty and the prediction of dependence and mortality in low- and middle-income countries: a 10/66 population-based cohort study
title_full Frailty and the prediction of dependence and mortality in low- and middle-income countries: a 10/66 population-based cohort study
title_fullStr Frailty and the prediction of dependence and mortality in low- and middle-income countries: a 10/66 population-based cohort study
title_full_unstemmed Frailty and the prediction of dependence and mortality in low- and middle-income countries: a 10/66 population-based cohort study
title_short Frailty and the prediction of dependence and mortality in low- and middle-income countries: a 10/66 population-based cohort study
title_sort frailty and the prediction of dependence and mortality in low- and middle-income countries: a 10/66 population-based cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481121/
https://www.ncbi.nlm.nih.gov/pubmed/26063168
http://dx.doi.org/10.1186/s12916-015-0378-4
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