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Defining Health Trajectories in Older Adults With Five Clinical Indicators
BACKGROUND: People age differently, challenging the identification of those more at risk of rapid health deterioration. This study aimed to explore the heterogeneity in the health of older adults by using five clinical indicators to detect age-related variation and individual health trajectories ove...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861965/ https://www.ncbi.nlm.nih.gov/pubmed/28329788 http://dx.doi.org/10.1093/gerona/glw204 |
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author | Santoni, Giola Marengoni, Alessandra Calderón-Larrañaga, Amaia Angleman, Sara Rizzuto, Debora Welmer, Anna-Karin Mangialasche, Francesca Orsini, Nicola Fratiglioni, Laura |
author_facet | Santoni, Giola Marengoni, Alessandra Calderón-Larrañaga, Amaia Angleman, Sara Rizzuto, Debora Welmer, Anna-Karin Mangialasche, Francesca Orsini, Nicola Fratiglioni, Laura |
author_sort | Santoni, Giola |
collection | PubMed |
description | BACKGROUND: People age differently, challenging the identification of those more at risk of rapid health deterioration. This study aimed to explore the heterogeneity in the health of older adults by using five clinical indicators to detect age-related variation and individual health trajectories over time. METHODS: Health of 3,363 people aged 60+ from the Swedish National study on Aging and Care-Kungsholmen (SNAC-K) assessed at baseline and at 3- and 6-year follow-ups. Number of chronic diseases, physical and cognitive performance, personal and instrumental activities of daily living were integrated in a health assessment tool (HAT). Interindividual health differences at baseline and follow-ups were assessed with logistic quantile regression. Intraindividual health trajectories were traced with quantile mixed-effect models. RESULTS: The HAT score ranges from 0 (poor health) to 10 (good health); each score corresponds to a specific clinical profile. HAT was reliable over time and accurately predicted adverse health outcomes (receiver-operating characteristic areas: hospitalization = 0.78; 95% confidence interval = 0.74–0.81; mortality = 0.85; 95% confidence interval = 0.83–0.87; similar areas obtained for gait speed). Before age 85, at least 90% of participants were free of severe disability, and at least 50% were functionally independent despite chronic disorders. Age- and sex-related variation and high heterogeneity in health were detected at baseline and confirmed by intraindividual health trajectories. CONCLUSIONS: This study provides a positive picture of the health status of people 60+. Despite the complexity and heterogeneity of health in this age group, we could identify age- and sex-specific health trajectories using an integrated HAT. HAT is potentially useful in clinical practice and public health interventions. |
format | Online Article Text |
id | pubmed-5861965 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-58619652018-03-28 Defining Health Trajectories in Older Adults With Five Clinical Indicators Santoni, Giola Marengoni, Alessandra Calderón-Larrañaga, Amaia Angleman, Sara Rizzuto, Debora Welmer, Anna-Karin Mangialasche, Francesca Orsini, Nicola Fratiglioni, Laura J Gerontol A Biol Sci Med Sci Research Article BACKGROUND: People age differently, challenging the identification of those more at risk of rapid health deterioration. This study aimed to explore the heterogeneity in the health of older adults by using five clinical indicators to detect age-related variation and individual health trajectories over time. METHODS: Health of 3,363 people aged 60+ from the Swedish National study on Aging and Care-Kungsholmen (SNAC-K) assessed at baseline and at 3- and 6-year follow-ups. Number of chronic diseases, physical and cognitive performance, personal and instrumental activities of daily living were integrated in a health assessment tool (HAT). Interindividual health differences at baseline and follow-ups were assessed with logistic quantile regression. Intraindividual health trajectories were traced with quantile mixed-effect models. RESULTS: The HAT score ranges from 0 (poor health) to 10 (good health); each score corresponds to a specific clinical profile. HAT was reliable over time and accurately predicted adverse health outcomes (receiver-operating characteristic areas: hospitalization = 0.78; 95% confidence interval = 0.74–0.81; mortality = 0.85; 95% confidence interval = 0.83–0.87; similar areas obtained for gait speed). Before age 85, at least 90% of participants were free of severe disability, and at least 50% were functionally independent despite chronic disorders. Age- and sex-related variation and high heterogeneity in health were detected at baseline and confirmed by intraindividual health trajectories. CONCLUSIONS: This study provides a positive picture of the health status of people 60+. Despite the complexity and heterogeneity of health in this age group, we could identify age- and sex-specific health trajectories using an integrated HAT. HAT is potentially useful in clinical practice and public health interventions. Oxford University Press 2017-08 2016-10-19 /pmc/articles/PMC5861965/ /pubmed/28329788 http://dx.doi.org/10.1093/gerona/glw204 Text en © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. http://creativecommons.org/licenses/by-nc/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Research Article Santoni, Giola Marengoni, Alessandra Calderón-Larrañaga, Amaia Angleman, Sara Rizzuto, Debora Welmer, Anna-Karin Mangialasche, Francesca Orsini, Nicola Fratiglioni, Laura Defining Health Trajectories in Older Adults With Five Clinical Indicators |
title | Defining Health Trajectories in Older Adults With Five Clinical Indicators |
title_full | Defining Health Trajectories in Older Adults With Five Clinical Indicators |
title_fullStr | Defining Health Trajectories in Older Adults With Five Clinical Indicators |
title_full_unstemmed | Defining Health Trajectories in Older Adults With Five Clinical Indicators |
title_short | Defining Health Trajectories in Older Adults With Five Clinical Indicators |
title_sort | defining health trajectories in older adults with five clinical indicators |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861965/ https://www.ncbi.nlm.nih.gov/pubmed/28329788 http://dx.doi.org/10.1093/gerona/glw204 |
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