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Mortality risk factors in community-dwelling, subjectively healthy, Swiss older adults: update after 8-years follow-up

BACKGROUND: Worldwide population is ageing, but little is known regarding risk factors associated with increased mortality in subjectively healthy, community-dwelling older adults. We present the updated results of the longest follow-up carried out on Swiss pensioners and we provide results on poten...

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Autores principales: Gutzwiller, Jean-Pierre, Müller-Bolla, Krisztina, Ferrari, Carlo, Stanga, Zeno, Nydegger, Urs E., Risch, Lorenz, Risch, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10189711/
https://www.ncbi.nlm.nih.gov/pubmed/37198577
http://dx.doi.org/10.1186/s12877-023-03959-2
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author Gutzwiller, Jean-Pierre
Müller-Bolla, Krisztina
Ferrari, Carlo
Stanga, Zeno
Nydegger, Urs E.
Risch, Lorenz
Risch, Martin
author_facet Gutzwiller, Jean-Pierre
Müller-Bolla, Krisztina
Ferrari, Carlo
Stanga, Zeno
Nydegger, Urs E.
Risch, Lorenz
Risch, Martin
author_sort Gutzwiller, Jean-Pierre
collection PubMed
description BACKGROUND: Worldwide population is ageing, but little is known regarding risk factors associated with increased mortality in subjectively healthy, community-dwelling older adults. We present the updated results of the longest follow-up carried out on Swiss pensioners and we provide results on potential risk factors associated with mortality before the onset of the COVID-19 pandemic. MATERIALS AND METHODS: Within the SENIORLAB study, we collected demographic data, anthropometric measures, medical history, and laboratory parameters of 1467 subjectively healthy, community-dwelling, Swiss adults aged ≥ 60 years over a median follow-up of 8.79 years. The variables considered in the multivariable Cox-proportional hazard model for mortality during follow-up were selected based on prior knowledge. Two separate models for males and females were calculated; moreover, we fitted the old model obtained in 2018 to the complete follow-up data to highlight differences and similarities. RESULTS: The population sample included 680 males and 787 females. Age of participants ranged between 60 and 99 years. We experienced 208 deaths throughout the entire follow-up period; no patients were lost at follow-up. The Cox-proportional hazard regression model included female gender, age, albumin levels, smoking status, hypertension, osteoporosis and history of cancer within predictors of mortality over the follow-up period. Consistent findings were obtained also after gender stratification. After fitting the old model, female gender, hypertension, and osteoporosis still showed statistically significant independent associations with all-cause mortality. CONCLUSIONS: Understanding the predictors of a healthy survival can improve the overall quality of life of the ageing population and simultaneously reduce their global economic burden. TRIAL REGISTRATION: The present study was registered in the International Standard Randomized Controlled Trial Number registry: https://www.isrctn.com/ISRCTN53778569 (registration date: 27/05/2015).
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spelling pubmed-101897112023-05-18 Mortality risk factors in community-dwelling, subjectively healthy, Swiss older adults: update after 8-years follow-up Gutzwiller, Jean-Pierre Müller-Bolla, Krisztina Ferrari, Carlo Stanga, Zeno Nydegger, Urs E. Risch, Lorenz Risch, Martin BMC Geriatr Research BACKGROUND: Worldwide population is ageing, but little is known regarding risk factors associated with increased mortality in subjectively healthy, community-dwelling older adults. We present the updated results of the longest follow-up carried out on Swiss pensioners and we provide results on potential risk factors associated with mortality before the onset of the COVID-19 pandemic. MATERIALS AND METHODS: Within the SENIORLAB study, we collected demographic data, anthropometric measures, medical history, and laboratory parameters of 1467 subjectively healthy, community-dwelling, Swiss adults aged ≥ 60 years over a median follow-up of 8.79 years. The variables considered in the multivariable Cox-proportional hazard model for mortality during follow-up were selected based on prior knowledge. Two separate models for males and females were calculated; moreover, we fitted the old model obtained in 2018 to the complete follow-up data to highlight differences and similarities. RESULTS: The population sample included 680 males and 787 females. Age of participants ranged between 60 and 99 years. We experienced 208 deaths throughout the entire follow-up period; no patients were lost at follow-up. The Cox-proportional hazard regression model included female gender, age, albumin levels, smoking status, hypertension, osteoporosis and history of cancer within predictors of mortality over the follow-up period. Consistent findings were obtained also after gender stratification. After fitting the old model, female gender, hypertension, and osteoporosis still showed statistically significant independent associations with all-cause mortality. CONCLUSIONS: Understanding the predictors of a healthy survival can improve the overall quality of life of the ageing population and simultaneously reduce their global economic burden. TRIAL REGISTRATION: The present study was registered in the International Standard Randomized Controlled Trial Number registry: https://www.isrctn.com/ISRCTN53778569 (registration date: 27/05/2015). BioMed Central 2023-05-17 /pmc/articles/PMC10189711/ /pubmed/37198577 http://dx.doi.org/10.1186/s12877-023-03959-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Gutzwiller, Jean-Pierre
Müller-Bolla, Krisztina
Ferrari, Carlo
Stanga, Zeno
Nydegger, Urs E.
Risch, Lorenz
Risch, Martin
Mortality risk factors in community-dwelling, subjectively healthy, Swiss older adults: update after 8-years follow-up
title Mortality risk factors in community-dwelling, subjectively healthy, Swiss older adults: update after 8-years follow-up
title_full Mortality risk factors in community-dwelling, subjectively healthy, Swiss older adults: update after 8-years follow-up
title_fullStr Mortality risk factors in community-dwelling, subjectively healthy, Swiss older adults: update after 8-years follow-up
title_full_unstemmed Mortality risk factors in community-dwelling, subjectively healthy, Swiss older adults: update after 8-years follow-up
title_short Mortality risk factors in community-dwelling, subjectively healthy, Swiss older adults: update after 8-years follow-up
title_sort mortality risk factors in community-dwelling, subjectively healthy, swiss older adults: update after 8-years follow-up
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10189711/
https://www.ncbi.nlm.nih.gov/pubmed/37198577
http://dx.doi.org/10.1186/s12877-023-03959-2
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