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Quest for a summary measure of biological age: the health and retirement study
Measures of biological age and its components have been shown to provide important information about individual health and prospective change in health as there is clear value in being able to assess whether someone is experiencing accelerated or decelerated aging. However, how to best assess biolog...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050146/ https://www.ncbi.nlm.nih.gov/pubmed/33544281 http://dx.doi.org/10.1007/s11357-021-00325-1 |
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author | Crimmins, Eileen M. Thyagarajan, Bharat Kim, Jung Ki Weir, David Faul, Jessica |
author_facet | Crimmins, Eileen M. Thyagarajan, Bharat Kim, Jung Ki Weir, David Faul, Jessica |
author_sort | Crimmins, Eileen M. |
collection | PubMed |
description | Measures of biological age and its components have been shown to provide important information about individual health and prospective change in health as there is clear value in being able to assess whether someone is experiencing accelerated or decelerated aging. However, how to best assess biological age remains a question. We compare prediction of health outcomes using existing summary measures of biological age with a measure created by adding novel biomarkers related to aging to measures based on more conventional clinical chemistry and exam measures. We also compare the explanatory power of summary biological age measures compared to the individual biomarkers used to construct the measures. To accomplish this, we examine how well biological age, phenotypic age, and expanded biological age and five sets of individual biomarkers explain variability in four major health outcomes linked to aging in a large, nationally representative cohort of older Americans. We conclude that different summary measures of accelerated aging do better at explaining different health outcomes, and that chronological age has greater explanatory power for both cognitive dysfunction and mortality than the summary measures. In addition, we find that there is reduction in the variance explained in health outcomes when indicators are combined into summary measures, and that combining clinical indicators with more novel markers related to aging does best at explaining health outcomes. Finally, it is hard to define a set of assays that parsimoniously explains the greatest amount of variance across the range of health outcomes studied here. All of the individual markers considered were related to at least one of the health outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11357-021-00325-1. |
format | Online Article Text |
id | pubmed-8050146 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-80501462021-04-30 Quest for a summary measure of biological age: the health and retirement study Crimmins, Eileen M. Thyagarajan, Bharat Kim, Jung Ki Weir, David Faul, Jessica GeroScience Original Article Measures of biological age and its components have been shown to provide important information about individual health and prospective change in health as there is clear value in being able to assess whether someone is experiencing accelerated or decelerated aging. However, how to best assess biological age remains a question. We compare prediction of health outcomes using existing summary measures of biological age with a measure created by adding novel biomarkers related to aging to measures based on more conventional clinical chemistry and exam measures. We also compare the explanatory power of summary biological age measures compared to the individual biomarkers used to construct the measures. To accomplish this, we examine how well biological age, phenotypic age, and expanded biological age and five sets of individual biomarkers explain variability in four major health outcomes linked to aging in a large, nationally representative cohort of older Americans. We conclude that different summary measures of accelerated aging do better at explaining different health outcomes, and that chronological age has greater explanatory power for both cognitive dysfunction and mortality than the summary measures. In addition, we find that there is reduction in the variance explained in health outcomes when indicators are combined into summary measures, and that combining clinical indicators with more novel markers related to aging does best at explaining health outcomes. Finally, it is hard to define a set of assays that parsimoniously explains the greatest amount of variance across the range of health outcomes studied here. All of the individual markers considered were related to at least one of the health outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11357-021-00325-1. Springer International Publishing 2021-02-05 /pmc/articles/PMC8050146/ /pubmed/33544281 http://dx.doi.org/10.1007/s11357-021-00325-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) . |
spellingShingle | Original Article Crimmins, Eileen M. Thyagarajan, Bharat Kim, Jung Ki Weir, David Faul, Jessica Quest for a summary measure of biological age: the health and retirement study |
title | Quest for a summary measure of biological age: the health and retirement study |
title_full | Quest for a summary measure of biological age: the health and retirement study |
title_fullStr | Quest for a summary measure of biological age: the health and retirement study |
title_full_unstemmed | Quest for a summary measure of biological age: the health and retirement study |
title_short | Quest for a summary measure of biological age: the health and retirement study |
title_sort | quest for a summary measure of biological age: the health and retirement study |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050146/ https://www.ncbi.nlm.nih.gov/pubmed/33544281 http://dx.doi.org/10.1007/s11357-021-00325-1 |
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