Physical activity phenotypes and mortality in older adults: a novel distributional data analysis of accelerometry in the NHANES

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ISSN: 0009-398X
E-ISSN: 1573-3327

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Physical activity is deemed critical to successful ageing. Despite evidence and progress, there is still a need to determine more precisely the direction, magnitude, intensity, and volume of physical activity that should be performed on a daily basis to effectively promote the health of individuals. This study aimed to assess the clinical validity of new physical activity phenotypes derived from a novel distributional functional analysis of accelerometer data in older adults. A random sample of participants aged between 65 and 80 years with valid accelerometer data from the National Health and Nutrition Examination Survey (NHANES) 2011–2014 was used. Five major clinical phenotypes were identified, which provided a greater sensitivity for predicting 5-year mortality and survival outcomes than age alone, and our results confirm the importance of moderate-to-vigorous physical activity. The new clinical physical activity phenotypes are a promising tool for improving patient prognosis and for directing to more targeted intervention planning, according to the principles of precision medicine. The use of distributional representations shows clear advantages over more traditional metrics to explore the effects of the full spectrum of the physical activity continuum on human health

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Matabuena, M., Félix, P., Hammouri, Z.A.A. et al. Physical activity phenotypes and mortality in older adults: a novel distributional data analysis of accelerometry in the NHANES. Aging Clin Exp Res 34, 3107–3114 (2022). https://doi.org/10.1007/s40520-022-02260-3

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Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This research was funded by the Ministry of Science and Innovation of Spain, under Grant No. PID2021-123152OB-C21

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© 2022 The Authors. 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/ublished by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
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