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

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URI: http://hdl.handle.net/10498/28560

DOI: 10.1007/s40520-022-02260-3

ISSN: 1720-8319

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SC2022_673.pdf (1.103Mb)
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Author/s
Matabuena, Marcos; Félix, Paulo; Ali Hammour, Ziad Akram; Mota, Jorge; Pozo Cruz, Borja delAuthority UCA
Date
2022-12
Department
Didáctica de la Educación Física, Plástica y Musical
Source
Aging Clinical and Experimental Research, Vol. 34, Núm. 12, 2022, pp. 3107-3114
Abstract
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 clini- cal 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.
Subjects
Physical activity; Precision medicine; Accelerometry; Distributional representation; Longevity
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  • Artículos Científicos [11595]
  • Articulos Científicos Did. E. Fis. [443]
Atribución 4.0 Internacional
This work is under a Creative Commons License Atribución 4.0 Internacional

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