2026-06-14T03:29:41Zhttps://repisalud.isciii.es/rest/oai/requestoai:repisalud.isciii.es:20.500.12105/71592025-05-07T09:31:31Zcom_20.500.12105_15322com_20.500.12105_2051com_20.500.12105_2052col_20.500.12105_16981col_20.500.12105_19618
Repisalud
author
Martinez-Nicolas, A
author
Madrid, J A
author
García, F J
author
Campos, M
author
Moreno-Casbas, Teresa
author
Almaida-Pagán, P F
author
Lucas-Sánchez, A
author
Rol, Maria-Angeles
funder
Ministerio de Economía y Competitividad (España)
funder
Instituto de Salud Carlos III
2019-02-11T11:10:49Z
2019-02-11T11:10:49Z
2018-10-09
Sci Rep. 2018 Oct 9;8(1):15027
10.1038/s41598-018-33195-3
2045-2322
Scientific reports
30301951
http://hdl.handle.net/20.500.12105/7159
The ageing process is associated with sleep and circadian rhythm (SCR) frailty, as well as greater sensitivity to chronodisruption. This is essentially due to reduced day/night contrast, decreased sensitivity to light, napping and a more sedentary lifestyle. Thus, the aim of this study is to develop an algorithm to identify a SCR phenotype as belonging to young or aged subjects. To do this, 44 young and 44 aged subjects were recruited, and their distal skin temperature (DST), activity, body position, light, environmental temperature and the integrated variable TAP rhythms were recorded under free-living conditions for five consecutive workdays. Each variable yielded an individual decision tree to differentiate between young and elderly subjects (DST, activity, position, light, environmental temperature and TAP), with agreement rates of between 76.1% (light) and 92% (TAP). These decision trees were combined into a unique decision tree that reached an agreement rate of 95.3% (4 errors out of 88, all of them around the cut-off point). Age-related SCR changes were very significant, thus allowing to discriminate accurately between young and aged people when implemented in decision trees. This is useful to identify chronodisrupted populations that could benefit from chronoenhancement strategies.
eng
Circadian monitoring as an aging predictor
research article
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URL
https://repisalud.isciii.es/bitstreams/39e4541d-3a24-43a6-ab2c-69db7f59ac68/download
File
MD5
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application/pdf
CircadiangMonitoringAgingPredictor_2018.pdf
URL
https://repisalud.isciii.es/bitstreams/e36bb53c-dd6b-45da-bdaa-240db9490904/download
File
MD5
ee279586f55b81399ad2ee2424b47032
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text/plain
CircadiangMonitoringAgingPredictor_2018.pdf.txt