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dc.contributor.authorHicks, Hilary
dc.contributor.authorLosinski, Genna
dc.contributor.authorThangwaritorn, Pilar
dc.contributor.authorLaffer, Alex
dc.contributor.authorWatts, Amber
dc.date.accessioned2023-02-09T19:19:39Z
dc.date.available2023-02-09T19:19:39Z
dc.date.issued2022-12-20
dc.identifier.citationHilary Hicks, Genna Losinski, Pilar Thangwaritorn, Alex Laffer, Amber Watts, USING ACTIGRAPHY TO ASSESS CHRONOTYPE AND PHYSICAL ACTIVITY IN OLDER ADULTS, Innovation in Aging, Volume 6, Issue Supplement_1, November 2022, Page 646, https://doi.org/10.1093/geroni/igac059.2390en_US
dc.identifier.urihttp://hdl.handle.net/1808/33762
dc.description.abstractChronotype refers to the time of day that people prefer to be active or to sleep and varies predictably across the lifespan. In younger samples, the morning-chronotype is related to greater levels of physical activity (PA) and improved health outcomes. It is unclear whether this pattern holds in older adults, a group that commonly exhibits an “early bird” preference. We investigated differences in PA patterns between chronotypes in 109 older adults (Mage = 70.45 years) using wrist-worn ActiGraphs in a free-living environment. ActiGraphs captured data about PA and sleep using a novel approach to measuring chronotype with the mid-point of the sleep interval. We categorized participants as morning-, intermediate-, or evening-chronotypes. We used ANCOVA to predict total and average peak PA from chronotype, adjusting for age, sex, education, and BMI. Total PA significantly differed between chronotypes such that evening-types engaged in less PA than both morning- and intermediate-types, F (2,102) = 4.377, p =.015. Average peak activity did not differ between chronotypes, p =.112. Consistent with findings in younger samples, our evening type participants engaged in less overall activity. A unique finding was that evening-types did not differ from their morning- and intermediate-chronotype peers in peak activity levels. This implies a key distinction between total activity and peak activity levels consistent with recent trends in PA research using a 24-hour-a-day framework instead of average or total activity levels. Future research should consider whether these differences in activity patterns translate into meaningful differences in health benefits in this age group.en_US
dc.publisherOxford University Pressen_US
dc.rights© The Author(s) 2022. Published by Oxford University Press on behalf of The Gerontological Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution License.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.titleUsing Actigraphy to Assess Chronotype and Physical Activity in Older Adultsen_US
dc.typeArticleen_US
kusw.kuauthorHicks, Hilary
kusw.kuauthorLosinski, Genna
kusw.kuauthorThangwaritorn, Pilar
kusw.kuauthorLaffer, Alex
kusw.kuauthorWatts, Amber
kusw.kudepartmentPsychologyen_US
dc.identifier.doi10.1093/geroni/igac059.2390en_US
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.identifier.pmidPMC9766216en_US
dc.rights.accessrightsopenAccessen_US


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© The Author(s) 2022. Published by Oxford University Press on behalf of The Gerontological Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution License.
Except where otherwise noted, this item's license is described as: © The Author(s) 2022. Published by Oxford University Press on behalf of The Gerontological Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution License.