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dc.contributor.authorPowell, Cormack
dc.contributor.authorBrowne, Leonard D.
dc.contributor.authorCarson, Brian P.
dc.contributor.authorDowd, Kieran P.
dc.contributor.authorPerry, Ivan J.
dc.contributor.authorKearney, Patricia M.
dc.contributor.authorHarrington, Janas M.
dc.contributor.authorDonnelly, Alan E.
dc.date.accessioned2019-09-03T08:26:17Z
dc.date.available2019-09-03T08:26:17Z
dc.date.copyright2019
dc.date.issued2019-07-26
dc.identifier.citationPowell C, Browne LD, Carson BP, Dowd KP, Perry IJ, Kearney PM, Harrington JM, Donnelly AE.(2019). Use of compositional analyis to show estimated changes in cardiometabolic health by reallocating time to light intensity physical activity in older adults. Sports Medicine, July 26. doi: 10.1007/s40279-019-01153-2.en_US
dc.identifier.issn1179-2035
dc.identifier.otherArticles - Sports & Health Science AITen_US
dc.identifier.urihttp://research.thea.ie/handle/20.500.12065/2799
dc.description.abstractAbstract Background All physical activity (PA) behaviours undertaken over the day, including sleep, sedentary time, standing time, light-intensity PA (LIPA) and moderate-to-vigorous PA (MVPA) have the potential to influence cardiometabolic health. Since these behaviours are mutually exclusive, standard statistical approaches are unable to account for the impact on time spent in other behaviours. Objective By employing a compositional data analysis (CoDA) approach, this study examined the associations of objectively measured time spent in sleep, sedentary time, standing time, LIPA and MVPA over a 24-h day on markers of cardiometabolic health in older adults. Methods Participants (n =366; 64.6 years [5.3]; 46% female) from the Mitchelstown Cohort Rescreen Study provided meas- ures of body composition, blood lipid and markers of glucose control. An activPAL3 Micro was used to obtain objective measures of sleep, sedentary time, standing time, LIPA and MVPA, using a 7-day continuous wear protocol. Regression analysis, using geometric means derived from CoDA (based on isometric log-ratio transformed data), was used to examine the relationship between the aforementioned behaviours and markers of cardiometabolic health. Results Standing time and LIPA showed diverging associations with markers of body composition. Body mass index (BMI), body mass and fat mass were negatively associated with LIPA (all p <0.05) and positively associated with standing time (all p <0.05). Sedentary time was also associated with higher BMI (p <0.05). No associations between blood markers and any PA behaviours were observed, except for triglycerides, which were negatively associated with standing time (p < 0.05). Reallocating 30 min from sleep, sedentary time or standing time, to LIPA, was associated with significant decreases in BMI, body fat and fat mass. Conclusion This is the first study to employ CoDA in older adults that has accounted for sleep, sedentary time, standing time, LIPA and MVPA in a 24-h cycle. The findings support engagement in LIPA to improve body composition in older adults. Increased standing time was associated with higher levels of adiposity, with increased LIPA associated with reduced adiposity; therefore, these findings indicate that replacing standing time with LIPA is a strategy to lower adiposity.en_US
dc.formatPDFen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofSports Medicineen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/ie/*
dc.subjectPhysical activity - Older adultsen_US
dc.subjectHealth and fitness - Measurementen_US
dc.subjectCompositional data analysisen_US
dc.subjectBody mass index - Older adultsen_US
dc.titleUse of compositional analyis to show estimated changes in cardiometabolic health by reallocating time to light intensity physical activity in older adults.en_US
dc.typeArticleen_US
dc.description.peerreviewyesen_US
dc.identifier.doidoi: 10.1007/s40279-019-01153-2.
dc.identifier.orcidhttps://orcid.org/0000-0002-1841-1604
dc.rights.accessOpen Accessen_US
dc.subject.departmentFaculty of Science and Healthen_US


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Attribution-NonCommercial-NoDerivs 3.0 Ireland
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Ireland