Deriving objectively-measured sedentary indices from free-living accelerometry data in rural and urban African settings: a cost effective approach.

BMC Res Notes

Physical Activity Epidemiology Laboratory, Faculty of Humanities, University of Limpopo (Turfloop Campus), P.O. Box 459, Fauna Park, Polokwane, Limpopo Province, 0787, South Africa.

Published: September 2019

Objectives: To investigate the agreement between two data reduction approaches for detecting sedentary breaks from uni-axial accelerometry data collected in human participants. Free-living, uni-axial accelerometer data (n = 318) were examined for sedentary breaks using two different methods (Healy-Matthews; MAH/UFFE). The data were cleaned and reduced using MAH/UFFE Analyzer software and custom Microsoft Excel macro's, such that the average daily sedentary break number were calculated for each data record, for both methods.

Results: The Healy-Matthews and MAH/UFFE average daily break number correlated closely (R = 99.9%) and there was high agreement (mean difference: + 0.7 breaks/day; 95% limits of agreement: - 0.06 to + 1.4 breaks/day). A slight bias of approximately + 1 break/day for the MAH/UFFE Analyzer was evident for both the regression and agreement analyses. At a group level there were no statistically or practically significant differences within sample groups between the two methods.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6739927PMC
http://dx.doi.org/10.1186/s13104-019-4606-4DOI Listing

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