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

ABSTRACT

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 (R2 = 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.