Prasangi Dabare, Pujitha Wickramasinghe, Indu Waidyatilaka, Sarita Devi, Anura V Kurpad, Dulani Samaranayake, Maduka de Lanerolle-Dias, Rajitha Wickremasinghe, Andrew P Hills, Pulani Lanerolle
Journal: Nutrients 2023;15(4):906
PMID: 36839264
This study aimed to develop a regression equation to predict physical activity energy expenditure (PAEE) using accelerometry. Children aged 11-13 years were recruited and randomly assigned to validation ( = 54) and cross-validation ( = 25) groups. The doubly labelled water (DLW) technique was used to assess energy expenditure and accelerometers were worn by participants across the same period. A preliminary equation was developed using stepwise multiple regression analysis with sex, height, weight, body mass index, fat-free mass, fat mass and counts per minute (CPM) as independent variables. Goodness-of-fit statistics were used to select the best prediction variables. The PRESS (predicted residual error sum of squares) statistical method was used to validate the final prediction equation. The preliminary equation was cross-validated on an independent group and no significant ( > 0.05) difference was observed in the PAEE estimated from the two methods. Independent variables of the final prediction equation (PAEE = [0.001CPM] - 0.112) accounted for 70.6% of the variance. The new equation developed to predict PAEE from accelerometry was found to be valid for use in Sri Lankan children.
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