OBJECTIVE: To determine accuracy of the use of triaxial accelerometry for measuring daily activity as a predictor of maintenance energy requirement (MER) in healthy adult Labrador Retrievers. ANIMALS: 10 healthy adult Labrador Retrievers. PROCEDURES: Dogs wore an accelerometer for two 2-week periods, with data on daily activity successfully collected for 24 to 26 days. These data, along with body weight, were used as independent variables in a multiple linear regression model to predict the dependent variable of daily MER. The predictive accuracy of the model was compared with that of a model that excluded activity. Dietary energy intake at a stated amount of body weight stability was used as an equivalent measure of MER in these analyses. RESULTS: The multiple linear regression model that included body weight and daily activity as independent variables could be used to predict observed MER with a mean absolute error of 63.5 kcal and an SE of estimation of 94.3 kcal. Removing activity from the model reduced the predictive accuracy to a mean absolute error of 129.8 kcal and an SE of estimation of 165.4 kcal. CONCLUSIONS AND CLINICAL RELEVANCE: Use of triaxial accelerometers to provide an independent variable of daily activity yielded a marked improvement in predictive accuracy of the regression model, compared with that for a model that used only body weight. Improved accuracy in estimations of MER could be made for each dog if an accelerometer was used to record its daily activity.
OBJECTIVE: To determine accuracy of the use of triaxial accelerometry for measuring daily activity as a predictor of maintenance energy requirement (MER) in healthy adult Labrador Retrievers. ANIMALS: 10 healthy adult Labrador Retrievers. PROCEDURES: Dogs wore an accelerometer for two 2-week periods, with data on daily activity successfully collected for 24 to 26 days. These data, along with body weight, were used as independent variables in a multiple linear regression model to predict the dependent variable of daily MER. The predictive accuracy of the model was compared with that of a model that excluded activity. Dietary energy intake at a stated amount of body weight stability was used as an equivalent measure of MER in these analyses. RESULTS: The multiple linear regression model that included body weight and daily activity as independent variables could be used to predict observed MER with a mean absolute error of 63.5 kcal and an SE of estimation of 94.3 kcal. Removing activity from the model reduced the predictive accuracy to a mean absolute error of 129.8 kcal and an SE of estimation of 165.4 kcal. CONCLUSIONS AND CLINICAL RELEVANCE: Use of triaxial accelerometers to provide an independent variable of daily activity yielded a marked improvement in predictive accuracy of the regression model, compared with that for a model that used only body weight. Improved accuracy in estimations of MER could be made for each dog if an accelerometer was used to record its daily activity.
Authors: Emma N Bermingham; David G Thomas; Nicholas J Cave; Penelope J Morris; Richard F Butterwick; Alexander J German Journal: PLoS One Date: 2014-10-14 Impact factor: 3.240
Authors: Elizabeth A Bruno; James W Guthrie; Stephen A Ellwood; Richard J Mellanby; Dylan N Clements Journal: PLoS One Date: 2015-02-18 Impact factor: 3.240