Measurement and prediction of energy expenditure in males during household and garden tasks

Participation in at least 30 min of moderate intensity activity on most days is assumed to confer health benefits. This study accordingly determined whether the more vigorous household and garden tasks (sweeping, window cleaning, vacuuming and lawn mowing) are performed by middle-aged men at a moderate intensity of 3-6 metabolic equivalents (METs) in the laboratory and at home. Measured energy expenditure during self-perceived moderate-paced walking was used as a marker of exercise intensity. Energy expenditure was also predicted via indirect methods. Thirty-six males [Xmacr (SD): 40.0 (3.3) years; 179.5 (6.9) cm; 83.4 (14.0) kg] were measured for resting metabolic rate (RMR) and oxygen consumption (V.O-2) during the five activities using the Douglas bag method. Heart rate , respiratory frequency, CSA (Computer Science Applications) movement counts, Borg scale ratings of perceived exertion and Quetelet's index were also recorded as potential predictors of exercise intensity. Except for vacuuming in the laboratory, which was not significantly different from 3.0 METs (P=0.98), the MET means in the laboratory and home were all significantly greater than 3.0 (Pless than or equal to0.006). The sweeping and vacuuming MET means were significantly higher (P

Predictive validity of three ActiGraph energy expenditure equations for children

Purpose: This Study evaluated the predictive validity of three previously published ActiGraph energy expenditure (EE) prediction equations developed for children and adolescents. Methods: A total of 45 healthy children and adolescents (mean age: 13.7 +/- 2.6 yr) completed four 5-min activity trials (normal walking. brisk walking, easy running, and fast running) in ail indoor exercise facility. During each trial, participants were all ActiGraph accelerometer oil the right hip. EE was monitored breath by breath using the Cosmed K4b(2) portable indirect calorimetry system. Differences and associations between measured and predicted EE were assessed using dependent t-tests and Pearson correlations, respectively. Classification accuracy was assessed using percent agreement, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve, Results: None of the equations accurately predicted mean energy expenditure during each of the four activity trials. Each equation, however, accurately predicted mean EE in at least one activity trial. The Puyau equation accurately predicted EE during slow walking. The Trost equation accurately predicted EE during slow running. The Freedson equation accurately predicted EE during fast running. None of the three equations accurately predicted EE during brisk walking. The equations exhibited fair to excellent classification accuracy with respect to activity intensity. with the Trost equation exhibiting the highest classification accuracy and the Puyau equation exhibiting the lowest. Conclusions: These data suggest that the three accelerometer prediction equations do not accurately predict EE on a minute-by-minute basis in children and adolescents during overground walking and running. The equations maybe, however, for estimating participation in moderate and vigorous activity.

Energy derivative market and derivative pricing via simulation

The deregulation of power industry worldwide has delivered the efficiency gains to the society; meanwhile, the intensity of competition has increased uncertainty and risks to market participants. Consequently, market participants are keen to hedge the market risks and maintain a competitive edge in the market; and this is a good explanation to the flourish of electricity derivative market. In this paper, the authors gave a comprehensive review of derivative contract pricing methods and proposed a new framework for energy derivative pricing to suit the needs of a deregulated electricity market