RMA DelaysOur Admin Portal website is currently experiencing technical difficulties, and it could result in delays with RMAs being processed. We are currently working to resolve these issues. We apologize for the inconvenience.
Join us on August 11th for an ActiGraph webinar hosted by Xtalks:
Oncology Research and Care: Reimagining Digital InnovationRegister Now
The Energy Cost of Household and Garden Activities in 55- to 65-year-old Males
- Published on 07/2005
This study measured the energy expenditure of four self-paced household and garden tasks to determine whether 55- to 65-year-old men performed them at a moderate intensity [3-6 metabolic equivalents (METs)] and to predict the activity intensity via indirect methods. Resting metabolic rate and oxygen consumption were measured using Douglas bags in 50 men (X +/- SD: 60.6 +/-3.2 years, 175.8 +/- 5.6 cm, 82.6 +/- 10.1 kg) who performed self-perceived moderate paced walking and self-paced sweeping, window cleaning, vacuuming and lawn mowing. Heart rate, CSA accelerometer counts (hip and arm), Quetelet’s index, Borg rating of perceived exertion and respiratory frequency were measured as possible predictors of energy expenditure. Each of the four household and garden activities was performed at a mean intensity of > or = 3.0 METs in both the standardised laboratory environment (sweeping = 3.4, window cleaning = 3.8, vacuuming = 3.0 and lawn mowing = 5.3 METs) and the subjects’ homes (sweeping = 4.1, window cleaning = 3.5, vacuuming = 3.6 and lawn mowing = 5.0 METs). Comparisons between the two settings were significantly different (p < or =0.008). Except for window cleaning, the MET values were not different from those of our previous younger sample (35-45 years). Regression analysis yielded prediction equations with 95% confidence intervals of +/-0.8 METs for both the laboratory and home environments. Although the energy expenditure means for these activities indicate that they can contribute to the 30 min·day-1 of moderate intensity physical activity required to confer health benefits, there was substantial inter-individual variability. While the regression equations lack predictive precision at the individual level, they were able to determine whether energy expenditure was above the 3.0 MET threshold with correct classification rates of 91% and 94% in the laboratory and home, respectively.
Link to Abstract: http://www.ncbi.nlm.nih.gov/pubmed/15815941
European Journal of Applied Physiology