Simon M. Gunn

Determining energy expenditure during some household and garden tasks

PURPOSE This study: a) calculated the reproducibility (intraclass correlation coefficient, ICC) and precision (technical error of measurement, TEM) for VO2 during moderate paced walking, self-paced sweeping, window cleaning, vacuuming and lawn mowing; b) determined which of the five activities rated >or= 3.0 when exercise intensity was calculated in METs (1 MET or metabolic equivalent = VO2 of 3.5 mL.kg-1.min-1) and multiples of the measured resting metabolic rate (RMR); and c) expanded the limited database on energy expenditure during household and garden activities. METHODS Twelve men and 12 women (mean +/- SD: 39.3 +/- 3.4 yr; 171.6 +/- 9.6 cm; 81.0 +/- 15.5 kg) were measured for RMR and VO2 during the five activities on two separate days via indirect calorimetry by using the Douglas bag method. RESULTS The interday ICCs and TEMs for the five activities ranged from 0.81 to 0.97 and from 2.1 to 7.0%, respectively. The means were significantly (P < 0.001) above 3.0 for moderate paced walking (range = 3.3-8.7), sweeping (2.9-6.7), window cleaning (3.0-6.0), vacuuming (2.6-4.4), and lawn mowing (4.9-7.5) when VO2 was divided by measured RMR, but one and five subjects scored below 3.0 for sweeping and vacuuming, respectively. Division of exercise VO2 by the convention of 3.5 mL O2.kg-1.min-1 significantly decreased (P < 0.001) each mean, and lawn mowing (5.0 METs) was the only activity where all subjects scored above 3.0 METs (P < 0.001; 3.8-6.4); nevertheless, the means for walking (3.7 METs), sweeping (3.2 METs), and window cleaning (3.6 METs) were also in the moderate intensity category of 3-6 METs. CONCLUSIONS These data: a) emphasize that the VO2 during self-paced moderate intensity walking and self-paced household and garden activities can be measured with reproducibility and precision, b) demonstrate that expressing energy expenditure in conventional METs yields lower values than when it is presented as a multiple of measured RMR, c) suggest that all activities except vacuuming are performed at moderate intensity when energy expenditure is expressed in conventional METs, and d) highlight the biological variability in energy expenditure when different people perform the same task.

Impact of indexing resting metabolic rate against fat-free mass determined by different body composition models

Objective: To examine the differences arising from indexing resting metabolic rate (RMR) against fat-free mass (FFM) determined using two-, three- and four-compartment body composition models.Design: All RMR and body composition measurements were conducted on the same day for each subject following compliance with premeasurement protocols.Subjects: Data were generated from measurements on 104 males (age 32.1±12.1 y (mean±s.d.); body mass 81.15±12.85 kg; height 179.5±6.5 cm; body fat 20.6±7.6%).Interventions: Body density (BD), total body water (TBW) and bone mineral mass (BMM) were measured by hydrodensitometry, deuterium dilution and dual energy X-ray absorptiometry (DXA), respectively. These measures were used to determine two (hydrodensitometry: BD; hydrometry: TBW)-, three (BD and TBW)- and four- compartment (BD, TBW and BMM) FFM values. DXA also provided three compartment derived FFM values. RMR was measured using open circuit indirect calorimetry.Results: Three (body fat group: lean, moderate, high) × five (body composition determination: hydrodensitometry, hydrometry, three-compartment, DXA, four-compartment) ANOVAs were conducted on FFM and RMR kJ.kg FFM−1.d−1. Within-group comparisons revealed that hydrodensitometry and DXA were associated with significant (P<0.001) overestimations and underestimations of FFM and RMR kJ.kg FFM−1.d−1, respectively, compared with four-compartment-derived criterion values. A significant interaction (P<0.001) resulted from DXAs greater deviations from criterion values in lean subjects. While hydrometric means were not significantly (P≥0.68) different from criterion values intraindividual differences were large (FFM: −1.5 to 2.9 kg; RMR: −6.0 to 3.2 kJ.kg FFM-1.d-1).Conclusion: The relationship between RMR kJ.kg FFM−1.d−1 and exercise status would best be investigated using three (BD, TBW)- or four (BD, TBW, BMM)-compartment body composition models to determine FFM. Other models either significantly underestimate indexed RMR (hydrodensitometry, DXA) or display large intraindividual differences (hydrometry) compared with four-compartment derived criterion values.Sponsorship: Australian Research Council (small grants scheme).