When processing free-living accelerometer data, invalid days are typically discarded, potentially resulting in loss of valuable information. The purpose of this semi-simulation study was to compare the accuracy of the conventional method of calculating free-living physical activity (PA) in average counts per day to three methods that can utilize all accelerometer data, including the invalid days (<10 hours per day). National Health and Nutrition Examination Survey data from 2003 to 2006 were used. Age and sample size were included as study conditions. Artificial missing data were created among the participants with 7 days of valid accelerometer data by imposing missing data patterns from a donor matched on age and gender. Results showed that the conventional method of calculating PA levels discarded 26.0% to 28.6% of the data. In most conditions, the within-minute average and day-level imputation method were able to recover the artificially deleted accelerometer counts better than the conventional method. As an exception, the within-minute average method overestimated PA among young people with ≥3 valid days. In conclusion, practitioners are suggested to use the within-minute average method for adults ≥18 years of age, and the day-level imputation method for children and teenagers. To note, the day-level imputation method may be unstable for sample sizes of <50. These methods are particularly useful when the number of valid days is ≤3. Potentially, these methods can allow some participants with insufficient number of valid days to be included in the final analysis.
Hotaka Maeda, Chris C. Cho, Young Cho and Scott J. Strath
Nicholas L. Lerma, Ann M. Swartz, Taylor W. Rowley, Hotaka Maeda and Scott J. Strath
The ill-health effects of sedentary behavior are becoming well-documented, yet older adults spend 70–80% of waking hours sedentary.
To determine if a portable elliptical device increases energy expenditure (EE) while performing popular seated activities.
Twenty older adults (68.1 ± 1.4 years) participated to compare the measured EE between seated rest and three randomized seated pedaling activities: computer use, reading, TV viewing. Each pedaling activity included 5-min of self-selected paced/no resistance (SSP) and externally paced/added resistance pedaling (Paced).
A significant increase in EE existed during SSP (+1.44 ± 0.12 kcal/min) and Paced (+2.19 ± 0.09 kcal/min) pedaling relative to Seated Rest (p < .001). EE during the Paced activities was significantly greater than all SSP activities (p <.01).
Extrapolating these results, pedaling at a SSP for an hour while performing seated activities is equivalent to the net EE of walking 1.6 miles. Future home-based effectiveness and feasibility should be explored.