Individually tailored, Internet-mediated PA interventions are an effective way to significantly increase PA in older adults.

There are many research studies documenting the validity and intervention effectiveness of consumer-WPAMs; evidence is emerging on the health benefits linked to use of such devices. Future work on the long-term effects of consumer-WPAMs on behavior and health is warranted, and prospects appear exciting as wearable technology advances and adoption increases.

This study examined the effects of a 12 week, treadmill-based, run sprint interval training (SIT) protocol compared with that of a moderate-intensity continuous training (MICT) protocol in healthy, inactive, overweight/obese women, on cardiovascular disease risk factors. After random assignment, the SIT group completed 4-10 × 30 s maximal sprints, with a 4 min active recovery between sprints, and the MICT group completed 30-60 min at moderate intensity (45-55% heart rate reserve (HRR)). The rate of perceived exertion (RPE) was recorded for each session, and perceived enjoyment was quantified every 3 weeks. Clinical and fitness testing were completed at baseline, 6 weeks, and 12 weeks. Twelve female participants (age: 34.1 ± 6.1; body mass index (BMI): 31.3 ± 6.8; VO 2peak : 27.0 ± 6.2) completed the intervention. There were significant main effects for time for VO 2peak (p = 0.001), body fat percentage (p = 0.001), and session RPE (p = 0.006). VO 2peak improved 20.7% in the SIT group (n = 5) and 24.4% in the MICT group (n = 7). Body fat percentage reduced by 1.7% in the SIT group and 2.6% in the MICT group. Perceived enjoyment was similarly high between the groups despite higher session RPE in the SIT group (p = 0.441). SIT training on a motor-driven treadmill elicits similar improvements in oxygen utilization and body composition as moderate-intensity training in this population.

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.

Introduction Field tests to estimate maximal oxygen consumption (VO2max) are an alternative to traditional exercise testing methods. Published field tests and their accompanying estimation equations account for up to 80% of the variance in VO2max with an error rate of ~4.5 ml.kg-1.min-1. These tests are limited to very specific age-range populations. The purpose of this study was to create and validate a series of easily administered walking and stepping field equations to predict VO2max across a range of healthy 18-79-year-old adults. Methods One-hundred-fifty-seven adults completed a graded maximal exercise test to assess VO2max. Five separate walking and three separate stepping tests of varying durations, number of stages, and intensities were completed. VO2max estimation equations were created using hierarchal multiple regression. Covariates including age, sex, body mass, resting heart rate, distance walked, gait speed, stepping cadence, and recovery heart rate were entered into each model using a stepwise approach. Each full model created had the same base model consisting of age, sex, and body mass. Validity of each model was assessed using a Jackknife cross-validation analysis, and percent bias and root mean square error (RMSE) were calculated. Results Base models accounted for ~72% of the total variance of VO2max. Full model variance ranged from ~79–83% and bias was minimal (<±1.0%) across models. RMSE for all models were approximately 4.5 ml.kg-1.min-1. Stepping tests performed better than walking tests by explaining ~2.5% more of the variance and displayed smaller RMSE. Conclusion All eight models accounted for a large percentage of VO2max variance (~81%) with a RMSE of ~4.5 ml.kg-1.min-1. The variance and level of error of models examined highlight good group mean prediction with greater error expected at the individual level. All the models perform similarly across a broad age range, highlighting flexibility in application of these tests to a more general population.