The SWA and IC EE rates were strongly correlated during sedentary and light activity office behaviors. However, the SWA may under predict EE during office work (standing or sitting) and when standing motionless, making it slightly less sensitive than IC.

George, JD, Tolley, JR, Vehrs, PR, Reece, JD, Akay, MF, and Cambridge, EDJ. New approach in assessing core muscle endurance using ratings of perceived exertion. J Strength Cond Res 32(4): 1081-1088, 2018-This study sought to develop regression models to estimate maximal endurance time using data from 4 core muscle endurance tests. Eighty healthy university students (age: 22.7 ± 1.9 years) performed the plank, right side-bridge, left side-bridge, and back extension tests in a random order. Participants were instructed to hold each static position for a maximal endurance time, while maintaining proper form, and then rest for 5 minutes between tests. A test administrator recorded participants' ratings of perceived exertion (RPE; a modified 10-point scale) every 5 seconds. Based on regression analysis, the elapsed time to reach an RPE of 8 (RPE8) exhibited statistical significance (p < 0.0001) and the highest accuracy as compared with lower RPE values. The following univariate regression models were generated to estimate maximal endurance time across the 4 tests: plank (r = 0.94; standard error of estimate [SEE] = 17.6 seconds; n = 77) = 23.9 + (1.110 × RPE8); right side-bridge (r = 0.92; SEE = 11.4 seconds; n = 80) = 18.5 + (1.022 × RPE8); left side-bridge (r = 0.93; SEE = 10.8 seconds; n = 80) = 16.8 + (1.062 × RPE8); and back extension (r = 0.93; SEE = 14.2 seconds; n = 79) = 21.5 + (1.027 × RPE8). These results suggest that submaximal protocols based on elapsed time to reach RPE8 provide strength and conditioning professionals relatively accurate univariate regression equation estimates of maximal core muscle endurance time and offer a viable submaximal alternative to maximal capacity testing when time efficiency, participant safety, or certain educational objectives may be a priority.

Objective: To compile and quantify the effectiveness of accumulated short-bout exercise interventions on reducing the obesity indices in adults using meta-analysis. Data Source: PubMed, PsycINFO, CINAHL, Cochrane Library, and SportDiscus. Study Inclusion and Exclusion Criteria: (1) Description of a short-bout exercise trial (<30 minutes); (2) obesity indices must be measured pre- and postintervention; and (3) only adults and published in English. Data Extraction: Two independent reviewers extracted data and assessed the quality of the studies included. Of 3257 articles retrieved, 18 studies met the inclusion criteria. Based on the Downs and Black checklist, the methodological quality of the included studies was fairly robust. Data Synthesis: Pooled effect sizes (ESs) were calculated using a random effects model. Results: Average intervention length was approximately 16 weeks (ranged from 4 to 72 weeks). All weighted mean ES values for each obesity index measure were non-negative, ranging from small to large (ES = 0.33-0.96) in magnitude. Weighted mean ES for body mass (BM; n = 18; ES = 0.51, 95% confidence interval [CI] = 0.22-0.80), body mass index (BMI; n = 13; ES = 0.61, 95% CI = 0.24-0.97), waist circumference (n = 9; ES = 0.44, 95% CI = 0.15-0.73), body fat percentage (BF%; n = 8; ES = 0.33, 95% CI = 0.09-0.58), skinfold (n = 7; ES = 0.96, 95% CI = 0.39 -1.53), and fat mass (FM; n = 6; ES = 0.55, 95% CI = 0.21-0.90) were statistically significant. Moderator effects of intervention length (weeks) were observed for BM (Qbetween [Cochran’s Q: a measure of heterogeneity between studies] = 6.83, P < .05); BMI (Qbetween = 13.93, P < .05); and FM (Qbetween = 10.41, P < .05). Intervention length >10 weeks was more effective than shorter (≤10) intervention period for reducing BM, BMI, and FM. Conclusion: Accumulated short bouts of exercise have a beneficial effect on reducing the obesity indices among adults. The current study can help health researchers and practitioners in designing their intervention programs, which can be applied within schools, clinics, and communities.

It is difficult for developers, researchers, and consumers to compare results among emerging wearable technology without using a uniform set of standards. This study evaluated the accuracy of commercially available wearable technology heart rate (HR) monitors using the Consumer Technology Association (CTA) standards. Participants (N = 23) simultaneously wore a Polar chest strap (criterion measure), Jabra Elite earbuds, Scosche Rhythm 24 armband, Apple Watch 4, and Garmin Forerunner 735 XT during sitting, activities of daily living, walking, jogging, running, and cycling, totaling 57 min of monitored activity. The Apple Watch mean bias was within ±1 bpm, and mean absolute percent error (MAPE) was <3% in all six conditions. Garmin underestimated HR in all conditions, except cycling and MAPE was >10% during sedentary, lifestyle, walk-jog, and running. The Jabra mean bias was within ±5 bpm for each condition, and MAPE exceeded 10% for walk-jog. The Scosche mean bias was within ±1 bpm and MAPE was <5% for all conditions. In conclusion, only the Apple Watch Series 4 and the Scosche Rhythm 24 displayed acceptable agreement across all conditions. By employing CTA standards, future developers, researchers, and consumers will be able to make true comparisons of accuracy among wearable devices.

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