Although much has been learned about the global determinants of physical activity in adults, there has been a lack of specific focus on gender, age, and urban/rural differences. In this church-based community sample of Appalachian adults (N = 1,239), the primary correlates of physical activity included age, gender, obesity, and self-efficacy. Overall, 42% of all participants and 31% of adults age 65 years or older met recommended guidelines for physical activity, which suggests that most participants do not engage in adequate levels of physical activity. Of participants who met physical activity guidelines, the most common modes of moderate and vigorous activity were walking briskly or uphill, heavy housework or gardening, light strength training, and biking. These particular activities that focus on building self-efficacy might be viable targets for intervention among older adults in rural communities.
Sam Zizzi, Dave Goodrich, Ying Wu, Lindsey Parker, Sheila Rye, Vivek Pawar, Carol Mangone and Irene Tessaro
Emma K. Zadow, Cecilia M. Kitic, Sam S.X. Wu, Stuart T. Smith and James W. Fell
To assess the validity of power output settings of the Wahoo KICKR Power Trainer (KICKR) using a dynamic calibration rig (CALRIG) over a range of power outputs and cadences.
Using the KICKR to set power outputs, powers of 100–999 W were assessed at cadences (controlled by the CALRIG) of 80, 90, 100, 110, and 120 rpm.
The KICKR displayed accurate measurements of power of 250–700 W at cadences of 80–120 rpm with a bias of –1.1% (95% limits of agreement [LoA] –3.6% to 1.4%). A larger mean bias in power was observed across the full range of power tested, 100–999 W (4.2%, 95% LoA –20.1% to 28.6%), due to larger biases of 100–200 and 750–999 W (4.5%, 95% LoA –2.3% to 11.3%, and 13.0%, 95% LoA –24.4% to 50.3%), respectively.
Compared with a CALRIG, the KICKR has acceptable accuracy reporting a small mean bias and narrow LoA in the measurement of power output of 250–700 W at cadences of 80–120 rpm. Caution should be applied by coaches and sports scientists when using the KICKR at power outputs of <200 W and >750 W due to the greater variability in recorded power.
Emma K. Zadow, Cecilia M. Kitic, Sam S.X. Wu and James W. Fell
Purpose: To assess the reliability of power-output measurements of a Wahoo KICKR Power Trainer (KICKR) on 2 separate occasions separated by 14 mo of regular use (∼1 h/wk). Methods: Using the KICKR to set power outputs, powers of 100–600 W in increments of 50 W were assessed at cadences of 80, 90, and 100 rpm that were controlled and validated by a dynamic calibration rig. Results: A small ratio bias of 1.002 (95% limits of agreement [LoA] 0.992–1.011) was observed over 100–600 W at 80–100 rpm between trials 1 and 2. Similar ratio biases with acceptable limits of agreement were observed at 80 rpm (1.003 [95% LoA 0.987–1.018]), 90 rpm (1.000 [0.996–1.005]), and 100 rpm (1.002 [0.997–1.007]). The intraclass correlation coefficient with 95% confidence interval (CI) for mean power between trials was 1.00 (95% CI 1.00–1.00) with a typical error (TE) of 3.1 W and 1.6% observed between trials 1 and 2. Conclusion: When assessed at 2 separate time points 14 mo apart, the KICKR has acceptable reliability for combined power outputs of 100–600 W at 80–100 rpm, reporting overall small ratio biases with acceptable LoA and low TE. Coaches and sport scientists should feel confident in the power output measured by the KICKR over an extended period of time when performing laboratory training and performance assessments.
Harry G. Banyard, James J. Tufano, Jonathon J.S. Weakley, Sam Wu, Ivan Jukic and Kazunori Nosaka
Purpose: To compare the effects of velocity-based training (VBT) and 1-repetition-maximum (1RM) percentage-based training (PBT) on changes in strength, loaded countermovement jump (CMJ), and sprint performance. Methods: A total of 24 resistance-trained males performed 6 weeks of full-depth free-weight back squats 3 times per week in a daily undulating format, with groups matched for sets and repetitions. The PBT group lifted with fixed relative loads varying from 59% to 85% of preintervention 1RM. The VBT group aimed for a sessional target velocity that was prescribed from pretraining individualized load–velocity profiles. Thus, real-time velocity feedback dictated the VBT set-by-set training load adjustments. Pretraining and posttraining assessments included the 1RM, peak velocity for CMJ at 30%1RM (PV-CMJ), 20-m sprint (including 5 and 10 m), and 505 change-of-direction test (COD). Results: The VBT group maintained faster (effect size [ES] = 1.25) training repetitions with less perceived difficulty (ES = 0.72) compared with the PBT group. The VBT group had likely to very likely improvements in the COD (ES = −1.20 to −1.27), 5-m sprint (ES = −1.17), 10-m sprint (ES = −0.93), 1RM (ES = 0.89), and PV-CMJ (ES = 0.79). The PBT group had almost certain improvements in the 1RM (ES = 1.41) and possibly beneficial improvements in the COD (ES = −0.86). Very likely favorable between-groups effects were observed for VBT compared to PBT in the PV-CMJ (ES = 1.81), 5-m sprint (ES = 1.35), and 20-m sprint (ES = 1.27); likely favorable between-groups effects were observed in the 10-m sprint (ES = 1.24) and nondominant-leg COD (ES = 0.96), whereas the dominant-leg COD (ES = 0.67) was possibly favorable. PBT had small (ES = 0.57), but unclear differences for 1RM improvement compared to VBT. Conclusions: Both training methods improved 1RM and COD times, but PBT may be slightly favorable for stronger individuals focusing on maximal strength, whereas VBT was more beneficial for PV-CMJ, sprint, and COD improvements.
Emma K. Zadow, James W. Fell, Cecilia M. Kitic, Jia Han and Sam S. X. Wu
Context: Time of day has been shown to impact athletic performance, with improved performance observed in the late afternoon–early evening. Diurnal variations in physiological factors may contribute to variations in pacing selection; however, research investigating time-of-day influence on pacing is limited. Purpose: To investigate the influence of time-of-day on pacing selection in a 4-km cycling time trial (TT). Methods: Nineteen trained male cyclists (mean [SD] age 39.0 [10.7] y, height 1.8 [0.1] m, body mass 78.0 [9.4] kg, VO2max 62.1 [8.7] mL·kg−1·min−1) completed a 4-km TT on 5 separate occasions at 08:30, 11:30, 14:30, 17:30, and 20:30. All TTs were completed in a randomized order, separated by a minimum of 2 d and maximum of 7 d. Results: No time-of-day effects were observed in pacing as demonstrated by similar power outputs over 0.5-km intervals (P = .78) or overall mean power output (333.0 [38.9], 339.8 [37.2], 335.5 [31.2], 336.7 [35.2], and 334.9 [35.7] W; P = .45) when TTs were performed at 08:30, 11:30, 14:30, 17:30, and 20:30. Preexercise tympanic temperature demonstrated a time-of-day effect (P < .001), with tympanic temperature higher at 14:30 and 17:30 than at 08:30 and 11:30. Conclusion: While a biological rhythm was present in tympanic temperature, pacing selection and performance when completing a 4-km cycling TT were not influenced by time of day. The findings suggest that well-trained cyclists can maintain a robust pacing strategy for a 4-km TT regardless of time of the day.
Sam S.X. Wu, Jeremiah J. Peiffer, Peter Peeling, Jeanick Brisswalter, Wing Y. Lau, Kazunori Nosaka and Chris R. Abbiss
To investigate the effect of 3 swim-pacing profiles on subsequent performance during a sprint-distance triathlon (SDT).
Nine competitive/trained male triathletes completed 5 experimental sessions including a graded running exhaustion test, a 750-m swim time trial (STT), and 3 SDTs. The swim times of the 3 SDTs were matched, but pacing was manipulated to induce positive (ie, speed gradually decreasing from 92% to 73% STT), negative (ie, speed gradually increasing from 73% to 92% STT), or even pacing (constant 82.5% STT). The remaining disciplines were completed at a self-selected maximal pace. Speed over the entire triathlon, power output during the cycle discipline, rating of perceived exertion (RPE) for each discipline, and heart rate during the cycle and run were determined.
Faster cycle and overall triathlon times were achieved with positive swim pacing (30.5 ± 1.8 and 65.9 ± 4.0 min, respectively), as compared with the even (31.4 ± 1.0 min, P = .018 and 67.7 ± 3.9 min, P = .034, effect size [ES] = 0.46, respectively) and negative (31.8 ± 1.6 min, P = .011 and 67.3 ± 3.7 min, P = .041, ES = 0.36, respectively) pacing. Positive swim pacing elicited a lower RPE (9 ± 2) than negative swim pacing (11 ± 2, P = .014). No differences were observed in the other measured variables.
A positive swim pacing may improve overall SDT performance and should be considered by both elite and age-group athletes during racing.