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Jeanette Gustat, Christopher E. Anderson, Keelia O’Malley, Tian Hu, Rachel G. Tabak, Karin Valentine Goins, Cheryl Valko, Jill S. Litt and Amy A. Eyler

Background: To assess how perceptions of the community built environment influence support for community policies that promote physical activity (PA). Methods: A national cross-sectional survey assessed perceptions of the local built environment and support of community policies, including school and workplace policies, promoting PA. A random digit–dialed telephone survey was conducted in US counties selected on Behavioral Risk Factor Surveillance System data for high or low prevalence of obesity and inactivity. A total of 1208 subjects were interviewed, 642 from high-prevalence counties and 566 from low-prevalence counties. Analyses were stratified by county prevalence of obesity and inactivity (high or low). Linear models adjusted for covariates were constructed to assess the influence of built environment perceptions on policy support. Results: Perception of more destinations near the residence was associated with increased support for community policies that promote PA, including tax increases in low-prevalence (obesity and inactivity) counties (P < .01). Positive perception of the workplace environment was associated (P < .001) with increased support for workplace policies among those in high-, but not low-, prevalence counties. Conclusions: Support for community policies promoting PA varies by perception of the built environment, which has implications for policy change.

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Katrina M. Moss, Annette J. Dobson, Kimberley L. Edwards, Kylie D. Hesketh, Yung-Ting Chang and Gita D. Mishra

Background: Play equipment at home could be targeted in interventions to increase children’s physical activity (PA), but evidence is mixed, potentially because current methods do not reflect children’s lived experience. This study investigated associations between combinations of equipment and PA. Methods: Data were from the Mothers and their Children’s Health study and the Australian Longitudinal Study on Women’s Health. Mothers (n = 2409) indicated the types of fixed active (eg, trampolines), portable active (eg, bicycles), and electronic (eg, computers) equipment at home, and the number of days children (n = 4092, aged 5–12 y, 51% boys) met PA guidelines. Latent class analysis was used to identify combinations of equipment, and linear regressions were used to investigate associations with PA. Results: Compared with children with high active (fixed and portable) and medium electronic equipment, children with portable active and medium (B = −0.53; 95% confidence interval, −0.72 to −0.34) or high (B = −0.58; 95% confidence interval, −0.83 to −0.33) electronic equipment met the guidelines on fewer days. Children with similar active equipment (but more electronic equipment) met the PA guidelines on fewer days (mean difference = −0.51, SE = 0.14, P = .002). Conclusion: Having the right combination of play equipment at home may be important for children’s PA.

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Kristy Martin, Kevin G. Thompson, Richard Keegan and Ben Rattray

The aim of this study was to investigate whether individuals who engage in more frequent self-regulation are less susceptible to mental fatigue. Occupational cognitive demand and participation in sports or exercise were quantified as activities requiring self-regulation. Cardiorespiratory fitness was also assessed. On separate occasions, participants either completed 90 min of an incongruent Stroop task (mental exertion condition) or watched a 90-min documentary (control condition). Participants then completed a cycling time-to-exhaustion (physical endurance) test. There was no difference in the mean time to exhaustion between conditions, although individual responses varied. Occupational cognitive demand, participation in sports or exercise, and cardiorespiratory fitness predicted the change in endurance performance (p = .026, adjusted R 2 = .279). Only cognitive demand added significantly to the prediction (p = .024). Participants who reported higher levels of occupational cognitive demand better maintained endurance performance following mental exertion.

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Kim Gammage, Rachel Arnold, Lori Dithurbide, Alison Ede, Karl Erickson, Blair Evans, Larkin Lamarche, Sean Locke, Eric Martin and Kathleen Wilson

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Ian M. Greenlund, Piersan E. Suriano, Steven J. Elmer, Jason R. Carter and John J. Durocher

Background: Sedentary activity and sitting for at least 10 hours per day can increase the risk for cardiovascular disease by more than 60%. Use of standing desks may decrease sedentary time and improve cardiovascular health. Acute standing lowers pulse wave velocity (PWV), but chronic effects remain unknown. The purpose of this study was to determine the effect of chronic standing desk use on arterial stiffness versus seated controls. Methods: A total of 48 adults participated in this study. Twenty-four participants qualified as seated desk users (age 41 [10] y, body mass index 25 [4] kg/m2) and 24 as standing desk users (age 45 [12] y, body mass index 25 [5] kg/m2). Arterial stiffness was assessed as PWV within the aorta, arm, and leg. Results: Carotid–femoral PWV (cfPWV) was not different between seated (6.6 [1.3] m/s) and standing (6.9 [1.3] m/s) groups (P = .47). Similarly, there were no differences in arm or leg PWV between groups (P = .13 and P = .66, respectively). A secondary analysis of traditional factors of age and aerobic fitness revealed significant differences in cfPWV in seated and standing desk participants. Age also significantly influenced cfPWV across conditions. Conclusions: Standing for >50% of a workday did not affect PWV. Consistent with previous research, fitness and age are important modulators of arterial stiffness.

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Dylan C. Perry, Christopher C. Moore, Colleen J. Sands, Elroy J. Aguiar, Zachary R. Gould, Catrine Tudor-Locke and Scott W. Ducharme

Background: While previous studies indicate an auditory metronome can entrain cadence (in steps per minute), music may also evoke prescribed cadences and metabolic intensities. Purpose: To determine how modulating the tempo of a single commercial song influences adults’ ability to entrain foot strikes while walking and how this entrainment affects metabolic intensity. Methods: Twenty healthy adults (10 men and 10 women; mean [SD]: age 23.7 [2.7] y, height 172.8 [9.0] cm, mass 71.5 [16.2] kg) walked overground on a large circular pathway for six 5-min conditions; 3 self-selected speeds (slow, normal, and fast); and 3 trials listening to a song with its tempo modulated to 80, 100, and 125 beats per minute. During music trials, participants were instructed to synchronize their step timing with the music tempo. Cadence was measured via direct observation, and metabolic intensity (metabolic equivalents) was assessed using indirect calorimetry. Results: Participants entrained their cadences to the music tempos (mean absolute percentage error = 5.3% [5.8%]). Entraining to a music tempo of 100 beats per minute yielded ≥3 metabolic equivalents in 90% of participants. Trials with music entrainment exhibited greater metabolic intensity compared with self-paced trials (repeated-measures analysis of variance, F 1,19 = 8.05, P = .01). Conclusion: This study demonstrates the potential for using music to evoke predictable metabolic intensities.

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Kayla J. Nuss, Joseph L. Sanford, Lucas J. Archambault, Ethan J. Schlemer, Sophie Blake, Jimikaye Beck Courtney, Nicholas A. Hulett and Kaigang Li

Background: The purpose of this study was to examine the accuracy of heart rate (HR) and energy expenditure (EE) estimated by the Apple Watch Series 1 worn both on the wrist and the upper arm. Methods: Thirty healthy, young adults (15 females) wore the two monitors while participating in a maximal exercise test. Criterion measures were obtained from the Parvo Medics TrueOne 2400 Metabolic Cart and an electrocardiograph. Results: The HR estimations of the arm-worn (AW) Apple Watch had the highest agreement with the electrocardiogram, with mean absolute percent error (MAPE) of <2.5% for the entire sample, for males, and for females, at all exercise intensities. The HR estimations of the wrist-worn Apple Watch had MAPEs ranging from 3.61% (females at very light intensity) to 14.97% (males at very vigorous intensity). When estimating EE for total exercise bout in the entire sample, the arm-worn Apple Watch overestimated EE, with a MAPE of 39.63%, whereas the wrist-worn underestimated EE, with a MAPE of 32.28%. Both the arm- and wrist-worn overestimated EE for females and underestimated EE for males. Conclusion: Wearing the Apple Watch Series 1 on the upper arm versus the wrist improves the MAPE for HR estimations, but does not improve MAPE for the EE calculations when compared to a criterion measure.

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Alexander H.K. Montoye, Jordana Dahmen, Nigel Campbell and Christopher P. Connolly

Purpose: This purpose of this study was to validate consumer-based and research-grade PA monitors for step counting and Calorie expenditure during treadmill walking. Methods: Participants (n = 40, 24 in second trimester and 16 in third trimester) completed five 2-minute walking activities (1.5–3.5 miles/hour in 0.5 mile/hour increments) while wearing five PA monitors (right hip: ActiGraph Link [AG]; left hip: Omron HJ-720 [OM]; left front pants pocket: New Lifestyles NL 2000 [NL]; non-dominant wrist: Fitbit Flex [FF]; right ankle: StepWatch [SW]). Mean absolute percent error (MAPE) was used to determine device accuracy for step counting (all monitors) and Calorie expenditure (AG with Freedson equations and FF) compared to criterion measures (hand tally for steps, indirect Calorimetry for Calories). Results: For step counting, the SW had MAPE ≤ 10% at all walking speeds, and the OM and NL had MAPE ≤ 10% for all speeds but 1.5 miles/hour. The AG had MAPE ≤ 10% for only 3.0–3.5 miles/hour speeds, and the FF had high MAPE for all speeds. For Calories, the FF and AG had MAPE > 10% for all speeds, with the FF overestimating Calories expended. Trimester did not affect PA monitor accuracy for step counting but did affect accuracy for Calorie expenditure. Conclusion: The ankle-worn SW and hip-worn OM had high accuracy for measuring step counts at all treadmill walking speeds, whereas the NL had high accuracy for speeds ≥2.0 miles/hour. Conversely, the monitors tested for Calorie expenditure have poor accuracy and should be interpreted cautiously for walking behavior.

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Alexandra Valencia-Peris, Joan Úbeda-Colomer, Jorge Lizandra, Carmen Peiró-Velert and José Devís-Devís

Background: Active gaming has emerged as a new option to foster physical activity in youth. The aim of this study was to estimate the prevalence of active gaming in adolescents, to determine differences between active and nonactive gamers by type of day, and to examine predictors of being an active gamer. Methods: A cross-sectional study was conducted with 3095 Spanish adolescents aged 12 to 18 years who self-reported their involvement in moderate to vigorous physical activity, sedentary behaviors, and active gaming. Those engaging in active gaming for at least 10 minutes per day were considered active gamers. Student’s 2-tailed t tests, chi-square test, and binomial logistic regression were performed. Results: About 25.9% of the adolescents were active gamers. They were younger, had higher body mass index, and spent more time on moderate to vigorous physical activity, television viewing, and sedentary video games with computer/console than nonactive gamers. There were more active gamers on weekends than on weekdays. On weekdays, more males than females were active gamers. Adolescents who did not meet sleep time guidelines were more likely to be active gamers on weekdays, whereas on weekends, being a girl, overweight/obese, and having a high socioeconomic status were predictors of being an active gamer. Conclusion: Because active gaming may contribute to meeting physical activity guidelines, the present findings could enable better targeting of physical activity promotion programs.

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Danilo R. Silva, Cláudia S. Minderico, Pedro B. Júdice, André O. Werneck, David Ohara, Edilson S. Cyrino and Luís B. Sardinha

Background: This investigation aimed to analyze the agreement between the GT3X accelerometer and the ActivPAL inclinometer for estimating and detecting changes in sedentary behavior of different contexts among adolescents. Methods: Secondary data from an intervention using standing desks in the classroom conducted within 2 sixth-grade classes (intervention [n = 22] and control [n = 27]) were used. The intervention took place over 16 weeks, with activity assessments (ActivPAL and GT3X) being performed 7 days before and in the last week of the intervention. Baseline information from both groups was considered for cross-sectional analysis (209 valid days), while data from 20 participants (intervention group) were used for longitudinal analysis. Results: The authors observed that GT3X overestimated sedentary time at school (16.8%), after school (13.5%), and during weekends (7.3%) compared with ActivPAL (P < .05). Outside the school (after school [r = −.188] and on weekends [r = −.260]), there was a trend to higher overestimation among adolescents with less sedentary behavior. Longitudinally, the GT3X was unable to detect changes resulting from an intervention in school hours (ActivPAL = −34.7 min·9 h−1 vs GT3X = +6.7 min·9 h−1; P < .05). Conclusions: The authors conclude that GT3X (cut-point of <100 counts·min−1) overestimated sedentary time of free-living activities and did not detect changes resulting from a classroom standing desk intervention in adolescents.