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Edgar J. Gallardo and Andrew R. Coggan

differences in subject selection or other aspects of the experimental design. Most studies of dietary NO 3 − and exercise have used beetroot juice (BRJ) as a source. This is because beets are relatively rich in NO 3 − ( Santamaria, 2006 ) and are readily juiced. Consequently, lay publications frequently

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Naomi M. Cermak, Martin J. Gibala and Luc J.C. van Loon

Six days of dietary nitrate supplementation in the form of beetroot juice (~0.5 L/d) has been reported to reduce pulmonary oxygen uptake (VO2) during submaximal exercise and increase tolerance of high-intensity work rates, suggesting that nitrate can be a potent ergogenic aid. Limited data are available regarding the effect of nitrate ingestion on athletic performance, and no study has investigated the potential ergogenic effects of a small-volume, concentrated dose of beetroot juice. The authors tested the hypothesis that 6 d of nitrate ingestion would improve time-trial performance in trained cyclists. Using a double-blind, repeated-measures crossover design, 12 male cyclists (31 ± 3 yr, VO2peak = 58 ± 2 ml · kg−1 · min−1, maximal power [Wmax] = 342 ± 10 W) ingested 140 ml/d of concentrated beetroot (~8 mmol/d nitrate) juice (BEET) or a placebo (nitrate-depleted beetroot juice; PLAC) for 6 d, separated by a 14-d washout. After supplementation on Day 6, subjects performed 60 min of submaximal cycling (2 × 30 min at 45% and 65% Wmax, respectively), followed by a 10-km time trial. Time-trial performance (953 ± 18 vs. 965 ± 18 s, p < .005) and power output (294 ± 12 vs. 288 ± 12 W, p < .05) improved after BEET compared with PLAC supplementation. Submaximal VO2 was lower after BEET (45% Wmax = 1.92 ± 0.06 vs. 2.02 ± 0.09 L/min, 65% Wmax 2.94 ± 0.12 vs. 3.11 ± 0.12 L/min) than with PLAC (main effect, p < .05). Wholebody fuel selection and plasma lactate, glucose, and insulin concentrations did not differ between treatments. Six days of nitrate supplementation reduced VO2 during submaximal exercise and improved time-trial performance in trained cyclists.

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Jessica L. Chandler, Keith Brazendale, Clemens Drenowatz, Justin B. Moore, Xuemei Sui, Robert G. Weaver and Michael W. Beets

.0b013e318161eaa5 18317385 10.1249/MSS.0b013e318161eaa5 6. Weaver RG , Beets MW , Huberty J , Freedman D , Turner-Mcgrievy G , Ward D. Physical activity opportunities in afterschool programs . Health Promot Pract . 2015 ; 16 ( 3 ): 371 – 382 . PubMed ID: 25586132 doi:10

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Michael William Beets, Jennifer Huberty and Aaron Beighle

Background:

National and state organizations have called upon afterschool programs (3–6 PM, ASP) to promote physical activity (PA). Few strategies exist that ASPs can use to increase the PA of children enrolled. This study evaluated a policy-level intervention (Movin’ Afterschool, MAS) designed to increase PA through staff implemented policy-level changes and ongoing technical support.

Methods:

Twelve preexisting community-based ASPs serving 580 children (5–12 yrs, 57% girls) were invited to take part in MAS. Evaluation of children’s PA, staff behaviors (engaged or promote PA, other ASP tasks, general supervising), and environmental features (equipment, organized PA) at baseline (Fall 2010) and postassessment (Spring 2011) were collected using SOPLAY (System for Observing Play and Leisure Activity in Youth) for boys and girls, separately. Random effects models evaluated changes in PA categories (sedentary, walking, vigorous).

Results:

The percentage of boys and girls sedentary decreased by 11.8% and 11.4%, respectively. Girls walking increased by 6.9% while boys vigorous PA increased by 6.5%. Greater increases in vigorous activity were observed as postassessment in organized activities for boys and during indoor activities for girls.

Conclusions:

Findings indicate a policy-level approach targeting staff training and ongoing technical support can produce notable increases in PA within the ASP setting.

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Michael W. Beets and Kenneth H. Pitetti

Background:

To examine the Healthy Fitness Zone (pass/fail) criterion-referenced reliability (CRR) and equivalency (CRE) of the 1-mile run/walk (MRW) and Progressive Aerobic Cardiovascular Endurance Run (PACER) in adolescents (13 to 18 years).

Methods:

Seventy-six girls and 165 boys were randomly assigned to complete 2 trials of each test.

Results:

CRR for the boys on the MRW (Pa = 77%, κq = 0.53) was lower than on the PACER (Pa = 81%, κq = 0.63); girls were classified more similarly on the MRW (Pa = 83%, κq = 0.67) than on the PACER (Pa = 79%, κq = 0.58). The CRE between the MRW and PACER indicated boys (Pa = 77%, κq = 0.55) were classified more consistently on both tests than girls (Pa = 73%, κq = 0.46).

Conclusions:

No test provided greater consistency. Practitioners may consider other features, such as ease of administration, environmental conditions, and comparative use in the literature.

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Michael W. Beets and John T. Foley

Background:

Much of the research conducted to date implies overweight youth exhibit uniform active and sedentary behavioral patterns. This approach negates the possibility that multiple co-occurring, and seemingly contrasting, behaviors may manifest within the same individual. We present a substantive dialogue on alternative analytical approaches to identifying risk-related active/sedentary behavioral patterns associated with overweight in adolescents.

Methods:

Comparisons were made among latent profile analysis (LPA), cluster analysis (CA), and multinomial logistic regression (MLR). A cross sectional sample of youth (N = 6603; 12−18 yrs) completed a questionnaire assessing: physical activity (PA); competing activities (COMP); and sedentary activities (SED). Demographics associated with PA (age, sex, BMI) were used as covariates/predictors.

Results:

Comparisons among methods revealed that LPA and CA detected subgroupings of behavioral patterns associated with overweight, each unique in regards to behaviors and demographic characteristics, whereas MLR results followed established associations of low PA and high SED without subgroup separation.

Conclusions:

Use of LPA and CA provides a rich understanding of behavioral patterns and the related demographic characteristics. Decisions guiding the selection of analytical techniques are discussed.

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Michael W. Beets and Kenneth H. Pitetti

This study was undertaken to initiate a standardized methodology model for reporting cardiovascular fitness (CVF) for youths in the US and to compare the CVF of youths from a Midwestern metropolitan area to their international and US peers. Participants were 795 youths 8–18 yrs old. The 20-m shuttle-run test (20MST) was used to determine CVF and body composition was determined by body mass index (BMI). Comparative analysis was made by sex and age. Participants in this study showed similar CVF levels with their US peers, but when compared with their international counterparts, they demonstrated considerably lower CVF and higher BMI.

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Jihong Liu, Han Sun, Michael William Beets and Janice C. Probst

Objectives:

We examined the natural groupings of leisure-time physical activities (LTPA) among US adolescents and their correlates.

Methods:

Data came from the 1999−2006 NHANES, restricted to 3865 boys and 3641 girls 12−19 years old. Respondents were asked to report > 40 types of moderate-to-vigorous LTPA in the past month. Latent class analyses were used to identify natural groupings of the top 10 LTPA using the proportion of each activity’s metabolic equivalents (METs) to total energy expenditure from all physical activities.

Results:

For each gender, 5 natural groupings of LTPA were identified. Among boys, they were basketball players and runners (72.8%), football players (9.0%), bicycle riders (7.5%), soccer players (5.8%), and walkers (4.7%). For girls, the 5 natural groupings in descending order were dancers/walkers/joggers (79.0%), aerobic exercisers (6.1%), swimmers (5.6%), volleyball players (4.9%), and soccer players (4.2%). The natural groupings of physical activities were also impacted by age, race, weight status, region, and season of interview.

Conclusions:

The natural groupings of LTPA reflect adolescent’s preference and these activity patterns are likely shaped by their social and physical environments. Better understanding of common LTPAs and their natural groupings is useful in the design of effective PA interventions.

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R. Glenn Weaver, Michael W. Beets, Collin Webster and Jennifer Huberty

Background:

Frontline-staff are critical to achieving policies related to child physical activity and nutrition (PAaN) in out-of-school-time programs (OSTP). Recent policies call upon staff to demonstrate behaviors related to PAaN. Currently, no instrument exists to measure these behaviors. This study fills the gap between policy mandates and staff behaviors by describing the development of the System for Observing Staff Promotion of Activity and Nutrition (SOSPAN) in OSTP.

Methods:

SOSPAN items were aligned with existing OSTP policies. Reliability and validity data of SOSPAN were collected across 8 OSTP: 4 summer day camps and 4 afterschool programs. Validity of SOSPAN staff behaviors/management of PA was established using the percent of children active measured concurrently via direct observation.

Results:

A total of 6437 scans were performed. Interrater percent agreement ranged from 74%–99% across PAaN behaviors. Children’s activity was associated with staff facilitative behaviors/management, such as playing with the children and providing 2 or more activities for children to choose, while prohibitive behaviors/management, such as waiting in line were related to increased sedentary behavior. Staff nutrition behaviors were observed in less than 0.6% of scans.

Conclusion:

SOSPAN is a reliable and valid tool to assess staff behaviors/management of PAaN in OSTPs.

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Kenneth H. Pitetti, Michael W. Beets and Judy Flaming

Pedometer accuracy for steps and activity time during dynamic movement for youth with intellectual disabilities (ID) were examined. Twenty-four youth with ID (13 girls, 13.1 ± 3.2 yrs; 11 boys, 14.7 ± 2.7 yrs) were videotaped during adapted physical education class while wearing a Walk4Life 2505 pedometer in five locations around the waist. Researchers viewed each videotape and recorded observed steps and activity time. Observed findings were compared with pedometer recorded steps and time. On average, pedometer registered steps were underestimated by approximately 14% ± 16.5%, whereas pedometer registered time was overestimated by approximately 8.7% ± 21.8%. The findings indicate that the accuracy of pedometers may be compromised during dynamic movement for youth with ID.