Background: Active workstations offer the potential for augmenting energy expenditure (EE) in sedentary occupations. However, comparisons of EE during pedal and treadmill desk usage at self-selected intensities are lacking. Methods: A sample of 16 adult participants (8 men and 8 women; 33.9 [7.1] y, 22.5 [2.7] kg/m2) employed in sedentary occupations had their EE measured using indirect calorimetry during 4 conditions: (1) seated rest, (2) seated typing in a traditional office chair, (3) self-paced pedaling on a pedal desk while typing, and (4) self-paced walking on a treadmill desk while typing. Results: For men and women, self-paced pedal and treadmill desk typing significantly increased EE above seated typing (pedal desk: +1.20 to 1.28 kcal/min and treadmill desk: +1.43 to 1.93 kcal/min, P < .001). In men, treadmill desk typing (3.46 [0.19] kcal/min) elicited a significantly higher mean EE than pedal desk typing (2.73 [0.21] kcal/min, P < .001). No significant difference in EE was observed between treadmill desk typing (2.68 [0.19] kcal/min) and pedal desk typing among women (2.52 [0.21] kcal/min). Conclusions: Self-paced treadmill desk usage elicited significantly higher EE than self-paced pedal desk usage in men but not in women. Both pedal and treadmill desk usage at self-selected intensities elicited approximate 2-fold increases in EE above what would typically be expected during traditional seated office work.
John M. Schuna Jr., Daniel S. Hsia, Catrine Tudor-Locke and Neil M. Johannsen
John M. Schuna Jr., Tiago V. Barreira, Daniel S. Hsia, William D. Johnson and Catrine Tudor-Locke
Energy expenditure (EE) estimates for a broad age range of youth performing a variety of activities are needed.
106 participants (6–18 years) completed 6 free-living activities (seated rest, movie watching, coloring, stair climbing, basketball dribbling, jumping jacks) and up to 9 treadmill walking bouts (13.4 to 120.7 m/min; 13.4 m/min increments). Breath-by-breath oxygen uptake (VO2) was measured using the COSMED K4b2 and EE was quantified as youth metabolic equivalents (METy1:VO2/measured resting VO2, METy2:VO2/estimated resting VO2). Age trends were evaluated with ANOVA.
Seated movie watching produced the lowest mean METy1 (6- to 9-year-olds: 0.94 ± 0.13) and METy2 values (13- to 15-year-olds: 1.10 ± 0.19), and jumping jacks produced the highest mean METy1 (13- to 15-year-olds: 6.89 ± 1.47) and METy2 values (16- to 18-year-olds: 8.61 ± 2.03). Significant age-related variability in METy1 and METy2 were noted for 8 and 2 of the 15 evaluated activities, respectively.
Descriptive EE data presented herein will augment the Youth Compendium of Physical Activities.
Alex V. Rowlands, John M. Schuna Jr., Victoria H. Stiles and Catrine Tudor-Locke
Previous research has reported peak vertical acceleration and peak loading rate thresholds beneficial to bone mineral density (BMD). Such thresholds are difficult to translate into meaningful recommendations for physical activity. Cadence (steps/min) is a more readily interpretable measure of ambulatory activity.
To examine relationships between cadence, peak vertical acceleration and peak loading rate during ambulation and identify the cadence associated with previously reported bone-beneficial thresholds for peak vertical acceleration (4.9 g) and peak loading rate (43 BW/s).
Ten participants completed 8 trials each of: slow walking, brisk walking, slow running, and fast running. Acceleration data were captured using a GT3×+ accelerometer worn at the hip. Peak loading rate was collected via a force plate.
Strong relationships were identified between cadence and peak vertical acceleration (r = .96, P < .05) and peak loading rate (r = .98, P < .05). Regression analyses indicated cadences of 157 ± 12 steps/min (2.6 ± 0.2 steps/s) and 122 ± 10 steps/min (2.0 ± 0.2 steps/s) corresponded with the 4.9 g peak vertical acceleration and 43 BW/s peak loading rate thresholds, respectively.
Cadences ≥ 2.0 to 2.6 steps/s equate to acceleration and loading rate thresholds related to bone health. Further research is needed to investigate whether the frequency of daily occurrences of this cadence is associated with BMD.
Emily J. Tomayko, Katherine B. Gunter, John M. Schuna Jr. and Paul N. Thompson
Background: Use of 4-day school weeks (FDSWs) as a cost-saving strategy has increased substantially as many US school districts face funding declines. However, the impacts of FDSWs on physical activity exposure and related outcomes are unknown. This study examined physical education (PE) exposure and childhood obesity prevalence in 4- versus 5-day Oregon schools; the authors hypothesized lower PE exposure and higher obesity in FDSW schools, given reduced school environment exposure. Methods: The authors utilized existing data from Oregon to compare 4- versus 5-day models: t tests compared mean school-level factors (PE exposure, time in school, enrollment, and demographics) and complex samples weighted t tests compared mean child-level obesity data for a state representative sample of first to third graders (N = 4625). Results: Enrollment, time in school, and student–teacher ratio were significantly lower in FDSW schools. FDSW schools provided significantly more PE, both in minutes (120 vs 101 min/wk in 4- vs 5-d schools, P < .01) and relative to total time in school (6.9% vs 5.0%, P < .0001). Obesity prevalence did not differ significantly between school models. Conclusion: Greater PE exposure in FDSW schools was observed, and it remains unknown whether differences in PE exposure contributed to obesity prevalence in this sample of students. Efforts to better understand how FDSWs impact physical activity, obesity risk, and related factors are needed.
Elroy J. Aguiar, John M. Schuna Jr., Tiago V. Barreira, Emily F. Mire, Stephanie T. Broyles, Peter T. Katzmarzyk, William D. Johnson and Catrine Tudor-Locke
Walking cadence (steps per minute) is associated with the intensity of ambulatory behavior. This analysis provides normative values for peak 30-min cadence, an indicator of “natural best effort” during free-living behavior. A sample of 1,196 older adults (aged from 60 to 85+) with accelerometer data from the National Health and Nutrition Examination Survey 2005–2006 was used. Peak 30-min cadence was calculated for each individual. Quintile-defined values were computed, stratified by sex and age groups. Smoothed sex-specific centile curves across the age span were fitted using the LMS method. Peak 30-min cadence generally trended lower as age increased. The uppermost quintile value was >85 steps/min (men: 60–64 years), and the lowermost quintile value was <22 steps/min (women: 85+). The highest 95th centile value was 103 steps/min (men: 64–70 years), and the lowest 5th centile value was 15 steps/min (women: 85+). These normative values may be useful for evaluating older adults’ “natural best effort” during free-living ambulatory behavior.
Catrine Tudor-Locke, John M. Schuna Jr, Damon L. Swift, Amber T. Dragg, Allison B. Davis, Corby K. Martin, William D. Johnson and Timothy S. Church
Background: Step-counting interventions with discrepant intensity emphases may elicit different effects. Methods: A total of 120 sedentary/low-active, postmenopausal women were randomly assigned to one of the following 3 groups: (1) 10,000 steps per day (with no emphasis on walking intensity/speed/cadence; basic intervention, 49 completers), (2) 10,000 steps per day and at least 30 minutes in moderate intensity (ie, at a cadence of at least 100 steps per minute; enhanced intervention, 47 completers), or (3) a control group (19 completers). NL-1000-determined steps and active minutes (a device-specific indicator of time at moderate+ intensity) were collected as process variables during the 12-week intervention. Outcome variables included systolic and diastolic blood pressure, anthropometric measurements, fasting blood glucose and insulin, flow-mediated dilation, gait speed, and ActiGraph GT3X+-determined physical activity and sedentary behavior. Results: The “basic group” increased 5173 to 9602 steps per day and 9.2 to 30.2 active minutes per day. The “enhanced group” similarly increased 5061 to 10,508 steps per day and 8.7 to 38.8 active minutes per day. The only significant change over time for clinical variables was body mass index. Conclusions: Interventions that use simple step-counters can achieve elevated volume and intensity of daily physical activity, regardless of emphasis on intensity. Despite this, few clinical outcomes were apparent in this sample of postmenopausal women with generally normal or controlled hypertension.
Jeremy A. Steeves, Catrine Tudor-Locke, Rachel A. Murphy, George A. King, Eugene C. Fitzhugh, David R. Bassett, Dane Van Domelen, John M. Schuna Jr and Tamara B. Harris
Background: Little is known about the daily physical activity (PA) levels of people employed in different occupational categories. Methods: Nine ActiGraph accelerometer-derived daily PA variables are presented and ranked for adults (N = 1465, 20–60 y) working in the 22 occupational categories assessed by NHANES 2005–2006. A composite score was generated for each occupational category by summing the rankings of 3 accelerometer-derived daily PA variables known to have strong associations with health outcomes (total activity counts [TAC], moderate to vigorous PA minutes per week in modified 10-minute bouts [MVPA 10], and percentage of time spent in sedentary activity [SB%]). Results: Classified as high-activity occupational categories, “farming, fishing, forestry,” and “building & grounds cleaning, maintenance” occupations had the greatest TAC (461 996 and 449 452), most MVPA 10 (149.6 and 97.8), most steps per day (10 464 and 11 602), and near the lowest SB% (45.2% and 45.4%). “Community, social services” occupations, classified as low-activity occupational categories, had the second lowest TAC (242 085), least MVPA 10 (12.1), fewest steps per day (5684), and near the highest SB% (64.2%). Conclusions: There is a strong association between occupational category and daily activity levels. Objectively measured daily PA permitted the classification of the 22 different occupational categories into 3 activity groupings.