The purpose of this study was to develop a compendium of wheelchair-related physical activities. To accomplish this, we conducted a systematic review of the published energy costs of activities performed by individuals who use wheelchairs. A total of 266 studies were identified by a literature search using relevant keywords. Inclusion criteria were studies utilizing individuals who routinely use a manual wheelchair, indirect calorimetry as the criterion measurement, energy expenditure expressed as METs or VO2, and physical activities typical of wheelchair users. Eleven studies met the inclusion criteria. A total of 63 different wheelchair activities were identified with energy expenditure values ranging from 0.8 to 12.5 kcal·kg-1·hr-1. The energy requirements for some activities differed between individuals who use wheelchairs and those who do not. The compendium of wheelchair-related activities can be used to enhance scoring of physical activity surveys and to promote the benefits of activity in this population.
Scott A. Conger and David R. Bassett Jr.
Scott A. Conger, Stacy N. Scott, Eugene C. Fitzhugh, Dixie L. Thompson and David R. Bassett
It is unknown if activity monitors can detect the increased energy expenditure (EE) of wheelchair propulsion at different speeds or on different surfaces.
Individuals who used manual wheelchairs (n = 14) performed 5 wheeling activities: on a level surface at 3 speeds, on a rubberized track at 1 fixed speed and on a sidewalk course at a self-selected speed. EE was measured using a portable indirect calorimetry system and estimated by an Actical (AC) worn on the wrist and a SenseWear (SW) activity monitor worn on the upper arm. Repeated-measures ANOVA was used to compare measured EE to the estimates from the standard AC prediction equation and SW using 2 different equations.
Repeated-measures ANOVA demonstrated a significant main effect between measured EE and estimated EE. There were no differences between the criterion method and the AC across the 5 activities. The SW overestimated EE when wheeling at 3 speeds on a level surface, and during sidewalk wheeling. The wheelchair-specific SW equation improved the EE prediction during low intensity activities, but error progressively increased during higher intensity activities.
During manual wheelchair propulsion, the wrist-mounted AC provided valid estimates of EE, whereas the SW tended to overestimate EE.
Scott A. Conger, Gordon L. Warren, Michelle A. Hardy and Mindy L. Millard-Stafford
Carbohydrate (CHO) and caffeine (CAF) both improve endurance performance.
To determine by systematic literature review coupled with meta-analysis whether CAF ingested with CHO (CHO+CAF) improves endurance performance more than CHO alone.
Databases were searched using the keywords caffeine, endurance, exercise, carbohydrate, and performance. Criteria for inclusion were studies that used human subjects performing an endurance-exercise performance task and included both a CHO and CHO+CAF condition. Effect sizes (ESs) were calculated as the standardized mean difference.
Twenty-one studies met the criteria for analysis. ESs for individual studies ranged from –0.08 (trivial effect favoring CHO) to 1.01 (large effect favoring CHO+CAF). The overall ES equaled 0.26 (95% CI 0.15–0.38, p < .001), indicating that CHO+CAF provides a small but significant performance benefit over CHO. ES was not significantly (p > .05) related to CAF dose, exercise duration, or performance-assessment method. To determine whether ES of CHO+CAF vs. CHO was different than CAF compared with water (placebo), a subgroup meta-analysis compared 36 CAF vs. placebo studies against the 21 CHO+CAF vs. CHO studies. The overall ES for the former group of studies (ES = 0.51, 95% CI 0.40–0.61) was nearly 2-fold greater than in CHO+CAF vs. CHO studies (p = .006).
CHO+CAF ingestion provides a significant but small effect to improve endurance performance compared with CHO alone. However, the magnitude of the performance benefit that CAF provides is less when added to CHO than when added to placebo.
David R. Bassett, Dinesh John, Scott A. Conger, Eugene C. Fitzhugh and Dawn P. Coe
Increases in childhood and adolescent obesity are a growing concern in the United States (U.S.), and in most countries throughout the world. Declines in physical activity are often postulated to have contributed to the rise in obesity rates during the past 40 years.
We searched for studies of trends in physical activity and sedentary behaviors of U.S. youth, using nontraditional data sources. Literature searches were conducted for active commuting, physical education, high-school sports, and outdoor play. In addition, trends in sedentary behaviors were examined.
Data from the Youth Risk Behavior Surveillance System (YRBSS) and other national surveys, as well as longitudinal studies in the transportation, education, electronic media, and recreation sectors showed evidence of changes in several indicators. Active commuting, high school physical education, and outdoor play (in 3- to 12-year-olds) declined over time, while sports participation in high school girls increased from 1971 to 2012. In addition, electronic entertainment and computer use increased during the first decade of the 21st century.
Technological and societal changes have impacted the types of physical activities performed by U.S. youth. These data are helpful in understanding the factors associated with the rise in obesity, and in proposing potential solutions.
David R. Bassett, Ray Browning, Scott A. Conger, Dana L. Wolff and Jennifer I. Flynn
The indoor built environment has the potential to influence levels of physical activity. However, the extent to which architectural design in commercial buildings can influence the percentage of people choosing to use the stairs versus elevators is unknown. The purpose of this study was to determine if buildings with centrally located, accessible, and aesthetically pleasing staircases result in a greater percentage of people taking the stairs.
Direct observations of stair and elevator use were conducted in 3 buildings on a university campus. One of the buildings had a bank of 4 centrally located elevators and a fire escape stairwell behind a steel door. The other 2 buildings had centrally located staircases and out-of-the-way elevators.
The percentage of people who ascended the stairs was 8.1% in the elevator-centric building, compared with 72.8% and 81.1% in the 2 stair-centric buildings (P < .001). In addition, the percentage of people who descended the stairs was 10.8% in the first building, compared with 89.5% and 93.7% in the stair-centric buildings (P < .001).
The results of the current study suggest that if buildings are constructed with centrally located, accessible, and aesthetically pleasing staircases, a greater percentage of people will choose to take the stairs.
Scott A. Conger, Alexander H.K. Montoye, Olivia Anderson, Danielle E. Boss and Jeremy A. Steeves
Speed of movement has been shown to affect the validity of physical activity (PA) monitors during locomotion. Speed of movement may also affect the validity of accelerometer-based PA monitors during other types of exercise. Purpose: To assess the ability of the Atlas Wearables Wristband2 (a PA monitor developed specifically for resistance training [RT] exercise) to identify the individual RT exercise type and count repetitions during RT exercises at various movement speeds. Methods: 50 male and female participants completed seven sets of 10 repetitions for five different upper/lower body RT exercises while wearing a Wristband2 on the left wrist. The speed of each set was completed at different metronome-paced speeds ranging from a slow speed of 4 sec·rep−1 to a fast speed of 1 sec·rep−1. Repeated Measures ANOVAs were used to compare the actual exercise type/number of repetitions among the seven different speeds. Mean absolute percent error (MAPE) and bias were calculated for repetition counting. Results: For each exercise, there tended to be significant differences between the slower speeds and the fastest speed for activity type identification and repetition counting (p < .05). Across all exercises, the highest accuracy for activity type identification (91 ± 1.8% correct overall), repetition counting (8.77 ± 0.17 of 10 reps overall) and the lowest MAPE (14 ± 1.7% overall) and bias (−1.23 ± 0.17 reps overall) occurred during the 1.5 sec·rep−1 speed (the second fastest speed tested). Conclusions: The validity of the Atlas Wearables Wristband2 to identify exercise type and count repetitions varied based on the speed of movement during RT exercises.
Alexander H.K. Montoye, Scott A. Conger, Joe R. Mitrzyk, Colby Beach, Alecia K. Fox and Jeremy A. Steeves
Background: Resistance training (RT) is an integral component of physical activity guidelines, but methods for the objective assessment of RT have been limited. Recently, the Atlas Wearables Wristband2 has been marketed to measure RT, but its reliability is unknown. Purpose: To determine the reliability of the Wristband2 for measuring RT exercises. Methods: Participants (n = 62) aged 18–52 yrs. wore two Wristband2 monitors on the left wrist and performed 2 sets of 12 repetitions of 14 different resistance training exercises. Test-retest reliability was determined by calculating percent agreement for exercise type and for repetitions recorded by a single Wristband2 between sets 1 and 2 for each exercise, and inter-monitor reliability was determined by calculating percent agreement for exercise type and for repetitions recorded by both Wristband2 monitors in set 1 of each exercise. Results: Test-retest reliability for exercise type was 80.0 ± 1.0% (lowest: 69.4% for bench press; highest: 95.2% for biceps curls) and for repetition count was 47.9 ± 2.2% (lowest: 19.4% for calf raises; highest: 82.3% for lateral raises). Inter-monitor reliability for exercise type was 80.4 ± 1.3% (lowest: 66.1% for bench press; highest: 95.2% for biceps curls) and for repetition count was 59.6 ± 2.2% (lowest: 32.3% for calf raises; highest: 88.7% for lateral raises). Subgroup analyses by gender, RT experience, and participant height revealed minimal differences in reliability. Repetition agreement of ≤1 repetition increased test-retest reliability to 74.7% and inter-monitor reliability to 83.7%. Conclusion: The Wristband2 had acceptable test-retest and inter-monitor reliability for the majority of exercises tested and for counting repetitions to within 1 repetition/set.
Jeremy A. Steeves, Scott A. Conger, Joe R. Mitrzyk, Trevor A. Perry, Elise Flanagan, Alecia K. Fox, Trystan Weisinger and Alexander H.K. Montoye
Background: Devices for monitoring physical activity have focused mainly on measuring aerobic activity; however, the 2018 Physical Activity Guidelines for Americans also recommend muscle-resistance training two or more days per week. Recently, a wrist-worn activity monitor, the Atlas Wristband2, was developed to recognize resistance training exercises. Purpose: To assess the ability of the Wristband2 to identify the type and number of repetitions of resistance training exercises, when worn on the left wrist as directed by the manufacturer, and when worn on the right wrist. Methods: While wearing monitors on both wrists, 159 participants completed a circuit-style workout consisting of two sets of 12 repetitions of 14 different resistance training exercises. Data from the monitors were used to determine classification accuracies for identifying exercise type verses direct observation. The average repetitions and mean absolute error (MAE) for repetitions were calculated for each exercise. Results: The Wristband2 classification accuracy for exercise type was 78.4 ± 2.5%, ranging from 54.7 ± 3.4% (dumbbell [DB] bench press) to 97.5 ± 1.0% (DB biceps curls), when worn on the left wrist. An average of 11.0 ± 0.2 repetitions, ranging from 9.0 ± 0.3 repetitions (DB lunges) to 11.9 ± 0.1 repetitions (push-ups), were identified. For all exercises, MAE ranged from 0.0–4.6 repetitions. When worn on the right wrist, exercise type classification accuracy dropped to 24.2 ± 5.1%, and repetitions decreased to 8.1 ± 0.8 out of 12. Conclusions: The Wristband2, worn on the left wrist, had acceptable exercise classification and repetition counting capabilities for many of the 14 exercises used in this study, and may be a useful tool to objectively track resistance training.
Jeffer Eidi Sasaki, Cheryl A. Howe, Dinesh John, Amanda Hickey, Jeremy Steeves, Scott Conger, Kate Lyden, Sarah Kozey-Keadle, Sarah Burkart, Sofiya Alhassan, David Bassett Jr and Patty S. Freedson
Thirty-five percent of the activities assigned MET values in the Compendium of Energy Expenditures for Youth were obtained from direct measurement of energy expenditure (EE). The aim of this study was to provide directly measured EE for several different activities in youth.
Resting metabolic rate (RMR) of 178 youths (80 females, 98 males) was first measured. Participants then performed structured activity bouts while wearing a portable metabolic system to directly measure EE. Steady-state oxygen consumption data were used to compute activity METstandard (activity VO2/3.5) and METmeasured (activity VO2/measured RMR) for the different activities.
Rates of EE were measured for 70 different activities and ranged from 1.9 to 12.0 METstandard and 1.5 to 10.0 METmeasured.
This study provides directly measured energy cost values for 70 activities in children and adolescents. It contributes empirical data to support the expansion of the Compendium of Energy Expenditures for Youth.