2024 Adult Compendium of Physical Activities: A third update of the energy costs of human activities

BACKGROUND

The Compendium of Physical Activities was published in 1993 to improve the comparability of energy expenditure values assigned to self-reported physical activity (PA) across studies. The original version was updated in 2000, and again in 2011, and has been widely used to support PA research, practice, and public health guidelines.

METHODS

This 2024 update was tailored for adults 19-59 years of age by removing data from those ≥60 years. Using a systematic review and supplementary searches, we identified new activities and their associated measured metabolic equivalent (MET) values (using indirect calorimetry) published since 2011. We replaced estimated METs with measured values when possible.

RESULTS

We screened 32,173 abstracts and 1507 full-text papers and extracted 2356 PA energy expenditure values from 701 papers. We added 303 new PAs and adjusted 176 existing MET values and descriptions to reflect the addition of new data and removal of METs for older adults. We added a Major Heading (Video Games). The 2024 Adult Compendium includes 1114 PAs (912 with measured and 202 with estimated values) across 22 Major Headings.

CONCLUSION

This comprehensive update and refinement led to the creation of The 2024 Adult Compendium, which has utility across research, public health, education, and healthcare domains, as well as in the development of consumer health technologies. The new website with the complete lists of PAs and supporting resources is available at https://pacompendium.com.

Older Adult Compendium of Physical Activities: Energy costs of human activities in adults aged 60 and older

PURPOSE

To describe the development of a Compendium for estimating the energy costs of activities in adults ≥60 years (OA Compendium).

METHODS

Physical activities (PAs) and their metabolic equivalent of task (MET) values were obtained from a systematic search of studies published in 4 sport and exercise databases (PubMed, Embase, SPORTDiscus (EBSCOhost), and Scopus) and a review of articles included in the 2011 Adult Compendium that measured PA in older adults. MET values were computed as the oxygen cost (VO2, mL/kg/min) during PA divided by 2.7 mL/kg/min (MET60+) to account for the lower resting metabolic rate in older adults.

RESULTS

We identified 68 articles and extracted energy expenditure data on 427 PAs. From these, we derived 99 unique Specific Activity codes with corresponding MET60+ values for older adults. We developed a website to present the OA Compendium MET60+ values: https://pacompendium.com.

CONCLUSION

The OA Compendium uses data collected from adults ≥60 years for more accurate estimation of the energy cost of PAs in older adults. It is an accessible resource that will allow researchers, educators, and practitioners to find MET60+ values for older adults for use in PA research and practice.

Cadence (steps/min) and relative intensity in 61 to 85-year-olds: the CADENCE-Adults study

BACKGROUND

We previously demonstrated that a heuristic (i.e., evidence-based, rounded yet practical) cadence threshold of ≥ 100 steps/min was associated with absolutely-defined moderate intensity physical activity (i.e., ≥ 3 metabolic equivalents [METs]) in older adults 61-85 years of age. Although it was difficult to ascertain achievement of absolutely-defined vigorous (6 METs) intensity, ≥ 130 steps/min was identified as a defensible threshold for this population. However, little evidence exists regarding cadence thresholds and relatively-defined moderate intensity indicators, including ≥ 64% heart rate [HR] maximum [HRmax = 220-age], ≥ 40% HR reserve [HRR = HRmax-HRresting], and ≥ 12 Borg Scale Rating of Perceived Exertion [RPE]; or vigorous intensity indicators including ≥ 77%HRmax, ≥ 60%HRR, and ≥ 14 RPE.

PURPOSE

To analyze the relationship between cadence and relatively-defined physical activity intensity and identify relatively-defined moderate and vigorous heuristic cadence thresholds for older adults 61-85 years of age.

METHODS

Ninety-seven ostensibly healthy adults (72.7 ± 6.9 years; 49.5% women) completed up to nine 5-min treadmill walking bouts beginning at 0.5 mph (0.8 km/h) and progressing by 0.5 mph speed increments (with 2-min rest between bouts). Directly-observed (and video-recorded) steps were hand-counted, HR was measured using a chest-strapped monitor, and in the final minute of each bout, participants self-reported RPE. Segmented mixed model regression and Receiver Operating Characteristic (ROC) curve analyses identified optimal cadence thresholds associated with relatively-defined moderate (≥ 64%HRmax, ≥ 40%HRR, and ≥ 12 RPE) and vigorous (≥ 77%HRmax, ≥ 60%HRR, and ≥ 14 RPE) intensities. A compromise between the two analytical methods, including Youden's Index (a sum of sensitivity and specificity), positive and negative predictive values, and overall accuracy, yielded final heuristic cadences.

RESULTS

Across all relatively-defined moderate intensity indicators, segmented regression models and ROC curve analyses identified optimal cadence thresholds ranging from 105.9 to 112.8 steps/min and 102.0-104.3 steps/min, respectively. Comparable values for vigorous intensity indicators ranged between126.1-132.1 steps/min and 106.7-116.0 steps/min, respectively. Regardless of the relatively-defined intensity indicator, the overall best heuristic cadence threshold aligned with moderate intensity was ≥ 105 steps/min. Vigorous intensity varied between ≥ 115 (greater sensitivity) or ≥ 120 (greater specificity) steps/min.

CONCLUSIONS

Heuristic cadence thresholds align with relatively-defined intensity indicators and can be useful for studying and prescribing older adults' physiological response to, and/or perceived experience of, ambulatory physical activity.

TRIAL REGISTRATION

Clinicaltrials.gov NCT02650258. Registered 24 December 2015.

A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study

BACKGROUND

Standardized validation indices (i.e., accuracy, bias, and precision) provide a comprehensive comparison of step counting wearable technologies.

PURPOSE

To expand a previously published child/youth catalog of validity indices to include adults (21-40, 41-60 and 61-85 years of age) assessed across a range of treadmill speeds (slow [0.8-3.2 km/h], normal [4.0-6.4 km/h], fast [7.2-8.0 km/h]) and device wear locations (ankle, thigh, waist, and wrist).

METHODS

Two hundred fifty-eight adults (52.5 ± 18.7 years, 49.6% female) participated in this laboratory-based study and performed a series of 5-min treadmill bouts while wearing multiple devices; 21 devices in total were evaluated over the course of this multi-year cross-sectional study (2015-2019). The criterion measure was directly observed steps. Computed validity indices included accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV).

RESULTS

Over the range of normal speeds, 15 devices (Actical, waist-worn ActiGraph GT9X, activPAL, Apple Watch Series 1, Fitbit Ionic, Fitbit One, Fitbit Zip, Garmin vivoactive 3, Garmin vivofit 3, waist-worn GENEActiv, NL-1000, PiezoRx, Samsung Gear Fit2, Samsung Gear Fit2 Pro, and StepWatch) performed at < 5% MAPE. The wrist-worn ActiGraph GT9X displayed the worst accuracy across normal speeds (MAPE = 52%). On average, accuracy was compromised across slow walking speeds for all wearable technologies (MAPE = 40%) while all performed best across normal speeds (MAPE = 7%). When analyzing the data by wear locations, the ankle and thigh demonstrated the best accuracy (both MAPE = 1%), followed by the waist (3%) and the wrist (15%) across normal speeds. There were significant effects of speed, wear location, and age group on accuracy and bias (both p < 0.001) and precision (p ≤ 0.045).

CONCLUSIONS

Standardized validation indices cataloged by speed, wear location, and age group across the adult lifespan facilitate selecting, evaluating, or comparing performance of step counting wearable technologies. Speed, wear location, and age displayed a significant effect on accuracy, bias, and precision. Overall, reduced performance was associated with very slow walking speeds (0.8 to 3.2 km/h). Ankle- and thigh-located devices logged the highest accuracy, while those located at the wrist reported the worst accuracy.

TRIAL REGISTRATION

Clinicaltrials.gov NCT02650258. Registered 24 December 2015.

Impact of Reduced School Exposure on Adolescent Health Behaviors and Food Security: Evidence From 4-Day School Weeks

BACKGROUND

Four-day school week (FDSW) use has increased substantially among US districts in recent years, but limited data exist on health impacts of this school schedule. This study examined associations of reduced school exposure via FDSWs with adolescent health and risk behaviors, obesity, and food security.

METHODS

Self-report data from 8th- and 11th-grade students from the Oregon Healthy Teens survey across 5 survey years (odd years 2007-2015, total N = 91,860-104,108 respondents depending on the survey question) were linked to a FDSW indicator. Regression analyses controlling for student and school characteristics compared outcomes between students in 4- and 5-day schools overall (without school fixed effects) and outcomes associated with switching to a FDSW (with school fixed effects).

RESULTS

When controlling for multiple student- and school-level factors, we observed adolescents in FDSW schools report they consume sugar sweetened beverages more frequently and water less frequently, have access to fewer days of physical education, are more likely to be food insecure, and are more likely to report the use of any drugs and specifically marijuana than 5-day school week students.

CONCLUSIONS

Limiting exposure to the school environment via FDSWs may impact adolescent health behaviors, including diet, physical activity, and drug use.

Walking cadence (steps/min) and intensity in 61-85-year-old adults: the CADENCE-Adults study

BACKGROUND

Heuristic (i.e., evidence-based, rounded) cadences of ≥100 and ≥ 130 steps/min have consistently corresponded with absolutely-defined moderate (3 metabolic equivalents [METs]) and vigorous (6 METs) physical activity intensity, respectively, in adults 21-60 years of age. There is no consensus regarding similar thresholds in older adults.

PURPOSE

To provide heuristic cadence thresholds for 3, 4, 5, and 6 METs in 61-85-year-old adults.

METHODS

Ninety-eight community-dwelling ambulatory and ostensibly healthy older adults (age = 72.6 ± 6.9 years; 49% women) walked on a treadmill for a series of 5-min bouts (beginning at 0.5 mph with 0.5 mph increments) in this laboratory-based cross-sectional study until: 1) transitioning to running, 2) reaching ≥75% of their age-predicted maximum heart rate, or 3) reporting a Borg rating of perceived exertion > 13. Cadence was directly observed and hand-tallied. Intensity (oxygen uptake [VO2] mL/kg/min) was assessed with indirect calorimetry and converted to METs (1 MET = 3.5 mL/kg/min). Cadence thresholds were identified via segmented mixed effects model regression and using Receiver Operating Characteristic (ROC) curves. Final heuristic cadence thresholds represented an analytical compromise based on classification accuracy (sensitivity, specificity, positive and negative predictive value, and overall accuracy).

RESULTS

Cadences of 103.1 (95% Prediction Interval: 70.0-114.2), 116.4 (105.3-127.4), 129.6 (118.6-140.7), and 142.9 steps/min (131.8-148.4) were identified for 3, 4, 5, and 6 METs, respectively, based on the segmented regression. Comparable values based on ROC analysis were 100.3 (95% Confidence Intervals: 95.7-103.1), 111.5 (106.1-112.9), 116.0 (112.4-120.2), and 128.6 steps/min (128.3-136.4). Heuristic cadence thresholds of 100, 110, and 120 were associated with 3, 4, and 5 METs. Data to inform a threshold for ≥6 METs was limited, as only 6/98 (6.0%) participants achieved this intensity.

CONCLUSIONS

Consistent with previous data collected from 21-40 and 41-60-year-old adults, heuristic cadence thresholds of 100, 110, and 120 steps/min were associated with 3, 4, and 5 METs, respectively, in 61-85-year-old adults. Most older adults tested did not achieve the intensity of ≥6 METs; therefore, our data do not support establishing thresholds corresponding with this intensity level.

TRIAL REGISTRATION

Clinicaltrials.gov NCT02650258 . Registered 24 December 2015.

A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-Kids study

BACKGROUND

Wearable technologies play an important role in measuring physical activity (PA) and promoting health. Standardized validation indices (i.e., accuracy, bias, and precision) compare performance of step counting wearable technologies in young people.

PURPOSE

To produce a catalog of validity indices for step counting wearable technologies assessed during different treadmill speeds (slow [0.8-3.2 km/h], normal [4.0-6.4 km/h], fast [7.2-8.0 km/h]), wear locations (waist, wrist/arm, thigh, and ankle), and age groups (children, 6-12 years; adolescents, 13-17 years; young adults, 18-20 years).

METHODS

One hundred seventeen individuals (13.1 ± 4.2 years, 50.4% female) participated in this cross-sectional study and completed 5-min treadmill bouts (0.8 km/h to 8.0 km/h) while wearing eight devices (Waist: Actical, ActiGraph GT3X+, NL-1000, SW-200; Wrist: ActiGraph GT3X+; Arm: SenseWear; Thigh: activPAL; Ankle: StepWatch). Directly observed steps served as the criterion measure. Accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV) were computed.

RESULTS

Five of the eight tested wearable technologies (i.e., Actical, waist-worn ActiGraph GT3X+, activPAL, StepWatch, and SW-200) performed at < 5% MAPE over the range of normal speeds. More generally, waist (MAPE = 4%), thigh (4%) and ankle (5%) locations displayed higher accuracy than the wrist location (23%) at normal speeds. On average, all wearable technologies displayed the lowest accuracy across slow speeds (MAPE = 50.1 ± 35.5%), and the highest accuracy across normal speeds (MAPE = 15.9 ± 21.7%). Speed and wear location had a significant effect on accuracy and bias (P < 0.001), but not on precision (P > 0.05). Age did not have any effect (P > 0.05).

CONCLUSIONS

Standardized validation indices focused on accuracy, bias, and precision were cataloged by speed, wear location, and age group to serve as important reference points when selecting and/or evaluating device performance in young people moving forward. Reduced performance can be expected at very slow walking speeds (0.8 to 3.2 km/h) for all devices. Ankle-worn and thigh-worn devices demonstrated the highest accuracy. Speed and wear location had a significant effect on accuracy and bias, but not precision.

TRIAL REGISTRATION

Clinicaltrials.gov NCT01989104 . Registered November 14, 2013.

GPS-based built environment measures associated with adult physical activity

Studies often rely on home locations to access built environment (BE) influences on physical activity (PA). We use GPS and accelerometer data collected for 288 individuals over a two-week period to examine eight GPS-derived BE characteristics and moderate-to-vigorous PA (MVPA) and light-to-moderate-vigorous PA (LMVPA). NDVI, parks, blue space, pedestrian-orientated intersections, and population density were associated with increased odds of LMVPA and MVPA, while traffic air pollution and noise were associated with decreased odds of LMVPA and MVPA. Associations varied by population density and when accounting for multiple BE measures. These findings provide further information on where individuals choose to be physically active.

Cadence (steps/min) and relative intensity in 21 to 60-year-olds: the CADENCE-adults study

BACKGROUND

Heuristic cadence (steps/min) thresholds of ≥100 and ≥ 130 steps/min correspond with absolutely-defined moderate (3 metabolic equivalents [METs]; 1 MET = 3.5 mL O2·kg- 1·min- 1) and vigorous (6 METs) intensity, respectively. Scarce evidence informs cadence thresholds for relatively-defined moderate (≥ 64% heart rate maximum [HRmax = 220-age], ≥ 40%HR reserve [HRR = HRmax -HRresting, and ≥ 12 Rating of Perceived Exertion [RPE]); or vigorous intensity (≥ 77%HRmax, ≥ 60%HRR, and ≥ 14 RPE).

PURPOSE

To identify heuristic cadence thresholds corresponding with relatively-defined moderate and vigorous intensity in 21-60-year-olds.

METHODS

In this cross-sectional study, 157 adults (40.4 ± 11.5 years; 50.6% men) completed up to twelve 5-min treadmill bouts, beginning at 0.5 mph and increasing by 0.5 mph. Steps were directly observed, HR was measured with chest-worn monitors, and RPE was queried in the final minute of each bout. Segmented mixed model regression and Receiver Operating Characteristic (ROC) curve analyses identified optimal cadence thresholds, stratified by age (21-30, 31-40, 41-50, and 51-60 years). Reconciliation of the two analytical models, including trade-offs between sensitivity, specificity, positive and negative predictive values, and overall accuracy, yielded final heuristic cadences.

RESULTS

Across all moderate intensity indicators, the segmented regression models estimated optimal cadence thresholds ranging from 123.8-127.5 (ages 21-30), 121.3-126.0 (ages 31-40), 117.7-122.7 (ages 41-50), and 113.3-116.1 steps/min (ages 51-60). Corresponding values for vigorous intensity were 140.3-144.1, 140.2-142.6, 139.3-143.6, and 131.6-132.8 steps/min, respectively. ROC analysis estimated chronologically-arranged age groups' cadence thresholds ranging from 114.5-118, 113.5-114.5, 104.6-112.9, and 103.6-106.0 across all moderate intensity indicators, and 127.5, 121.5, 117.2-123.2, and 113.0 steps/min, respectively, for vigorous intensity.

CONCLUSIONS

Heuristic cadence thresholds corresponding to relatively-defined moderate intensity for the chronologically-arranged age groups were ≥ 120, 120, 115, and 105 steps/min, regardless of the intensity indicator (i.e., % HRmax, %HRR, or RPE). Corresponding heuristic values for vigorous intensity indicators were ≥ 135, 130, 125, and 120 steps/min. These cadences are useful for predicting/programming intensity aligned with age-associated differences in physiological response to, and perceived experiences of, moderate and/or vigorous intensity.

TRIAL REGISTRATION

Clinicaltrials.gov NCT02650258 . Registered 24 December 2015.

Comparison of uniaxial and triaxial accelerometer outputs among individuals with and without Down syndrome

BACKGROUND

Using uniaxial accelerometry approach in measuring physical activity levels of individuals with Down syndrome (DS) might underestimate their energy expenditure due to the unique mediolateral walking pattern. Therefore, the purpose of this study was to examine and compare the relationship between two types of accelerometer outputs, uniaxial and triaxial, and energy expenditure in individuals with and without DS.

METHODS

Eighteen participants with DS and 19 participants without DS wore a GT3X+ accelerometer and a portable metabolic system in three different walking conditions.

RESULTS

Correlations between V̇O2 and each of the two accelerometer outputs (uniaxial: r = 0.75, triaxial: r = 0.75) were not significantly different among individuals without DS (z = 0.14, P = 0.89); however, significant differences in the relationship between V̇O2 and accelerometer outputs (uniaxial: r = 0.53, triaxial: r = 0.64) were observed among individuals with DS (z = -1.72, P < 0.046).

CONCLUSIONS

The findings suggest that when using accelerometers to measure physical activity levels for individuals with DS, triaxial outputs may better predict physical activity levels.

Using Cadence to Predict the Walk-to-Run Transition in Children and Adolescents: A Logistic Regression Approach

The natural transition from walking to running occurs in adults at ≅140 steps/min. It is unknown when this transition occurs in children and adolescents. The purpose of this study was to develop a model to predict age- and anthropometry-specific preferred transition cadences in individuals 6-20 years of age. Sixty-nine individuals performed sequentially faster 5-min treadmill walking bouts, starting at 0.22 m/s and increasing by 0.22 m/s until completion of the bout during which they freely chose to run. Steps accumulated during each bout were directly observed and converted to cadence (steps/min). A logistic regression model was developed to predict preferred transition cadences using the best subset of parameters. The resulting model, which included age, sex, height, and BMI z-score, produced preferred transition cadences that accurately classified gait behaviour (k-fold cross-validated prediction accuracy =97.02%). This transition cadence ranged from 136-161 steps/min across the developmental age range studied. The preferred transition cadence represents a simple and practical index to predict and classify gait behaviour from wearable sensors in children, adolescents, and young adults. Moreover, herein we provide an equation and an open access online R Shiny app that researchers, practitioners, or clinicians can use to predict individual-specific preferred transition cadences.

Walking cadence (steps/min) and intensity in 41 to 60-year-old adults: the CADENCE-adults study

BACKGROUND

In younger adults (i.e., those < 40 years of age) a walking cadence of 100 steps/min is a consistently supported threshold indicative of absolutely-defined moderate intensity ambulation (i.e., ≥ 3 metabolic equivalents; METs). Less is known about the cadence-intensity relationship in adults of middle-age.

PURPOSE

To establish heuristic (i.e., evidence-based, practical, rounded) cadence thresholds for absolutely-defined moderate (3 METs) and vigorous (6 METs) intensity in adults 41 to 60 years of age.

METHODS

In this cross-sectional study, 80 healthy adults of middle-age (10 men and 10 women representing each 5-year age-group between 41 to 60 years; body mass index = 26.0 ± 4.0 kg/m2) walked on a treadmill for 5-min bouts beginning at 0.5 mph and increasing in 0.5 mph increments. Performance termination criteria included: 1) transitioning to running, 2) reaching 75% of age-predicted maximum heart rate, or 3) reporting a Borg rating of perceived exertion > 13. Cadence was directly observed (i.e., hand tallied). Intensity (i.e., oxygen uptake [VO2] mL/kg/min) was assessed with an indirect calorimeter and converted to METs (1 MET = 3.5 mL/kg/min). A combination of segmented regression and Receiver Operating Characteristic (ROC) modeling approaches was used to identify optimal cadence thresholds. Final heuristic thresholds were determined based on an evaluation of classification accuracy (sensitivity, specificity, positive and negative predictive value, overall accuracy).

RESULTS

The regression model identified 101.7 (95% Predictive Interval [PI]: 54.9-110.6) and 132.1 (95% PI: 122.0-142.2) steps/min as optimal cadence thresholds for 3 METs and 6 METs, respectively. Corresponding values based on ROC models were 98.5 (95% Confidence Intervals [CI]: 97.1-104.9) and 117.3 (95% CI: 113.1-126.1) steps/min. Considering both modeling approaches, the selected heuristic thresholds for moderate and vigorous intensity were 100 and 130 steps/min, respectively.

CONCLUSIONS

Consistent with our previous report in 21 to 40-year-old adults, cadence thresholds of 100 and 130 steps/min emerged as heuristic values associated with 3 and 6 METs, respectively, in 41 to 60-year-old adults. These values were selected based on their utility for public health messaging and on the trade-offs in classification accuracy parameters from both statistical methods. Findings will need to be confirmed in older adults and in free-living settings.

Effects of Four-Day School Weeks on Physical Education Exposure and Childhood Obesity

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.

Association of Teacher-Level Factors With Implementation of Classroom-Based Physical Activity Breaks

BACKGROUND

Classroom-based physical activity (CBPA) breaks are a common strategy to increase elementary school children's physical activity (PA) levels. There is limited research examining how teacher-level factors impact teacher implementation of CBPA breaks. In this study, we assessed the relationship of teacher-level factors with teacher use of a CBPA resource.

METHODS

We randomized 6 elementary schools in rural Oregon into control (N = 3) or intervention (N = 3) conditions. Each teacher at intervention schools received the CBPA resource. Teachers at control schools received 1 CBPA-Toolkit per grade level to share, and received no training. We surveyed teachers on their use of the toolkit, implementation support and self-efficacy, and value for PA. Logistic regression was used to examine the odds of toolkit use by teacher-level factors.

RESULTS

Among survey respondents (N = 83), 57% were self-identified toolkit users and 48% attended a training. Training participation and teacher implementation self-efficacy were associated with greater odds of using the toolkit (odds ratio, OR = 7.76 [95% confidence interval, CI = 1.39-43.19] and OR = 5.54 [95% CI = 1.24-23.87], respectively).

CONCLUSION

CBPA tools supported with training aimed at developing teachers' implementation self-efficacy increased the likelihood of teachers employing CBPA tools.

Scaling of adult human bone and skeletal muscle mass to height in the US population

OBJECTIVES

The scaling of structural components to body size is well studied in mammals, although comparable human observations in a large and diverse sample are lacking. The current study aimed to fill this gap by examining the scaling relationships between total body (TB) and regional bone and skeletal muscle (SM) mass with body size, as defined by stature, in a nationally representative sample of the US population.

METHODS

Subjects were 17,126 non-Hispanic (NH) white, NH black, and Mexican American men and women, aged ≥18 years, evaluated in the National Health and Nutrition Examination Survey who had TB and regional bone mineral (BMin) and lean soft tissue (LST) mass measured by dual-energy X-ray absorptiometry. BMin and appendicular LST served as surrogate bone and SM mass measures, respectively. The allometric model, BMin or LST = α(height)^β , in a logarithmic form was used to generate scaling exponents.

RESULTS

The findings were similar across all gender and race groups: body mass scaled to height with powers of ~2.0 (mean β ± SE, 1.94 ± 0.08-2.29 ± 0.09) while TB and appendicular BMin and appendicular LST scaled to height with consistently larger powers than those for body mass (eg, all P < .05 in NH white men and women); the largest BMin and LST scaling powers to height were observed in the lower extremities.

CONCLUSIONS

Bone and SM mass, notably those of the lower extremities, increase as proportions of body mass with greater adult height. Metabolic and biomechanical implications emerge from these observations, the first of their kind in a representative adult US population sample.

Walking cadence (steps/min) and intensity in 21-40 year olds: CADENCE-adults

BACKGROUND

Previous studies have reported that walking cadence (steps/min) is associated with absolutely-defined intensity (metabolic equivalents; METs), such that cadence-based thresholds could serve as reasonable proxy values for ambulatory intensities.

PURPOSE

To establish definitive heuristic (i.e., evidence-based, practical, rounded) thresholds linking cadence with absolutely-defined moderate (3 METs) and vigorous (6 METs) intensity.

METHODS

In this laboratory-based cross-sectional study, 76 healthy adults (10 men and 10 women representing each 5-year age-group category between 21 and 40 years, BMI = 24.8 ± 3.4 kg/m2) performed a series of 5-min treadmill bouts separated by 2-min rests. Bouts began at 0.5 mph and increased in 0.5 mph increments until participants: 1) chose to run, 2) achieved 75% of their predicted maximum heart rate, or 3) reported a Borg rating of perceived exertion > 13. Cadence was hand-tallied, and intensity (METs) was measured using a portable indirect calorimeter. Optimal cadence thresholds for moderate and vigorous ambulatory intensities were identified using a segmented regression model with random coefficients, as well as Receiver Operating Characteristic (ROC) models. Positive predictive values (PPV) of candidate heuristic thresholds were assessed to determine final heuristic values.

RESULTS

Optimal cadence thresholds for 3 METs and 6 METs were 102 and 129 steps/min, respectively, using the regression model, and 96 and 120 steps/min, respectively, using ROC models. Heuristic values were set at 100 steps/min (PPV of 91.4%), and 130 steps/min (PPV of 70.7%), respectively.

CONCLUSIONS

Cadence thresholds of 100 and 130 steps/min can serve as reasonable heuristic thresholds representative of absolutely-defined moderate and vigorous ambulatory intensity, respectively, in 21-40 year olds. These values represent useful proxy values for recommending and modulating the intensity of ambulatory behavior and/or as measurement thresholds for processing accelerometer data.

TRIAL REGISTRATION

Clinicaltrials.gov ( NCT02650258 ).

Worker acceptability of the Pennington Pedal Desk™ occupational workstation alternative

BACKGROUND

Active workstation alternatives (e.g., treadmill desks and pedal desks) have the potential to elevate workplace energy expenditure by replacing occupational sedentary behavior with opportunities to generate low-intensity non-exercise physical activity, but only to the extent that workers find them acceptable and congruent with their primary working tasks and therefore can frequently use them for extended periods of time.

OBJECTIVE

To assess workers' acceptability of the Pennington Pedal Desk™.

METHODS

Full-time sedentary workers (N = 42; 76% female; mean+SD age 39.6±11.3 years; BMI 25.7±5.4 kg/m2) used the pedal desk for 15 minutes while they: 1) searched the internet, 2) composed an email, and 3) completed acceptability ratings using an online Likert scale anchored from 1/strongly disagree to 5/strongly agree. Garmin Vector power meter pedals and EDGE 510 GPS bike computer (Garmin ®, USA) continuously captured revolutions per minute (RPM) and power.

RESULTS

Participants indicated that they would use the pedal desk for 4 (median) hours per work day and 97.6% of participants were somewhat or completely confident that they could type proficiently while using the pedal desk. Participants pedaled at 54.8±11.2 RPM and 23.1±8.6 watts (mean+SD).

CONCLUSIONS

Participants rated the Pennington Pedal Desk™ workstation positively and indicated potential for extended daily use.

Daily Physical Activity by Occupational Classification in US Adults: NHANES 2005-2006

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.

Can an automated sleep detection algorithm for waist-worn accelerometry replace sleep logs?

The purpose of this study was to test whether estimates of bedtime, wake time, and sleep period time (SPT) were comparable between an automated algorithm (ALG) applied to waist-worn accelerometry data and a sleep log (LOG) in an adult sample. A total of 104 participants were asked to log evening bedtime and morning wake time and wear an ActiGraph wGT3X-BT accelerometer at their waist for 24 h/day for 7 consecutive days. Mean difference and mean absolute difference (MAD) were computed. Pearson correlations and dependent-sample t tests were used to compare LOG-based and ALG-based sleep variables. Effect sizes were calculated for variables with significant mean differences. A total of 84 participants provided 2+ days of valid accelerometer and LOG data for a total of 368 days. There was no mean difference (p = 0.47) between LOG 472 ± 59 min and ALG SPT 475 ± 66 min (MAD = 31 ± 23 min, r = 0.81). There was no significant mean difference between bedtime (2348 h and 2353 h for LOG and ALG, respectively; p = 0.14, MAD = 25 ± 21 min, r = 0.92). However, there was a significant mean difference between LOG (0741 h) and ALG (0749 h) wake times (p = 0.01, d = 0.11, MAD = 24 ± 21 min, r = 0.92). The LOG and ALG data were highly correlated and relatively small differences were present. The significant mean difference in wake time might not be practically meaningful (Cohen’s d = 0.11), making the ALG useful for sample estimates. MAD, which gives a better estimate of the expected differences at the individual level, also demonstrated good evidence supporting ALG individual estimates.

Promoting Healthy Diet, Physical Activity, and Life-Skills in High School Athletes: Results from the WAVE Ripples for Change Childhood Obesity Prevention Two-Year Intervention

The purpose of this study was to compare changes in diet and daily physical activity (PA) in high school (HS) soccer players who participated in either a two-year obesity prevention intervention or comparison group, while controlling for sex, race/ethnicity, and socioeconomic status. Participants (n = 388; females = 58%; Latino = 38%; 15.3 ± 1.1 years, 38% National School Breakfast/Lunch Program) were assigned to either an intervention (n = 278; 9 schools) or comparison group (n = 110; 4 schools) based on geographical location. Pre/post intervention assessment of diet was done using Block Fat/Sugar/Fruit/Vegetable Screener, and daily steps was done using the Fitbit-Zip. Groups were compared over-time for mean changes (post-pre) in fruit/vegetables (FV), saturated fat (SF), added sugar, and PA (daily steps, moderate-to-vigorous PA) using analysis of covariance. The two-year intervention decreased mean added sugar intake (-12.1 g/day, CI (7.4, 16.8), p = 0.02); there were no differences in groups for FV or SF intake (p = 0.89). For both groups, PA was significantly higher in-soccer (9937 steps/day) vs. out-of-soccer season (8117 steps/day), emphasizing the contribution of organized sports to youth daily PA. At baseline, Latino youth had significantly higher added sugar intake (+14 g/day, p < 0.01) than non-Latinos. Targeting active youth in a diet/PA intervention improves diet, but out of soccer season youth need engagement to maintain PA (200).

How fast is fast enough? Walking cadence (steps/min) as a practical estimate of intensity in adults: a narrative review

Background

Cadence (steps/min) may be a reasonable proxy-indicator of ambulatory intensity. A summary of current evidence is needed for cadence-based metrics supporting benchmark (standard or point of reference) and threshold (minimums associated with desired outcomes) values that are informed by a systematic process.

Objective

To review how fast, in terms of cadence, is enough, with reference to crafting public health recommendations in adults.

Methods

A comprehensive search strategy was conducted to identify relevant studies focused on walking cadence and intensity for adults. Identified studies (n=38) included controlled (n=11), free-living observational (n=18) and intervention (n=9) designs.

Results

There was a strong relationship between cadence (as measured by direct observation and objective assessments) and intensity (indirect calorimetry). Despite acknowledged interindividual variability, ≥100 steps/min is a consistent heuristic (e.g, evidence-based, rounded) value associated with absolutely defined moderate intensity (3 metabolic equivalents (METs)). Epidemiological studies report notably low mean daily cadences (ie, 7.7 steps/min), shaped primarily by the very large proportion of time (13.5 hours/day) spent between zero and purposeful cadences (<60 steps/min) at the population level. Published values for peak 1-min and 30-min cadences in healthy free-living adults are >100 and >70 steps/min, respectively. Peak cadence indicators are negatively associated with increased age and body mass index. Identified intervention studies used cadence to either prescribe and/or quantify ambulatory intensity but the evidence is best described as preliminary.

Conclusions

A cadence value of ≥100 steps/min in adults appears to be a consistent and reasonable heuristic answer to ’How fast is fast enough?' during sustained and rhythmic ambulatory behaviour.

Trial registration number

NCT02650258

Cadence (steps/min) and intensity during ambulation in 6-20 year olds: the CADENCE-kids study

BACKGROUND

Steps/day is widely utilized to estimate the total volume of ambulatory activity, but it does not directly reflect intensity, a central tenet of public health guidelines. Cadence (steps/min) represents an overlooked opportunity to describe the intensity of ambulatory activity. We sought to establish thresholds linking directly observed cadence with objectively measured intensity in 6-20 year olds.

METHODS

One hundred twenty participants completed multiple 5-min bouts on a treadmill, from 13.4 m/min (0.80 km/h) to 134.0 m/min (8.04 km/h). The protocol was terminated when participants naturally transitioned to running, or if they chose to not continue. Steps were visually counted and intensity was objectively measured using a portable metabolic system. Youth metabolic equivalents (METy) were calculated for 6-17 year olds, with moderate intensity defined as ≥4 and < 6 METy, and vigorous intensity as ≥6 METy. Traditional METs were calculated for 18-20 year olds, with moderate intensity defined as ≥3 and < 6 METs, and vigorous intensity defined as ≥6 METs. Optimal cadence thresholds for moderate and vigorous intensity were identified using segmented random coefficients models and receiver operating characteristic (ROC) curves.

RESULT

Participants were on average (± SD) aged 13.1 ± 4.3 years, weighed 55.8 ± 22.3 kg, and had a BMI z-score of 0.58 ± 1.21. Moderate intensity thresholds (from regression and ROC analyses) ranged from 128.4 steps/min among 6-8 year olds to 87.3 steps/min among 18-20 year olds. Comparable values for vigorous intensity ranged from 157.7 steps/min among 6-8 year olds to 119.3 steps/min among 18-20 year olds. Considering both regression and ROC approaches, heuristic cadence thresholds (i.e., evidence-based, practical, rounded) ranged from 125 to 90 steps/min for moderate intensity, and 155 to 125 steps/min for vigorous intensity, with higher cadences for younger age groups. Sensitivities and specificities for these heuristic thresholds ranged from 77.8 to 99.0%, indicating fair to excellent classification accuracy.

CONCLUSIONS

These heuristic cadence thresholds may be used to prescribe physical activity intensity in public health recommendations. In the research and clinical context, these heuristic cadence thresholds have apparent value for accelerometer-based analytical approaches to determine the intensity of ambulatory activity.

Step-Based Physical Activity Metrics and Cardiometabolic Risk: NHANES 2005-2006

PURPOSE

This study aimed to catalog the relationships between step-based accelerometer metrics indicative of physical activity volume (steps per day, adjusted to a pedometer scale), intensity (mean steps per minute from the highest, not necessarily consecutive, minutes in a day; peak 30-min cadence), and sedentary behavior (percent time at zero cadence relative to wear time; %TZC) and cardiometabolic risk factors.

METHODS

We analyzed data from 3388 participants, 20+ yr old, in the 2005-2006 National Health and Nutrition Examination Survey with ≥1 valid day of accelerometer data and at least some data on weight, body mass index, waist circumference, systolic and diastolic blood pressure, glucose, insulin, HDL cholesterol, triglycerides, and/or glycohemoglobin. Linear trends were evaluated for cardiometabolic variables, adjusted for age and race, across quintiles of steps per day, peak 30-min cadence, and %TZC.

RESULTS

Median steps per day ranged from 2247 to 12,334 steps per day for men and from 1755 to 9824 steps per day for women, and median peak 30-min cadence ranged from 48.1 to 96.0 steps per minute for men and from 40.8 to 96.2 steps per minute for women for the first and fifth quintiles, respectively. Linear trends were statistically significant (all P < 0.001), with increasing quintiles of steps per day and peak 30-min cadence inversely associated with waist circumference, weight, body mass index, and insulin for both men and women. Median %TZC ranged from 17.6% to 51.0% for men and from 19.9% to 47.6% for women for the first and fifth quintiles, respectively. Linear trends were statistically significant (all P < 0.05), with increasing quintiles of %TZC associated with increased waist circumference, weight and insulin for men, and insulin for women.

CONCLUSIONS

This analysis identified strong linear relationships between step-based movement/nonmovement dimensions and cardiometabolic risk factors. These data offer a set of quantified access points for studying the potential dose-response effects of each of these dimensions separately or collectively in longitudinal observational or intervention study designs.

Allometrically Scaled Children's Clinical and Free-Living Ambulatory Behavior

PURPOSE

This study aimed to compare clinical and free-living walking cadence in school-age children and to examine how the allometric scaling of leg length variability affects objective ambulatory activity assessment.

METHODS

A total of 375 children (154 boys and 221 girls, 9-11 yr old) completed GAITRite-determined slow, normal, and fast walks and wore accelerometers for 1 wk. Dependent variables from clinical assessment included gait speed, cadence, and step length, whereas steps per day, peak 1-min cadence, and peak 60-min cadence were assessed during free living. Analogous allometrically scaled variables were used to account for leg length differences. Free-living times above clinically determined individualized slow, normal, and fast cadence values were calculated. Differences in dependent variables between sex and sex-specific leg length tertiles were assessed.

RESULTS

Clinically assessed cadence (mean ± SD) was 90.9 ± 15.2 (slow), 113.8 ± 12.9 (normal), and 148.9 ± 20.9 (fast) steps per minute, respectively. During free living, participants accumulated 8651 ± 2259 steps per day. Peak 1-min cadence was 113.4 ± 12.4 steps per minute and peak 60-min cadence was 60.1 ± 11.4 steps per minute. Allometrically scaling gait variables to leg length eliminated the previously significant leg length effect observed in both clinical and free-living gait variables but did not affect the observation that girls exhibited lower levels of free-living ambulatory behavior measured by mean steps per day. On average, all groups spent <15 min·d above clinically determined slow cadence; this was unaffected by leg length.

CONCLUSION

Allometrically scaling gait variables to leg length significantly affected the assessment of ambulatory behavior, such that different leg length groups appear to walk in a dynamically similar manner. Leg length effects on free-living ambulatory behavior were also eliminated by implementing estimates of time spent above individualized cadence cut points derived from clinical gait assessment.

Impact of Prescribed Exercise on Physical Activity Compensation in Young Adults

Liguori, G, Schuna, JM Jr, Tucker, J, and Fountaine, CM. Impact of prescribed exercise on physical activity compensation in young adults. J Strength Cond Res 31(2): 503-508, 2017-Army Reserve Officers' Training Corps cadets present a unique subpopulation because they are required to participate in regular physical activity (PA). This study describes PA patterns of cadets and attempts to identify evidence of nonexercise PA compensation (activitystat) as a result of prescribed PA (pPA) by comparing differences between training and nontraining days for (a) autonomous PA among cadets and (b) PA between cadets and noncadets. Participants included 84 university students (33 cadets and 51 noncadets) who each wore an accelerometer for 5 consecutive days to estimate moderate and vigorous physical activity (MVPA). A 2×2 mixed model analysis of variance was used to examine within- and between-group differences in MVPA on training and nontraining days. This analysis was repeated after removing the cadet's pPA. Cadets had lower-body fat than noncadets (p = 0.044), but all other characteristics were similar. Overall, moderate PA (MPA) and vigorous PA (VPA) were significantly greater among cadets (p = 0.048 and p < 0.001), because of greater weekend MPA (p = 0.021) and greater weekday VPA (p < 0.001). Cadets accumulated more MVPA on training days than nontraining days (p < 0.001) and accumulated more MVPA than noncadets on training days (p = 0.004). However, after accounting for pPA, cadet MVPA did not differ between training and nontraining days (within 1.2Â ± 18.4 min·d) and was similar between cadets and noncadets (within 1.5Â ± 5.9 min·d). These results suggest that cadets were significantly more active than noncadets due mainly to pPA. When controlling for pPA, cadets were similarly active across all days, and were as active as noncadets, indicating no evidence of activitystat in this population.