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.

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.

Cadence (steps/min) as an indicator of the walk-to-run transition.

BACKGROUND: Humans naturally transition from walking to running at a point known as the walk-to-run transition (WRT). The WRT commonly occurs at a speed of ∼2.1 m/s (m/s) or a Froude number (dimensionless value considering leg length) of 0.5. Emerging evidence suggests the WRT can also be classified using a cadence of 140 steps/min. An accurate cadence-based WRT metric would aid in classifying wearable technology minute-level step metrics as walking vs. running. PURPOSE: To evaluate performance of 1) WRT predictors directly identified from a treadmill-based dataset of sequentially faster bouts, and 2) accepted WRT predictors compiled from previous literature. METHODS: Twenty-eight adults (71.4% men; age = 36.6 ± 12.8 years, BMI = 26.2 ± 4.7 kg/m2) completed a series of five-minute treadmill walking bouts increasing in 0.2 m/s increments until they freely chose to run. Optimal WRT values for speed, Froude number, and cadence were identified using receiver operating characteristic (ROC) curve analyses. WRT value performance was evaluated via classification accuracy metrics. RESULTS: Overall accuracies (metric, percent) according to WRT predictors from previous literature were: speed (2.1 m/s, 55.0%), Froude number (0.5, 76.8%), and cadence (140 steps/min, 91.1%), and those from the dataset herein were: speed (1.9 and 2.0 m/s, 78.6%), Froude number (0.68, 77.3%), and cadence (134, 139, and 141 steps/min, 92.9%). The three equally accurate cadence values support a heuristic range of cadence-based WRT values in young and middle-aged adults: 135-140 steps/min. SIGNIFICANCE: A tight range of cadence values performed better as WRT predictors compared to either previously reported or directly identified speed or Froude number values. These findings have important implications for gait classification, especially considering cadence is a simple metric which can be readily assessed across settings using direct observation or wearable technologies.

Cadence-based classification of moderate-intensity overground walking in 41- to 85-year-old adults.

BACKGROUND: Walking cadence (steps/min) has emerged as a valid proxy of physical activity intensity, with consensus across numerous laboratory-based treadmill studies that ≥100 steps/min approximates absolutely defined moderate intensity (≥3 metabolic equivalents; METs). We recently reported that this cadence threshold had a classification accuracy of 73.3% for identifying moderate intensity during preferred pace overground walking in young adults. The purpose of this study was to evaluate and compare the performance of a cadence threshold of ≥100 steps/min for correctly classifying moderate intensity during overground walking in middle- and older-aged adults. METHODS: Participants (N = 174, 48.3% female, 41-85 years of age) completed laboratory-based cross-sectional study involving an indoor 5-min overground walking trial at their preferred pace. Steps were manually counted and converted to cadence (total steps/5 min). Intensity was measured using indirect calorimetry and expressed as METs. Classification accuracy (sensitivity, specificity, accuracy) of a cadence threshold of ≥100 steps/min to identify individuals walking at ≥3 METs was calculated. RESULTS: The ≥100 steps/min threshold demonstrated accuracy of 74.7% for classifying moderate intensity. When comparing middle- vs. older-aged adults, similar accuracy (73.4% vs. 75.8%, respectively) and specificity (33.3% vs. 34.5%) were observed. Sensitivity was high, but was lower for middle- vs. older-aged adults (85.2% vs. 93.9%, respectively). CONCLUSION: A cadence threshold of ≥100 steps/min accurately identified moderate-intensity overground walking. Furthermore, accuracy was similar when comparing middle- and older-aged adults. These findings extend our previous analysis in younger adults and confirm the appropriateness of applying this cadence threshold across the adult lifespan.

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.

Time Trends of Step-Determined Physical Activity Among Adolescents With Different Activity Levels in Czech Republic.

BACKGROUND: This study aimed to present step-determined physical activity trends in adolescents with different activity levels over a period of 10 years. METHODS: Pedometers were used to monitor weekly physical activity in 1855 boys and 2648 girls aged 15-19 years recruited from 155 schools in the Czech Republic between 2009 and 2018. Trends for average steps/day and percent of accumulating various levels of steps/day (<10,000, 10,000-13,000, and >13,000 steps/d) were analyzed by sex. RESULTS: There was a statistically significant decrease in average steps/day between 2009-2010 and 2017-2018 in boys from 12,355 (3936) steps/d to 10,054 (3730) steps/d and girls from 11,501 (3278) steps/d to 10,216 (3288) steps/d. The percent accumulating <10,000 steps/d increased by 21% in boys and 12% in girls. The percent achieving >13,000 steps/d decreased by 17% in boys and 10% in girls. CONCLUSIONS: Objectively collected evidence indicates an overall decrease in Czech adolescents' steps/day over a 10-year period concurrent with an increase in the percent of boys and girls accumulating <10,000 steps/d. These trends are concerning as they portend a decline in physical activity as adolescents transition to adulthood and continue to age, which also may have major health implications.

Classification of moderate-intensity overground walking speed in 21- to 85-year-old adults.

The Compendium of Physical Activities reports that walking at 2.5 mph associates with absolutely-defined moderate intensity (i.e., ≥3 metabolic equivalents [METs]). However, it is unclear whether this speed threshold is accurate during overground walking and/or across the adult age-span. This study aimed to identify optimal and heuristic speed thresholds associated with 3 METs during overground walking across age groups. Healthy adults (n = 248, 21-85 years old, 49% women) performed a 5-minute self-paced overground walking trial. Speed was measured using an electronic gait mat, and oxygen uptake was measured using indirect calorimetry and converted to METs. Optimal and heuristic thresholds and classification accuracy metrics were determined and compared using ROC curve analyses. Speed thresholds (95% CIs) associated with 3 METs for the whole sample, young (21-40 years), middle-aged (41-60 years) and older-aged (61-85 years) groups were 1.29 (1.25, 1.33), 1.30 (1,26, 1,35), and 1.25 (1.21, 1.29) m/s, respectively. Overall, 3 mph and 5 km/h performed better than 2.5 mph and 4.5 km/h in balancing both sensitivity and specificity (higher Youden's Indices). Overground walking speeds associated with 3 METs were similar across age groups. A heuristic threshold of 3 mph or 5 km/h may better identify absolutely-defined moderate intensity overground walking.

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.

Ratings of Perceived Exertion During Walking: Predicting Major Mobility Disability and Effect of Structured Physical Activity in Mobility-Limited Older Adults.

BACKGROUND: This study evaluated the association between ratings of perceived exertion (RPE) of walking and major mobility disability (MMD), as well as their transitions in response to a physical activity (PA) compared to a health education (HE) program. METHODS: Older adults (n = 1633) who were at risk for mobility impairment were randomized to structured PA or HE programs. During a 400 m walk, participants rated exertion as "light" or "hard." An MMD event was defined as the inability to walk 400 m. MMD events and RPE values were assessed every 6 months for an average of 2.6 years. RESULTS: Participants rating their exertion as "hard" had a nearly threefold higher risk of MMD compared with those rating their exertion as "light" (HR: 2.61, 95% CI: 2.19-3.11). The association was held after adjusting for disease conditions, depression, cognitive function, and walking speed (HR: 2.24, 95% CI: 1.87-2.69). The PA group was 25% more likely to transition from "light" to "hard" RPE than the HE group (HR: 1.25, 95% CI: 1.05-1.49). Additionally, the PA group was 27% (HR: 0.73, 95% CI: 0.55 - 0.97) less likely to transition from a "hard" RPE to inability to walk 400 m and was more likely to recover their ability to walk 400 m by transitioning to a "hard" RPE (HR: 2.10, 95% CI: 1.39-3.17) than the HE group. CONCLUSIONS: Older adults rating "hard" effort during a standardized walk test were at increased risk of subsequent MMD. A structured PA program enabled walking recovery, but was more likely to increase transition from "light" to "hard" effort, which may reflect the greater capacity to perform the test.

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.

Effect of an office-based intervention on visceral adipose tissue: the WorkACTIVE-P randomized controlled trial.

Office-based activity reduces sedentariness, yet no randomized controlled trials (RCTs) have assessed how such activity influences visceral adipose tissue (VAT). This study examined the effect of an office-based, multicomponent activity intervention on VAT. The WorkACTIVE-P RCT enrolled sedentary office workers (body mass index: 31.4 (standard deviation (SD) 4.4) kg/m2) to an intervention (n = 20) or control (n = 20) group. For 3 months, the intervention group received an office-based pedal desk, further to an intervention promoting its use and increased walking. The control group maintained habitual activity. At baseline and follow-up, VAT, cardiometabolic disease risk markers, physical activity, and food intake were measured. Steps/day were not altered relative to control (P ≥ 0.51), but the pedal desk was utilized for 127 (SD 61) min/day. The intervention reduced VAT relative to control (-0.15 kg; 95% confidence interval (CI) = -0.29 to -0.01; P = 0.04). Moreover, the intervention decreased fasting glucose compared with control (-0.29 mmol/L; 95% CI = -0.51 to -0.06; P = 0.01), but no differences in other cardiometabolic disease markers or food intake were revealed (P ≥ 0.11). A multicomponent intervention decreased VAT in office workers who were overweight or obese. Though longer-term studies are needed, office-based, multicomponent activity regimens may lower cardiometabolic disease risk. Trial registered at ClinicalTrials.gov (NCT02561611). Novelty: In WorkACTIVE-P, a multicomponent activity intervention decreased visceral adipose tissue relative to control in office workers. The intervention also reduced glucose compared with control, though other metabolic risk markers and food intake were not altered. Such multicomponent interventions could help reduce cardiometabolic disease risk, but longer studies are needed.

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.

Development of a Cadence-based Metabolic Equation for Walking.

PURPOSE: This study aimed to develop cadence-based metabolic equations (CME) for predicting the intensity of level walking and evaluate these CME against the widely adopted American College of Sports Medicine (ACSM) Metabolic Equation, which predicts walking intensity from speed and grade. METHODS: Two hundred and thirty-five adults (21-84 yr of age) completed 5-min level treadmill walking bouts between 0.22 and 2.24 m·s, increasing by 0.22 m·s for each bout. Cadence (in steps per minute) was derived by dividing directly observed steps by bout duration. Intensity (oxygen uptake; in milliliters per kilogram per minute) was measured using indirect calorimetry. A simple CME was developed by fitting a least-squares regression to the cadence-intensity relationship, and a full CME was developed through best subsets regression with candidate predictors of age, sex, height, leg length, body mass, body mass index (BMI), and percent body fat. Predictive accuracy of each CME and the ACSM metabolic equation was evaluated at normal (0.89-1.56 m·s) and all (0.22-2.24 m·s) walking speeds through k-fold cross-validation and converted to METs (1 MET = 3.5 mL·kg·min). RESULTS: On average, the simple CME predicted intensity within ~1.8 mL·kg·min (~0.5 METs) at normal walking speeds and with negligible (<0.01 METs) bias. Including age, leg length, and BMI in the full CME marginally improved predictive accuracy (≤0.36 mL·kg·min [≤0.1 METs]), but may account for larger (up to 2.5 mL·kg·min [0.72 MET]) deviations in the cadence-intensity relationships of outliers in age, stature, and/or BMI. Both CME demonstrated 23%-35% greater accuracy and 2.2-2.8 mL·kg·min (0.6-0.8 METs) lower bias than the ACSM metabolic equation's speed-based predictions. CONCLUSIONS: Although the ACSM metabolic equation incorporates a grade component and is convenient for treadmill-based applications, the CME developed herein enables accurate quantification of walking intensity using a metric that is accessible during overground walking, as is common in free-living contexts.

Older Adults' Daily Step Counts and Time in Sedentary Behavior and Different Intensities of Physical Activity.

BACKGROUND: Daily step count is the simplest measure of physical activity. However, little is known about how daily step count related to time spent in different intensities of physical activity (PA) and sedentary behavior (SB). METHODS: These cross-sectional data were derived from 450 older Japanese adults (56.7% men; mean age, 74.3 years) who were randomly selected from three communities and responded a survey. Daily step count and time spent in moderate-to-vigorous PA (MVPA), light-intensity PA (LPA), and SB were measured using a validated wearable technology (HJA-350IT). Associations of daily step count with time spent in measured behaviors were examined using linear regression models with isometric log-ratio transformations of time-use composition, adjusting for gender, age, and residential area. RESULTS: Participants averaged 5,412 (standard deviation, 2,878) steps/d and accumulated MVPA, LPA, and SB corresponding to 4.0%, 34.8%, and 61.2% of daily waking time, respectively. Daily step count significantly increased with increase in time spent in MVPA relative to other behaviors (ie, LPA and SB) and in the ratio of LPA to SB after allowing for MVPA. After stratification, daily step count was significantly related to the ratio of LPA to SB in those taking <5,000 steps/d, but not in those taking 5,000-7,499 and ≥7,500 steps/d. CONCLUSIONS: Higher daily step count can be an indicator of not only larger relative contribution of time spent in MVPA, but also higher ratio between LPA and SB, particularly among those who are the least physically active.

A Transparent Method for Step Detection using an Acceleration Threshold.

Step-based metrics provide simple measures of ambulatory activity, yet device software either includes undisclosed proprietary step detection algorithms or simply do not compute step-based metrics. We aimed to develop and validate a simple algorithm to accurately detect steps across various ambulatory and non-ambulatory activities. Seventy-five adults (21-39 years) completed seven simulated activities of daily living (e.g., sitting, vacuuming, folding laundry) and an incremental treadmill protocol from 0.22-2.2ms-1. Directly observed steps were hand-tallied. Participants wore GENEActiv and ActiGraph accelerometers, one of each on their waist and on their non-dominant wrist. Raw acceleration (g) signals from the anterior-posterior, medial-lateral, vertical, and vector magnitude (VM) directions were assessed separately for each device. Signals were demeaned across all activities and bandpass filtered [0.25, 2.5Hz]. Steps were detected via peak picking, with optimal thresholds (i.e., minimized absolute error from accumulated hand counted) determined by iterating minimum acceleration values to detect steps. Step counts were converted into cadence (steps/minute), and k-fold cross-validation quantified error (root mean squared error [RMSE]). We report optimal thresholds for use of either device on the waist (threshold=0.0267g) and wrist (threshold=0.0359g) using the VM signal. These thresholds yielded low error for the waist (RMSE<173 steps, ≤2.28 steps/minute) and wrist (RMSE<481 steps, ≤6.47 steps/minute) across all activities, and outperformed ActiLife's proprietary algorithm (RMSE=1312 and 2913 steps, 17.29 and 38.06 steps/minute for the waist and wrist, respectively). The thresholds reported herein provide a simple, transparent framework for step detection using accelerometers during treadmill ambulation and activities of daily living for waist- and wrist-worn locations.

Outdoor Walking Speeds of Apparently Healthy Adults: A Systematic Review and Meta-analysis.

BACKGROUND: Walking outdoors can be used by many individuals to meet public health guidelines for moderate-to-vigorous-intensity physical activity. The speed at which adults walk may be a proxy for intensity. Traditional estimates of indoor walking speed are unlikely to reflect self-selected usual or other instructed paces of outdoor walking speed. OBJECTIVE: To inform estimates of pace-based walking speed of apparently healthy adults in outdoor settings. METHODS: We searched four electronic databases for articles published in English between January 1970 and March 2019. Studies that reported walking speed (m/s), cadence (steps/min), or intensity (mL/kg/min) of ambulatory, apparently healthy, and community-dwelling adults (> 18 years) were included. Walking speed categories were defined according to the description provided in each study. Meta-analysis was used to synthesise speed, cadence, and intensity data by slow, usual, medium, fast, and maximal pace (where reported). RESULTS: Thirty-five studies, representing 14,015 participants (6808 women, 5135 men, and 2072 sex not specified), were identified. The mean (95% CI) walking speed for slow, usual, medium, fast, and maximal pace was 0.82 (0.77-0.86), 1.31 (1.27-1.35), 1.47 (1.44-1.49), 1.72 (1.64-1.81), and 1.62 (1.45-1.79) m/s, respectively. Mean cadence (95% CI) for usual and fast paces were 116.65 (114.95-118.35) and 126.75 (121.87-131.63) steps/min, respectively. The mean oxygen consumption (95% CI) for the usual and medium paces was 11.97 (11.69-12.25) and 13.34 (12.94-13.73) mL/kg/min, respectively. CONCLUSION: These findings provide greater clarity with regard to how various indicators of enacted walking pace, speed, and intensity overlap and how each can be best communicated in the real-world setting to optimise health-related outcomes. Pace-based instructions can be used to support walking in outdoor settings within public health guidelines.