Jerks are Useful: Extracting pulse rate from wrist-placed accelerometry jerk during sleep in children

STUDY OBJECTIVES

Evaluate wrist-placed accelerometry predicted heartrate compared to electrocardiogram (ECG) heartrate in children during sleep.

METHODS

Children (n=82, 61% male, 43.9% Black) wore a wrist-placed Apple Watch Series 7 (AWS7) and ActiGraph GT9X during a polysomnogram. 3-Axis accelerometry data was extracted from AWS7 and the GT9X. Accelerometry heartrate estimates were derived from jerk (the rate of acceleration change), computed using the peak magnitude frequency in short time Fourier Transforms of Hilbert transformed jerk computed from acceleration magnitude. Heartrates from ECG traces were estimated from R-R intervals using R-pulse detection. Lin's Concordance Correlation Coefficient (CCC), mean absolute error (MAE) and mean absolute percent error (MAPE) assessed agreement with ECG estimated heartrate. Secondary analyses explored agreement by polysomnography sleep stage and a signal quality metric.

RESULTS

The developed scripts are available on Github. For the GT9X, CCC was poor at -0.11 and MAE and MAPE were high at 16.8 (SD=14.2) beats/minute and 20.4% (SD=18.5%). For AWS7, CCC was moderate at 0.61 while MAE and MAPE were lower at 6.4 (SD=9.9) beats/minute and 7.3% (SD=10.3%). Accelerometry estimated heartrate for AWS7 was more closely related to ECG heartrate during N2, N3 and REM sleep than lights on, wake, and N1 and when signal quality was high. These patterns were not evident for the GT9X.

CONCLUSIONS

Raw accelerometry data extracted from AWS7, but not the GT9X, can be used to estimate heartrate in children while they sleep. Future work is needed to explore the sources (i.e., hardware, software, etc.) of the GT9X's poor performance.

Comparison of raw accelerometry data from ActiGraph, Apple Watch, Garmin, and Fitbit using a mechanical shaker table

The purpose of this study was to evaluate the reliability and validity of the raw accelerometry output from research-grade and consumer wearable devices compared to accelerations produced by a mechanical shaker table. Raw accelerometry data from a total of 40 devices (i.e., n = 10 ActiGraph wGT3X-BT, n = 10 Apple Watch Series 7, n = 10 Garmin Vivoactive 4S, and n = 10 Fitbit Sense) were compared to reference accelerations produced by an orbital shaker table at speeds ranging from 0.6 Hz (4.4 milligravity-mg) to 3.2 Hz (124.7mg). Two-way random effects absolute intraclass correlation coefficients (ICC) tested inter-device reliability. Pearson product moment, Lin's concordance correlation coefficient (CCC), absolute error, mean bias, and equivalence testing were calculated to assess the validity between the raw estimates from the devices and the reference metric. Estimates from Apple, ActiGraph, Garmin, and Fitbit were reliable, with ICCs = 0.99, 0.97, 0.88, and 0.88, respectively. Estimates from ActiGraph, Apple, and Fitbit devices exhibited excellent concordance with the reference CCCs = 0.88, 0.83, and 0.85, respectively, while estimates from Garmin exhibited moderate concordance CCC = 0.59 based on the mean aggregation method. ActiGraph, Apple, and Fitbit produced similar absolute errors = 16.9mg, 21.6mg, and 22.0mg, respectively, while Garmin produced higher absolute error = 32.5mg compared to the reference. ActiGraph produced the lowest mean bias 0.0mg (95%CI = -40.0, 41.0). Equivalence testing revealed raw accelerometry data from all devices were not statistically significantly within the equivalence bounds of the shaker speed. Findings from this study provide evidence that raw accelerometry data from Apple, Garmin, and Fitbit devices can be used to reliably estimate movement; however, no estimates were statistically significantly equivalent to the reference. Future studies could explore device-agnostic and harmonization methods for estimating physical activity using the raw accelerometry signals from the consumer wearables studied herein.

Sociodemographic influences on youth sport participation and physical activity among children living within concentrated Hispanic/Latino rural communities

Introduction

Lack of physical activity (PA) among children living in rural communities is a documented public health problem. Although studies have examined community conditions defined by a rural-urban dichotomy, few have investigated rural community conditions with a concentration of Hispanic/Latino people. This cross-sectional study examined sociodemographic characteristics associated with youth sport (YS) participation and daily PA among children living within concentrated Hispanic/Latino rural U.S. Midwest communities.

Methods

During spring 2022, 97% of 3rd-6th grade children (n = 281, aged approximately 8-12 years) attending school in rural Midwestern communities (n = 2) with >50% concentration of Hispanic students participated in the Wellscapes Project, a community randomized trial. Participants completed the Youth Activity Profile and supplemental National Survey of Children's Health questions assessing PA behaviors and YS participation. Caregivers of a subsample of children (n = 215; males, n = 93; females, n = 122) consented to pair their child's survey results with school enrollment records (e.g., free/reduced lunch status and race and ethnicity). Mixed models with community as a random effect examined main and interaction effects of grade, sex, ethnoracial status, and family income on YS participation and these sociodemographic characteristics and YS participation on daily moderate-to-vigorous PA (MVPA).

Results

Approximately half of children participated in YS. Non-Hispanic White children (n = 82) were over five times more likely to participate in YS than Hispanic peers (n = 133) (OR = 5.54, 95% CI = 2.64-11.61, p < 0.001). YS participants accumulated 8.3 ± 2.3 more minutes of daily MVPA than non-participants (p < 0.001). Sixth graders, females, and Hispanic children reported lower daily MVPA than comparison groups (p < 0.05). Significant interaction effects on daily MVPA between grade and ethnoracial status (F(3, 204) = 3.04, p = 0.030) were also found.

Discussion

Disparities in sport participation and PA outcomes based on sociodemographic characteristics exist among children living in ethnoracially diverse rural communities. Strategies to promote YS participation, including community structural changes, may help reduce PA disparities. The research provides valuable insights for policymakers, public health professionals, and community members to address YS participation barriers, not limited to cost, while considering other PA-promotion efforts to improve child population health.

A Device Agnostic Approach to Predict Children's Activity from Consumer Wearable Accelerometer Data: A Proof-of-Concept Study

INTRODUCTION

This study examined the potential of a device agnostic approach for predicting physical activity from consumer wearable accelerometry compared with a research-grade accelerometry.

METHODS

Seventy-five 5- to 12-year-olds (58% male, 63% White) participated in a 60-min protocol. Children wore wrist-placed consumer wearables (Apple Watch Series 7 and Garmin Vivoactive 4) and a research-grade device (ActiGraph GT9X) concurrently with an indirect calorimeter (COSMED K5). Activity intensities (i.e., inactive, light, moderate-to-vigorous physical activity) were estimated via indirect calorimetry (criterion), and the Hildebrand thresholds were applied to the raw accelerometer data from the consumer wearables and research-grade device. Epoch-by-epoch (e.g., weighted sensitivity, specificity) and discrepancy (e.g., mean bias, absolute error) analyses evaluated agreement between accelerometry-derived and criterion estimates. Equivalence testing evaluated the equivalence of estimates produced by the consumer wearables and ActiGraph.

RESULTS

Estimates produced by the raw accelerometry data from ActiGraph, Apple, and Garmin produced similar criterion agreement with weighted sensitivity = 68.2% (95% confidence interval (CI), 67.1%-69.3%), 73.0% (95% CI, 71.8%-74.3%), and 66.6% (95% CI, 65.7%-67.5%), respectively, and weighted specificity = 84.4% (95% CI, 83.6%-85.2%), 82.0% (95% CI, 80.6%-83.4%), and 75.3% (95% CI, 74.7%-75.9%), respectively. Apple Watch produced the lowest mean bias (inactive, -4.0 ± 4.5; light activity, 2.1 ± 4.0) and absolute error (inactive, 4.9 ± 3.4; light activity, 3.6 ± 2.7) for inactive and light physical activity minutes. For moderate-to-vigorous physical activity, ActiGraph produced the lowest mean bias (1.0 ± 2.9) and absolute error (2.8 ± 2.4). No ActiGraph and consumer wearable device estimates were statistically significantly equivalent.

CONCLUSIONS

Raw accelerometry estimated inactive and light activity from wrist-placed consumer wearables performed similarly to, if not better than, a research-grade device, when compared with indirect calorimetry. This proof-of-concept study highlights the potential of device-agnostic methods for quantifying physical activity intensity via consumer wearables.

Estimating Physical Activity and Sleep using the Combination of Movement and Heart Rate: A Systematic Review and Meta-Analysis

The purpose of this meta-analysis was to quantify the difference in physical activity and sleep estimates assessed via 1) movement, 2) heart rate (HR), or 3) the combination of movement and HR (MOVE+HR) compared to criterion indicators of the outcomes. Searches in four electronic databases were executed September 21-24 of 2021. Weighted mean was calculated from standardized group-level estimates of mean percent error (MPE) and mean absolute percent error (MAPE) of the proxy signal compared to the criterion measurement method for physical activity, HR, or sleep. Standardized mean difference (SMD) effect sizes between the proxy and criterion estimates were calculated for each study across all outcomes, and meta-regression analyses were conducted. Two-One-Sided-Tests method were conducted to metaanalytically evaluate the equivalence of the proxy and criterion. Thirty-nine studies (physical activity k = 29 and sleep k = 10) were identified for data extraction. Sample size weighted means for MPE were -38.0%, 7.8%, -1.4%, and -0.6% for physical activity movement only, HR only, MOVE+HR, and sleep MOVE+HR, respectively. Sample size weighted means for MAPE were 41.4%, 32.6%, 13.3%, and 10.8% for physical activity movement only, HR only, MOVE+HR, and sleep MOVE+HR, respectively. Few estimates were statistically equivalent at a SMD of 0.8. Estimates of physical activity from MOVE+HR were not statistically significantly different from estimates based on movement or HR only. For sleep, included studies based their estimates solely on the combination of MOVE+HR, so it was impossible to determine if the combination produced significantly different estimates than either method alone.

An observational pilot evaluation of the Walk with Ease program for reducing fall risk among older adults

BACKGROUND

Physical activity is an effective method of reducing fall risk among older adults. Previous evaluations of the six-week Walk with Ease (WWE) program have documented benefits to functional outcomes, but the potential effects on reducing fall risk have not been evaluated. This pilot study evaluates outcomes of a community delivered WWE program for potential suitability as a fall risk reduction program.

METHODS

A total of 59 older adults (age > 60) enrolled in a group version of WWE delivered by trained community-based leaders. Complete data (pre- and post-program) from functional fitness tests and behavioral instruments were obtained from 41 participants (aged 74.4 ± 6.6 years, 70% female). Functional outcomes included the 10-foot timed up and go (TUG), 30-second chair stand (CST) and 4-stage balance test (BT) included as part of STEADI, as well as a two-minute step test (ST) and normal gait speed test (GST). Survey assessments included STEADI fall risk screening, self-reported physical activity, and fear of falling measures. Analyses focused on reporting pre-post effect sizes, but paired t-tests were used to test statistical significance of differences.

RESULTS

Improvements in functional performance approached significance for both CST (d = 0.31, p = 0.06) and ST (d = 0.26, p = 0.12), but all other tests were nonsignificant. Survey results demonstrated significant increases in self-reported walking (d = 0.54, p = 0.02) and moderate-to-vigorous physical activity (MVPA; d = 0.56, p = 0.004), but perceived fear of falling and overall fall risk scores had smaller, non-significant, effects (d ranging from 0.01 to 0.31). Stratified analysis suggested that participants screened at an elevated risk for falls at baseline consistently had larger effects on all functional and survey assessments, though the analysis was underpowered to test significance.

CONCLUSIONS

Walk with Ease participation significantly increased self-reported physical activity but did not significantly improve physical function or reduce fall risk. However, consistently larger effect sizes among participants screened as at-risk for falls suggest that the program may be beneficial for those with elevated risk for falls or functional limitations. Further research is needed to document the consistency of these effects among participants with elevated fall risk status.

Criterion validity of wrist accelerometry for assessing energy intake via the intake-balance technique

BACKGROUND

Intake-balance assessments measure energy intake (EI) by summing energy expenditure (EE) with concurrent change in energy storage (ΔES). Prior work has not examined the validity of such calculations when EE is estimated via open-source techniques for research-grade accelerometry devices. The purpose of this study was to test the criterion validity of accelerometry-based intake-balance methods for a wrist-worn ActiGraph device.

METHODS

Healthy adults (n = 24) completed two 14-day measurement periods while wearing an ActiGraph accelerometer on the non-dominant wrist. During each period, criterion values of EI were determined based on ΔES measured by dual X-ray absorptiometry and EE measured by doubly labeled water. A total of 11 prediction methods were tested, 8 derived from the accelerometer and 3 from non-accelerometry methods (e.g., diet recall; included for comparison). Group-level validity was assessed through mean bias, while individual-level validity was assessed through mean absolute error, mean absolute percentage error, and Bland-Altman analysis.

RESULTS

Mean bias for the three best accelerometry-based methods ranged from -167 to 124 kcal/day, versus -104 to 134 kcal/day for the non-accelerometry-based methods. The same three accelerometry-based methods had mean absolute error of 323-362 kcal/day and mean absolute percentage error of 18.1-19.3%, versus 353-464 kcal/day and 19.5-24.4% for the non-accelerometry-based methods. All 11 methods demonstrated systematic bias in the Bland-Altman analysis.

CONCLUSIONS

Accelerometry-based intake-balance methods have promise for advancing EI assessment, but ongoing refinement is necessary. We provide an R package to facilitate implementation and refinement of accelerometry-based methods in future research (see paulhibbing.com/IntakeBalance).

Evaluation of a device-agnostic approach to predict sleep from raw accelerometry data collected by Apple Watch Series 7, Garmin Vivoactive 4, and ActiGraph GT9X Link in children with sleep disruptions

GOAL AND AIMS

Evaluate the performance of a sleep scoring algorithm applied to raw accelerometry data collected from research-grade and consumer wearable actigraphy devices against polysomnography.

FOCUS METHOD/TECHNOLOGY

Automatic sleep/wake classification using the Sadeh algorithm applied to raw accelerometry data from ActiGraph GT9X Link, Apple Watch Series 7, and Garmin Vivoactive 4.

REFERENCE METHOD/TECHNOLOGY

Standard manual PSG sleep scoring.

SAMPLE

Fifty children with disrupted sleep (M = 8.5 years, range = 5-12 years, 42% Black, 64% male).

DESIGN

Participants underwent to single night lab polysomnography while wearing ActiGraph, Apple, and Garmin devices.

CORE ANALYTICS

Discrepancy and epoch-by-epoch analyses for sleep/wake classification (devices vs. polysomnography).

ADDITIONAL ANALYTICS AND EXPLORATORY ANALYSES

Equivalence testing for sleep/wake classification (research-grade actigraphy vs. commercial devices).

CORE OUTCOMES

Compared to polysomnography, accuracy, sensitivity, and specificity were 85.5, 87.4, and 76.8, respectively, for Actigraph; 83.7, 85.2, and 75.8, respectively, for Garmin; and 84.6, 86.2, and 77.2, respectively, for Apple. The magnitude and trend of bias for total sleep time, sleep efficiency, sleep onset latency, and wake after sleep were similar between the research and consumer wearable devices.

IMPORTANT ADDITIONAL OUTCOMES

Equivalence testing indicated that total sleep time and sleep efficiency estimates from the research and consumer wearable devices were statistically significantly equivalent.

CORE CONCLUSION

This study demonstrates that raw acceleration data from consumer wearable devices has the potential to be harnessed to predict sleep in children. While further work is needed, this strategy could overcome current limitations related to proprietary algorithms for predicting sleep in consumer wearable devices.

Contextualizing Adolescent Female Physical Activity Behavior: A Descriptive Study

Physical activity (PA) behavior tends to decline as youth get older, especially in female adolescents. The purpose of this study was to develop an understanding of female adolescent moderate-to-vigorous physical activity (MVPA) behavior. Baseline MVPA data was collected during year one of a female-specific PA related program. The Youth Activity Profile was administered to contextualize current middle school female PA levels. Data were collected on over 600 6th-8th grade youths with even distributions by grade. No significant differences between grade, race/ethnicity, and MVPA minutes were found. The average estimated value for daily MVPA across all grades was 43.93 (+/-12.97) min, which is considerably lower than the public health recommendation of 60 min per days. Similar amounts were observed for weekend days 45.03 (+/-19.98) and weekdays 45.50 (+/-13.14); however, allocations were smaller during school (9.45 +/- 5.13 min) than at home (34.04 +/- 11.15). The findings from this study highlight the need for further investigation in developing sustainable and innovative PA interventions that target adolescent females.

Effects of a peer health coaching program on college student lifestyle behaviors

Objective: Health coaching (HC) may promote healthy behaviors in incoming college students. Participants: 187 undergraduate students (76% female; age 18.6 ± 1.6) were recruited to participate in a peer HC program. Methods: Participants received four HC sessions in eight-weeks to work toward self-selected goals of physical activity (PA), diet, or stress management. PA was assessed using the International Physical Activity Questionnaire Short-Form, diet with the Eating Habits Confidence Survey, and stress with the Perceived Stress Scale. Results: Repeated measures ANOVAs investigated lifestyle behavior changes in 130 participants. Significant effects of time were reported, with a 39.6% gain in PA, 9.9% increase in dietary habit, and 16.3% decline in stress levels with moderate to large effect sizes (ηp2: 0.07-0.17; p< 0.01). Conclusion: The peer HC model promoted healthy lifestyles in college students. Additional research is needed to understand the effects of HC specifically for each goal, and student reactions to peer-led HC.

A cluster-randomized trial comparing two SWITCH implementation support strategies for school wellness intervention effectiveness

BACKGROUND

The School Wellness Integration Targeting Child Health (SWITCH) intervention has demonstrated feasibility as an implementation approach to help schools facilitate changes in students' physical activity (PA), sedentary screen time (SST), and dietary intake (DI). This study evaluated the comparative effectiveness of enhanced (individualized) implementation and standard (group-based) implementation.

METHODS

Twenty-two Iowa elementary schools participated, with each receiving standardized training (wellness conference and webinars). Schools were matched within region and randomized to receive either individualized or group implementation support. The PA, SST, and DI outcomes of 1097 students were assessed at pre- and post-intervention periods using the Youth Activity Profile. Linear mixed models evaluated differential change in outcomes by condition, for comparative effectiveness, and by gender.

RESULTS

Both implementation conditions led to significant improvements in PA and SST over time (p < 0.01), but DI did not improve commensurately (p value range: 0.02‒0.05). There were no differential changes between the group and individualized conditions for PA (p = 0.51), SST (p = 0.19), or DI (p = 0.73). There were no differential effects by gender (i.e., non-significant condition-by-gender interactions) for PA (p_{for interaction} = 0.86), SST (p_{for interaction} = 0.46), or DI (p_{for interaction} = 0.15). Effect sizes for both conditions equated to approximately 6 min more PA per day and approximately 3 min less sedentary time.

CONCLUSION

The observed lack of difference in outcomes suggests that group implementation of SWITCH is equally effective as individualized implementation for building capacity in school wellness programming. Similarly, the lack of interaction by gender suggests that SWITCH can be beneficial for both boys and girls. Additional research is needed to understand the school-level factors that influence implementation (and outcomes) of SWITCH.

Comparing enhancements to well-child visits in the prevention of obesity: ENCIRCLE cluster-randomized controlled trial

BACKGROUND

Obesity disproportionally impacts rural, lower-income children in the United States. Primary care providers are well-positioned to engage parents in early obesity prevention, yet there is a lack of evidence regarding the most effective care delivery models. The ENCIRCLE study, a pragmatic cluster-randomized controlled trial, will respond to this gap by testing the comparative effectiveness of standard care well-child visits (WCV) versus two enhancements: adding a patient-reported outcome (PRO) measure (PRO WCV) and PRO WCV plus Food Care (telehealth coaching and a grocery store tour).

METHODS

A total of 2,025 parents and their preschool-aged children (20-60 months of age) will be recruited from 24 Geisinger primary care clinics, where providers are randomized to the standard WCV, PRO WCV, or PRO WCV plus Food Care intervention arms. The PRO WCV includes the standard WCV plus collection of the PRO-the Family Nutrition and Physical Activity (FNPA) risk assessment-from parents. Parents complete the PRO in the patient-portal or in the clinic (own device, tablet, or kiosk), receive real-time feedback, and select priority topics to discuss with the provider. These results are integrated into the child's electronic health record to inform personalized preventive counseling by providers. PRO WCV plus Food Care includes referrals to community health professionals who deliver evidence-based obesity prevention and food resource management interventions via telehealth following the WCV. The primary study outcome is change in child body mass index z-score (BMIz), based on the World Health Organization growth standards, 12 months post-baseline WCV. Additional outcomes include percent of children with overweight and obesity, raw BMI, BMI50, BMIz extended, parent involvement in counseling, health behaviors, food resource management, and implementation process measures.

DISCUSSION

Study findings will inform health care systems' choices about effective care delivery models to prevent childhood obesity among a high-risk population. Additionally, dissemination will be informed by an evaluation of mediating, moderating, and implementation factors.

TRIAL REGISTRATION

ClinicalTrials.gov identifier (NCT04406441); Registered May 28, 2020.

COVID-19 pandemic and changes in children's physical activity in a rural US community: a mixed methods study

OBJECTIVES

To examine differences in rural community children's moderate-to-vigorous physical activity (MVPA) and participation in out-of-school activities from fall 2019 to fall 2020 and explore enacted PA opportunity modifications post initial COVID-19 disruption.

DESIGN

Mixed methods study using the validated Youth Activity Profile (YAP), administrator reports and stakeholder surveys and semistructured interviews.

SETTING

Children and community stakeholders from one rural US Great Plains community in the state of Nebraska were recruited.

PARTICIPANTS

Third through fifth graders in fall 2019 (n=144) and fall 2020 (n=174) reported MVPA and participation in out-of-school activities using the YAP. School administrators reported weekly physical education (PE) and recess minutes. Community stakeholders reported pandemic-related changes in community social structures in semistructured interviews (n=4) and surveys (n=19).

RESULTS

Average daily MVPA minutes increased from 2019 to 2020 (75.0 vs 81.3, SE=1.6, p<0.05). Minutes of MVPA increased during: school hours (MD=2.7, SE=0.5, p<0.5); out-of-school time on weekdays (MD=3.9, SE=1.3, p<0.5); and on weekends (MD=5.5, SE=2.4, p<0.5). On average, fewer children participated in youth sport (42.5% vs 47.2%), youth clubs (10.3% vs 16.0%) and other out-of-school activities (24.1% vs 38.2%) in 2020, compared with 2019. Weekly PE/recess minutes increased from 208.3 to 241.7 from 2019 to 2020. Stakeholder surveys revealed community-driven modifications to PA opportunities, and interviews suggested children played outside more frequently, especially when school was closed and out-of-school activities were shut down.

CONCLUSIONS

Increased minutes of PE and recess, and decreased out-of-school activity participation may have increased children's overall free play and MVPA during the pandemic. Free play was an important contributor to children's PA during the pandemic and should be prioritised by educators, coaches and other leaders of child PA opportunities.

TRIAL REGISTRATION NUMBER

NCT03380143.

Family-Based Telehealth Initiative to Improve Nutrition and Physical Activity for Children With Obesity and Its Utility During COVID-19: A Mixed Methods Evaluation

Guidelines recommend primary care providers refer children with obesity to behavioral interventions, but given limited program availability, access, and parental engagement, referrals remain rare. We developed telehealth coaching interventions for families whose children received care at a health system in Pennsylvania, United States in 2019-2020. Intervention referrals were facilitated by the pediatrician and/or project team for 6–12-year-old children with obesity following well-child visits. Participants chose one of three 26-week interventions focused on healthy eating, physical activity, or a hybrid clinical/nutrition intervention. Interventions engaged parents as change agents, enhancing self-efficacy to model and reinforce behavior and providing resources to help create a healthy home environment. We enrolled 77 of 183 eligible parent/child dyads. We used mixed methods to evaluate the interventions. Repeated measures models among participants showed significant reductions in obesogenic nutrition behaviors post-intervention and at 1-year follow-up, including a reduction in sugar-sweetened beverage intake of 2.14 servings/week (95% confidence interval: −3.45, −0.82). There were also improvements in obesoprotective nutrition behaviors (e.g., frequency of family meals, parental self-efficacy related to meal management). One year post-baseline, we observed no significant differences in changes in body mass index (BMI) z-scores comparing child participants with matched controls. Given potential impacts of COVID-19 community restrictions on study outcomes, we conducted qualitative interviews with 13 participants during restrictions, which exemplified how disrupted routines constrained children’s healthy behaviors but that intervention participation prepared parents by providing cooking and physical activities at home. Findings support the potential of a telehealth-delivered nutrition intervention to support adoption of healthy weight behaviors.

Accuracy and Precision of Energy Expenditure, Heart Rate, and Steps Measured by Combined-Sensing Fitbits Against Reference Measures: Systematic Review and Meta-analysis

BACKGROUND

Although it is widely recognized that physical activity is an important determinant of health, assessing this complex behavior is a considerable challenge.

OBJECTIVE

The purpose of this systematic review and meta-analysis is to examine, quantify, and report the current state of evidence for the validity of energy expenditure, heart rate, and steps measured by recent combined-sensing Fitbits.

METHODS

We conducted a systematic review and Bland-Altman meta-analysis of validation studies of combined-sensing Fitbits against reference measures of energy expenditure, heart rate, and steps.

RESULTS

A total of 52 studies were included in the systematic review. Among the 52 studies, 41 (79%) were included in the meta-analysis, representing 203 individual comparisons between Fitbit devices and a criterion measure (ie, n=117, 57.6% for heart rate; n=49, 24.1% for energy expenditure; and n=37, 18.2% for steps). Overall, most authors of the included studies concluded that recent Fitbit models underestimate heart rate, energy expenditure, and steps compared with criterion measures. These independent conclusions aligned with the results of the pooled meta-analyses showing an average underestimation of -2.99 beats per minute (k comparison=74), -2.77 kcal per minute (k comparison=29), and -3.11 steps per minute (k comparison=19), respectively, of the Fitbit compared with the criterion measure (results obtained after removing the high risk of bias studies; population limit of agreements for heart rate, energy expenditure, and steps: -23.99 to 18.01, -12.75 to 7.41, and -13.07 to 6.86, respectively).

CONCLUSIONS

Fitbit devices are likely to underestimate heart rate, energy expenditure, and steps. The estimation of these measurements varied by the quality of the study, age of the participants, type of activities, and the model of Fitbit. The qualitative conclusions of most studies aligned with the results of the meta-analysis. Although the expected level of accuracy might vary from one context to another, this underestimation can be acceptable, on average, for steps and heart rate. However, the measurement of energy expenditure may be inaccurate for some research purposes.

Commercial Devices Provide Estimates of Energy Balance with Varying Degrees of Validity in Free-Living Adults

BACKGROUND

The challenges of accurate estimation of energy intake (EI) are well-documented, with self-reported values 12%-20% below expected values. New approaches rely on gold-standard assessments of the other components of energy balance, energy expenditure (EE) and energy storage (ES), to estimate EI.

OBJECTIVES

The purpose of this study was to evaluate the validity, repeatability, and measurement error of consumer devices when estimating energy balance in a free-living population.

METHODS

Twenty-four healthy adults (14 women, 10 men; mean ± SD age: 30.7 ± 8.2 y) completed two 14-d assessment periods, including assessments of EE and ES using gold-standard [doubly labeled water (DLW) and DXA] and commercial devices [Fitbit Alta HR activity monitor (Alta) and Fitbit Aria wireless body composition scale (Aria)], and of EI by dietician-administered recalls. Accuracy and validity were assessed using Spearman correlation, interclass correlation, mean absolute percentage error, and equivalency testing. We also applied linear measurement error modeling including error in gold-standard devices and within-subject repeated-measures design to calibrate consumer devices and quantify error.

RESULTS

There was moderate to strong agreement for EE between the Fitbit Alta and DLW at each time point (rs = 0.82 and 0.66 for Times 1 and 2, respectively). There was weak agreement for ES between the Fitbit Aria and DXA (rs = 0.15 and 0.49 for Times 1 and 2, respectively). Correlations between methods to assess EI ranged from weak to strong, with agreement between the DXA/DLW-calculated EI and dietary recalls being the highest (rs = 0.63 for Time 1 and 0.73 for Time 2). Only EE from the Fitbit Alta at Time 1 was equivalent to the DLW value using equivalency testing.

CONCLUSIONS

Commercial devices provide estimates of energy balance in free-living adults with varying degrees of validity compared to gold-standard techniques. EE estimates were the most robust overall, whereas ES estimates were generally poor.

Evaluation of a Large-Scale School Wellness Intervention Through the Consolidated Framework for Implementation Research (CFIR): Implications for Dissemination and Sustainability

Background

Numerous studies have tested school-based interventions promoting healthy behaviors in youth, but few have integrated dissemination and implementation (D&I) frameworks. Using D&I frameworks can inform if and how an evidence-based intervention is implemented and maintained and provide strategies to address contextual barriers. Such application is necessary to understand how and why interventions are sustained over time. We evaluated a school wellness initiative called SWITCH® (School Wellness Integration Targeting Child Health) to (1) assess implementation outcomes of adoption, fidelity, and penetration, (2) discern implementation determinants through the Consolidated Framework for Implementation Research (CFIR), and (3) examine differences among inexperienced and experienced schools and influential factors to sustainment.

Methods

A total of 52 schools from Iowa, United States enrolled in the 2019-2020 iteration of SWITCH (22 inexperienced; 30 experienced). The CFIR guided the adaptation of mixed methods data collection and analysis protocols for school settings. Specific attention was focused on (1) fidelity to core elements; (2) adoption of best practices; and (3) penetration of behavior change practices. Determinants were investigated through in-depth qualitative interviews and readiness surveys with implementation leaders. A systematic process was used to score CFIR domains (between -2 and +2) indicating positive or negative influence. Independent t-tests were conducted to capture differences between samples, followed by a cross-case analysis to compare determinants data. Inductive coding yielded themes related to sustainment of SWITCH beyond formal implementation support.

Results

Experienced schools had higher scores on fidelity/compliance (t = -1.86 p = 0.07) and adoption (t = -2.03 p = 0.04). CFIR determinants of innovation source, culture, relative priority, and leadership engagement were positive implementation determinants, whereas tension for change and networks and communications were negative determinants. Distinguishing factors between experienced and inexperienced schools were Readiness for Implementation and Self-efficacy (experienced significantly higher; p < 0.05). Strategies to enhance sustainability were increasing student awareness/advocacy, keeping it simple, and integrating into school culture.

Conclusions

Findings provide specific insights related to SWITCH implementation and sustainability but more generalized insights about the type of support needed to help schools implement and sustain school wellness programming. Tailoring implementation support to both inexperienced and experienced settings will ultimately enhance dissemination and sustainability of evidence-based interventions.

Association with Temperature Variability and Physical Activity, Sedentary Behavior, and Sleep in a Free-Living Population

The present study examines the temperature variability in physical activity (PA), sedentary behavior (SB), and sleep in a free-living population. A representative sample of 1235 adults (ages 21–70) from Iowa, U.S.A., wore a SenseWear Mini Armband (SWA) for a randomly assigned day. Koppen’s weather climate classification was used to precisely classify the temperature: cold (−13 to 32 °F), cool (32 to 50 °F), mild (50 to 64 °F), warm (64 to 73 °F), and hot (73 to 95 °F). The main effect of three-way ANOVA (age × gender × temperature) had differences for SB and sleep, with older adults having higher levels than younger adults (p < 0.05). However, moderate to vigorous PA (MVPA) did not vary systematically by age or gender, and contrary to expectations, the main effect of the weather was not significant for MVPA (p > 0.05). Participants spent more time participating in PA at cold than at hot temperatures. The results clarify the impact of temperature on shaping PA and SB patterns in adults. The variable impacts and differential patterns by age suggest that weather should be considered when interpreting differences in PA patterns in research or surveillance applications.

A protocol for coordinating rural community stakeholders to implement whole-of-community youth physical activity surveillance through school systems

Accurate and effective local data collection systems are needed to inform community change on youth health behaviors such as physical activity (PA). Systematic methods are particularly important for understanding PA behaviors that may be influenced by individual, interpersonal, organizational, and regional factors. The purpose of this study was to describe a protocol for coordinating community stakeholders to implement an online youth PA surveillance instrument. The research team collaborated with local health departments (LHDs) from two rural communities to coordinate schools in implementing school-wide youth PA surveillance. A data sharing agreement was established between all partners. School administrators and teachers attended in-person training sessions for an online PA survey and how to use the data. Following the training, students were provided individualized logins to complete the survey once a semester over a two-year academic period. Across both communities, 23 teachers and administrators attended the training sessions that were facilitated by the LHDs and research team. In Year 1 (Y1), a total of 465 3rd through 6th grade students were enrolled in the participating schools (community 1 = 227; community 2 = 238). Survey response rates ranged from 86.1% to 95.4% completion, depending on the community and semester. In Year 2 (Y2), a total of 501 3rd through 6th grade students were enrolled (community 1 = 260; community 2 = 241). Response rates ranged from 86.3% to 89.6% in the fall term. A protocol for coordinating LHD and community stakeholders was an effective strategy for implementing population-level youth PA surveillance with high levels of reach.

Parent and Child Perceptions of Barriers to Active School Commuting

BACKGROUND

Active commuting (AC) to and from school can contribute to physical activity, although it has recently seen a global decline. The purpose of this study was to examine the agreement between parent and child perceptions of barriers to school AC.

METHODS

Participants were parents (N = 152, M_age  = 40.6 ± 6.3 years) and elementary school children (N = 98, M_age  = 10.0 ± 1.2 years). School commute type/frequency and barriers to AC were collected via surveys. Intraclass correlation coefficients (ICCs) were used to assess relative agreement between parent and child perceptions (N = 98 dyads). Paired t tests and equivalence testing were employed to assess group-level agreement. Bland-Altman analysis was used to assess individual-level agreement. Partial correlations of AC with perceptions were also assessed.

RESULTS

All parent and child perceptions of barriers to AC to school had low agreement. Bland-Altman Plots indicated negative bias for all but 3 barrier perceptions. Paired t tests indicated significant differences between parent and child perceptions for 8 out of 15 barriers while equivalence testing deemed no parent-child perception equivalent. Partial correlations with AC frequency were significant for 7 parent perceptions and 2 child perceptions.

CONCLUSIONS

Parent and child perceptions have low agreement. Programs aimed at promoting AC to and from school should account for these discrepancies.

Parent Preferences for Physical Activity in Before and After School Programs in Rural and Suburban Communities: A Discrete Choice Experiment

BACKGROUND

The purpose of this study was to examine and compare parent preferences of before and after school physical activity program components in rural and suburban elementary schools.

METHODS

A discrete choice experiment was conducted to measure parent preferences for components of before/after school programs. A total of 183 parents (age = 37.2 [8.2] y, 155 females) sampled from 15 elementary schools (K-6 grades) in the Western United States took part in the study, half of which were from a rural community (n = 93, 50.8%). Results from the discrete choice experiment were analyzed using hierarchic Bayesian methodology, which estimated utility scores and was used to calculate important scores for program components.

RESULTS

The specific goal of the before/after school program was the strongest determinant of parents' stated choice overall, followed by leaders, time of day, length, and main focus. Learning sports as the physical activity goal was the top-rated attribute. Subgroup analyses revealed discrepancies between suburban and rural parents and parents of boys and girls.

CONCLUSION

This study extends the application of discrete choice experiments to school-based programming, providing a unique way to design empirically based, stakeholder informed school programs, specifically within before and after school settings.

Calibration of the Online Youth Activity Profile Assessment for School-Based Applications

A balance between the feasibility and validity of measures is an important consideration for physical activity research - particularly in school-based research with youth. The present study extends previously tested calibration methods to develop and test new equations for an online version of the Youth Activity Profile (YAP) tool, a self-report tool designed for school applications. Data were collected across different regions and seasons to develop more robust, generalizable equations. The study involved a total of 717 youth from 33 schools (374 elementary (ages 9-11), 224 middle (ages 11-14), and 119 high school (ages 14-18)) in two different states in the U.S. Participants wore a Sensewear monitor for a full week and then completed the online YAP at school to report physical activity (PA) and sedentary behaviors (SB) in school and at home. Accelerometer data were processed using an R-based segmentation program to compute PA and SB levels. Quantile regression models were used with half of the sample to develop item-specific YAP calibration equations and these were cross validated with the remaining half of the sample. Computed values of Mean Absolute Percent Error (MAPE) ranged from 15-25% with slightly lower error observed for the middle school sample. The new equations had improved precision compared to the previous versions when tested on the same sample. The online version of the YAP provides an efficient and effective way to capture school level estimates of PA and SB in youth.

School-based physical activity interventions in rural and urban/suburban communities: A systematic review and meta-analysis

Disparities in physical activity and health outcomes exist between urban and rural youth. School settings can be utilized to promote physical activity in youth regardless of urban-rural status. This systematic review and meta-analysis aimed to assess and compare the effect of rural and urban/suburban school-based physical activity programs on total physical activity in youth. A search of five databases was conducted. A total of 33 studies remained after the exclusion process, 28 of which took place in urban/suburban schools and five of which took place in rural schools. The DerSimonian and Laird random effects model was employed with the estimates of heterogeneity taken from the inverse-variance fixed-effect model. For rural studies, the Hartung-Knapp-Sidak-Jonkman method was used to obtain error estimates. Results from the total sample indicated a significant but small pooled increase in daily physical activity (Hedge's g = 0.12, 95% confidence interval [CI]: 0.06-0.18), which held for interventions conducted in urban/suburban schools (Hedge's g = 0.12, 95% CI: 0.06-0.19). For rural school-based interventions, there was no significant pooled effect (Hedge's g = 0.06, 95% CI: -0.50 to 0.61). This meta-analysis provides evidence that school-based interventions can be marginally effective for increasing daily physical activity in children and adolescents; however, no effect was observed for interventions implemented in rural settings.

Rural community systems: Youth physical activity promotion through community collaboration

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A community systems approach is important to identify social and geographic health impacts.

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Community stakeholders residing within the city had higher trust and collective efficacy scores.

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These stakeholders had roles directly leading physical activity opportunities for youth.

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Youth physical activity was greater in the community with stakeholders in administrative roles.

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Unique community variables should be studied to elucidate system drivers of physical activity.

A common way to address rural population health issues is through community stakeholders working together. Youth physical activity (PA) happens in adult-led in-school and out-of-school group opportunities that vary across communities and generally occur in isolated settings. This study explores similarities and differences in rural community system structure and collaborative process variables that help to conceptualize the collaborative impact influencing population youth PA outcomes. Stakeholders (Community 1, n = 23; Community 2, n = 26) and youth (Community 1, n = 205; Community 2, n = 213) were recruited in 2018–2019 as part of Wellscapes, a hybrid implementation-effectiveness community randomized trial. A stakeholder survey (n = 49) measured community system structures and collaboration processes. Youth completed the Youth Activity Profile to measure PA levels. More Community 1 respondents than Community 2 resided within city limits (73.9% vs. 34.6%). Collective efficacy was significantly greater in Community 1 (M = 4.0, SD = 0.5) than in 2 (M = 3.2, SD = 0.4), p < 0.05. Perceptions of trust scored significantly greater in Community 1 (M = 4.1, SD = 0.3) than in 2 (M = 3.3, SD = 0.5), p < 0.05. Though both communities met rural definitions and had stakeholder investment, Community 1 had a greater proportion of PA-implementing stakeholders and more residing within city limits which may have influenced that community’s higher scores in collective efficacy and trust. Community 2 had more stakeholders in administrator roles and yielded greater youth PA levels. Unique and common variables of rural communities should be considered in understanding system factors that impact youth PA.

Self-Regulations for Educators Questionnaire (SREQ) for implementation programming

The adoption and dissemination of evidence-based programs is predicated on multiple factors, including the degree to which key stakeholders are motivated to implement program best practices. The present study focuses on the development of indicators that capture motivations of teachers to adopt school wellness programming since personal motivations are central to achieving sustainable impacts in these settings. The study specifically describes the measurement development and validation of the Self-Regulations for Educators Questionnaire (SREQ), designed to measure educators’ autonomous and controlled motivation for adopting evidence-based programming in their schools. A naturalistic design to study motivation to adopt aspects of NFL PLAY60 programming through the NFL PLAY60 FitnessGram Partnership Project was used. A total of 1,106 teachers completed the SREQ online. Internal validity was assessed through exploratory and confirmatory factor analysis, and predictive validity using structural equation modeling (SEM). The results supported the two-factor solution with separate items capturing aspects of autonomous and controlled motivation. Both factors had good internal reliability and the item-total correlation coefficients were above 0.40 for both factors. The results also supported the predictive validity as autonomous motivation positively predicted the level of overall engagement, teaching effectiveness, fitness testing reports sent home, and completion of fitness testing with students (p < .05). Controlled motivation positively predicted whether the teachers conducted fitness testing and the engagement of Play 60 Challenge (p < .05). Findings suggest that the SREQ displays a number of psychometric characteristics that make the instrument useful for examining motivation of providers to implement evidence-based best practices.

Youth sport participation and physical activity in rural communities

Background

Physical activity, a high-frequency health behavior, varies by where children live, learn, and play. Children accumulate physical activity in adult-led in-school and out-of-school settings. Youth sport is a potential setting for physical activity, but there are differences in youth sport participation based on age, sex, and socioeconomic status. There is a gap in understanding demographic influences on youth sport participation and how these factors interact to influence physical activity. This study examines influences of grade, sex, and family income on youth sport participation and these factors and youth sport participation on moderate-to-vigorous physical activity of children in rural communities.

Methods

Children (n = 418 3rd–6th graders) living in two rural communities completed the online Youth Activity Profile as part of Wellscapes, a type 3 hybrid implementation-effectiveness community randomized trial. Mixed models with community as a random effect examined main effects and interactions of grade, sex, and family income on youth sport participation and these factors and youth sport participation on moderate-to-vigorous physical activity.

Results

About 80% of children engaged in youth sport, and full-pay lunch students were almost four times more likely to have youth sport participation than students with free/reduced lunch (OR = 3.91, 95% CI = 1.95, 7.8). Females and 6th graders (p < 0.05) had lower physical activity than comparison groups. Males with higher family income had greater physical activity; females with higher family income had less physical activity. For 6th graders, high family income had less effect on physical activity than similar 3rd-5th graders (p < 0.01).

Conclusions

While a fairly high percentage of children participate in youth sports, there are disparities in rural communities on youth sport participation and physical activity outcomes based on age, sex, and family income.

Transdisciplinary Translational Science for Youth Health and Wellness: Introduction to a Special Issue

Background

Transdisciplinary translational science applies interdisciplinary approaches to the generation of novel concepts, theories and methods involving collaborations among academic and non-academic partners, in order to advance the translation of science into broader community practice.

Objective

This paper introduces a special issue on transdisciplinary translational science for youth health and wellness. We provide an overview of relevant research paradigms, share the related goals of the Iowa State University Translational Research Network (U-TuRN), and introduce the specific papers in the issue.

Method

Authors were asked to submit empirical reports, programmatic reviews or policy-related papers that examined youth health issues from a transdisciplinary translational perspective.

Results

The papers included in this special issue each involve direct and fully-integrated community-university partnerships and collaborations between academic and non-academic partners in scholarship and research. Reports emphasize the value of the applied nature of the work with a research agenda driven primarily by real-world health and social needs.

Conclusions

There is growing acceptance of the need for transdisciplinary, community-university collaborative research approaches as a means to meet both the requirements posed by real-world problems as well as goals of advancing scientific knowledge and innovation. In this issue, readers will find papers that show the promise of rethinking existing conceptual frameworks to incorporate transdisciplinary approaches as a catalyst to addressing translational science questions related to the field of children and youth care.

Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis

BACKGROUND/OBJECTIVES

Evidence on the associations between lifestyle movement behaviors and obesity has been established without taking into account the time-constrained nature of categorized, time-based lifestyle behaviors. We examined the associations of sleep, sedentary behavior (SED), light-intensity physical activity (LPA), and moderate-to-vigorous PA (MVPA) with body mass index (BMI) using Compositional Data Analysis (CoDA), and compared the associations between a report-based method (24-h Physical Activity Recall; 24PAR) and a monitor-based method (SenseWear Armband; SWA).

SUBJECTS/METHODS

Replicate data from a representative sample of 1247 adults from the Physical Activity Measurement Survey (PAMS) were used in the study. Participants completed activity monitoring on two randomly selected days, each of which required wearing a SWA for a full day, and then completing a telephone-administered 24PAR the following day. Relationships among behavioral compositional parts and BMI were analyzed using CoDA via multiple linear regression models with both 24PAR and SWA data.

RESULTS

Using 24PAR, time spent in sleep (γ = -3.58, p = 0.011), SED (γ = 3.70, p = 0.002), and MVPA (γ = -0.53, p = 0.018) was associated with BMI. Using SWA, time spent in sleep (γ = -5.10, p < 0.001), SED (γ = 8.93, p < 0.001), LPA (γ = -3.12, p < 0.001), and MVPA (γ = -1.43, p < 0.001) was associated with BMI. The SWA models explained more variance in BMI (R2 = 0.28) compared with the 24PAR models (R2 = 0.07). The compositional isotemporal substitution models revealed reductions in BMI when replacing SED by MVPA, LPA (not with 24PAR) or sleep for both 24PAR and SWA, but the effect estimates were larger with SWA.

CONCLUSIONS

Favorable levels of relative time spent in lifestyle movement behaviors were, in general, associated with decreased BMI. The observed associations were stronger using the monitor-based SWA method compared with the report-based 24PAR method.

Evaluating the implementation of the SWITCH® school wellness intervention and capacity-building process through multiple methods

Background

School wellness programming is important for promoting healthy lifestyles and academic achievement in youth; however, research is needed on methods that can help schools implement and sustain such programs on their own. The purpose of this study was to investigate factors within and outside the school environment that influenced school capacity for implementation and potential sustainability of wellness programming.

Methods

As part of the School Wellness Integration Targeting Child Health (SWITCH®) intervention, elementary school wellness teams (N = 30) were guided through a capacity-building process focused on promoting the adoption of healthy lifestyle behaviors in students. Data on implementation were collected through three standardized surveys and interviews (pre-mid-post) and a post-implementation interview. Indicators of organizational capacity were assessed using the School Wellness Readiness Assessment (SWRA). Paired t-tests were run to assess changes in implementation (classroom, physical education, and lunchroom settings), capacity, and stakeholder engagement over time. One-way analysis of variance (ANOVA) tests were run to examine how implementation of best practices (low, moderate, high) explained differences in capacity gains. Qualitative data were analyzed through inductive and deductive analysis, following the Consolidated Framework for Implementation Research (CFIR).

Results

Paired t-tests showed non-significant increases in school and setting-specific capacity and implementation of SWITCH best practices over time, in addition to a consistent level of engagement from key stakeholders. ANOVA results revealed non-significant associations between implementation group and gains in school capacity (F [2, 24] = 1.63; p = .21), class capacity (F [2, 24]=0.20 p = .82), lunchroom capacity (F [2, 24]=0.29; p = .78), and physical education (F [2, 24]=1.45; p = .25). Qualitative data demonstrated that factors within the outer setting (i.e., engaging community partners) facilitated programming. Inner-setting factors (i.e., relationships with administration and staff) influenced implementation. Implementation process themes (e.g., planning, adaptation of resources to meet school capacity/needs, and engaging students as leaders) were cited as key facilitators. Schools discussed factors affecting sustainability, such as school culture and knowledge of school wellness policy.

Conclusions

The results from this implementation study document the importance of allowing schools to adapt programming to meet their local needs, and highlight the strengths of measuring multiple implementation outcomes. Increased support is needed for schools regarding the formation and improvement of wellness policies as a means to enhance sustainability over time.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-020-01070-y.

Feasibility and reliability of the Spanish version of the Youth Activity Profile questionnaire (YAP-Spain) in children and adolescents

Considerable public health efforts across the globe have focused on promoting physical activity (PA) and minimizing sedentary behaviour (SB) in youths. However, it is important to have valid, reliable and feasible methods to assess these behaviours in youths. The purpose of this study was to analyse the feasibility and reliability of the Spanish version of the previously validated Youth Activity Profile questionnaire (YAP) in children and adolescents. The YAP-S is a 15-item self-report instrument designed to capture PA and SB in youths. A total of 604 children (5-12 years old) and 346 adolescents (12-17 years old) filled out the questionnaire twice (14 days apart). Feasibility was evaluated through required time and number of misunderstood questions by participants. The test-retest reliability was examined using the weighted kappa coefficient (κ) and intraclass correlation coefficient. The average time to complete the questionnaire was 28.85 ± 14.28 and 12.24 ± 9.84 minutes in children and adolescents, respectively. No misunderstanding of questions was reported. The questionnaire showed an adequate reliability for activity at school, out-of-school and sedentary behaviours (k = 0.61-0.77; ICC = 0.77-0.89) in children and adolescents. The YAP-S might be considered a feasible and reliable questionnaire for assessing PA and SB in Spanish children and adolescents.

Longitudinal Associations between Physical Fitness and Academic Achievement in Youth

INTRODUCTION

Data from clinical trials have justified the promotion of fitness as a means to enhance facets of cognitive control and academic achievement in youth. However, such associations, when tested under real-world conditions, are equivocal. The purpose of this study, therefore, was to evaluate longitudinal associations between aerobic capacity (AC), weight status, and academic achievement within a large urban county.

METHODS

Longitudinal data were obtained from a sample of third, fifth, and seventh grade students in schools within an urban county in Georgia. Data on body mass index (BMI) were available from 11,639 students; AC data from 5735 students. Data on both indicators were obtained through the established FitnessGram assessment battery with 2-yr changes calculated using standardized Z scores. Academic achievement data were available from three subjects (math, science, and reading) for third, fifth, and seventh grade students, and 2-yr changes were computed using changes in Z scores for each test. Data were analyzed using generalized logistic models to test associations between change in BMI and AC in relation to changes in academic achievement.

RESULTS

Positive associations were observed between improvements in weight status and academic achievement for the fifth grade boys and girls ([reading] odds ratio [OR], 1.47; 95% confidence interval [CI], 1.25-1.72; [science] OR, 1.22; 95% CI, 1.04-1.42). Maintaining weight status was associated with improved scores in the third grade ([math] OR, 1.16; 95% CI, 1.012-1.327; [reading] OR, 1.47; 95% CI, 1.25-1.72) and fifth grade cohorts (math OR, 1.20; 95% CI, 1.00.1.43). For AC, no significant associations were found for any age cohort.

CONCLUSIONS

Modest associations between improvements in weight status, AC, and academic achievement are noteworthy, despite the lack of statistical significance for AC. The results provide a robust evaluation of associations between fitness and academic achievement.

School Wellness Environments: Perceptions Versus Realities

The U.S. Department of Agriculture Final Rule on School Wellness Policy requires schools to self-evaluate wellness policies and environments. To understand the utility of this information, this study evaluates the validity of school-reported wellness information against directly observed data. Wellness leaders at 10 Midwestern elementary schools completed a questionnaire spanning nine school wellness settings. School-reported information was compared against a direct observation protocol. Percent agreement and κ statistics were used to assess agreement between school reporters and direct observation. Overall percent agreement between reporters and direct observation was 77.1%. Agreement ranged from 67.3% (Lunchroom Environment) to 92.0% (School Wellness Policies) across the nine categories. κ results showed that 65.7% of the items demonstrated fair or better reporter agreement. The results provide preliminary support for the utility of schools' self-reported wellness information. Facilitation of independent reporting on wellness environments by school leaders will contribute to broader applications for school wellness programming.

Standardizing Analytic Methods and Reporting in Activity Monitor Validation Studies

INTRODUCTION

A lack of standardization with accelerometry-based monitors has made it hard to advance applications for both research and practice. Resolving these challenges is essential for developing methods for consistent, agnostic reporting of physical activity outcomes from wearable monitors in clinical applications.

METHODS

This article reviewed the literature on the methods used to evaluate the validity of contemporary consumer activity monitors. A rationale for focusing on energy expenditure as a key outcome measure in validation studies was provided followed by a summary of the strengths and limitations of different analytical methods. The primary review included 23 recent validation studies that collectively reported energy expenditure estimates from 58 monitors relative to values from appropriate criterion measures.

RESULTS

The majority of studies reported weak indicators such as correlation coefficients (87%), but only half (52%) reported the recommended summary statistic of mean absolute percent error needed to evaluate actual individual error. Fewer used appropriate tests of agreement such as equivalence testing (22%).

CONCLUSIONS

The use of inappropriate analytic methods and incomplete reporting of outcomes is a major limitation for systematically advancing research with both research grade and consumer-grade activity monitors. Guidelines are provided to standardize analytic methods and reporting in these types of studies to enhance the utility of the devices for clinical mHealth applications.

Association Between Comprehensive School Physical Activity Program Implementation and Principal Support

The use of Comprehensive School Physical Activity Program (CSPAP) has been recommended to help students achieve 60-minutes of physical activity each day. Implementing a CSPAP requires planning, coordination, and ongoing oversight, but an understudied factor is how principal support influences CSPAP implementation. The purpose of this study was to evaluate the impact of principal support on CSPAP implementation. Method. Schools in the Iowa FitnessGram Initiative (n = 84), a participatory network of schools committed to supporting physical education and wellness efforts, were invited to participate in the study. Physical education teachers from 42 schools completed a survey assessing CSPAP implementation and principal support for school wellness. Descriptive statistics and correlation analyses were used to report associations between the variables. A regression analysis was conducted to evaluate the impact of principal support on CSPAP implementation. Results. Almost half of the schools were reported to be fully implementing just one CSPAP component and no school was reported to be fully implementing all five. The CSPAP component with the highest reported level of implementation was quality physical education, while the lowest level of implementation was reported for family and community engagement and staff involvement. The regression analysis identified that principal support was a significant predictor of CSPAP implementation, b = 0.55, t(37) = 3.10, p < .004. Conclusions. Principal support is associated with implementation of CSPAP initiatives. Strategies that focus on how to attain principal support for CSPAP initiatives are needed and could have a significant impact on student physical activity and health.

Use of previous-day recalls of physical activity and sedentary behavior in epidemiologic studies: results from four instruments

BACKGROUND

The last few years have seen renewed interest in use-of-time recalls in epidemiological studies, driven by a focus on the 24-h day [including sleep, sitting, and light physical activity (LPA)] rather than just moderate-vigorous physical activity (MVPA). This paper describes four different computerised use-of-time instruments (ACT24, PAR, MARCA and cpar24) and presents population time-use data from a collective sample of 8286 adults from different population studies conducted in Australia/New Zealand, Germany and the United States.

METHODS

The instruments were developed independently but showed a number of similarities: they were self-administered through the web or used computer-assisted telephone interviews; all captured energy expenditure using variants of the Ainsworth Compendium; each had been validated against criterion measures; and they used a domain structure whereby activities were aggregated under categories such as Personal Care and Work.

RESULTS

Estimates of physical activity level (average daily rate of energy expenditure in METs) ranged from 1.53 to 1.78 in the four studies, strikingly similar to population estimates derived from doubly labelled water. There was broad agreement in the amount of time spent in sleep (7.2-8.6 h), MVPA (1.6-3.1 h), personal care (1.6-2.4 h), and transportation (1.1-1.8 h). There were consistent sex differences, with women spending 28-81% more time on chores, 8-40% more time in LPA, and 3-39% less time in MVPA than men.

CONCLUSIONS

Although there were many similarities between instruments, differences in operationalizing definitions of sedentary behaviour and LPA resulted in substantive differences in the amounts of time reported in sedentary and physically active behaviours. Future research should focus on deriving a core set of basic activities and associated energy expenditure estimates, an agreed classificatory hierarchy for the major behavioural and activity domains, and systems to capture relevant social and environmental contexts.

Accelerometer and self-reported measures of sedentary behaviour and associations with adiposity in UK youth

This study used accelerometer and self-report measures of overall sedentary time (ST) and screen time behaviours to examine their respective associations with adiposity among UK youth. Participants (Year groups 5, 8, and 10; n=292, 148 girls) wore the SenseWear Armband Mini accelerometer for eight days and completed the Youth Activity Profile, an online report tool designed to estimate physical activity and ST.Stature, body mass and waist circumference were measured to classify adiposity outcomes (overweight/obese and central obesity). One-way between groups ANOVA and adjusted linear, logistic and multinomial logistic regression analyses were conducted. There was a significant main effect of age on total ST across the whole week (F(2, 289)=41.64, p≤0.001). ST increased monotonically across Year 5 (581.09±107.81 min·d-¹), 8 (671.96±112.59 min·d-¹) and 10 (725.80±115.20 min·d-¹), and all pairwise comparisons were significant at p≤0.001. A steep age-related gradient to mobile phone use was present (p≤0.001). ST was positively associated with adiposity outcomes independent of moderate-to-vigorous intensity physical activity (MVPA; p≤0.001). Engaging in >3 hours of video gaming daily was positively associated with central obesity (OR=2.12, p≤0.05) but not after adjustment for MVPA. Results further demonstrate the importance of reducing overall ST to maintain healthy weight status among UK youth.

Evaluating Motivational Interviewing and Habit Formation to Enhance the Effect of Activity Trackers on Healthy Adults' Activity Levels: Randomized Intervention

Background

While widely used and endorsed, there is limited evidence supporting the benefits of activity trackers for increasing physical activity; these devices may be more effective when combined with additional strategies that promote sustained behavior change like motivational interviewing (MI) and habit development.

Objective

This study aims to determine the utility of wearable activity trackers alone or in combination with these behavior change strategies for promoting improvements in active and sedentary behaviors.

Methods

A sample of 91 adults (48/91 female, 53%) was randomized to receive a Fitbit Charge alone or in combination with MI and habit education for 12 weeks. Active and sedentary behaviors were assessed pre and post using research-grade activity monitors (ActiGraph and activPAL), and the development of habits surrounding the use of the trackers was assessed postintervention with the Self-Reported Habit Index. During the intervention, Fitbit wear time and activity levels were monitored with the activity trackers. Linear regression analyses were used to determine the influence of the trial on outcomes of physical activity and sedentary time. The influence of habits was examined using correlation coefficients relating habits of tracker use (wearing the tracker and checking data on the tracker and associated app) to Fitbit wear time and activity levels during the intervention and at follow-up.

Results

Regression analyses revealed no significant differences by group in any of the primary outcomes (all P>.05). However, personal characteristics, including lower baseline activity levels (beta=–.49, P=.01) and lack of previous experience with pedometers (beta=–.23, P=.03) were predictive of greater improvements in moderate and vigorous physical activity. Furthermore, for individuals with higher activity levels at the baseline, MI and habit education were more effective for maintaining these activity levels when compared with receiving a Fitbit alone (eg, small increase of ~48 steps/day, d=0.01, vs large decrease of ~1830 steps/day, d=0.95). Finally, habit development was significantly related to steps/day during (r=.30, P=.004) and following the intervention (r=.27, P=.03).

Conclusions

This study suggests that activity trackers may have beneficial effects on physical activity in healthy adults, but benefits vary based on individual factors. Furthermore, this study highlights the importance of habit development surrounding the wear and use of activity trackers and the associated software to promote increases in physical activity.

Trial Registration

ClinicalTrials.gov NCT03837366; https://clinicaltrials.gov/ct2/show/NCT03837366

Adapted Sojourn Models to Estimate Activity Intensity in Youth: A Suite of Tools

The challenges of using physical activity data from accelerometers have been compounded with the recent focus on wrist-worn monitors and raw acceleration (as opposed to activity counts).

PURPOSE

This study developed and systematically evaluated a suite of new accelerometer processing models for youth.

METHODS

Four adaptations of the Sojourn method were developed using data from a laboratory-based experiment in which youth (N = 54) performed structured activity routines. The adaptations corresponded to all possible pairings of hip or wrist attachment with activity counts (AC) or raw acceleration (RA), and they estimated time in sedentary behavior, light activity, and moderate-to-vigorous physical activity. Criterion validity was assessed using direct observation in an independent free-living sample (N = 27). Monitors were worn on both wrists to evaluate the effect of handedness on accuracy, and status quo methods for each configuration were also evaluated as benchmarks for comparison. Tests of classification accuracy (percent accuracy, κ statistics, and sensitivity and specificity) were used to summarize utility.

RESULTS

In the development sample, percent accuracy ranged from 68.5% (wrist-worn AC, κ = 0.42) to 71.6% (hip-worn RA, κ = 0.50). Accuracy was lower in the free-living evaluation, with values ranging from 49.3% (hip-worn RA, κ = 0.25) to 56.7% (hip-worn AC, κ = 0.36). Collectively, the suite predicted moderate-to-vigorous physical activity well, with the models averaging 96.5% sensitivity and 67.5% specificity. However, in terms of overall accuracy, the new models performed similarly to the status quo methods. There were no meaningful differences in performance at either wrist.

CONCLUSIONS

The new models offered minimal improvements over existing methods, but a major advantage is that further tuning of the models is possible with continued research.

A Primer on the Use of Equivalence Testing for Evaluating Measurement Agreement

PURPOSE

Statistical equivalence testing is more appropriate than conventional tests of difference to assess the validity of physical activity (PA) measures. This article presents the underlying principles of equivalence testing and gives three examples from PA and fitness assessment research.

METHODS

The three examples illustrate different uses of equivalence tests. Example 1 uses PA data to evaluate an activity monitor's equivalence to a known criterion. Example 2 illustrates the equivalence of two field-based measures of physical fitness with no known reference method. Example 3 uses regression to evaluate an activity monitor's equivalence across a suite of 23 activities.

RESULTS

The examples illustrate the appropriate reporting and interpretation of results from equivalence tests. In the first example, the mean criterion measure is significantly within ±15% of the mean PA monitor. The mean difference is 0.18 METs and the 90% confidence interval of -0.15 to 0.52 is inside the equivalence region of -0.65 to 0.65. In the second example, we chose to define equivalence for these two measures as a ratio of mean values between 0.98 and 1.02. The estimated ratio of mean V˙O2 values is 0.99, which is significantly (P = 0.007) inside the equivalence region. In the third example, the PA monitor is not equivalent to the criterion across the suite of activities. The estimated regression intercept and slope are -1.23 and 1.06. Neither confidence interval is within the suggested regression equivalence regions.

CONCLUSIONS

When the study goal is to show similarity between methods, equivalence testing is more appropriate than traditional statistical tests of differences (e.g., ANOVA and t-tests).

Feasibility study of the SWITCH implementation process for enhancing school wellness

BACKGROUND

There is a need to identify strategies that enhance the implementation of evidence-based school wellness intervention programs in real-world settings. The present study evaluates the feasibility of empowering school wellness leaders to deliver an evidence-based, childhood obesity-prevention program called Switch ™. We specifically evaluated the feasibility of a new implementation framework, based on the robust Healthy Youth Places framework, to increase capacity of school leaders to lead school wellness programming.

METHODS

The SWITCH (School Wellness Integration Targeting Child Health) implementation process was evaluated in a convenience sample of eight Iowa elementary schools. Teams of three leaders from each school attended an in-person school wellness conference followed by five online webinar sessions delivered by two SWITCH team members. The capacity-building and quality improvement process was designed to empower schools to lead wellness change using methods and concepts from the original 16-week Switch ™ program. School wellness leaders completed checklists on two occasions to assess overall school-level implementation as well as setting-level changes in physical education, classrooms, and the lunchroom. Student acceptability of SWITCH was evaluated by the degree of behavior tracking using an online SWITCH Tracker system that promoted self-monitoring. School acceptability and practicality were assessed through an exit survey completed by school leaders.

RESULTS

All school staff reported satisfaction with the SWITCH implementation process. Reports of school- and setting-level implementation were relatively high (2.0 to 2.8 on a 3-point scale) but student engagement, based on use of the online tracking system, varied greatly over time and across schools. Three high implementation schools had average tracking rates exceeding 70% (range: 72-90%) while three low implementation schools had rates lower than 30% (range = 0-23%).

CONCLUSIONS

This feasibility study supports the utility of the new implementation framework for promoting school and student engagement with SWITCH. Further testing regarding effectiveness and scale-up of this evidence-based school wellness intervention program is warranted.

Grip strength cutpoints for youth based on a clinically relevant bone health outcome

The National Academy of Medicine recommends the handgrip for school-based surveillance of muscle strength for bone health. We established grip strength cutpoints that are linked to bone health in both US and European youth. These cutpoints could serve as a potential set of standards for surveillance and clinical applications.

PURPOSE

The U.S. National Academy of Medicine and experts in Europe recommend the use of grip strength as a valuable and accessible musculoskeletal fitness measure due to its association with bone health. This is the first study to facilitate this recommendation by developing bone health-related grip strength cutpoints for youth based on empirical associations with the well accepted marker of bone development, i.e., height-adjusted total body less head bone mineral content (TBLH_BMC).

METHODS

A purposive sample of healthy youth from Midwest USA (n = 433 youth; 14.1 ± 2.3 years; 1998-2004) and a random sample of healthy adolescents from Zaragoza, Spain (n = 355 youth; 14.9 ± 1.2 years; 2006-2007) were used to develop and test cut-points. Participants' grip strength was measured using a hand-held dynamometer while height-adjusted TBLH_BMC was determined using dual-energy x-ray absorptiometry. Grip strength scores were linked to TBLH_BMC using receiver operator characteristic curves, and grip strength cutpoints were tested based on the area under the curve (AUC), sensitivity (Se), specificity (Sp), and predictive odds ratios. All analyses were conducted in 2016.

RESULTS

The AUC approximated or exceeded 0.80 for grip strength cutpoints, and the associated Se and Sp indices ranged from 53.6 to 92.5%. Sensitivity and Sp remained similar in the validation sample and those not meeting the grip strength cutpoints were five to eight times more likely to have insufficient TBLH_BMC, depending on their sex and cutpoint being considered.

CONCLUSIONS

Grip strength is strongly related to TBLH_BMC, and the proposed cutpoints demonstrated acceptable classification accuracy for screening healthy youth and tracking healthy bone development in community settings. The utility of the cutpoints should be further examined in more diverse populations of youth.