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.

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.

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.

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.

Equating NHANES Monitor-Based Physical Activity to Self-Reported Methods to Enhance Ongoing Surveillance Efforts.

PURPOSE: Harmonization of assessment methods represents an ongoing challenge in physical activity research. Previous research has demonstrated the utility of calibration approaches to enhance agreement between measures of physical activity. The present study utilizes a calibration methodology to add behavioral context from the Global Physical Activity Questionnaire (GPAQ), an established report-based measure, to enhance interpretations of monitor-based data scored using the novel Monitor Independent Movement Summary (MIMS) methodology. METHODS: Matching data from the GPAQ and MIMS were obtained from adults (20-80 yr of age) assessed in the 2011-2014 National Health and Nutrition Examination Survey. After developing percentile curves for self-reported activity, a zero-inflated quantile regression model was developed to link MIMS to estimates of moderate to vigorous physical activity (MVPA) from the GPAQ. RESULTS: Cross-validation of the model showed that it closely approximated the probability of reporting MVPA across age and activity-level segments, supporting the accuracy of the zero-inflated model component. Validation of the quantile regression component directly corresponded to the 25%, 50%, and 75% values for both men and women, further supporting the model fit. CONCLUSIONS: This study offers a method of improving activity surveillance by translating accelerometer signals into interpretable behavioral measures using nationally representative data. The model provides accurate estimates of minutes of MVPA at a population level but, because of the bias and error inherent in report-based measures of physical activity, is not suitable for converting or interpreting individual-level data. This study provides an important preliminary step in utilizing information from both device- and report-based methods to triangulate activity related outcomes; however additional measurement error modeling is needed to improve precision.

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 (pfor interaction = 0.86), SST (pfor interaction = 0.46), or DI (pfor 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.

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.

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.

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.

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.

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.

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.

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, Mage  = 40.6 ± 6.3 years) and elementary school children (N = 98, Mage  = 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.