Disentangling associations between pubertal development, healthy activity behaviors, and sex in adolescent social networks.

With the onset of puberty, youth begin to choose their social environments and develop health-promoting habits, making it a vital period to study social and biological factors contextually. An important question is how pubertal development and behaviors such as physical activity and sleep may be differentially linked with youths' friendships. Cross-sectional statistical network models that account for interpersonal dependence were used to estimate associations between three measures of pubertal development and youth friendships at two large US schools drawn from the National Longitudinal Study of Adolescent to Adult Health. Whole-network models suggest that friendships are more likely between youth with similar levels of pubertal development, physical activity, and sleep. Sex-stratified models suggest that girls' friendships are more likely given a similar age at menarche. Attention to similar pubertal timing within friendship groups may offer inclusive opportunities for tailored developmental puberty education in ways that reduce stigma and improve health behaviors.

Association of Time-of-Day Physical Activity With Incident Cardiovascular Disease: The UK Biobank Study.

INTRODUCTION: Early morning is characterized by an increased risk of cardiovascular events, a sudden rise in blood pressure, impaired endothelial function, and exacerbated hemodynamic changes during physical activity. The study aims to examine whether the time of day of physical activity is associated with incident cardiovascular disease (CVD). METHODS: We prospectively analyzed 83,053 participants in the UK Biobank with objectively measured physical activity and initially free of CVD. Based on the diurnal patterns of physical activity, participants were categorized into 4 groups: early morning (n = 15,908), late morning (n = 22,371), midday (n = 24,764), and evening (n = 20,010). Incident CVD was defined as the first diagnosis of coronary heart disease or stroke. RESULTS: During 197.4 million person-years of follow-up, we identified 3454 CVD cases. After adjusting for the overall acceleration average, the hazard ratios and 95% confidence intervals were 0.95 (0.86-1.07) for late morning, 1.15 (1.03-1.27) for midday, and 1.03 (0.92-1.15) for evening, as compared with the early morning group. In the joint analyses, higher levels of physical activity were associated with a lower risk of incident CVD in a similar manner across the early morning, late morning, and evening groups. However, the beneficial association was attenuated in the midday group. CONCLUSION: In conclusion, early morning, late morning, and evening are all favorable times of day to engage in physical activity for the primary prevention of CVD, while midday physical activity is associated with an increased risk of CVD compared with early morning physical activity after controlling for the levels of physical activity.

Association of the time of day of peak physical activity with cardiovascular mortality: Findings from the UK Biobank study.

Cardiovascular physiology and pathophysiology display pronounced circadian rhythms. The study is designed to examine whether the time of day of physical activity is associated with cardiovascular mortality. We analyzed 94,489 UK Biobank adults with objectively measured physical activity, including 53,328 morning-type participants and 30,962 evening-type participants based on self-reported chronotypes. The time of day of peak physical activity was categorized using a machine learning algorithm: early morning (n = 18,477), late morning (n = 25,700), midday (reference) (n = 27,803), and night (n = 22,509). Hazard ratios of cardiovascular mortality were examined using the Cox proportional hazards model. During a median follow-up of 6.9 years (interquartile range, 6.3-7.4 years), we identified 629 cardiovascular deaths. The hazard of cardiovascular mortality was elevated in the early morning group (hazard ratio = 1.56, 95% Confidence Interval [1.23-1.98]) and night group (1.49, [1.18-1.88]) but not in the late morning group (1.21, [0.98-1.47]) compared to the referent midday group. In the chronotype-stratified analysis, the increased cardiovascular mortality in the morning group was only observed in the evening-type participants, while the increased cardiovascular mortality in the night group was only observed in the morning-type participants. In conclusion, optimizing the timing of peak physical activity according to cardiovascular circadian rhythms and individual chronotypes could be a potential therapeutic target that brings additional health benefits.

Clinical Relevance and Implementation Considerations of Physical Activity in Young Adult Cancer Survivorship: An Expert Consensus Study.

Significance: Elevated survival rates in young adult cancer survivors (YACS) are accompanied by high morbidity levels resulting in an array of unmet needs limiting full life potential. Physical activity (PA) improves physical, psychological, and social aspects of health after a cancer diagnosis. There are no standardized PA guidelines tailored to YACS. Therefore, there is a critical need to understand areas of clinical relevance/agreement on PA use and implementation in young adult (YA) survivorship care. Aim: To identify expert consensus areas on the assessment, prescription, and implementation of PA in YA survivorship care; identify areas of clinical relevance and endorsement of PA as a health optimization strategy in YA survivorship care. Methods: A four-round modified Delphi study of international multidisciplinary experts (Round I/II n = 18; Round III n = 57, Round IV n = 45) in exercise oncology, symptom management, survivorship care, youth cancer care was conducted. Qualitative content analysis, descriptive statistics (% agreement, standard deviation, mean), and inter-rater reliability (Kappa) were calculated. Results: Experts reached a consensus on clinical providers needed to assess, refer, and provide PA interventions, the need for guidelines, and essential care delivery system components to foster the integration of PA integration in YA survivorship care as a health optimization activity. Conclusions/Implications: Cancer care integration models should optimize the unique preferences, strengths, and developmental stage of YA affected by cancer. The study adds to the existing literature on multidisciplinary teams needed to provide clinical expertise and organizational support to foster PA integration into YA survivorship care.

Sleep Measurement Using Wrist-Worn Accelerometer Data Compared with Polysomnography.

This study determined if using alternative sleep onset (SO) definitions impacted accelerometer-derived sleep estimates compared with polysomnography (PSG). Nineteen participants (48%F) completed a 48 h visit in a home simulation laboratory. Sleep characteristics were calculated from the second night by PSG and a wrist-worn ActiGraph GT3X+ (AG). Criterion sleep measures included PSG-derived Total Sleep Time (TST), Sleep Onset Latency (SOL), Wake After Sleep Onset (WASO), Sleep Efficiency (SE), and Efficiency Once Asleep (SE_ASLEEP). Analogous variables were derived from temporally aligned AG data using the Cole-Kripke algorithm. For PSG, SO was defined as the first score of 'sleep'. For AG, SO was defined three ways: 1-, 5-, and 10-consecutive minutes of 'sleep'. Agreement statistics and linear mixed effects regression models were used to analyze 'Device' and 'Sleep Onset Rule' main effects and interactions. Sleep-wake agreement and sensitivity for all AG methods were high (89.0-89.5% and 97.2%, respectively); specificity was low (23.6-25.1%). There were no significant interactions or main effects of 'Sleep Onset Rule' for any variable. The AG underestimated SOL (19.7 min) and WASO (6.5 min), and overestimated TST (26.2 min), SE (6.5%), and SE_ASLEEP (1.9%). Future research should focus on developing sleep-wake detection algorithms and incorporating biometric signals (e.g., heart rate).

Expert Consensus on Physical Activity Use for Young Adult Cancer Survivors' Biopsychosocial Health: A Modified Delphi Study.

Significance: Cancer treatment impacts young adults' (YA) biological and psychosocial health, with over >50% reporting unmet needs. Physical activity (PA) offers symptom mitigation, risk reduction, and critical independence to YA (age 18-39 years) affected by cancer. When tailored to YA, PA guidelines can facilitate PA integration into survivorship care. However, no current expert consensus on PA use in YA exists. Aim: To describe expert consensus and opinions on the application of PA as a biopsychosocial health promotion strategy for YA cancer survivors, guided by the Revised Symptom Management Theory. Methods: A four-round modified Delphi study was conducted with international multidisciplinary experts (round I/II, n = 18; round III, n = 57; round IV, n = 45) in exercise oncology, symptom management, survivorship care, and adolescent-YA cancer care. Qualitative content analysis, descriptive statistics (% agreement, SD, mean), and inter-rater reliability (Kappa) were calculated. Results: Experts reached a consensus on the following: PA should be integrated into YA cancer care as part of supportive oncology to mitigate symptoms of fatigue, cardiometabolic health, muscle mass loss, altered body composition, and anxiety/depression; PA improves functional capacity and wellbeing; at all points on the care continuum YA should be asked if they would like guidance on PA use; PA interventions should be tailored for personal facilitators, barriers, and motivations, to maximize survivorship adaptations. Conclusion/Implication: The results of this study identified areas of expert consensus that warrant PA implementation in YA survivorship care to guide future research and clinical endeavors.

School-Based Secondary Obesity Prevention for Eight- to Twelve-Year-Olds: Results from the Students, Nurses, and Parents Seeking Healthy Options Together Randomized Trial.

Objective: The primary aim of this randomized controlled trial, conducted in Minneapolis/St. Paul, Minnesota (2014-2019), was to evaluate the effects of a school-based, school nurse-delivered, secondary obesity prevention intervention to reduce excess weight gain among preadolescent children with obesity or at risk of developing obesity. Methods: Parent/child dyads (n = 132) were randomized to the 9-month Students, Nurses, and Parents Seeking Healthy Options Together (SNAPSHOT) intervention (32.5 contact hours) or newsletter-only control group. Eligible children were 8 to 12 years old, proficient in English, and with a BMI ≥75th percentile, calculated using height/weight reported by a parent, school nurse, or clinician. The primary outcome was child BMI for sex/age z-score (BMIz) at postintervention (12 months) and follow-up (24 months). Results: Among children, 63% were non-White, 51% were male, and 51% with obesity, including 21% with severe obesity. Among families, 59% received economic assistance and 30% reported food insecurity. The mean number of intervention contact hours received was 20 (range: 0-32.5). Among dyads (n = 54) receiving the intervention, parents were very satisfied/satisfied with SNAPSHOT and SNAPSHOT staff, 96% and 100%, respectively, and very likely/likely (97%) to recommend SNAPSHOT to others. Most (70%) children liked the kid group sessions "a lot." In an intent-to-treat analysis, there were no significant between-group differences in child BMIz at 12 [0.04; 95% confidence interval (CI) -0.07 to 0.16] or 24 months (0.06; 95% CI -0.08 to 0.20), with participant retention of 92% and 93%, respectively. Conclusions: The SNAPSHOT intervention was well received, but did not improve BMI in a mostly diverse, low-income preadolescent population. Approaches to intervention delivery that are feasible, maximize accessibility, and optimize clinician and school nurse collaboration warrant consideration. Clinical trial registration identifier NCT02029976.

Sleep is Inversely Associated with Sedentary Time among Youth with Obesity.

Objective: Pathways underlying the sleep-obesity relationship in youth are poorly understood. In this study, we examined associations of sleep with sedentary time and moderate-to-vigorous physical activity (MVPA) among youth, stratified by weight category (obesity versus no obesity). A sub-aim examined whether controlling for screen time changed the sleep-sedentary time association. Methods: Methods entailed secondary analysis of baseline data collected June-August 2014-2017 during a school-based healthy weight management trial in Minneapolis/St. Paul, Minnesota. Participants (N = 114) were 8-to-12 years old with BMI ≥ 75th percentile, most of whom were members of racial/ethnic minority groups (57%) or from households receiving economic assistance (55%). Mean nightly sleep duration and daily screen time were measured by survey, MVPA and sedentary time by accelerometer, and height and weight by research staff. Multivariate linear regression examined associations of sleep with sedentary time and MVPA. Results: Sleep was inversely associated with hours of sedentary time (ß = -1.34 [-2.11, -0.58] p = .001) and percent of time spent sedentary (ß = -2.92 [-4.83, -1.01], p = .004), for youth with obesity only. The association was unchanged by screen time. Sleep was not significantly associated with MVPA in total sample or stratified models. Conclusions: Associations among sleep, activity levels, and obesity may differ based upon movement type (sedentary time vs MVPA) and weight category (obesity vs no obesity).

Estimating Sedentary Time from a Hip- and Wrist-Worn Accelerometer.

PURPOSE: This study aimed to determine the validity of existing methods to estimate sedentary behavior (SB) under free-living conditions using ActiGraph GT3X+ accelerometers (AG). METHODS: Forty-eight young (18-25 yr) adults wore an AG on the right hip and nondominant wrist and were video recorded during four 1-h sessions in free-living settings (home, community, school, and exercise). Direct observation videos were coded for postural orientation, activity type (e.g., walking), and METs derived from the Compendium of Physical Activities, which served as the criterion measure of SB (sitting or lying posture, <1.5 METs). Thirteen methods using cut points from vertical counts per minute (CPM), counts per 15-s (CP15s), and vector magnitude (VM) counts (e.g., CPM1853VM), raw acceleration and arm angle (sedentary sphere), Euclidean norm minus one (ENMO) corrected for gravity (mg) thresholds, uni- or triaxial sojourn hybrid machine learning models (Soj1x and Soj3x), random forest (RF), and decision tree (TR) models were used to estimate SB minutes from AG data. Method bias, mean absolute percent error, and their 95% confidence intervals were estimated using repeated-measures linear mixed models. RESULTS: On average, participants spent 34.1 min per session in SB. CPM100, CPM150, Soj1x, and Soj3x were the only methods to accurately estimate SB from the hip. Sedentary sphere and ENMO44.8 overestimated SB by 3.9 and 6.1 min, respectively, whereas the remaining wrist methods underestimated SB (range, 9.5-2.5 min). In general, mean absolute percent error was lower using hip methods compared with wrist methods. CONCLUSION: Accurate group-level estimates of SB from a hip-worn AG can be achieved using either simpler count-based approaches (CPM100 and CPM150) or machine learning models (Soj1x and Soj3x). Wrist methods did not provide accurate or precise estimates of SB. The development of large open-source free-living calibration data sets may lead to improvements in SB estimates.

Self-Efficacy, Not Peer or Parent Support, Is Associated With More Physical Activity and Less Sedentary Time Among 8- to 12-Year-Old Youth With Elevated Body Mass Index.

BACKGROUND: Youth experience a decrease in physical activity (PA) and an increase in sedentary time during adolescence. Better understanding of factors associated with activity levels during preadolescence may inform interventions to minimize decline. This study compared the association of self-efficacy for PA, parent support for PA, and peer support for PA with moderate-to-vigorous PA (MVPA) and sedentary time among 8- to 12-year-old children with body mass index ≥75th percentile. METHODS: This study analyzed baseline data from a school-based healthy weight management intervention trial, conducted in metropolitan Minnesota. Self-efficacy for PA, parent support for PA, and peer support for PA were measured by child survey using reliable tools. MVPA and sedentary time were measured using accelerometer. RESULTS: Participants included 114 children; mean age was 9.4 (0.9) years, 51% were females, 55% received public assistance, and 57% were racial/ethnic minorities. Self-efficacy for PA was positively associated with moderate to vigorous PA for girls (ß = 1.83, P < .01) and inversely with sedentary time for the total sample (ß = -7.00, P = .03). Parent support for PA was positively associated with sedentary time for girls (ß = 9.89, P = .04) and the total sample (ß = 7.83, P = .04). CONCLUSIONS: Interventions for preadolescents with elevated body mass index may improve activity levels by increasing self-efficacy for PA.

Efficacy of Community-Based Exercise Therapy Among African American Patients With Peripheral Artery Disease: A Randomized Clinical Trial.

Importance: African American individuals are 2 times more likely than non-Hispanic white individuals to have peripheral artery disease (PAD). Structured community-based exercise therapy improves walking distance among patients with PAD, but these patients require motivation to adhere to therapy. Objective: To assess whether motivational interviewing (MI) is more efficacious than Patient-Centered Assessment and Counseling for Exercise (PACE) or control to improve walking distance in African American patients with PAD. Design, Setting, and Participants: In this 3-group randomized clinical trial, 174 African American patients with PAD were studied from May 1, 2012, to November 30, 2016, at health care centers, churches, and health fairs in Wichita, Kansas; Kansas City, Kansas, and Kansas City, Missouri. Interventions: Patients were randomized in a 1:1:1 fashion to 1 of 3 groups (57 to MI, 57 to PACE, and 60 to control). The 2 counseling interventions were delivered biweekly for 3 months and monthly for 3 months followed by a 6-month maintenance phase with limited contact. Control participants received a mailing at 3 and 9 months. Main Outcomes and Measures: The primary outcome was 6-month change in 6-minute walking performance. Secondary outcomes included 12-month change in walking performance and 6- and 12-month changes in quality of life. Results: A total of 174 African American patients (mean [SD] age, 64.2 [11.2] years; 128 [74.0%] female) were studied. At 6 months, mean (SE) change in walking distance by group was as follows: MI, -3.42 (4.55) m; PACE, 2.74 (6.00) m; and control, -0.18 (4.40) m. At 12 months, mean (SE) change in walking distance by group was as follows: MI, -7.75 (5.50) m; PACE, 13.75 (6.13) m; and control, -1.08 (5.73) m. Comparing each of the intervention arms (MI and PACE) with the control arm, no statistically significant increases in walking distance at 6 months (MI: change, -2.10 m; 95% CI, -16.54 to 12.35 m; PACE: change, 2.31 m; 95% CI, -11.36 to 15.97 m) or 12 months (MI: change, -5.56 m; 95% CI, -21.18 to 10.06 m; PACE: change, 14.24 m; 95% CI, -1.85 to 30.34 m) were found. Compared with MI, PACE resulted in a statistically significant increase in walking distance at 12 months of 19.80 m (95% CI, 3.33-36.28 m). Conclusions and Relevance: In a cohort of African American patients with PAD, MI was not efficacious in improving walking distance at 6 or 12 months. The results of this study do not support the use of MI to improve walking performance in African American patients with PAD. Trial Registration: ClinicalTrials.gov Identifier: NCT01321086.

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

BACKGROUND: Previous studies have reported that walking cadence (steps/min) is associated with absolutely-defined intensity (metabolic equivalents; METs), such that cadence-based thresholds could serve as reasonable proxy values for ambulatory intensities. PURPOSE: To establish definitive heuristic (i.e., evidence-based, practical, rounded) thresholds linking cadence with absolutely-defined moderate (3 METs) and vigorous (6 METs) intensity. METHODS: In this laboratory-based cross-sectional study, 76 healthy adults (10 men and 10 women representing each 5-year age-group category between 21 and 40 years, BMI = 24.8 ± 3.4 kg/m2) performed a series of 5-min treadmill bouts separated by 2-min rests. Bouts began at 0.5 mph and increased in 0.5 mph increments until participants: 1) chose to run, 2) achieved 75% of their predicted maximum heart rate, or 3) reported a Borg rating of perceived exertion > 13. Cadence was hand-tallied, and intensity (METs) was measured using a portable indirect calorimeter. Optimal cadence thresholds for moderate and vigorous ambulatory intensities were identified using a segmented regression model with random coefficients, as well as Receiver Operating Characteristic (ROC) models. Positive predictive values (PPV) of candidate heuristic thresholds were assessed to determine final heuristic values. RESULTS: Optimal cadence thresholds for 3 METs and 6 METs were 102 and 129 steps/min, respectively, using the regression model, and 96 and 120 steps/min, respectively, using ROC models. Heuristic values were set at 100 steps/min (PPV of 91.4%), and 130 steps/min (PPV of 70.7%), respectively. CONCLUSIONS: Cadence thresholds of 100 and 130 steps/min can serve as reasonable heuristic thresholds representative of absolutely-defined moderate and vigorous ambulatory intensity, respectively, in 21-40 year olds. These values represent useful proxy values for recommending and modulating the intensity of ambulatory behavior and/or as measurement thresholds for processing accelerometer data. TRIAL REGISTRATION: Clinicaltrials.gov ( NCT02650258 ).

The Influence of Friends and Psychosocial Factors on Physical Activity and Screen Time in Normal and Overweight Adolescents: A Mixed-Methods Analysis.

BACKGROUND: Understanding factors that influence physical activity (PA) and sedentary behavior is crucial to develop interventions to improve adolescents' health-related behaviors. PURPOSE: To compare the influence of friends and psychosocial factors on moderate-to-vigorous physical activity (MVPA) and screen time (ST) between normal weight (NW) and overweight (OW) adolescents. METHODS: In all, 21 OW and 21 NW adolescents wore accelerometers and completed questionnaires assessing MVPA, ST, and psychosocial variables. The MVPA and ST were assessed in nominated friends. Adolescents participated in focus groups assessing influence on activity behaviors. RESULTS: There were no differences in MVPA; however, NW adolescents reported less ST than OW adolescents (8.9 vs 13.1 h/wk, P = .04). For OW adolescents, friends' ST ( P = .002) and psychosocial factors ( P = .05) were associated with ST, while only PA self-efficacy was associated with MVPA. For NW adolescents, only friends' MVPA ( P = .04) was associated with self-reported PA. Exploratory analyses revealed differences among weight status and gender. Focus group discussions revealed that friends influenced both OW and NW adolescents' MVPA; however, this appeared to be more apparent for NW males, while psychosocial factors played a role in both OW and NW females. The OW adolescents reported that friends were more of an influence on their ST levels, while NW adolescents indicated that their ST was not affected by their friends' behaviors. CONCLUSIONS: Interventions to increase MVPA and/or decrease ST may need to be tailored for NW and OW adolescents.

School-based secondary prevention of overweight and obesity among 8- to 12-year old children: Design and sample characteristics of the SNAPSHOT trial.

Rising levels of severe obesity among children, worsening disparities by race and ethnicity and reluctance of primary care clinicians' to provide obesity management to children are compelling reasons to consider alternatives to primary care management of childhood obesity. The Students Nurses and Parents Seeking Healthy Options Together (SNAPSHOT) trial will test the efficacy of an elementary school-based, school nurse-led, healthy weight management program to reduce excess weight gain among children, 8- to 12-years old with a body mass index (BMI) ≥75th percentile, by increasing healthy dietary practices and physical activity and decreasing sedentary behaviors. SNAPSHOT has enrolled and randomized 132 child/parent dyads to either the: (1) 9-month SNAPSHOT intervention that includes four home visits, 14 kid groups held during out-of-school time and five parent groups or (2) a newsletter program consisting of monthly mailings and family-focused healthy lifestyle information. Outcomes are assessed at baseline, 12-months (post intervention) and 24-months (follow-up) post randomization. The primary outcome is child age- and gender-adjusted BMI z-score. Secondary outcomes include child dietary intake assessed with 24-h dietary recall interviews and accelerometer-measured activity levels. The SNAPSHOT intervention is a model of secondary obesity prevention for children that addresses the urgent need for theory-informed, evidence-based and safe weight management programs, delivered by skilled health professionals in accessible settings. This report describes development of the SNAPSHOT trial, including recruitment and randomization procedures, assessments, intervention and implementation plans, and baseline characteristics of the study sample.

Effect of a Suspension-Trainer-Based Movement Program on Measures of Fitness and Functional Movement in Children: A Pilot Study.

PURPOSE: The purpose of this pilot study was to assess the efficacy of a suspension-training movement program to improve muscular- and skill-related fitness and functional movement in children, compared with controls. METHODS: In total, 28 children [male: 46%; age: 9.3 (1.5) y; body mass index percentile: 68.6 (27.5)] were randomly assigned to intervention (n = 17) or control (n = 11) groups. The intervention group participated in a 6-week suspension-training movement program for two 1-hour sessions per week. Muscular- and skill-related fitness and functional movement assessments were measured at baseline and following the intervention. Analyses of covariance models were used to assess the effects of time and intervention. RESULTS: The intervention participants achieved greater improvements in Modified Pull-Up performance (P = .01, Cohen's d = 0.54) and Functional Movement Screen score (P < .001, Cohen's d = 1.89), relative to controls. CONCLUSION: The suspension-training intervention delivered twice a week was beneficial for upper body pulling muscular endurance and the Functional Movement Screen score. Future interventions using this modality in youth would benefit from larger, more diverse samples (through schools or community fitness centers) and a longer intervention length.

Sedentary behavior and physical activity of young adult university students.

Movement and non-movement behaviors include sleep, sedentary behavior (SB) and physical activity (PA). While young adults are generally perceived as healthy, the level and relationship of SB and PA in college-age students has not been greatly explored. The purpose of this study was to objectively measure the levels of SB and PA in 18-20 year-old university students, record their self-reported extracurricular activities, and explore the relationship of all these with body mass index (BMI) and waist circumference (WC). Male (n = 48) and female (n = 46) students participated in this cross-sectional study. Hierarchical multiple regression analyses were used to examine time spent in SB, moderate to vigorous physical activity (MVPA), number of self-reported sedentary extracurricular activities, and their relation to the dependent variables of BMI and WC. In correlation analyses, SB (p < .001) and MVPA (p = .017) both were negatively associated with BMI, and "other" race or ethnicity (African American, Hispanic, mixed; p = .013) and number of self-reported sedentary extracurricular activities (p = .006) were positively associated with BMI. In the WC regression model, SB (p = .018) was negatively associated and number of self-reported sedentary extracurricular activities (p = .006) was positively associated with WC. University students may be both highly active and highly sedentary. Future researchers should consider targeting interventions to reduce SB in addition to improving PA.

Impacts of active school design on school-time sedentary behavior and physical activity: A pilot natural experiment.

BACKGROUND: Children spend a significant portion of their days in sedentary behavior (SB) and on average fail to engage in adequate physical activity (PA). The school built environment may influence SB and PA, but research is limited. This natural experiment evaluated whether an elementary school designed to promote movement impacted students' school-time SB and PA. METHODS: Accelerometers measured SB and PA at pre and post time-points in an intervention group who moved to the new school (n = 21) and in a comparison group experiencing no school environmental change (n = 20). Difference-in-difference (DD) analysis examined SB and PA outcomes in these groups. Measures were also collected post-intervention from an independent, grade-matched group of students in the new school (n = 21). RESULTS: As expected, maturational increases in SB were observed. However, DD analysis estimated that the intervention attenuated increase in SB by 81.2 ± 11.4 minutes/day (p<0.001), controlling for time in moderate to vigorous physical activity (MVPA). The intervention was also estimated to increase daily number of breaks from SB by 23.4 ± 2.6 (p < .001) and to increase light physical activity (LPA) by 67.7 ± 10.7 minutes/day (p<0.001). However, the intervention decreased MVPA by 10.3 ± 2.3 minutes/day (p<0.001). Results of grade-matched independent samples analysis were similar, with students in the new vs. old school spending 90.5 ± 16.1 fewer minutes/day in SB, taking 21.1 ± 2.7 more breaks from SB (p<0.001), and spending 64.5 ± 14.8 more minutes in LPA (p<0.001), controlling for time in MVPA. Students in the new school spent 13.1 ± 2.7 fewer minutes in MVPA (p<0.001) than their counterparts in the old school. CONCLUSIONS: This pilot study found that active school design had beneficial effects on SB and LPA, but not on MVPA. Mixed results point to a need for active classroom design strategies to mitigate SB, and quick access from classrooms to areas permissive of high-intensity activities to promote MVPA. Integrating active design with programs/policies to promote PA may yield greatest impact on PA of all intensities.

Youth Oriented Activity Trackers: Comprehensive Laboratory- and Field-Based Validation.

BACKGROUND: Commercial activity trackers are growing in popularity among adults and some are beginning to be marketed to children. There is, however, a paucity of independent research examining the validity of these devices to detect physical activity of different intensity levels. OBJECTIVES: The purpose of this study was to determine the validity of the output from 3 commercial youth-oriented activity trackers in 3 phases: (1) orbital shaker, (2) structured indoor activities, and (3) 4 days of free-living activity. METHODS: Four units of each activity tracker (Movband [MB], Sqord [SQ], and Zamzee [ZZ]) were tested in an orbital shaker for 5-minutes at three frequencies (1.3, 1.9, and 2.5 Hz). Participants for Phase 2 (N=14) and Phase 3 (N=16) were 6-12 year old children (50% male). For Phase 2, participants completed 9 structured activities while wearing each tracker, the ActiGraph GT3X+ (AG) research accelerometer, and a portable indirect calorimetry system to assess energy expenditure (EE). For Phase 3, participants wore all 4 devices for 4 consecutive days. Correlation coefficients, linear models, and non-parametric statistics evaluated the criterion and construct validity of the activity tracker output. RESULTS: Output from all devices was significantly associated with oscillation frequency (r=.92-.99). During Phase 2, MB and ZZ only differentiated sedentary from light intensity (P<.01), whereas the SQ significantly differentiated among all intensity categories (all comparisons P<.01), similar to AG and EE. During Phase 3, AG counts were significantly associated with activity tracker output (r=.76, .86, and .59 for the MB, SQ, and ZZ, respectively). CONCLUSIONS: Across study phases, the SQ demonstrated stronger validity than the MB and ZZ. The validity of youth-oriented activity trackers may directly impact their effectiveness as behavior modification tools, demonstrating a need for more research on such devices.

The Physical Activity Tracker Testing in Youth (P.A.T.T.Y.) Study: Content Analysis and Children's Perceptions.

BACKGROUND: Activity trackers are widely used by adults and several models are now marketed for children. OBJECTIVE: The aims of this study were to (1) perform a content analysis of behavioral change techniques (BCTs) used by three commercially available youth-oriented activity trackers and (2) obtain feedback describing children's perception of these devices and the associated websites. METHODS: A content analysis recorded the presence of 36 possible BCTs for the MovBand (MB), Sqord (SQ), and Zamzee (ZZ) activity trackers. In addition, 16 participants (mean age 8.6 years [SD 1.6]; 50% female [8/16]) received all three trackers and were oriented to the devices and websites. Participants were instructed to wear the trackers on 4 consecutive days and spend ≥10 min/day on each website. A cognitive interview and survey were administered when the participant returned the devices. Qualitative data analysis was used to analyze the content of the cognitive interviews. Chi-square analyses were used to determine differences in behavioral monitoring and social interaction features between websites. RESULTS: The MB, SQ, and ZZ devices or websites included 8, 15, and 14 of the possible 36 BCTs, respectively. All of the websites had a behavioral monitoring feature (charts for tracking activity), but the percentage of participants indicating that they "liked" those features varied by website (MB: 8/16, 50%; SQ: 6/16, 38%; ZZ: 11/16, 69%). Two websites (SQ and ZZ) included an "avatar" that the user could create to represent themselves on the website. Participants reported that they "liked" creating and changing their avatar (SQ: 12/16, 75%, ZZ: 15/16, 94%), which was supported by the qualitative analyses of the cognitive interviews. Most participants (75%) indicated that they would want to wear the devices more if their friends were wearing a tracker. No significant differences were observed between SQ and ZZ devices in regards to liking or use of social support interaction features (P=.21 to .37). CONCLUSIONS: The websites contained several BCTs consistent with previously identified strategies. Children "liked" the social aspects of the websites more than the activity tracking features. Developers of commercial activity trackers for youth may benefit from considering a theoretical perspective during the website design process.

Cross-Validation of Two Accelerometers for Assessment of Physical Activity and Sedentary Time in Preschool Children.

PURPOSE: The purpose of this study was to cross-validate previously developed Actiwatch (AW; Ekblom et al. 2012) and AcitGraph (AG; Sirard et al. 2005; AG-P, Pate et al. 2006) cut-point equations to categorize free-living physical activity (PA) of preschoolers using direct observation (DO) as the criterion measure. A secondary aim was to compare output from the AW and the AG from previously developed equations. METHODS: Participants' (n = 33; age = 4.4 ± 0.8 yrs; females, n=12) PA was directly observed for three 10-min periods during the preschool-day while wearing the AW (nondominant wrist) and AG (waist). Device specific cut-points were used to reduce the AW-E (Ekblom et al. 2012) and AG (AG-S, Sirard et al. 2005; AG-P, Pate et al. 2006) data into intensity categories. Spearman correlations (rsp) and agreement statistics were used to assess associations between the DO intensity categories and device data. Mixed model regression was used to identify differences in times spent in activity intensity categories. RESULTS: There was a significant correlation between AW and AG output across all data (rsp = 0.41, p < .0001) and both were associated with the DO intensity categories (AW: rsp = 0.47, AG: rsp = 0.47; p < .001). At the individual level, all devices demonstrated relatively low sensitivity but higher specificity. At the group level, AW-E and AG-P provided similar estimates of time spent in moderate-to-vigorous PA (MVPA, AW-E: 4.7 ± 4.1, AG-P: 4.4 ± 3.3), compared with DO (5.1 ± 3.5). CONCLUSION: The AW-E and AG-P estimated times spent in MVPA were similar to DO, but the weak agreement statistics indicate that neither device cut-point equations provided accurate estimates at the individual level.