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 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.

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.

Socioeconomic status and physical fitness in youth: Findings from the NHANES National Youth Fitness Survey.

This study examined the associations between socioeconomic status (SES) and musculoskeletal (MSF) and cardiorespiratory fitness (CRF) in youth.  The sample consisted of boys and girls between 3-15 years.  SES was categorized utilizing family-income-to-poverty ratio (FIPR).  All analyses were standardized for age and sex.  For each test of physical fitness, SES was used to estimate mean fitness test percentile and 95% confidence intervals, controlling for race/ethnicity and physical activity.  Odds ratios were calculated for the likelihood of having low fitness by SES category.  In general, the high SES group had a better composite MSF, body composition, and CRF profiles than low and moderate SES groups.  Statistically significant differences were identified for relative grip strength, plank, body mass index, and cardiovascular endurance time (all p < 0.05).  Additionally, the odds of low/poor MSF fitness were 1.7 and 1.6 times higher in the low and moderate SES groups (respectively) compared to the children from high SES families.  The moderate SES group had an odds of poor CRF 1.6 times higher than the high SES group as well.  Children and adolescents from high SES families tend to have higher mean fitness and were less likely to have low/poor fitness.

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.

Concurrent validation of the Actigraph gt3x+, Polar Active accelerometer, Omron HJ-720 and Yamax Digiwalker SW-701 pedometer step counts in lab-based and free-living settings.

Activity monitors are frequently used to assess activity in many settings. But as technology advances, so do the mechanisms used to estimate activity causing a continuous need to validate newly developed monitors. The purpose of this study was to examine the step count validity of the Yamax Digiwalker SW-701 pedometer (YX), Omron HJ-720 T pedometer (OP), Polar Active accelerometer (PAC) and Actigraph gt3x+ accelerometer (AG) under controlled and free-living conditions. Participants completed five stages of treadmill walking (n = 43) and a subset of these completed a 3-day free-living wear period (n = 37). Manually counted (MC) steps provided a criterion measure for treadmill walking, whereas the comparative measure during free-living was the YX. During treadmill walking, the OP was the most accurate monitor across all speeds (±1.1% of MC steps), while the PAC underestimated steps by 6.7-16.0% per stage. During free-living, the OP and AG counted 97.5% and 98.5% of YX steps, respectively. The PAC overestimated steps by 44.0%, or 5,265 steps per day. The Omron pedometer seems to provide the most reliable and valid estimate of steps taken, as it was the best performer under lab-based conditions and provided comparable results to the YX in free-living. Future studies should consider these monitors in additional populations and settings.

Trail use and recreational physical activity behavior of trail users and non-users during COVID-19 restrictions in Colorado Springs, Colorado.

Physical activity (PA) is an important health behavior that was impacted for many by the public health response to the COVID-19 pandemic. In many places, indoor recreational facilities were required to close; however, many outdoor spaces like trails were available for recreational use. The purpose of this study was to examine the use of a mixed-use trail before, during, and after COVID-19 restrictions in a large Colorado city and explore if recreational PA behavior differed between trail users and non-users during those periods. Trail user counts on a mixed-use trail were extracted for 2019 and 2020 from continuous-count data. Trail use habits and recreational PA behavior from before, during, and after restrictions were collected via a retrospective internet survey (N=183). Minutes per week of walking, moderate-to-vigorous PA and total PA were calculated from survey responses. Trail use data were analyzed with a two-way ANOVA and PA data were analyzed with a two-way repeated measures ANOVA. Trail use (average count/day) during COVID-19 restrictions was greater than before by 178 users and after by 96 users. During restrictions, trail users reported 153.5 more minutes of total PA per week than non-users. These results suggest the importance of maintaining accessible outdoor infrastructure for promoting positive PA behaviors in general, and especially in a pandemic situation.

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.

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.

Sleep Moderates Improvements in Mental Health Outcomes in Youth: Building Resilience for Healthy Kids.

PURPOSE: To examine the role of sleep in a school-based resiliency intervention. DESIGN: Single group feasibility study. SETTING: Urban middle school. SUBJECTS: Sixth grade students. INTERVENTION: A total of 285, 11-12-year-old students (70% White, 18% Hispanic, 55% female) participated in the six-week 1:1 Healthy Kids intervention. Youth (n = 248) completed electronic surveys at pre-post the 6-week study assessing mental health parameters and self-reported bed and wake time. MEASURES: Students were categorized as having insufficient sleep opportunity if they reported time in bed of <9 hours per night. ANALYSIS: General linear models examined differences between groups for each mental health parameters pre-post-study. RESULTS: A third of participants (28%) were classified as having insufficient sleep opportunity. Youth with insufficient sleep were more often Hispanic (27% vs 16%; P < .001) and were more often classified with both mild to severe depression and anxiety symptoms (55% vs 35%; P = .004). The health coaching intervention was found to have a significant improvement on overall resilience and self-efficacy only among students who reported sufficient sleep, while no significant intervention effect was found for those students who reported insufficient sleep. CONCLUSIONS: Our findings suggest that youth with poor sleep health may not benefit from school-based resiliency interventions.

Evaluation of a Resiliency Focused Health Coaching Intervention for Middle School Students: Building Resilience for Healthy Kids Program.

INTRODUCTION: Youth mental health issues are a growing public health concern. Resilience has been identified as a mitigating factor for adverse mental health outcomes. Schools have shown an increasing interest in strategies to support students' mental health. The purpose of this study was to evaluate a school-based 1:1 health coaching program designed to build resilience by teaching students coping skills and strategies to increase their self-efficacy. STUDY DESIGN: Single group intervention study with pre/post measures. SETTING/PARTICIPANTS: Sixth grade students (aged 11-12 years) attending an urban middle school. INTERVENTION: Youth participated in up to 6 resiliency-focused, 1:1 health coaching sessions completed over 8 weeks and conducted during the school day. Health coaches utilized motivational interviewing techniques to set and work toward resilience-related goals focused on improving coping skills and self-efficacy with youth during the intervention (January through March 2020). MAIN OUTCOME MEASURES: The Child and Youth Resilience Measure-Revised and other mental health assessments were completed at baseline and immediately following completion of the intervention to evaluate outcomes. Paired sample t-tests and Hedges' g effect sizes were conducted to evaluate intervention effectiveness. Student participation rates were assessed throughout the intervention. RESULTS: 287 youth participated in the study (87% participation rate) and participated in over 85% of health coaching sessions offered. A paired samples t-test revealed the youth resilience significantly increased from pre (M = 75.7, SD = 6.9) to post (M = 77.6, SD = 6.8) intervention (t[257] = 3.73, p < .001) and the size of the effect was medium (g = 0.29, 95% CI = 0.11, 0.46). CONCLUSIONS: The findings demonstrate that health coaching can be an effective strategy for improving resiliency in youth. Future studies evaluating how to effectively disseminate this intervention strategy are planned.

Study protocol for a school-based single group pragmatic trial to promote resilience in youth: Building Resilience for Healthy Kids.

BACKGROUND: There is a growing prevalence of mental health disorders among youth. Helping youth develop skills that promote and support mental well-being is an important strategy for addressing this public health concern. Building Resilience for Healthy Kids (Healthy Kids) is a school-based program designed to improve resiliency in youth aged 9-13 years old using an innovative health coaching framework. METHODS: Healthy Kids is a multi-phased intervention that aims to improve youth resilience using a 6-week, 1:1 health coaching program. The program develops youth resilience and was derived from models for developing youth resilience: Positive Relationships, Coping, Skill Development, Healthy Lifestyle, Sense of Culture, and Connectedness. Effectiveness of the intervention will be evaluated using a single-group, pragmatic trial design with pretest-posttest and follow-up assessments up to 12 months. Process measures will evaluate youth's acceptance and satisfaction of the program and attendance rates. Effectiveness will be evaluated by examining changes in resilience and mental health indicators from pre-to-post program and tracking sustainment of changes in mental health indicators over time. DISCUSSION: Given the pragmatic nature of the study design to work with generally healthy populations of students, we expect small, but sustainable, improvements in youth resilience to be achieved through the intervention. Further, this study will provide insight into the potential effectiveness of using health coaching as a strategy to support and promote youth mental well-being in school settings. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04202913. Registered December 18, 2019.

The Importance of Self-Monitoring for Behavior Change in Youth: Findings from the SWITCH® School Wellness Feasibility Study.

School Wellness Integration Targeting Child Health (SWITCH®) is a school wellness implementation initiative focused on building capacity for schools to plan and coordinate wellness programming. Grounded in Social Cognitive Theory (SCT), the purpose of this study was to evaluate the utility of the web-based, self-regulation system on physical activity (PA) behavior outcomes. At pre-test and post-test, students in SWITCH® schools (n = 8) completed the online Youth Activity Profile (YAP) to assess PA and sedentary behavior (SB). Students (n = 513) were categorized into high or low self-monitoring groups (using a median split) based on their use of the web-based self-regulation platform. Linear mixed models were used to assess differences in moderate-to-vigorous PA (MVPA) and sedentary behavior, with school, classroom, student, time-by-school, and time-by-classroom random effects and main and interaction fixed effects for student self-monitoring, gender, and time. Significant self-monitoring-by-time interactions were observed for estimates of PA F(1, 477) = 5.55, p = 0.02 and SB F(1, 477) = 4.90, p = 0.03. Students in the high self-monitoring group had larger gains in PA per day and larger declines in hours per day of sedentary screen time behavior compared to students in the low self-monitoring group. These findings support the utility of web-based self-regulation for facilitating PA change in youth.

Obesity and Insulin Resistance Screening Tools in American Adolescents: National Health and Nutrition Examination Survey (NHANES) 1999 to 2010.

OBJECTIVE: To identify which feasible obesity and insulin resistance (IR) screening tools are most strongly associated in adolescents by using a nationally representative sample. METHODS: Adolescents aged 12.0 to 18.9 years who were participating in the National Health and Nutrition Examination Survey (NHANES) (n=3584) and who were measured for height, weight, waist circumference (WC), triceps and subscapular skinfold thickness, glycated hemoglobin, fasting glucose (FG) and fasting insulin (FI) level were included. Adolescents were split by gender and grouped by body mass index (BMI) percentile. Age- and gender-specific classifications were constructed for each obesity screening tool measure to account for growth and maturation. General linear models were used to establish groups objectively for analysis based on when IR began to increase. Additional general linear models were used to identify when IR significantly increased for each IR measure as obesity group increased and to identify the variance accounted for among each obesity-IR screening tool relationship. RESULTS: As the obesity group increased, homeostasis model assessment-insulin resistance (HOMA-IR) and FI significantly increased, while FG increased only (above the referent) in groups with BMI percentiles ≥95.0, and glycated hemoglobin level did not vary across obesity groups. The most strongly associated screening tools were WC and FI in boys (R(2)=0.253) and girls (R(2)=0.257). FI had the strongest association with all of the obesity measures. BMI associations were slightly weaker than WC in each in relation to IR. CONCLUSIONS: Our findings show that WC and FI are the most strongly associated obesity and IR screening tool measures in adolescents. These feasible screening tools should be utilized in screening practices for at-risk adolescents.

Comparison of Consumer and Research Monitors under Semistructured Settings.

PURPOSE: This study evaluated the relative validity of different consumer and research activity monitors during semistructured periods of sedentary activity, aerobic exercise, and resistance exercise. METHODS: Fifty-two (28 male and 24 female) participants age 18-65 yr performed 20 min of self-selected sedentary activity, 25 min of aerobic exercise, and 25 min of resistance exercise, with 5 min of rest between each activity. Each participant wore five wrist-worn consumer monitors [Fitbit Flex, Jawbone Up24, Misfit Shine (MS), Nike+ Fuelband SE (NFS), and Polar Loop] and two research monitors [ActiGraph GT3X+ on the waist and BodyMedia Core (BMC) on the arm] while being concurrently monitored with Oxycon Mobile (OM), a portable metabolic measuring system. Energy expenditure (EE) on different activity sessions was measured by OM and estimated by all monitors. RESULTS: Mean absolute percent error (MAPE) values for the full 80-min protocol ranged from 15.3% (BMC) to 30.4% (MS). EE estimates from ActiGraph GT3X+ were found to be equivalent to those from OM (± 10% equivalence zone, 285.1-348.5). Correlations between OM and the various monitors were generally high (ranged between 0.71 and 0.90). Three monitors had MAPE values lower than 20% for sedentary activity: BMC (15.7%), MS (18.2%), and NFS (20.0%). Two monitors had MAPE values lower than 20% for aerobic exercise: BMC (17.2%) and NFS (18.5%). None of the monitors had MAPE values lower than 25% for resistance exercise. CONCLUSION: Overall, the research monitors and Fitbit Flex, Jawbone Up24, and NFS provided reasonably accurate total EE estimates at the individual level. However, larger error was evident for individual activities, especially resistance exercise. Further research is needed to examine these monitors across various activities and intensities as well as under real-world conditions.

The cumulative impact of physical activity, sleep duration, and television time on adolescent obesity: 2011 Youth Risk Behavior Survey.

BACKGROUND: Physical activity (PA), television time (TV), and sleep duration (SLP) are considered individual risk factors for adolescent obesity. Our aim was to investigate the concurrent influence of meeting PA, SLP, and TV recommendations on adolescent obesity utilizing 2011 Youth Risk Behavior Surveillance Survey (YRBSS) data. METHODS: Subjects included 9589 (4874 females) high school students. PA, SLP, and TV were categorized utilizing established national recommendations and youth were cross-tabulated into 1 of 8 groups based on meeting or not meeting each recommendation. Logistic models were used to examine the odds of obesity for each group. RESULTS: Youth meeting the PA recommendation were not at increased odds of obesity, regardless of SLP or TV status. However, not meeting any single recommendation, in general, led to increased odds of not meeting the other two. In boys, 11.8% met all recommendations while 14.1% met 0 recommendations. In girls, only 5.0% met all recommendations while 17.8% met none. CONCLUSIONS: Boys and girls not meeting any of the recommendations were 4.0 and 3.8 times more likely to be obese compared with their respective referent groups. Further research considering the simultaneous influence these risk factors may have on obesity and on one another is warranted.

Concurrent Associations between Physical Activity, Screen Time, and Sleep Duration with Childhood Obesity.

Aim. To examine the simultaneous influence of physical activity, screen time, and sleep duration recommendations on the odds of childhood obesity (including overweight). Methods. Physical activity was assessed via pedometer and screen time, and sleep duration were assessed via survey in a cross sectional sample of 674 children (aged 7-12 years) from two Midwestern communities in the fall of 2005. Participants were cross tabulated into four groups depending on how many recommendations were being met (0, 1, 2, or all 3). Linear and logistic regression were used to examine the influence of physical activity, screen time and sleep duration on obesity and interactions among the three variables. Results. Children achieving all three recommendations simultaneously (9.2% of total sample) were the least likely to be obese. Approximately 16% of boys and 9% of girls achieving all recommendations were overweight or obese compared to 53% of boys and 42.5% of girls not achieving any. Conclusions. The odds of obesity increased in a graded manner for each recommendation which was not met. Meeting all three recommendations appears to have a protective effect against obesity. Continued efforts are warranted to promote healthy lifestyle behaviors that include meeting physical activity, screen time, and sleep duration recommendations concurrently.