Differences in elementary-age children's accelerometer - measured physical activity between school and summer: three-year findings from the What's UP (Undermining Prevention) with summer observational cohort study.

BACKGROUND: Among elementary-aged children (5-12yrs), summer vacation is associated with accelerated gains in Body Mass Index (BMI). A key behavioral driver of BMI gain is a lack of physical activity (PA). Previous studies indicate PA decreases during summer, compared to the school year but whether this difference is consistent among boys and girls, across age, and by income status remains unclear. This study examined differences in school and summer movement behaviors in a diverse cohort of children across three years. METHODS: Children (N = 1,203, age range 5-14 years, 48% girls) wore wrist-placed accelerometers for a 14-day wear-period during school (April/May) and summer (July) in 2021 to 2023, for a total of 6 timepoints. Mixed-effects models examined changes in school vs. summer movement behaviors (moderate-to-vigorous physical activity [MVPA], sedentary) for boys and girls, separately, and by age and household income groups (low, middle, and upper based on income-to-poverty ratio). RESULTS: Children provided a total of 35,435 valid days of accelerometry. Overall, boys (+ 9.1 min/day, 95CI 8.1 to 10.2) and girls (+ 6.2 min/day, 95CI 5.4 to 7.0) accumulated more MVPA during school compared to summer. Boys accumulated less time sedentary (-9.9 min/day, 95CI -13.0 to -6.9) during school, while there was no difference in sedentary time (-2.7 min/day, 95CI -5.7 to 0.4) for girls. Different patterns emerged across ages and income groups. Accumulation of MVPA was consistently greater during school compared to summer across ages and income groups. Generally, the difference between school and summer widened with increasing age, except for girls from middle-income households. Accumulation of sedentary time was higher during school for younger children (5-9yrs), whereas for older children (10-14yrs), sedentary time was greater during summer for the middle- and upper-income groups. For boys from low-income households and girls from middle-income households, sedentary time was consistently greater during summer compared to school across ages. CONCLUSIONS: Children are less active and more sedentary during summer compared to school, which may contribute to accelerated BMI gain. However, this differs by biological sex, age, and income. These findings highlight the complex factors influencing movement behaviors between school and summer.

Differences by School Location in Summer and School Monthly Weight Change: Findings from a Nationally Representative Sample.

OBJECTIVES: To examine changes in accelerations of Body Mass Index (BMI), age-and-sex specific body mass index (zBMI), and 95th percentile of BMI (%BMIp95) during the summer months and school year by school location designation (i.e., urban, suburban, exurban). This study utilized the Early Childhood Longitudinal Study Kindergarten Class of 2010-2011. METHODS: Of the 18,174 children in the ECLS-K:2011 dataset, I restricted participants to those with at least two consecutive measures that occurred August/September or April/May. Mixed-effect regression analyses estimated differences in monthly change in BMI, zBMI, and %BMIp95 between the summer and school year while accounting for the ECLS-K complex sampling design. Models also examined differences in the magnitude of BMI, zBMI, and %BMIp95 change between the summer and school year by school location. Post-hoc Benjamini-Hochberg (BH) procedure set at 10% false discovery was incorporated to account for multiple comparisons. RESULTS: A total of 1549 children (48% female, 42% White) had at least two consecutive measures that occurred in August/September or April/May. Among all locale classifications (i.e., urban, suburban, and exurban), children from high-income households comprised the largest proportions for each group (31%, 39%, and 37%), respectively. Among urban and suburban locations, Hispanic children comprised the largest proportions for both groups (43% and 44%), respectively. Among exurban locale classifications, White children comprised the largest proportion of children (60%). Children from suburban and exurban schools experienced significantly less accelerations in monthly zBMI gain when compared to their urban counterparts -0.038 (95CI = -0.071, -0.004) and -0.045 (95CI = -0.083, -0.007), respectively. Children from exurban schools experienced significantly less acceleration in monthly %BMIp95 during the summer months when compared to the school year -0.004 (95CI = -0.007, 0.000). CONCLUSIONS: This is one of the first studies to examine summer weight gain by school location. Summer appears to impact children more negatively from urban schools when compared to their suburban and exurban counterparts.

The application of mHealth to monitor implementation of best practices to support healthy eating and physical activity in afterschool programs.

BACKGROUND: Childhood obesity continues to be a global epidemic and many child-based settings (e.g. school, afterschool programs) have great potential to make a positive impact on children's health behaviors. Innovative and time-sensitive methods of gathering health behavior information for the purpose of evaluation and strategically deploying support are needed in these settings. PURPOSE: The aim is to (1) demonstrate the feasibility of mobile health (mHealth) for monitoring implementation of healthy eating and physical activity (HEPA) standards and, (2) illustrate the utility of mHealth for identifying areas where support is needed, within the afterschool setting. METHODS: Site leaders (N = 175) of afterschool programs (ASPs) were invited to complete an online observation checklist via a mobile web app (Healthy Eating and Physical Activity Mobile, HEPAm) once per week during ASP operating hours. Auto-generated weekly text reminders were sent to site leaders' mobile devices during spring and fall 2015 and 2016 and spring 2017 school semesters. Data from HEPAm was separated into HEPA variables, and expressed as a percent of checklists where an item was present. A higher percentage for a given item would indicate an afterschool has higher compliance with current HEPA standards. RESULTS: A total of 141 site leaders of ASPs completed 13,960 HEPAm checklists. The average number of checklists completed per ASP was 43 (range 1-220) for healthy eating and 50 (range 1-230) for physical activity. For healthy eating, the most common challenge for ASPs was 'Staff educating children about healthy eating', and for physical activity checklists, 'Girls only physical activity is provided at ASP'. CONCLUSION: HEPAm was widely used and provided valuable information that can be used to strategically deploy HEPA support to ASPs. This study gives confidence to the adoption of mHealth strategies as a means for public health practitioners to monitor compliance of an initiative or intervention.

Identifying Strategies Programs Adopt to Meet Healthy Eating and Physical Activity Standards in Afterschool Programs.

BACKGROUND: The YMCA of USA has adopted Healthy Eating and Physical Activity (HEPA) Standards for its afterschool programs (ASPs). Little is known about strategies YMCA ASPs are implementing to achieve Standards and these strategies' effectiveness. AIMS: (1) Identify strategies implemented in YMCA ASPs and (2) evaluate the relationship between strategy implementation and meeting Standards. METHOD: HEPA was measured via accelerometer (moderate-to-vigorous-physical-activity [MVPA]) and direct observation (snacks served) in 20 ASPs. Strategies were identified and mapped onto a capacity building framework ( Strategies To Enhance Practice [STEPs]). Mixed-effects regression estimated increases in HEPA outcomes as implementation increased. Model-implied estimates were calculated for high (i.e., highest implementation score achieved), moderate (median implementation score across programs), and low (lowest implementation score achieved) implementation for both HEPA separately. RESULTS: Programs implemented a variety of strategies identified in STEPs. For every 1-point increase in implementation score 1.45% (95% confidence interval = 0.33% to 2.55%, p ≤ .001) more girls accumulated 30 min/day of MVPA and fruits and/or vegetables were served on 0.11 more days (95% confidence interval = 0.11-0.45, p ≤ .01). Relationships between implementation and other HEPA outcomes did not reach statistical significance. Still regression estimates indicated that desserts are served on 1.94 fewer days (i.e., 0.40 vs. 2.34) in the highest implementing program than the lowest implementing program and water is served 0.73 more days (i.e., 2.37 vs. 1.64). CONCLUSIONS: Adopting HEPA Standards at the national level does not lead to changes in routine practice in all programs. Practical strategies that programs could adopt to more fully comply with the HEPA Standards are identified.

Intervention leads to improvements in the nutrient profile of snacks served in afterschool programs: a group randomized controlled trial.

Widely adopted nutrition policies for afterschool programs (ASPs) focus on serving a fruit/vegetable daily and eliminating sugar-sweetened foods/beverages. The impact of these policies on the nutrient profile of snacks served is unclear. Evaluate changes in macro/micronutrient content of snacks served in ASPs. A 1-year group randomized controlled trial was conducted in 20 ASPs serving over 1700 elementary-age children. Intervention ASPs received a multistep adaptive framework intervention. Direct observation of snack served was collected and nutrient information determined using the USDA Nutrient Database, standardized to nutrients/100 kcal. By post-assessment, intervention ASPs reduced total kcal/snack served by 66 kcal (95CI -114 to -19 kcal) compared to control ASPs. Total fiber (+1.7 g/100 kcal), protein (+1.4 g/100 kcal), polyunsaturated fat (+1.2 g/100 kcal), phosphorous (+49.0 mg/100 kcal), potassium (+201.8 mg/100 kcal), and vitamin K (+21.5 µg/100 kcal) increased in intervention ASPs, while added sugars decreased (-5.0 g/100 kcal). Nutrition policies can lead to modest daily caloric reductions and improve select macro/micronutrients in snacks served. Long-term, these nutritional changes may contribute to healthy dietary habits.

Development and testing of mobile technology for community park improvements: validity and reliability of the eCPAT application with youth.

Creation of mobile technology environmental audit tools can provide a more interactive way for youth to engage with communities and facilitate participation in health promotion efforts. This study describes the development and validity and reliability testing of an electronic version of the Community Park Audit Tool (eCPAT). eCPAT consists of 149 items and incorporates a variety of technology benefits. Criterion-related validity and inter-rater reliability were evaluated using data from 52 youth across 47 parks in Greenville County, SC. A large portion of items (>70 %) demonstrated either fair or moderate to perfect validity and reliability. All but six items demonstrated excellent percent agreement. The eCPAT app is a user-friendly tool that provides a comprehensive assessment of park environments. Given the proliferation of smartphones, tablets, and other electronic devices among both adolescents and adults, the eCPAT app has potential to be distributed and used widely for a variety of health promotion purposes.

Process Evaluation of Making HEPA Policy Practice: A Group Randomized Trial.

This study examines the link between implementation of Strategies to Enhance Practice (STEPs) and outcomes. Twenty after-school programs (ASPs) participated in an intervention to increase children's accumulation of 30 minutes/day of moderate to vigorous physical activity (MVPA) and quality of snacks served during program time. Outcomes were measured via accelerometer (MVPA) and direct observation (snacks). STEPs implementation data were collected via document review and direct observation. Based on implementation data, ASPs were divided into high/low implementers. Differences between high/low implementers' change in percentage of boys accumulating 30 minutes/day of MVPA were observed. There was no difference between high/low implementers for girls. Days fruits and/or vegetables and water were served increased in the high/low implementation groups, while desserts and sugar-sweetened beverages decreased. Effect sizes (ES) for the difference in changes between the high and low group ranged from low (ES = 0.16) to high (ES = 0.97). Higher levels of implementation led to increased MVPA for boys, whereas girls MVPA benefited from the intervention regardless of high/low implementation. ESs of the difference between high/low implementers indicate that increased implementation of STEPs increases days healthier snacks are served. Programs in the high-implementation group implemented a variety of STEPs strategies, suggesting local adoption/adaptation is key to implementation.