Cody D. Neshteruk

Background: Intensive health‐behaviour lifestyle treatment is recommended for paediatric obesity, but evidence for young children and synchronous online delivery remains limited. Objectives: To evaluate the feasibility, acceptability, and preliminary effectiveness of an adapted online clinic‐community model for children aged 4 to < 8 years with overweight or obesity. Methods: In this two‐arm randomized controlled trial, children were randomized to an online family‐based intervention or usual care. The primary outcome was treatment dose at 6 months, defined as intervention contact hours. Secondary outcomes included BMI z‐score, percentage of the 95th BMI percentile, health‐related quality of life, eating behaviours, and perceived movement skills at 3 and 6 months. Results: Forty children were enrolled; mean age was 6.6 ± 1.0 years and 58% were male. At 6 months, 70% of intervention participants achieved at least 26 treatment hours. Although the between‐group differences were not statistically significant, the intervention group demonstrated numerically greater reductions in BMI z‐score (−0.2 ± 0.3 vs. −0.1 ± 0.1; p = 0.091) and percentage of the 95th BMI percentile (−3.5 ± 6.4 vs. −0.2 ± 4.0; p = 0.075). Physical quality of life improved at 3 and 6 months, object control skills at 3 months, and perceived locomotor skills at 6 months. Conclusions: The adapted online model was feasible and acceptable, with preliminary improvements in physical quality of life, movement skills, and BMI metrics. Larger adequately powered trials are needed to confirm effectiveness and longer‐term outcomes.

Neighborhood structural factors are associated with greater feasibility of youth active travel and thus, greater levels of physical activity. However, limited prior work has addressed walkability factors specific to the school neighborhood related to adolescent physical activity during the school day. Therefore, the purpose of this study was to examine the relationship between two school neighborhood walkability factors (neighborhood density and neighborhood age) and school-related adolescent MVPA). We analyzed cross-sectional data from the Family Life, Activity, Sun, Health, and Eating (FLASHE) study for 1,183 adolescents ages 12-17 years. linear regression models assessed the association between both (i.e., population/housing unit density and age of buildings/units, respectively, within a 400m buffer around school address) and , adjusting for ge, sex, race/ethnicity, weight status, urban/rural environment and parent MVPA. neighborhood density (8.62, 95% CI: 0.70, 16.53) and school-neighborhood age (6.38, 95% CI: -0.29, 13.05, n.s.) were both positively associated with school-related MVPA. When seeking to improve physical activity among adolescents, school neighborhood structural factors that support physical activity throughout a school day should be considered. These findings can be used to support environmental and policy changes to improve school-neighborhood walkability and adolescent participation in physical activity.

Routine youth physical activity (PA) fosters healthy habits and lasting cardiometabolic benefits into adulthood; however, significant disparities in PA persist by race, ethnicity, and income. Active transportation is an optimal intervention target to promote youth PA equity by building transportation self-efficacy skills. Going Places, a multilevel transportation self-efficacy intervention, aims to increase underserved youth PA and cardiometabolic health. We demonstrate preliminary efficacy, based on increased levels of PA, improved transportation self-efficacy, and reduced barriers to transportation use and PA to support positive patterns for lifelong health. ( Am J Public Health. 2025;115(5):693–697. https://doi.org/10.2105/AJPH.2025.308012 )

Policy, systems, and environmental (PSE) approaches, including those enacted in early childhood education (ECE) settings, can improve child health outcomes. The use of implementation strategies, or the ways in which these approaches are enacted across settings, may modify intervention impact. Therefore, the purpose of this review was to examine the implementation strategies used among interventions utilizing PSE approaches in the ECE setting. Seven databases including MEDLINE, PubMed, Web of Science, and EMBASE, were searched for interventions in ECE settings including children (0–6 years) that utilized ≥ 1 PSE approach. Eligible studies included either a child-level outcome (i.e., weight, physical activity, or diet) or an environmental outcome (i.e., nutrition and physical activity environment). Data extracted included study characteristics, description of the intervention, and description of the implementation of the intervention. Implementation strategies were coded using the School Implementation Strategies Translating ERIC Resources (SISTER) taxonomy. The Downs and Black checklist was completed to assess study quality. One hundred and four studies representing 97 interventions were identified. Fourteen (14%) did not report any implementation strategies. Of the remaining 83 interventions reporting implementation strategies, the mean number of implementation strategies employed per intervention was 3.8 (± 2.3) (range 1–11). However, few interventions (5/83, 6%) clearly named and defined implementation strategies. Most implementation strategies came from the “train and educate stakeholders” SISTER domain (177/318, 56%), and the most frequently used implementation strategy was “conduct educational meetings (50/83, 60%). Most studies were classified as good (59/104, 57%) or fair (40/104, 38%) quality. In this review, many interventions appeared to use multiple implementation strategies to support ECE PSE interventions, though few explicitly documented or described those strategies. These findings suggest that more precise documentation of implementation strategies is needed to enhance replication and scalability of ECE interventions. PROSPERO# CRD42022306670.

Objective: We assessed the impact of a food‐provisioning intervention on diet quality in children with obesity.Methods: Participants (n = 33, aged 6–11 years) were randomly assigned to either usual care (intensive health behavior and lifestyle treatment) or intervention (usual care + food provisioning; high‐fiber, low‐dairy diet) for 4 weeks. The primary outcome was a change in child diet quality at Week 4. Secondary outcomes were changes in weight, food insecurity, gut microbiome composition (16S ribosomal RNA), and dietary intake, measured via an objective DNA‐based biomarker (i.e., FoodSeq). Genomic dietary data were analyzed against a larger pediatric adolescent obesity cohort (n = 195, aged 10–18 years) from similar households.Results: Intervention demonstrated changes across all assessed diet components and was more effective than usual care in increasing whole grain (β = 0.20, 95% CI: 0.05 to 0.34; p = 0.013) and fiber (β = 2.52, 95% CI: 1.28 to 3.76; p < 0.001) and decreasing dairy (β = −1.31, 95% CI: −2.02 to −0.60; p = 0.001). FoodSeq results, highly concordant with grocery orders (adjusted R² = 0.65; p < 0.001), indicated a dietary shift toward low‐energy‐density plant taxa in the intervention relative to a prior survey of diet in a related cohort (β = 8.64, 95% CI: 5.18 to 12.14; p < 0.001). No significant changes were observed in microbiome, weight, or food insecurity.Conclusions: Our study supports the potential of dietitian‐guided food provisioning for improving diet quality in children with obesity and demonstrates an objective genomic approach for evaluating dietary shifts.

Background: Fewer than 1/4th of US children and adolescents meet physical activity (PA) guidelines, leading to health disparities that track into adulthood. Neighborhood opportunity may serve as a critical modifiable factor to improve fitness attainment and reduce these disparities. We drew data from the Child Opportunity Index to examine associations between neighborhood indicators of opportunity for PA and multiple fitness indicators among New York City public school youth. Methods: Multilevel generalized linear mixed models were used to estimate the overall and sex-stratified associations between neighborhood indicators (green space, healthy food, walkability, commute time) and indicators for physical fitness [curl-ups, push-ups, Progressive Aerobic Cardiovascular Endurance Run (PACER), sit-and-reach] using the New York City FITNESSGRAM data set. Results: The analytic sample [n = 299,839; median (interquartile range) age = 16 (12–17)] was 50.1% female, 37.5% Hispanic, 26.2% non-Hispanic Black, and most (69.5%) qualified for free/reduced price school meals. Neighborhood indicators were positively associated with higher values of indicators for physical fitness. The strongest associations were observed between walkability and both BMI and PACER, and commute time with BMI, push-ups, and PACER. For example, walkability had the greatest magnitude of effects for BMI and muscular strength and endurance (BMI: β: −0.75, 95% confidence interval, CI: −1.01 to −0.49; PACER: β: 1.98, 95% CI: 1.59 to 2.37), and particularly for girls compared with boys (BMI, girls: β: −0.91, 95% CI: −1.22 to −0.66); BMI, boys: β: −0.56, 95% CI: −0.86 to −0.25); PACER, girls: β: 2.11, 95% CI: 1.68 to 2.54; push-ups, boys: β: 1.71, 95% CI: 1.31 to 2.12). Conclusion: Neighborhood indicators were associated with multiple measures of youth fitness. Continued research on neighborhood opportunity and youth fitness may better inform place-based public health interventions to reduce disparities.

Background: Prior investigators have examined the relationship between neighborhood public transportation access and physical activity among adolescents, but research is lacking on the association with obesity in this age group. This study examines the association between neighborhood public transportation access and adolescent BMI using a national sample. Methods: We used cross-sectional data from the Family Life, Activity, Sun, Health, and Eating study, a national survey (2014) that assessed physical activity and diet, among adolescents (aged 12–17 years, N = 1737) and their parents. We ran crude and adjusted linear regression models to test the association between neighborhood-level public transportation access (less prevalent and prevalent) and individual participant-level BMI z-scores. Results: The analytic sample included 336 adolescents (50% female; 69% had healthy weight; 28% had overweight or obesity). Adjusted models showed a positive relationship between high public transportation access and adolescent z-BMI (b = 0.25, confidence interval [95% CI]: −0.01 to 0.50). In stratified analyses, high public transportation access was associated with higher z-BMI for high school students (b = 0.57, 95% CI: 0.23–0.91), males (b = 0.48, 95% CI: 0.09–0.87), and adolescents in households with an income below $99,999 (0.29, 95% CI: 0.02–0.56). Conclusion: Neighborhood public transportation access is associated with adolescent BMI, but the direction of this association varies across urban adolescent demographic subgroups. Further research is needed to clarify the relationships between individual and social-environmental factors that impact public transportation access and its association with adolescent BMI.

Summary: Background: Neighbourhood factors are associated with cardiovascular health in adults, but these relationships are under‐explored in youth.Objectives: To characterize the associations between neighbourhood factors and child and adolescent health among youth with obesity.Methods: Data were drawn from patient health records at a pediatric weight management clinic (n = 2838) and the Child Opportunity Index (COI). Exposures were area‐level neighbourhood factors (commute duration, walkability, greenspace and industrial pollutants). Outcomes included BMI relative to the 95th percentile (BMIp95) and blood pressure (continuous variables). Longitudinal models examined associations between COI indicators and outcomes.Results: Shorter commute duration (β = −4.31, 95% CI: −5.92, −2.71) and greater walkability (β = −4.40, 95% CI: −5.98, −2.82) were negatively associated with BMIp95. Increased greenspace availability was positively associated with BMIp95 (β = 1.93, 95% CI: 0.19, 3.67). None of the COI indicators were associated with cardiovascular outcomes in the full sample. Analyses stratified by sex and race/ethnicity showed similar patterns for BMIp95. For commute duration, there was a negative association with blood pressure for female, non‐Hispanic White and other race/ethnicity youth.Conclusions: Neighbourhood factors should be considered as contextual factors when treating youth with obesity. Additional research is needed to understand the relationship between neighbourhood factors and cardiovascular outcomes.