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Objective: To quantify the potential population-wide costs, number of individuals reached, and impact on obesity of five effective interventions to reduce children's television viewing if implemented nationally. Study Design: Utilizing evidence from systematic reviews, the Childhood Obesity Intervention Cost Effectiveness Study (CHOICES) microsimulation model estimated the cost, population reach, and impact on childhood obesity from 2020 to 2030 of five hypothetical policy strategies to reduce the negative impact of children's TV exposure: (1) eliminating the tax deductibility of food and beverage advertising; (2) targeting TV reduction during home visiting programs; (3) motivational interviewing to reduce home television time at Women, Infants, and Children (WIC) clinic visits; (4) adoption of a television-reduction curriculum in child care; and (5) limiting noneducational television in licensed child care settings. Results: Eliminating the tax deductibility of food advertising could reach the most children [106 million, 95% uncertainty interval (UI): 105–107 million], prevent the most cases of obesity (78,700, 95% UI: 30,200–130,000), and save more in health care costs than it costs to implement. Strategies targeting young children in child care and WIC also cost little to implement (between $0.19 and $32.73 per child reached), and, although reaching fewer children because of the restricted age range, were estimated to prevent between 25,500 (95% UI: 4600–59,300) and 35,400 (95% UI: 13,200–62,100) cases of obesity. Home visiting to reduce television viewing had high costs and a low reach. Conclusions: Interventions to reduce television exposure across a range of settings, if implemented widely, could help prevent childhood obesity in the population at relatively low cost.

Although the national obesity epidemic has been well documented, less is known about obesity at the U.S. state level. Current estimates are based on body measures reported by persons themselves that underestimate the prevalence of obesity, especially severe obesity.We developed methods to correct for self-reporting bias and to estimate state-specific and demographic subgroup-specific trends and projections of the prevalence of categories of body-mass index (BMI). BMI data reported by 6,264,226 adults (18 years of age or older) who participated in the Behavioral Risk Factor Surveillance System Survey (1993-1994 and 1999-2016) were obtained and corrected for quantile-specific self-reporting bias with the use of measured data from 57,131 adults who participated in the National Health and Nutrition Examination Survey. We fitted multinomial regressions for each state and subgroup to estimate the prevalence of four BMI categories from 1990 through 2030: underweight or normal weight (BMI [the weight in kilograms divided by the square of the height in meters],25), overweight (25 to30), moderate obesity (30 to35), and severe obesity (≥35). We evaluated the accuracy of our approach using data from 1990 through 2010 to predict 2016 outcomes.The findings from our approach suggest with high predictive accuracy that by 2030 nearly 1 in 2 adults will have obesity (48.9%; 95% confidence interval [CI], 47.7 to 50.1), and the prevalence will be higher than 50% in 29 states and not below 35% in any state. Nearly 1 in 4 adults is projected to have severe obesity by 2030 (24.2%; 95% CI, 22.9 to 25.5), and the prevalence will be higher than 25% in 25 states. We predict that, nationally, severe obesity is likely to become the most common BMI category among women (27.6%; 95% CI, 26.1 to 29.2), non-Hispanic black adults (31.7%; 95% CI, 29.9 to 33.4), and low-income adults (31.7%; 95% CI, 30.2 to 33.2).Our analysis indicates that the prevalence of adult obesity and severe obesity will continue to increase nationwide, with large disparities across states and demographic subgroups. (Funded by the JPB Foundation.).

Background There is a great need to identify implementation strategies to successfully scale-up public health interventions in order to achieve their intended population impact. The Out-of-school Nutrition and Physical Activity group-randomized trial previously demonstrated improvements in children’s vigorous physical activity and the healthfulness of foods and beverages consumed. This implementation study aimed to assess the effects and costs of two training models to scale-up this evidence-based intervention. Methods A 3-arm group-randomized trial was conducted to compare effectiveness of in-person and online training models for scaling up the intervention compared to controls. One-third of sites were randomized to the in-person train-the-trainer model: local YMCA facilitators attended a training session and then conducted three learning collaborative meetings and technical assistance. One-third were assigned to the online model, consisting of self-paced monthly learning modules, videos, quizzes, and facilitated discussion boards. Remaining sites served as controls. Fifty-three afterschool sites from three YMCA Associations in different regions of the country completed baseline and follow-up observations using a validated tool of afterschool nutrition and physical activity practices. We used multivariable regression models, accounting for clustering of observations, to assess intervention effects on an aggregate afterschool practice primary outcome, and conducted secondary analyses of nine intervention goals (e.g. serving water). Cost data were collected to determine the resources to implement each training model. Results Changes in the primary outcome indicate that, on average, sites in the in-person arm achieved 0.44 additional goals compared to controls (95%CI 0.02, 0.86, p = 0.04). Increases in the number of additional goals achieved in sites in the online arm were not significantly greater than control sites (+ 0.28, 95% CI -0.18, 0.73, p = 0.24). Goal-specific improvements were observed for increasing water offered in the in-person arm and fruits and vegetables offered in the online arm. The cost per person trained was $678 for the in-person training model and $336 for the on-line training model. Conclusions This pilot trial presents promising findings on implementation strategies for scale-up. It validated the in-person training model as an effective approach. The less expensive online training may be a useful option for geographically disbursed sites where in-person training is challenging. Trial registration Although this study does not report the results of a health care intervention on human subjects, it is a randomized trial and was therefore retrospectively registered in ClinicalTrials.gov on July 4, 2019 in accordance with the BMC guidelines to ensure the complete publication of all results (NCT04009304).

Although the current obesity epidemic has been well documented in children and adults, less is known about long-term risks of adult obesity for a given child at his or her present age and weight. We developed a simulation model to estimate the risk of adult obesity at the age of 35 years for the current population of children in the United States.We pooled height and weight data from five nationally representative longitudinal studies totaling 176,720 observations from 41,567 children and adults. We simulated growth trajectories across the life course and adjusted for secular trends. We created 1000 virtual populations of 1 million children through the age of 19 years that were representative of the 2016 population of the United States and projected their trajectories in height and weight up to the age of 35 years. Severe obesity was defined as a body-mass index (BMI, the weight in kilograms divided by the square of the height in meters) of 35 or higher in adults and 120% or more of the 95th percentile in children.Given the current level of childhood obesity, the models predicted that a majority of today's children (57.3%; 95% uncertainly interval [UI], 55.2 to 60.0) will be obese at the age of 35 years, and roughly half of the projected prevalence will occur during childhood. Our simulations indicated that the relative risk of adult obesity increased with age and BMI, from 1.17 (95% UI, 1.09 to 1.29) for overweight 2-year-olds to 3.10 (95% UI, 2.43 to 3.65) for 19-year-olds with severe obesity. For children with severe obesity, the chance they will no longer be obese at the age of 35 years fell from 21.0% (95% UI, 7.3 to 47.3) at the age of 2 years to 6.1% (95% UI, 2.1 to 9.9) at the age of 19 years.On the basis of our simulation models, childhood obesity and overweight will continue to be a major health problem in the United States. Early development of obesity predicted obesity in adulthood, especially for children who were severely obese. (Funded by the JPB Foundation and others.).

Objective To examine changes in prevalence of obesity and target health behaviors (fruit, vegetable, and beverage consumption; physical activity; screen time; sleep duration) among students from communities that participated in the Massachusetts Childhood Obesity Research Demonstration (MA-CORD) project compared to controls. Methods MA-CORD was implemented in two low-income communities. School-level prevalence of obesity among students in first, fourth, and seventh grades was calculated for the intervention communities and nine matched control communities pre and post intervention. Fourth- and seventh-grade students’ self-reported health behaviors were measured in intervention communities at baseline and post intervention. Results Among seventh-graders (the student group with greatest intervention exposure), a statistically significant decrease in prevalence of obesity from baseline to post intervention in Community 2 (−2.68%, P = 0.049) and a similar but nonsignificant decrease in Community 1 (−2.24%, P = 0.099) was observed. Fourth- and seventh-grade students in both communities were more likely to meet behavioral targets post intervention for sugar-sweetened beverages (both communities: P

Participation in recommended levels of physical activity promotes a healthy body weight and reduced chronic disease risk. To inform investment in prevention initiatives, we simulate the national implementation, impact on physical activity and childhood obesity and associated cost-effectiveness (versus the status quo) of six recommended strategies that can be applied throughout childhood to increase physical activity in US school, afterschool and childcare settings. In 2016, the Childhood Obesity Intervention Cost Effectiveness Study (CHOICES) systematic review process identified six interventions for study. A microsimulation model estimated intervention outcomes 2015-2025 including changes in mean MET-hours/day, intervention reach and cost per person, cost per MET-hour change, ten-year net costs to society and cases of childhood obesity prevented. First year reach of the interventions ranged from 90,000 youth attending a Healthy Afterschool Program to 31.3 million youth reached by Active School Day policies. Mean MET-hour/day/person increases ranged from 0.05 MET-hour/day/person for Active PE and Healthy Afterschool to 1.29 MET-hour/day/person for the implementation of New Afterschool Programs. Cost per MET-hour change ranged from cost saving to $3.14. Approximately 2500 to 110,000 cases of children with obesity could be prevented depending on the intervention implemented. All of the six interventions are estimated to increase physical activity levels among children and adolescents in the US population and prevent cases of childhood obesity. Results do not include other impacts of increased physical activity, including cognitive and behavioral effects. Decision-makers can use these methods to inform prioritization of physical activity promotion and obesity prevention on policy agendas.

Objective This study aimed to estimate the cost-effectiveness and impact on childhood obesity of installation of chilled water dispensers ("water jets") on school lunch lines and to compare water jets' cost, reach, and impact on water consumption with three additional strategies. Methods The Childhood Obesity Intervention Cost Effectiveness Study(CHOICES) microsimulation model estimated the cost-effectiveness of water jets on US childhood obesity cases prevented in 2025. Also estimated were the cost, number of children reached, and impact on water consumption of the installation of water jets and three other strategies. Results Installing water jets on school lunch lines was projected to reach 29.6 million children (95% uncertainty interval [UI]: 29.4 million-29.8 million), cost $4.25 (95% UI: $2.74-$5.69) per child, prevent 179,550 cases of childhood obesity in 2025 (95% UI: 101,970-257,870), and save $0.31 in health care costs per dollar invested (95% UI: $0.15-$0.55). In the secondary analysis, installing cup dispensers next to existing water fountains was the least costly but also had the lowest population reach. Conclusions Installating water jet dispensers on school lunch lines could also save almost half of the dollars needed for implementation via a reduction in obesity-related health care costs. School-based interventions to promote drinking water may be relatively inexpensive strategies for improving child health.

Many children are not sufficiently physically active. This study uses a quasi-experimental design to evaluate whether participation in a before-school physical activity program called Build Our Kids' Success (BOKS) increases physical activity. Participants (n = 426) were students in Fall, 2016 enrolled in BOKS programming and matched non-BOKS control students from the same grades (Kindergarten-6) and schools in Massachusetts and Rhode Island. Analyses conducted in 2017 examined differences between children in BOKS versus controls in total daily steps, minutes of moderate-to-vigorous (MVPA), vigorous (VPA), and total physical activity (TPA) assessed via Fitbit Charge HR™ monitors. Additional analyses compared physical activity on program days and non-program days. Students (mean age = 8.6 y; 47% female, 58% White, Non-Hispanic) wore monitors an average of 21.7 h/day on 3.2 days during the school week. Compared with controls, on BOKS days, BOKS participants accumulated more steps (1147, 95% confidence interval (CI): 583–1712, P, Highlights • Activity programs before school may increase physical activity levels. • Program participants were more active than non-participants. • Program participants accumulated more physical activity on days they participated.

BACKGROUND/OBJECTIVES: State-specific obesity prevalence data are critical to public health efforts to address the childhood obesity epidemic. However, few states administer objectively-measured BMI surveillance programs. This study reports state-specific childhood obesity prevalence by age and sex correcting for parent-reported child height and weight bias. SUBJECTS/METHODS: As part of the Childhood Obesity Intervention Cost Effectiveness Study (CHOICES), we developed childhood obesity prevalence estimates for states for the period 2005–2010 using data from the 2010 U.S. Census and American Community Survey (ACS), 2003–2004 and 2007–2008 National Survey of Children’s Health (NSCH) (n=133,213), and 2005–2010 National Health and Nutrition Examination Surveys (NHANES) (n=9,377; ages 2–17). Measured height and weight data from NHANES were used to correct parent-report bias in NSCH using a non-parametric statistical matching algorithm. Model estimates were validated against surveillance data from five states (AR, FL, MA, PA, and TN) that conduct censuses of children across a range of grades. RESULTS: Parent-reported height and weight resulted in the largest overestimation of childhood obesity in males ages 2–5 years (NSCH: 42.36% vs. NHANES: 11.44%). The CHOICES model estimates for this group (12.81%) and for all age and sex categories were not statistically different from NHANES. Our modeled obesity prevalence aligned closely with measured data from five validation states, with a 0.64 percentage point mean difference (range: 0.23–1.39) and a high correlation coefficient (r=0.96, p=0.009). Estimated state-specific childhood obesity prevalence ranged from 11.0% to 20.4%. CONCLUSION: Uncorrected estimates of childhood obesity prevalence from NSCH vary widely from measured national data, from a 278% overestimate among males aged 2–5 years to a 44% underestimate among females aged 14–17 years. This study demonstrates the validity of the CHOICES matching methods to correct the bias of parent-reported BMI data and highlights the need for public release of more recent data from the 2011–2012 NSCH.

Objective To evaluate the potential cost-effectiveness of and stakeholder perspectives on a sugar-sweetened beverage (SSB) excise tax and a Supplemental Nutrition Assistance Program (SNAP) policy that would not allow SSB purchases in Maine, US. Design A cost-effectiveness simulation model combined with stakeholder interviews. Setting Maine, US. Participants Microsimulation of the Maine population in 2015 and interviews with stakeholders (n = 14). Study conducted from 2013 to 2017. Main Outcome Measures Health care cost savings, net costs, and quality-adjusted life-years (QALYs) from 2017 to 2027. Stakeholder positions on policies. Retail SSB cost and implementation cost data were collected. Analysis Childhood Obesity Intervention Cost-Effectiveness Study project microsimulation model with uncertainty analysis to estimate cost-effectiveness. Thematic stakeholder interview coding. Results Over 10 years, the SSB and SNAP policies were projected to reduce health care costs by $78.3 million (95% uncertainty interval [UI], $31.7 million–$185 million) and $15.3 million (95% UI, $8.32 million–$23.9 million), respectively. The SSB and SNAP policies were projected to save 3,560 QALYs (95% UI, 1,447–8,361) and 749 QALYs (95% UI, 415–1,168), respectively. Stakeholders were more supportive of SSB taxes than the SNAP policy because of equity concerns associated with the SNAP policy. Conclusions and Implications Cost-effectiveness analysis provided evidence of potential health improvement and cost savings to state-level stakeholders weighing broader implementation considerations.

OBJECTIVES: To estimate the cost-effectiveness and population impact of the national implementation of the Study of Technology to Accelerate Research (STAR) intervention for childhood obesity. METHODS: In the STAR cluster-randomized trial, 6- to 12-year-old children with obesity seen at pediatric practices with electronic health record (EHR)-based decision support for primary care providers and self-guided behavior-change support for parents had significantly smaller increases in BMI than children who received usual care. We used a microsimulation model of a national implementation of STAR from 2015 to 2025 among all pediatric primary care providers in the United States with fully functional EHRs to estimate cost, impact on obesity prevalence, and cost-effectiveness. RESULTS: The expected population reach of a 10-year national implementation is ∼2 million children, with intervention costs of $119 per child and $237 per BMI unit reduced. At 10 years, assuming maintenance of effect, the intervention is expected to avert 43 000 cases and 226 000 life-years with obesity at a net cost of $4085 per case and $774 per life-year with obesity averted. Limiting implementation to large practices and using higher estimates of EHR adoption improved both cost-effectiveness and reach, whereas decreasing the maintenance of the intervention’s effect worsened the former. CONCLUSIONS: A childhood obesity intervention with electronic decision support for clinicians and self-guided behavior-change support for parents may be more cost-effective than previous clinical interventions. Effective and efficient interventions that target children with obesity are necessary and could work in synergy with population-level prevention strategies to accelerate progress in reducing obesity prevalence.

BACKGROUND: Afterschool interventions have been found to improve the nutritional quality of snacks served. However, there is limited evidence on how these interventions affect children’s snacking behaviors. OBJECTIVE: To determine the impact of an afterschool intervention focused at the school district, site, family, and child levels on dietary consumption of foods and beverages served at snack. DESIGN: Secondary analysis of a group-randomized controlled trial. PARTICIPANTS/SETTING: Data were collected from 400 children at 20 Boston, MA afterschool sites before (fall 2010) and after (spring 2011) intervention implementation. INTERVENTION: The Out-of-School Nutrition and Physical Activity intervention aimed to promote fruits, vegetables, whole grains, and water, while limiting sugary drinks and trans fats. Researchers worked with district foodservice staff to change snack foods and beverages. Teams of afterschool staff participated in three three-hour learning collaborative sessions to build skills and created action plans for changing site practices. The intervention included family and child nutrition education. MAIN OUTCOME MEASURES: Research assistants observed dietary snack consumption using a validated measure on two days per site at baseline and follow-up. STATISTICAL ANALYSES PERFORMED: This study used multivariable regression models, accounting for clustering of observations, to assess the intervention effect, and conducted post-hoc stratified analyses by foodservice type. RESULTS: Children in intervention sites had greater decreases in consumption of juice (−0.61 ounces/snack, 95% CI −1.11 – −0.12), beverage calories (−29.0 kcal/snack, 95% CI −40.1 – −17.9), foods with trans fats (−0.12 servings/snack, 95% CI −0.19 – −0.04), total calories (−47.8 kcal/snack, 95% CI −68.3 – −27.3) and increases in consumption of whole grains (0.10 servings/snack, 95% CI 0.02–0.18) compared to controls. In post hoc analyses, sites with on-site foodservice had significant improvements for all outcomes (p

Author(s): Blaine, Rachel E; Franckle, Rebecca L; Ganter, Claudia; Falbe, Jennifer; Giles, Catherine; Criss, Shaniece; Kwass, Jo-Ann; Land, Thomas; Gortmaker, Steven L; Chuang, Emmeline; Davison, Kirsten K; MA-CORD Project Group | Abstract: IntroductionAlthough evidence-based interventions to prevent childhood obesity in school settings exist, few studies have identified factors that enhance school districts' capacity to undertake such efforts. We describe the implementation of a school-based intervention using classroom lessons based on existing "Eat Well and Keep Moving" and "Planet Health" behavior change interventions and schoolwide activities to target 5,144 children in 4th through 7th grade in 2 low-income school districts.MethodsThe intervention was part of the Massachusetts Childhood Obesity Research Demonstration (MA-CORD) project, a multisector community-based intervention implemented from 2012 through 2014. Using mixed methods, we operationalized key implementation outcomes, including acceptability, adoption, appropriateness, feasibility, implementation fidelity, perceived implementation cost, reach, and sustainability.ResultsMA-CORD was adopted in 2 school districts that were facing resource limitations and competing priorities. Although strong leadership support existed in both communities at baseline, one district's staff reported less schoolwide readiness and commitment. Consequently, fewer teachers reported engaging in training, teaching lessons, or planning to sustain the lessons after MA-CORD. Interviews showed that principal and superintendent turnover, statewide testing, and teacher burnout limited implementation; passionate wellness champions in schools appeared to offset implementation barriers.ConclusionFuture interventions should assess adoption readiness at both leadership and staff levels, offer curriculum training sessions during school hours, use school nurses or health teachers as wellness champions to support teachers, and offer incentives such as staff stipends or play equipment to encourage school participation and sustained intervention activities.

Introduction Routine collection, analysis, and reporting of data on child height, weight, and body mass index (BMI), particularly at the state and local levels, are needed to monitor the childhood obesity epidemic, plan intervention strategies, and evaluate the impact of interventions. Child BMI surveillance systems operated by the US government do not provide state or local data on children across a range of ages. The objective of this study was to describe the extent to which state governments conduct child BMI surveillance. Methods From August through December 2014, we conducted a structured telephone survey with state government administrators to learn about state surveillance of child BMI. We also searched websites of state health and education agencies for information about state surveillance. Results State agency administrators in 48 states and Washington, DC, completed telephone interviews (96% response rate). Based on our interviews and Internet research, we determined that 14 states collect child BMI data in a manner consistent with standard definitions of public health surveillance. Conclusion The absence of child BMI surveillance systems in most states limits the ability of public health practitioners and policymakers to develop and evaluate responses to the childhood obesity epidemic. Greater investment in surveillance is needed to identify the most effective and cost-effective childhood obesity interventions.

Background State-level estimates from the Centers for Disease Control and Prevention (CDC) underestimate the obesity epidemic because they use self-reported height and weight. We describe a novel bias-correction method and produce corrected state-level estimates of obesity and severe obesity. Methods Using non-parametric statistical matching, we adjusted self-reported data from the Behavioral Risk Factor Surveillance System (BRFSS) 2013 (n = 386,795) using measured data from the National Health and Nutrition Examination Survey (NHANES) (n = 16,924). We validated our national estimates against NHANES and estimated bias-corrected state-specific prevalence of obesity (BMI≥30) and severe obesity (BMI≥35). We compared these results with previous adjustment methods. Results Compared to NHANES, self-reported BRFSS data underestimated national prevalence of obesity by 16% (28.67% vs 34.01%), and severe obesity by 23% (11.03% vs 14.26%). Our method was not significantly different from NHANES for obesity or severe obesity, while previous methods underestimated both. Only four states had a corrected obesity prevalence below 30%, with four exceeding 40%–in contrast, most states were below 30% in CDC maps. Conclusions Twelve million adults with obesity (including 6.7 million with severe obesity) were misclassified by CDC state-level estimates. Previous bias-correction methods also resulted in underestimates. Accurate state-level estimates are necessary to plan for resources to address the obesity epidemic.

Importance Millions of children attend after-school programs in the United States. Increasing physical activity levels of program participants could have a broad effect on children’s health. Objective To test the effectiveness of the Out of School Nutrition and Physical Activity (OSNAP) Initiative in increasing children’s physical activity levels in existing after-school programs. Design, Setting, and Participants Cluster-randomized controlled trial with matched program pairs. Baseline data were collected September 27 through November 12, 2010, with follow-up data collected April 25 through May 27, 2011. The dates of our analysis were March 11, 2014, through August 18, 2015. The setting was 20 after-school programs in Boston, Massachusetts. All children 5 to 12 years old in participating programs were eligible for study inclusion. Interventions Ten programs participated in a series of three 3-hour learning collaborative workshops, with additional optional opportunities for training and technical assistance. Main Outcomes and Measures Change in number of minutes and bouts of moderate to vigorous physical activity, vigorous physical activity, and sedentary activity and change in total accelerometer counts between baseline and follow-up. Results Participants with complete data were 402 racially/ethnically diverse children, with a mean age of 7.7 years. Change in the duration of physical activity opportunities offered to children during program time did not differ between conditions (−1.2 minutes; 95% CI, −14.2 to 12.4 minutes; P = .87). Change in moderate to vigorous physical activity minutes accumulated by children during program time did not differ significantly by intervention status (−1.0; 95% CI, −3.3 to 1.3; P = .40). Total minutes per day of vigorous physical activity (3.2; 95% CI, 1.8-4.7; P P P = .01) increased significantly during program time among intervention participants compared with control participants. Conclusions and Relevance Although programs participating in the OSNAP Initiative did not allot significantly more time for physical activity, they successfully made existing time more vigorously active for children receiving the intervention. Trial Registration clinicaltrials.gov Identifier:NCT01396473

Background Nutrition and physical activity interventions have been effective in creating environmental changes in afterschool programs. However, accurate assessment can be time-consuming and expensive as initiatives are scaled up for optimal population impact. This study aims to determine the criterion validity of a simple, low-cost, practitioner-administered observational measure of afterschool physical activity, nutrition, and screen time practices and child behaviors. Methods Directors from 35 programs in three cities completed the Out-of-School Nutrition and Physical Activity Observational Practice Assessment Tool (OSNAP-OPAT) on five days. Trained observers recorded snacks served and obtained accelerometer data each day during the same week. Observations of physical activity participation and snack consumption were conducted on two days. Correlations were calculated to validate weekly average estimates from OSNAP-OPAT compared to criterion measures. Weekly criterion averages are based on 175 meals served, snack consumption of 528 children, and physical activity levels of 356 children. Results OSNAP-OPAT validly assessed serving water (r = 0.73), fruits and vegetables (r = 0.84), juice >4oz (r = 0.56), and grains (r = 0.60) at snack; sugary drinks (r = 0.70) and foods (r = 0.68) from outside the program; and children’s water consumption (r = 0.56) (all p

INTRODUCTION Little is known about how the nutrition environment in after-school settings may affect children's dietary intake. We measured the nutritional quality of after-school snacks provided by programs participating in the National School Lunch Program or the Child and Adult Care Food Program and compared them with snacks brought from home or purchased elsewhere (nonprogram snacks). We quantified the effect of nonprogram snacks on the dietary intake of children who also received program-provided snacks during after-school time. Our study objective was to determine how different sources of snacks affect children's snack consumption in after-school settings. METHODS We recorded snacks served to and brought in by 298 children in 18 after-school programs in Boston, Massachusetts, on 5 program days in April and May 2011. We measured children's snack consumption on 2 program days using a validated observation protocol. We then calculated within-child change-in-change models to estimate the effect of nonprogram snacks on children's dietary intake after school. RESULTS Nonprogram snacks contained more sugary beverages and candy than program-provided snacks. Having a nonprogram snack was associated with significantly higher consumption of total calories (+114.7 kcal, P < .001), sugar-sweetened beverages (+0.5 oz, P = .01), desserts (+0.3 servings, P < .001), and foods with added sugars (+0.5 servings; P < .001) during the snack period. CONCLUSION On days when children brought their own after-school snack, they consumed more salty and sugary foods and nearly twice as many calories than on days when they consumed only program-provided snacks. Policy strategies limiting nonprogram snacks or setting nutritional standards for them in after-school settings should be explored further as a way to promote child health.