Person:

Gortmaker, Steven

Background: Built environment features of neighborhoods may be related to obesity among adolescents and potentially related to obesity-related health disparities. The purpose of this study was to investigate spatial relationships between various built environment features and body mass index (BMI) z-score among adolescents, and to investigate if race/ethnicity modifies these relationships. A secondary objective was to evaluate the sensitivity of findings to the spatial scale of analysis (i.e. 400- and 800-meter street network buffers). Methods: Data come from the 2008 Boston Youth Survey, a school-based sample of public high school students in Boston, MA. Analyses include data collected from students who had georeferenced residential information and complete and valid data to compute BMI z-score (n = 1,034). We built a spatial database using GIS with various features related to access to walking destinations and to community design. Spatial autocorrelation in key study variables was calculated with the Global Moran’s I statistic. We fit conventional ordinary least squares (OLS) regression and spatial simultaneous autoregressive error models that control for the spatial autocorrelation in the data as appropriate. Models were conducted using the total sample of adolescents as well as including an interaction term for race/ethnicity, adjusting for several potential individual- and neighborhood-level confounders and clustering of students within schools. Results: We found significant positive spatial autocorrelation in the built environment features examined (Global Moran’s I most ≥ 0.60; all p = 0.001) but not in BMI z-score (Global Moran’s I = 0.07, p = 0.28). Because we found significant spatial autocorrelation in our OLS regression residuals, we fit spatial autoregressive models. Most built environment features were not associated with BMI z-score. Density of bus stops was associated with a higher BMI z-score among Whites (Coefficient: 0.029, p < 0.05). The interaction term for Asians in the association between retail destinations and BMI z-score was statistically significant and indicated an inverse association. Sidewalk completeness was significantly associated with a higher BMI z-score for the total sample (Coefficient: 0.010, p < 0.05). These significant associations were found for the 800-meter buffer. Conclusion: Some relationships between the built environment and adolescent BMI z-score were in the unexpected direction. Our findings overall suggest that the built environment does not explain a large proportion of the variation in adolescent BMI z-score or racial disparities in adolescent obesity. However, there are some differences by race/ethnicity that require further research among adolescents.

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 <0.05). Reports of physical activity time offered were correlated with accelerometer estimates (minutes of moderate and vigorous physical activity r = 0.59, p = 0.02; vigorous physical activity r = 0.63, p = 0.01). The reported proportion of children participating in moderate and vigorous physical activity was correlated with observations (r = 0.48, p = 0.03), as were reports of computer (r = 0.85) and TV/movie (r = 0.68) time compared to direct observations (both p < 0.01). Conclusions: OSNAP-OPAT can assist researchers and practitioners in validly assessing nutrition and physical activity environments and behaviors in afterschool settings. Trial registration Phase 1 of this measure validation was conducted during a study registered at clinicaltrials.gov NCT01396473. Electronic supplementary material The online version of this article (doi:10.1186/s12966-014-0145-5) contains supplementary material, which is available to authorized users.

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.

Background: United States pediatric guidelines recommend that childhood obesity counseling be conducted in the primary care setting. Primary care-based interventions can be effective in improving health behaviors, but also costly. The purpose of this study was to evaluate the cost of a primary care-based obesity prevention intervention targeting children between the ages of two and six years who are at elevated risk for obesity, measured against usual care. Methods: High Five for Kids was a cluster-randomized controlled clinical trial that aimed to modify children’s nutrition and TV viewing habits through a motivational interviewing intervention. We assessed visit-related costs from a societal perspective, including provider-incurred direct medical costs, provider-incurred equipment costs, parent time costs and parent out-of-pocket costs, in 2011 dollars for the intervention (n = 253) and usual care (n = 192) groups. We conducted a net cost analysis using both societal and health plan costing perspectives and conducted one-way sensitivity and uncertainty analyses on results. Results: The total costs for the intervention group and usual care groups in the first year of the intervention were $65,643 (95% CI [$64,522, $66,842]) and $12,192 (95% CI [$11,393, $13,174]). The mean costs for the intervention and usual care groups were $259 (95% CI [$255, $264]) and $63 (95% CI [$59, $69]) per child, respectively, for a incremental difference of $196 (95% CI [$191, $202]) per child. Children in the intervention group attended a mean of 2.4 of a possible 4 in-person visits and received 0.45 of a possible 2 counseling phone calls. Provider-incurred costs were the primary driver of cost estimates in sensitivity analyses. Conclusions: High Five for Kids was a resource-intensive intervention. Further studies are needed to assess the cost-effectiveness of the intervention relative to other pediatric obesity interventions. Trial registration ClinicalTrials.gov Identifier: NCT00377767.

In an attempt to contain costs, 27 Medicaid programs have implemented patient-level payment limits for medications, but the effects of these restrictions on quality of care, costs, and health status remain largely unknown. We measured the effect of one state's limit of three paid prescriptions per month and its replacement a year later by a $1 copayment. Using data on 48 months of claims in the study state (New Hampshire) and a comparison state (New Jersey), we employed time-series analysis to evaluate patient-level changes in the number of prescriptions filled for 16 drugs that varied in their clinical importance and cost. Among 10,734 continuously enrolled patients, the limit of three paid prescriptions per month caused a sudden, sustained drop of 30 percent in the number of prescriptions filled (from 1.10 to 0.77 prescriptions per patient per month); no change was observed in the comparison state. The 860 recipients of multiple drugs, who were predominantly female and elderly or disabled, were most severely affected; the number of prescriptions per month dropped from 5.2 to 2.8 (46 percent). The decrease was greatest for "ineffective drugs" (58 percent), but large drops were also observed for "essential" medications, such as insulin (28 percent), thiazides (28 percent), and furosemide (30 percent). Reductions in Medicaid prescriptions were minimally offset by increases in the size of the prescription or in out-of-pocket payments. When a $1 copayment replaced the three-prescription cap, prescriptions for most medications increased to just below precap levels. Medicaid's savings on drug costs resulting from both policies were comparable ($0.4 to $0.8 million annually), but the copayment policy had less effect on patients receiving multiple drugs. Because the clinical consequences of such policies cannot be assessed from prescription data alone, further study is needed to determine the effects of cost-containment strategies on health status and the use of other services among poor populations. (N Engl J Med 1987; 317:550–6.)

Introduction: Although 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. Methods: The 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. Results: MA-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. Conclusion: Future 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.

Background: In 1999, the Centers for Disease Control and Prevention (CDC) funded Play Across Boston to address disparities in access to physical activity facilities and programs for Boston, Mass, inner-city youths. Context: Local stakeholders worked with the Harvard School of Public Health Prevention Research Center and Northeastern University's Center for the Study of Sport in Society to improve opportunities for youth physical activity through censuses of facilities and programs and dissemination of results. Methods: Play Across Boston staff conducted a facility census among 230 public recreational complexes and a program census of 86% of 274 physical activity programs for Boston inner-city youths aged 5 to 18 years during nonschool hours for the 1999 to 2000 school year and summer of 2000. Comparison data were collected from three suburban communities: one low income, one medium income, and one high income. Consequences: Although Boston has a substantial sports and recreational infrastructure, the ratio of youths to facilities in inner-city Boston was twice the ratio found in the medium- and high-income suburban comparison communities. The low-income suburban comparison community had the highest number of youths per recreational facility with 137 youths per facility, followed by Boston with 117 youths per facility. The ratio of youths to facilities differed among Boston neighborhoods. Boston youths participated less in school-year physical activities than youths in medium- and high-income communities, and less advantaged Boston neighborhoods had lower levels of participation than more advantaged Boston neighborhoods. Girls participated less than boys. Interpretation: Play Across Boston successfully developed and implemented a rigorous needs assessment with local relevance and important implications for public health research on physical activity and the environment. Boston Mayor Thomas M. Menino called the Play Across Boston report a "playbook" for future sports and recreation planning by the city of Boston and its community partners.

Establishing healthy habits in youth can help prevent many chronic health problems later in life that are attributable to unhealthy eating, sedentary lifestyle, and overweight. For this reason, many public health professionals are interested in working with school systems to reach children in school settings. However, a lack of familiarity with how schools operate can be a substantial impediment to developing effective partnerships with schools. We describe lessons learned from three successful school health promotion programs that were developed and disseminated through collaborations between public health professionals, academic institutions, and school personnel. The programs include two focused on physical activity and good nutrition for elementary and middle school children — Coordinated Approach to Child Health (CATCH) and Planet Health — and one focused on smoking cessation among adolescents — Not-On-Tobacco (N-O-T). Important features of these school health programs include 1) identification of staff and resources required for program implementation and dissemination; 2) involvement of stakeholders (e.g., teachers, students, other school personnel, parents, nonprofit organizations, professional organizations) during all phases of program development and dissemination; 3) planning for dissemination of programs early in the development and testing process; and 4) rigorous evaluation of interventions to determine their effectiveness. The authors provide advice based on lessons learned from these programs to those who wish to work with young people in schools.

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.

Introduction: Competitive beverages are drinks sold outside of the federally reimbursable school meals program and include beverages sold in vending machines, a la carte lines, school stores, and snack bars. Competitive beverages include sugar-sweetened beverages, which are associated with overweight and obesity. We described competitive beverage availability 9 years after the introduction in 2004 of district-wide nutrition standards for competitive beverages sold in Boston Public Schools. Methods: In 2013, we documented types of competitive beverages sold in 115 schools. We collected nutrient data to determine compliance with the standards. We evaluated the extent to which schools met the competitive-beverage standards and calculated the percentage of students who had access to beverages that met or did not meet the standards. Results: Of 115 schools, 89.6% met the competitive beverage nutrition standards; 88.5% of elementary schools and 61.5% of middle schools did not sell competitive beverages. Nutrition standards were met in 79.2% of high schools; 37.5% did not sell any competitive beverages, and 41.7% sold only beverages meeting the standards. Overall, 85.5% of students attended schools meeting the standards. Only 4.0% of students had access to sugar-sweetened beverages. Conclusion: A comprehensive, district-wide competitive beverage policy with implementation support can translate into a sustained healthful environment in public schools.