Person: Gortmaker, Steven
Loading...
Email Address
AA Acceptance Date
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Gortmaker
First Name
Steven
Name
Gortmaker, Steven
16 results
Search Results
Now showing 1 - 10 of 16
Publication Evaluating the Impact of the Healthy Beverage Executive Order for City Agencies in Boston, Massachusetts, 2011–2013(Centers for Disease Control and Prevention, 2015) Cradock, Angie; Kenney, Erica; McHugh, Anne; Conley, Lisa; Mozaffarian, Rebecca; Reiner, Jennifer F.; Gortmaker, StevenIntroduction: Intake of sugar-sweetened beverages (SSBs) is associated with negative health effects. Access to healthy beverages may be promoted by policies such as the Healthy Beverage Executive Order (HBEO) established by former Boston mayor Thomas M. Menino, which directed city departments to eliminate the sale of SSBs on city property. Implementation consisted of “traffic-light signage” and educational materials at point of purchase. This study evaluates the impact of the HBEO on changes in beverage availability. Methods: Researchers collected data on price, brand, and size of beverages for sale in spring 2011 (899 beverage slots) and for sale in spring 2013, two years after HBEO implementation (836 beverage slots) at access points (n = 31) at city agency locations in Boston. Nutrient data, including calories and sugar content, from manufacturer websites were used to determine HBEO beverage traffic-light classification category. We used paired t tests to examine change in average calories and sugar content of beverages and the proportion of beverages by traffic-light classification at access points before and after HBEO implementation. Results: Average beverage sugar grams and calories at access points decreased (sugar, −13.1 g; calories, −48.6 kcal; p<.001) following the implementation of the HBEO. The average proportion of high-sugar (“red”) beverages available per access point declined (−27.8%, p<.001). Beverage prices did not change over time. City agencies were significantly more likely to sell only low-sugar beverages after the HBEO was implemented (OR = 4.88; 95% CI, 1.49–16.0). Discussion Policies such as the HBEO can promote community-wide changes that make healthier beverage options more accessible on city-owned properties.Publication Informal Training in Staff Networks to Support Dissemination of Health Promotion Programs(SAGE Publications, 2010) Ramanadhan, Shoba; Wiecha, Jean L.; Gortmaker, Steven; Emmons, Karen; Viswanath, KasisomayajulaPublication Validity of a practitioner-administered observational tool to measure physical activity, nutrition, and screen time in school-age programs(BioMed Central, 2014) Lee, Rebekka; Emmons, Karen M; Okechukwu, Cassandra; Barrett, Jessica L; Kenney, Erica; Cradock, Angie; Giles, Catherine; deBlois, Madeleine E; Gortmaker, StevenBackground: 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.Publication Identifying Sources of Children’s Consumption of Junk Food in Boston After-School Programs, April–May 2011(Centers for Disease Control and Prevention, 2014) Kenney, Erica; Austin, S. Bryn; Cradock, Angie; Giles, Catherine; Lee, Rebekka; Davison, Kirsten; Gortmaker, StevenIntroduction: 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.Publication The cost of a primary care-based childhood obesity prevention intervention(BioMed Central, 2014) Wright, Davene R; Taveras, Elsie; Gillman, Matthew; Horan, Christine M; Hohman, Katherine H; Gortmaker, Steven; Prosser, LisaBackground: 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.Publication US States’ Childhood Obesity Surveillance Practices and Recommendations for Improving Them, 2014–2015(Centers for Disease Control and Prevention, 2016) Blondin, Kelly J.; Giles, Catherine; Cradock, Angie; Gortmaker, Steven; Long, MichaelIntroduction: 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.Publication Social and Economic Consequences of Overweight in Adolescence and Young Adulthood(New England Journal of Medicine (NEJM/MMS), 1993) Gortmaker, Steven; Must, Aviva; Perrin, James; Sobol, Arthur; Dietz, William H.Publication Withdrawing Payment for Nonscientific Drug Therapy(American Medical Association (AMA), 1990) Soumerai, Stephen; Ross-Degnan, Dennis; Gortmaker, Steven; Avorn, Jeromeittle is known about the effect on clinical decision making of nonreimbursement for ineffective medical technologies. Using a time-series design, we studied the effects of cessation of government payment for 12 categories of drugs of questionable efficacy (Drug Efficacy Study Implementation drugs) in a random sample of the New Jersey Medicaid population (N = 390 465) and in four cohorts of regular users of these products. We measured changes in the overall levels of prescriptions, expenditures, and physicians' use of substitute drugs. Although withdrawn drugs accounted for 7% of prescriptions in the base year, there was no measurable reduction in overall drug use or expenditures after the regulation; prescription rates actually rose from 0.86 to 1.00 monthly prescriptions per enrollee throughout the 42-month study. Controlling for preexisting trends, an estimated drop in the use of study drugs of 21.7 prescriptions per 1000 enrollees per month was offset by an increase in the use of substitute drugs of 33.7 prescriptions. Both desirable and unimproved therapeutic substitutions were observed. Used alone, curtailment of reimbursement for marginally effective therapies results in both desirable and unintended clinical substitutions and may not reduce costs. Supplementing such restrictions with education may be necessary to promote practices that are more therapeutically and economically appropriate.Publication Assessment of a Districtwide Policy on Availability of Competitive Beverages in Boston Public Schools, Massachusetts, 2013(Centers for Disease Control and Prevention, 2016) Mozaffarian, Rebecca; Gortmaker, Steven; Kenney, Erica; Carter, Jill E.; Howe, M. Caitlin Westfall; Reiner, Jennifer F.; Cradock, AngieIntroduction: 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.Publication Redrawing the US Obesity Landscape: Bias-Corrected Estimates of State-Specific Adult Obesity Prevalence(Public Library of Science, 2016) Ward, Zachary; Long, Michael W.; Resch, Stephen; Gortmaker, Steven; Cradock, Angie; Giles, Catherine; Hsiao, Amber; Wang, Y. ClaireBackground: 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.