Working Group Report on Future Research Directions in Childhood Obesity Prevention and Treatment

August 21-22, 2007


Planning Group
Roster - Presenters and Moderators
Roster - NIH and Other Agency Staff

Workshop Report (in-page links)
Background and Objectives
Summary of Childhood Obesity Prevention Panel Meeting
Summary of Childhood Obesity Treatment Panel Meeting
Cross-cutting Issues
Recommendations for Research in Childhood Obesity Prevention
Recommendations for Research in Childhood Obesity Treatment
Cross-cutting Research Recommendations
Priorities for Research

Background and Objectives

Childhood overweight and obesity have reached epidemic proportions and are major public health problems nationally and globally (1). Between 1970 and 2004, the prevalence of overweight almost tripled among U.S. preschoolers and adolescents and quadrupled among children aged 6 to11 years (2). In 2003-2004, 17.1% of children aged 2 to 19 years were at or above the 95th percentile of Body Mass Index (BMI) compared to 5-6% in the 1970s, and these percentages are higher in non-Hispanic Blacks and Mexican Americans (20.0% and 19.2%) than in Whites (16%) (2). Obesity rates are also high among American Indian children with a prevalence estimate of 22% for boys and 18% for girls (3). Currently, about 25 million U.S. children and adolescents are overweight or obese (1, 4), and children from families that are of low socio-economic status are disproportionately affected.

Obesity epidemic bar graph and link to data table

Obesity during childhood has been associated with numerous adverse effects including a variety of health complications such as hypertension, dyslipidemia, left ventricular hypertrophy, atherosclerosis, metabolic syndrome, type 2 diabetes, sleep disorders, and non-alcoholic fatty liver disease (5-7) as well as psychological effects such as stigmatization, discrimination, depression and emotional trauma. Obesity in childhood also substantially increases the risk of being an obese adult (8). In addition, adults who were obese during childhood have higher risk of developing hypertension, dyslipidemia, metabolic syndrome, diabetes, and coronary heart disease than those who were not obese during childhood (8).

These health consequences of childhood overweight and obesity add to the burden of health-care costs. The annual U.S. obesity-attributable medical expenditures were estimated at $75 billion in 2003 dollars (9-10). Hospital discharges for obesity-associated diseases in youth aged 6 to 17 years increased more than three-fold from 1979-81 to 1997-99 (35 million to 127 million) (11). Hospital charges of obesity-associated comorbidities that required hospitalization of pediatric patients were higher than those that were not obesity-associated (e.g., discharges with obesity as a secondary diagnosis vs. those without for asthma cost $7,766 vs. $6,043; p<0.05), providing a financial imperative for obesity prevention initiatives (12).

The development of obesity in childhood and subsequently in adulthood involves interactions among multiple factors that may shape daily diet and physical activity behaviors and increase obesity and cardiovascular disease risks. These factors are personal (e.g., beliefs, attitudes, cultural experiences, taste preferences, and dietary composition), environmental (e.g., homes, schools, community, food availability and cost, built environment), societal (e.g., cultural norms, advertising and food marketing, social networks, technological developments, economics, public policy) and healthcare-related (e.g., provider counseling and treatment, reimbursement), as well as physiological (e.g., intrauterine and early life “programming”, appetite and satiety mechanisms and regulation, adipose tissue metabolism, genetic predisposition) (13).

In light of the recognition of childhood obesity as a major public health problem with multiple etiological factors and with comorbidities and their associated high health-care costs, numerous health organizations and foundations (e.g., Institutes of Medicine, American Academy of Pediatrics, American Medical Association, American Heart Association, Robert Wood Johnson Foundation, and the National Institutes of Health [NIH]) have called for a collective effort to combat the problem from multiple fronts, including innovative cutting-edge research (1). To advise the National Heart, Lung, and Blood Institute (NHLBI) and other NIH Institutes on which research areas to stimulate to advance knowledge about effective obesity prevention and treatment in childhood, NHLBI convened a Working Group meeting on August 21-22, 2007. The objective of the Working Group was to identify priorities for future research directions in childhood obesity prevention and treatment. The Working Group meeting was sponsored by NHLBI with co-sponsorship by the Office of Behavioral and Social Science Research (OBSSR) and the Office of Dietary Supplements (ODS).

The Working Group was organized into a Prevention Panel, chaired by Dr. June Stevens, Professor of Nutrition and Chair of the Department of Nutrition, University of North Carolina, Chapel Hill; and a Treatment Panel, chaired by Dr. Stephen Daniels, Professor of Pediatrics and Preventive Medicine, University of Colorado School of Medicine, and Chair of the Department of Pediatrics. Participants included leaders and representatives from public and private academic and medical institutions with expertise in a variety of health specialties, including pediatrics, preventive medicine, bariatric surgery, nutrition and diet therapy, physical activity, epidemiology, physiology, genetics, and research methodology, as well as staff from NHLBI, National Institute of Digestive, Diabetes and Kidney Diseases (NIDDK), National Institute of Child Health and Development (NICHD), National Center for Research Resources (NCRR), National Cancer Institute (NCI), OBSSR, ODS, and United States Department of Agriculture (USDA).

The Prevention Panel focused on research priorities to prevent excess weight gain in children and adolescents. The Treatment Panel focused on research priorities for treatment of obesity which has already developed in children and adolescents. Panel members reviewed the state of the science, and identified many opportunities for research in childhood obesity prevention and treatment. Topics discussed included behavioral and lifestyle interventions for childhood obesity prevention and treatment, pharmacologic and surgical treatment of severely obese youth, need for multi-level multi-component interventions, opportunities to advance research on the effects of the built environment, use of theoretical models and conceptual frameworks in the design of interventions, approaches for obesity prevention and weight loss treatment interventions for low socioeconomic status and minority populations, design and methodological approaches to make interventions more potent, and translation of promising childhood obesity prevention and treatment research into both clinical and community settings. Participants provided recommendations on how to advance knowledge through both observational and intervention studies.

The panels were charged to identify priorities for future research directions in childhood obesity prevention and treatment based on the following four criteria: scientific importance of the research question, potential likelihood of public health impact, likelihood of not being addressed by other funding entities, and feasibility and timeliness. This report is a summary of the Working Group meeting and the recommendations from the Working Group’s two panels.

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Summary of Childhood Obesity Prevention Panel Meeting

Overview of Pediatric Obesity Prevention Research

Prevention research, in contrast to treatment research, focuses on entire populations or a subpopulation of children to decrease the number who become overweight or obese and to reduce additional weight gain in those who may already be overweight. Prevention research is concerned about intervention sustainability and maintenance of intervention effects. The Working Group discussed recent reviews of pediatric obesity prevention research (14-19) and noted many limitations in research designs and outcomes. For example, a Cochran review (15) of 22 randomized controlled trials concluded that there was not enough evidence from trials to prove any one program or approach can prevent obesity in children or adolescents. Twelve of the 22 studies were short-term (<12 months), of which 8 focused on combined diet and physical activity interventions and found no intervention effects on BMI. The other 4 studies focused on single interventions (i.e., physical activity/TV reduction time), but only 2 found significantly lower BMI in the intervention group compared to the control group (20-21). Of the 10 longer-term studies ( ≥ 12 months), only 2 reported significantly lower BMI or fat skinfolds in the intervention compared to the control group (22-23). Other reviews by Flynn et al. (16) and Bluford et al. (17) reported a paucity of studies that addressed obesity prevention in certain subgroups of children (e.g., preschoolers, minorities, males, and immigrants). The Working Group noted the need for transdisciplinary studies that separately test efficacy, effectiveness and translation/dissemination. However, given the urgency of finding solutions to the problem of childhood obesity, it was recommended that these different types of research proceed simultaneously rather than following a strict trajectory from efficacy to effectiveness to translation in discrete, sequential steps (24).

Theoretical Models in Childhood Obesity Prevention

Theoretical models and conceptual frameworks that have been used in childhood obesity prevention research include the Transtheoretical Model (25), Health Belief Model (26), Social Cognitive Theory (27, 28), and Socio-ecological Models (29). In most cases these models and theories have provided the bases for studies that intervene on a select number of modifiable variables. However, theoretical models have accounted for less than 50% of the variance resulting from behavior change interventions (30). The Working Group noted that behavior change is highly variable, sensitive to initial conditions, and non-linear, and involves multiple interactions with, and influences from, the social and physical environments (30, 31). One proposed approach presented at the working group meeting stemmed from the observation that since behavior change is often non–linear, one could consider principles from “chaos” and self-determination theories as a framework for conceptualizing change. Motivational interviewing represents a clinical strategy that is consistent with these theories, as it can help induce epiphanies for individual behavior change (30). The Working Group concluded that theoretical and conceptual frameworks must be used, including innovative frameworks and models from other health fields (e.g., substance abuse literature) in designing interventions for pediatric obesity prevention and treatment. However, more research is needed to assess the potential for various behavioral models to contribute to obesity prevention (31-33) and to potentially develop new theoretical models or modify existing models for greater utility in obesity research.

Environmental Interventions

The environments of children include the home, child-care settings, school, community, recreational facilities, and community and transportation infrastructure. Studies on environmental correlates of children’s eating and physical activity behaviors are mostly cross-sectional and thus cannot provide causal inferences between the environment and behavior or BMI. For example, if it is observed that people who are on a walking track have lower BMIs, we don’t know if walking on the track leads to lower BMIs or whether those with lower BMIs simply choose to use a walking track. However, such studies help to identify environmental determinants of obesity, targets for interventions, and relationships of the built environment to physical activity and eating behaviors. For example, the home environment has shown that children who watched less than 2 hours of TV per day had a significantly lower average BMI z score than children who watched more than 2 hours per day (BMI z scores of 0.22 vs. 0.73, respectively; F[1,152] = 5.0, p < .03). (34). In one intervention trial, increases in the number of physical activity equipment, infrastructural changes made to playgrounds, and added supervision in middle school gymnasiums resulted in increased physical activity of middle school students (35). In an observational study, proximity to recreational facilities and programs was associated with higher total daily physical activity in children (36). In a study of 201 parents of children aged 4 to 17, active commuting (i.e., walking or bicycling) to school was higher in more walkable neighborhoods compared to less walkable neighborhoods (25% vs. 11%) (37). Other studies have found direct associations between neighborhood walkability and children’s physical activity levels (38, 39). Associations between the environment and eating behaviors have also been reported. Distance to the nearest food store was associated with greater preference for vegetables (z = 2.32, p = 0.020) (40). The Working Group called for observational studies that examine the association between the built environment and BMI as well as diet and physical activity behaviors, and intervention studies that assess whether larger-scale environmental changes (e.g., improving quality of parks and access to healthful foods, changing transportation systems such as trails, sidewalks, and crosswalks) improve physical activity and eating behaviors and reduce rate of weight gain in youth. Research is also needed for both individual-level and environmental-level interventions and studies that take advantage of the changes in the built environment as natural experiments that can be used with an appropriate evolutionary component to evaluate the utility of these alterations. When it is not feasible to evaluate changes in the built environment, then rigor can be improved with prospective studies that evaluate changes in behavior or BMI when families move to different neighborhoods, as well as with studies that assess changes in behavior or BMI among children living in neighborhoods with contrasting food and built environment attributes.

Multi-level Interventions

A review of 147 intervention studies by Flynn et al. (16) concluded that there have been a paucity of studies testing population-based and multi-level intervention approaches and that studies that focused on modifying the nutrition and physical activity environments lacked adequate methodological rigor. Very few studies conducted interventions in community or home settings or both, involved stakeholders in program implementation and evaluation, or intervened on preschool children, immigrant populations and males. Few interventions focused on environmental change. In a review of 38 school-based studies by Centers for Disease Control and Prevention Task Force (14), only 10 studies were judged to have adequate methodology to be considered. Many of those studies showed some behavioral and or weight changes in the hypothesized direction favoring the intervention group; however, the interventions and measures used were so varied that the CDC Task Force could not determine which approaches to school-based interventions were effective, defined as weight loss of ≥ 4 lb after ≥ 6 months of intervention, and thus did not develop specific recommendations based on these studies. The Task Force concluded that more evidence is needed before recommendations could be made concerning effective school-based interventions to control overweight or obesity. Other reviews of childhood obesity prevention interventions (15, 16) have also found a lack of evidence that identified the intervention components, duration, intensity, and settings most effective for childhood obesity prevention. The studies also lacked appropriate evaluations of mediating and moderating variables that could be important in determining changes in behavior.

From their review of the literature, the Working Group concluded that the existing body of research provides no definitive answers concerning the optimal intervention approaches or settings for obesity prevention. There is a substantial gap between the call for multi-level interventions by such groups as the Institute of Medicine (1) and evidence to guide what are believed to be the most promising interventions. The Working Group recommended more research that included multi-level and multi-component interventions, recognizing the additional challenges presented by such studies. In particular, the role of parents and other family members, as well as parental lifestyle factors and their effects on child body weight, deserves more study and should be incorporated into interventions to change children’s behaviors. It was apparent that school-based interventions must provide students with a larger intervention dose than interventions currently deliver. This could be accomplished through combining school-level interventions with interventions delivered in other settings. Such strategies could link schools with families, community organizations and health care providers to change the physical activity and food environments fostering a “behavior-environmental” synergy. The Working Group recommended that more research should be targeted at the environmental levels and that policy changes at multiple levels be studied carefully as facilitators of change. Multi-level and multi-component interventions should be accompanied by process evaluation and cost-effectiveness analyses, and aim to evaluate the effects of the intervention components separately and in combination.

• Design Issues in Childhood Obesity Prevention

The Working Group made the following suggestions to provide the information needed to increase intervention potency and improve scientific rigor in childhood obesity prevention studies (24): 1) Investigators should describe the intervention as it was actually delivered, including midstream changes and fidelity measures. Adaptive intervention designs are needed that include a priori plans for modifying the intervention based on interim evaluations. Also needed are statistical methods that are appropriate for this approach; 2) For group randomized designs (the unit of assignment and analysis is the group), investigators must use appropriate analyses and account for intraclass correlations in their sample size calculations. In a review of the literature on 59 group randomized designs, 54% used appropriate analyses, 25% a mixture (unit of analysis was both the group and individual) and 20% used inappropriate analyses (individual was used as the unit of analysis in a group randomized design) (41, 42); 3) Investigators should carefully consider their outcome measures.

Percent body fat derived from an appropriate prediction equation may be a better outcome measure than BMI, especially if changes in activity are specific targets of the intervention. Whenever possible, investigators should use objective measures rather than self reported measures. When self-reported measures must be used, they should be prominently identified as such and the potential for differential bias between the control and intervention groups addressed; and 4) Investigators should consider conducting “evidentiary studies” (24), before undertaking a large randomized trial. Evidentiary studies break down a planned randomized trial into pieces and test selected components in a design that is adequately powered. The outcome of an evidentiary study is never the same as that planned for the larger randomized trial and is usually more modest and easily changed than the primary outcome of the larger trial. For example, prior to conducting a multi-component school-based randomized trial aimed at changing student’s percent body fat through an intervention that includes, as one component, increased physical activity in physical education (PE) classes, an evidentiary study might assess activity in PE using direct observation or accelerometry following implementation of that component of the intervention. A social marketing component planned as part of the same randomized trial might assess impact on targeted attitudes using a questionnaire. Evidentiary studies are larger and more fully powered than pilot or feasibility studies, and often assess mediating and process variables. The Working Group recommended that evidentiary studies be conducted of natural experiments and quasi experimental designs be used to generate hypotheses in addition to randomized controlled trials. Studies could be in two phases: phase 1 evidentiary studies followed by larger-scale phase II studies.

• Translational Issues in Pediatric Obesity Prevention Research

Translation research has been categorized into two phases: basic research to clinical science (Translation 1), and clinical science to clinical practice and in community settings (Translation 2) (43). The Working Group appreciated that theory provides the foundation for the design of behavior change programs. Since the basic research in this area has not been highly predictive of behavior, thereby placing limits on what the ensuing interventions might achieve, the Working Group believes basic research must be supported in this area. As new theoretical ideas and models show promise in basic research, interventions based on them can be tested with greater chances for effectiveness. However, at this point in the obesity epidemic, the Working Group believed that for childhood obesity prevention, Translation 2 is the more important of the two.

Translation 2 research studies can examine factors associated with implementation of proven approaches, and can test various approaches to improving implementation of proven interventions in practice. Although substantially more research is needed in this area, successful translation of research findings into practice would seem to entail researchers addressing barriers to dissemination and implementation in their intervention designs. In addition, when designing multilevel intervention programs, researchers could use systems and socio-ecological models that attend to the “connectedness” and integration across program components and levels (43, 44). The Working Group called for research that identifies successful strategies that can be used to translate research into action in a diverse array of individuals and settings and via a multitude of channels. Researchers were encouraged not to consider only the use of very low-cost strategies for translation when those strategies are unlikely to be successful. Rather creative strategies should be devised, tested and evaluated for their cost-effectiveness. Obesity prevention research should draw from research advances in other disciplines (e.g., basic sciences, behavioral or environmental) to more appropriately test potential novel interventions and speed effective interventions into clinical practice and public health use.

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Summary of Childhood Obesity Treatment Panel Meeting

• Identification and Treatment of Pediatric Obesity

The Working Group discussed the Expert Committee Recommendations on the Assessment, Prevention and Treatment of Child and Adolescent Overweight and Obesity (45). Expert Committee recommended a new classification to replace the definitions for overweight and “at risk of overweight:” Children, ages 2 to 18 years, with a BMI ≥ 95th percentile for age and sex should be considered obese. Children with BMI ≥ 85th percentile but < 95th percentile for age and sex should be considered overweight. This replaces “at risk of overweight.” The use of the 99th percentile of BMI for age cut-offs was recommended (for severely obese) to allow for improved accessibility of the data in the clinical setting and for additional study (45).

The Working Group reviewed the literature on childhood obesity treatment research and noted there is a paucity of research on treatment as well as numerous methodological limitations of studies that do exist, including small samples sizes that are often convenience samples and therefore not representative, wide ranges of age groups with no stratification by age or risk, and short intervention and follow-up periods (usually less than 12 months). The prevalence of multiple risk factors increases as the BMI percentile increases, and severe obesity is associated with increased risk of co-morbidities and resistance to sustained weight loss (46). However, it remains unknown why some pediatric patients with obesity are at higher risk of certain complications compared to others.

• Overview of Pediatric Obesity Treatment Research

Treatment of obesity in children and adolescents has many similarities to treatment in adults, including available modes of treatment (i.e., behavioral, pharmacologic and/or surgical). However, children differ biologically, behaviorally and socially from adults as well as from stage of growth and biological and developmental age. Weight maintenance (until BMI is < 85 th percentile) with behavioral treatment is recommended for overweight and obese children, ages 2 or more years who have no health complications (e.g., hypertension or dyslipidemia), and weight loss is recommended for those with health complications (45). Differences in the treatment of obesity in youth compared to adults pertain to special circumstances in children’s physiology (e.g., growth, pubertal development, fat distribution, comorbidities, side effects from medications), psychosocial factors (e.g., cognitive development, motivating factors, body image, short-term attention span, risk-taking behaviors, lack of concern about health), and environmental influences (e.g., family control, schools, food environment, changing peer groups, effects of advertising, availability of sedentary opportunities). The mainstay of obesity treatment in children and adolescents is to change behaviors related to energy balance. Behavior change in this group is generally safe and, when effective, is generally sustained longer than in adults (47, 48). Pediatric obesity treatment research can also be informed by successful prevention research.

The Expert Committee’s recommendations include a staged approach to treatment and weight maintenance or weight loss goals (45). Stage 1 – “Prevention Plus” includes family visits with physician or health professional and lifestyle/behavioral treatment; Stage 2 - Structured Weight Management: stage 1 recommendations plus more structure and support including individual or group follow-up visits with a dietitian and exercise therapist that include self-monitoring, goal setting and rewards, and monthly individualized treatment. Stage 3- Comprehensive and multidisciplinary approach that includes increased intensity and frequency of stage 2 approaches; structured behavioral program with diet and physical activity goals; and weekly group sessions for 8-12 weeks plus follow-up. Stage 4 - Tertiary care intervention for severely obese youth includes use of medications (e.g., sibutramine, orlistat), very-low-calorie diets and/or surgical approaches in combination with behavioral treatment (45). However, within this framework, there is still a substantial number of research questions that must be addressed.

The Working Group noted that more information is needed on best approaches for behavioral treatment in obese children and adolescents. For example, what is the best intervention content and how should it vary by age? How should family members be involved and should the focus of the intervention be on the child alone, parent alone, or entire family? What predicts the likelihood of success of treatment? How should treatment programs be designed? Who are the optimum team members?

A second option for childhood obesity treatment is the use of pharmacologic agents. However, there are only two drugs approved by FDA specifically for obese adolescents, and their long-term safety is unknown: orlistat (approved for age 12 and older) and sibutramine (approved for age 16 and older). Orlistat inhibits fat absorption and is associated with gastrointestinal side effects including steatorrhea, bloating, cramping, and fecal incontinence. Sibutramine is a monoamine reuptake inhibitor that enhances adrenergic serotonergic and dopaminergic signaling in the brain and suppresses appetite. Side effects include increases in blood pressure and heart rate. A third option for treatment of pediatric obesity is bariatric surgery. Two surgical procedures are being offered: Gastric bypass with Roux-En-Y anastomosis and adjustable gastric banding.

The Working Group concluded that much more information is needed to address obesity treatment in children and adolescents.

• Settings for Pediatric Obesity Treatment and Research

The Working Group noted that the recommendations of the Expert Committee have implications for treatment in various settings. In a primary care setting, the goals include BMI screening and early identification of overweight and mildly obese youth, support of clinical practice changes to enhance identification and timely treatment of overweight children, and stage 1 “prevention plus” interventions and follow-up that emphasize small specific lifestyle changes. In school and community settings, the goals should be early screening to identify children who are mildly-to- moderately obese followed by stage 2 “structured weight management” interventions that are comprehensive, of longer duration, and linked with a health-care practitioner and team. In referral centers, stage 3 “comprehensive, multidisciplinary team of interventionists” and stage 4 “tertiary care intervention” should be the goal for moderate to severe obesity, especially when comorbid conditions are present.

The Working Group noted that although there are recommendations for treatment, they are based on insufficient scientific data. They recommended randomized controlled treatment trials testing efficacy and effectiveness of tailored intervention approaches with attention paid to participant characteristics (e.g., severity of weight status, age, presence of risk factors), sufficient intervention intensity and duration, and including formative and process evaluations. The Working Group emphasized the need for studies that have adequate power and that stratify participants based on weight status; include diet and physical activity interventions that are tailored to severity of obesity status, risk factors, and phenotypes (e.g., hypertensives); and include parent-centered interventions, particularly for younger patients. The Working Group noted that there is a paucity of research on how to implement pediatric obesity treatment in the primary care setting, and concluded that research is needed to develop a model of care for treatment of childhood obesity in the primary care setting, analogous to the chronic care model for treatment of chronic diseases in adults (49).

The Working Group discussed reviews of the literature on skills of health professionals for treating pediatric obesity. Training is needed of health care providers in behavior change as an integral part of the model of care for obesity treatment. In a study by O’Brien et al. (50), in a large, primary care practice (urban, minority, 90% Medicaid), pediatric residents, nurse practitioners and faculty physicians documented obese status in only 53% of obese patients and only 15% were counseled to increase physical activity (50). A Cochrane review (51) of interventions for treating childhood obesity concluded that “there is a limited amount of quality data on the components of programs to treat childhood obesity that favor one program over another. Further research that considers psychosocial determinants of behavior change, strategies to improve clinician-family interaction, and cost-effective programs for primary and community care is required.”

• Behavioral and Lifestyle Interventions to Treat Obese Children

The Working Group discussed family-based studies and noted that parent’s weight loss predicted child’s weight loss in a family-based behavioral weight control study (52-54). Treating parents alone was associated with a reduction in percent of overweight children [-9.5% (0.4 BMI Z score; P=0.003) in the parents-only group vs. -2.4% (0.1 BMI Z score) in the parents–children group] (53). However, few studies have reported on family relationships or family outcome measures (54). Self-monitoring of target behaviors was positively associated with weight loss (average of 30 kg for an average of 5.5 years) in adults (55). Such studies in children are limited. The Working Group called for research to identify strategies to enhance self-monitoring practices and determine their association with successful weight management in children and adolescents.

The Working Group made three research recommendations for behavioral and lifestyle interventions to treat obese children: 1) identify family dynamics which predict success of certain interventions and changes in family dynamics and relationships that are associated with favorable treatment outcomes; 2) identify utility of and methods for promoting self-monitoring of target behaviors by parents and children; and 3) investigate strategies to effectively recruit families into family-based interventions.

• Pharmacologic Treatment of Childhood Obesity

The Working Group reviewed studies that used orlistat in treating obese adolescents and noted that in general there were small but significant reductions in BMI after one year but no significant differences in blood glucose, insulin, or lipids compared to controls on placebo. In one randomized controlled trial, orlistat was found to reduce BMI by 5% in 26% of children who took the drug compared to 15% of those on placebo (56). Gastrointestinal tract adverse events were more common in the orlistat than placebo group (56, 57).

The Working Group reviewed the trials using sibutramine. Two 6-month and one 1-year controlled studies of sibutramine found significant weight loss (e.g., 7.2 kg vs. 3.2 kg), and improvements in insulin, HDL, and triglycerides compared with placebo (58). However, adverse effects on blood pressure and pulse rate were noted (58-60) and long-term cardiovascular effects of sibutramine are unknown.

The Working Group discussed many issues related to studies of pharmacologic agents to treat pediatric obesity. Important unanswered questions include the following: Which patients (e.g., age, BMI level, presence of comorbidities) are the best candidates for pharmacologic intervention? Should pharmacologic studies be limited to adolescents? What behavioral interventions work best in conjunction with pharmacologic treatment? What is the appropriate comparison (e.g., placebo, behavioral intervention, bariatric surgery, other drugs)? What is the appropriate duration of treatment to best assess efficacy and safety? What constitutes sufficient evidence to recommend pharmacologic therapy in clinical practice? What information do third party payors need to determine what treatments to cover for pediatric obesity?

The Working Group noted that greater prevention and treatment efforts are needed for severely obese youth (approximately 4% of children and adolescents currently). Longer-term studies of severely obese adolescents combining pharmacotherapy and lifestyle modification are also needed. Treatment of severely obese youth is unlikely to be successfully implemented in the primary care setting alone and would require interventions in multiple-settings.

• Surgery and Devices to Treat Severely Obese Adolescents

About 5% of U.S. adults (>14 million) and 4% of children and adolescents (>2 million) are severely obese (BMI ≥ 40 for adults and ≥ 99th percentile for children). Severe obesity in children is associated with comorbidities for cardiovascular diseases (e.g., hypertension, hyperinsulinemia, Type 2 diabetes). Bariatric surgery is increasingly being used in both adults and children. From 1996 to 2002, U.S. population-adjusted rates of bariatric surgery in youth (<20 years old) increased from 0.23 per 100,000 to 73 per 100,000 (61). A report on bariatric surgery in adolescents identified retrospective studies suggesting that both gastric bypass and gastric banding led to sustained and clinically significant weight loss compared to non-surgical approaches in adolescents (62). However the cost of bariatric procedures was high, ranging from $8,650 to $25,000 per surgical treatment. A limited number of studies (62-64) have found improvement in depressive symptoms, quality of life, type 2 diabetes, cardiovascular risk factors, and obstructive sleep apnea with bariatric surgery. Adverse events and complications from bariatric surgery are lower in adolescents compared to adults, but the long-term effects are unknown. Weight regain is also known to occur in some patients post surgery.

The Working Group concluded that there are many unanswered questions regarding the efficacy of bariatric surgery in adolescents. Should patients be selected for surgery based on age, BMI, comorbidities, psychological and/or quality of life issues? Are there unique benefits or risks of surgical weight loss procedures in adolescents compared to adults? Is there any effect of weight loss procedures on linear growth and bone health? What are the long-term psychosocial issues? Is there a way to predict which procedures are of greatest benefit and lowest risk for various types of patients? What are the predictors of success or failure and how efficacious are combination approaches (e.g., surgical treatment with pharmacotherapy; or surgical treatment with environmental and behavioral interventions)? Does the mechanism of weight loss differ from mechanisms of comorbidity resolution? How will decisions regarding insurance coverage be determined?

• Translational Issues in Pediatric Obesity Treatment Research

The Working Group discussed issues related to the translation of childhood obesity treatment research and concluded that research in pediatric obesity treatment has been slow and has not provided adequate information for practitioners. The Cochrane Effective Practice and Organization of Care (EPOC) Group reviewed 18 studies and noted: “the heterogeneity and generally limited quality of identified studies make it difficult to provide recommendations for improving health professionals’ obesity management. At present, there are few solid leads about improving obesity management, although reminder systems, brief training interventions, shared care, inpatient care and dietician-led treatments may all be worth further investigation. Further research is needed to identify cost-effective strategies for improving the management of obesity (64).”

The Working Group recommended the following research that would be relevant to translation into practice: 1) clinical studies to develop and evaluate effective strategies for getting pediatric care providers to calculate, plot and track adiposity indicators (e.g., BMI percentile, waist circumference), and to initiate discussions regarding treatment for overweight children and their families; 2) development and evaluation of effective strategies for dissemination and implementation of evidence-based overweight treatment guidelines into pediatric care practices; 3) development and evaluation of effective counseling strategies for use by pediatric care providers when implementing treatment recommendations for overweight children and their families; 4) identification and evaluation of resources, services and care strategies that are effective as adjuncts to healthy lifestyle counseling and medical/surgical therapy within pediatric care settings for overweight children and their families, and 5) support of basic science research to evaluate the mechanisms of the development of obesity and its comorbidities that can serve as targets for new interventions. These targets, should they be studied to evaluate their effectiveness, may help develop new pharmacologic and surgical approaches to obesity treatment.

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Cross-cutting Issues

• Low Socioeconomic Status and Minority Issues

The Working Group discussed the childhood obesity problem as it relates to socio-economic status (SES) and race/ethnicity. As previously noted, there is excess risk of obesity among children in ethnic minority populations, and some of this excess may relate to ethnic group differences in socioeconomic status (65). The relationship of SES and obesity in children and adolescents may not be consistent by age and gender or over time (66). For example, the prevalence of obesity may be higher in African American and Mexican American adolescents in middle to high income families than among those in lower income families, at least among girls, whereas the more typical inverse gradient (less obesity among higher income families) may be observed in white children (66).

The Working Group noted that there are many unanswered questions regarding how race/ethnicity and SES predispose children to becoming obese (67). For example, what food-intake behaviors or child feeding practices that might contribute to excess weight gain are specific to or more prevalent in these population groups? What is the relative importance of cultural attitudes and beliefs regarding obesity and its effects versus the physical, social, economic, and policy environments of children and their families? Why is time spent watching television so much higher among African American and Hispanic children than among whites? Other issues, not specific to minority children but possibly different or of greater relative importance include parental attitudes about eating, physical activity, and weight control and family environments for eating and physical activity as well as how the fear of crime affect children’s access to physical activity resources and healthy foods. Consideration should also be given to psychosocial factors and their role in obesity and development of cardiovascular diseases. Additional variables possibly associated with excess risks in minority and low income groups include adult role models, the socio-political contexts in which ethnic minority and low-SES families live and work, food and economic insecurity, discretionary income as a proportion of total income, coping styles, access to physical activity resources and to healthy foods, costs of healthy versus unhealthy food choices, level of resources available to schools, and media, technology (65, 67) and neighborhood environments (e.g., crime and fear of crime).

The Working Group recommended research to inform population-based approaches for the prevention of childhood obesity in high-risk populations—research targeted specifically to these populations, in addition to research applicable to ethnically and socio-economically diverse populations. Research on intensive, individually tailored “high-risk” strategies for obesity prevention, which may be analogous to the types of approaches used for obesity treatment, should also be emphasized in the populations most disproportionately affected (African Americans, Hispanics, Native American Indians, Asian/Pacific Islanders, rural and low-income children in general). However, individually-oriented approaches without companion approaches at the environmental or community level may not be effective and could be counterproductive (65). Research issues of particular interest include effective strategies for community engagement and community-based participatory research, how to incorporate more ethnographic or other types of qualitative research to better understand factors that might facilitate or hinder obesity prevention in high-risk populations, and how to expand the paradigms used to develop obesity research so that intervention approaches take into account population-specific historical legacy, core values, and family and community life issues (68).

The Working Group recommended various methods to increase recruitment of more minorities into research studies including community engagement in study design and implementation, fostering trust and being careful not to overwhelm enrollees, providing solutions to barriers to participation (e.g., by providing transportation, child care and parking vouchers), creating communities within the study population, and more community-based participation in research with bi-directional partnerships between researchers and communities. The Working Group suggested that interventions be initiated in preschool through high school, targeting parents, especially obese mothers, as well as children’s diet and physical activity behaviors, and that considerations be given to recruitment-related cultural and economic factors as well as social networks associated with food and physical activity among ethnic/racial groups at risk for obesity.

• Gene-environment interactions

The Working Group discussed interactions between environmental and genetic factors that lead to phenotypic expressions of obesity, and noted that genetic variants associated with childhood obesity, and type 2 diabetes as well as family association studies have been reported in the literature (69,70). It is anticipated that better understanding of the genetic and physiologic contributions of obesity will be forthcoming. The Working Group noted that some patients do better with certain interventions than others. Genetic markers of obesity susceptibility may be used to target individuals for a specific intervention or treatment. Conducting genome-wide association studies with childhood obesity could identify genetic factors and mechanisms, and pharmacogenomics could provide a basis for future personalized medicine approaches. The Working Group suggested that future research in childhood obesity collect DNA samples to examine genetic variants and their associations with obesity and risk for comorbidities.

• Methodological Issues in Pediatric Obesity Prevention and Treatment

Research from the field of engineering has demonstrated that study designs, when appropriately implemented, can isolate effects of individual program components and help fine-tune interventions with an efficient use of samples of subjects (71). Innovative research designs such as the Sequential Multiple Assignment Randomized Trial (SMART) have been instrumental in helping to develop “adaptive interventions” that are optimally tailored to individuals and individual progress over time (71-74). The Working Group discussed various methodological approaches and analyses to making interventions more potent. These include using missing data to make causal inferences, modeling of phenomena that have complex patterns of change over time and relating them to other phenomena, modeling complex growth patterns in intensive longitudinal data (e.g., data collected via PDAs, actigraphs) (72, 73), combining expensive biological/instrument-gathered observations with cheaper self-reports for improved validity while conserving resources, addressing key research hypotheses by obtaining the more expensive measures on a small subset of study participants, using reliable and valid measurements and multilevel analysis, employing integrating latent variable models and multilevel models, and using partial factorial designs (74-76).

The Working Group noted that appropriate research designs are needed to build innovative and potent interventions. They recommended interdisciplinary methodological perspectives (e.g., statistics, biostatistics, psychometrics, education, economics, and qualitative method) be included in research and collaboration between methodologists and prevention/treatment scientists to conduct methodological research within the context of childhood obesity prevention and treatment research.

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Enhanced Understanding of the Influences on Children’s Diet, Physical Activity and 0besity

  • Conduct observational and experimental research to test new ideas and develop new models of factors influencing children’s diet, physical activity and obesity, including environmental, social (family and peer), psychological, biological, and genetic factors. Studies integrating behavioral with biological and genetic factors are particularly needed in light of many recent advances in genetic and biological science in this area.
  • Identify specific modifiable factors in children’s built environment that can make a justifiable difference in children’s ability to be more active.
  • Identify environmental and policy determinants of obesity and health behaviors (characteristics of neighborhood, schools, child-care centers, playgrounds; effects of fast food, fresh food markets, TV and other electronic media, and food marketing), as well as factors related to maintenance of a healthy weight over time.
  • Identify critical periods for obesity development (e.g., factors associated with excess weight gain throughout childhood; CVD risk evaluation in the transition from childhood obesity to adult CVD in existing cohort studies).
  • Increase use of prospective and quasi-experimental designs to improve causal inference for environmental and societal variables.

Obesity Prevention Interventions in Young Children

  • Test studies of family-based interventions (e.g., studies intervening on parenting style, and on home availability of healthful food and opportunities for physical activity).
  • Test interventions with physicians and other healthcare providers combined with community involvement (e.g., train physicians to screen, nurses to be coaches and healthcare settings to refer to community resources).
  • Test long-term effects of obesity prevention interventions on weight and cardiovascular risk factors.
  • Test effects of having single and multiple behavioral targets (e.g., intervening on a targeted food (e.g., fructose) vs. multiple foods; dietary interventions with and without modifications in physical activity and sedentary behaviors).
  • Conduct studies that consider critical developmental periods of weight gain.
  • Test interventions that use novel theories beyond the models that dominated the literature in the past 20 years.
  • Conduct interventions in a variety of settings (e.g., home, child-care, WIC, health-care settings).

Multi-level Multi-Component Interventions (any age)

  • Examine multi-level and multi-component community-based interventions in multiple settings (e.g., schools, healthcare, home, community, built environment, public policy, social marketing; diet, physical activity behaviors).
  • Test a multi-level comprehensive intervention targeting minority population and low-income populations (e.g., culturally appropriate ways to reach Latino, African American, Native American and Asian/Pacific Islander children).
  • Test interventions that use technology (e.g., internet, media, novel electronic approaches) to influence behavior change.
  • Develop and test interventions that can be effectively incorporated into existing school and community infrastructures (e.g., curriculum, physical activity, lunch modification) to maximize effectiveness and minimize cost.
  • Conduct intervention studies that address issues related to the interface between individual behaviors and the environment.

Implementation, Dissemination, Translation, Evaluation

  • Identify and test approaches for community partnerships in dissemination and implementation of evidence-based obesity prevention programs.
  • Evaluate the effectiveness of existing promising programs (e.g., NIH Ways to Enhance Children’s Activity and Nutrition (We CAN ))..
  • Identify and test food marketing strategies.

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Behavioral Approaches to Obesity Treatment in Children (includes severely obese)

  • Identify and test components of behavioral approaches for weight loss in obese children (e.g., self-monitoring, goal setting; individual vs. group sessions; technology including video games, telemedicine; parent, child, and/or family as intervention targets).
  • Identify and test components of behavioral approaches for weight control or maintenance (not weight loss) in obese children.
  • Identify and test diet and physical activity programs (e.g., dietary and physical activity patterns, single dietary components such as fructose).
  • Identify and test psychosocial influences on behavioral changes in obese children.

Pharmacologic and Surgical Treatment of Severe Obesity in Children

  • Compare pharmacological agents, including off-label uses, or compare surgical procedures versus pharmacologic agents for weight loss with and without behavioral approaches.
  • Test effects of different surgical procedures for weight loss in combination with behavioral approaches and evaluate safety parameters (e.g., psychosocial factors, height, and bone density).
  • Test a stepped approach to obesity treatment (Expert Committee Recommendations).
  • Identify biologic mechanisms of severe obesity to develop better therapeutic targets (pharmacologic or surgical).
  • Identify and test interventions in various settings for obesity treatment (e.g., primary care and community linkages).
  • Identify psychosocial aspects of obesity among the most obese children in relation to pharmacologic and surgical treatments.

Health Systems and Primary Care Practices

  • Identify and test models for delivering obesity care.
  • Test approaches to changing behaviors of health practitioners.
  • Identify and test approaches to translate and/or disseminate evidenced-based therapies to primary care practices.
  • Support research on macro-environment influences on healthcare delivery, e.g., health policy, business models for practice, insurance coverage.
  • Evaluate cost-effectiveness of primary care interventions.

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  • Support methodological research on study designs and analytic approaches (identify optimal study designs and analytic approaches for various types of research questions, e.g., surgical and/or pharmacologic treatments, multi-component and multi-level influences and interventions).
  • Use appropriate study designs and methods including natural experiments, quasi-experimental designs and randomized designs; develop time-sensitive funding mechanisms for natural experiments.
  • Standardize use of outcome measures to improve comparability of studies.

High-Risk Populations

  • Study a diversity of high-risk subgroups including low-income families, ethnically and socio-economically diverse populations, males and children in rural communities as well as immigrants.
  • Examine differences in treatment approaches or effects by age, race/ethnicity, and socioeconomic status.
  • Conduct environmental and policy intervention research to improve access to healthy foods and opportunity for physical activity in low-income communities.

Other Recommendations

  • Identify biologic and behavioral mechanisms of obesity development, including gene-environment interactions.
  • Support long-term studies (~10 years) studies as well as short-term “evidentiary” studies with intermediate outcomes.
  • Support studies to improve technological approaches to prevent and treat obesity (e.g., bioengineering approaches, internet, video, and electronic medical records).
  • Support translational research (Basic research ↔ clinical science research ↔ clinical practice ↔ community/dissemination research).
  • Measure cost-effectiveness of interventions.
  • Consider using networks, consortia, Specialized Centers of Excellence, partnerships with Clinical Translational Science Award (CTSA) or Academic Research Centers.

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  1. Obesity Prevention Interventions in Young Children: Test family-based interventions to prevent excess weight gain in young children, including high-risk populations such as minorities, children in low-income families, children in rural communities, using multi-component and multi-level approaches (e.g., home and school; community-school; home-community).
  2. Treatment interventions in obese children (includes severely obese): Test weight loss interventions that use behavioral approaches (e.g., self-monitoring, goal setting; social support, stimulus control, cognitive restructuring) with or without pharmacotherapy or surgical approaches, and include multi-component multi-level approaches (e.g., healthcare practice and home, healthcare practice and community, health care practice and school).
  3. Health Systems and Primary Care Practices: Test models for delivering obesity prevention and treatment to change behaviors of health practitioners and to translate and/or disseminate evidenced-based therapies to primary care practices.
  4. Implementation, Dissemination, Translation, Evaluation: Evaluate the effectiveness of existing promising programs (e.g., NIH Ways to Enhance Children’s Activity and Nutrition (WE CAN)).
  5. Methodology: Support methodological research on study designs and analytic approaches (identify optimal study designs and analytic approaches for various types of research questions, e.g., surgical and/or pharmacologic treatments, multi-component and multi-level influences and interventions).

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  1. Institute of Medicine. Preventing Childhood Obesity, Washington, D.C: National Academy Press, 2005.
  2. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999-2004. JAMA 2006; 295, (13): 1549-1555.
  3. Caballero B, Clay T, Davis SM, Ethelbah B, Rock BH, Lohman T, Norman J, Story M, Stone EJ, Stephenson L, Stevens J; Pathways Study Research Group. Pathways: a school-based, randomized controlled trial for the prevention of obesity in American Indian schoolchildren. American Journal of Clinical Nutrition, 2003 Nov;78(5):1030-8.
  4. Robert Wood Johnson Foundation. Childhood Obesity, 2007.
  5. Daniels SR, Arnett DK, Eckel RH, Gidding SS, Hayman LL, Kumanyika S, Robinson TN, Scott BJ, St Jeor S, Williams CL. Overweight in children and adolescents: pathophysiology, consequences, prevention, and treatment. Circulation, 2005, 111 (15), 1999-2012.
  6. Din-Dzietham R, Liu Y, Bielo MV, Shamsa F. High blood pressure trends in children and adolescents in national surveys 1963-2002. Circulation, 2007, 116:1488-1496.
  7. Lorch SM, Sharkey A. Myocardial velocity, strain, and strain rate abnormalities in healthy obese children. J Cardiometabolic Syndrome, 2007, 2(1):30-34.
  8. Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH. Predicting obesity in young adulthood from childhood and parental obesity. N Engl J Med. 1997, 25;337(13):869-73.
  9. Finkelstein EA, Fiebelkorn IC, and Wang G. National medical spending attributable to overweight and obesity: How much, and who’s paying? Health Affairs (Millwood) Suppl. Web Exclusive (2003): W3-219-26.
  10. Finkelstein EA, Fiebelkorn IC, and Wang G. State-level estimates of annual medical expenditures attributable to obesity. Obesity Research, 2004,12;18-24.
  11. Wang G, Dietz WH. Economic Burden of Obesity in Youth Aged 7 to 17 years, 1979-1999, Pediatrics, 2002, 109, 5: E81.
  12. Woolford SJ, Gebremarian A, Clark SJ, Davis MM. Incremental hospital charges associated with obesity as a secondary diagnosis in children. Obesity 2007, 15 (7): 1895-901.
  13. Schonfeld-Warden N, Warden CH. Pediatric obesity: An overview of etiology and treatment. Pediatr Clin North Am. 1997, 44(2):339-61.
  14. Katz DL, O’Connell M, Yeh M, Nawaz H, Njike V, Anderson LM, Cory S, Dietz W. Public Health Strategies for Preventing and Controlling Overweight and Obesity in School and Worksite Settings: A Report on Recommendations of the Task Force on Community Preventive Services. MMWR, October 7, 2005 / 54(RR10);1-12.
  15. Summerbell CD, Waters E, Edmunds LD, Kelly S, Brown T, Campbell KJ. Interventions for preventing obesity in children Cochran Database of Systematic Reviews, Issue 3 Art. No.: CD001871. DOI: 10.1002/14651858. CD001871.pub2, 2007.
  16. Flynn MAT, McNeil DA, Maloff B, Wu M, Ford, C Tough SC. Reducing obesity and related chronic disease risk in children and youth: a synthesis of evidence with ‘best practice’ recommendations. Obesity Reviews, 2006; 7(Suppl. 1), 7-66.
  17. Bluford DAA, Sherry B, Scanlon KS. Interventions to prevent or treat obesity in preschool children: A review of evaluated programs. Obesity, 2007; 15(6):1356-1372.
  18. Stice E, Shaw H, Mati N. A meta-analytic review of obesity prevention programs for children and adolescents: The skinny on intervention that work. Pscyhological Bulletin, 2006, 132(5):667-691.
  19. Doak CM, Visscher RLS, Renders CM et al. The prevention of overweight and obesity in children and adolescents: A review of interventions and programs. Obesity Reviews, 2006, 7, 111-136.
  20. Robinson TN. Reducing children’s television, viewing to prevent obesity: A randomized controlled trial. JAMA 1999; 282 (16): 1561-1567.
  21. Flores R. Dance for Health. Public Health Reports, 1995;110 (2):189-193.
  22. Gortmaker SL, Peterson K, Wiecha J, Soal Am, Dixit S, Fox MK, et al. Reducing obesity via a school-based interdisciplinary intervention among youth. Archives of Pediatrics and Adolescent Medicine, 1999; 153(4):409-418.
  23. Mueller MJ, I Asbeck, Mast M, Langnase K, Grund A. Prevention of obesity—more than an intention. Concept and first results of the Kiel Obesity Prevention Study (KOPS). International Journal of Obesity, 2001, 25, Suppl 1, S66-S74.
  24. Stevens J, Taber DR, Murray DM, Ward DS. Advances and controversies in the design of obesity prevention trials. Obesity, 2007, 15(9):2163-70.
  25. Prochaska JO, Velicer WF. The Transtheoretical Model of Health Behavior Change. Am J Health Promotion, 1997, (1):38-48.
  26. Becker MH. The Health Belief Model and Personal Health Behavior. Health Education Monographs, 1974, 2 (4): 324-473.
  27. Bandura A. Social foundations of thought and action: Social Cognitive Theory. Englewood Place, NJ, Prentice- Hall, 1986.
  28. Rosentock IM, Strecher VJ, Becker MH. Social Learning Theory and the Health Belief Model. Health Education Quarterly, 15 (2) 173-183.
  29. Glanz K, Rimer BK, Lewis FM. Ed. Health Behavior and Health Education: Theory, Research and Practice. San Francisco, CA, Jossey-Bass, 2002, 573pp.
  30. Resnicow K, Vaughan R. A chaotic view of behavior change: a quantum leap for health promotion. International Journal of Behavioral Nutrition and Physical Activity, 2006,12;3:25-30.
  31. Baranowski T. Crisis and chaos in behavioral nutrition and physical activity. International Journal of Behavioral Nutrition and Physical Activity, 2006, 14; 3:27.
  32. Baranowski T, Cullen KW, Nicklas T, Thompson D, Baranowski J. Are current health behavioral change models helpful in guiding prevention of weight gain efforts? Obesity Research, 2003, 11 Suppl: 23S-43S.
  33. Baranowski T, Lin L, Wetter DW, Resnicow K, Davis M. Theory as mediating variables: Why aren't community interventions working as desired? Annals of Epidemiology 1997; 7(S7):89-95.
  34. Saelens BE, Sallis JF, Nader PR, Broyles SL, Berry CC, Taras HL. Home environmental influences on children's television watching from early to middle childhood. J Dev Behav Pediatr. 2002, 23(3):127-32.
  35. Sallis JF, McKenzie TL, Conway TL, Elder JP, Prochaska JJ, Brown M, Zive MM, Marshall SJ, Alcaraz JE. Environmental interventions for eating and physical activity: A randomized controlled trial in middle schools. American Journal of Preventive Medicine, 2003, 24 (3), 209-217.
  36. Kligerman M, Sallis JF, Ryan S, Frank LD, Nader PR. Association of neighborhood design and recreation environment variables with physical activity and body mass index in adolescents. Am J Health Promotion, 2007, 21(4):274-7.
  37. Kerr J, Rosenberg D, Sallis JF, Saelens BE, Frank LD, Conway TL. Active commuting to school: Associations with environment and parental concerns. Med Sci Sports Exerc. 2006, 38(4):787-94.
  38. Cooper AR, Andersen LB, Wedderkopp N, Page AS, Froberg K. Physical activity levels of children who walk, cycle, or are driven to school. Am J Prev Med. 2005, 29(3):179-84
  39. Frank L, Kerr J, Chapman J, Sallis J. Urban form relationships with walk trip frequency and distance among youth. Frank L. Am J Health Promot. 2007, 21(4 Suppl):305-11.
  40. Jago R, Baranowski T, Baranowski JC, Cullen KW, Thompson D. Distance to food stores & adolescent male fruit and vegetable consumption: mediation effects. International Journal of Behavioral Nutrition and Physical Activity, 2007,13;4:35.
  41. Murray DM, Varnell SP, Blitstein JL. Design and analysis of group-randomized trials: a review of recent methodological developments. Am J Public Health, 2004, 94(3):423-32.
  42. Varnell SP, Murray DM, Janega JB, Blitstein JL. Design and analysis of group-randomized trials: a review of recent practices. Am J Public Health, 2004, 94(3):393-9.
  43. Sung NS, Crowly WF, Salber P, Sandy L, Sherwood LM et al. Central challenges facing the national clinical research enterprise. JAMA 2003, 289 (10), 1278-1287.
  44. Glasgow RE, Emmons KM. How can we increase translation of research into practice? Types of evidence needed. Annu Rev Public Health, 2007; 28:413-33.
  45. Expert Committee Recommendations on the Assessment, Prevention, and Treatment of Child and Adolescent Overweight and Obesity, January 25, 2007.
  46. Freedman DS, Mei Z, Srinivasan SR, Berenson GS, Dietz WH. Cardiovascular risk factors and excess adiposity among overweight children and adolescents: the Bogalusa Heart Study. Journal of Pediatrics, 2007, 150(1):12-17.
  47. Epstein LH, Valoski A, Wing RR, McCurley J. Ten-year outcomes of behavioral family-based treatment for childhood obesity. Health Psychology, 1994,13(5):373-83
  48. Epstein LH, Valoski AM, Kalarchian MA, McCurley J. Do children lose and maintain weight easier than adults: a comparison of child and parent weight changes from six months to ten years. Obesity Research, 1995, 3(5):411-417.
  49. The Chronic Care Model.
  50. O’Brien H et al., Identification, evaluation and management of obesity in an academic primary care center. Pediatrics 2004; 114:e154-e159.
  51. Summerbell CD, Ashton V,, Campbell KJ, Edmunds L, Kelly S, Waters E. Interventions for treating obesity in children (Review). Cochrane Database of Systematic Reviews, 2003, (3) Art No. CD001872. DOI 1002/1451858. CD001872.
  52. Epstein LH, Paluch RA, Gordy CC, Dorn J. Decreasing sedentary behaviors in treating pediatric obesity. Arch Pediatr Adolesc Med., 2000,154(3):220-6.
  53. Golan M, Kaufmann A, Shahar DR. Childhood obesity treatment: targeting parents exclusively v. parents and children. British Journal of Nutrition, 2006:95, 1008-1015.
  54. Kitzmann KM, Beech BM. Family-based interventions for pediatric obesity: methodological and conceptual challenges from family psychology. J Fam Psychol. 2006, 20(2):175-89.
  55. Wing RR, Hill JO. Successful weight loss maintenance. Annual Review of Nutrition, 2001;21:323-41.
  56. Chanoine JP, Hampl S, Jensen C, et al. Effect of orlistat on weight and body composition in obese adolescents: a randomized controlled trial. JAMA, 2005; 293(23):2873-83.
  57. McDuffie JR, Calis KA, Uwaifo GI, Sebring NG, Fallon EM, Hubbard VS, Yanovski JA. Three-month tolerability of orlistat in adolescents with obesity-related comorbid conditions. Obesity Research, 2002, 10(7):642-50.
  58. Berkowitz RI, Wadden TA, Tershakovec AM, Cronquist JL. Behavior therapy and sibutramine for the treatment of adolescent obesity: a randomized controlled trial. JAMA, 2003, 289(14):1805-12.
  59. Berkowitz RI, Fujioka K, Daniels SR, Hoppin AG, Owen S, Perry AC, Sothern MS, Renz CL, Pirner MA, Walch JK, Jasinsky O, Hewkin AC, Blakesley VA; Sibutramine Adolescent Study Group. Effects of sibutramine treatment in obese adolescents: a randomized trial. Ann Intern Med, 2006,18;145(2):81-90.
  60. Godoy-Matos A, Carraro L, Vieira A, et al. Treatment of obese adolescents with sibutramine: a randomized, double-blind, controlled study. J Clin Endocrinol Metab., 2005; 90(3):1460-5.
  61. Davis MM, Slish K, Chao C, Cabana MD. National Trends in Bariatric Surgery, 1996-2002. Arch Surg., 2006;141:71-74.
  62. Inge TH, Krebs NF, Garcia VF, Skelton JA, Guice KS, Strauss RS et al. Bariatric surgery for severely overweight adolescents: Concerns and recommendations. Pediatrics, 2004, 114 (1), 217-223.
  63. Kalra M, Inge T. Effect of bariatric surgery on obstructive sleep apnoea in adolescents. Paediatr Respir Rev., 2006, 7(4):260-7.
  64. Harvey EL, Glenny AM, Kirk SF, Summerbell CD An updated systematic review of interventions to improve health professionals' management of obesity. Obes Rev. 2002, 3(1):45-55.
  65. Kumanyika S, Grier S. Targeting interventions for ethnic minority and low-income populations. Future of Children, 2006, 16(1):187-207.
  66. Wang Y, Kumanyika S. Descriptive Epidemiology of Obesity in the United States. Chapter 3, in Kumanyika SK, Brownson RC. (Eds.). Handbook of Obesity Prevention. New York: Springer Publishing Co., 2007, pp. 45-71.
  67. Kumanyika SK. Environmental influences on childhood obesity: Ethnic and cultural influences in context. Physiol Behav. 2008 22;94(1):61-70.
  68. Kumanyika SK, Whitt-Glover MC, Gary TL, Prewitt, TE, Odoms-Young AM, Banks-Wallace J, Beech BM, Hughes Halbert C, Karanja N, Lancaster KJ, Samuel-Hodge CD. Expanding the obesity research paradigm to reach African American communities. Preventing Chronic Diseases, 2007; 4(4).
  69. Herbert A, Gerry NP, McQueen MB, Heid IM, Pfeufer A, Illig T, Wichmann HE, Meitinger T, Hunter D, Hu FB, Colditz G, Hinney A, Hebebrand J, Koberwitz K, Zhu X, Cooper R, Ardlie K, Lyon H, Hirschhorn JN, Laird NM, Lenburg ME, Lange C, Christman MF. A common genetic variant is associated with adult and childhood obesity. Science, 2006, 312(5771):279-83.
  70. Loos RJ, Barroso I, O'rahilly S, Wareham NJ. Comment on "A common genetic variant is associated with adult and childhood obesity". Science, 2007, 12;315(5809):187.
  71. Collins LM, Murphy SA, Strecher V. The Multiphase Optimization Strategy (MOST) and the Sequential Multiple Assignment Randomized Trial (SMART): New methods for more potent e-health interventions. American Journal of Preventive Medicine, 2007, 32, S112-S118.
  72. Rivera DE, Pew MD, Collins LM. Using engineering control principles to inform the design of adaptive interventions. Drug and Alcohol Dependence, 2007, 88, S31-S40.
  73. Murphy SA, Lynch KG, McKay JR, Oslin D, TenHave T. Developing adaptive treatment strategies in substance abuse research. Drug and Alcohol Dependence, 2007, 88, S24-S30.
  74. A Collins LM, Murphy SA, Bierman KL. Conceptual framework for adaptive preventive interventions. Prev Sci., 2004, 5(3):185-96.
  75. Li R, Root T L, Shiffman S. A local linear estimation procedure for functional multilevel modeling. In T. A. Walls & J. L. Schafer (Eds.). Models for intensive longitudinal data (pp. 63-83). New York: Oxford University Press, 2006.
  76. Graham JW, Taylor BJ, Olchowski AE, Cumsille PE. Planned missing data designs in psychological research. Psychological Methods, 2006, 11, 323-343.

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