The objective of this technical report is to provide clinicians with evidence-based, actionable information upon which to make assessment and treatment decisions for children and adolescents with obesity. In addition, this report will provide an evidence base to inform clinical practice guidelines for the management and treatment of overweight and obesity in children and adolescents.
To this end, the goal of this report was to identify all relevant studies to answer 2 overarching key questions: (KQ1) “What are clinically based, effective treatments for obesity?” and (KQ2) “What is the risk of comorbidities among children with obesity?” See Appendix 1 for the conceptual framework and a priori key questions.
Obesity is a common concern in pediatric practice. In caring for patients with obesity or patients who may be at risk for developing obesity, clinicians have many unanswered questions. Examples of these questions include: What is the best way to identify excess adiposity, and does the identification of obesity provide opportunities for treatment? If so, what evidence-based interventions for obesity treatment, delivered at least in part by clinicians in office-based settings, are most effective? Among children and adolescents identified as having obesity, does screening for comorbidities result in improved health outcomes?
Many previous studies, most notably the systematic review conducted for the US Preventive Services Task Force (USPSTF), have synthesized research regarding the efficacy of treatment of obesity, particularly in the context of prevention of future comorbidities.1 However, some important gaps remain. First, the USPSTF recommended that obesity treatment should include at least ≥26 hours of face-to-face contact over 2 to 12 months. However, subsequent studies have failed to demonstrate a consistent hours-based dose-response. In addition, feasibility studies have clearly shown how unrealistic it is for primary care or tertiary care providers to deliver this many hours of treatment in real-world, clinical settings.2 Additional information is needed about resources or partnerships that help reach that contact hour goal, the essential components delivered during these contact hours, the period of time over which this is delivered, and information about lower-intensity strategies with some effectiveness.
Second, most treatment decisions are made in the context of choosing between alternative treatments, not effectiveness compared with no treatment, like many current randomized controlled trials (RCTs). The USPSTF had a primary goal of determining which interventions were efficacious, compared with no or minimal treatment. Our goal was to provide greater contextual evidence of the types of interventions that are effective, effectiveness compared with alternative interventions, and promising interventions that do not yet have randomized trials underlying them.
Finally, primary care pediatricians have a great need to understand how to approach recommendations for screening comorbidities in their patients with obesity. Although previous recommendations have supported screening for common comorbidities, such as dyslipidemia and diabetes, there has been conflicting evidence regarding timing and effectiveness of screening. We now have additional data that provide clinicians and researchers with information about comorbidity prevalence and severity by obesity class. The intent is to help the clinician screen for comorbidities when there is a high likelihood of detecting an abnormality and when detection of that abnormality leads to treatment options that can improve child health. Obesity classifications, including a more granular categorization of obesity as classes I through III, might assist us in determining for whom screening would be most useful, rather than viewing screening as a homogeneous approach for anyone whose BMI is ≥95th percentile.
Scope of the Review
This technical report was designed to answer 2 overarching key questions: (KQ1) “What are effective clinic-based treatments for pediatric obesity?” and (KQ2) “What is the risk of comorbidities among children with obesity?” We developed this focus based on the needs of clinicians and the evidence required to inform the future development of clinical practice guidelines. This report will not attempt to quantify the magnitude of the effect of obesity on child or adult outcomes. It will also not attempt to address treatment strategies for comorbidities (eg, hypertension), as other guidelines and reviews are available to guide such treatment.3–6
In this paper, we report the results for KQ1, intervention studies. Results for KQ2, comorbidity studies, are reported separately.7 The 2 components of the review were conducted concurrently, so we present methods for both below.
Rationale for KQ1 (Intervention Studies)
Clinicians are a trusted source of health information for parents, including issues related to nutrition and physical activity, which are key components of obesity prevention and treatment. Clinicians need to know what strategies have high-quality evidence for effectiveness in preventing and treating obesity. Additionally, clinicians need guidance on which treatments are effective for their patient population and how to leverage available resources for treatment efforts.
Rationale for KQ2 (Comorbidity Studies)
Previous recommendations have included assessments of comorbidities, including hypertension, dyslipidemia, glucose, fatty liver disease, and others. It is not clear whether these assessments lead to improved treatment strategies or outcomes. Additionally, it is not clear whether conducting these assessments would result in an adverse patient outcome. We will examine specific conditions that were previously recommended or that would reasonably require screening: dyslipidemia, hypertension, diabetes, fatty liver disease, depression, sleep apnea, and asthma.
We searched Pubmed and CENTRAL (for trials), completing the final search on April 6, 2018. An additional search was conducted to update the review, covering the time period April 7, 2018, through February 15, 2020. We combined the searches for both key questions because of significant overlap and to more efficiently review studies. Because our focus was on interventions that are relevant to primary care, we did not search other discipline-specific databases, such as ERIC or PsycInfo.
The complete search strategies are included in Appendix 2. Briefly, we searched for studies of children or adolescents; with a focus on overweight, obesity, or weight status; involving clinicians, health care, or other treatment or screening (KQ1); and examining common comorbidities (KQ2). For both questions, we limited only using key words, not filters, to ensure we included the newest studies that were not yet fully indexed. No date limits were placed on searches. In practice, this meant we reviewed studies from 1950 to 2020, although <2% were published before 1980.
The complete inclusion criteria are included in Appendix 3.
Inclusion Criteria Common to All Studies
All studies were required to include children ages 2 to 18 years, although studies could also include young adults up to age 25 years if stratified from older adult participants, as long as children younger than 18 years were also included. Children could have other conditions (eg, asthma), as long as they were not known to cause obesity, such as Prader-Willi syndrome, obesogenic medication (eg, antipsychotics), or known genetic mutations associated with obesity (eg, MC4R). All studies had to originate from Organization for Economic Cooperation and Development (OECD) member countries and had to be available in English.
Inclusion Criteria for KQ1 (Intervention Studies)
The primary aim of the intervention studies had to be examination of an obesity prevention (targeting children of any weight status) or treatment intervention (targeting children with overweight or obesity). The primary intended outcome had to be obesity, broadly defined, and not an obesity comorbidity. Studies of obesity interventions that reported only other outcomes were not included. Interventions could be comprised of any approach, including screening, lifestyle counseling, medically managed weight loss, pharmaceutical treatment, or surgery. Regardless of the components, there had to be some level of outpatient clinical involvement in the treatment (ie, not just referral to an outside program), such as screening or a clinic follow-up appointment. Interventions completely outside the scope of health care were excluded. We did not limit based on study design but did report experimental and nonexperimental studies separately. Although we included nonexperimental designs, all studies had to have a relevant comparison group.
See the other technical report on comorbidities7 for a detailed description of KQ2 inclusion criteria.
We used Covidence to manage the review process. Covidence is a program for online collaboration and management of systematic reviews. All abstracts were reviewed by 2 independent reviewers for inclusion in full-text review. Articles were reviewed by 2 reviewers, with conflicts discussed and resolved. Articles excluded at this stage were assigned an exclusion reason, with a hierarchy as shown in Appendix 4.
Data Extraction and Quality Assessment
All articles deemed relevant for full text inclusion were categorized into different data extraction strategies. Those given a quality assessment were reviewed using the Cochrane Risk of Bias tool. We chose not to limit studies based on quality, as many did not reach “high quality” using any tools. These studies did not meet “high quality” criteria largely because they were primarily behavioral interventions without the possibility of blinding. All studies, regardless of group, were fully extracted by 2 reviewers, and conflicts were reviewed.
Group 1 Extraction
Group 1 articles included randomized trials of diet or lifestyle interventions. “Diet” includes specific meal plans or substitutes, whereas “lifestyle” refers to nonpharmaceutical, nonsurgical intervention and may incorporate nutrition, activity, and other components. Extraction of these articles included sponsorship or funder, design, population information, provider type, detailed intervention strategies and intensity, and BMI-based outcomes. We also identified outcomes other than BMI, including lipids, glucose metabolism, blood pressure, other laboratory values, other obesity measures, psychosocial outcomes, mental health, behaviors, and other outcomes (primarily parent BMI and child cardiovascular fitness). We categorized the intensity of interventions in a manner consistent with the USPSTF, to allow for comparisons with its findings, into <5 hours, 5 to 25 hours, 26 to 51 hours, and 52 or more hours, all over ≤12 months. Quality assessment was conducted for group 1 articles.
Group 2 Extraction
Group 2 articles included randomized controlled trials of pharmaceutical treatments. We extracted similar information as above, using a brief description of the intervention and no categorization of intensity. These articles also received a quality assessment.
Groups 3 to 5 Extraction
Group 3 articles included nonrandomized comparative studies of diet and lifestyle interventions. Group 4 articles included nonrandomized comparative studies of pharmaceutical treatment, and Group 5 articles included any surgical studies. Because of small numbers, we combined randomized and nonrandomized surgical studies. Brief intervention descriptions and BMI-related outcome data were extracted from these, but the Cochrane Risk of Bias tool was not used because these were observational designs.
See other report for detailed description of KQ2 extraction procedures.
Data Synthesis and Analysis
Our primary method of data synthesis is narrative. To allow broad inclusion, we did not limit to specific designs or measures that would facilitate meta-analysis. We report on studies in each group, based on their type and design, and we report findings for outcomes other than BMI.
A total of 15 988 studies were screened in the title and abstract stage. Of these, 1642 were given a full-text review. Excluded studies (n = 1260) were most commonly not original research, did not compare comorbidities by obesity (KQ2), or were not health-care system based (KQ1). See Fig 1 for the complete PRISMA diagram. Of the 382 studies included, 215 were intervention studies and 167 were comorbidity studies. This report focuses on the 215 intervention studies; the 167 comorbidity studies are reported separately.7
Intervention Studies (KQ1)
Of the 215 studies included for KQ1, the majority (n = 126) were randomized trials of lifestyle or diet interventions (group 1), 27 were randomized trials of pharmaceutical treatments (group 2), 43 were observational studies of lifestyle or diet interventions (group 3), 8 were observational studies of pharmaceutical treatment (group 4), and 11 were studies of surgical interventions (group 5). Complete data extraction for all KQ1 studies is available in Appendix 5.
BMI Outcomes of Lifestyle RCTs (Group 1)
Group 1 studies included 54 with minimal-intervention controls8–61 and 72 comparative effectiveness studies62–133 (Table 1). Overall, 35% of the studies demonstrated any difference in BMI SD score (SDS) or BMI attributable to the intervention. There was significant variation in the number of hours of contact among the studies, with an overall increase in the likelihood of any successful weight change as contact hours increased. Detailed summaries of each of these studies are available in Tables 2 and 3.
Quality of Lifestyle RCTs
A summary of the Cochrane Risk of Bias tool is provided in Fig 2, with further details in Table 4. The majority of studies were of medium to poor quality based on this risk of bias tool. However, the major contributor to the quality assigned to these studies was their inability to blind participants or personnel. Additionally, the reporting of most studies did not allow for complete ascertainment of selective reporting or other sources of bias.
Lifestyle RCTs With Minimal-Intervention Control
For lifestyle and diet studies with minimal-intervention controls, Table 2 provides additional information on the type of intervention, sample size, age, BMI inclusion, and intervention components. These are categorized by the intensity, in hours, of the comparison group and listed with the intervention intensity. Published articles did not typically quantify dose of intervention in a consistent manner. Therefore, we extrapolated dose based on the number of sessions and average time each session lasted, to the extent this information was available from the published manuscript. We categorized findings using the USPSTF intensities of intervention delivery as <5 hours (n = 20),13,15,17,19,25,29,30,32,33,37,39–41, 44,46,48–51,56 5 to 25 hours (n = 26),8,11, 14,16,18,20–24,26–28,31,36,38,42,43,45,47,52,53,57, 59–61 and 26 to 51 hours (n = 7).9–11, 34,35,54,55 There was only 1 RCT with a minimal intervention control in which the intervention arm provided an intensity >51 hours.58 Most studies relied on usual care or primary care provider (PCP)-only as a comparison group. The sample size ranged widely, from 17 to 645.
To understand how intensity of treatment and treatment components were associated with BMI outcomes, we examined patterns noted in Table 2. For studies that provided fewer than 5 hours of contact hours over 2 to 24 months, for children ages 2 to 17 years, 25% demonstrated improvement in BMI outcomes; none of the 5 that included a second measurement time point showed differences at this later time-point. These studies typically included nutrition and physical activity counseling to children who had overweight and/or obesity. Providing additional components, such as addressing sleep or motivational interviewing (MI), did not distinguish effective studies from noneffective studies for this limited number of contact hours. Although virtually all studies resulting in statistically significant BMI reduction included MI, many of the studies without significant effects also included MI.
More than 35% of the studies that provided 5 to 25 hours of contact hours demonstrated a statistically significant change in BMI outcomes in the desired direction. More than half focused on adolescents. The majority of these lifestyle interventions focused on children who had obesity and provided nutrition and physical activity counseling with the assistance of a nutrition provider. Additional components such as sleep or participation of a mental health provider, such as a clinical psychologist, did not distinguish effective from noneffective trials.
Although there were many fewer studies that provided 26 to 51 hours of intervention contact hours (n = 7), 71% demonstrated effective change in BMI over 3 to 24 months. More than half of these included children and adolescents with obesity or severe obesity who were between the ages of 3 and 17 years. In addition to nutrition and physical activity counseling, the interventions provided activity training—that is, the incorporation of exercise during sessions (rather than only counseling on physical activity). Three of the 5 with significant improvements in BMI addressed both mental health and parenting skills.
As referenced above, we identified only 1 RCT with contact hours that exceeded 51 hours. Although this study demonstrated an effective outcome after 1 year, it included a small sample size of 73 children ages 7 to 15 years in Germany. This study provided the components of both nutrition and physical activity counseling and training as well as addressing mental health.
Primary care providers were included in almost all studies, in both the treatment arm and the minimal-intervention comparison arm. Nutrition providers and mental or behavioral health counselors were also common providers. Despite their frequency of use, none of these provider types distinguished interventions with significant improvements in BMI from those showing no differences. Other providers, such as exercise trainers or social workers, were commonly used in high-intensity interventions but did not, on their own, differentiate studies with improvements in BMI.
Overall, as the intensity of the treatment increased, the sample size of the study generally decreased, highlighting the challenges, even in a research setting, of delivering an intensive intervention to a large population. Interventions that were less intensive often included children with both overweight and obesity, whereas more intensive studies predominantly set the cut-point higher, only including children with obesity. The components of the various interventions include medical care, dietary and exercise counseling, psychosocial and mental health counseling, and MI. In addition, there were innovative strategies highlighted as well including text messaging, telehealth, and sleep training. Behavioral components, such as nutrition and activity counseling, were nearly universally present in the interventions. No single intervention component was consistently associated with improved BMI outcomes, nor were any clusters of intervention components associated with improved BMI. Although most trials with statistically significant improvements in BMI included diet and activity counseling, as well as direct activity sessions, many with these components did not demonstrate any significant differences.
Comparative Effectiveness Lifestyle RCTs
The lifestyle and diet comparative effectiveness trials (Table 3) are listed by the most intensive comparator and included the intensity of all groups. The comparator arm of these studies varied, and the most commonly used included enhanced primary care, multidisciplinary clinic treatment, mailers, or group-based education. Many of the studies in this group compared different versions of a similar intervention (primary care versus enhanced primary care versus primary care plus coaching), similar interventions delivered in different settings (inpatient versus outpatient, home versus clinic), or comparison of specific dietary strategies (low-fat versus low-carb). As seen with the studies that included a control group, the interventions that included children with more severe degrees of obesity tended to be more intensive by hours and setting (eg, inpatient) but shorter in duration as compared with less intensive interventions. No outcomes beyond 36 months were reported, although most were reported only at 6 or 12 months. Nearly all the studies included some type of nutrition and activity counseling for all comparator arms.
As with the minimal-intervention control studies, most comparative effectiveness studies included primary care providers in both study arms. Nutrition and mental and behavioral health providers were also common. In more intensive studies, exercise trainers and social workers were often used. No specific provider type was clearly associated with significant improvements in BMI.
Most comparative effectiveness studies included both nutrition and activity counseling, whereas fewer included direct provision of physical activity and nutrition training. These components were not clearly associated with improved BMI outcomes—many studies including activity and nutrition training did not find significant differences. All studies that included parenting training in the comparator demonstrated improved BMI; however, these were limited largely to very young children, 2 to 5 years of age. Otherwise, no single component of the intervention was consistently associated with positive BMI outcomes, regardless of intensity, and no clusters of intervention components distinguished studies demonstrating significant improvements in BMI.
Magnitude of Effects on BMI
Among the RCTs showing effectiveness, we also examined the magnitude of BMI change (Table 5). The magnitude of change varied widely, with lower-intensity interventions resulting in less BMI change. Several metrics were used to monitor change in children’s relative adiposity during the obesity treatment trials. BMI was the most commonly used metric of weight change among the successful lifestyle and diet trials (n = 30), followed by BMI SDS (n = 29), absolute weight (n = 16), BMI percentile (n = 12), percentage over median BMI or other (n = 6), and percentage of the 95th percentile (n = 1). Table 5 presents detailed information about the magnitude of changes, limited only to the studies showing any statistically significant differences between included groups.
Differences in BMI change between treatment arms ranged from −4.30 to −0.10. The greatest BMI changes (>2 BMI unit reduction) were observed in trials of ≥52 contact hours, mostly delivered over 12 months and to children and adolescents with obesity.58,102,118,119 The greatest differences in BMI reduction occurred in studies of older children and adolescents, with smaller reductions seen in younger children, as would be expected based on BMI for these groups. However, many studies included wide age ranges, encompassing early school age through adolescence.
Most BMI SDS changes ranged from −0.10 to −0.25 (14 of 29 studies), although 5 trials produced a BMI SDS change between −0.25 and −0.50,10,11,75,115,120 and 3 trials produced a BMI SDS change >−0.50.47,58,122 A difference of >0.25 BMI SDS has been suggested as a clinically meaningful difference.134,135 Differences between treatment arms in BMI percentile changes ranged from −0.6 to −7.2. Difference between study arms for absolute change in weight (kg) varied from −1.6 to −8.1 kg, with larger weight loss observed in trials with more contact hours and among older children and adolescents who had obesity.
Other Health Outcomes in Group 1
Many of the studies examined other health outcomes, in addition to BMI. Table 6 summarizes the other outcomes reported. These include other obesity-related metrics (eg, waist circumference), behaviors, glucose metabolism, lipids, blood pressure, psychosocial outcomes, other laboratory measures, mental health, and other outcomes.
Other Obesity-Related Metrics
The most commonly reported outcomes other than BMI were other measures of obesity, such as waist circumference or body fat percentage, which were reported in 56% of the included studies.9–11,15,16,23–29,33–35, 37,39,46,51,55,57,58,63,65,67,70,71,73–75,77, 79–83,85,86,88,89,91–102,105,106,108,110, 112,113,117–121,124,127,128,132,133 Of these studies, 50% (n = 35) noted some significant reduction in obesity-related measures attributable to the intervention. These interventions are listed in Table 7. Of the studies showing significant changes, 16 reported improvements in waist circumference, 8 reported improvements in waist circumference-to-height ratio, and 8 reported improvements in body fat percentage. Other studies reported improved outcomes in fat mass, weight, skinfold, and waist circumference-to-height ratio. Fewer studies focusing primarily on adolescents demonstrated significant improvements in obesity-related metrics, compared with those primarily including younger children. However, many studies included a wide age range (eg, 6–17 years).
Almost half (48%) of included studies reported on changes in obesity-related behaviors, primarily changes in diet or physical activity, virtually all self- or parent-reported.8–10,12–14,17–21,23,29, 31–38,41–45,48,49,51,52,56,57,60,61,63,64, 67,69,75–77,85,87,90,93,94,99,103,104,106,107, 113,117,120–124,129,130,132 Of these, half (31 of 61) reported significant improvements attributable to the intervention. These interventions are listed in Table 8. Three trials observed significant improvements in multiple behaviors, including both physical activity and diet. Twenty trials observed significant improvements in diet, including reduced caloric intake, fast food consumption, desserts, sugary beverages, sweets, and glycemic load, and improved intake of fiber, family meals, vegetables, and fruit. Finally, 10 trials observed improvements in physical activity, including increased moderate-to-vigorous physical activity and reduced television viewing.
Nearly all of the 31 interventions that noted significant changes in health-related behaviors were led by a primary care provider, and about half of these involved a nutrition provider (13 of 31 trials). Nine of the interventions that changed health behaviors involved other health professionals, including 5 interventions that involved a mental health specialist and 2 interventions that involved an exercise specialist. About half of the interventions that reported significant improvements in dietary intake involved a nutrition provider, and the rest of the interventions that improved eating behaviors were led by a primary care provider. In general, all behaviors were more amenable to change in the preschool-aged children (6 of 9 trials resulted in improved behaviors), with more inconsistency during middle childhood and adolescence (25 of 52 trials resulted in improved behaviors). There were no observable patterns in length of treatment as a determinant of effectively changing behaviors (ie, 16 of 29 interventions ≥6 months in duration noted behavior change vs 14 of 31 interventions <6 months in duration). Additionally, specific behavior changes did not consistently predict studies showing improvements in BMI outcomes.
Twenty-seven percent of the included studies reported on some form of glucose metabolism, including fasting glucose, insulin, or homeostatic model assessment for insulin resistance.8,20,26,29,35,52, 55,61,63,65,71,74,77,79–81,83,85, 88,89,92,97–100,105,107,110–113,118,119,127 Of these, 10 of 34 studies (29%) observed significant improvements, including 6 of 30 reporting a significant reduction in fasting glucose, insulin, or homeostatic model assessment for insulin resistance attributable to the intervention and 4 additional studies showing significant improvements in multiple measures. These interventions are listed in Table 9. Forty percent (4 of 10) of the trials that reported a significant improvement in glucose or insulin metabolism were specific dietary interventions, 5 trials were intensive lifestyle modification studies, and 1 study occurred in the inpatient setting. Most studies including glucose metabolism as an outcome focused on older children and adolescents. Those focusing on younger children did not typically demonstrate significant improvements in glucose metabolism.
Of the included studies, 25% reported on lipid outcomes, including total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), or triglycerides.8,20,26,29,52,55,61,65, 71,74,77,79,80,83,85,88,89,92,97–100, 105,110–113,118,119,127,132 Of these, one-third (10 of 31) reported significant improvements in lipids attributable to the intervention. These interventions are listed in Table 10. The most common lipid improvement observed was a decrease in triglyceride levels, which occurred in 4 of the 10 studies. HDL and LDL were also positively impacted, with an increase in HDL in 5 studies and a decrease in LDL in 4 studies. Total cholesterol improvement was only observed in 3 of the studies. Three studies (1 inpatient and 2 intensive outpatient group intervention studies) demonstrated improvement in 2 or more lipid parameters. Forty of the trials with a significant positive impact on lipids focused on specific dietary interventions, 5 trials were intensive outpatient lifestyle modification studies, and 1 study occurred in the inpatient setting. Of the 21 studies that did not report a significant improvement in lipid outcomes, about half observed a trend in improved lipids, most notably for a decrease in triglyceride levels. As with studies including glucose metabolism, most measuring lipids focused primarily on older children and adolescents.
Other Laboratory Values
Only 6% of studies reported on other laboratory values, such as alanine aminotransferase (A or aspartate aminotransferase (AST).8,52,65,77,83, 97,98,100 Of these, only reported improvements attributable to the intervention in 1 or more of the measures (C-peptide). These interventions are listed in Table 11.
Of the included studies, 23% reported on blood pressure outcomes.16,26,29,37,55,58,61,65,71,73,75,77,80,83,85,86,88,89,92,97,105,110–113,118,119,127 Of these, 17% reported a positive effect attributable to the intervention in either systolic or diastolic blood pressure. These interventions are listed in Table 12. The 5 interventions that showed improvements targeted different age groups and differing levels of obesity severity. One was focused on macronutrient intake, and the other 4 included substantial physical activity components.
Quality of Life
Of the 19 studies that reported on quality of life, 8 studies observed improvements and 11 studies did not observe any differences; no studies showed a decrease in quality of life. Studies demonstrating improvements were primarily higher-intensity studies with low-intensity comparisons. There were no apparent differences in participant age, weight status, or treatment duration between the studies that did versus did not detect significant changes in quality of life. Thirteen of the studies used the Pediatric Quality of Life (PedsQL), which assesses health-related quality of life in the domains of physical, emotional, social, and school functioning; 4 of these studies observed significant improvements in this scale, whereas 9 did not.
Two studies reported on self-efficacy, and both observed improvements. Both studies used the Child Dietary Self-Efficacy Scale; additionally, 1 used the Weight Efficacy Lifestyle questionnaire and 1 used the Self-efficacy Scale for Children’s Physical Activity.
Other Psychosocial Outcomes
Other reported psychosocial outcome results varied. Four studies found no significant difference between the study groups and psychosocial outcomes, including problematic eating behaviors, well-being, mood disorder symptoms, body satisfaction, internalization of social-cultural attitudes toward appearance, and self-esteem. One study showed improvements in intrinsic regulation after a motivational interviewing intervention.
Only 5% of the studies reported on a mental health outcome, most commonly depression.16,20,63,71, 109,120 Interventions are listed in Table 14. Of these, only 2 reported any improvement attributable to the intervention in 1 or more of the measures.63,120 One study observed reductions in both internalizing and externalizing behavioral and emotional problems at 12 months among children ages 5 to 16 years, of age, and the other a reduction in anxiety among those 8 to 12 years of age at 6 months. Interestingly, the participants in all 5 trials were in the healthy range on the mental health assessments; further, each study had eligibility criteria that excluded participants with significant psychological conditions, psychiatric disorders, or mental health problems, or receiving current psychological or psychiatric counseling including medication. None of the studies showed worsening of mental health outcomes.
Of the included studies, 18% reported on other outcomes, primarily parent BMI and child’s cardiovascular fitness (eg, maximal oxygen consumption [VO2 max] or 3-minute step test).12,22,30,43, 55–57,64,65,76,83,92,97,98,100, 106,109,114,120,122–124,127 These interventions are listed in Table 15. Nine trials measured parental weight or BMI outcomes at the end of the interventions; of these, 2 reported decreases in parental weight or BMI, and the remaining 7 studies reported no significant change. The 2 studies reporting a decrease in parental weight or BMI were family-based interventions in 2- to 5-year-olds, both of which included a parenting component. The remaining studies measuring parent weight and BMI included interventions ranging from self-help to telemedicine, clinic community partnership, parent group education, and primary care. None of the studies that observed no change in parents’ weight and BMI outcomes had a parenting component.
BMI Outcomes of Pharmaceutical RCTs (Group 2)
Quality of Pharmaceutical RCTs
Overall, the quality of the pharmaceutical RCTs exceeded that of the lifestyle interventions, because participants could be blinded. Despite this, in nearly half of studies, participants and personnel were not blinded. See Fig 3 for the summary and Table 17 for additional details.
Metformin was the most commonly studied medication, with 12 placebo-controlled trials137,141, 143,146,148,151,152,155,158,160–162 and 5 additional trials without placebo (most commonly lifestyle-only).138–140,145,156 No study examined children younger than 6 years, and most focused on adolescents. All studies required children to have obesity, with many limiting to children with severe obesity. In 12 of these 17 studies, metformin showed improved BMI in metformin compared with the comparison group, including both placebo controls and lifestyle comparison137,138,140,141,143,145, 148,151,156,158,160,161 ; 1 showed no improvement compared with oral contraceptive pills.139 Other studies showed reduced BMI using mixed carotenoids (n = 1),142 orlistat (n = 2),144,154 exenatide (n = 2),149,150 ephedrine + caffeine (n = 1),153 metformin + Policaptil Gel Retard (n = 1),159 and metformin + rosiglitazone (n = 1).136 Two showed no difference using topiramate (n = 1)147 or rhGH (n = 1; no difference).157 Only 5 studies included results beyond 6 months, showing improved BMI with metformin at 12 months160 and 18 months,137 improved BMI with orlistat at 12 months,144 improved BMI with Policaptil Gel Retard at 24 months,159 and improved BMI with metformin + rosiglitazone at 2 years.161 Magnitudes of BMI reduction were generally similar to those of lifestyle interventions.
BMI Outcomes of Observational Studies of Lifestyle and Diet (Group 3)
Observational studies of lifestyle and diet were often based on reports of clinical experience. Of the 43 included studies,163–206 54% (n = 23) showed some improvement in BMI outcomes compared with the nonintervention group (Table 18). Many of these studies used nonrandomized waitlist controls, historical controls, or an identified group of children seen by PCPs.
As detailed in Appendix 5, studies often showed significant reductions in BMI measures within groups, even if between-group differences were not significant. Compared with the RCTs of lifestyle and diet, the observational studies typically had larger sample sizes and longer follow-up periods, although this was not universal. Studies with the longest follow-up periods varied: 5 showed no effect at 2 years,164,183–185 5 showed improvement at 2 years,170,192,197,201,205 1 showed improvement at 3 years,191 and 1 showed improvement at 5 years.172 Because these studies are observational, selection effects should be carefully considered, particularly when comparison groups comprise children who were not referred for treatment or who declined to participate in treatment. The marked difference in the number of observational studies showing BMI improvement (54%) compared with the RCTs (35%) may reflect this selection bias or may indicate publication bias.
BMI Outcomes of Observational Studies of Pharmaceutical Treatment (Group 4)
Observational studies of pharmaceutical treatment were often based on reports of children receiving different clinical care. Of the 8 included studies,207–214 50% showed some effectiveness compared with the nonintervention group (Table 19). In these studies, 4 compared metformin to lifestyle207,208,210–212 ; 2 of these showed improved BMI for those using metformin.208,210 Metformin was not significantly different from omega-3 fatty acid supplements.209 Metformin + Policaptil Gel Retard was associated with greater BMI loss than metformin alone,213 as was phentermine compared with lifestyle intervention.212 These studies were primarily conducted with adolescents with obesity and some included diets with low glycemic indices as well as medication.
BMI Outcomes of Surgical Interventions (Group 5)
Most studies of surgical interventions were observational in nature (Table 20). Of the 11 included studies,215–225 7 compared surgical intervention (eg, Roux-en-Y bypass or laparoscopic adjustable gastric band [LAGB]) to lifestyle-only intervention or controls. All of these studies demonstrated significant reduced BMI among those receiving surgical treatment compared with lifestyle. One study showed greater BMI reduction at 2 years among adolescents receiving vertical sleeve gastrectomy (VSG), compared with intragastric weight loss device or lifestyle, although the difference across all 3 groups was not significant. Three additional studies compared 2 surgical interventions. One study showed greater BMI reduction at 3 years for those receiving gastric bypass compared with VSG. A second showed much greater BMI reduction at 12 months for VSG compared with LAGB. The third shows greater BMI reduction at 5 years for gastric bypass and VSG compared with LAGB. Most surgical interventions resulted in significant BMI loss—consistently about 15 BMI units or 30% BMI reduction.
Subquestions Relevant to all Interventions
Effects for Specific Subgroups
Few interventions specifically analyzed the effects of their interventions on subgroups, such as by age, sex, or obesity severity classification. Some studies showed differences by sex, but the findings were inconsistent. Often children with obesity were considered as 1 group, regardless of severity, making it difficult to understand differential effects based on classes of obesity.
Sustained Treatment Effect
Of the lifestyle RCTs, 57 included at least 1 follow-up measure. There was a lower likelihood of success at a subsequent time point (33%) than at the first time point (35%). However, several studies (n = 26) reported outcomes beyond 12 months; 22 reported outcomes at 2 years or later, with 36 months being the longest time frame. Only 6 of these studies showed any success of the intervention at this later time point. Two of these were primary-care based MI studies with <5 hours of contact.40,51 Two others were high-intensity (≥52 hours) family-based interventions.96,118 An additional 2 reports of the same population demonstrated success among 2- to 5-year-olds in medium-intensity (5–25 hours) family-based treatment.114,115
Barriers, Engagement, and Attrition
Overall, attrition from the interventions was high. Attrition of greater than 25% was not uncommon. Although global attrition was usually reported, factors associated with attrition were not. Lack of follow-up data on dropouts prevents a clear understanding of whether attrition is related to obesity severity or initial success in treatment. Many studies commented on barriers to participation in the interventions, but few specifically measured these. One study specifically measured barriers to adherence, identifying transportation time and expenses as barriers.31
Summary of the Evidence
Most of the studies (n = 109) included in this review were randomized trials of lifestyle or diet interventions, with fewer studies on pharmaceutical treatments or surgical interventions. Following the guidelines endorsed by the American Academy of Pediatrics in 2007,226 the interventions would largely qualify as stage 1 (those with minimal intervention comparators of <5 hours) or stages 2 or 3 (those utilizing a multidisciplinary team including dietitians and nutritionists and multicomponent behavioral treatment approach with higher intensity), with few examining stage 4 (pharmaceutical or surgical intervention, with no very low calorie diets). We did not assess interventions that occurred entirely outside of the clinical setting but instead focused on those approaches that included the pediatric outpatient clinical setting in some meaningful way. Most of the clinical settings were pediatric primary care practices, although pediatric weight management programs were also common. Although we included prevention studies in our search strategy, only treatment studies including children with overweight or obesity met criteria.
Almost half of the lifestyle and diet RCTs demonstrated clinically significant changes in BMI or BMI SDS. Interventions demonstrating improved BMI typically including a nutritionist along with physical activity and nutrition counseling (if less than 26 hours of contact time), or actual physical activity training as part of the visit along with behavioral health support (if at least 26 hours of contact hours). The more intense studies typically included only children and adolescents with obesity, and those studies with fewer contact hours included children and adolescents who had overweight or obesity. Higher-intensity studies were more effective in reducing BMI. However, the few studies demonstrating long-term effectiveness included low-intensity MI in primary care as well as high-intensity family-based treatment. No other intervention components were consistently associated with positive results. Some studies tested novel strategies to deliver counseling to families, including telehealth and sleep training, which represent promising areas of future research to fill the gap in supporting families in between face-to-face counseling sessions, but these were not clearly associated with BMI reduction.
The most notable finding of the RCTs of interventional lifestyle treatment studies (both with controls and comparative effectiveness studies) is simply how few (n = 28) of them meet the currently recommended USPSTF standard of at least 26 hours of contact time. The implication is twofold. First, many published studies do not clearly calculate contact hours. Clear standards should be set to consistently operationalize and report the delivered dose. Second, it demonstrates the difficulty of successfully translating the high-intensity research-setting interventions into real-world situations. In fact, even in ideal research conditions, there was significant attrition of participants, evidence of the difficulty in consistently delivering a higher number of contact hours.
Obesity is a chronic disease, but very few of the interventions delivered care consistent with the chronic care model.227 This model considers not just health care provision, but patient factors, accessibility of healthy food and activity spaces, and the broader social context in which people live, as well as the importance ongoing connection between health care and community. Interventions in all categories of intensity delivered the intervention over the short-term (2 months) to midterm (24 months). Interestingly, lower-intensity studies, largely based in primary care, tended to be longer-term as compared with the more intensive interventions delivered in specialty settings. Although that finding likely reflects the resources required to deliver an intervention, the result is that children with less severe degrees of obesity in effect are receiving less intensive, longer-term care than children with severe obesity who are receiving more intensive, shorter-term care. Although this strategy might be acceptable for low-risk patients, a chronic disease approach would suggest that children with severe obesity should receive intensive and long-term care.
This review prioritized a reduction in BMI or BMI SDS as the primary outcome and traditional comorbidities as secondary outcomes. However, there may have been unmeasured factors that would better predict response to treatment in addition to basic demographic information. Several studies collected psychosocial variables at baseline and at varying endpoints; these variables may be used also as predictors or moderators of outcomes to learn who is most likely to benefit from obesity treatment. In addition, several factors related to long-term progression of obesity were not collected by any of the studies contained in this review. For example, weight bias—and in particular, internalization of weight bias—is known to negatively impact an individual’s likelihood of seeking care, which may limit their ability to obtain treatment of obesity and related illnesses into the future. A recent systematic review identified 74 studies assessing the relationship between weight bias internalization and health; this review identified a strong, negative relationship between weight bias and mental health.228
The majority of interventions used patient or family education about health behaviors, provider education, and experiential exercise and/or nutrition opportunities. However, additional strategies may be important to understand who benefits from child obesity interventions but were not consistently observed in this review. For example, in a meta-analysis of interventions used in chronic-disease programs among adults, the factors most closely related to positive outcomes were not patient or provider education, but digital engagement strategies, such as text-message reminders, and a host of social and financial incentives inspired by the field of behavioral economics.229
It is also important to consider other outcomes based on the family’s expectations, culture, and desired changes. Family-centered outcomes may include improving the child’s self-esteem, coping with bullying, and quality of life, which were measured to some extent in the studies reviewed but with no consistent pattern of improvement. Further, the way to quantify and track children’s weight remains a subject of controversy. Improvements in health (blood pressure, glycemic control) and in fitness might also be important outcomes to collect. Although some studies reported these as secondary outcomes, the lack of power reporting makes it difficult to understand the true impact of interventions.
Anthropometric measurements, such as height and weight, are easiest to obtain in a clinical setting, yet these have limitations in tracking changes in adiposity over time.230 Absolute change in BMI or weight (kg) are useful indicators in short-term trials when height is stable, but because children’s height rapidly changes over time, BMI needs to be adjusted based on age and biological sex.231 BMI was the most commonly used metric in the present review but was also used in long-term trials, including those over 12 to 24 months, without adjustment for age or biological sex. Although BMI SDS was the second most frequently used metric of weight change in the included interventions, BMI SDS is not recommended for detecting changes in weight at the upper end of the spectrum among children with severe obesity.232 Absolute BMI, BMI percentage of the 95th percentile, change in percentage of the 95th percentile, and BMI as a percentage of the median BMI for age and biological sex are indicated as useful to monitor patient-level change in severe obesity over time.231 An important future direction is to integrate these more sensitive weight metrics into electronic health record portals in a way that providers and families understand and can monitor, alongside other outcomes that both the family and health care provider deem to be important.
A unique contribution of this review is the inclusion of comparative effectiveness studies; indeed, half of the lifestyle interventions were comparative effectiveness trials. The USPSTF 2018 report only included trials that had a minimal or control comparator arm. Comparative effectiveness studies can reveal important findings on differential effects of treatments based on adjunct components, specific dietary plans, delivery of treatment in different settings, or directly comparing interventions of different intensity or content. Although the interventions with higher intensity in terms of contact hours typically produced greater weight loss, there were no specific intervention components that consistently explained stronger effects. Therefore, more comparative effectiveness trials are required to identify the critical ingredients of lifestyle or diet interventions, to compare pharmaceutical versus lifestyle versus surgical approaches as well as combinations, and to understand whether some intervention approaches are more effective among certain populations or patients. In general, it is challenging to interpret findings from comparative effectiveness studies without an established margin of equivalence (ie, what is a meaningful difference in BMI change between the 2 comparator arms) or an established threshold for a clinically meaningful reduction in BMI or BMI SDS (ie, 1 intervention achieved clinically meaningful reduction whereas the other did not).
Barriers to Treatment
Trials faced problems with high attrition and low adherence, particularly among the more intensive interventions with more frequent contacts. Multicomponent approaches had smaller sample sizes indicative of the challenges of deploying a large-scale pragmatic clinical trial. For example, none of the minimal-intervention control studies that examined interventions with more than 25 hours of contact had a sample size larger than 100. Research studies do pose additional burdens to families and providers beyond clinical treatment, including strictly following a clinical protocol that includes eligibility screening, consenting, and assessment visits. However, the adherence and motivation challenges will persist outside of research studies in traditional clinical practices, particularly the logistical challenges of high-intensity treatment.233,234 Future studies should gather more information on the predictors of treatment success as well as the facilitators and barriers to adherence, both in terms of families meeting their commitment to scheduled counseling sessions as well as families changing their behaviors and sustaining this outside of the sessions. Moreover, more accessible strategies that link patients to providers, such as telehealth or phone call counseling and texting, could be important to consider to realistically achieve additional contact hours. With the emergence of additional health technologies, opportunities will exist that did not at the time that these studies were conducted.
Limitations of the Included Studies
Short Follow-up Periods
Few studies included follow-up visits to determine whether weight loss was sustained, and the longest study period involved 36 months of follow-up, which is a stark contrast to the data available on adult weight loss interventions out to 10 years. In children, the desired outcomes may be to plateau weight gain or to arrest the development of obesity-related cardiovascular and metabolic disease until adulthood. Longer-term data are needed to establish sufficient weight loss or cardiovascular improvements than can affect health into adulthood. Also, most of the lifestyle, diet, pharmaceutical, and surgery trials excluded children with mobility impairments, chronic diseases, and mental health conditions; therefore, there is less evidence on effective weight management approaches for these populations despite their elevated risk for obesity.
Limited Description of Intervention Components, Dose, and Duration
Published intervention studies often provided limited information about the dose, duration, and specifics of the intervention components and implementation procedures. This lack of detail significantly limits the opportunity to inform recommendations in practice. More details are needed on what is effective intervention content, behavior change techniques, and successful efforts to improve retention and family motivation. This information is critical if we are to create replicable findings and application of evidence. Drilling down to the essential ingredients of an effective lifestyle or diet intervention and how those components affect comorbidities is also important so that providers can focus on the critical content. This is particularly important when faced with limited contact hours because of family transportation or scheduling barriers or limited personnel or resources and financial constraints. Further, determining potential synergies among diet, lifestyle, pharmaceutical, and surgical interventions is important to develop individualized treatment plans that may start with more or less aggressive strategies depending on the child’s weight and health status, motivation, and readiness. Lifestyle interventions are core to good health but need to exist in context.
Inclusion Criteria Limit Translation to Clinical Care
Additionally, many studies had relatively restrictive inclusion criteria, excluding children with comorbidities (including mental health conditions), children with physical activity limitations, or those using medications. In clinical practice, these children often have the greatest need for support in addressing obesity.
Gaps in the Field
This review identified several critical gaps in the field that should be considered in the development of future studies. The most important gaps include: (1) systems context for interventions, (2) assessment of harms, (3) economics and sustainability, (4) heterogeneity of treatment effects, and (5) patient engagement.
First, current intervention studies include minimal consideration of the systems surrounding them. Although the goal of most research is to limit the influence of external factors, child obesity results from the interactions within a complex system. The social context for families will be critical to understanding which interventions work, for whom they work, and the situations in which they work.
Second, most studies provided no or very limited assessment of harms or unintended consequences. In general, behavioral interventions carry low risk of harms; however, this is not well-documented in the existing literature, as few studies report adverse events. Restrictive dieting is known to lead to disordered eating patterns, is associated with adult obesity, and may worsen the quality of a child’s food intake. Likewise, short-term weight loss has been shown to lead to weight regain above the initial weight, making it less clear whether a short period of weight loss adds more benefit than the likely common weight regain. These unintended consequences are less likely for nonrestrictive eating interventions; however, failure to assess and report this does not allow for reassurance and may ultimately limit dissemination. In addition, families living in low-resource environments may suffer financially by switching to foods that cost more and may lead to unintended consequences. Little is known about the psychological effects on children of increasing their awareness of their own condition of obesity.
Third, the economics of the interventions were rarely considered, including challenges with sustainability and payment mechanisms. Access to care is severely limited by inconsistent and insufficient payment for effective treatment options.235 In the United States, the USPSTF is authorized by Congress to assign grades to the state of the evidence regarding treatment options for diseases; grades of A or B are mandated by the Affordable Care Act that patients pay no deductibles or copayments and do not participate in cost-sharing.236 The USPSTF assigned a B grade to recommend clinicians screen children 6 years and older for obesity and offer or refer them to comprehensive, intensive behavioral interventions to promote improvements in weight status.1 Despite this mandate, many insurance providers are not paying for these services. For example, a Children’s Hospital Association survey conducted in 2013 surveyed 218 children’s hospitals.237 Of the 118 that responded, only 52 reported providing comprehensive, multidisciplinary weight management consistent with USPSTF recommendations, and half of these programs were fewer than 20 weeks in length. Importantly, 84% of children’s hospitals that had weight management programs reported operating at a financial loss, with about half of physicians being fully reimbursed by Medicaid or commercial plans and far less reimbursement available for other health care providers, such as registered dietitians or behavioral counselors. However, as payment models shift from fee-for-service toward population-based payment models, there are promising avenues toward securing reimbursement consistent with legislative mandates for comprehensive obesity treatment.235
Fourth, the current research does not provide sufficient information about the heterogeneity of treatment effects for obesity interventions. Studies generally did not identify demographic or social factors beyond biological sex, age, race, and ethnicity. Geographical region, food insecurity, poverty, and adverse childhood experiences (ACEs) may all be important and possibly salient factors in explaining treatment outcomes. Identifying clusters of comorbidities and obesity risk behaviors as well as duration and timing of onset of obesity during childhood and adolescence would also allow within-study results to be analyzed for potential heterogeneous responses to obesity treatment. Family and child readiness to change would also be useful to characterize the population entering the study and the potential for efficacy by these factors. Finally, severity of obesity must be considered in understanding treatment effects. Given that severe forms of obesity have increased, examining this group in future studies, rather than condensing all forms of obesity together, will be important.
Finally, current interventions include limited input from children, families, and caregivers regarding development, refinement, and implementation. Few studies included patients and families in the development of interventions, limiting the ability to ensure they are meeting the preferences and unique needs of the populations. True patient engagement could bring new insight and improve the quality of interventions and their effectiveness. This patient perspective is particularly important for the Medicaid population with their limited financial resources and unmet social needs. Despite the implementation of strong, evidence-based interventions and engagement of kids and families, overcoming financial and social barriers is critical to the success of interventions.
Contrary to the conventional wisdom that childhood and adolescent obesity interventions are ineffective, almost half of the diet and lifestyle RCTs included in this review were effective in reducing adiposity, at least in the short-term. Given the heterogeneity of the intervention types, intensity, duration, and individuals involved in delivering the intervention, it is nearly impossible at this time to specify the “optimal” childhood obesity treatment. However, it is clear that the more intense the intervention, based on hours of contact, the greater the benefit to the child in terms of BMI reduction, while keeping in mind that the more intense interventions are more costly and can impact fewer total number of people. This report highlights the promise of childhood obesity treatment but also the challenging way forward. Interventions must be sustained financially to be effective and must leverage innovative strategies to keep families engaged throughout treatment. It is also reassuring to see some benefit of lower-intensity interventions delivered in primary care, particularly those that use MI. Moving forward, a shared resource of metrics by which to compare interventions but also to predict success at the individual level will advance the science more rapidly.
We thank Chelsea Kracht, PhD, for her help in reviewing abstracts.
Technical reports from the American Academy of Pediatrics benefit from expertise and resources of liaisons and internal (AAP) and external reviewers. However, technical reports from the American Academy of Pediatrics may not reflect the views of the liaisons or the organizations or government agencies that they represent.
The guidance in this report does not indicate an exclusive course of treatment or serve as a standard of medical care. Variations, taking into account individual circumstances, may be appropriate.
All technical reports from the American Academy of Pediatrics automatically expire 5 years after publication unless reaffirmed, revised, or retired at or before that time.
COMPANION PAPER: Companions to this article can be found online at http://www.pediatrics.org/cgi/doi/10.1542/peds.2022-060640, http://www.pediatrics.org/cgi/doi/10.1542/peds.2022-060641, and http://www.pediatrics.org/cgi/doi/10.1542/peds.2022-060643.
This document is copyrighted and is property of the American Academy of Pediatrics and its Board of Directors. All authors have filed conflict of interest statements with the American Academy of Pediatrics. Any conflicts have been resolved through a process approved by the Board of Directors. The American Academy of Pediatrics has neither solicited nor accepted any commercial involvement in the development of the content of this publication.
FUNDING: Some support for the technical report came from the Strengthening Public Health Systems and Services QT18-1802 through the National Partnerships to Improve and Protect the Nation's Health grant from the Centers for Disease Control and Prevention.
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primary care provider
randomized controlled trial
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US Preventive Services Task Force
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FINANCIAL/CONFLICT OF INTEREST DISCLOSURES: The authors have indicated they have no potential conflicts of interest to disclose.