Impact of Strategies for Preventing Obesity and Risk Factors for Eating Disorders among Adolescents: A Systematic Review

An effective behavior change program is the first line of prevention for youth obesity. However, effectiveness in prevention of adolescent obesity requires several approaches, with special attention paid to disordered eating behaviors and psychological support, among other environmental factors. The aim of this systematic review is to compare the impact of two types of obesity prevention programs, inclusive of behavior change components, on weight outcomes. “Energy-balance” studies are aimed at reducing calories from high-energy sources and increasing physical activity (PA) levels, while “shared risk factors for obesity and eating disorders” focus on reducing disordered eating behaviors to promote a positive food and eating relationship. A systematic search of ProQuest, PubMed, PsycInfo, SciELO, and Web of Science identified 8825 articles. Thirty-five studies were included in the review, of which 20 regarded “energy-balance” and 15 “shared risk factors for obesity and eating disorders”. “Energy-balance” studies were unable to support maintenance weight status, diet, and PA. “Shared risk factors for obesity and eating disorders” programs also did not result in significant differences in weight status over time. However, the majority of “shared risk factors for obesity and eating disorders” studies demonstrated reduced body dissatisfaction, dieting, and weight-control behaviors. Research is needed to examine how a shared risk factor approach can address both obesity and eating disorders.


Introduction
Pediatric obesity is a well-accepted major public health concern [1]. The World Health Organization (WHO) defines pediatric obesity as a body mass index (BMI) at or above the 95th percentile among children and adolescents of the same age and sex, often measured on BMI growth charts [2]. The global age-standardized prevalence of obesity increased more than 5% for girls and almost 8% for boys over the last 40 years [2]. Causes and effects of obesity are complex and multifaceted, and obesity is exclusion criteria were placed on intervention duration, length of follow-up, or date, but this review was limited to studies published in the English, Portuguese, and Spanish languages.

Data Extraction
Data were independently extracted from eligible studies by one reviewer and cross-checked for accuracy by a second reviewer. The extracted data included sample characteristics, intervention setting, intensity and design, type of studies, tools used to assess outcome measurement, and pre-, post-intervention and/or follow-up data for both types of approaches.

Data Synthesis
Due to the heterogeneity of the study population's characteristics and programs features (i.e., length of treatment, outcomes measured, and timing of assessment), it was not possible to perform a meta-analysis. A narrative summary of the findings was conducted.

Quality Assessment and Risk of Bias
Study quality was assessed using a designed appraisal tool developed by Cochrane: Version 2 of the Cochrane Risk-of-Bias tool for randomized trials (RoB 2) [22] and Risk-Of-Bias In Non-Randomized Studies (ROBINS-I tool) [23]. Individual component quality rankings, including the risk of bias measures, are included in Figure 1. Component and overall quality ratings were scored as "low risk", "moderate", or "high" for the RoB 2; and as "low risk", "moderate", and "serious" for the ROBINS-I [22,23].   . Based on the revised Cochrane Risk-of-Bias tools for randomized controlled trials (ROB-2) and non-randomized controlled trials (ROBINS-1) (n = 6).

Overview of Studies
A flowchart summarizing the study selection procedure is presented in Figure 2. Electronic searches returned 8825 records. To begin, duplicates (n = 4106) were removed. Secondly, a total of Nutrients 2020, 12, 3134 5 of 27 4629 studies were screened by titles and abstracts. Finally, 211 studies were further excluded after reading through the full text. Of the excluded studies, 83 targeted children (≤10 years old) or adults (≥20 years old), 101 included non-healthy individuals (e.g., obese, eating disorders, or other health conditions), and in 28 studies an intervention was not considered. The remaining 35 studies met the inclusion criteria and were therefore eligible and included in this review. A total of 20 studies were energy-balance intervention studies, and 15 studies regarded a shared risk obesity and eating disorders program.

Overview of Studies
A flowchart summarizing the study selection procedure is presented in Figure 2. Electronic searches returned 8825 records. To begin, duplicates (n = 4106) were removed. Secondly, a total of 4629 studies were screened by titles and abstracts. Finally, 211 studies were further excluded after reading through the full text. Of the excluded studies, 83 targeted children (≤10 years old) or adults (≥20 years old), 101 included non-healthy individuals (e.g., obese, eating disorders, or other health conditions), and in 28 studies an intervention was not considered. The remaining 35 studies met the inclusion criteria and were therefore eligible and included in this review. A total of 20 studies were energy-balance intervention studies, and 15 studies regarded a shared risk obesity and eating disorders program.
Data abstraction revealed 15 programs that had multiple publications; these included protocols, additional cohorts, further follow-up timepoints, different outcome measures, or other secondary analysis. Thus, for reporting and analysis, studies were grouped by program cohort. Any uncertainties regarding appropriate program cohort for categorization were resolved through discussion.  Data abstraction revealed 15 programs that had multiple publications; these included protocols, additional cohorts, further follow-up timepoints, different outcome measures, or other secondary analysis. Thus, for reporting and analysis, studies were grouped by program cohort. Any uncertainties regarding appropriate program cohort for categorization were resolved through discussion.

Study Characteristics
The characteristics of the selected studies are reported in Table 1 and divided by intervention types: "energy-balance" and "shared risk factors for obesity and eating disorders" programs. All studies were published between 2005 and 2019.

Shared Risk Factors for Obesity and Eating Disorders Programs
From the fourteen studies that have shared risk factors for obesity and eating disorders as the program approach, thirteen (92.3%) were conducted at school or university [5,28,29,31,33,42,43,[51][52][53][54]56,57], and one was delivered through an internet-based platform [55]. Some of the school programs focused only on psychotherapy sessions to promote a healthy relationship with body and food [28,33,42,43,52,54,58], while others (n = 6, 42.8%) [5,29,31,51,56,57] focused on both the psychotherapy sessions and other components to help achieve a sustainable diet and PA behaviors through their life course. Other components included weekly text messages, cooking classes, enhanced physical education classes, and healthy lunches and morning snacks at school time. Two studies [29,51] Nutrients 2020, 12, 3134 7 of 27 used individual counseling techniques to promote intrinsic motivational for behavior change via the motivational interview technique.

Shared Risk Factors for Obesity and Eating Disorders Programs
For the shared risk factors for obesity and eating disorders program, all of these studies evaluated participant weight status through the use of BMI. Five studies (35.7%) [5,51,54,57,58] combined this measure with other anthropometric measures, including waist circumference and % body fat (measured using DEXA, bioimpedance, or skinfolds). Seven studies (50.0%) evaluated diet intake through validated and reproduced food frequency questionnaires [5,52,54] and others through 24 h recalls [28,51,56,57]. Those studies that used a 24 h recall only collected data from one-day of diet intake. PA was assessed by seven studies: five studies [5,51,52,56,57] used at least a 3-day recall to assess the PA of the participants, while the remaining studies [28,43,54] used a validated and reproduced questionnaire (e.g., International Physical Activity Questionnaire (IPAQ) [59] and the Paffenbarg Activity Questionnaire [60]).
Measures used to evaluate the shared risk factors for obesity and eating disorders are shown in Table 1 along with the study characteristics. Ten studies (71.4%) [28,31,33,42,52,54,55,58,61] used validated and reliable measurements that are used to assess eating disorders, including the "Eating Disorder Diagnostic Screening (EDDS)" [62], "Eating Disorder Questionnaire with Instruction (EDQ-I)" [63,64], "Difficulties in Emotion Regulation Scale (DERS)" [65], "Sociocultural Attitudes Towards Appearance Scale (SATAQ)" [66], and "Perceptions Of Teasing Scale (POTS)" [67], or used measures to assess emotion regulation and positive and negative effects through the "Dutch Restrained Eating Scale (DERS)" [68] and "Positive and Negative Scale-Revised (PANAS-X)" [69]. The purpose of these scales is to evaluate the occurrence of eating disorder symptoms, disordered eating behaviors, body shape and weight satisfaction, and weight-teasing by family and friends/peers. The other five studies (35.7%) [5,42,51,56,57] assessed these measures through questionnaires used in previous surveillance studies, specifically the "Youth Risk Behavioral Surveillance System Survey (YRBSSS)" and "Project EAT". These questionnaires assessed the risk for disordered eating behaviors, including dieting, weight control behaviors, binge eating, weight-teasing, and body/weight/shape concern. Raise awareness to beauty standards and perpetuated by the mass media. Increase physical activity and healthy eating. Improve self-esteem, build positive self-concept, and reduce extreme perfectionism, and resolve conflicts.
Lenz and Claudino et al. 2018 [29] Adaption of the US New Moves Wilksch et al. 2015 [28] No intervention name (Australia) Four-arm randomized controlled trial with post, intervention, 6-month and 12-month follow-up.

Principles of media internalization
(Media Smart group). Principles that health is more than weight (Life Smart group). Principles of eating disorder risk factors of internalization of social appearance ideals and comparisons. Evidence principles of being interactive, avoiding psychoeducation on weight-related concerns and with multiple sessions.  Reduce weight gain at school and home environments.
Program developed by a registered dietitian and cardiologist. Promote healthy eating and physical activity, integrating the head of the local council stakeholders and school teachers Yang et al. 2017 [39] No intervention name (South Korea) Quasi-experimental trial with 1-year follow-up 768 adolescents (M = 11.0 ± 1.5 years old) with 418 in intervention group.
Based on pre-intervention results + personalized suggestions for improving physical strength and dietary intake. School-based interventions with continuation in the community.
Internet-based obesity program. Information on health nutrition, food habits, and physical activity included in text and graphics.
Participants collect their weight and height and interpreted their weight status.
ANGELO framework-identify and prioritize key determinants, considering gaps in knowledge community capacity, culturally specific needs, and current health promotion. Changes in school and community-based environment.
Ardic and Erdogan 2017 [34] COPE Healthy lifestyles teen program (Turkey) Quasi-experimental trial with post and 12-month follow-up. Family changes on planning, frequency, and healthiness of family meals and snacks (limiting meals related to screen-time). Nollen et al. 2014 [46] No intervention name (USA) Personal skills were used for educational strategy, detection of weight-related problems, and proposing a care model for a screening strategy and favorable and supportive environment for environmental strategy.
* Screening = non-education Lubans et al. 2011 [27] Physical Activity Leaders-PAL (Australia) Randomized controlled trial with 3-and 6-month follow-up.  Develop on communities the capacity to build on their own promotion for a healthy lifestyle. Social marketing approaches, community capacity building, and grass-roots activities.
Chen et al. 2011 [49] WEB Based on the learning outcomes of a previous study reporting increased risk for diabetes type 2. Changes in social structures to promote physical activity, fiber intake, and reduce saturated fat, sugar, and sedentary time.

Outcomes
The focus of this review was to assess the impact of obesity prevention programs on improving disordered eating behaviors and maintaining a healthy weight status among adolescents by comparing the types of interventions: energy-balance and shared risk factors for obesity and eating disorders programs ( Table 2).

Energy-Balance Programs
Ten studies [24,26,27,32,35,[37][38][39]44,50,70] showed small improvements on youth weight status as measured by BMI, the BMI z-scores, or percent prevalence for being overweight/obese. A reduction was observed by a difference between groups (intervention vs. control) of at least 0.1 kg/m 2 , or by a 1.7% decrease on the prevalence of being overweight/obese from baseline to post-intervention/follow-up assessments. Five studies [25,26,34,40] did not find any significant effects on weight status change, while three studies [30,36,41] showed an increase in weight status change. For example, one study showed a large increase in overweight and obesity prevalence (10.1% and 12.6%) [41], and another study [30] showed a small increase in BMI of 0.2 kg/m 2 for the intervention group and a decrease in % of body fat. Interestingly, a study conducted by Fulkerson et al. [47] found that although they found no significant treatment group differences in BMI z-scores post-intervention, a post-hoc stratification by pubertal onset indicated pre-pubescent youth had significantly lower BMI z-scores than their control group counterparts (ß = 0.08, 95%CI 0.01, 0.34).
Four studies (20.0%) [26,30,41,45] did not find significant differences in diet outcomes after the intervention, which included the reduction of total energy intake and improvement on the intake of certain food groups (e.g., fruit and vegetables). However, five studies (25.0%) [25,27,34,46,49] showed an improvement in the intake of sugar-sweetened beverages, as well as fruit and vegetables. Sgambato et al. [30] did not find any significant differences when evaluating diet intake using a food frequency questionnaire; however, analyses of 30% of the sample that used a 24 h recall showed a significant decrease in the intake of fruit juice ( = −0.42 ± 0.18 serving/day) compared to the control group.
PA level was improved in four studies (20.0%) [30,34,37,49] with an average of +12.5 min/week. Two studies conducted by Lubans et al., one targeting only boys [25] and the other both sexes [27], found an improvement in physical fitness (i.e., muscular fitness and resistance training) despite finding no significant effect on PA level. The remaining four studies [26,32,45,46] found no significant effect on PA level. Shawn-Peri et al. [50] found that large classes and short physical education periods are major challenges when implementing programs. Sedentary behaviors or screen-time were improved in three studies [25,26,37]. Dewar et al. [26] showed improvement in screen-time behaviors at immediate post-intervention (after 12 months from the baseline), but at follow-up (after 24 months) found no significant differences. An average of the significant difference was −30.7 min/day.
Three studies [34,44,49] evaluated the participants' knowledge of nutrition and PA, and found significant improvements in their knowledge. Three studies [39,49,50] assessed the biological markers to verify the improvements in lifestyle behaviors, including blood pressure and fasting capillary plasma. Significant results were found among male participants with a higher BMI and older adolescents. Week and weekends decrease time on screens.
Weekends increase vegetables intake. Social support and strategies were improved. Unhealthy weight was increased (favoring intervention group).
Castillo et al. 2019 [43] Body and weight image. Risk factors for eating disorders.
Emotion regulation. Sex-specific image concerns.
Physical Activity. Weight status.
Male students did not present any significant effect. Girls improved significant for thin-ideal internalization and disordered eating attitudes.
Weight status.
No significant results for any eating disorders risk factors. Participants' low adherence in the program.
Shomaker et al. 2017 [58] Weight status and body fat. Risk factors for eating disorders.
Intervention was feasible and acceptable. Benefits to social interactions and eating. Family-based interpersonal therapy improved depression and anxiety, and loss of control compared to health education (control). Family-based interpersonal therapy reduced disordered eating attitudes. No significant differences in BMI Sanchez-Carracedo et al. 2016 [31] Risk for eating disorders. Body image concern. Emotional regulations. Weight status and body fat.
Diet intake. Physical activity.
Media Smart and HELPP were less concerned about their shape and weight compared to control girls. Media Smart and control had less eating concerns and pressure than HELPP girls. Media Smart and HELPP benefitted from media internalization compared to control boys.
Media Smart had more physical activity than HELPP and control participants. Media Smart had less time spent on screens than control participants.

Shared Risk Factors for Obesity and Eating Disorders Studies
Wilksch et al. 2015 [28] Weight status Risk for eating disorders.
Body image concern. Emotional regulations. Weight status and body fat.
Diet intake. Physical activity.
Intervention group reduced body dissatisfaction and eating disorders symptoms. No effects for BMI, depressive symptoms, dieting, energy intake, and physical activity.
Body image concern. Emotion regulation.
Intervention decreased body image concerns compared to control girls (but not sustained over a 3-month follow-up). Among boys there were no significant differences between intervention and control groups.
Body image concern.
Prevention presented lower risk factors for eating disorders and body image concern than the control group.
Gonzalez et al. 2011 [33] Weight status and body fat %. Physical activity. Diet intake. Body image concern. Weight control behaviors. Social cognitive aspects of health. No significant differences in BMI. Improvement in screen-time, diet intake, weight-control behaviors, and body image.
Friends, teachers and family support for diet and physical activity behaviors.
Physical fitness. Knowledge on behavior and attitudes towards health behaviors. Emotional regulation. Body image concern. Risk for eating disorders.
BMI and weight decreased. Improvement in health knowledge: body image, eating disorders risk factors, physical activity and diet. Increase in systolic blood pressure. Stock et al. 2007 [42] Weight control behaviors.
Diet intake. Physical activity. Weight status and body fat %.

Girls reported less weight-control behaviors after intervention.
No significant differences for boys.
Austin et al. 2007 [56] Weight control behaviors. Diet intake. Physical activity. Weight status and body fat %.
Girls reported less purging and using diet pills to control weight from both intervention and control groups.

Shared Risk Factors for Obesity and Eating Disorders Studies
Austin et al. 2005 [57] Eating disorders symptoms/Body shape satisfaction. Emotion regulation. Positive/negative affect.
Weight status. Diet intake. Physical activity.
Acceptable and feasible.
Weight status and body fat %.
Weight status increased in the intervention group. Small decrease in body fat %. No significant differences on daily frequency intake of foods.
Physical activity increased in the intervention group. 30% of the sample was analyzed using a 24 h Recall and significantly decrease fruit juice in the intervention group.
Body image. Emotion regulations. Parents' obesity social-determinants aspects.
Overweight and obesity decreased only in the intervention group.
Religious children have increased risk for being overweight. Knowledge improved in the intervention and control groups.
No significant difference in overweight incidence between the intervention and control groups. Intervention decreased BMI, height, body fat %, and increased muscular fitness compared to the control group. Blood pressure was significantly reduced, mainly in those with higher BMI, boys, and older children. Physical fitness was improved. Normal weight boys and younger individuals showed better weight-related outcomes.
Rerksuppaphol and Rerksuppaphol 2017 [40] Weight status. Control showed an increased in overweight and BMI compared to the intervention group.
Environment perceptions (home, school, and neighborhood). Emotional regulations.
Two of three intervention schools decreased the prevalence of overweight.
Diet and water intake. Nutrition and physical activity knowledge.
Emotional regulations.
Intervention group improve diet, physical activity, and stress management. Increased number of daily steps/weeks, fruit and vegetables, and water intake.
Knowledge about nutrition and physical activity was improved. Anxiety levels and BMI were reduced, but effects were not significant.
Lubans et al. 2016 [25] Weight status and waist circumference. Physical activity and sedentary behaviors.
Sugar-sweetened beverages intake. Muscular fitness and resistance training skills.
School sports motivation regulation.
No significant effect for BMI, waist circumference, and body fat %. No significant effect for physical activity. Screen-time, sugar-sweetened beverages, muscular fitness, and resistance training were improved.
MATCH significant decreased BMI compared to the control group. Subgroup analysis showed decreased among overweight and obese participants.
Lifestyle behaviors were not significant.
Family dinner frequency.
No significant difference in BMI; but promising reduction in excess weight gain. Subgroup analysis showed that pre-pubescent children showed lower BMI in the intervention group.
Gonzalez-Jimenez et al. 2014 [32] Weight status, waist circumference, and waist-to-hip ratio. Pubertal category scores Weight status was improved. Significant results for diet intake. No significant results for physical activity.
Nollen et al. 2014 [46] Home availability of fruit and vegetables, sugar-sweetened beverages, and screen devices.
Diet intake. Screen-time behaviors.
Mobile technology used the program about 63% of days compared to the control girls. Non-significant increase in fruit and vegetables and decrease in sugar-sweetened beverage intake. No significant differences for BMI and screen-time use.
Dewar et al. 2013 [26] Weight status and body fat %. Physical activity and sedentary behaviors.
Diet intake.
Non-significant effect on the decrease for BMI and body fat % between the intervention and control groups. Screen-time was significantly reduced. No significant effect for physical activity, diet intake, and self-esteem.
Screening improved the BMI and decreased the overweight incidence compared to the non-screening strategy. Education and environment strategies were less effective.

Energy-Balance Programs
Lubans et al. 2011 [27] Weight status, body fat %, and waist circumference. Physical fitness. Physical activity. Fruit and vegetables, sugar-sweetened beverages, and water intake.
Significant effect in BMI and body fat %. No significant effect for waist circumference, muscular fitness, and physical activity. Adolescents reported less intake on sugar-sweetened beverages after intervention.
Overweight increased at both the intervention and control groups. No significant effects for BMI.
Increased in overweight prevalence. Intervention group decrease body fat %. Diet and physical activity were not improved.
Blood pressure. Diet and physical activity knowledge and self-efficacy.
Diet intake. Physical activity.
Waist-to-hip ratio and diastolic blood pressure were decreased. Fruit and vegetables intake, and physical activity were improved.
Nutrition and physical activity knowledge improved.
Effects on BMI only for girls. Beneficial effect for BMI in participants with high educated parents. Negative effects for waist-to-hip ratio in participants with low educated parents.
No significant for waist circumference and weight status.
Intervention lower increased in BMI than control groups.
Intervention better effect on non-overweight students. Non-significant differences in overweight students. Intervention improved supervised PA, screen-time, and HDL-c.
Shaw-Peri et al. 2007 [51] Weight status and % body fat. Plasma glucose. Fitness laps, fasting glucose, and % body fat improved by the end of the study.

Shared Risk Factors for Obesity and Eating Disorders Programs
All 14 studies showed no significant effects on weight status post-intervention. Two programs [42,52] showed an increase in BMI and weight from post-intervention to follow-up. This increase in BMI ranged from 0.2 to 0.4 kg/m 2 , reflecting on average increase of 2.9 kg. Leme et al. [5], although not finding significant results for BMI, found that results favored the intervention group ( = −0.26 kg/m 2 ), with a lower increase in waist circumference for both groups. Female participants with high levels of anxiety demonstrated stabilization in adiposity (% body fat). Moderation analyses also indicated a stronger BMI effect for youths with initially elevated symptoms of eating disorders and higher initial BMI scores [54,55], as well as for weaker eating disorder symptoms and body image dissatisfaction [54].
Six studies [28,33,51,52,56,57] also found a reduction in several risk factors that were sustained at follow-up; specifically, eating pathology, appearance satisfaction, a thin ideal, negative affect, and emotion dysregulation. Two studies [43,55] that targeted both sexes found an interaction effect for time and group in thin idealization, but disordered eating attitudes/behaviors for females only. Leme et al. [5] and Sanchez-Carracedo et al. [31] found that results for eating disorder risk factors were in the opposite hypothesis direction, including results for appearance attitudes, eating disorders symptoms, and unhealthy weight control behaviors (e.g., skipped meals, eating very little, and fasting).
Leme et al. [5], Simpson et al. [52], and Neumark-Sztainer et al. [51] were the only studies that assessed the dietary intake, PA, and sedentary behaviors of the participants. These two studies showed an improvement in healthy eating and PA. Both showed that social support, particularly for the family, was improved after intervention along with other socio-cognitive aspects. For example, behavioral strategies for healthy eating, such as preparing meals or snacks with little fat or sugar.

Discussion
This systematic review filled a gap in the literature by assessing the impact of obesity prevention programs, with behavior change components, on weight outcomes in adolescents. Diet intervention, as either a primary goal or combined with PA, has emerged as a promising component in youth obesity prevention programs. In order to assess the impact of these programs, two approaches were compared: "energy-balance" and "shared risk factors for obesity and eating disorders". This systematic review highlights the specific differences in the program components and outcomes that goes above and beyond simply using BMI or other anthropometric measurement as the primary outcome. This review demonstrates better anthropometric outcome measures in the "energy-balance" programs that include PA components, such as enhanced physical education classes and encouragement of behavior change activities immediately post-intervention. Upon examination of interventional studies, PA seems to be moderately to highly effective in improving body composition, especially with improving resistance exercise [25,27,50] and increasing lean mass [71]. However, a posteriori effect on BMI and body weight may not be affected by PA. In line with previous work [71], several intervention studies were unable to prove success at long-term follow-up with PA outcomes. This may be explained by the approach used in these interventions, specifically educational and behavioral, which did not produce sustainable results. As shown in the risk of bias, a meta-analysis of reviews [71] has found low methodological quality of the studies included in the meta-analysis, a high level of heterogeneity, a limited number of studies available, mixed populations of overweight and non-overweight adolescents, as well as inadequate description of the interventions.

Combining Diet and Physical Activity Components to Promote Sustainable Lifestyle Behaviors
Numerous programs have been evaluated in the literature; however, the most effective strategy remains to be developed. Studies that have diet as a primary component have not been shown to be sustainable over time. The combination of diet and PA was shown to be a more effective tool against preventing youth obesity than diet alone. Schools were the most common setting where these interventions were implemented. Alternatively, results derived from combining PA or a diet with a secondary component like education and/or changes in the environment, such as policies focused on food canteens and the school curriculum, were associated with smaller effect sizes or even non-significant results [71]. When integrating diet and PA via mindfulness-based approaches seem to be more effective in preventing eating disorder risk factors, such as body image concerns and weight-control behaviors, and as consequence would help maintain a healthy weight status and well-being [72].

Maintaining Healthy Weight through Preventing Eating Disorders Risk Factors
Population-based interventions designed to maintain a healthy weight status that focused on shared risk factors for obesity and eating disorders have been a focus of attention in the general adolescent literature over the past few years [4,10,73,74]. However, few studies have been designed to reduce the burden of these shared risk factors. Indeed, results of at least some of the prevention programs suggest that weight status should not be the main outcome when considering obesity management strategies. This is because some of the disordered eating factors, mainly dieting, can lead to unsustainable dietary practices, which can lead to unhealthy weight gain or eating disorders [4]. Tanofsky-Kraff et al. [53], via exploratory post-hoc analyses, suggested evaluating the baseline social-adjustment problems (as an index for mental health problems) [75] and anxiety as moderators of the group effect on weight gain. This study revealed that adolescents with more psychosocial difficulties initially had the most benefit with intervention programs using interpersonal techniques compared to health education techniques. Moreover, both social functioning and anxiety moderate the intervention outcomes for depressed adolescents [76], as youths with a worse baseline psychosocial functioning experience the greatest improvements in depressive symptoms if they received interpersonal interventions targeting the shared risk factors as opposed to conventional approaches. Therefore, social adjustment and anxiety are important components for weight-related prevention trials and should directly focus on improving interpersonal functioning and negative mood states.

Other Factors That May Be Associated with an Increased Risk for Eating Disorders and Obesity, Which May Be the Target for Behavioral Interventions
Despite an overall improvement in the disordered eating risk factors, such as body satisfaction, unhealthy weight control behaviors, and teasing, two studies [5,31] identified an increased risk for these factors at follow-up, and female adolescents tend to have a less favorable impact on these risk factors than male participants. One study reported an increased risk for skipping meals, eating too little, and fasting at 6-month follow-up [5]. Similarly, a Spanish quasi-experimental trial [31] found that, post-intervention, a drive for thinness, being negatively affected, and self-esteem were in the hypothesized direction, but socio-attitudes towards appearance and eating disorder symptoms were in the opposite direction to what was hypothesized. All outcomes were non-significant. It is uncertain if these findings differ from the typical rate of development of eating disorders or obesity that are seen within obesity prevention trials targeting adolescents, and especially adolescent girls. Nevertheless, the early signs and symptoms of these shared risk factors in adolescents attempting to lose weight may be missed, particularly when the focus is on weight loss or the adolescent remains within or above a healthy weight status [18]. These findings support previous recommendations [77] that interventionists, public health policy makers, and other behavior-change researchers should monitor for the development of or exacerbation of these combined risk factors during weight-related prevention programs.

Caution When Targeting Other Modifiable and Non-Modifiable Risk Factors for Weight-Prevention Programs
Research suggests that attitudes towards individuals with obesity may be reduced through the provision of non-modifiable risk factors for these specific concerns [78]. Considering this, studies that focused on causes and risk factors for obesity and eating disorders identified in this review, as well as other corroborating reviews [73,79,80], showed that biological and genetic factors played a minor role in the etiology of these shared risk factors when compared with social-cultural factors. This was confirmed in studies that include both public and health professionals [73]. Thus, the published literature seems to indicate an opportunity for change in this respect. Even if successful, prevention programs of this kind presented conflicting ethical questions [81].

Interventions Should Be Based on Theory and Use of Psychometric Tested Measurements
The findings demonstrated that less than half of the studies with an energy-balance approach was theory-based, with the Social Cognitive Theory (SCT) [82,83] being the most used. A review suggest that interventions aimed at changing health behaviors in adolescents should target the key constructs of the theories [84]. For example, the core construct of the SCT is self-efficacy, which is the individual confidence in personal ability to acquire a certain health behavior [85]. Research criterion and findings with adolescents suggested that these constructs are important and reliable mechanisms of dietary and PA behaviors that can be changed when using extant intervention programs. However, given the validity of the theoretical determinants of behavior change in adolescents, it is hard to provide a conclusion. This might be due to the use of less optimal measures of mediators [84]. A product-o-coefficients test may be used to examine potential mechanisms of dietary [86] and physical activity behavior change [87], and this method has been used to identify mediators even if the intervention effects are not significant.
A study that tested the social cognitive mediators of behavior change [86], although none of the action theory results were significant, showed there was a few significant conceptual theory test results; this suggests that the intervention was not successful in changing key dietary and physical activity behaviors, yet the significant conceptual theory test results demonstrated that specific social cognitive constructs predicted behavior change in this trial [86,87]. Hence, findings of this review suggested the need for further good-quality, trial-based evidence, and highlights the importance of these potential mediators in changing health behaviors [88].

Final Thoughts on Effective Behavioral Change Interventions for Youth
As previously known [4,89], eating disorders and obesity share similar traits, but have not been the focus in the majority of the prevention trials. Further trials combining both fields are needed to clarify the components added to promote a positive food and weight relationship. For example, adding weight-teasing and body image with weight-status measurement are necessary to examine if the "shared risk factors for obesity and eating disorders" programs demonstrate key sustainable lifestyle behaviors from each weight-related component by motivating youth under a social-cognitive approach. Establishing such components would greatly inform a more precise weight-related behavioral-change prevention programs and public health policies.

Strengths and Limitations
The strength of this systematic review includes the development of a comprehensive search strategy applied in order to fill the literature gap on the impact of weight-related prevention trials, maintenance of a healthy weight status, and decreasing the burden of the shared risk factors for obesity and eating disorders among adolescents. However, there are some limitations of the current review that should be noted. Despite the authors' extensive efforts, including systematic searching of databases and manual searching of literature reference lists, it is possible that studies meeting the inclusion criteria may have been missed. Furthermore, only one author performed title, abstract, and full-text screenings. However, any uncertainties regarding study inclusion were resolved through discussion among three authors. Moreover, although strict inclusion and exclusion criteria were established, the aim of some studies included in this review was not explicitly to measure the influence of weight-related concerns on weight status and other behaviors. Thus, some outcome data was not provided in detail, limiting the conclusions able to be drawn in these instances. This review was also limited by the heterogeneity of the included studies, whereby reporting measures and outcomes were often not consistent. Finally, uncertainties on risk of bias information may be considered as a limitation. Some studies did not provide relevant information on certain sources of bias, such as allocation concealment and blinding of participants, personnel and outcome assessment, an underpowered study, and an analysis not accounting for clustering.

Conclusions
In sum, this systematic review showed that energy-balance interventions produced better results on weight outcomes when integrating physical activity associated with changes in school or other community environments. Improved disordered risk factors were seen in the shared risk factors, e.g., weight-control behaviors and shape and weight concerns, especially among overweight adolescents. However, some studies found non-significant effects or even an increased risk of these shared risk factors at the post-intervention stage among adolescent girls, suggesting that a more intensive or targeted approach may be needed for this at-risk group. These findings may suggest that efficacious approaches to support a sustainable weight status, by integrating the risk factors for eating disorders with changes in the environment, could promote healthy lifestyle behaviors, especially regarding diet and physical activity. However, more research is needed to examine how a shared risk factor approach can address both obesity and eating disorders, as well as to identify whether additional support is needed for adolescent girls.