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American Journal of Clinical Nutrition, Vol. 87, No. 5, 1134-1140, May 2008
© 2008 American Society for Nutrition

ORIGINAL RESEARCH COMMUNICATION

Cognitive behavioral therapy improves diet and body composition in overweight and obese adolescents1,2,3

Margarita D Tsiros1, Natalie Sinn1, Leah Brennan1, Alison M Coates1, Jeff W Walkley1, John Petkov1, Peter RC Howe1 and Jonathan D Buckley1

1 From the Australian Technology Network Centre for Metabolic Fitness (MDT, NS, LB, AMC, JWW, PRCH, and JDB) and the Nutritional Physiology Research Centre (MDT, NS, AMC, PRCH, and JDB), School of Health Sciences, University of South Australia, Adelaide, Australia; the School of Medical Sciences, RMIT University, Melbourne, Australia (JWW and LB); the Parenting Research Centre, Melbourne, Australia (LB); and the Centre for Regional Engagement, University of South Australia, Adelaide, Australia (JP)

2 Supported by the Australian Technology Network Centre for Metabolic Fitness.

3 Reprints not available. Address correspondence to JD Buckley, ATN Centre for Metabolic Fitness and Nutritional Physiology Research Centre, School of Health Sciences, University of South Australia, PO Box 2471, Adelaide, SA 5001, Australia. E-mail: jon.buckley{at}unisa.edu.au.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background:Cognitive behavioral therapy (CBT) teaches behavioral and cognitive strategies that focus on achieving and maintaining lifestyle changes.

Objective:We examined the effectiveness of a CBT program (CHOOSE HEALTH) for improving body composition, diet, and physical activity in overweight and obese adolescents.

Design:Adolescents [16 male, 31 female; aged 14.5 ± 1.6 y; body mass index (BMI; in kg/m2) 30.9 ± 4.2] were block-matched into 2 groups by age, sex, Tanner stage, BMI, and hip and waist circumferences and were randomly assigned to CBT or no treatment (control). CBT consisted of 10 weekly sessions, followed by 5 fortnightly telephone sessions.

Results:Compared with the control, over 20 wk, CBT improved (significant group x time interactions) BMI (CBT, –1.3 ± 0.4; control, 0.3 ± 0.3; P = 0.007), weight (CBT, –1.9 ± 1.0 kg; control, 3.8 ± 0.9 kg; P = 0.001), body fat (CBT, –1.5 ± 0.9 kg; control, 2.3 ± 1.0 kg; P = 0.001), and abdominal fat (CBT, –124.0 ± 46.9 g; control, 50.1 ± 53.5 g; P = 0.008). CBT showed a greater reduction in intake of sugared soft drinks as a percentage of total energy (CBT, –4.0 ± 0.9%; control, –0.3 ± 0.9%; P = 0.005 for group x time interaction), which was related to reductions in weight (r = 0.48, P = 0.04), BMI (r = 0.53, P = 0.02), and waist circumference (r = 0.54, P = 0.02). Physical activity did not change significantly.

Conclusions:A 10-wk CBT program followed by 10 wk of fortnightly phone contact improved body composition in overweight and obese adolescents. Changes in soft drink consumption may have contributed to this benefit.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The prevalence of overweight and obesity is increasing worldwide at an alarming rate in children and adolescents (1). Many adverse health effects generally associated with adult obesity are now being seen in obese adolescents (1–3), and there is concern that the strong tracking of adolescent weight into adulthood will exacerbate the increasing incidence of adult obesity and obesity-related disease (4–6). Although adolescence may be a particularly vulnerable period for the development of obesity (7), information is scarce on effective obesity treatments for this group (8). Most interventions for reducing adolescent obesity have included preadolescent children, whose behavior may be more easily modified (1). Although primary prevention of obesity is, and should be, a preeminent public health goal, effective interventions are also required to treat existing obesity in adolescent populations to stem the increasing prevalence of adult obesity (9).

Epstein et al (10) suggested that long-term weight loss and weight maintenance in children and adolescents could only be achieved if unhealthy eating and activity behaviors are replaced with healthier lifestyle changes that persist into adulthood. As a result, interest has been growing in the use of strategies to alter and maintain behaviors associated with healthier weight (11). Cognitive behavioral therapy (CBT) is a psychological treatment based on the theory that the problem in question (eg, obesity) is maintained by certain dysfunctional cognitions and beliefs (11, 12). CBT uses behavioral therapy techniques in an effort to modify behaviors by changing antecedents and consequences and combines these with cognitive techniques designed to identify, evaluate, and then restructure dysfunctional cognitions and beliefs. CBT also uses strategies to promote the generalization and transfer of new skills and behaviors learned in therapy into everyday life and the maintenance of these changes across time (11, 13, 14). CBT has previously been used to treat obesity in adults (15) and to a lesser extent in adolescents, with the adolescent studies providing mixed results (12, 16–19). Several studies reported significant improvements in adolescent weight status (16–18), 2 of which included follow-up beyond 12 mo (17, 18). By contrast, studies by Duffy and Spence (12) and Warschburger et al (19) found that CBT effects on weight were not significantly different from those of behavioral therapy and relaxation therapy, respectively. More recently, a 12-wk CBT program (CHOOSE HEALTH; L Brennan, Melbourne, Australia) in adolescents resulted in a 6% reduction in body fat relative to the control group that was sustained for 12 mo (20). Although these data are promising, the 12-wk program was longer than a standard school term, which created difficulties for attendance at sessions during school holidays (20). The purpose of the present study was to determine whether a shorter version of this same CBT program, which could be delivered within a single school term, would be effective for improving diet, physical activity, and body composition in overweight and obese adolescents.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Subjects
Overweight and obese adolescents (International Task Force on Obesity criteria; 21) aged 12–18 y were recruited. Participants were excluded if they were involved in other weight-loss programs, were not residing with a parent or cargiver, were unwilling to attend sessions, were pregnant, were physically or intellectually disabled, or had a medical cause for their obesity (eg, endocrine disorders, hypothalamic damage, acute lymphatic leukemia, etc). After all baseline assessments, the participants were block-matched into 2 groups on the basis of age, sex, pubertal development, body mass index (BMI), hip circumference, and waist circumference. The groups were then randomly assigned to either the CBT treatment or a control group that received no treatment. All volunteers provided written informed consent before participation, and all procedures were approved by the Human Research Ethics Committee of The University of South Australia. The study was conducted from February to December, 2006.

Intervention
The intervention was delivered by a psychology researcher and 2 clinical psychology masters students, all of whom received training in CBT. Participants in the CBT group took part in a shortened version of the CHOOSE HEALTH program (22). This shortened program consisted of two 10-wk blocks. The first 10 wk comprised the initial treatment phase (core program), and the second 10 wk was a maintenance phase. The core program (outlined in Table 1Go) consisted of 8 clinic sessions and 1 phone-call session during the school term and 1 final session after the school holidays. Sessions were held after school on weekdays and lasted 1 h each. Adolescents attended sessions accompanied by a parent who could assist their adolescent to relate the information to their specific circumstances. Face-to-face sessions were videotaped to ensure treatment fidelity. The first 5 sessions focused on improving diet and activity habits through the use of behavioral strategies such as self-monitoring of diet and activity, external control strategies, and goal setting. Sessions 6 to 10 focused on teaching strategies to maintain new health behaviors and introduced CBT strategies such as reframing of unhelpful thoughts and problem solving. Two of these later sessions were completed by the adolescents alone. Each adolescent was provided a pedometer to promote physical activity and a book on healthy eating with menu suggestions and recipes (23). They were also given the Australian Guide to Healthy Eating (24) and Australia's physical activity recommendations for 12–18-y-olds (25). After the 10-wk core program, the adolescents entered the 10-wk maintenance phase, which involved 4 fortnightly phone calls. At the end of the maintenance phase, 8 participants from the control group crossed over into the core program, and a second control group was recruited and paid an honorarium as compensation for their time and effort rather than being offered the intervention.


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  		TABLE 1. Outline of core program treatment sessions

 
Outcome measures
All assessments (except physical activity assessment by pedometer) were conducted at the Nutritional Physiology Research Centre clinic at baseline, week 10, and week 20.

Anthropometry
Body composition was assessed by dual-energy X-ray absorptiometry (DXA; Lunar Prodigy, GE Medical Systems, Madison, WI) with standard software (ENCORE 2003, version 7.52; GE Medical Systems) for determination of fat mass, percentage body fat, lean tissue, bone mineral content, and bone mineral density (26). The SEs of the measurements of body composition by DXA in our laboratory were previously determined to be 0.87% for percentage body fat, 0.53 kg (1.6%) for fat mass, 1.05 kg (2.3%) for lean mass, and 0.02 g/cm2 (1.3%) for bone mineral density when performed on consecutive days in 11 overweight and obese subjects not involved in this study. Abdominal fat content was determined for the body segment bordered superiorly and inferiorly by the lowest point of the rib cage and the uppermost aspect of the iliac crest, respectively, and extended laterally to the outer edge of the rib cage (27). All DXA scans were performed by a licensed operator, and adolescents were scanned while wearing a hospital gown.

Hip and waist circumferences were measured to the nearest millimeter with a flexible nonelastic measuring tape. Waist circumference was measured at the level of the iliac crest (28). Hip circumference was measured over underwear at the point of maximum buttock protrusion (29). The SEs in our laboratory for these measures were 0.41 cm (0.4%) for waist circumference and 0.15 cm (0.1%) for hip circumference when performed as consecutive measures of 30 overweight and obese subjects.

Height was measured with a wall-mounted stadiometer (SECA, Vogel & Halke, Hamburg, Germany) to the nearest 0.1 cm with the volunteers barefoot. Weight was measured with a TANITA Ultimate Scale 2000 (Tanita Corporation, Tokyo, Japan) to the nearest 0.1 kg with the participants wearing a hospital gown. BMI was then calculated as body mass (kg) divided by height (m)2.

Pubertal development
The Tanner scale (30) was used to provide an approximation of self-reported pubertal development. Although the Tanner scale was designed for direct clinical assessment by physicians, it has also been validated as a self-assessment tool with correlations of 0.82 between physician reports and self-reports and an interobserver reliability of 0.86 (31).

Dietary behaviors
Dietary intake during the previous month was assessed at baseline and weeks 10 and 20 by using a food-frequency questionnaire (Victorian Cancer Council, Melbourne, Australia; 32) that has been validated for use in short-term intervention trials (33). In addition, participants were interviewed about sugared soft drink consumption (because this was not surveyed in the original questionnaire) by using the same frequency responses as on the food-frequency questionnaire. Energy, carbohydrate, and sugar intakes from sugared soft drinks were calculated independently by using FOOD WORKS PROFESSIONAL (version 2005; Xyris Software Pty Ltd, Brisbane, Australia) and were then added to the corresponding food-frequency questionnaire nutrient outputs.

Physical activity
Physical activity was assessed by using the Yamax Digiwalker (SW700) pedometer (Yamax Corporation, Tokyo, Japan). The Digiwalker pedometer has been found to record within 3% of actual steps taken and has high intra-instrument reliability (Cronbach's alpha of >0.99) (34). Participants received training in how to position the pedometers (on their right hip) and recorded their daily steps in an activity diary. Physical activity was assessed during the week before baseline and again during the week before assessments at weeks 10 and 20. Physical activity was monitored during typical school weeks rather than holiday periods. Participants were asked to record their steps for 7 consecutive days. Minimum inclusion criteria for physical activity data consisted of 4 weekdays and 1 weekend day (35).

Statistical analyses
Data were analyzed on an intention-to-treat basis by using SPSS version 15 for WINDOWS (SPSS Inc, Chicago, IL). Baseline characteristics for the treatment and control groups were compared by using unpaired Student's t tests. To determine the effects of the treatments on the dependent variables over time, data were analyzed by using random effects mixed modeling. The use of a mixed model procedure was deemed valid because an analysis revealed no significant differences at baseline between those who completed the full 20-wk program and those who completed only to week 10, which indicates that noncompletion was random. The distribution of data for sugared soft drink intake was skewed, and many values were missing. These data were normalized by using a Johnson transformation, and missing values were then imputed (multiple imputation) before applying an analysis of covariance using a mixed model procedure with participants treated as random effects. Pearson's correlations coefficients were calculated, followed by linear regression analyses to determine relations between changes in body composition and changes in diet and physical activity. Statistical significance was set at an {alpha}-level of <0.05.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
General
Participation and dropouts are provided in Figure 1Go. A total of 14 participants dropped out by the end of the 20-wk intervention period, and 15 participants were not offered the maintenance phase because of resource constraints. The baseline characteristics of the treatment (CBT) and control groups are shown in Tables 2Go and 3Go. The mean age of participants in the CBT and control groups was 14.6 ± 1.6 y and 14.6 ± 1.8 y, respectively. There were similar distributions of boys and girls in each group (9 boys and 16 girls in the CBT group and 7 boys and 15 girls in the control group). The groups were similar at baseline for all outcomes except for percentage of total energy intake from sugared soft drinks, which was significantly higher in the CBT group (Table 3Go). Tanner stage did not differ significantly between the CBT and control groups at baseline (P = 0.50) and did not change significantly (P = 0.07 for time, P = 0.2 for group x time interaction).


Figure 1
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  		FIGURE 1.. Flowchart of participation. A total of 14 participants dropped out and 15 were not offered the maintenance phase because of time and resource constraints. Five participants were declined enrollment because of resource constraints. CBT, cognitive behavioral therapy. *Eight participants are counted twice because they participated in the control group and then crossed over into the treatment group, where they were offered the core program (10 weeks only), and additional participants were recruited as controls.

 

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  		TABLE 2. Anthropometric measures in the cognitive behavioral therapy (CBT) and control (CON) groups1

 

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  		TABLE 3. Mean values for diet and physical activity in the cognitive behavioral therapy (CBT) and control (CON) groups1

 
Anthropometry and body composition
Anthropometric and body-composition data are provided in Table 2Go. Adolescents in the CBT group achieved significant improvements in weight, BMI, fat mass, abdominal fat, and hip circumference compared with the control group (P < 0.05 for all group x time interactions), whereas improvements in percentage body fat and waist circumference were not significant (P = 0.08 for group x time interaction for both). The differences in body composition between groups increased progressively during the intervention, such that the largest differences were evident by week 20 (ie, the end of the 10-wk maintenance period; Table 2Go).

Diet
Dietary intake data are provided in Table 3Go. There were reductions in total energy intake (P = 0.001 for time), carbohydrate intake (P < 0.001 for time), fat intake (P = 0.01 for time), and total sugar intake (P < 0.001 for time) during the study period. However, protein intake did not change, and there were no significant differences between the control and CBT groups for these components of dietary intake.

With control for higher energy intake from sugared soft drinks at baseline in the CBT group, soft drink consumption was reduced significantly in the CBT group compared with the control group during the study period (P = 0.005 for group x time interaction; Table 3Go). Furthermore, the reduction in the proportion of total energy intake derived from the consumption of sugared soft drinks at week 10 was significantly correlated with reductions in BMI, fat mass, hip circumference, waist circumference, and weight at week 10 (Table 4Go). These correlation coefficients were similar at 20 wk but were not all significant because of a loss of participants and reduced power (Table 4Go).


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  		TABLE 4. Relation between change in percentage of total energy intake from soft drinks and changes in body composition at weeks 10 and 201

 
Physical activity
Pedometer data for adolescents who failed to meet the minimum recording criteria of 4 weekdays and 1 weekend day were excluded from the analysis. The number of participants with valid data and the pedometer values at each assessment point are shown in Table 3Go. The average weekly steps measured by the pedometer did not change significantly during the study period (P = 0.12 for time, P = 0.12 for group x time interaction).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
A 20-wk program of CBT (modified CHOOSE HEALTH program), involving a 10-wk core program followed by a less intensive 10-wk follow-up, improved dietary behavior and body composition in overweight and obese adolescents but did not influence physical activity levels. Although adolescents in the treatment group were still, by definition, obese by the end of the intervention, it was not expected that they would reach a normal BMI range within such a short timeframe, as this would have required dramatic and rapid lifestyle changes that are not recommended for adolescents (36). Adiposity tended to increase in the control group during the study period, which supports the contention that adolescence may be a particularly risky developmental period, with a strong tendency for increased fatness (1). Furthermore, it appeared that the CBT program offset this tendency, at least in the short term.

Although obesity is a risk factor for cardiovascular and metabolic disease, the distribution of body fat plays an important role, with abdominal fat being most strongly associated with the development of insulin resistance, type 2 diabetes, dyslipidemia, and cardiovascular disease (37). Hence, although the CBT intervention resulted in an overall reduction in body fat, importantly, there was a small but significant reduction in abdominal fat. DXA measures of abdominal fat are highly correlated with computed-tomography measures of total abdominal adipose tissue (r = 0.89–0.985) (38, 39). The small but progressive improvement in abdominal fat over time holds promise for long-term health if it can be maintained, particularly when one considers that body fat and abdominal fat increased in the control group during the intervention period.

The reduction in weight (–1.7%) in the CBT group and the increase in the control group (4.6%) resulted in a 6.2% difference in weight change between groups. This magnitude of differential weight change suggests that it may have provided health benefits for the adolescents in the CBT group given that it approached the 7–10% weight loss that has been reported to result in health benefits for adults (40). Importantly, the differential weight change between groups in the present study was due almost entirely to changes in body fat. Although other studies have shown that CBT can achieve weight loss with the use of BMI as an outcome criterion (16–18), the current study and preliminary findings from a prior trial conducted by this group (20) are the only studies published to date that have demonstrated changes in body fat with the use of DXA. The finding that the difference in weight change between treatment groups was due to changes in body fat rather than to changes in lean tissue or bone indicates that this intervention did not compromise the normal development of lean tissue. Furthermore, given the magnitude of the effect and the correlation of fat mass with cardiovascular risk in adolescents (41), there may have been a reduction in cardiovascular risk in the CBT group compared with the control group.

Previous studies using energy-restricted dietary approaches have shown negative effects on adolescent growth and development (42, 43), although Figueroa-Colon et al (43) did report catch-up growth once energy intake was increased. Furthermore, restrictive diets have been shown to have limited long-term efficacy in the management of obesity (44). The CBT approach used in the present study did not recommend an energy-restricted diet, but rather encouraged healthy eating habits in line with the Australian Guide to Healthy Eating (24). Importantly, both the intervention and the control groups increased their height and bone mass over time with no significant difference between the groups, which indicates that the intervention did not have any detrimental effect on growth or development.

Although CBT improved the body composition of adolescents in the present study, it was less clear which changes in behavior contributed to this success. Compared with the control, CBT reduced the percentage of total energy intake derived from sugared soft drinks, the only dietary factor that correlated with changes in body composition. This finding agrees with those of another randomized controlled trial that found that BMI could be improved by replacing sugared beverages with unsugared beverages (45). Interestingly, both the CBT and the control groups reduced their overall intakes of energy, fat, carbohydrate, and sugar. The reason for these reductions in the control group are not clear, but may be due to a Hawthorne effect (46) whereby participants modified their behavior as a result of just being enrolled and assessed for a weight-loss study. The adolescents who volunteered for this study may have been particularly interested in modifying their behavior and decided to modify their behavior despite being allocated to the control group. However, despite similar self-reported changes in some dietary components, only the treatment group experienced significant improvements in body composition, whereas the control group increased in several markers of fatness. Therefore, these dietary changes may also reflect limitations in the food-frequency questionnaire for assessing adolescent dietary habits or underreporting of food and beverage intake. It should be noted that the second but not the first group of control subjects was remunerated for their participation. This difference in incentives may have had some influence on the outcomes of the study.

Pedometer data from the current study, which indicated that adolescents averaged 63 000–89 000 steps/wk, reflected that adolescents were engaged in low levels of physical activity when compared with current recommendations of 91 000–112 000 steps/wk for reducing the risk of excess body fat in children aged 5–12 y (47). Furthermore, the CBT intervention indicated that adolescents did not increase their levels of physical activity, which suggests that the improvements in body composition in the intervention group were mediated by other behavioral changes. In saying that, there are limitations in the ability of pedometers to detect subtle and important changes in physical activity (48). Additionally, there was low compliance with physical activity measurement compared with other outcomes, leading to a small sample size and lower power to detect change. Therefore, there may have been changes in physical activity that were not detected.

In conclusion, the findings of this study suggest that CBT may be an effective strategy for achieving improvements in body composition in adolescents by focusing on sustainable lifestyle changes and may be a useful intervention for treating adolescent obesity. Long-term follow-up studies are needed to determine whether maintenance of weight loss can be achieved over the longer term and into the adult years.


   ACKNOWLEDGMENTS
 
We thank Keren Kneebone for her assistance with data collection and data entry and Amber Owen, Anna Asebol, and Denise Skinner for their assistance with the delivery of the CBT program. The study was funded internally by the universities collaborating with the ATN Centre for Metabolic Fitness.

The contributions of the authors were as follows—MDT: contributed to study design and conception, recruitment, data collection, data entry, data analysis, data interpretation, and manuscript preparation; NS: contributed to the administration and local adaptation of the CBT program, data analysis, data interpretation, and manuscript preparation; LB: developed the CBT program (Choose Health) and professional training, provided training in program delivery, contributed to study design and conception, and manuscript preparation; AMC: contributed to study design and conception, data collection, data analysis, data interpretation, and manuscript preparation; JWW: contributed to study design and conception, data analysis, and manuscript preparation; JP: contributed to study design, data analysis, and manuscript preparation; PRCH: contributed to study design and conception, sourcing funding support, data interpretation, and manuscript preparation; JDB: contributed to study design and conception, data analysis, data interpretation, sourcing funding support, and manuscript preparation. None of the authors had a financial or personal conflict of interest.


   REFERENCES
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 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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Received for publication October 4, 2007. Accepted for publication December 19, 2007.





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