Behavioral Weight Control for Overweight ... - Wiley Online Library

Behavioral Weight Control for Overweight Adolescents Initiated in Primary Care Brian E. Saelens,*† James F. Sallis,† Denise E. Wilfley,† Kevin Patrick,‡ John A. Cella,§ and Richard Buchta¶

Abstract SAELENS, BRIAN E., JAMES F. SALLIS, DENISE E. WILFLEY, KEVIN PATRICK, JOHN A. CELLA, AND RICHARD BUCHTA. Behavioral weight control for overweight adolescents initiated in primary care. Obes Res. 2002;10:22-32. Objective: This study evaluates the post-treatment and short-term follow-up efficacy of, as well as participant satisfaction for, a 4-month behavioral weight control program for overweight adolescents initiated in a primary care setting and extended through telephone and mail contact. Research Methods and Procedures: 44 overweight adolescents were randomly assigned to either a multiple component behavioral weight control intervention (Healthy Habits [HH]; n ⫽ 23) or a single session of physician weight counseling (typical care [TC]; n ⫽ 21). Weight, height, dietary intake, physical activity, sedentary behavior, and problematic weight-related and eating behaviors and beliefs were assessed before treatment, after the 4-month treatment, and at 3-month follow-up. Participant satisfaction and behavioral skills use were measured. Results: HH adolescents evidenced better change in body mass index z scores to post-treatment than TC adolescents. Body mass index z scores changed similarly in the conditions from post-treatment through follow-up. Behavioral skills use was higher among HH than TC adolescents, and higher behavioral skills use was related to better weight outcome. Energy intake, percentage of calories from fat, physical activity, sedentary behavior, and problematic

Submitted for publication May 3, 2001. Accepted for publication in final form September 25, 2001. *Department of Pediatrics, Division of Psychology, Children’s Hospital Medical Center, Cincinnati, Ohio; †Department of Psychology, San Diego State University, San Diego, California; ‡Graduate School of Public Health and Student Health Services, San Diego State University, San Diego, California; §Department of Pediatrics, Southern California Kaiser Permanente, La Mesa, California; and the ¶Department of Pediatrics, Scripps Clinic, La Jolla, California. Address correspondence to Dr. Brian E. Saelens, Children’s Hospital Medical Center, Division of Psychology, 3333 Burnet Avenue, Cincinnati, OH 45229. E-mail: [email protected] Copyright © 2002 NAASO

22

OBESITY RESEARCH Vol. 10 No. 1 January 2002

weight-related or eating behaviors/beliefs did not differ by condition or significantly change over time independent of condition. The behavioral intervention evidenced good feasibility and participant satisfaction. Discussion: A telephone- and mail-based behavioral intervention initiated in primary care resulted in better weight control efficacy relative to care typically provided to overweight adolescents. Innovative and efficacious weight control intervention delivery approaches could decrease provider and participant burden and improve dissemination to the increasing population of overweight youth. Key words: adolescence, telephone, mail, intervention, physician counseling

Introduction The prevalence of obesity in young childhood through adolescence continues to increase in the United States (1). Population trends suggest that overweight children are heavier than overweight youth in previous decades (2). Such trends are disconcerting given the psychosocial and physical health risk associated with being overweight in childhood (3). Long-term health risk seems greater for overweight adolescents than for younger overweight children, independent of adult weight (4). Obese adolescents are also more likely to track obesity into adulthood than younger children (5). These factors make adolescent weight control a high priority (6). Traditional weight control clinic-based interventions for adolescent obesity have demonstrated some success (7). However, the paucity of obesity treatment research for overweight adolescents is remarkable relative to the quantity of treatment research directed at overweight younger children and adults (8 –10). Adolescent treatment research is especially limited regarding the format of treatment delivery, which has included only more costly and labor-intensive hospital in-patient or weight control clinic-based formats (9). Adult weight-loss and weight-gain prevention programs have extended into applications without in-person

Weight Control for Adolescents, Saelens et al.

contact (e.g., telephone, mail, and Internet) (11,12), while still maintaining primarily behavioral and cognitive– behavioral components. Clinic-based family behavioral weight control interventions for younger children have strong evidence of long-term efficacy (8), but have generally not tested innovative delivery formats that would increase cost effectiveness and be more easily disseminated. Pediatric primary care clinics are ideal settings for identifying overweight adolescents and initiating delivery of more readily disseminated approaches for adolescent weight control. The majority of adolescents visit a physician in any given year (13,14). Overweight youth may be even more likely to visit their pediatrician than non-overweight children (15). Although health care providers sometimes fail to capitalize on opportunities to address weight-related issues with overweight patients (16), adolescents perceive their providers as a valuable source of such information (13,17). Indeed, adults who receive weight control advice from physicians are more likely to attempt weight loss (18). Health care providers seem amenable to changing current practices to increase and improve their weight-related counseling (19). Professional-based recommendations and involvement in adolescents’ weight control efforts may also decrease the likelihood that overweight youth will engage in problematic weight-related and eating behaviors (e.g., skipping meals, and purging). This is particularly relevant for the overweight child population, who could be at increased risk of developing disordered eating (20). The present study was designed to evaluate the acceptability and efficacy of a multi-component behavioral intervention for weight control among overweight adolescents. The intervention includes computer interaction and physician counseling in the pediatric primary care clinic, followed by 4 months of telephone- and mail-based behavioral counseling. It was hypothesized that adolescents receiving this intervention would have better weight outcomes than adolescents receiving single-session physician counseling (typical care [TC]) by the end of the behavioral intervention time period and at the follow-up 3 months after treatment cessation. It was further hypothesized that intervention adolescents would have improved weight control behaviors (e.g., more physical activity) and more behavioral skills use for weight control relative to TC adolescents. It was proposed that neither the behavioral intervention nor the TC approach would result in increased problematic eating- or weight-related behaviors or beliefs, given both conditions involved health professional contact.

Research Methods and Procedures Subjects Adolescents were recruited over a 5-month period from two pediatric primary care clinics in southern California. Participants were recruited from waiting room flyers and by

Figure 1: Participant flow chart representing recruitment, randomization, and retention of cohort of the Healthy Habits (HH) intervention and typical care (TC) participants. *One TC adolescent completed follow-up measurement of height and weight but did not complete follow-up measures of secondary outcomes (e.g., physical activity).

encouraging pediatricians in the clinics to discuss possible study participation with seemingly eligible adolescents. Fifty-nine interested participants were encouraged to schedule an appointment at one of the clinics for baseline assessment (see Figure 1 for participant flow). Only gender and age information were collected before baseline assessment. There was no significant difference in gender distribution or age between those individuals completing (n ⫽ 47) and not completing baseline assessment (n ⫽ 12). Inclusion/exclusion criteria were being between 12 and 16 years old, 20% to 100% above the median (50th percentile) for body mass index (BMI) for sex and age (21), interested in weight control, but not currently engaged in another weight control program, and otherwise healthy as determined by a pediatrician. Randomized participants were on average 14.2 years old (SD ⫽ 1.2) with a BMI of 30.7 kg/m2 (SD ⫽ 3.1), 59.1% were boys (26/44), and selfidentified as 70.5% white, 15.9% Hispanic, 4.5% African American, 2.3% Asian, and 6.8% multi-ethnic. All participants had a BMI above the 89th percentile for their respective age and gender. The parents of participants reported a median household income of $60,000 to $69,000, with 24% OBESITY RESEARCH Vol. 10 No. 1 January 2002

23


Table 1. Brief descriptions of the behavioral skills and developmental tailoring of the Healthy Habits telephone and mail contacts Behavioral skills Self-monitoring: writing down specific foods, amounts, calories, and each food’s category (GREEN, RED, no color) daily; weighing weekly; writing down type and amount of physical activity Goal setting: weekly establishment of goals for calories, GREEN and RED foods, and amount of physical activity Problem solving: identifying specific problems/barriers that prevent goal attainment; brainstorming solutions and ways to implement modified plan Stimulus control: modifying the food and physical activity environment to make healthful choices more available and less healthful choices more difficult to obtain Self-reward: rewarding self for reaching goals Preplanning: establishing plans for high-risk situations (e.g., parties) to decrease likelihood of unhealthful eating or lack of physical activity Developmental tailoring 11-module illustrated manual detailing behavioral skills, written at the 7th to 9th grade reading level Telephone contact only with adolescent and infrequent mail-only contact with parent(s) to promote autonomy Lottery reward system for goal achievement provided by study staff rather than parent Encouragement to have adolescents ask others (e.g., parents) for help to meet eating and physical activity goals

of adolescents living in single-parent homes. Parental consent and adolescent assent were obtained. Study procedures were approved by the San Diego State University Committee on the Protection of Human Subjects and the Institutional Review Boards of each of the clinics. Study Design Sample size determination was based on moderate to large short-term differences found between previous comprehensive weight control intervention and nonspecific treatment for childhood obesity (22) and an interest in pursuing novel adolescent obesity interventions (e.g., telephone-based) only if adequate intervention potency could be demonstrated relative to TC. With large effect size estimates of f ⱖ 0.40 (23), ⬃21 participants per condition would provide adequate power (⬎0.80) to detect post-treatment condition differences at p ⬍ 0.05. Three interested adolescents did not meet BMI inclusion criteria, leaving 44 adolescents to be randomized (Figure 1). After baseline assessment, eligible adolescents were stratified by sex and level of percent overweight (low, 20% to 40%; moderate, 41% to 60%; or high, 61% to 100%) and randomly assigned to the intervention (Healthy Habits [HH]) or TC condition. Randomization occurred by selection among opaque envelopes labeled with levels of percent overweight, each envelope containing an HH or TC card. Baseline assessments were conducted at the pediatric clinic before the condition-specific physician counseling. Posttreatment (median ⫽ 4.1 months after clinic visit) and follow-up (actual median ⫽ 7.2 months after pediatric clinic visit) assessments occurred at a university-based weight control clinic. 24


Conditions HH Intervention. The newly developed HH intervention included various delivery formats. Formats, particularly computer and telephone, were selected given their appeal to adolescents, and materials and procedures were developmentally tailored (Table 1). Immediately after baseline assessment in the clinic, HH adolescents engaged in a computer program adapted from PACE⫹ (Patient-Centered Assessment and Counseling for Exercise plus Nutrition) software designed for adolescents (24) and modified for overweight adolescents. The computer program assessed eating, physical activity, and sedentary behavior and guided adolescents through individualized plans generated to increase physical activity or decrease sedentary behavior and decrease dietary fat or increase fruits/vegetables or decrease overeating/snacking. Plan generation included identifying benefits, barriers, and specific strategies to achieve goals. The program generated printed action plan summaries and produced a provider summary form that helped identify for pediatricians which behaviors were targeted by the adolescent and whether problematic eating behaviors were reported (e.g., taking laxatives or other purging). HH adolescents then met with a pediatrician to discuss and finalize their individualized action plans. This tailored physician counseling was based on the computer responses of the adolescents. Approximately 1 week after the clinic visit, each HH adolescent and his/her parent met in-person with the first author (B.E.S.) to discuss upcoming mail and phone contacts and to learn food self-monitoring. Calls from a phone counselor began 1 week after this meeting. Telephone coun-


selors had at least a bachelor’s degree in psychology or nutrition and received weekly supervision in the provision of behavioral weight control treatment by the first author. Calls were intermittently monitored for compliance with call scripts. For each HH adolescent, the telephone counselor remained constant throughout intervention. Telephone contact was structured to last 10 to 20 minutes and scheduled weekly for the first eight calls and biweekly for the last three calls, thus, lasting a total of 14 to 16 weeks. Telephone counselors used detailed telephone scripts to address adolescents’ weight change since the last call (adolescents were encouraged to weigh once weekly), the link between weight change and eating and physical activity behaviors, instruction and feedback on previous self-monitoring, eating and physical activity goals, and the use of behavioral skills relevant to goal achievement. Behavioral skills examples are provided in Table 1. A participant manual designed to help adolescents acquire various behavioral skills for weight control was developed and distributed to HH adolescents. Initial manual sections were provided at the in-person meeting with the first author, with subsequent sections mailed after the 5th, 8th, and 10th calls. Counselors referred adolescents to the computer printouts generated in clinic and relevant manual sections to help adolescents formulate strategies for meeting goals. HH adolescents were encouraged to self-monitor all food and beverage intake and the amount and calories consumed. Adolescents were given self-monitoring booklets, one booklet for each week, to record daily: time foods/beverages consumed, description of foods/beverages, food/beverage amounts, calories, and whether a food/beverage was a RED or GREEN food (described below). Stamped envelopes were provided with each self-monitoring booklet, so adolescents could mail booklets to their telephone counselor after the call in which the self-monitoring was reviewed. Calories were estimated using The Fat Counter (25), which was provided. Telephone counselors helped HH adolescents gradually reduce calories from baseline levels to ⬃1200 to 1500 kcal/d, although this goal was flexible upward dependent on initial weight. Adapted from Epstein and Squires’ Stoplight Diet (26), foods were also categorized into GREEN, RED, or no color foods. GREEN foods were defined as having 1 or fewer fat grams per serving, ⬍150 calories per serving, and providing a good source of one or more valuable dietary components (e.g., calcium, fiber, or protein). RED foods were defined as having 5 or more grams of fat per serving or were diet versions of high-fat foods. The eventual GREEN food goal was 40 GREEN food servings (based on standard serving sizes) or more per week, and the RED food goal was ⬍15 RED food servings per week. Telephone counselors did not encourage or discourage eating any prescribed foods but encouraged reduction in food quantity and more healthful eating, within established eating preferences and food availability. For

example, if an adolescent liked eating tacos, he/she was not discouraged from eating tacos, but rather encouraged to eat fewer tacos and to reduce or eliminate the high-fat highcalorie food items often in tacos (e.g., fried tortilla, sour cream, and guacamole). This procedure allowed for flexibility in addressing adolescents’ individual food preferences within a given adolescent’s family and cultural context. Telephone counselors provided calorie and macronutrient information for foods not listed in The Fat Counter (e.g., carne asada). Beginning at the fifth call, HH adolescents were encouraged to self-monitor physical activity daily. The physical activity goal was a minimum of 60 minutes of at least moderate intensity physical activity on 5 days per week (27), with gradual increases from baseline levels. Telephone counselors encouraged adolescents to increase time in preferred physical activities and to add new types of physical activity. Conversely, adolescents were encouraged to decrease time spent in least preferred sedentary behaviors and to reallocate that time to being more active. Adolescents were awarded 1 point each for meeting selfmonitoring, physical activity, calorie, GREEN food, and RED food goals each week (total maximum of 5 points/wk), based solely on the counselor’s review of self-monitoring booklets. Points were accumulated for tickets for a studybased lottery (1 point ⫽ 1 ticket). The lottery occurred after all adolescents had completed post-treatment assessment, and the adolescent with the randomly selected ticket received $50. Parents of HH adolescents were sent information sheets when adolescents were sent manual sections. Parent information sheets highlighted ways parents could be most helpful with their adolescents’ behavior change. Recommended parental skills included stimulus/environmental control, positive reinforcement, and preplanning. There was no telephone contact with parents during the HH intervention. TC Intervention. Immediately after baseline assessment, TC adolescents met with a pediatrician. Based on expert committee recommendations regarding pediatric obesity that were given to pediatricians (28), pediatricians were instructed to assess/encourage adolescent’s motivation for weight-related behavior change, provide information about short- and long-term health consequences of high weight status and benefits of better weight control, make recommendations for healthful eating consistent with the Food Guide Pyramid (29), review physical activity recommendations for adolescents (60 min/d of at least moderate intensity physical activity) (27), and encourage consistency and persistence with health behavior changes. Pediatricians used a worksheet outlining these topics to facilitate thorough discussion with each TC adolescent. TC adolescents were encouraged to implement recommended behavior changes on their own and with the help of their family. After this non-tailored physician-counseling session, TC adolescents OBESITY RESEARCH Vol. 10 No. 1 January 2002

25


were not contacted again until scheduling for the posttreatment assessment ⬃4 months later. The same pediatricians provided counseling for HH and TC adolescents. Pediatricians had participated in previous intervention studies for dietary and physical activity change among non-overweight adolescents (24). Pediatricians met with the first author (B.E.S.) once before the study beginning to review the training and procedural materials. After completing post-treatment assessment, neither HH nor TC adolescents were contacted until scheduling for follow-up assessment. Adolescents received $25 for posttreatment and $25 for follow-up assessment. Measures Measures were obtained at all assessment time-points unless otherwise noted. Weight and Height. Weight was measured at baseline in the pediatric clinic using a calibrated standard digital scale. Weight was measured at post-treatment and follow-up on a calibrated balance beam scale. Height was measured by stadiometer at all assessments. BMI was calculated as kilograms per square meters. For purposes of determining study inclusion, population data from Rosner and colleagues (21) were used to calculate percent overweight. Updated national norms published during the course of this study were used to calculate the BMI z scores and percentage of overweight presented and used in data analysis (30). BMI z scores were calculated using age- (to the nearest month) and sex-specific median, SD, and power of the Box-Cox transformation (30). Dietary Intake. Dietary intake was assessed by the 2-day dietary recall interview. Among youth, the recall procedure has evidenced high levels of between-interviewer reliability for total calories recalled (coefficient of variation ⬍ 17%) (31), and moderate correlations between observed and recalled total calories consumed (0.47 to 0.57) (32,33), with similar associations for calories from fat (33). Foods and beverages were entered into Nutritionist-V software (34) to determine total average daily energy intake and percentage of calories from dietary fat. Consistency estimates across the two recalled days were similar at different assessment time-points for calories (0.59 to 0.65) and the percentage of dietary fat (0.31 to 0.51). Physical Activity. Physical activity was assessed by the Seven-Day Physical Activity Recall (PAR) interview. 1-week test–retest reliability for total physical activity estimates obtained by PAR are 0.47 to 0.59 for adolescent samples, with correlations of 0.44 to 0.53 between PAR physical activity estimates and heart rate monitoring (35) and similar correlations between PAR and accelerometer estimates of physical activity among adults (36). Standardized scoring procedures (37) were used to estimate daily physical activity-related energy expenditure, independent of body weight (kcal/kg per day), that was at least moderate in 26


intensity (i.e., energy expenditure by sleeping and light activity was not included). Sedentary Behavior. Sedentary behavior was measured through self-report questionnaire that queried participation in various discretionary sedentary behaviors (e.g., television watching, but not homework) during the past 7 days. Adolescents indicated the number of days engaged in and amount of time typically spent in each sedentary behavior over the past week. This methodology is similar to that used to assess television watching (38) but to date has unknown reliability and validity. Mean daily time in individual sedentary behaviors was calculated by multiplying the number of days by the typical time spent doing that sedentary behavior and then dividing by seven. Total daily sedentary behavior was the sum of these daily individual sedentary behavior estimates. Problematic Eating and Weight-Related Behaviors and Beliefs. Cognitive dietary restraint and eating disinhibition were assessed by the Three-Factor Eating Questionnaire (39). The restraint and disinhibition subscales have demonstrated internal consistency ⬎0.79 across adult dieters and free eaters (39) and were 0.81 to 0.87 for restraint and 0.63 to 0.75 for disinhibition at different assessment time-points in this study. The total score from the Children’s Eating Attitude Test (26-item CHEAT) was used to obtain a continuous measure of eating disorder psychopathology. The CHEAT has previous internal consistency coefficients between 0.76 and 0.87 (40,41) and current study internal consistency of 0.70 to 0.81 at different assessment timepoints, a previous test–retest estimate of 0.81 (40), and seems related to body dissatisfaction and problematic weight management behaviors (41). The Killen Weight Concerns scale (42), with present internal consistency of 0.75 to 0.79 at different assessment time-points, assessed concern about weight and weight change and is related to the development of eating disorders (42,43). Physician Counseling, Behavioral Skills Use, and Participant Satisfaction. After physician counseling, adolescents and physicians rated the perceived efficacy, specificity, and the extent of tailoring of the physician’s counseling using 1- to 7-point Likert scale items (higher ratings indicating more). Adolescents and physicians also reported length of physician counseling. At post-treatment and follow-up, using Likert scales (1 ⫽ never to 5 ⫽ very often), adolescents and their parents rated the frequency of adolescents’ behavioral skills use (e.g., self-monitoring and stimulus control). Skills use was asked separately for eating and physical activity/sedentary behavior. Only HH adolescents rated satisfaction for intervention components (computer program, physician counseling, manual and other written materials, and telephone counseling) at post-treatment, using Likert scale items (1 ⫽ not at all to 5 ⫽ very much) that measured helpfulness, perceived satisfaction, perceived impact on weight-related behaviors, and overall appeal.


Demographics. Parents self-reported level of household income and adolescents self-reported birth date, gender/sex, and ethnicity. Data Analysis Data were screened for normality, with sedentary behavior time requiring logarithmic transformation. To test for baseline condition differences, ␹2 analyses were used for dichotomous variables (e.g., ethnicity) and one-way ANOVAs for continuous variables (e.g., BMI z score). BMI z score was considered the primary outcome measure so that comparisons could be made among adolescents across age, gender, and over time. To test for site and sex effects, two-way ANOVAs examined condition by clinic site and condition by sex interactions at baseline and repeated measures three-way ANOVAs tested corresponding interactions with time (baseline, post-treatment, and follow-up). For main analyses, repeated measures ANOVA were used to assess change over time among primary (BMI z scores) and secondary outcomes (e.g., physical activity), with condition as the between-subjects factor and time as the within-subjects factors. Analyses were conducted separately for baseline to post-treatment and for baseline to post-treatment to follow-up. Completers were considered those adolescents who completed assessments (e.g., regardless of amount of phone contact completed among HH adolescents). Linear contrasts allowed for post-treatment to follow-up and baseline to follow-up comparisons. Conservative intent-to-treat analyses on the primary outcome were conducted by replacing missing values of HH adolescents at post-treatment (N ⫽ 3) and follow-up (N ⫽ 5) with the mean change of the TC condition from the baseline to post-treatment and post-treatment to follow-up, respectively. Mean change in the TC condition also replaced missing TC participant data (N ⫽ 2). ␹2 analyses were used to test the frequency of increases vs. decreases in BMI z scores from baseline to post-treatment and follow-up. One-way ANOVAs were used to test condition differences in physician counseling characteristics and behavioral skills use and paired t tests allowed for comparison of satisfaction among different HH intervention components. Exploratory bivariate correlations were used to examine relations between process variables (e.g., counseling characteristics, skills use) and post-treatment BMI z score, after partialing out baseline BMI z score. Statistical significance was set at p ⬍ 0.05 and all tests were two-tailed.

Results There were no significant differences by condition on demographic variables or baseline weight status variables (e.g., BMI z-scores), physical activity, dietary intake, or problematic eating and weight-related behaviors or beliefs (Table 2). In addition, there were no significant site

or sex by condition effects or three-way interactions with time on BMI z scores, so data were collapsed across site and sex for all analyses. There was a significant group by time interaction from baseline to post-treatment for BMI z scores among posttreatment completers (F(1,37) ⫽ 6.04, p ⬍ 0.02; effect size f ⫽ 0.40). As seen in Figure 2, mean BMI z scores significantly increased among TC adolescents compared with the slight decrease of BMI z scores among HH adolescents during the intervention period. Intent-to-treat analyses did not markedly alter these results (F(1,42) ⫽ 5.59, p ⬍ 0.03). More HH adolescents had reduced their BMI z score by post-treatment than TC adolescents (40.0% vs. 10.5%, respectively; ␹2(1) ⫽ 4.44, p ⬍ 0.04). Despite differential weight status outcomes, there were no significant differential changes by condition from baseline to post-treatment or main effects of time in the secondary outcomes of total energy or dietary fat intake, physical activity, sedentary behavior, or problematic eating- and weight-related behaviors or beliefs (Table 2). With the inclusion of the follow-up assessment, the overall condition by time interaction for BMI z scores remained statistically significant (F(2,70) ⫽ 4.08, p ⬍ 0.03, effect size f ⫽ 0.35; Figure 2). However, the baseline to follow-up contrast for BMI z scores only approached statistical significance (F(1,35) ⫽ 3.50, p ⫽ 0.070, effect size f ⫽ 0.32). Linear contrasts suggested no differential change in BMI z scores by condition from post-treatment to follow-up, with mean BMI z scores remaining generally stable from posttreatment to follow-up in both conditions. Intent-to-treat analyses only slightly attenuated the overall follow-up results (F(2,84) ⫽ 3.60, p ⬍ 0.04) and the baseline to follow-up contrast (F(1,42) ⫽ 3.11, p ⬍ 0.09). From baseline to followup, more HH adolescents had decreased BMI z score from baseline values than TC adolescents (55.6% vs. 15.8%; ␹2(1) ⫽ 6.41, p ⬍ 0.02). Again, there were no significant interactions of condition by time or main effects of time for any secondary outcomes from baseline to post-treatment to follow-up (Table 2). The HH and TC condition did not significantly differ in the amount of time adolescents (3.6 vs. 4.9 minutes, respectively) or pediatricians (6.3 vs. 8.1 minutes, respectively) perceived the physician counseling session lasted (both F(1,44) ⬍ 4.0, p ⬎ 0.05). There were no significant condition differences in how adolescents and physicians perceived the effectiveness, specificity, or extent of tailoring of the physician counseling. At post-treatment, HH adolescents reported higher rates of total and eating- and physical activityspecific behavioral skills use than TC adolescents (all F(1,37) ⬎ 5.17, p ⬍ 0.03). Parents of HH adolescents also reported that their adolescents used more overall and specifically eating-related behavioral skills than parents of TC adolescents (both F(1,37) ⬎ 4.50, p ⬍ 0.04). HH adolescents continued to report higher overall and eating-related behavOBESITY RESEARCH Vol. 10 No. 1 January 2002

27


Table 2. Weight status and secondary outcomes for post-treatment and follow-up assessment completers, mean (SD) Baseline

Body mass index (BMI) Percentage of overweight§ Weight (kg) Height (cm) Calories (kcal/d) Percentage of calories from fat Physical activity (kcal/kg/d) Sedentary behavior (min/d) TFEQ¶ restraint TFEQ¶ disinhibition Total CHEAT** Killen scale

Post-treatment

Follow-up

HH* (n ⴝ 20)

TC† (n ⴝ 19)

HH (n ⴝ 20)

TC (n ⴝ 19)

HH (n ⴝ 18)

TC (n ⴝ 19)‡)

31.0 (3.5) 62.0 (20.5) 85.5 (13.9) 166.1 (10.4) 2010 (903)

30.7 (3.1) 62.3 (17.4) 80.5 (13.5) 161.4 (8.7) 2062 (564)

30.9 (3.8) 59.8 (21.8) 86.1 (14.0) 166.7 (9.6) 1919 (653)

31.8 (3.4) 66.2 (18.6) 84.1 (13.8) 162.1 (9.0) 1715 (540)

31.1 (4.5) 59.6 (24.6) 87.5 (16.0) 167.5 (9.9) 1820 (677)

32.1 (3.8) 66.4 (20.1) 85.8 (14.6) 163.0 (9.1) 1640 (608)

33.9 (8.8)

34.3 (4.9)

32.8 (10.0)

34.2 (7.5)

32.9 (9.4)

35.6 (6.4)

6.7 (5.6)

5.6 (5.1)

7.8 (5.0)

6.4 (6.1)

6.3 (3.5)

6.9 (3.6)

260 (260) 10.3 (4.8) 6.6 (2.8) 13.4 (6.7) 49.1 (18.2)

240 (136) 8.8 (4.1) 6.4 (3.1) 10.7 (6.5) 42.7 (21.3)

268 (230) 11.7 (4.9) 5.3 (2.5) 14.5 (6.7) 54.2 (21.6)

309 (182) 9.6 (5.0) 6.2 (3.4) 11.3 (7.7) 44.6 (23.0)

281 (245) 12.4 (5.5) 4.6 (2.7) 11.3 (7.8) 52.2 (21.7)

267 (117) 9.6 (3.9) 6.1 (3.7) 11.0 (8.6) 49.9 (19.9)

* HH ⫽ Healthy Habits intervention participants. † TC ⫽ typical care participants. ‡ 1 TC adolescent completed follow-up measurement of height and weight but refused completion of follow-up measures of secondary outcome (e.g., physical activity). § Average percentage above the 50th-percentile BMI, based on National Center for Health Statistics/Centers for Disease Control and Prevention 2000 growth curves (30). ¶ TFEQ ⫽ Three-Factor Eating Questionnaire. ** CHEAT ⫽ Children’s Eating Attitude Test.

ioral skills use at the follow-up assessment compared with TC adolescents (both F(1,33) ⬎ 7.88, p ⬍ 0.01), but parent reports of adolescent behavioral skills use were no longer significantly different between HH and TC conditions at follow-up. The median number of HH intervention calls completed was 9.0 of the planned 11 calls among all adolescents randomized to HH, with calls lasting on average 16.4 minutes (SD ⫽ 4.6). Approximately 70% of the HH adolescents completed 9 or more calls. HH adolescents were significantly more satisfied with the telephone counseling component than all other intervention components (mean of 4.05 of 5, SD ⫽ 0.87; all t(18) ⬎ 3.33, p ⬍ 0.01). HH adolescents reported significantly greater satisfaction for mailed materials/manual than the computer interaction (t(18) ⫽ 3.01, p ⬍ 0.01) but indicated similar levels of satisfaction between the mailed materials/manual (mean ⫽ 3.57, SD ⫽ 1.13) and the physician counseling (mean ⫽ 3.39, SD ⫽ 0.92), and between physician counseling and the computer interaction (mean ⫽ 2.98, SD ⫽ 1.06). 28


Figure 2: Mean body mass index (BMI) z scores (⫹SEs) for the Healthy Habits intervention and typical care conditions among adolescents completing assessments at post-treatment and follow-up.


Bivariate partial correlations revealed a significant negative association between adolescent behavioral skills use and post-treatment BMI z scores (r(36) ⫽ ⫺0.48, p ⬍ 0.003; more skill use related to lower post-treatment BMI z scores). Neither the length of physician counseling (perceived by adolescents or physicians) nor the amount of telephone contact (number of calls and average call length) was related to weight outcomes.

Discussion A 4-month behavioral intervention initiated in primary care with continuing telephone and mail contact led to a modest decrease in weight status among overweight adolescents (approximately ⫺0.05 in BMI z score). In contrast, adolescents provided TC of a single provider counseling session had an increase in BMI z score of 0.06, suggesting weight acceleration among these already overweight adolescents above the normative positive BMI trajectories of adolescence. Although it is necessary to interpret cautiously across age and gender among adolescents, these BMI z score differences were associated with a ⫺0.2 BMI decrease for the multiple component intervention and a BMI increase of ⫹1.1 among adolescents provided TC. The behavioral intervention did not produce absolute average weight loss, but intervention adolescents were more likely than TC adolescents to have improved their relative weight status, with 40% reducing BMI z scores by post-treatment. There was no evidence that the intervention further favorably affected weight from treatment cessation to follow-up. By the follow-up, intervention adolescents continued to be more likely to have decreased their BMI z scores and did not fully return to their average baseline BMI z scores level or reach those of TC adolescents. Adolescents reported high levels of satisfaction with provider interaction around weight-related issues, regardless of whether they received intervention after physician contact. The multi-component intervention, and especially the telephone component, was also rated highly. The telephone and mail components seemed feasible and effective in promoting behavioral skills use for weight control. Both adolescent and parent reports indicated greater behavioral skills use among intervention adolescents relative to typical care, at least initially. Greater use of behavioral skills could have served as a mechanism for better outcome among intervention adolescents, because adolescents’ report of greater behavioral skills use was related to more positive weight outcomes. The association between skills use and outcome has been documented in other health behavior interventions (44), and weight control interventions for younger children (45) and adults (46,47). Despite differential skills use and weight change by condition, there were no observed differential changes by condition in diet or physical activity behaviors. This disparity has been found among some recent childhood obesity treat-

ment (48) and prevention (49) studies. It could be that measures of weight-related behaviors in this study were not sensitive enough to detect actual behavior change because small daily changes in energy balance could explain weight changes. Self-report methodology, consisting of short sampling duration among constructs known to exhibit variation across days (e.g., eating) (50), and modest measurement reliability and validity, could have affected the results. Given the intervention emphasis on self-monitoring, the accuracy of self-reporting of diet and physical activity may have improved among intervention adolescents, thus, increasing the ratio of calories reported to actual calories eaten, and perhaps resulting in the lack of condition differences. Furthermore, the social desirability of reporting more physical activity and less overall and dietary fat calories within the context of weight control study assessments could decrease the likelihood of condition differences. Participants could also have temporarily improved eating and physical activity behaviors immediately before assessments, which at most assessed the past week (e.g., PAR). More frequent and objective diet and physical activity assessment in the future would alleviate many of these possible limitations. The lack of change in problematic eating- and weightrelated behaviors and beliefs suggests that neither the multicomponent intervention nor physician counseling alone promotes increased problematic eating or weight-related behaviors and beliefs among overweight youth. Present mean scores on these measures were similar to those found among normative adult and youth samples (39,41). The lack of disturbed eating-related effects is consistent with results from studies involving younger overweight children provided professionally led weight-loss treatment (51). The magnitude of weight status change among intervention adolescents was generally lower than results obtained by the best clinic-based weight control treatments for overweight youth (7). Possible reasons for this difference could include intervention intensity. The present 4-month intervention was shorter than most typical adult (10) and pediatric obesity interventions (8). Duration of each intervention contact was shorter than most in-person treatment contacts. In addition, the reinforcement system assigned points weekly, but rewards were distal (only delivered at program end), not guaranteed (lottery-based), and were programadministered and not parent-based. Whereas phone counselors praised healthful changes in eating and physical activity, this motivational encouragement was infrequent (weekly at best) and nonexistent for adolescents who did not adhere well to the contact schedule. The level and type of optimal parental involvement in adolescent weight control remains unknown (7,52), but perhaps involving parents and other caregivers in the praise and other positive reinforcement of adolescents’ weight control behaviors, as is done with younger children, would improve efficacy. OBESITY RESEARCH Vol. 10 No. 1 January 2002

29


Reduced intensity may reduce efficacy but may expand the number of adolescents who can participate and benefit from more flexible intervention delivery format. Present results compare favorably with other telephone- and correspondence-based programs for adult weight-loss and weight-gain prevention (11). Adolescents in the present study may also differ from those included in previous youth weight-control research. The telephone- and mail-based intervention benefits from greater generalization, but the less stringent inclusion criteria (e.g., no exclusion for psychiatric comorbidity) and higher inclusion rate in the present study relative to many previous randomized trials (8) could have resulted in lower average short-term weight control or maintenance. Initially interested participants (⬃75%) were randomized in this study (Figure 1), whereas recent clinicbased studies have generally randomized fewer than 50% of initially interested individuals (53,54). The factors that reduce likelihood of engaging in clinic-based interventions (e.g., chaotic lifestyle) may be those related to poorer behavioral compliance and outcome. Boys and adolescents from across ethnic groups were also well-represented in the current study, unlike many previous evaluations of adolescent weight-control treatment. However, as with previous pediatric obesity treatment research, this sample was not generally from low socioeconomic strata, perhaps due to the bias of recruiting overweight adolescents from primary care clinics and only those with an interest in weight control. That single-episode provider counseling did not result in positive weight change among overweight adolescents converges with effects of other minimal and no-treatment control conditions on overweight children’s weight change (55). There is some evidence that untreated overweight youth gradually increase their weight status above expected increases in BMI associated with age (56), although more comprehensive data on weight-gain trajectories of overweight youth are generally lacking. Naturalistic or selfinitiated weight control efforts by youth may not only be ineffective, but also perhaps paradoxically facilitating weight gain (57). Such weight gain among the typical care adolescents is consistent with the higher BMIs of overweight adolescents in the population compared with previous decades (2). However, it is also possible that an inadequate level of guidance in the TC condition somehow promoted weight gain. Given high youth obesity prevalence and high rates of weight dissatisfaction and reported weightcontrol attempts among adolescents (58), more information is needed about the effects of self-initiated weight control practices among overweight youth. This study provides preliminary evidence for the acceptability and short-term efficacy of a multi-component intervention for adolescent weight control beginning in primary care. The small sample size and response variability limited power to detect statistically significant condition differences through follow-up, because the effect size of condition 30


differences in BMI z scores to follow-up were moderate in size (23). Studies including larger sample sizes, longer follow-up, and more thorough process evaluation would inform more comprehensive examination of efficacy and identify the most potent components of this multi-component approach. This could help formulate stepped-care treatment models for intervening with overweight adolescents. Innovative adolescent interventions that do not involve weekly clinic-based visits have the potential to decrease provider and participant cost, increase the number and diversity of treated overweight youth, and perhaps increase participants’ acceptability of greater length of therapeutic contact. This may help treatment providers capitalize on the positive relationship between length of provider contact and weight loss/maintenance success (59), consistent with a continuous care model of obesity intervention (60).

Acknowledgments This research was supported in part by a Young Investigator’s Grant awarded by the North American Association for the Study of Obesity to the first author. Appreciation is expressed to Richard I. Stein, Danielle Kukene, and Beatrice Schmid for their invaluable assistance with the health counseling and data collection. References 1. Troiano RP, Flegal KM. Overweight children and adolescents: description, epidemiology, and demographics. Pediatrics. 1998;101:497–504. 2. Flegal KM, Troiano RP. Changes in the distribution of body mass index of adults and children in the U.S. population. Int J Obes Relat Metab Disord. 2000;24:807–18. 3. Must A, Strauss RS. Risks and consequences of childhood and adolescent obesity. Int J Obes Relat Metab Disord. 1999; 23:S2–S11. 4. Must A, Jacques PF, Dallal GE, Bajema CJ, Dietz WH. Long-term morbidity and mortality of overweight adolescents: a follow-up of the Harvard Growth Study of 1922 to 1935. N Engl J Med. 1992;327:1350 –5. 5. Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH. Predicting obesity in young adulthood from childhood and parental obesity. N Engl J Med. 1997;337:869 –73. 6. U.S. Department of Health and Human Services. Healthy People 2010. Washington, DC: U.S. Department of Health and Human Services; 2000. 7. Brownell KD, Kelman JH, Stunkard AJ. Treatment of obese children with and without their mothers: changes in weight and blood pressure. Pediatrics. 1983;71:515–23. 8. Epstein LH, Myers MD, Raynor HA, Saelens BE. Treatment of pediatric obesity. Pediatrics. 1998;101:554 –70. 9. Jelalian E, Saelens BE. Empirically supported treatments in pediatric psychology: pediatric obesity. J Pediatr Psychol. 1999;24:223– 48. 10. National Institutes of Health, National Heart Lung and Blood Institute. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults—the evidence report. Obes Res. 1998;6:51S–129S.


11. Leermakers EA, Jakicic JM, Viteri J, Wing RR. Clinicbased vs. home-based interventions for preventing weight gain in men. Obes Res. 1998;6:346 –52. 12. Tate DF, Wing RR, Winett RA. Using Internet technology to deliver a behavioral weight loss program. JAMA. 2001;285: 1172–7. 13. Marks A, Malizio J, Hoch J, Brody R, Fisher M. Assessment of health needs and willingness to utilize health care resources of adolescents in a suburban population. J Pediatr. 1983;102:456 – 60. 14. Gans JE, McManus MA, Newacheck PW. Adolescent Health Care: Use, Costs, and Problems of Access. Chicago, IL: American Medical Association; 1991. 15. Gauthier BM, Hickner JM, Ornstein S. High prevalence of overweight children and adolescents in the Practice Partner Research Network. Arch Pediatr Adolesc Med. 2000;154: 625– 8. 16. Nawaz H, Adams ML, Katz DL. Weight loss counseling by health care providers. Am J Public Health. 1999;89:764 –7. 17. Hodgson C, Feldman W, Corber S, Quinn A. Adolescent health needs: utilization of health care by adolescents. Adolescence. 1986;21:383–90. 18. Sciamanna CN, Tate DF, Lang W, Wing RR. Who reports receiving advice to lose weight?: results from a multistate survey. Arch Intern Med. 2000;160:2334 –9. 19. Simkin-Silverman LR, Wing RR. Management of obesity in primary care. Obes Res. 1997;5:603–12. 20. Fairburn CG, Doll HA, Welch SL, et al. Risk factors for binge eating disorder: a community-based case-control study. Arch Gen Psychiatry. 1998;55:425–32. 21. Rosner B, Prineas R, Loggie J, Daniels SR. Percentiles for body mass index in U.S. children 5 to 17 years of age. J Pediatr. 1998;132:211–22. 22. Haddock CK, Shadish WR, Klesges RC, Stein RJ. Treatments for childhood and adolescent obesity. Ann Behav Med. 1994;16:235– 44. 23. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates; 1988. 24. Prochaska JJ, Zabinski MF, Calfas KJ, Sallis JF, Patrick K. PACE⫹: interactive communication technology for behavior change in clinical settings. Am J Prev Med. 2000;19: 127–31. 25. Natow AB, Heslin J. The Fat Counter. 4th ed. New York, NY: Pocket Books; 1998. 26. Epstein LH, Squires S. The Stoplight Diet for Children. Boston, MA: Little, Brown and Co.; 1988. 27. Pate R, Trost S, Williams C. Critique of existing guidelines for physical activity in young people. In: Biddle S, Sallis J, Cavill N, eds. Young and Active? Young People and HealthEnhancing Physical Activity—Evidence and Implications. London, UK: Health Education Authority; 1998, pp. 162–73. 28. Barlow SE, Dietz WH. Obesity evaluation and treatment: expert committee recommendations. Pediatrics. 1998;102:E29. 29. U.S. Department of Agriculture, U.S. Department of Health and Human Services. Dietary Guidelines for Americans 2000. 5th ed. Washington, DC: U.S. Department of Agriculture, U.S. Department of Health and Human Services; 2000.

30. Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, et al. CDC Growth Charts: United States Advance Data from Vital and Health Statistics. Hyattsville, MD: National Center for Health Statistics; 2000, no. 314. 31. Frank GC, Berenson GS, Schilling PE, Moore MC. Adapting the 24-hr recall for epidemiologic studies of school children. J Am Diet Assoc. 1977;71:26 –31. 32. Lytle LA, Murray DM, Perry CL, Eldridge AL. Validating fourth-grade students’ self-report of dietary intake: results from the 5 a Day Power Plus Program. J Am Diet Assoc. 1998;98:570 –2. 33. Crawford PB, Obarzanek E, Morrison J, Sabry ZI. Comparative advantage of 3-day food records over 24-hour recall and 5-day food frequency validated by observation of 9- to 10-year-old girls. J Am Diet Assoc. 1994;94:626 –30. 34. First DataBank I. Nutritionist Five User’s Guide, Version 1.6. San Bruno, CA: First DataBank I; 1998. 35. Sallis JF, Buono MJ, Roby JJ, Micale FG, Nelson JA. Seven-day recall and other physical activity self-reports in children and adolescents. Med Sci Sports Exerc. 1993;25: 99 –108. 36. Sallis JF, Saelens BE. Assessment of physical activity by self-report: status, limitations, and future directions. Res Q Exerc Sport. 2000;71:1–14. 37. Sarkin JA, Nichols JF, Sallis JF, Calfas KJ. Self-report measures and scoring protocols affect prevalence estimates of meeting physical activity guidelines. Med Sci Sports Exerc. 2000;32:149 –56. 38. Guillaume M, Lapidus L, Bjo¨ rntorp P, Lambert A. Physical activity, obesity, and cardiovascular risk factors in children: the Belgian Luxembourg Child Study II. Obes Res. 1997;5:549 –56. 39. Stunkard AJ, Messick S. The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J Psychosom Res. 1985;29:71– 83. 40. Maloney MJ, McGuire JB, Daniels SR. Reliability testing of a children’s version of the eating attitude test. J Am Acad Child Adolesc Psychiatry. 1988;27:541–3. 41. Smolak L, Levine MP. Psychometric properties of the children’s eating attitudes test. Int J Eat Disord. 1994;16:275– 82. 42. Killen JD, Taylor CB, Hayward C, et al. Pursuit of thinness and onset of eating disorder symptoms in a community sample of adolescent girls: a three-year prospective analysis. Int J Eat Disord. 1994;16:227–38. 43. Killen JD, Taylor CB, Hayward C, et al. Weight concerns influence the development of eating disorders: a 4-year prospective study. J Consult Clin Psychol. 1996;64:936 – 40. 44. Saelens BE, Gehrman CA, Sallis JF, et al. Use of selfmanagement strategies in a two-year cognitive-behavioral intervention to promote physical activity. Behav Ther. 2000;31: 365–79. 45. Israel AC, Silverman WK, Solotar LC. The relationship between adherence and weight loss in a behavioral treatment program for overweight children. Behav Ther. 1988;19:25–33. 46. Boutelle KN, Kirschenbaum DS. Further support for consistent self-monitoring as a vital component for successful weight control. Obes Res. 1998;6:219 –24. OBESITY RESEARCH Vol. 10 No. 1 January 2002

31


47. Baker RC, Kirschenbaum DS. Self-monitoring may be necessary for successful weight control. Behav Ther. 1993;24: 377–94. 48. Epstein LH, Valoski AM, Vara LS, et al. Effects of decreasing sedentary behavior and increasing activity on weight change in obese children. Health Psychol. 1995;14: 109 –15. 49. Robinson TN. Reducing children’s television viewing to prevent obesity: a randomized controlled trial. JAMA. 1999;282: 1561–7. 50. de Castro JM. Prior day’s intake has macronutrient-specific delayed negative feedback effects on the spontaneous food intake of free-living humans. J Nutr. 1998;128:61–7. 51. Epstein LH, Paluch RA, Saelens BE, Ernst MM, Wilfley DE. Changes in eating disorder symptoms with pediatric obesity treatment. J Pediatr. 2001;139:58 – 65. 52. Wadden TA, Stunkard AJ, Rich L, et al. Obesity in black adolescent girls: a controlled clinical trial of treatment by diet, behavior modification, and parental support. Pediatrics. 1990; 85:345–52. 53. Golan M, Weizman A, Apter A, Fainaru M. Parents as the exclusive agents of change in the treatment of childhood obesity. Am J Clin Nutr. 1998;67:1130 –5.

32


54. Epstein LH, Paluch RA, Gordy CC, Saelens BE, Ernst MM. Problem solving in the treatment of childhood obesity. J Consult Clin Psychol. 2000;68:717–21. 55. Lansky D, Vance MA. School-based intervention for adolescent obesity: analysis of treatment, randomly selected control, and self-selected control subjects. J Consult Clin Psychol. 1983;51:147– 8. 56. Braet C, Van Winckel M, Van Leeuwen K. Follow-up results of different treatment programs for obese children. Acta Paediatr. 1997;86:397– 402. 57. Stice E, Cameron RP, Killen JD, Hayward C, Taylor CB. Naturalistic weight-reduction efforts prospectively predict growth in relative weight and onset of obesity among female adolescents. J Consult Clin Psychol. 1999;67:967–74. 58. Neumark-Sztainer D, Hannan PJ. Weight-related behaviors among adolescent girls and boys: results from a national survey. Arch Pediatr Adolesc Med. 2000;154:569 –77. 59. Perri MG, Nezu AM, Patti ET, McCann KL. Effect of length of treatment on weight loss. J Consult Clin Psychol. 1989;57:450 –2. 60. Latner JD, Stunkard AJ, Wilson GT, et al. Effective longterm treatment of obesity: a continuing care model. Int J Obes Rel Metab Disord. 2000;24:893– 8.