Lifestyle Interventions for Youth Who Are Overweight: A ... - PsycNET

Health Psychology 2010, Vol. 29, No. 1, 91–101

© 2010 American Psychological Association 0278-6133/10/$12.00 DOI: 10.1037/a0017437

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Lifestyle Interventions for Youth Who Are Overweight: A Meta-Analytic Review Katherine M. Kitzmann

William T. Dalton, III

The University of Memphis

East Tennessee State University

Caroline M. Stanley

Bettina M. Beech

The Children’s Hospital of Philadelphia

Vanderbilt University School of Medicine

Tamara P. Reeves, Joanna Buscemi, Clayton J. Egli, Heather L. Gamble, and Ericka L. Midgett The University of Memphis Objective: Clear evidence suggests that lifestyle interventions can be helpful in the treatment of youth who are overweight, but translational research is needed to address the gap between treatment research and clinical care. Design: This meta-analysis integrated the results of 66 treatment– control comparisons and 59 alternate treatment comparisons evaluating lifestyle interventions for children and adolescents who were overweight. Main Outcome Measures: Between-groups differences in weight-related outcomes and other health-related behaviors at the end of treatment. Results: Lifestyle interventions were effective in a range of settings and with a range of participants. Even relatively brief programs had benefits apparent months after the end of treatment. A key component appeared to be the expectation that parents would be actively involved in treatment. Program benefits included not only better weight management but also better eating habits. Conclusion: The results suggest that lifestyle interventions can be effective under a wide range of conditions not limited to the highly controlled conditions of efficacy studies. Parent involvement is associated with significantly better results. Keywords: pediatric overweight, lifestyle intervention, parent involvement, meta-analysis Supplemental materials: http://dx.doi.org/10.1037/a0017437.supp

earlier mortality (Jelalian & Mehlenbeck, 2003). Being overweight also places youth at risk for lower health-related quality of life (Tyler, Johnston, Fullerton, & Foreyt, 2007), lower self-esteem (Zeller, Saelens, Roehrig, Kirk, & Daniels, 2004), more symptoms of depression (Zeller & Modi, 2006), and more psychosocial difficulties associated with weight bias and discrimination (Puhl & Latner, 2007). The documented trends in prevalence and risk for children and adolescents who are overweight highlight the need for effective interventions. Lifestyle interventions—those that include some combination of diet, exercise, and other weight-related behavior change—are among the most commonly used treatments for youth who are overweight. There are now several decades of research suggesting that these programs can promote healthy weight management in children and adolescents. Several quantitative reviews have re-

The Centers for Disease Control and Prevention (Ogden et al., 2006) estimate that approximately one third of U.S. youth ages 2–19 are overweight (sex-specific body mass index [BMI] for age ⱖ 95th percentile) or at risk for being overweight (85th to 95th percentile).1 Over the past several decades, these rates have more than doubled among children and tripled among adolescents (Ogden, Flegal, Carroll, & Johnson, 2002). Youth who are overweight are at risk for Type II diabetes and cardiovascular disease; the risk for health problems continues into adulthood and includes

Katherine M. Kitzmann, Tamara P. Reeves, Joanna Buscemi, Clayton J. Egli, Heather L. Gamble, and Ericka L. Midgett, Department of Psychology, The University of Memphis; William T. Dalton, III, Department of Psychology, East Tennessee State University; Caroline M. Stanley, Department of Psychology, The Children’s Hospital of Philadelphia; Bettina M. Beech, Division of General Internal Medicine and Public Health, Vanderbilt University School of Medicine. This research was conducted with the support of the Center for Applied Psychological Research, Department of Psychology, The University of Memphis. We thank William R. Shadish for advice on statistical analysis, and Suzanne Allen, Stephanie E. Aring, and Katianne M. Howard for assistance with preparing drafts of the article. Correspondence concerning this article should be addressed to Katherine M. Kitzmann, 202 Psychology Building, University of Memphis, Memphis, TN 38152-3230. E-mail: [email protected]

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Consistent with commonly used terminology at the time, Ogden et al. (2006) classified youth as overweight if the BMI score was above the 95th percentile for the sex and age group and at risk for overweight if the BMI score was between the 85th and 95th percentiles. Since then, the American Academy of Pediatrics and other organizations have begun to label youth with scores above the 95th percentile as obese and to label those with scores between the 85th and 95th percentiles as overweight (Barlow & The Expert Committee, 2007). 91


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ported positive outcomes in terms of weight and weight-related variables such as BMI. In these reviews, as in the current review, effect sizes were calculated on the basis of differences between treatment and comparison groups, measured either in terms of posttest scores (e.g., absolute weight) or change scores (e.g., weight loss), with positive effect sizes representing more positive outcomes in the treatment group relative to the comparison group. In treatment– control comparisons, overall average effect sizes have been estimated as Cohen’s d ⫽ 0.56 (Haddock, Shadish, Klesges, & Stein, 1994), d ⫽ 0.95 (Snethen, Broome, & Cashin, 2006), and Hedges’s g ⫽ 0.75 (Wilfley et al., 2007); the effect size has been estimated as g ⫽ 0.48 when treatments were compared with education-only groups (Wilfley et al., 2007). These are moderate to large effect sizes (Cohen, 1988), and even the smallest estimate suggests that the average treatment participant fared better than 70% of the comparison group at the end of treatment. In the review by Wilfley et al. (2007) of randomized controlled trials, analysis of change scores showed that treatment groups showed a reduction of about 8% overweight from baseline to the end of treatment, whereas control groups showed about a 2% increase in overweight. Although the body of evidence suggests that lifestyle interventions can be helpful in the treatment of youth who are overweight, much more needs to be known to address the gap between treatment research and clinical care (Saelens & Liu, 2007). The current meta-analysis was designed as translational research to address specific questions about lifestyle interventions that have not been thoroughly examined in the literature to date: (a) In addition to showing efficacy in randomized controlled trials, do these treatment programs also show effectiveness under less controlled conditions? (b) How long should treatment last to be effective, and how long do the benefits last? (c) In what ways should parents be involved in treatment? (d) Do these programs produce other benefits besides weight change? First, do lifestyle interventions for pediatric overweight show both efficacy and effectiveness? The efficacy of these programs has been documented in both randomized controlled trials (Wilfley et al., 2007) and randomized comparisons of various lifestyle treatments (Epstein, Paluch, Roemmich, & Beecher, 2007). This evidence is critical in establishing the validity of these approaches. However, because these efficacy studies are conducted under well-controlled conditions, for example, using manualized treatments implemented by teams of highly trained staff in research settings or specialized obesity clinics (Whitlock, Williams, Gold, Smith, & Shipman, 2005), it is also important to assess whether lifestyle programs can be effective in a wide range of conditions. In the current meta-analysis, we examined whether outcomes differ significantly in programs that are older versus more recent, use random versus nonrandom group assignment, are conducted in research versus nonresearch settings, and use objective versus nonobjective methods for selecting participants. Second, how long should treatment last to be effective, and how long are the benefits maintained? These questions have been difficult to answer in part because past meta-analyses have averaged effect sizes across programs of varying treatment lengths and across varying periods of time to follow-up. In addition, it can be difficult to get information about treatment maintenance from treatment– control studies because researchers using betweengroups designs often provide treatment to the control group after

the posttest evaluation (Haddock et al., 1994). To this point, clearer information about maintenance has been provided by within-group analyses of treatments of similar length. Epstein et al. (2007) examined within-group change from baseline in 17 treatment groups. The average effect sizes at 6, 12, 24, and 120 months posttreatment were d ⫽ ⫺1.20, d ⫽ ⫺1.02, d ⫽ ⫺0.82, d ⫽ ⫺0.55, and d ⫽ ⫺0.67, respectively, with negative effect sizes representing weight loss over time. In the current meta-analysis, we examined questions about treatment length and treatment maintenance in between-groups analyses by focusing on comparisons made at similar time points across subsets of studies, namely at 4 months, 8 months, 1 year, and 2 years after initiating treatment. Third, what forms of parent involvement are most helpful in lifestyle treatments for overweight youth? Most programs involve parents to some degree, and parent involvement is seen as essential in comprehensive programs (Spear et al., 2007), family-based treatments (Kitzmann & Beech, 2006), and programs that view parents as the “exclusive agents of change” (Golan, 2006). The focus on parent involvement is consistent with the growing emphasis on systemic and ecological models of youth weight problems (Davison & Birch, 2001). In the current meta-analysis, we examined whether outcomes are significantly better in programs with high parent involvement, and we compared the effectiveness of programs that do and do not include specific treatment components such as parents’ participation in their own weight loss program, parent training in behavior modification, and parent education about diet and activity. Fourth, do lifestyle treatments have benefits other than weight management? Many lifestyle programs are of short duration, and there may be minimal evidence of weight loss or weight gain prevention during this period. Other changes may be more noticeable in the short term, including changes in weight-related behaviors such as eating and activity habits, which are important because of their positive effects on overall health (Barlow & The Expert Committee, 2007). Lipid levels, blood pressure, and physical fitness may be other useful “intermediate” measures of outcome (Whitlock et al., 2005). The current meta-analysis examined a wide range of outcomes including youths’ health behaviors, youth and parent knowledge of weight management strategies, and parents’ own weight management. Treatment– control comparisons were the primary focus of this review. For the analyses regarding parent involvement, we also examined comparisons of alternate treatments. Within-study alternate treatment comparisons are typically not reported in metaanalyses, but they can provide important information about relative treatment effects (Shadish et al., 1993). On the other hand, these results can be difficult to interpret because of the heterogeneity in the alternative treatments being compared. For this reason, treatment– control studies are the basis of our analyses, with alternate treatment studies providing supplemental information. We examined published papers as well as unpublished theses and dissertations and included both randomized and nonrandomized studies. The comprehensiveness of this set of studies is important for several reasons. First, relying only on published papers may overestimate the true effect size if there is a bias toward publishing statistically significant findings (Rosenthal, 1995). Second, this set of studies provides information on the full range of methods by which lifestyle interventions are being implemented and evaluated in both research and nonresearch settings.

INTERVENTIONS FOR YOUTH WHO ARE OVERWEIGHT

Third, these studies maximize the information available to address our questions concerning treatment effectiveness, long-term outcomes, parent involvement, and outcomes other than weight change.

Method

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alternate treatment comparison related to parent involvement in treatment (n ⫽ 36 studies). When the same data were reported in more than one outlet (e.g., a dissertation and a publication based on the dissertation), the more complete report was included.

Coding Procedures, Effect Size Calculation, and Significance Testing


Literature Search Multiple sources were used to identify potential studies, including (a) more than 60 qualitative and quantitative reviews of research on the treatment of pediatric overweight; (b) reference lists from the studies cited in these reviews; and (c) more than 39,000 abstracts identified through searches of the PsycInfo, Dissertation Abstracts, and PubMed computer databases, using boolean combinations of keywords related to intervention, overweight, and age. In all, 865 studies were individually examined.

Inclusion and Exclusion Criteria Studies included in the current meta-analysis met the following inclusion and exclusion criteria: (1) The intervention (a) was designed to produce weight loss or prevention of further weight gain in youth who were already overweight; (b) had as its primary purpose the treatment of overweight rather than another condition such as high blood pressure or diabetes; (c) focused on change in weight-related health behaviors rather than the effects of surgical methods, controlled diets (e.g., high vs. low fiber), or inpatient treatment; (d) focused primarily on the evaluation of weightrelated treatment efficacy or effectiveness rather than change in variables such as blood pressure, food preferences, or self-esteem in programs with established efficacy or effectiveness. (2) The sample (a) was restricted to children and adolescents; samples that included 19-year-olds at baseline were included if most of the sample was 18 or younger, but college or adult samples were excluded even if some participants were younger than 19; (b) was limited to youth who were identified as overweight; programs targeting “at-risk” youth who were not overweight were excluded; (c) was selected for the intervention on the basis of overweight rather than another medical condition such as Prader–Willi syndrome or diabetes. (3) The study design was a between-groups design in which the treatment was compared either with a notreatment control group or to an alternate treatment group, with overweight participants in both groups; studies were excluded if the two treatment conditions varied only in terms of sample characteristics (e.g., boys vs. girls) or treatment duration rather than being a test of alternate treatments. (4) Treatment outcomes (a) were assessed in terms of weight, BMI (either unstandardized BMI or standardized zBMI), or percentage overweight, although additional outcomes (such as fitness or health behavior) may also have been assessed; (b) were assessed at the same time point (or after the same number of weeks of participation) in both groups. (5) The research report (a) reported empirical data; thus, case studies and qualitative studies were excluded; (b) provided the necessary information to compute an effect size; (c) was published in 2004 or earlier; (d) was reported in English. There were 98 studies that met these criteria. Of these, all studies that included a treatment– control comparison were retained (n ⫽ 40 studies) as well as any studies that included an

Two doctoral- or postdoctoral-level researchers used a coding manual to code each study and consensus discussions to resolve differences. Shadish, Robinson, and Lu’s (1997) Effect Size analysis software was used to calculate or estimate Cohen’s (1988) d, using the pooled standard deviation as the variance component. Each comparison-level effect size represented the magnitude of difference between outcomes in the treatment group relative to outcomes in the comparison group within the same study. Information from each study was coded so that better outcomes in the treatment group were represented by a positive effect size. If the two groups were compared on multiple related outcome measures (e.g., weight and BMI), the comparison-level effect size was an average effect size across these outcomes. Effect sizes at the end of treatment were calculated separately from effect sizes at follow-up. Group comparisons could be based on posttest scores or on change scores (taking into account the intraclass correlation); in both cases, however, effect sizes represented between-groups differences rather than within-group change. The effect size d was calculated directly from means, standard deviations, and group sizes or was estimated on the basis of other data such as t scores or chi-square values, using one of nearly 40 estimation methods available in the Effect Size analysis software (Shadish et al., 1997). Results reported simply as “not statistically significant” were estimated conservatively as d ⫽ 0 (Lipsey & Wilson, 2001). When results were reported both with and without statistical controls, we calculated effect sizes on the basis of results with statistical controls. Rooney and Murray’s (1996) correction formulas were used to adjust effect sizes when researchers used a nested design but did not use statistics appropriate for nested models. Significance testing was used to determine (a) whether the effect size from each treatment– control or alternate treatment comparison was significantly different from zero, (b) whether the average effect size across a set of comparisons was significantly different from zero, and (c) whether one set of comparisons generated a significantly larger effect size than another set (e.g., treatment– control effect sizes for programs with high vs. low parent involvement). All analyses were conducted using David B. Wilson’s macros for use with SPSS.2 Random effects models were used for significance testing because we were interested in making inferences about the entire population of studies from which these studies were drawn rather than limiting inferences only to the selected studies (Rosenthal, 1995). As opposed to fixed effects models, which adjust only for sampling variance, random effects models weight each study by the inverse of the combined effects of sampling variance and population variance (see Formula 14 –24 in Shadish & Haddock, 2009). For this reason, 2

These macros are available at the Web site http://mason.gmu.edu/ ⬃Edwilsonb/ma.html

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random effects models tend to produce more conservative estimates than fixed effects models.


Descriptive Information The studies used in the current analysis were reported between 1965 and 2004. The median treatment length was about 14 sessions, occurring over the course of 3 to 4 months. However, there was considerable diversity in length (ranging from 1 week to 104 weeks) and in number of sessions (ranging from 1 to 144). Although all participants were chosen because they were overweight, fewer than two thirds of the studies provided information about the severity of overweight at baseline. Samples were often described as meeting a cutoff, with the most common being 20% overweight. About half the studies focused on participants in middle childhood (ages 6 to 12 years). There were no studies that focused exclusively on preschoolers (5 and younger), and only four studies focused exclusively on adolescents (13 and older). All other studies included samples that crossed two or more age categories.

Average Effect Size in Treatment–Control Comparisons There were 66 treatment– control comparisons in the studies that met the selection criteria for this review. Each comparison-level effect size was weighted by a function of sample size (Lipsey & Wilson, 2001), and then effect sizes were averaged across all comparisons. The weighted least squares average effect size was d ⫽ 0.41, SE ⫽ 0.07, n ⫽ 66, significantly different from zero at p ⬍ .001, with a 95% confidence interval of 0.26 to 0.55. The test of homogeneity was rejected, Q(65) ⫽ 192.08, p ⬍ .001, indicating more heterogeneity in the effect sizes than would be expected due to random variation (Hedges & Olkin, 1985). Therefore, the overall average effect size should be interpreted with caution because this overall result may be moderated by study, program, or sample characteristics. The weighted least squares average effect size is not reported for the set of alternate treatment studies because this value would be difficult to interpret. Whereas effect sizes from treatment– control studies can be directly compared because they all share a common comparison group (i.e., a no-treatment control group), effect sizes from alternate treatment studies represent the effects of treatment relative to a wide range of comparison groups. In the current analyses on parent involvement, we report the average effect size only for small sets of alternate treatment studies in which all treatment groups and all alternative treatment groups shared relevant features. Table 1 (available online as supplementary material) shows a chronological list of all studies that included a treatment– control comparison. Each comparison is identified by a number that is also used in later tables and figures. Table 2 (available online as supplementary material) shows similar information for all studies that included an alternate comparison related to parent involvement.

Publication Bias The treatment– control studies were reported in 28 published papers and 12 unpublished theses or dissertations, and the alternate

treatment studies were reported in 30 published papers and six unpublished theses or dissertations. For both the treatment– control studies and the alternate treatment studies, the plot of effect size as a function of sample size was symmetrical and showed an inverted funnel shape, suggesting a lack of publication bias (Eggar, Smith, Schneider, & Minder, 1997). This suggests that including unpublished theses and dissertations did not substantially alter overall estimates of effect size. Inclusion of these studies thus provides a larger descriptive catalog of interventions and potentially greater statistical power.

Treatment Effectiveness This set of analyses addresses whether lifestyle inventions for youth who are overweight show positive results in a wide range of conditions. These results are summarized in Table 3 (available online as supplementary material). Study year. There was no significant correlation between comparison-level effect size and the year in which the study was reported (1965–2004). Nor did the association appear to be curvilinear, as the addition of quadratic and cubic terms did not explain significant additional variance in the multiple regression model. Randomization. In the treatment– control studies, comparisons using randomization produced effect sizes that were significantly different zero, as did studies using nonrandom methods of group assignment. There was no significant difference in the magnitude of effect size generated by these two types of study design. This comparison provides a useful gauge for interpreting the following results on other potential moderators. The effect size from randomized studies represented about 1⁄2 standard deviation difference between the treatment and control groups, which in these samples translated into about 14 pounds greater weight loss in the treatment group. Nonrandomized studies produced an effect size representing a difference of about 1⁄3 standard deviation, or 9 pounds, between the treatment and control groups. Participants in both study designs lost significant weight relative to control groups, and although effect sizes were larger in the randomized studies compared with the nonrandomized studies, the difference was not significant. Randomization was not a significant moderator of effect size. Treatment setting. Fewer than half the treatment– control studies provided information about treatment setting. Similar results were found in treatments conducted in community or school settings, treatments conducted in medical settings such as pediatricians’ offices or obesity clinics, and one treatment conducted in a physical training and research center. Methods for identifying participants. Treatment– control studies that selected participants using subjective methods such as a physician- or self-referral generated effect sizes that were similar in size to those from studies that used objective methods such as a BMI cutoff score. Only about half the studies provided information about recruitment, with the major methods being community advertisements, large-group group screenings, and physician referral. In these studies, effect size did not vary significantly depending on recruitment method. There was also no significant difference between programs that ruled out participation by severely overweight youth (defined differently by different researchers, with the least stringent criterion being 80% overweight) and those that were open to participants of any weight.


Multivariate analyses. Because of the high rate of missing data on treatment setting and recruitment methods, these variables were not considered further. Multiple regression analyses showed that, together, the other variables in this section accounted for a nonsignificant amount of variance in comparison-level effect size, with R2 ⫽ .08, n ⫽ 66, p ⫽ .19. The individual beta weights were each nonsignificant, consistent with the univariate results.

There were 45 treatment– control comparisons in which outcomes in both groups were assessed at the last treatment session. These programs are identified in Figure 1, in which the effect size representing between-groups differences at the end of treatment is plotted as a function of time since initiating treatment. For these programs, time since initiating treatment was the same as treatment length, which was less than 8 months in 90% of the programs. In programs lasting 0 to 4 months, the average effect size was d ⫽ 0.48, SE ⫽ 0.09, n ⫽ 31, a value that was significantly different from zero at p ⬍ .001. Programs lasting 4 to 8 months had an average effect size of d ⫽ 0.20, SE ⫽ 0.13, n ⫽ 12, p ⫽ .12. This set of programs included one study with a significant negative effect size (Seltzer & Mayer, 1970). In this study, the groups were not randomized, and the measure of weight-related outcomes did not take into account initial group differences in weight. Thus, although the treatment group did show substantial progress from baseline, the between-groups effect size showed that the control

group had significantly lower weight than the treatment group at the end of treatment. When this program was excluded from the analysis, the average effect size for programs lasting 4 to 8 months became significant, with d ⫽ 0.28, SE ⫽ 0.13, n ⫽ 11, p ⬍ .03, a value that was not significantly different from that generated in the shorter treatments, Qb(1) ⫽ 1.73, p ⫽ .19. In the treatment– control studies in which outcomes in both groups were assessed at the last treatment session, there were only two treatments lasting longer than 1 year. Yoshinaga, Sameshima, Miyata, Hashiguchi, and Imamura (2004) reported on a 14-month study in which participants and their parents received a 20-min counseling session about nutrition and exercise during monthly visits with their family physician. Treatment participants showed a significant drop in relative body weight compared with controls, with a comparison-level effect size of d ⫽ 0.94, SE ⫽ 0.18, p ⬍ .001. Mo-suwan, Junjana, and Puetpaiboon (1993) reported on a 26-month school-based program focused on diet and exercise. Relative to controls, participants showed significantly smaller increases in BMI during the first year, but there was a nonsignificant comparison-level effect size at the end of treatment, d ⫽ 0.03, SE ⫽ 0.25, p ⫽ .89. There were 11 treatment– control comparisons that had both a posttreatment assessment and at least one follow-up assessment of weight-related outcomes. These treatments ranged in length from 2 months to 5 months. Follow-up assessments were made anywhere from 2 months to 16 months after the end of treatment. Figure 2

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Months Since Initiating Treatment Figure 2. Posttreatment and follow-up comparison-level effect sizes for weight-related outcomes in treatment– control studies with follow-up data. These between-groups effect sizes are plotted as a function of time since initiating treatment. Study number can be found in Table 1.

shows effect sizes representing between-groups differences at both posttreatment and follow-up plotted as a function of time since initiating treatment. The average comparison-level effect size at the end of treatment was d ⫽ 0.31, SE ⫽ 0.12, n ⫽ 11, p ⬍ .001. At the final follow-up, the average effect size was d ⫽ 0.22, SE ⫽ 0.11, n ⫽ 11, a value that showed a trend toward significance at p ⫽ .06. This suggests that in these six studies, the advantages of treatment were still somewhat apparent an average of 10 months after the beginning (and 7 months after the end) of treatment.

Parent Involvement in Treatment Results of analyses regarding parent involvement are presented in Table 4 (available online as supplementary material). Results based on treatment– control comparisons are shown at the top of the table, and results of analyses based on alternate treatment comparisons are shown at the bottom of the table. Overall involvement. Overall parent involvement was rated as low if the youth had primary responsibility for most of the treatment, medium if the parents were involved in many aspects of treatment but the youth had primary responsibility for part, or high if the parents were involved in all aspects of treatment. In treatment– control studies, 27 programs were classified as low, 21 as medium, and 18 as high. The test of homogeneity was rejected, and post hoc comparisons showed significant differences between the high and medium groups, Qb(1) ⫽ 5.71, p ⬍ .02, and between the high and low groups, Qb(2) ⫽ 5.53, p ⬍

.02. We also examined alternate treatment studies that provided information relevant to the analysis of parent involvement. There were 17 alternate treatment comparisons in which the treatment of interest had a higher level of parent involvement than the alternate treatment. Studies comparing programs with high versus low involvement found statistically significant group differences. Together, the results in Table 4 suggest that youth in programs with high parent involvement had outcomes about 3⁄4 standard deviation better than controls and about 1⁄4 standard deviation better than youth in alternate programs with low parent involvement. In these samples, this translates to about a 21-pound difference between participants and controls and about a 7-pound difference between groups when programs with high and low parent involvement were compared within the same study. Parent attendance at sessions. Programs varied in terms of format; parents might attend sessions with their children, attend separate parent groups, or both. In treatment– control comparisons, programs that involved parents in any way produced comparisonlevel effect sizes that were not significantly different from those generated in youth-only programs. However, a different pattern of results emerged in 15 comparisons of alternate treatments in which a parent or parent–youth format was compared with a youth-only format. These studies showed a significant average effect size at the end of treatment, suggesting better outcomes in formats that included parents relative to those that did not.



Parent weight management as a part of treatment. In treatment– control studies, effect sizes did not vary significantly depending on whether the treatment focused on youth weight control only, focused on both youth and parent weight control, or focused on youth weight control but also tracked changes in parent weight. Among the alternate treatment studies, only two were designed to compare treatments that varied in terms of whose weight was the focus of treatment. Israel, Stolmaker, Sharp, Silverman, and Simon (1984) allowed parents to elect to focus on their own weight control or to serve as a helper in the youth’s treatment. The two groups did not differ in terms of youth (or parent) weight loss at the end of treatment. Epstein, Wing, Koeske, Andrasik, and Ossip (1981) also found a nonsignificant effect when comparing a treatment focused on both parent and youth weight with a treatment focused on youth weight only. Treatment components involving parents. Parent training in general behavior management was associated with significantly better outcomes. This training was typically in the form of insession discussions, although some programs also provided the book Living With Children (Patterson & Gullion, 1971). Table 4 shows that although programs with and without behavior management training produced significant outcomes, programs that did include this component generated effect sizes that were 3 times larger than those that did not. Youth whose parents received behavior management training had outcomes that were about 1 standard deviation better than controls, which in these samples translates to a difference of about 28 pounds between the treatment and control groups. For programs without this component, the difference between treatment and control groups was about 9 pounds. Effect sizes were also significantly larger when programs educated parents about nutrition and food preparation than when they did not. Although programs without nutrition education for parents did produce significant weight loss relative to controls (in these samples, about 7 pounds), programs fared even better when they did include parent education about food (a difference of about 14 pounds relative to controls). Treatment– control effect sizes did not vary depending on whether or not the program included the other treatment components listed in Table 4. There were three comparisons in which a treatment that provided parents with general training in behavior management was compared with a treatment that did not, and the average effect size from these studies indicated significant benefits associated with this type of parent training. There were 14 comparisons in which a treatment that expected parents to provide healthier foods was compared with a treatment that did not; in these studies, this treatment component was associated with significantly better outcomes. However, no significant effects were found for the other treatment components listed in Table 4. Multivariate analyses. Because of the large number of parent involvement variables, only those that were shown to be significant predictors of effect size in the univariate analyses were then included in the multiple regression analysis. As a group, these three variables accounted for significant variance in comparisonlevel effect size, with R2 ⫽ .17, n ⫽ 66, p ⬍ .01. The beta weights showed that general training in behavior modification remained a significant predictor at p ⬍ .03, but other individual predictors were no longer significant.

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Other Treatment Outcomes Thus far, the analyses have focused on treatment outcomes assessed in terms of weight, BMI, or percentage overweight. This information was available for all 66 treatment– control comparisons. As Table 5 (available online as supplementary material) highlights, a small number of studies also reported information about other outcomes. One benefit of treatment appeared to be improved eating habits. This finding was based on three studies that used food diaries or eating habit checklists to assess eating behaviors at the end of treatment. Two of these studies found large and statistically significant effect sizes in the treatments being tested (Shapiro, 1975; Stolmaker, 1986), whereas the other reported nonsignificant results for outcomes related to eating (Gutin et al., 1999). Table 5 also shows that parents of treatment participants showed significantly better weight management themselves, compared with parents of control groups in five studies. However, this finding appeared to be due to the large and significant effects in the Epstein, Wing, Koeske, and Valoski (1984) study, in which parents and children both received weight management treatment in the form of either a diet or diet and exercise group. In four other studies, parent weight was tracked, but parents did not receive weight management treatment; in these studies, the average effect size for parents’ weight-related outcomes was not significantly different from zero.

Retrospective Power Analyses Formulae provided by Hedges and Pigott (2001) showed that there was high statistical power to detect a medium effect size (d ⫽ 0.5) as significantly different from zero. The median estimate of power in these analyses was 0.95. As is common in meta-analysis (Hedges & Pigott, 2004), there was lower power when testing whether two or more groups of studies generated average effect sizes that were significantly different from each other. Formulae provided by Hedges and Pigott (2004) showed the median estimate of power in the moderator analyses to be 0.19.

Discussion Children and adolescents who are overweight are commonly treated with lifestyle interventions focusing on some combination of diet, activity, and change in weight-related health behaviors. This meta-analysis integrated the results of 66 treatment– control comparisons evaluating lifestyle interventions for pediatric overweight. Evidence from 59 comparisons of lifestyle interventions and alternate treatments provided additional information about the benefits of these programs. Together, these studies provided a large body of evidence to address issues of relevance to clinical care. In the current analyses, we examined evidence related to treatment effectiveness, treatment length, parent involvement, and additional benefits other than weight management. The results suggest that lifestyle interventions can be effective under a wide range of conditions not limited to the highly controlled conditions of efficacy studies. Similar results were found in studies that did and did not use random assignment, in samples that were identified using a variety of recruitment and screening methods, and in treatments conducted in a variety of settings. Together, these results suggest that lifestyle interventions for youth who are


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overweight are not only efficacious but also effective under a wide range of conditions. However, this conclusion must be considered speculative as it is based on null findings—that is, the absence of any significant difference in effect sizes generated from programs showing various characteristics. In addition, these results were sometimes based on small groups of studies. As is common in meta-analysis (Hedges & Pigott, 2004), retrospective power analysis showed limited statistical power to detect true differences between groups of studies, meaning that the null results should not be overinterpreted. An interesting finding was that programs from recent decades produced effect sizes that were similar to those produced in older studies. This finding is actually consistent with results reported by Haddock et al. (1994) and Epstein et al. (2007), and could suggest that newer programs are faring no better than older programs. However, as Epstein et al. note, this result may be misleading because recent cohorts are heavier and live in more obesiogenic environments. Indeed, in the current meta-analysis, studies after 1990 used selection criteria that were more stringent than most studies reported in earlier decades (e.g., a cutoff of 20% overweight rather than 10% overweight). In this respect, more recent programs may actually be outperforming programs from the 1960s, ’70s, and ’80s (Epstein et al.). Most studies provided no information about the number of severely overweight youth who participated. However, the question of treatment effectiveness for severely overweight youth has practical importance for two reasons. First, severely overweight youth may need more aggressive treatment (Dietz & Robinson, 2005; Spear et al., 2007), but there is little empirical support for outpatient treatments specifically tailored to this group (for an exception, see Levine, Ringham, Kalarchian, Wisniewski, & Marcus, 2001). Second, patients who self-present for treatment may be more severely overweight because many parents do not recognize the significance of weight problems (Eckstein et al., 2006; Etelson, Brand, Patrick, & Shirali, 2003) and thus may be less likely to seek treatment until the problem has substantially progressed. It will be important in the future research to examine the extent to which lifestyle interventions can assist youth who are severely overweight and the ways in which standard programs could be modified to address these patients’ needs. The results suggest that treatment participants show significantly better weight management than controls even in even relatively brief lifestyle interventions. Significant effects were seen in programs lasting less than 4 months, as well as in programs lasting up to 8 months. In six treatment– control studies with follow-up data, the average effect size was about 1⁄3 standard deviation at the end of treatment and about 1⁄4 standard deviation at the last follow-up. In these samples, this meant that the treatment group weighed about 9 pounds less than the control group at the end of treatment and was still about 7 pounds lighter an average of 7 months later. Together, what can these results tell us about the time needed for treatment to be effective? Compared with no intervention, interventions as brief as 4 months can be expected to produce significant change in measures such as BMI and percentage overweight, and the benefits should be evident for several months after treatment stops. Gradual change, however, is thought to be most beneficial, especially for younger children and for those who are heavier (Barlow & The Expert Commit-

tee, 2007), and this may be better accomplished in longer rather than shorter treatments. The results clearly suggest benefits of parent involvement in the treatment of youth who are overweight, with indicators of parent involvement accounting for nearly 20% of the variance in weight-related outcomes. A key component appeared to be the expectation that parents would change their own behavior as a way to help their child. Participants achieved better weight management when their parents were educated about food preparation and nutrition and were expected to provide healthy foods for their child. Participants also fared better when parents were provided training in behavior modification, although this benefit did not appear to be related to any one technique. These findings document the importance of targeting parent behavior change as a part of treatment. As others have noted, parent readiness to change is likely to be a key predictor of treatment success (Barlow & The Expert Committee, 2007). The current results suggest that parents may be more ready to make changes related to food preparation than changes related to activity. Consistent with earlier meta-analyses, lifestyle interventions produced significant benefits in terms of participants’ weight management relative to controls. A minority of studies also reported other outcomes as indicators of treatment success. For example, a small number of studies using food diaries and eating habits checklists showed that, on average, participants had significantly better eating habits than controls at the end of treatment. Because eating habits and other health-related behaviors are assumed to be an important mechanism for producing change, greater improvements in weight status may result from treatments that can effectively modify these health behaviors. In future research, within-group correlational analyses will be useful to assess the extent to which treatment affects healthrelated behaviors and, in turn, the extent to which these behaviors predict better weight management. Parent weight management was assessed in five treatment– control comparisons, but significant effects were found only when the parent was actively engaged in a weight loss program along with the overweight youth (Epstein et al., 1984). When there was not an explicit emphasis on parent treatment, parents did not appear to show any benefit in terms of their own weight management. This issue is important given that many parents of overweight youth are themselves overweight (Whitaker, Wright, Pepe, Seidel, & Dietz, 1997). Family-based programs that emphasize the role of parents as agents of change may be especially well suited to engage overweight parents and youth together in treatment and to assess the benefits (or drawbacks) of this approach. The current analyses integrated results from a wide range of programs and treatment settings. The variation across studies was important for providing evidence of treatment effectiveness, and the large number of studies allowed us to address several important questions related to clinical care. However, this variety also meant that the average effect size for a set of studies could be misleading. For example, we found that programs that taught parents about nutrition generated significantly larger effect sizes than programs that did not, but this finding ignores diversity in terms of how nutrition education was provided and in terms of programs’ treatment components as a whole. In this respect, meta-analytic findings should be seen as



a complement to, not a substitute for, knowledge gained in individual studies. This translational research provides encouraging evidence of the efficacy and effectiveness of lifestyle interventions for pediatric overweight. However, this evidence must be viewed as speculative and for the most part limited to middle childhood samples. The results suggest that interventions lasting only a few months can be expected to produce significant change, especially if they communicate an expectation that parents change their own behavior as a way to help their child. However, as Saelens and Liu (2007) note, many health care providers feel unprepared to implement lifestyle treatments, even though the increasing rates of pediatric obesity mean that health care providers will likely be seeing a greater number of overweight patients. This impending change will require a significant shift in thinking for the health care profession, including greater attention to how health care providers are trained to treat overweight (Caprio, 2006).

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