A Primary Care–Based, Multicomponent LifestyleIntervention for Overweight Adolescent Females
WHAT’S KNOWN ON THIS SUBJECT: Clinic-based weight controltreatments for youth have largely been designed forpreadolescent children and their families by using family-basedcare, a strategy that may be less appealing to adolescents as theybecome increasingly motivated by peer acceptance rather thanparental influence.
WHAT THIS STUDY ADDS: To our knowledge, this is the first studyto demonstrate the efficacy of a primary care–based,multicomponent lifestyle intervention specifically tailored foroverweight adolescent females and demonstrating a sustained effect(at 12 months) extending beyond the active 5-month intervention.
abstractBACKGROUND AND OBJECTIVE: Most clinic-based weight controltreatments for youth have been designed for preadolescent childrenby using family-based care. However, as adolescents become moreautonomous and less motivated by parental influence, this strategymay be less appropriate. This study evaluated a primary care–based,multicomponent lifestyle intervention specifically tailored for overweightadolescent females.
METHODS: Adolescent girls (N = 208) 12 to 17 years of age (mean 6SD: 14.1 6 1.4 years), with a mean 6 SD BMI percentile of 97.09 62.27, were assigned randomly to the intervention or usual care con-trol group. The gender and developmentally tailored intervention in-cluded a focus on adoptable healthy lifestyle behaviors and wasreinforced by ongoing feedback from the teen’s primary care physician.Of those randomized, 195 (94%) completed the 6-month posttreatmentassessment, and 173 (83%) completed the 12-month follow-up. Theprimary outcome was reduction in BMI z score.
RESULTS: The decrease in BMI z score over time was significantlygreater for intervention participants compared with usual care par-ticipants (20.15 in BMI z score among intervention participants com-pared with 20.08 among usual care participants; P = .012). The 2groups did not differ in secondary metabolic or psychosocial out-comes. Compared with usual care, intervention participants reportedless reduction in frequency of family meals and less fast-food intake.
CONCLUSIONS: A 5-month, medium-intensity, primary care–based,multicomponent behavioral intervention was associated with significantand sustained decreases in BMI z scores among obese adolescent girlscompared with those receiving usual care. Pediatrics 2012;129:e611–e620
AUTHORS: Lynn L. DeBar, PhD, MPH,a Victor J. Stevens,PhD,a Nancy Perrin, PhD,a Philip Wu, MD,b John Pearson,MD,a,b Bobbi Jo Yarborough, PsyD,a John Dickerson, MS,a
and Frances Lynch, PhDa
aKaiser Permanente Center for Health Research, Portland,Oregon; and bPermanente Northwest, Portland, Oregon
ABBREVIATIONSHMO—health maintenance organizationPCP—primary care providerPedsQL—Pediatric Quality of Life Inventory–Child ReportPHQ-A—Patient Health Questionnaire for AdolescentsQEWP-A—Questionnaire of Eating and Weight Patterns–Adoles-cent Version
This trial has been registered at www.clinicaltrials.gov(identifier NCT01068236).
www.pediatrics.org/cgi/doi/10.1542/peds.2011-0863
doi:10.1542/peds.2011-0863
Accepted for publication Nov 9, 2011
Address correspondence to Lynn DeBar, PhD, MPH, KaiserPermanente Center for Health Research, 3800 N. Interstate Ave,Portland, OR 97227. E-mail: [email protected]
Obesity prevalence among youth is ata historic high,with 16%of 6- to 19-year-olds overweight and 19% obese.1
Treating adolescents has particularpublic health importance becauseoverweight teens have longer-termhealth risks and greater probabilityof adult obesity than youth who developweight problems earlier in childhood.2–6
Furthermore, population-based studieshave found high rates of psychologicalsymptoms among obese adolescents,especially in females.7–12 Finally, potentialserious social and economic conse-quences exist for overweight adoles-cents who, over their lifetimes, havebeen found to have fewer years of edu-cation, lower family income, and higherpoverty rates.13,14
Youth clinic-based weight controltreatments have demonstrated somesuccess, but most have been designedfor preadolescent children and theirfamilies.15,16 Although promising, suchinterventions are usually focused onfamily-based care, a strategy generallyless appealing to adolescents as theybecome more autonomous and moti-vated by peer acceptance rather thanparental influence.17–19 Accordingly,some teen weight management studiessuggest superior results when teensand parents are seen separatedly.20,21
Also, some behaviorally based youthweight management interventions in-clude amix of adolescents and youngerchildren and are therefore not deve-lopmentally tailored to adolescents.22–25
Furthermore, most interventions havebeen conducted in specialty settings oracademic research clinics rather thanprimary medical care settings, whereweight problems are more often iden-tified and efficiently treated. Two pre-vious primary care–based treatmentstudies among overweight and obeseadolescents reported favorable changesin BMI,25,26 suggesting the promise ofproviding adolescent weight manage-ment programs within primary care
settings. Some adolescent weightmanagement efforts have achievedlimited success, but sustaining longer-term weight loss has been difficult.27–29
This study evaluated a primary care–based, multicomponent lifestyle in-tervention for overweight adolescentfemales. We hypothesized that, rela-tive to usual care, the intervenztionwould reduce BMI and improve se-lected metabolic health behavior out-comes. We also anticipated thatfocusing on easily adoptable healthylifestyle behaviors, rather than stricteradherence to caloric guidelines, mightimprove sustained weight manage-ment.
METHODS
Design
This randomized trial was conductedwithin a large health maintenance or-ganization (HMO) in the Pacific North-west between September 2005 andMay2009. The HMO Human Subjects Pro-tection Committee approved and mon-itored all study procedures. Parents orguardians provided informed consent,and adolescents provided assent. Thestudy design is presented in Fig 1.
Study Participants, Recruitment,Screening, and Randomization
Eligibility was limited to female healthplan members aged 12 to 17 years with
FIGURE 1Study design and participant flow.
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anage- andgender-adjustedBMI$90thpercentile. At the study’s outset, theCenters for Disease Control and Pre-vention guidelines identified youth withadjusted BMI at or above the 95thpercentile as overweight. However, welowered the eligibility criteria to the90th percentile to accommodate HMOpediatricians’ requests and to increasethe findings’ generalizability. Exclusioncriteria included: significant cognitiveimpairment or psychosis, severe obe-sity (BMI .45), use of medicationsknown to affect body weight, andpregnancy.
Potential participants who met selec-tion criteriawere identifiedbyusing theHMO’s electronic medical record. Aspart of the baseline assessment, allparticipants received physical exami-nations from their pediatric primarycare providers (PCPs), who were askedto review each potential recruit’smedical record before determiningappropriateness for study inclusion. Inaddition, PCPs were encouraged to re-fer their BMI-eligible adolescent femalepatients to the study, and recruitmentposters in pediatric primary careclinics prompted self-referral. Individ-uals who met selection criteria weremailed study invitations, which werefollowed by telephone calls from re-search staff.
An informationalmeeting for interestedfamilies preceded randomization. Eli-gible adolescents were randomized tothe intervention or control condition bya computer program using a well-validated procedure to balance ageand obesity severity.30 Project inter-ventionists informed participants oftreatment assignment to keep asses-sors masked.
The teen intervention compromised 90-minute groupmeetings conducted over5 months. Groups met 16 times, weekly
for 3 months and biweekly duringmonths 4 and 5. At each session, teenswereweighedandrevieweddietaryandphysical activity self-monitoring re-cords. If unable to attend a particularsession, teens were offered telephonesessions. The multicomponent inter-vention included the following: (1)change in dietary intake and eatingpatterns; (2) increasing physical ac-tivity by using developmentally tailoredforms of exercise (eg, exergaming); (3)addressing issues associated withobesity in adolescent girls (eg, de-pression, disordered eating patterns,poor body image); and (4) trainingparticipants’ PCPs to support behav-ioral weight management goals col-laboratively (Table 1).
In addition to caloric guidelines (1600–1800 kcal daily), we emphasized 3 mainareas for dietary change: decreasingportion sizes, limiting consumption ofenergy-dense foods, and increasingconsumption of lower energy–densefoods.31 Otherdietary strategies included:establishing regular meal patterns(especially breakfast),32 substituting
water for sugar-sweetened beverages,reducing fast-food consumption, andincreasing frequency of family mealsand fruit and vegetable consumption.Physical activity goals included: 30 to60minutes of physical activity at least 5days a week; 15 minutes of daily yoga;limiting screen time to 2 hours per day;and increasing “found exercise” op-portunities whenever possible (eg,taking stairs instead of elevators). Be-cause obese youth report fear of peervictimization, embarrassment, and lowself-confidence as reasons for notparticipating in physical activity andorganized sports,33–35 we chose coreactivities designed to overcome theseobstacles. We also chose to integrateexercise with play to help distract par-ticipants from the initial discomfort ofincreased physical activity.36 Participantswere provided with exergaming equip-ment (Konami Dance Dance Revolution;Konami Digital Entertainment, Inc, ElSegundo, CA) to encourage fun activitythey could do at home, either alone orwith peers or family members. We alsoincluded yoga-based stretching and
Generalizing skills (i.e.,eating at school, dining out,high-risk situations)
In-session yoga Eat family mealswhenever possible
Broader psychosocial issues:s Mood regulations Body images Self esteem
Dance Video Games &Play Stations providedto families as aid to meetphysical activity targets
Reduce portion sizes
s Media educationUse energy density as aguide in making decisionsabout healthy eating
s Sleep
12 group sessions for parents
Limited focus on decreasedcalorie consumptionPhysician visits (baseline,
post-treatment)Reduce fast food consumption
Health education andpsychoeducational materials
Replace high caloriebeverages with water
Increase physical activity to30-60 minutes per day
Practice yoga 15 minutes / day
Limit screen time
Lose 10-15 lbs. over 6 months
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strength training as in-session physi-cal activities to increase body aware-ness, core strength, and coordination.By providing teens with training in safeand basic yoga practices, equipment,an instructional booklet, and CD, weencouraged yoga practice outside thestudy sessions. In addition, interven-tionists introduced strategies for in-creasingphysical activity (eg, pedometers,resistance bands) to encourage par-ticipants to set goals tailored to theirinterests. Every session included re-viewing goals and problem solving toovercome barriers and challenges toincreased activity.
The intervention included discussion oftopics particularly pertinent to ado-lescent girls (eg, recognizing andavoiding disordered eating patterns,promoting body image, coping withfamily and peer teasing, minimizingemotional eating). We also taught spe-cific behavioral and cognitive tools forcoping, including: (1) regular self-monitoring of dietary intake, physicalactivity, and screen time; (2) stimuluscontrol and environmental changes,stepwise goal-setting, and problemsolving; (3) setting goals for increasingpleasant activities (as self-reward andalternatives to eating/screen time); and(4) cognitive restructuring techniquesto combat negative self-talk.
Teens were required to attend 5 of thefirst 6 intervention sessions and com-plete diet and exercise self-monitoringrecords to receive the exergaming equip-ment. Interventionists includedmaster’slevel nutritionists and health educatorsand doctoral level clinical psychologists.
Parent Support Meetings
Over the intervention’s first 3 months,parents were invited to separate,weekly group meetings, during whichstaff explained the nutritional andphysical activity principles the teenswould learn so that parents could helpsupport their daughters and reduce
potential barriers to success. In addi-tion, parents were encouraged to in-crease or maintain the frequency offamily meals, which are associated withimproved nutrition and decreased riskfor unhealthy weight control practicesamong youth.37–39 Finally, because highlevels of parental monitoring of teeneating behavior are associated withmore disordered eating among over-weight adolescent girls,40,41 we workedwith parents to encourage appropriateteen autonomy and healthier familyinteractions and improve understandingof how parents’ own attitudes, eatingbehaviors, monitoring, and commentsregarding their teen’s weight andshape may affect their daughters.
Pediatrician Involvement
To improve interactions with all of theiroverweight teen patients, pediatricproviders received study-sponsoredtraining in motivational enhancementtechniques for health behavior change.This training used the FRAMES approach(provide feedback about personal risk,responsibilityofpatient,advicetochange,menu of strategies, empathic style, andpromote self-efficacy). Study staffscheduled individual sessions for eachintervention participant and her PCP atstudy onset and 6 months later (aftercompletion of the group sessions). Theyalso provided PCPs with summaries ofthe teen’s current health habits (eg,meal patterns, physical activity) andareas that could be targeted for im-provement. PCPs were encouraged toassist patients in selecting 1 or 2 ofthese behavioral targets (eg, reducingscreen time, increasing physical activity,eating more fruits and vegetables,establishing regular meals).
Usual Care
Usual care participants received apacket ofmaterials, includingoutlinesofevidence-based approaches to weightmanagement for youth and adults, a
parents’ guide to help adolescentsmake healthy lifestyle changes, localresources for weight management andhealthy activity, and suggested booksand online materials on healthy lifestylechange. Usual care participants alsomet with their PCPs at the study onset toencourage healthy lifestyle changes,although PCPs were not given the tai-lored patient assessment summariesdescribed earlier in the intervention armfor use in their visit nor were usual careparticipants scheduled for a 6-monthstudy-related session with their PCPs.
Measures
Baseline measurements occurred be-fore randomization, and follow-up datawere collected by staff blinded to par-ticipant treatment assignment.
Anthropometry and MetabolicMeasures
Height and weight were measured withparticipants lightly clothed andwithoutshoes and taken 3 times for quality as-surance. Height was measured to thenearest 0.5 cm by using a Harpendenportable stadiometer (Holtain Limited,Crosswell, Crymych, Pemborokeshire,UK) calibrated monthly. Weight wasmeasured to the nearest 0.25 lb witha Healthometer electronic scale (Health-0-Meter 400kl, Sunbeam Products COLLC, Toledo, OH) calibrated monthly. BMIwas converted to z score during analy-sis.42 Blood samples were obtainedafter a minimum 10-hour overnight fast.
Certified dietary interviewers con-ducted 3 unannounced 24-hour tele-phone dietary recalls at baseline andagainat6-month follow-up.Participantswere trained to estimate portion size byusing real food and food models at thescreening visit and received visual aidsfor estimating portion sizes during re-calls. Recall data were entered into the
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ESHA database (ESHA Food Processor,version 8.1, 2003; ESHA Research Inc,Salem, OR). We adapted a 24-hourtelephone physical activity recall fromthe 7-day physical activity recall.43,44 Tolimit participant study burden, diet andphysical activity recalls were collectedat baseline and 6-month follow-up only.Otherquestionnairemeasures included:hours per week of screen time andaverage days per week breakfast waseaten (both adapted from the YouthRisk Behavior Survey45), average timesper week a “family” meal was eatentogether, and average times per weekfast food and sweetened beverages/sodas were consumed (adapted fromthe Project EAT Student Survey46). Useof other professional weight manage-ment services was assessed by usingquestions adopted from a previoushealth care utilization survey.47 Infor-mation on health/lifestyle behaviorsand utilization of weight managementservices was collected at each majorassessment point (baseline, 6-, and 12-month follow-ups).
Psychosocial Assessments
Self-report questionnaires at baseline,posttreatment, and 12-month follow-upassessed eating and mood disordersymptoms, body satisfaction, internal-izationofsocioculturalattitudes towardappearance, self-esteem, and quality oflife. Unhealthy attitudes and eatingpractices were assessed by using theQuestionnaire of Eating and WeightPatterns–Adolescent Version (QEWP-A48) with binge-related eating disorderscategorized as “disordered eating.” Weexamined changes in mood by using thedepression section of the Patient HealthQuestionnaire for Adolescents (PHQ-A49),with major depression categorized asa “mood disorder.” Body satisfactionwas assessed by using a modifiedversion of the Body SatisfactionScale.50,51 We measured perceivedpressure to conform to social norms re-garding female attractiveness by using
the Sociocultural Attitudes Towards Ap-pearanceScale(SATAQ-3).52 TheRosenbergSelf-Esteem Scale53 and the PediatricQuality of Life Inventory–(PedsQL54–56)were also included.
Sample Size and StatisticalAnalyses
Power computations were performedbyusingPASS2000 (NCSS, LLC, Kaysville,UT) fora repeatedmeasures analysis ofvariance design, assuming ana level of0.05 (2-tailed) and a correlation acrosstime of 0.50. Enrolling 100 participantsper study condition allowed power of0.98 to detect difference between amean 3% increase in BMI z score in thecontrol group and a mean 3% decreasein BMI z score in the intervention group.Baseline comparisons between usualcare and intervention groups wereconducted by using x2 and t tests.Generalized estimating equationswere used to test for differencesacross 3 time points in usual care andintervention. Specifically, we examinedif the pattern of outcomes change overtime differed between the usual careand intervention groups. Becausethese equations do not require sub-jects to have data at each time point, allrandomized participants were includedin the analyses consistent with anintention-to-treat approach.
RESULTS
Sample Characteristics
Adolescents (N = 208) 14.16 1.4 yearsof age, with a mean BMI percentile of97.096 2.27, were randomized into thetrial (Table 2). Compared with usualcare participants, intervention partic-ipants reported higher use of profes-sional weight management servicesduring the 6 months before enrollmentas well as more regular breakfasteating, but no other baseline charac-teristics differed significantly accordingto treatment assignment. Randomizedparticipants represented only a modest
proportion (8%) of the 2467 initiallyscreened (Fig 1). Although mostcommunity-conducted weight manage-ment trials rely only on self-referralsfrom an undefined population, in con-trast, we contacted all teens and fami-lies for whom health records indicatedpotential eligibility ($90th percentileBMI). This recruitment method includedthose unmotivated to enroll in this typeof study. Furthermore, unlike recruit-ment of adults (or even younger chil-dren and families) in which an adult canindependently elect to participate orhave their child and family partici-pate, the interest and willingnessof both parent(s) and teen to partic-ipate are critical for recruitmentinto this type of trial. Of those ran-domized, 195 (94%) completed the 6-month posttreatment assessment, and173 (83%) completed the 12-monthfollow-up.
Acceptability and TreatmentExpectations
Participants attended a mean 6 SD of10.3 6 5.1 of 16 intervention sessionsfor teens and 7.9 6 3.9 of 12 sessionsfor parents. Posttreatment ratings sug-gested that most participants rated theintervention services as high quality(4.4 6 0.8 for teens and 4.4 6 0.8 forparents on a 1–5 scale [5 being “ex-cellent”]) and reported that the pro-gram met their needs (4.0 6 1.0 forteens and 3.9 6 1.1 for parents ona 1–5 scale [5 being “definitely metneeds”]).
Primary and Secondary Outcomes
Theprimary outcome, age-adjustedBMIz score, is shown in Fig 2, and sec-ondary outcomes are shown in Table 3.The decrease in BMI z scores over timewas significantly greater for interven-tion participants compared with usualcare participants (P = .01); however,the intervention effect size was low-to-moderate (Cohen’s d =20.18 for BMI z
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score and 20.27 for BMI percentile).The 2 study groups did not differ sig-nificantly on change over time on anysecondary metabolic outcomes. Forpsychosocial outcomes, those in theintervention group reported greaterbody satisfaction (P = .03) and less in-ternalization of social norms regardingfemale attractiveness (P = .02) post-treatment compared with those inusual care. For health behaviors, dif-ferences were observed in frequencyof family meals (P = .03) and fast-foodconsumption (P = .02); those in theintervention reported less reductionin family meals frequency and less
fast-food intake compared with usualcare.
DISCUSSION
Thismedium-intensity,multicomponentbehavioral intervention resulted in amodestdecrease inweightstatusamongoverweight teen-aged girls (20.15 inBMI z score among intervention par-ticipants compared with20.08 amongusual care participants). To our knowl-edge, this is the first study to demon-strate the efficacy of a behaviorallybased intervention specifically target-ing teen-aged girls and demonstrating
a sustained effect (at 12 months) be-yond the active 5-month intervention.Those in the intervention group reportedmore frequent family meals and lessfast-food consumption. There were noother significant differences in repor-ted health behaviors, and no indicationthat the intervention increased disor-dered eating practices. Among inter-vention participants, changes betweenbaseline and posttreatment (6 months)in the magnitude of screen time re-duction (∼5 hours per week) and re-duction in reported energy consumption(a decrease of 240 kcal/day) is con-sistent with changes considered clini-cally significant by most PCPs. However,given the high variance for thesevariables, there were no statisti-cally significant differences betweenthe intervention and usual caregroups.
Despite the statistical significanceof ourprimary study outcome (BMI z score),the weight reduction magnitude wasmodest (Cohen’s d = 20.27 for BMIpercentile and 20.18 for BMI z score),suggesting that a more intensive in-tervention might achieve more clinicallysignificant outcomes. Previous primarycare interventions targeting adoles-cents found somewhat larger effects,25,26 although these results may not becomparable because participant pop-ulations were at least 50% male and 1study25 included younger school-agedchildren. Furthermore, our partic-ipants reported frequent dieting anduse of professional weight manage-ment services in the 6 months beforestudy enrollment, so they likely hadpreviously adopted some weight man-agement strategies—and thereforeachieved more modest effects thanthose observed in overweight teenboys, who are less likely to reportprevious weight control attempts.57,58 Amodest proportion (17%–18%) of par-ticipants in both study arms reportedusing ancillary professional services
TABLE 2 Baseline Characteristics of Study Participants
Characteristic Intervention(n = 105)
Usual Care(n = 103)
Test Statistic P
Anthropometric measuresWeight, mean 6 SD, lb 189.68 6 33.47 186.4 3 6 34.39 t = 0.69 .492BMI, mean 6 SD, kg/m2 32.03 6 4.79 31.84 6 4.63 t = 0.29 .771BMI percentile, mean 6 SD 97.09 6 2.27 97.10 6 2.29 t = 20.03 .977Obese ($95th percentile BMI), n (%) 88 (83.81) 87 (84.47) x2 = 0.02 .897Severely obese ($97th percentile BMI),
n (%)65 (61.90) 70 (67.96) x2 = 0.84 .360
DemographicAge, mean 6 SD, y 14.12 6 1.48 14.03 6 1.50 t = 0.46 .647Grade in school, n (%) x2 = 0.00 .9486th–8th 55 (52.88) 54 (52.43)9th–12th 49 (47.12) 49 (47.57)Race/% white, n (%) 75 (71.43) 75 (72.82) x2 = 0.05 .824Family income .$75 000, n (%) 40 (40.0) 35 (36.46) x2 = 0.26 .610Menarche (% yes), n (%) 93 (88.57) 86 (85.15) x2 = 0.53 .467
Psychosocial functioningDisordered eating (QEWP-A), n (%) 13 (12.38) 13 (12.62) x2 = 0.01 .937Mood disorder (PHQ-A), n (%) 10 (9.52) 12 (11.65) x2 = 0.27 .601Quality of life (PedsQL), mean 6 SD 71.11 6 16.22 68.81 6 16.55 t = 21.02 .311
Health behaviorsScreen time, mean 6 SD, h/wk 30.54 6 14.91 32.23 6 15.43 t = 20.80 .423Physical activity recall, mean 6 SD,min/day
55.35 6 51.81 49.68 6 39.47 t = 20.88 .379
METa/day, mean 6 SD 4.28 6 3.97 3.80 6 3.13 t = 0.97 .334Team sports participation, n (%) 33 (31.73) 33 (32.35) x2 = 0.01 .924Eat breakfast, mean 6 SD, days/wk 4.86 6 2.47 4.17 6 2.60 t = 1.97 .051Family meals, mean 6 SD, times/wk 3.85 6 2.55 4.34 6 2.51 t = 21.42 .158Fast-food, mean 6 SD, times/wk 1.17 6 1.06 1.27 6 1.12 t = 20.69 .489Total kilocalories per day (24-h dietaryrecall), mean 6 SD
1601.36 6 452.73 1583.95 6 502.92 t = 0.26 .795
% of calories from fat (24-h dietaryrecall), n (%)
NA (32.53) NA (32.78) x2 = 20.27 .790
Self-reported dieting in previous 6 mo,n (%)
93 (88.57) 83 (81.37) x2 = 2.04 .147
Use of professional weight managementservices during previous 6 mo, n (%)
37 (35.24) 20 (19.42) x2 = 6.54 .011
Data are presented as mean 6 SD unless otherwise indicated. MET, metabolic equivalent; NA, not applicable.a MET is equivalent to a metabolic rate consuming 1 calorie per kilogram of body weight per hour (http://www.sizes.com/units/metequiv.htm).
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for weight control during the activeintervention. Furthermore, our partic-ipants had high overall BMI at studyonset (.97th percentile for age andgender on average). Therefore, oursample may have been treatment re-sistant, as more severely obese youthare significantly more likely to havepersistent weight problems as adults59
and obtaining sustained decreases inobesity in this population has proveddifficult.60 Finally, because our pilotwork for the study suggested sub-stantial teen and parent sensitivity tothe teen’s identification as overweight,we purposefully emphasized goals toimprove body image and self-esteemwhile learning about healthy choicesfor eating and exercise, and explicitlyde-emphasized weight management.Our results suggest that body imagewas improved by the intervention.
There were important differences inour intervention approach that, al-though purposeful, may have attenu-ated its overall impact. Unlike the vast
majority of behavioral weight lossinterventions, we de-emphasized calo-riecounting.Weanticipated thatdietarychanges related to decreasing energydensity of consumed foods and estab-lishing healthier eating patterns wouldproduce more achievable and sustain-able results; unfortunately, these guide-lines may not have been adequate inachieving clinically meaningful caloricreductions and sustained weight loss.Finally, rather than adopting a morefamily-centric approach, we purposelyfocused on helping teens manage theirweight with more autonomy. Yet pre-vious interventions, particularly withyounger children, have demonstratedthat the most robust weight man-agement occurs when parents alsoadopt targeted lifestyle changes.61
This finding suggests that an inter-vention which actively targets parentlifestyle changes (rather than focusing,as this intervention did, primarilyon supporting the teen’s efforts) mayhave the benefit of allowing teen auton-omy while supporting healthy weight
management and lifestyle changeswithin the broader family.
A limitation of the study was the lack ofracial/ethnic and socioeconomic di-versity among study participants, par-ticularly given known health disparitiesrelated to obesity.1,62,63 As children ofworking insured parents, study partic-ipants represent this sizable sector ofthe population. Yet, we acknowledgethat the results might not be generaliz-able to other subpopulations.
A strength of our study was our in-clusion of participants with comorbidmoodanddisordered eating practices;we believe this was important to in-crease generalizability given thehigher incidence of such problemsamong overweight youth. Also, untilrecently, most research-based youthobesity interventions have been con-ducted in university settings andtherefore may not have been repre-sentative of efforts in the community.Increasingly, however, health plansare adopting practices to identify
FIGURE 2Change over time in BMI z scores.
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members who may benefit from simi-lar health behavior interventions;therefore, our efforts to expand eligi-bility may render our results moregeneralizable.
CONCLUSIONS
A 5-month, medium-intensity, primarycare–basedmulticomponent behavioral
intervention was associated with sig-nificant and sustained decreases inBMI z score among obese adolescentgirls when compared with those ran-domized to receive usual care. Al-though the magnitude of the effectwas modest, these early findingssuggest the promise of interventionsdelivered within primary care settings
tailored specifically for teen-agedgirls. Future research should con-sider more intensive models buildingon these foundational elements; namely,whether adoption of specific caloric andactivity guidelines as well as more ac-tive participation of parents and otherfamily members may enhance teenoutcomes.
TABLE 3 Twelve-Month Changes in BMI and Secondary Health Outcomes
Measure Full Intervention(n = 105)
Usual Care(n = 103)
Wald x2 Group 3 TimeP value
Baseline 6 mo 12 mo Baseline 6 mo 12 mo
Main outcome measure n = 105 n = 100 n = 90 n = 103 n = 95 n = 83Weight, lb 189.68 (33.47) 190.05 (35.46) 194.56 (38.20) 186.43 (34.39) 190.01 (37.32) 193.50 (37.35) 8.40 0.015BMI percentile 97.09 (2.27) 95.80 (4.22) 95.19 (6.79) 97.10 (2.29) 96.50 (2.91) 96.28 (3.31) 5.41 0.067BMI z score 2.00 (0.34) 1.88 (0.41) 1.85 (0.46) 2.00 (0.33) 1.94 (0.38) 1.92 (0.39) 8.77 0.012
Total kcal/day (ESHA) 1601.36 (452.73) 1361.32 (412.14) — 1593.95 (502.92) 1425.00 (458.72) — 0.97 0.325% of calories from fat(24-h dietary recall)
32.53 32.54 — 32.78 33.77 — 0.59 0.441
OtherUse of professionalweight managementservices duringprevious 6 mo, %
35.24 16.48 16.67 19.42 18.07 12.00 3.56 0.169
Data are presented as mean6 SD unless otherwise indicated. BSS, Body Satisfaction Scale; HDL, high-density lipoprotein; LDL, low-density lipoprotein; MET, metabolic equivalent; PAR, physicalactivity recall; RSE, Rosenberg Self-Esteem Scale; SATAQ, Sociocultural Attitudes Towards Appearance Scale.a MET is equivalent to a metabolic rate consuming 1 calorie per kilogram of body weight per hour; http://www.sizes.com/units/metequiv.htm.
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DOI: 10.1542/peds.2011-0863 originally published online February 13, 2012; 2012;129;e611Pediatrics
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Adolescent FemalesBased, Multicomponent Lifestyle Intervention for Overweight−A Primary Care
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