Assessing Weight-Related Quality of Life in Adolescents

doi:10.1038/oby.2006.59

Obesity (Silver Spring). Author manuscript; available in PMC 2008 May 9.

Published in final edited form as:

Obesity (Silver Spring). 2006 March; 14(3): 448–457.

doi: 10.1038/oby.2006.59

PMCID: PMC2374918

NIHMSID: NIHMS41943

Assessing Weight-Related Quality of Life in Adolescents

Ronette L. Kolotkin,^*^† Meg Zeller,^‡ Avani C. Modi,^‡ Gregory P. Samsa,^§^¶ Nicole Polanichka Quinlan,^# Jack A. Yanovski,^** Stephen K. Bell,^†† David M. Maahs,^‡‡ Daniela Gonzales de Serna,^§§ and Helmut R. Roehrig^‡

^*Obesity and Quality of Life Consulting, Durham, North Carolina

^†Departments of Community and Family Medicine, Duke University Medical Center, Durham, North Carolina

^§Center for Clinical Health Policy Research, Duke University Medical Center, Durham, North Carolina

^¶Departments of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina

^‡Division of Psychology, Cincinnati Children’s Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, Ohio

^#Department of Psychology, Social and Health Sciences, Duke University, Durham, North Carolina

^**Unit on Growth and Obesity, National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland

^††Children’s Health System, Children’s Behavioral Health, Birmingham, Alabama

^‡‡Barbara Davis Center for Diabetes, University of Colorado Health Sciences Center, Denver, Colorado

^§§Department of Internal Medicine, University Hospital, Albuquerque, New Mexico.

Address correspondence to Ronette L. Kolotkin, Obesity and Quality of Life Consulting, 1004 Norwood Avenue, Durham NC 27707. E-mail: rkolotkin/at/qualityoflifeconsulting.com

See other articles in PMC that cite the published article.

Abstract

Objective

The development of a new weight-related measure to assess quality of life in adolescents [Impact of Weight on Quality of Life (IWQOL)-Kids] is described.

Research Methods and Procedures

Using a literature search, clinical experience, and consultation with pediatric clinicians, 73 items were developed, pilot tested, and administered to 642 participants, 11 to 19 years old, recruited from weight loss programs/studies and community samples (mean z-BMI, 1.5; range, –1.2 to 3.4; mean age, 14.0; 60% female; 56% white). Participants completed the 73 items and the Pediatric Quality of Life Inventory and were weighed and measured.

Results

Four factors (27 items) were identified (physical comfort, body esteem, social life, and family relations), accounting for 71% of the variance. The IWQOL-Kids demonstrated excellent psychometric properties. Internal consistency coefficients ranged from 0.88 to 0.95 for scales and equaled 0.96 for total score. Convergent validity was demonstrated with strong correlations between IWQOL-Kids total score and the Pediatric Quality of Life Inventory (r = 0.76, p < 0.0001). Significant differences were found across BMI groups and between clinical and community samples, supporting the sensitivity of this measure. Participants in a weight loss camp demonstrated improved IWQOL-Kids scores, suggesting responsiveness of the IWQOL-Kids to weight loss/social support intervention.

Discussion

The present study provides preliminary evidence regarding the psychometric properties of the IWQOL-Kids, a weight-related quality of life measure for adolescents. Given the rise of obesity in youth, the development of a reliable and valid weight-related measure of quality of life is timely.

Keywords: health-related quality of life, Impact of Weight on Quality of Life-Kids, weight loss, pediatric, adolescent

Introduction

Current estimates indicate that ~16% of children and adolescents are overweight, and an additional 15% are considered at risk for becoming overweight (1,2). Not only has the prevalence of pediatric overweight increased, but the degree of overweight is becoming more severe (3). Although overweight youth may experience significant health consequences associated with their weight (4), one of the most salient consequences of pediatric obesity may be psychosocial in nature (5,6).

Health-related quality of life (HRQOL)¹ is defined as the impact of health or disease on physical, mental, and social well-being from the patient’s point of view (7). Generic measures of pediatric HRQOL, such as the Child Health Questionnaire (8) or the generic core scales of the Pediatric Quality of Life Inventory (PedsQL) (9), contain general items that are applicable to a wide variety of populations and allow for comparisons across disease groups. Because generic instruments may not be specific enough to provide information about the particular quality of life issues associated with a specific disease, condition-specific measures are often developed. Condition-specific instruments focus on the domains, characteristics, and complaints most relevant to a particular disease or condition. Additionally, condition-specific instruments are frequently more responsive to changes after treatment than generic instruments (10). Because generic and condition-specific instruments assess different aspects of HRQOL, most often clinical research questions require a combination of condition-specific and generic measures (11–13). Although there are a number of condition-specific measures developed for pediatric conditions, e.g., asthma (14), cystic fibrosis (15), diabetes (16), and juvenile rheumatoid arthritis (17), to date, there are no weight-related quality of life measures for youth.

In the adult obesity literature, HRQOL has been assessed using generic measures (18–21), condition-specific measures (i.e., weight-related) (22–24), or a multi-method approach (25–28). Numerous studies using generic measures to investigate the association between BMI and HRQOL in adults have found differences between obese and non-obese persons on the physical domains of quality of life but not on the psychosocial domains (19,29–31). In contrast, weight-related measures have discriminated among BMI groups on the psychological and emotional domains of functioning, as well as the physical domains (32,33). Furthermore, weight-related measures have shown greater responsiveness to weight loss than generic measures in studies of adult obesity (27,34).

Although interest in assessing the HRQOL of children and adolescents is growing (35–37), few studies have examined self-reported HRQOL in obese youth. Obese youth have reported more impaired generic HRQOL than youth with asthma and atopic dermatitis (38), instrument norms on healthy children and adolescents (39), and normal-weight youth from population-based community samples (40,41). These data highlight the significant impact of overweight and obesity on children’s and adolescents’ generic HRQOL. However, generic measures of HRQOL in pediatric obesity have their limitations. For example, generic measures have identified differences across BMI groups but on only some domains of HRQOL. Swallen et al. (41) have found statistically significant differences among BMI groups for general health and functional limitations but not for psychosocial domains such as school/social functioning, self-esteem, and depression. Similarly, Williams et al. (40) found differences across BMI groups for physical and social domains but not for school and emotional domains. Thus, data from both the adult and pediatric obesity literature support the value of developing and using measures to assess weight-related HRQOL in pediatric obesity.

The present study describes the development and validation of a measure of weight-related quality of life for adolescents, the Impact of Weight on Quality of Life (IWQOL)-Kids. Preliminary reliability and validity are assessed. It was hypothesized that the IWQOL-Kids would support factors that are: internally consistent (α> 0.70), able to discriminate among weight status groups (non-overweight, at-risk-for-overweight, overweight/obese), convergent with collateral measures (e.g., PedsQL), and responsive to change after a weight loss/social support intervention.

Research Methods and Procedures

Participants

Data were pooled from multiple sites where youth were participating in site-specific psychosocial research or clinical protocols (N = 642). Demographic and weight status characteristics of the sample are presented in Table 1. The at-risk-for-overweight (BMI between 85th and 95th percentiles, N = 64) and the overweight/obese (BMI ≥ 95th percentile, N = 362) participants were youth seeking weight loss treatment, youth who had one or both parents with a lifetime BMI > 25 kg/m² recruited from schools and physicians’ offices for ongoing metabolic studies, and youth from a school-based community sample. Non-overweight participants (BMI < 85th percentile, N = 216) included healthy controls in a study of pediatric chronic illnesses and community youth recruited from middle schools and high schools. Participants who had BMI ≤ 10th percentile (N = 17) were excluded from all analyses. Race/ethnicity data were available for 97% of participants, of whom ~54% were white, non-Hispanic, 32% African-American, 7% white, Hispanic, and 7% other.

Table 1

Subject characteristics

Measures

IWQOL-Kids

Three of the study authors (R.L.K., M.H.Z., and H.R.R.) wrote 73 items. Item content was derived from both the published literature on childhood and adolescent obesity and anecdotal material based on clinical exposure to youth undergoing pediatric weight management treatment. All items were written to begin with the phrase, “Because of my weight,” to orient the responses to be weight-specific (42). Items were modeled after the IWQOL-Lite (32,43) and the IWQOL (42,44), both of which assess weight-related quality of life in adults. Response options ranged from always true (1) to never true (5). Items were pilot-tested for readability with older children and adolescents at one site (Cincinnati Children’s Hospital Medical Center), and wording was subsequently modified. The age range of 11 to 19 years was chosen due to appropriateness of both language and conceptual comprehension of items.

PedsQL

The PedsQL is a generic HRQOL self-report measure with complementary scales for children (ages 8 to 12) and adolescents (ages 13 to 18) (9). The measure consists of four core scales (physical, emotional, social, and school), two broad domain scores (physical and psychosocial functioning), and a total score. Scales are standardized, and scores range from 0 to 100, with higher scores representing better quality of life. The PedsQL has been shown to be both reliable and valid, with internal consistency reliability coefficients approaching or exceeding 0.70.

Anthropometric Measures

Participants’ body weights and heights were recorded by trained research personnel using calibrated scales and stadiometers. Participants were weighed and measured without shoes. BMI values were calculated (kilograms per meter squared) and standardized (z-BMI) using age-and gender-specific median, standard deviation (SD), and power of the Box-Cox transformation (least mean square method) based on national norms from the Centers for Disease Control and Prevention (45).

Procedures

Data were collected either as part of an ongoing clinical or research protocol or a protocol specific to the aims of the present study. Approval for each protocol was obtained from site Institutional Review Boards. Written parental consent and participant assent were obtained for all participants. Participants completed the 73-item version of the IWQOL-Kids and the PedsQL. Subjects at one site (weight loss camp) completed the IWQOL-Kids pre- and post-treatment.

Statistical Methods

Exploratory factor analyses using principal components with promax rotation were performed on the 73-item pool. Items were preferentially deleted for one or more of the following reasons: high cross-loadings, high pair-wise correlations with other items, or redundant item content (e.g., lack of self-confidence, unsure of self). A meaningful factor structure was determined based on simple structure (46), and internal consistency coefficients were calculated for these factors. Next, the construct validity of these factors was examined by tests of mean group differences among BMI groups (ANOVA) and between clinical and community samples (Student’s t test), as well as by Spearman correlations with z-BMI. Pearson correlations were also calculated between factors and PedsQL. Gender and race differences in factor scores, when controlling for z-BMI, were also examined. In an effort to assess the sensitivity of the IWQOL-Kids, effect sizes were calculated comparing the highest and lowest BMI groups. Additionally, scale changes were calculated (one-sample paired Student’s t test) for a subset of the population who participated in a weight loss/social support intervention. Finally, effect sizes were estimated by first creating difference scores for each subject (i.e., post-treatment scores minus baseline scores), then by dividing the mean of these difference scores by its SD.

Results

Factor Analysis

The entire data set (N = 642) was examined for missing values. Missing values were noted for 149 subjects on at least one of the 73 items; thus, these participants were excluded, and a final sample of 491 participants was retained for the exploratory factor analysis. The pattern of missing items appeared to be uninformative. Eigenvalues supported consideration of a three- to five-factor solution. Each of these solutions was examined with respect to the pattern of item loadings and cross-loadings, and a four-factor solution was deemed best because it described the separation of moderate numbers of items into factors that were statistically distinct and conceptually interpretable. Although a five-factor solution was considered initially, it was not pursued because items on the fourth and fifth factors appeared similar in content, and they loaded onto a single factor. Moreover, the number of items loading onto these last factors was small.

IWQOL-Kids Scales and Items

Results of the iterative analyses described above resulted in a 27-item instrument consisting of four scales: physical comfort (six items), body esteem (nine items), social life (six items), and family relations (six items). The scales and corresponding items are presented in Table 2, along with factor loadings from the exploratory factor analysis. The Eigenvalues (and percentage of variance) for each scale were: physical comfort, 2.89 (11%); body esteem, 13.7 (51%); social life, 1.1 (4%); and family relations, 1.4 (5%). All items loaded between 0.51 and 0.87 on their corresponding factors and <0.26 on all remaining factors. Internal consistency coefficients (Cronbach’s α) for the individual scales were strong, ranging from 0.88 to 0.95 for scales and equal to 0.96 for total score (Table 2). Factor intercorrelations were positive and ranged from 0.32 to 0.65 (Table 3).

Table 2

Exploratory factor loadings

Table 3

Scale intercorrelations and convergence

The physical comfort scale assessed adolescents’ perceptions of how weight impacts their physical mobility and comfort, such as difficulty moving around and body limitations. The body esteem scale reflected adolescents’ preoccupation with weight and appearance, as well as how they feel about themselves and their body. The social life scale assessed adolescents’ perceptions of how they are treated within their social environment and their ability to establish friendships as a result of their weight. The family relations scale reflected adolescents’ perceptions of what family members think and feel about them due to their weight status. The score on each scale (physical comfort, body esteem, social life, and family relations) was calculated as an unweighted sum of that scale’s constituent items and then transformed to 0 to 100 scoring, where 100 represents the best quality of life, and 0 represents the worst quality of life. For computation of the total score, the unweighted sum of all of the items was used, and then scores were similarly transformed to the 0 to 100 scoring.

Discriminant Validity

Comparison of BMI Groups

IWQOL-Kids scales were significantly and inversely related to z-BMI (p < 0.0001): physical comfort (r = −0.51), body esteem (r = −0.51), social life (r = −0.48), family relations (r = −0.25), and total score (r = −0.54) for the total sample (N = 642). Differences in mean IWQOL-Kids scores by BMI group (non-overweight, at-risk-for-overweight, overweight/obese) were examined for each scale (Table 4). Significant differences in groups were found for physical comfort [F(2,639) = 101.7; p < 0.0001], body esteem [F(2,639) = 122.3; p < 0.0001], social life [F(2,639) = 98.5; p < 0.0001], family relations [F(2,639) = 26.7; p < 0.0001], and total score [F(2,639) = 138.1; p < 0.0001]. Post hoc analyses indicated significant differences between the non-overweight and overweight/obese groups for all scales, with overweight/obese adolescents reporting poorer functioning (p < 0.0001). Similarly, significant differences were also noted between the at-risk-for-overweight and overweight/obese groups for all scales (p < 0.0001). Furthermore, a significant difference was noted between non-overweight and at-risk-for-overweight adolescents on the body esteem scale (p < 0.05), with at-risk-for-overweight children reporting lower scores.

Table 4

Mean IWQOL-Kids scores by BMI group

Comparison of Clinical and Community Samples

Adolescents seeking weight management treatment (n = 292) reported poorer weight-related quality of life than community youth (n = 350) after controlling for weight status. Significant differences were found on all IWQOL-Kids scales: physical comfort [F(2,638) = 65.6; p < 0.0001], body esteem [F(2,638) = 60.3; p < 0.0001], social life [F(2,638) = 46.2; p < 0.0001], family relations [F(2,638) = 9.2; p < 0.01], and total score [F(2,638) = 71.2; p < 0.0001].

Associations with PedsQL: Convergent and Discriminant Validity

As expected, the highest correlations (Table 3) between IWQOL-Kids and PedsQL scales were obtained on similar domains (e.g., IWQOL physical comfort with PedsQL physical), supporting convergent validity of the IWQOL-Kids. Additionally, lower correlations were found between dissimilar constructs on the IWQOL-Kids scales and the PedsQL (e.g., IWQOL-Kids family relations, PedsQL school), showing evidence of discriminant validity.

In an effort to determine how the sensitivity of the IWQOL-Kids compared with the sensitivity of the PedsQL in this data set, effect sizes were calculated comparing the highest and lowest BMI groups. For the IWQOL-Kids (Table 4), effect sizes exceeded 1.00 for all scales except family relations. For the PedsQL, effect sizes were 0.95, physical; 0.46, emotional; 0.80, social; 0.47, school; 0.71, psychosocial summary; and 0.86, total. Noteworthy results of this comparison were the ability of both instruments to discriminate between the highest and lowest BMI groups and the greater sensitivity of the IWQOL-Kids.

Responsiveness to Weight Change

Changes in IWQOL-Kids scores were examined in relation to changes in BMI in weight camp participants (n = 80) (Figure 1). The mean BMI change for weight camp participants was a reduction of 3 BMI points (range of reduction, 0.5 to 7.4 kg/m², SD = 1.4). Significant improvements (p < 0.0001) were found on all IWQOL-Kids scales after intervention: physical comfort, 9.95; body esteem, 17.89; social life, 13.54; family relations, 9.84; and total score, 13.43. Pre- to post-effect sizes were as follows: physical comfort, 0.43; body esteem, 0.72; social life, 0.60, family relations; 0.41; and total score, 0.75.

Figure 1

Changes in IWQOL-Kids scores after weight loss camp intervention. Significant differences between pre- and post-weight loss camp intervention (p < 0.0001).

Gender and Race Differences

Gender differences were examined on IWQOL-Kids scaled scores adjusted for z-BMI. Significant differences were demonstrated on body esteem [F(1,641) = 26.6; p < 0.0001] and total score [F(1,641) = 10.0; p < 0.01], with females reporting lower scores. No significant gender differences were noted on the physical comfort, social life, and family relations scales. Race differences were also examined between the two largest racial groups represented in the sample (N = 334, white, non-Hispanic; N = 198, African-American). After adjusting for z-BMI, significant race group differences were demonstrated for physical comfort [F(1,529) = 8.0; p < 0.01], body esteem [F(1,529) = 44.0; p < 0.0001], social life [F(1,529) = 13.0; p < 0.0001], and total score [F(1,529) = 27.2; p < 0.0001], with white, non-Hispanic youth reporting lower scores. No significant race differences were noted on the family relations scales.

Discussion

The overall purpose of this study was to develop and evaluate the reliability and validity of the IWQOL-Kids, a 27-item measure of weight-related quality of life for adolescents (ages 11 to 19). These preliminary analyses provide support for the measure’s strong psychometric properties, discrimination among BMI groups and between clinical and community samples, and responsiveness to a weight loss/social support intervention. Four factors, accounting for 71% of the variance, were identified, including physical comfort, body esteem, social life, and family relations.

The items on the physical comfort scale assess one’s perception of how weight impacts mobility and comfort in everyday life (e.g., difficulties fitting into seats, bending over, climbing stairs, or crossing legs). These physical discomforts are known to be significant issues for obese adults (42,47); however, to our knowledge, there are no studies documenting the impact of these physical discomforts in obese youth. Although existing generic measures of HRQOL assess one’s general ability to run or play sports (9) or strength and endurance (48), the IWQOL-Kids physical comfort scale specifically addresses bodily comfort associated with an individual’s weight status.

The body esteem scale assesses the impact of weight on body self-perceptions and appearance. This domain finds empirical support from the broader pediatric obesity literature in that data have shown consistently that obesity in youth is associated with poor body-esteem or body image (49) and poor self-concept (50,51). As expected, female (52,53) and white, Non-Hispanic (54) adolescents reported greater impairment in body esteem when compared with males and African-American youth, respectively. Given its novelty and demonstrated sensitivity, this domain, which is not assessed on existing generic HRQOL measures, may prove important to intervention research focusing on weight change.

Although social functioning is often assessed in both pediatric and adult measures of HRQOL, the social life scale of the IWQOL-Kids asks adolescents to examine their social relations within the context of their weight status. It is known that obese adolescents are more socially isolated than their non-overweight peers (55) and have fewer friendships (56). Obese youth report more victimization by peers (57) and are subject to more stigmatization (e.g., name-calling, teasing) (58–61). The IWQOL-Kids social life domain captures the adolescents’ perceptions of their peer group experience and confirms what has often been reported stereotypically for obese youth.

The assessment of pediatric HRQOL must be considered within the family context; accordingly, the family relations scale provides a window into how the adolescent perceives family members’ interactions with them as a result of their weight. The present data suggest that the family relations of obese youth are characterized by stigmatization, exclusion, and shame. To date, the literature on the family correlates of pediatric obesity is lacking (62), although there are published data describing weight-related teasing by family members (61) and low family connectedness (63) within families of overweight youth. Although there are established generic HRQOL measures that assess the impact of pediatric chronic health conditions on parent and family functioning [e.g., Child Health Questionnaire (8), PedsQL Family Impact Module (64)], the IWQOL-Kids family relations scale uniquely assesses how weight impacts family relations.

In the past, researchers utilized adult instruments to measure HRQOL in the adolescent population (e.g., 65). However, given the developmental and contextual differences in the daily lives of children and adolescents, there has been a significant push in the past decade for the development of youth-specific HRQOL measures. The literature suggests that pediatric measures should contain items that correspond to the experiences, activities, and contexts that are directly relevant to the age of the sample (66). Although some content areas assessed by the IWQOL-Kids are similar to those on its adult counterpart (i.e., IWQOL-Lite), there are notable differences between these two measures due to developmental issues relating to youth. For example, several items on the IWQOL-Kids focus on the school and peer environments because they are particularly salient for adolescents. As a result, the IWQOL-Kids is a developmentally appropriate, weight-specific measure that should be utilized for adolescents between the ages of 11 and 19.

Because generic and condition-specific measures of HRQOL each offer unique advantages, studies may benefit from including both types of measures (11–13). Evaluation with generic measures is useful for comparing HRQOL across different diseases. For example, obese children and adolescents report their generic quality of life to be similar to that of pediatric cancer patients receiving chemotherapy (39). On the other hand, use of condition-specific measures has several advantages, one of which is greater sensitivity, which was observed in the current study when comparing the IWQOL-Kids and the PedsQL.

Quality of life concerns are important to address for a number of reasons. Assessing quality of life may help clinicians and researchers to understand the burden of a specific disease, establish the comparative efficacy of different treatments, and directly treat concerns that are important to patients (67,68). Increasingly, clinical trials include quality of life assessments in addition to standard medical endpoints (66). Although the goal of some treatments may be to improve quality of life, an alternate goal may be to ensure that quality of life does not deteriorate when a new treatment designed to improve health is administered (69,70). Because weight loss may be difficult to achieve, many youth may experience obesity as a chronic condition. Directly improving their quality of life even in the absence of weight loss may be a desirable goal.

There are several notable strengths of this study, including sample size, geographic and ethnic diversity, range of z-BMI, and the inclusion of both clinical and community samples. This allows for greater generalization to adolescent youth of all weight ranges. Nevertheless, some limitations of the present study must be noted. First, psychome-tricians have long recognized that instrument validation is a multistep, iterative process (71). The present paper is a preliminary step in this process. Critical psychometric measurement issues, such as test-retest reliability and confirmatory factor analysis, will be addressed in future studies. Second, similarly to well-established generic measures [e.g., PedsQL (9), Child Health Questionnaire (8), and Short Form-36 (72)], the IWQOL-Kids demonstrates ceiling effects, especially in adolescents within the normal-weight range. These ceiling effects were anticipated for this particular group given that weight does not influence their daily functioning in the same way as it does obese adolescents.

Future studies should also evaluate the impact of moderating variables that have proven important to understanding weight-related HRQOL in adults, such as the presence of comorbid medical conditions (73), non-obesity-related chronic illnesses (30), pain (74–76), binge eating (26,77), and depression (75). Clearly, further exploration of demographic variations by gender (24,41,78,79), age (41), and ethnicity (24,41,78) will be important. Other areas for future research include the development of a weight-related measure for use in younger children and a parent-proxy form, with subsequent further evaluation of convergence between youth and parent reports of weight-related quality of life.

Given the growing prevalence and extent of obesity in youth, the development of a reliable and valid measure that assesses the impact of weight on quality of life in this age group is timely. Because the IWQOL-Kids is self-administered and brief (taking ~8 minutes to complete), it poses minimal respondent burden. Given these preliminary data documenting its strong psychometric properties, the IWQOL-Kids is likely to be a valuable tool for both obesity clinicians and researchers.

Acknowledgments

We thank the following programs and individuals for allowing us to recruit participants: Healthy Kids Camps (Durham, NC), HealthWorks! (Cincinnati Children’s Hospital Medical Center, Cincinnati, OH), Children’s Health Systems Center for Weight Management (Birmingham, AL), Durham Public Schools (Durham, NC), Immaculata Catholic School, Duke School for Children, NC School of Science and Mathematics, and Kestrel Heights School (Durham, NC), National Institute of Child Health and Development, NIH (Bethesda, MD), and nurses and dietary staff at the University of New Mexico General Clinical Research Center. We also wish to acknowledge Stephen R. Daniels (HealthWorks!) and Jeffrey B. Schwimmer (University of California, San Diego) for providing valuable feedback on IWQOL-Kids items; Jan Croft (Durham, NC), Aislinn Pentecost-Farren (Chapel Hill, NC), and Tara Jean Loux (Birmingham, AL), for assistance with data collection; and Jodi Swanson (Neuropsychiatric Research Institute, Fargo, ND) for data entry. This work was supported by NIH (Grants DK600301 to M.Z. and HD00641 to J.Y.); grants from the University of New Mexico Department of Pediatrics Research Committee and the Research Allocation Committee, University of New Mexico, and the University of New Mexico General Clinical Research Center (NIH, National Center for Research Resources GCRC Grant M01-RR00997 to D.M.); and funding from Bristol-Myers Squibb Pharmaceutical Research Institute (Wallingford, CT; to R.K.). The IWQOL-Kids is a copyrighted instrument (2005; R.L.K. and Cincinnati Children’s Hospital Medical Center).

Footnotes

¹Nonstandard abbreviations: HRQOL, health-related quality of life; PedsQL, Pediatric Quality of Life Inventory; IWQOL, Impact of Weight on Quality of Life; SD, standard deviation.

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