Eating disorders often begin in adolescence, affecting more than 28 million people in the US,1 although the prevalence of disordered eating behaviors (DEBs) is even greater.1,2 Data on DEBs among children younger than age 12 years are scant. Ascertaining the prevalence of DEBs in children is critical because rapid maturational and weight-related changes in puberty are independently associated with DEBs,3 and some youth may experience different rates of growth and weight gain vs their peers. We sought to characterize DEB prevalence in US children aged 9 to 10 years and the associations of DEBs with sex, pubertal maturation, and weight.
We conducted a cross-sectional analysis of children aged 9 to 10 years using ABCD Study baseline data collected from 2016 to 2018. The University of California, San Diego Institutional Review Board approved the study and waived the requirement for informed consent because only deidentified data were used. We followed the STROBE reporting guideline.
Using parent-informed diagnostic assessments (Kiddie-Structured Assessment for Affective Disorders and Schizophrenia for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition),4 we examined 3 DEBs: (1) compensatory behaviors to prevent weight gain (ever or at least once per week for 3 months); (2) binge eating (ever or at least once per week for 3 months); and (3) ever vomiting for weight control. Multivariable logistic regression models using proc surveylogistic in SAS, version 9.4 accounted for complex sampling weights5 and regressed each DEB outcome by sex assigned at birth; pubertal maturation; and body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) percentile-based weight status. Models were adjusted for race and ethnicity, and adjusted odds ratios (ORs) and 95% CIs were reported (Table). P = .05 was considered statistically significant. Data were analyzed October 14, 2021, to April 7, 2022.
In this study of 11 878 children, no sex differences in DEBs were found. Advanced pubertal maturation was associated with elevated odds of ever engaging in compensatory behaviors to prevent weight gain (Table). Children with higher BMI had elevated odds of compensatory behaviors to prevent weight gain (ever or at least once per week for 3 months) or ever vomiting. The prevalence of ever binge eating was 5.0% (weighted, 5.5%) and of binge eating at least once per week for 3 months was 2.2% (weighted, 2.5%). The association of pubertal maturation (measured by the Pubertal Development Scale [PDS]) with binge eating differed by weight status. Weight status–stratified models found that, among children with BMI ranging from the 5th percentile to less than the 85th percentile, advanced pubertal maturation was associated with elevated odds of ever binge eating (OR, 1.88; 95% CI, 1.35-2.60; P < .001) or binge eating at least once per week for 3 months (OR, 2.13; 95% CI, 1.21-3.76; P = .01). Among children whose BMI ranged from the 85th to less than 95th percentile, advanced pubertal maturation was associated with elevated odds of ever binge eating (OR, 1.55; 95% CI, 1.04-2.33; P = .03).
Sex differences in DEBs were minimal in children aged 9 to 10 years, consistent with full-threshold eating disorder diagnoses at these ages.6 Children with higher BMIs were at elevated risk for DEBs. Although advanced pubertal maturation was associated with greater report of compensatory behaviors to prevent weight gain, the association of pubertal maturation with binge eating differed by weight status. Parents might interpret eating behaviors differentially in the context of their child’s weight and development, such that overeating in the context of advanced pubertal maturation may be perceived as binge eating among children with lower BMI but not among similarly developed children with BMIs in the 95th percentile or greater. Findings underscore the importance of parental education around discerning DEBs. Limitations of the study include reliance on parental report and the relatively low prevalence of DEBs, which may impact the statistical power in discerning smaller yet meaningful consequences.
Accepted for Publication: May 4, 2022.
Published Online: August 1, 2022. doi:10.1001/jamapediatrics.2022.2490
Corresponding Author: Jerel P. Calzo, PhD, MPH, Division of Health Promotion and Behavioral Science, San Diego State University School of Public Health, 5500 Campanile Dr, San Diego, CA 92182 (jcalzo@sdsu.edu).
Author Contributions: Drs Murray and Calzo had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Murray, Calzo.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Murray, Calzo.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Blashill, Calzo.
Supervision: All authors.
Conflict of Interest Disclosures: Dr Murray reported receiving grants from the National Institutes of Health National Institute of Mental Health. No other disclosures were reported.
Additional Information: Data used in the preparation of this article were obtained from the ABCD Study held in the National Institute of Mental Health Data Archive. It was supported by the National Institutes of Health and additional federal partners under award numbers U01DA041022, U01DA041025, U01DA041028, U01DA041048, U01DA041089, U01DA041093, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, and U24DA041147. A full list of supporters is available at https://abcdstudy.org/nihcollaborators. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/principal-investigators.html. ABCD consortium investigators designed and implemented the study and/or provided data but did not participate in analysis or writing of this report.
2.Haynos
AF, Wall
MM, Chen
C, Wang
SB, Loth
K, Neumark-Sztainer
D. Patterns of weight control behavior persisting beyond young adulthood: results from a 15-year longitudinal study.
Int J Eat Disord. 2018;51(9):1090-1097. doi:
10.1002/eat.22963
PubMedGoogle ScholarCrossref 4.Kaufman
J, Birmaher
B, Brent
D. Kiddie schedule for affective disorders and schizophrenia.
J Am Acad Child Adolesc Psychiatry. 1997;36:545-553.
Google Scholar 5.Heeringa
SG, Berglund
PA. A guide for population-based analysis of the Adolescent Brain Cognitive Development (ABCD) Study baseline data.
bioRxiv. Preprint posted online February 10, 2020. doi:
10.1101/2020.02.10.942011
Google Scholar