Overweight and Obesity: Prevalence and Correlates in a Large Clinical Sample

Background:  Previous studies have shown that the rate of obesity in children with autism spectrum disorders is significantly higher than that in the typically developing population, though consistent with rates of obesity being higher in other populations with chronic developmental disabilities (Rimmer et al 2010; Chen et al., 2010). Specific predictors of overweight and obesity in ASD children should be identified in order to promote healthier life and inform clinical management

Objectives: To identify predictors of overweight and obesity in a  clinical sample of children with ASD.

Methods:  Data collected at the Oregon Health and Sciences University (OHSU) site of the Autism Treatment Network (ATN) on 388 diagnosed subjects (83% male; mean age: 5.4 years; range: 2.0 -16.9 years) were available . Overweight (OWT)  and obesity (OBY) were respectively defined as a BMI >= 85^th or >=95^th centiles derived  from CDC population norms. Data on parental concerns, autism severity, adaptive behavior, verbal level, medication use, socio-demographic background were available through the ATN database.

Results:  The mean BMI  was 17.4  (17.5, boys; 17.3, girls) and the median was 16.5. Prevalence was 33.8% for OWT and 16.5% for OBY. Both OWT and OBY were unrelated to sex (p>.50). OVW ranged from 21% to 40% and OBY from 9.1% to 22.5% by age group. Age was not significantly associated with either OVW (p=.10) or OBY (=.48).

Bivariate analyses showed that  parental education level, ethnicity, verbal level of the ASD child, autism severity and diagnostic subtype were unrelated to OVW (all NS). Standardized scores of the Vineland did not vary by OVW status. OVW was also unrelated with high t-scores on subscales (anxiety,  somatic complaints, attention, aggression, oppositionality) and broader band t-scores (internalizing , externalizing and total) of the CBCL (all p: NS). Correlations between BMI and CBCL continuous scores were small and nonsignificant.  Most parental concerns (sleep, language, self-injury, aggression, adhd-type behaviors, mood swings, anxiety, sensory issues, repetitive behaviors) and, surprisingly, concerns about eating problems, were also unrelated to OVW. However, parental concerns about socialization difficulties were associated with child OVW (p=.02). No association was found with use of any psychotropic medication (p=.27) as well as with specific classes of medications. In a subsample of 94 children (mean age: 8.9 years; 87.2% male) with Stanford-Binet data, a trend emerged for a negative association between full scale IQ and BMI (r=-.19; p=.06).

Analyses were repeated for OBY children and broadly comparable results were obtained. One exception was that melatonin use was significantly higher in OBY children than in their counterparts (32.8% vs 19.4%; p=.02). Comparisons with population norms and data from other atypical groups will be performed.

Conclusions:  OVW and OBY were highly prevalent in this ASD clinical sample. Attempts to identify predictors of OVW and OBY were unsuccessful. In particular, none of the specific characteristics of autism predicted OVW or OBY, suggesting that the same risk factors apply for OVW and OBY occurring in ASD children ASD and typical and other atypical populations.