BACKGROUND: We sought to assess the association between age and the prevalence of obesity among children with and without autism spectrum disorder (ASD) in the 2011-2012 National Survey of Children's Health. METHODS: Analyses were restricted to 43,777 children, ages 10-17, with valid measures of parent-reported weight, height, and ASD status. Exploratory analyses describe the impact of sex, race/ethnicity, and household income on the relationship between age and obesity in ASD. RESULTS: Although the overall prevalence of obesity among children with ASD was significantly (p < 0.001) higher than among children without ASD (23.1% vs. 14.1%, 95% confidence interval for difference 3.6 to 14.4), child age significantly (p = 0.035) modified this difference. In a multivariable logistic regression analysis, adjusted for sex, race/ethnicity, and household income, the odds of obesity among children with ASD compared with children without ASD increased monotonically from ages 10 to 17 years. This pattern arose due to a consistently high prevalence of obesity among children with ASD and a decline in prevalence with advancing age among children without ASD. These findings were replicated using a propensity score analysis. Exploratory analyses suggested that the age-related change in obesity disparity between children with and without ASD may be further modified by sex, race/ethnicity, and household income. CONCLUSIONS: The patterns of prevalence observed with increasing age among children with and without ASD were unexpected. A better understanding of the etiological and maintenance factors for obesity in youth with ASD is needed to develop interventions tailored to the specific needs of these children.

Time spent in sedentary behavior is largely due to time spent engaged with electronic screen media. Little is known about the extent to which sedentary behaviors for children with autism spectrum disorder differ from typically developing children. We used parental report to assess and compare time spent in sedentary behaviors for 53 children with autism spectrum disorder and 58 typically developing children aged 3-11 years. We also determined how sedentary behavior was related to child weight status (body mass index z-score). Overall, children with autism spectrum disorder spent an hour more in sedentary behaviors on weekdays compared to typically developing children (5.2 vs 4.2 h, p = 0.03), and most of this difference was due to screen time. The age- and sex-adjusted estimate of weekday total daily screen time was 1.6 h (typically developing) compared to 2.5 h (autism spectrum disorder, p = 0.004 for difference). A significant relationship between BMI z-score and total sedentary behavior time on weekend days was observed among young children with ASD, but not among TD children. The modest association between weekend sedentary behaviour time and BMI z-score among children with ASD suggests that sedentary behaiour is linked to relative weight status in these children. Further research is needed to confirm these findings and identify causal pathways.

BACKGROUND: The most recent Dietary Reference Intakes (DRIs) (2002) for energy were based on pooled data from convenience samples of individuals with energy expenditure determined by using doubly labeled water (DLW). To our knowledge, the accuracy of these intake estimates has not been assessed in children. OBJECTIVE: We assessed the accuracy of DRI prediction equations for determining daily energy needs in girls by comparing the individual-level prediction of estimated energy requirements with the measured value of total energy expenditure (TEE) from DLW, which is considered the gold standard. DESIGN: In this cross-sectional analysis, we measured the resting metabolic rate (RMR) by using indirect calorimetry and TEE by using DLW in 161 nonobese premenarcheal girls aged 8-12 y. The activity factor TEE/RMR was used to categorize the physical activity level used in DRI equations. RESULTS: We observed a strong linear relation between TEE by using DLW and estimated energy requirements predicted from DRI equations (Pearson's r = 0.78, P < 0.0001, R(2) = 0. 61). The DRI-predicted energy requirements underestimated measured TEE by ~120 kcal on average. The overall mean (+/-SD) error in the sample was -121.3 +/- 163.9 kcal. The average (+/-SD) percentage error in the sample was -5.8 +/- 7.9%. Seventy percent of participants had predicted TEE values < /=10% of measured TEE. CONCLUSIONS: DRI equations for girls predict well for the group. The use of these equations for individuals may result in the underestimation of energy requirements for a significant percentage of girls.