Sleep as a Modifiable Risk Factor for Childhood Autism: Stratified Analysis of U.S. National Survey of Children’s Health Data

Purpose This study aimed to examine the association between age-specific sleep sufficiency and autism spectrum disorders (ASD) among U.S. children aged 6–17 years. Methods Data were gathered from the 2022-2023 National Survey of Children’s Health (NSCH), including 63,866 children. Sleep sufficiency was defined based on age-specific guidelines from the American Academy of Sleep Medicine. Descriptive statistics, incidence risk ratios (IRRs), and adjusted logistic regression models were used to assess associations between ASD and key predictors. Stratified models by sex and BMI were conducted to explore effect modification. Additionally, a machine learning model was developed to predict the adjusted probability of ASD risk. Results Children with insufficient sleep had a significantly higher incidence of ASD (5.16%) compared to those with sufficient sleep (4.05%) (p < 0.001). In adjusted models, sufficient sleep was associated with lower odds of ASD (OR = 0.78; 95% CI: 0.72–0.85; p < 0.001). Stratified analyses showed a protective effect in both males (OR = 0.78; 95% CI: 0.71–0.86) and females (OR = 0.80; 95% CI: 0.68–0.93), more pronounced in males. Machine learning analysis revealed that females with sufficient sleep and age below 14 years exhibited the lowest probability of ASD, whereas males aged 8 to 14 years with insufficient sleep demonstrated the highest likelihood of ASD risk. Conclusion These results suggest that sufficient age-specific sleep is significantly associated with reduced odds of ASD, particularly in male children. Findings highlight the importance of sleep as a potentially modifiable factor in ASD risk and support targeted public health interventions.