Risk factors and a prediction model for ASD symptoms in Chinese preschool children

Background: The global prevalence of autism spectrum disorder (ASD) is rising, creating an urgent need for practical early screening tools, especially in community and resource-limited settings. This study aimed to identify key risk factors and develop an individualized prediction model for ASD symptoms in Chinese preschool children. Methods: A cross-sectional study was conducted in 2024, involving 13,641 children aged 3-6 years from 32 kindergartens in Guizhou Province, China. ASD symptoms were screened using the Autism Behavior Checklist. Predictor variables were selected via LASSO regression with 10-fold cross-validation. A multivariable logistic regression model was constructed and presented as a nomogram. Model discrimination was evaluated by the area under the receiver operating characteristic curve (AUC) with bootstrapped 95% confidence intervals (CI). Calibration was assessed using calibration curves and the Hosmer-Lemeshow test, and clinical utility was measured by decision curve analysis. Results: Among the participants, 324 (2.38%) screened positive for ASD symptoms. Multivariable analysis identified several independent risk factors: lower degree of fondness for the child (OR = 1.53, 95% CI: 1.29-1.81), inconsistency in parenting beliefs (OR = 1.17, 95% CI: 1.06-1.30), poorer sleep quality (OR = 1.55, 95% CI: 1.33-1.80), and a family history of mental disorders (OR = 2.80, 95% CI: 1.81-4.32). Higher parental education (OR = 0.86, 95% CI: 0.78-0.94) and balanced caregiving time (OR = 0.82, 95% CI: 0.76-0.88) were protective factors. The nomogram demonstrated moderate discrimination (AUC = 0.757, 95% CI: 0.731-0.782), was well-calibrated, and provided a net clinical benefit for threshold probabilities between 0.1% and 19.6%. Conclusion: We successfully developed and validated a practical nomogram that integrates multiple familial and child-level factors for predicting ASD symptoms. This tool exhibits good performance and clinical applicability, offering a valuable approach for early community-based screening of preschool children.