Investigating the association between sociodemographic variables, comorbidities and treatment patterns and the risk of falls in children with ASD

Alshammari,Musaad A.; Alnemari,Hadeel M.; Alfadhel,Sara A.; Rogowska,Aleksandra M.; Alshammari,Tahani K.

doi:10.3892/wasj.2025.375

Investigating the association between sociodemographic variables, comorbidities and treatment patterns and the risk of falls in children with ASD

Authors:
- Musaad A. Alshammari
- Hadeel M. Alnemari
- Sara A. Alfadhel
- Aleksandra M. Rogowska
- Tahani K. Alshammari
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Affiliations: Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh 11451, Kingdom of Saudi Arabia, College of Pharmacy, King Saud University, Riyadh 11451, Kingdom of Saudi Arabia, Institute of Psychology, University of Opole, 45‑052 Opole, Poland
Published online on: July 14, 2025 https://doi.org/10.3892/wasj.2025.375
Article Number: 87
Copyright : © Alshammari et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].

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Abstract

Autism spectrum disorder (ASD) is a severe developmental disability, the incidence of which is rapidly increasing. A comorbidity profile and a risk of falls are highly prevalent in children with ASD. The aim of the present study was to map relevant sociodemographic variables, analyze the types of medication that children with ASD receive, and determine the comorbidities that exist among this cohort. In addition, a correlation analysis was conducted to evaluate the risk of falls among the different age groups. A retrospective cohort study was designed using electronic medical record systems. The sample comprised 250 children with ASD, among whom 74.4% were male and 12% were <6 years of age. The demographics of the study participants were analyzed along with the frequency and types of comorbidities. Subsequently, pediatric risk of fall scores [Humpty Dumpty Falls Scale (HDFS)] were obtained and Spearman's correlation analyses and ANOVA were employed to analyze the associations between age and the number of medications taken. Linear regression slopes were then used to determine which variables predicted the risk of falls. The results revealed that the age of the children was positively associated with the total number of medications taken and antipsychotic medications used (P<0.001). There was also a significant association between pediatric risk of falls and age (P<0.001). Binary logistic regression analysis revealed that the risk of falls (HDFS) were predicted by a lower current age and the male sex. Almost 39% of the participants had another health condition, the most prevalent of which was attention deficit hyperactivity disorder (ADHD) (46%), followed by intellectual disability (18.4%) and epilepsy (17.6%). The findings also indicated that functioning improved as children with ASD grew older. In addition, it was revealed that the majority of participants were taking antipsychotics and exhibited clinical features of ADHD. On the whole, the present study provides further evidence regarding the link between the pediatric risk of falls and younger age.

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