Prevalence of Periodontal Tissue Diseases in Children With Autism

Abstract

It is known that among the many factors that cause dental diseases in children, disorders of mental development and disorders of the nervous system, including autism, are important. The study of dental incidence in children with autism is relevant in view of the need to develop and implement effective methods of treatment and prevention of the main dental diseases in these children.
 The aim of the study was to study the prevalence and features of the course of periodontal tissue diseases in children with autism.
 Methods and Material. 38 children with autism and 49 practically healthy children aged 13-18 were ex-amined. Assessment of periodontal tissue condition was carried out on the basis of clinical data. For an objective assessment of periodontal status, the papillary-marginal-alveolar index (PMA) was determined (S. Parma, 1960). The prevalence of periodontal diseases was determined using WHO criteria.
 Results. When analyzing the obtained results, periodontal tissue pathology was diagnosed in children of the main group in 68.42±6.67%, which is 1.4 times more than among children in the control group (48.86±5.89%, p<0.05 ). Basically, chronic catarrhal gingivitis (CCG) was diagnosed, the prevalence of which was 60.72±4.67%. In addition, 14.99±2.46% of the children of the main group had generalized periodontitis of mild severity. It was established that, on average, children with autism have a PMA index of 39.01±3.76%, which corresponds to the average severity of gingivitis. So, among the children of the main group, a mild degree of severity of CCG was diagnosed, on average, in 41.96±3.56%, an average degree in 44.92±7.64% of children with autism, severe in 5.34±2, 33%.
 Conclusions. Summary, children with autism have a high prevalence of periodontal diseases, in particular, chronic catarrhal gingivitis and generalized periodontitis. This requires the creation of special educational programs for children with autism in order to develop algorithms for providing individualized dental care to these children.