Prevalence of halitosis in children considering oral hygiene, gender and age. Issue 3 (28th March 2014) - Villa, A; Zollanvari, A; Alterovitz, G; Cagetti, MG; Strohmenger, L; Abati, S
Abstract Background To date, few studies have addressed halitosis in the paediatric population. As such, the aim of the present study was to investigate symptoms, signs and risk factors associated with halitosis in healthy children and to present a model based on the clinical data that predicts the presence of halitosis. Methods A total of 101 individuals were included. All patients received a questionnaire that queried on sociodemographic characteristics, self‐reported halitosis and dental treatment history. Individuals received a thorough intra‐oral examination, and the volatile sulphur compounds (VSC) were measured to test the presence of halitosis with a portable sulphide monitor (Halimeter®; Interscan Co., Chatsworth, CA, USA). The distribution of the sociodemographic characteristics, self‐reported halitosis, dental treatment history and other oral features was evaluated. Finally, a statistical model was constructed with the best set of features to predict halitosis in children. Results The median age was 12.0 years (mean: 11.7 ± SD 2.7) with 54.5% males. Halitosis (VSC > 100 parts per billion, or ppb) was objectively measured in 37.6% of patients. For comparison purposes, Bayesian network was obtained using clinical and demographic data. The model consisted of four variables (sex, age, oral hygiene status and self‐reported halitosis) directly related to the presence of halitosis (VSC > 100 ppb). This model achieved 76.4% area under receiver operating characteristics curve (AUROC). Overall, female patients or individuals with dental plaque on more than 25% of the dental surfaces or patients older than 13 year old were more prone to present with halitosis. Conclusions The results suggest that halitosis in the paediatric population is related to poor oral hygiene and may be more common in females and older individuals. This specific predictive model may be useful to identify subgroups to target for intervention to treat oral halitosis.