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Tusek I.,University of Novi Sad | Carevic M.,University of Belgrade | Tusek J.,Private Dental Office Palmadent
Srpski Arhiv za Celokupno Lekarstvo | Year: 2011

Introduction Early childhood caries (ECC) is a special form of caries that affects decideous teeth with rapid progression and numerous complications. Objective The aim of the study was to define the prevalence of ECC in children of the South Bačka area, the importance of social environment for the prevalence and severity of ECC, and define the model for its prevention. Methods The survey was the cross-sectional analytical study in the 10% sample of children, aged 13-64 months, different sex, social status and human enviroment. Severity and prevalence of ECC were assesed by dental check-ups. The epidemiological data were obtained by the interview of parents. The tests of significant statistical differences were performed by the analysis variance and χ2 (p<0.05) test, as well as interdependence of ECC and single characteristics that could be a predictor of the disease by the logistic regression. Results The prevalence of ECC was 30.5%. The highest disease frequency was found in children of male sex (35.1%), out of kindergardens (54.2%), in the third and the next born child in the family (46.9%) and in part-time employed mothers (47.2%) who had only elementary education (59.3%) and were poorly informed about oral health. The highest prevalence (47.1%) of ECC was found in children whose parents had the lowest income per month. Type 1 of ECC was the most presented one (75.0%). Conclusion The higher prevalence and more severe ECC were found in the third and the next born male child from rural environment.


Ivancevic V.,University of Novi Sad | Tusek I.,University of Novi Sad | Tusek J.,Private Dental Office Palmadent | Knezevic M.,University of Novi Sad | And 2 more authors.
Computer Methods and Programs in Biomedicine | Year: 2015

Background and objective: Early childhood caries (ECC) is a potentially severe disease affecting children all over the world. The available findings are mostly based on a logistic regression model, but data mining, in particular association rule mining, could be used to extract more information from the same data set. Methods: ECC data was collected in a cross-sectional analytical study of the 10% sample of preschool children in the South Bačka area (Vojvodina, Serbia). Association rules were extracted from the data by association rule mining. Risk factors were extracted from the highly ranked association rules. Results: Discovered dominant risk factors include male gender, frequent breastfeeding (with other risk factors), high birth order, language, and low body weight at birth. Low health awareness of parents was significantly associated to ECC only in male children. Conclusions: The discovered risk factors are mostly confirmed by the literature, which corroborates the value of the methods. © 2015 Elsevier Ireland Ltd.

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