Using association rule mining to identify risk factors for early childhood caries.
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.
University of Novi Sad, Faculty of Technical Sciences, Trg Dositeja Obradovića 6, 21 000 Novi Sad, Serbia. Electronic address: dragoman@uns.ac.rs.
Vladimir
V
Ivančević
University of Novi Sad, Medical Faculty, Hajduk Veljkova 3, 21 000 Novi Sad, Serbia.
Ivan
I
Tušek
Private Dental Office Palmadent, Mažuranićeva 4, 21 131 Petrovaradin, Serbia.
Jasmina
J
Tušek
University of Novi Sad, Faculty of Technical Sciences, Trg Dositeja Obradovića 6, 21 000 Novi Sad, Serbia.
Marko
M
Knežević
University of Novi Sad, Faculty of Technical Sciences, Trg Dositeja Obradovića 6, 21 000 Novi Sad, Serbia.
Salaheddin
S
Elheshk
University of Novi Sad, Faculty of Technical Sciences, Trg Dositeja Obradovića 6, 21 000 Novi Sad, Serbia.
Ivan
I
Luković
D017677:Age Distribution; D001942:Breast Feeding; D002675:Child, Preschool; D057225:Data Mining / Q000379:methods*; D020000:Decision Support Systems, Clinical / Q000458:organization & administration*; D003731:Dental Caries / Q000175:diagnosis* / Q000453:epidemiology*; D042241:Early Diagnosis; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D015995:Prevalence; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods*; D012680:Sensitivity and Specificity; D055771:Serbia / Q000453:epidemiology; D017678:Sex Distribution
Association rule mining; Data mining; Early childhood caries; Objective measure of interestingness; Risk factor