Applying Bayesian Model to Predict Socio-demographic and Occlusal Determinants of Early Childhood Caries (ECC)
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Date
2017Author
Kemoli, A M
Chepkwony, F
Type
ArticleLanguage
enMetadata
Show full item recordAbstract
Objective: To use the Bayesian statistical Model approach to predict the most
important socio-demographic and occlusal factors pertinent to high prevalence of ECC.
Material and Methods: A questionnaire and an oral examination was conducted on
children who attended a pediatric dental clinic in Nairobi during the period of study.
The parents provided information on socio-demographic and oral habits of the children.
The oral examination for presence of dental caries was recorded for each child.
Descriptive statistics were obtained for dental caries, oral hygiene, using plaque score,
and malocclusion. The results of the questionnaire and presence of dental caries were
analyzed and the results subjected to Bayesian statistical analysis to determine any
predictive factors for ECC. Results: 55% of the children had plaque accumulating on
more than one third but less than two thirds of tooth surfaces. The highest plaque
scores were reported among children whose fathers (48.2%) and mothers (42.0%) had
completed secondary, and whose fathers were in non-formal employment 73.2%. The
overall prevalence of dental caries in the study group was 95.5% with a mean dmft of
8.53 (+ 5.52 SD), with the male children having higher dmft 8.65 (SD+5.54) than the
female children 8.37 (SD+ 5.50). The prevalence of malocclusion among children in the
study was 55%. The majority had mesial step, 51.5% (n=140) and flush terminal plane
28.3% (n=77). Conclusion: The Bayesian Model, with a correct assumption, can be used
to determine the important factors involved in high prevalence of ECC.
Publisher
University of Nairobi
Rights
Attribution-NonCommercial-NoDerivs 3.0 United StatesUsage Rights
http://creativecommons.org/licenses/by-nc-nd/3.0/us/Collections
- Faculty of Health Sciences (FHS) [10387]
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