Title: The value of a baseline caries risk assessment model in the primary dentition for the prediction of caries incidence in the permanent dentition
Authors: Vanobbergen, J ×
Martens, L
Lesaffre, Emmanuel
Bogaerts, Kris
Declerck, Dominique #
Issue Date: 2001
Series Title: Caries research vol:35 issue:6 pages:442-50
Abstract: To establish a reliable screening method for caries prediction and to identify predominant risk factors, this study tested whether a cross-sectional caries risk model assessed at age 7 could be used to predict future caries onset in the permanent first molars at age 10 in 3,303 children born in 1989. As prediction variables, assessing the believed risk, baseline data at age 7 on oral health status, oral hygiene level, oral health behaviour and sociodemographic factors were used. The real risk, based on data collected for the first permanent molars during the follow-up, was assessed by different approaches. Cumulative incidence during the 3-year observation period was 31.6%, ranging from 22.4% in the believed low-risk group to 43.2% in the believed high-risk group. A stepwise logistic regression analysis was performed with net caries increment as outcome measure, adjusted for the real time at risk, using eruption times. Baseline dmfs and occlusal and buccal plaque indices were highly significant for having a high caries increment in permanent first molars with respective odds ratios of 1.07, 1.43 and 1.35. Brushing less than once a day and the daily use of sugar-containing drinks between meals were confirmed as risk factors (OR 2.43 and 1.25, respectively). The logistic regression analysis provided a sensitivity of 59-66% and a specificity of 65.7-72.8%, which indicates that the risk marker did not have an important predictive power. None of the socio-demographic and behavioural variables had enough predictive power at community level to be useful for identifying caries susceptible children. Even the power of dmfs at baseline must be considered modest.
ISSN: 0008-6568
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat)
Biomaterials - BIOMAT
× corresponding author
# (joint) last author

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