Compared to younger adults, older adults are at greater risk for root caries. A model of root caries may assist dentists in predicting disease outcomes.
Objectives: Using the Iowa 65+ Oral Health Survey, analysis was done to model the patterns of the root caries development in older adults.
Methods: The statistical analysis included Markov chain modeling, model estimation and validation.
Results: The model effectively predicts root caries using an 18-month predictive cycle and is validated up to 36 months (two cycles), with no significant differences (Chi-square test p-values >0.1) between predicted and observed distributions. However, we do not have observed data for validation beyond 36 months since the model was designed to perform only at single or multiple 18-month cycles. As expected, the predicted distribution at 54-month (3 cycles) and the observed distribution at 60-month differed significantly (p<0.0001).
Conclusions: The model demonstrated a high probability that a sound surface will remain caries free. However, one and multiple-surface lesions aggressively infect adjoining surfaces. Maturing of the carious lesion occurs with the 4-surface lesion, decreasing the probability of tooth loss. Thus, maintaining a sound root surface and early treatment intervention reduces the risk of tooth dysfunction (morphological destruction) and loss. DATABASE FILTERS: P: Tooth/Subject characteristics-Older adults, 65 years of age or more, male and female participants, regional rural Iowa residents, race unspecified, functional status-non-institutionalized level unspecified, risk level unspecified I: Root caries P (C-not applicable): Probability/Statistical significance for decision data only/Clinical significance-dataset over 20 years old/Utility data not included/Cost data not included/Meaning in practice undetermined. O: Each year through a three year cycle, caries progression from a sound root surface A: Data attached: ■ Published manuscript □ Unpublished manuscript □ Raw data R: Primary author contact information present.