Predicting tooth loss for older adults with special needs

Abstract

Older Adults with Special Needs (OASN) have more oral health needs compared with healthy, independent elders. Currently, little is known about tooth loss, a key indicator of oral function loss, among OASN. Risk assessment is primarily based on clinical experience rather than scientific evidence, raising concerns for quality of care. The study's objective was to develop an evidence-based model to quantitatively predict tooth loss for OASN. Four hundred ninety-one dentate older adults, including 235 from long-term care facilities, were retrospectively recruited. Subjects were treated and brought to a state of oral health before enrollment. Medical and dental assessments were abstracted from dental records and used to predict risk of tooth loss. Tooth loss events were recorded for subjects during follow-up. Multivariate negative-binomial regression was used, starting with 27 risk factors and removing variables using Akaike's Information Criterion. Pearson's correlation was then conducted to evaluate the overall fit of the final fitted model. The final fitted model included eight predictors. Among them, age, number of decayed/broken teeth at arrival, anticholinergic burden of medications and physical mobility were associated with risk of tooth loss in OASN (P ≤ 0.05). Internal validation indicated satisfactory fit of the final fitted model. An evidence-based model with eight predictors was developed to quantitatively predict risk of tooth loss for OASN at the individual level.