Aim: The aim of the present study was to determine the association between dental visiting and missing teeth using propensity score (PS) adjustment to control for confounding bias, and to compare the estimates with those obtained from traditional regression models.
Methods: A population-based study was conducted on adults aged 35-54 years in India. Multistage stratified cluster random sampling was used. Data were collected through interviews and oral examinations. The exposure factor was 'dental visiting', and the outcome was number of missing teeth. Sociodemographic factors, oral hygiene practices, periodontal disease, and caries experience were the covariates. Inverse probability weight (IPW) calculated from the PS for dental visiting from a logistic regression model was used to balance the covariates. The association between dental visiting and missing teeth was estimated from log-binomial regression models with and without using IPW.
Results: Of the 873 participants, 77.7% visited a dentist. The ≥1 missing teeth prevalence was 65.3%. Post-IPW adjustment covariate standardized bias between groups with or without dental visit was lower than the pre-IPW adjustment. Those who visited a dentist had an adjusted prevalence ratio of 2.40 when IPW was used, and 2.03 when IPW was not used.
Conclusion: Dental visiting was strongly associated with missing teeth in this rural population.
Keywords: dental visiting; inverse probability weight; missing teeth; propensity score; rural.
© 2018 John Wiley & Sons Australia, Ltd.