Parsimonious prediction model for the prevalence of dental visits.

OBJECTIVES

To analyze the prevalence of dental visits within the last year in the Behavioral Risk Factor Surveillance System or BRFSS (2003) national database by simple sociodemographic factors, and to predict prevalence in States that have not participated in BRFSS 2003.

METHODS

Behavioral Risk Factor Surveillance System is a cross-sectional telephone survey conducted by the state-level authorities in the United States and based on a standardized questionnaire to determine the distribution of risk behaviors and health practices among noninstitutionalized adults. A multivariable logistic regression model considers the complex sample design of the BRFSS was used to predict the prevalence of dental visits based on four nonclinic parsimonious variables.

RESULTS

White race, high income (>or=$35 000), education above high school, and marital status were associated with an annual dental visit with odds ratios of 1.38, 2.09, 1.61, and 1.18, respectively. Utah had the highest percentage (78%) of estimated annual users, while 'Virgin Islands' had the lowest percentage (59%). The model's correct classification rate was 61.5%.

CONCLUSIONS

State and local governments, health promotion organizations, insurance companies, and organizations that administer public health programs (such as Medicare and Medicaid in the U.S.) will benefit by applying this model to the available nonclinical databases, and will be able to improve planning of dental health services and required dental workforce.