Regular dental visits are essential for oral health, yet disparities between regions exist due to socioeconomic and geographic factors. National surveys generally lack sufficient sample sizes at the local level to generate reliable county-level estimates. Small area estimation techniques, such as multilevel regression and post-stratification (MRP) can help address this gap by producing robust estimates for smaller geographic areas. However, the MRP approach relies on detailed population data in the form of joint distributions and cannot be applied when only marginal distributions are available.

This paper introduces a hybrid approach combining multilevel modeling with the raking procedure. Authors used individual-level data from the 2018 Behavioral Risk Factor Surveillance System (BRFSS) and census data from American Community Survey to estimate county-level dental care utilization among adults in California. 2017–2018 California Health Interview Survey (CHIS) data were used for external validation.

Findings: The county-level dental care utilization in California ranged from 52.5% to 73.1%, with a median of 63.1%. Model-based estimates matched direct BRFSS estimates at metropolitan and micropolitan statistical area levels. Furthermore, authors found significantly positive correlations between our model-based estimates and direct estimates from the California Health Interview Survey for 41 counties.