Estimating county-level tobacco use and exposure in South Carolina: a spatial model-based small area estimation approach

Abstract Purpose Local health statistics are increasingly requested for policy-making and programmatic purposes; however, population-based surveys are often inadequate to support direct estimation for small areas. Model-based estimation techniques can be used to create local estimates for public health outcomes. Using the 2014–2015 South Carolina (SC) Adult Tobacco Survey, we examined tobacco-related outcomes at the county level using a spatial multilevel, poststratification approach. Methods To create county-level tobacco estimates, we used a two-level model with a spatially intrinsic conditional autoregressive random intercept. Stratum-specific (race, age, and sex) estimates for each county were then created and averaged based on population data obtained from the U.S. Census. Results The estimated prevalence of current smoking in SC counties among adults ranged from 7.4% to 35.1%, and the percentage reporting ever trying an e-cigarette ranged from 4.2% to 30.2%. Model validation showed considerable agreement between direct and indirect estimates (Pearson and Spearman correlations all >0.75) that varied by the sample size of the outcome, as hypothesized. Conclusions Data from the SC Adult Tobacco Survey were used to develop county-level estimates of multiple tobacco-related outcomes using a spatial multilevel, poststratification approach. The results showed heterogeneity in smoking behaviors across the state along with marked spatial correlation.