Modeling geographic and demographic variability in residential concentrations of environmental tobacco smoke using national data sets.

Despite substantial attention toward environmental tobacco smoke (ETS) exposure, previous studies have not provided adequate information to apply broadly within community-scale risk assessments. We aim to estimate residential concentrations of particulate matter (PM) from ETS in sociodemographic and geographic subpopulations in the United States for the purpose of screening-level risk assessment. We developed regression models to characterize smoking using the 2006-7 Current Population Survey--Tobacco Use Supplement, and linked these with air exchange models using the 2007 American Housing Survey. Using repeated logistic and log-linear models (n = 1000), we investigated whether household variables from the 2000 United States census can predict exposure likelihood and ETS-PM concentration in exposed households. We estimated a mean ETS-PM concentration of 16 μg/m(3) among the 17% of homes with non-zero exposure (3 μg/m(3) overall), with substantial variability among homes. The highest exposure likelihood was in the South and Midwest regions, rural populations, and low-income households. Concentrations in exposed households were highest in the South and demonstrated a non-monotonic association with income, related to air exchange rate patterns. We provide estimates of ETS-PM concentration distributions for different subpopulations in the United States, providing a starting point for communities interested in characterizing aggregate and cumulative risks from indoor pollutants.