Int. J. Environ. Res. Public Health 2009, 6 1637 for Disease Control and Prevention laboratory at the National Centers for Environmental Health. In the 1999-2000 survey cycle, serum cotinine measurement was designed to detect levels as low as 0.05 ng/mL. Beginning in 2001-2002, a similar but more sensitive cotinine assay allowed for a lower detectable limit of 0.015 ng/mL. We defined two kinds of cotinine measured exposure: whether or not someone has a detectable serum cotinine level of 0.05 ng/mL or greater, and the actual level of serum cotinine. The detectable limit of 0.05 ng/mL was used so that our data would be comparable across all years. 2.4. Measurement of Sociodemographic Characteristics We considered the following sociodemographic variables: gender, race/ethnicity (non-Hispanic White, non-Hispanic Black, Mexican-American, other Hispanic, other race/ethnicity), country of birth (U.S., Mexico, elsewhere), poverty status and educational level. Poverty status was measured by the poverty income ratio (PIR) developed by the U.S. Census Bureau [19]. PIR is the ratio of family income to the family’s appropriate poverty threshold taking family size into account [20]. We classified PIR into four categories: poor (0.0-0.99), low income (1.0-1.99), mid income (2.0-3.99), and high income (≥ 4.0). Values less than 1.0 indicate that family income is below the official poverty threshold. Education level was classified into less than high school, high school graduate or General Educational Development (GED) diploma, and more than high school graduate. The education level for children and adolescents was determined by the status of the reference person in their household. 2.5. Statistical Analysis All analyses accounted for the complex survey design and incorporated sampling weights that adjusted for unequal probabilities of sample selection, nonresponse, and sample noncoverage. All the statistical analyses were carried out using SAS version 9.1 [21] PROC SURVEYMEANS, PROC SURVEYREG, and PROC SURVEYLOGISTIC procedures which adjust for complex sample design when variance estimates are computed. We calculated the percentages of nonsmokers with self- reported SHS exposure and the percentages of nonsmokers with detectable serum cotinine levels. We also calculated the geometric means of the serum cotinine levels among nonsmokers. Because the cotinine levels were not normally distributed, we log-transformed the actual values before performing any analyses [9,10]. For nonsmokers whose serum cotinine level was below the detectable limit, we used an estimated level of 0.035 ng/mL (ie, the detectable limit, 0.050 ng/mL, divided by the square root of 2) [9,22,23]. Exposure prevalence rates and geometric means as well as their 95% confidence intervals (CIs) were calculated by age group (children, adolescents, adults), time period (1999-2000, 2001-2002, 2003-2004, 2005-2006), and sociodemographic characteristics. To assess whether there was a significant time trend in SHS exposure during the eight years from 1999 to 2006, we fit an ordinary least squares regression model for all nonsmokers within each age group. In the model, the dependent variable is one of the three SHS exposure measures and the independent variable is the “time trend” variable with the value of 1 for 1999-2000, 2 for 2001-2002, and so forth. If the coefficient of the time trend variable is negative and statistically significant, it indicates there was a decreasing trend. For the analyses of the relationship between sociodemographic