8%) respondents reported in 2002 being current or former smokers: Bosutinib chemical structure 730 stated that they were former smokers, 193 identified themselves as everyday smokers, and 100 stated they were smoking some days. Logistic Regression Analysis All final models in Tables 3 and and44 are significant overall (p < .001). Table 3 presents the results for all levels of main effects not included in interactions. Table 4 presents the estimated conditional ORs, which were obtained using ��effects�� statements (SUDAAN; Research Triangle Institute, 2008, pp. 276�C289), and corresponding 95% CIs adjusted via the Bonferroni method; only results for selected levels of interaction terms are presented and discussed below. Table 3. Estimated Odds Ratios and Adjusted 95% CIs for Main Effects That Were Not Involved in Any Interaction Terms Table 4.

Estimated Odds Ratios and Corresponding Adjusted 95% C Is for Some Levels of Interaction Effects Measure 1: Time since completely quitting smoking. The final model included two-way interactions of age by region (p = .004), 2002 interview method by race/ethnicity (p = .004), 2002 interview method by region (p = .006), and 2003 interview method by region (p < .001). For those main effects that were not involved in any interaction terms, only sex was significant (p = .043): Male respondents were overall less likely to report the same time since completely quitting smoking at both reports than were female respondents. Among the statistically significant conditional interaction effects we examined, we observed that Midwestern residents who had a phone interview in 2003 were less likely to provide consistent responses than were the ones who had an in-person interview in 2003 (adjusted p = .

048), while Southern residents who had a phone interview in 2003 were more likely to provide consistent responses than were the ones who had an in-person interview in 2003 (adjusted p = .043). The interaction effects between age and region involve a large number of comparisons. Although some of the comparisons were significant, we do not report the detailed results here unless we noted a consistent pattern. We found: (a) younger age groups to be more reliable than each subsequent older age group in the South for reporting time since completely quitting smoking; (b) 15- to 24-year-olds to be more reliable than all other individual age groups in the Midwest for reporting this measure.

Measure 2: Age at which fairly regular smoking was initiated. The final model contained only the main effects, where only age was significant (p = .016), but none of the individual comparisons revealed any significant differences. Drug_discovery Measure 3.1: The number of cigarettes smoked per day when former smoker smoked every day. Again, the final model contained only main effects. Only metropolitan status was significant (p = .002).