In our initial regression models, we controlled for variables known to be associated with metabolism (the predictor variable), including sex, race, and CPD. However, we opted to exclude these variables because they decreased the adjusted R2 values for the models. In addition, the analysis revealed that Body Mass Index (BMI) was negatively correlated with metabolism (r = −.229, p < .05); however, models controlling for BMI did not alter results. A significant relationship between hormonal contraception use and nicotine metabolism was found (r = −.345, p = .001). Thus we controlled for hormonal contraception use in subsequent relevant analyses. Therefore, we used bivariate linear regressions, with each topography measure as the dependent variable (mean puff volume, mean puff duration, mean puff interval, mean puff velocity, or total puff volume) and metabolism and hormonal contraception (HC) use as the predictor variables. Additional regression analyses were performed using the dependent variables: number of puffs and CO level.
