Background: Although it has been reported that low socioeconomic position (SEP) is associated with lung cancer, the extent to which this reflects SEP differences in cigarette smoking is unclear. We investigated how various modeling approaches for smoking might influence this observed association.
Methods: We used data from a case-control study conducted in Montreal, Canada (1996−2002), comprising 1203 subjects with incident lung cancer and 1513 population controls. SEP was measured by census-based and self-reported income, residential value, education level, and occupational class. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression, and Akaike's Information Criterion (AIC) was used to compare model fit.
Results: Associations were observed between SEP indicators and lung cancer, but gradually disappeared with more comprehensive adjustment for smoking. For comparisons of the highest to lowest categories of census-based income, the OR for lung cancer was 0.58 (95% CI = 0.32−1.05) when adjusting only for smoking status (never, former, current), but 0.97 (0.51−1.86) when adjusting for smoking status, cigarette-years, and time since cessation. For comparisons of highest to lowest levels of education, the ORs for lung cancer were 0.50 (0.38−0.65) and 0.76 (0.57−1.02), when making the least and most comprehensive adjustments for smoking, respectively. Similarly, comparing highly skilled with unskilled manual workers, the ORs were 0.78 (0.54−1.12) and 1.00 (0.68−1.47), respectively. With thorough smoking adjustment, associations between SEP indicators and lung cancer virtually disappeared, and SEP did not improve model fit.
Conclusions: Previously reported associations of SEP with lung cancer may be attributable to incomplete adjustment for smoking. Our findings underline the importance of adjusting for several dimensions of smoking behavior to make correct inferences.