Exact(20)
The age-only adjusted risk estimates for smoking changed only slightly after adjusting for alcohol and other variables (see Materials and Methods), including alcohol intake (data not shown).
The risk estimates for smoking and colon cancer mortality and by location did not reveal any significant results among male ever smokers compared with male never smokers.
Our price elasticity estimates for smoking participation by high school youths are generally smaller than previous cross-sectional approaches but are similar to recent quasi-experimental estimates.
Table 2 presents the effect estimates for smoking abstinence.
Estimates for smoking among South Africans vary considerably.
After adjustment for potential confounders, all beta estimates for smoking status categories were attenuated but remained statistically significant (Table 2).
Similar(40)
However, the observed point estimate for smoking 1 extra CPD on log-transformed search speed was −0.005 z-score units, which would require a sample size of 386 815 current smokers in a 2SLS IV analysis.
The random forest MICE estimate for smoking (categorical) was biased towards the null (Table 3, Web Figure 2), but there was no material bias in other parameters estimated by random forest or parametric MICE (Table 2, Web Tables 3 and 4, Web Figure 3).
Odds ratios (OR) and 95% confidence intervals (CIs) were estimated for smoking status using unconditional logistic regression and controlling for known risk factors, including age, sex, race (white or other), average drinks per week (continuous), education (less/high school graduate or more), income, number of sexual partners and age at first intercourse.
Heterogeneity was also investigated further, separately for estimates unadjusted for any factor and estimates adjusted for smoking.
Therefore, we present unadjusted estimates, estimates adjusted for smoking status (never, former, current) and length of schooling (long, medium, short), and estimates additionally adjusted for baseline HPV16 positivity (yes/no).
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