. Author manuscript; available in PMC: 2014 Jul 29.

Published in final edited form as: Ann Behav Med. 2012 Apr;43(2):253–261. doi: 10.1007/s12160-011-9318-5

Table 2. The associations between amounts of daily cigarette consumption, serum cotinine, CYP2A6 genotypes, and abdominal obesity in 954 current male smokers with blood samples.

	Number (%)	Abdominal obesity	Amounts of daily cigarette consumption (>15 cigarettes/day)	Serum cotinine (≥225.31 ng/ml)
		Adjusted OR (95% CI)	Adjusted OR (95% CI)	Adjusted OR (95% CI)
Amounts of daily cigarette consumption
1–15 cigarettes/day	545 (57.1)	1
>15 cigarettes/day	409 (42.9)	1.57^* (1.13–2.19)^a
Serum cotinine
<225.31 ng/ml	477 (50.0)	1	1
≥225.31 ng/ml	477 (50.0)	0.61^* (0.41–0.90)^b	2.53^* (1.92–3.32)^c
CYP2A6 genotypes
CYP2A6 normal metabolizer genotype	441 (46.2)	1	1	1
CYP2A6 intermediate metabolizer genotype	137 (14.4)	0.72 (0.41–1.26)^a	1.03 (0.70–1.53)^c	1.08 (0.73–1.60)^c
CYP2A6 slow metabolizer genotype	254 (26.6)	0.90 (0.57–1.41)^a	0.89 (0.65–1.22)^c	0.89 (0.65–1.22)^c
CYP2A6 poor metabolizer genotype	122 (12.8)	0.94 (0.53–1.66)^a	0.59^* (0.38–0.90)^c	0.52^* (0.34–0.79)^c

p<0.05

Binary logistic regression adjusted for age, occupation, education, family income, alcohol consumption, exercise, coffee consumption, tea consumption, and BMI

Binary logistic regression adjusted for age, occupation, education, family income, alcohol consumption, exercise, coffee consumption, tea consumption, daily cigarettes consumption, and BMI

Binary logistic regression adjusted for age, occupation, education, family income, alcohol consumption, exercise, coffee consumption, and tea consumption