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. 2016 Nov 11;28(2):408–414. doi: 10.1093/annonc/mdw618

Table 2.

Pooled odds ratios (OR), and corresponding 95% confidence intervals (CI), of pancreatic cancer for high versus low acrylamide intake, overall and in strata of selected covariates. International Pancreatic Cancer Case–Control Consortium (PanC4)

Covariate Low intake (1st quartile)
High intake (4th quartile)
OR (95% CI)a P valueb
Cases, n (%) Controls, n (%) Cases, n (%) Controls, n (%)
Overall 450 (22.8) 1057 (24.9) 559 (28.3) 1064 (25.1) 0.92 (0.66–1.28)
Sex
 Male 207 (18.0) 471 (20.2) 375 (32.6) 695 (29.8) 0.78 (0.44–1.36)
 Female 243 (29.4) 586 (30.7) 184 (22.3) 369 (19.3) 1.16 (0.67–2.01) 0.32
Age
 <65 181 (19.0) 469 (23.1) 299 (31.3) 549 (27.1) 0.88 (0.51–1.51)
 ≥65 269 (26.3) 588 (26.6) 260 (25.5) 515 (23.3) 0.94 (0.72–1.23) 0.83
Smoking habit
 Never smokers 204 (27.7) 528 (27.8) 179 (24.3) 416 (21.9) 1.08 (0.79–1.47)
 Former cigarette smokers 167 (22.4) 414 (24.0) 220 (29.4) 459 (26.6) 0.79 (0.50–1.23)
 Current cigarette smokers 72 (16.2) 95 (18.8) 144 (32.5) 164 (32.5) 0.56 (0.22–1.46) 0.29
Body mass index (BMI)c
 <30 kg/m2 315 (22.3) 768 (24.8) 402 (28.4) 779 (25.2) 0.93 (0.60–1.43)
 ≥30 kg/m2 75 (20.9) 142 (24.7) 107 (29.8) 143 (24.9) 0.90 (0.46–1.78) 0.94
Diabetes
 No 347 (22.2) 957 (25.0) 442 (28.3) 953 (24.9) 0.92 (0.65–1.30)
 Yesd 96 (24.5) 100 (24.4) 111 (28.3) 111 (27.1) 0.79 (0.41–1.51) 0.69
Study area
 USA (4 studies) 305 (24.2) 744 (24.9) 336 (26.6) 750 (25.1) 0.80 (0.50–1.26)
 Other (2 studies) 145 (20.3) 313 (25.0) 223 (31.2) 314 (25.1) 1.17 (0.77–1.77) 0.23
a

ORs from multivariate logistic regression models adjusted for age, sex, race/ethnicity, education, smoking habits, diabetes, body mass index, and total energy intake.

b

P value for heterogeneity between strata.

c

Information was not available in the University of Minnesota study, thus, the OR estimates on acrylamide intake in strata of BMI are based on five studies.

d

OR estimate is based on five studies, since for the LSU study, there were too few diabetic patients for the model to converge.