The collected data was analysed using the IBM SPSS for Windows, version 20.0 (IBM, Armonk, NY, USA). The distribution of all variables was verified for normality using the Kolmogorov–Smirnoff test, with verification using skewness and kurtosis. Continuous and categorical variables were expressed as means with standard deviation (SD) and frequency as percentages (%), respectively. The Jonckheere–Terpstra test and the Mantel–Haenszel Chi-square test were used to evaluate trends in p values for continuous and categorical data, respectively. Analysis of variance (ANOVA) was used to test for a mean difference in the distribution of the dietary intake and specific food groups across the E-DII quartiles. A multiple covariate-adjusted logistic regression model was applied to generate the OR and corresponding 95% confidence interval (95% CI) for the risk of CRC and colonic polyps according to E-DII quartile. The multivariable model was adjusted for BMI (for all subjects), age, sex, and smoking status. A linear test for trend was conducted by including the median value of each E-DII quartile as a continuous variable in the regression model. Stratified analyses were carried out in subgroups of factors that have been linked with CRC risk, including sex, age groups, smoking status, and anthropometric indices. The lowest E-DII quartile (the most anti-inflammatory diet) was the reference group for all models. All statistical tests were run with an alpha level of 0.05.
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