Statistical analyses

We used Shapiro-Wilk test to check the normal distribution of continuous variables. Normally distributed quantitative data were described as means with their standard deviations and were analyzed using the independent t-test. The Pearson r² test was used to check linear correlation. We used the chi-square test for categorical variables.

We utilized multiple logistic regression analysis to estimate the odds ratio (OR) with 95% confidence interval (CI) for the odds of COPD (post-bronchodilation FEV₁/FVC <0.7) in relation to the Fagerström score, age, and pack-years smoking index as independent variables. Multiple linear regression analysis served to evaluate FEV₁%predicted values in relation to the Fagerström score, age, sex, and pack-years smoking index as independent variables. The multiple linear regression analysis was performed both in the overall population and in participants with COPD. The models’ independent variables were initially explored in univariate analyses checking statistical significance; the non-statistically significant independent variables were discarded from the multiple logistic and linear regression models.

We conducted the statistical analysis using IBM/SPSS version 25. The significance level was set to α = 0.05 (two-tailed).