## 2 Materials and Methods
### Statistical Analysis  
All statistical analyses were performed using the statistical software IBM SPSS Statistics Version 26 [17]. Baseline characteristics were stratified by smoking status (never, current, past). Continuous data are presented as mean (\(\pm\)standard deviation) or median (interquartile range) and compared using analysis of variance (ANOVA) or Kruskal-Wallis tests as appropriate. Categorical variables are presented as counts (percentages) and compared with Chi-square tests (Table 1). To investigate the associations between smoking and hs-cTnI levels, we constructed multivariable adjusted linear regression models using log-transformed hs-cTnI levels as the dependent variable. Hs-cTnI levels were log-transformed due to their skewed distribution. In a first model (Table 2), the smoking status was used as the predictor of interest. In a second model (Table 3), a potential dose-response relationship was assessed using the number of pack-years (classified as \(<\)5, 5-10 or \(>\)10) as the predictor of interest. Based on the Fagerstrom test score [13,14], current smokers were allocated to three groups (2, 3-5, and \(>\)5 points) to further assess the relationship between smoking intensity and hs-cTnI levels (Table 4). To investigate the association between years since smoking cessation and hs-cTnI levels, years since smoking cessation were classified as \(<\)2 years, 2-4 years and \(>\)4 years. (Table 5). The never-smoking group was used as reference for analysis performed using the linear regression models. All the models were first adjusted for age and sex. In a second step, the models were additionally adjusted for a predefined set of covariates including BMI, hypertension, alcohol consumption, educational status, fruit/vegetable consumption, physical activity, LDL-C, HDL-C, and total cholesterol. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**N = 2155**} & \multirow{2}{*}{**Never Smokers N = 1174**} & **Past Smokers** & **Current Smokers** & \multirow{2}{*}{_p-Value_} \\  & & **N = 503** & **N = 478** & \\ \hline
**Sex**, **Female (\%)** & 667 (58.1) & 260 (51.7) & 222 (46.4) & \(<\)0.001 \\
**Age**, **Years** & \(35.6\pm 5.3\) & \(35.8\pm 4.9\) & \(34.5\pm 5.3\) & \(<\)0.001 \\
**Height**, **cm** & \(172\pm 9.19\) & \(172\pm 9.09\) & \(172\pm 9.11\) & 0.31 \\
**Weight**, **kg** & \(71\pm 14\) & \(75\pm 16\) & \(75\pm 15\) & \(<\)0.001 \\
**BMI**, **kg/m\({}^{2}\)** & \(24\pm 4\) & \(25\pm 4\) & \(25\pm 4\) & \(<\)0.001 \\
**Physical Activity**1 (\%)** & 619 (52.7) & 270 (53.7) & 244 (51.0) & 0.70 \\
**Alcohol Consumption**, **g/24 h** & 0.00 (0.00; 1.44) & 0.80 (0.00; 2.14) & 0.80 (0.00; 2.35) & \(<\)0.001 \\
**Highest Education Level** (\%)** & 504 (43.4) & 175 (35.10) & 117 (24.8) & \(<\)0.001 \\
**Fruit/**Vegetable Consumption**2 (\%)** & 271 (23.1) & 110 (21.9) & 82 (17.2) & 0.03 \\
**Systolic BP**, **mm Hg/24 h** & 122.27 \(\pm\) 11.53 & 124.91 \(\pm\) 11.00 & 124.41 \(\pm\) 11.89 & \(<\)0.001 \\
**Diastolic BP**, **mm Hg/24 h** & 78.15 \(\pm\) 7.94 & 79.35 \(\pm\) 8.06 & 79.53 \(\pm\) 8.30 & \(<\)0.001 \\
**Hypertension** (\%)** & 163 (13.9) & 80 (15.9) & 59 (12.3) & 0.27 \\
**LDL-C**, **mmol/L** & 2.84 (23.35; 34.44) & 2.85 (2.31; 3.44) & 2.98 (2.38; 3.63) & 0.06 \\
**HDL-C**, **mmol/L** & 1.53 (1.30; 1.84) & 1.50 (12.12; 1.80) & 1.37 (1.11; 1.66) & \(<\)0.001 \\
**Total Cholesterol**, **mmol/L** & 4.81 (4.26; 5.48) & 4.78 (4.29; 5.35) & 4.78 (4.27; 5.52) & 0.81 \\
**Hs-cTnI**, **ng/L** & 0.70 (0.43; 1.23) & 0.69 (0.43; 1.28) & 0.67 (0.41; 1.04) & 0.04 \\ \hline \hline \end{tabular} Data are presented as mean \(\pm\) SD, median (interquartile range) or number (percentage). 1 Regular physical activity was defined as \(>\)150 min of vigorous activity per week. 2 Regular consumption of fruits and/or vegetables was defined as 5 servings per day.  
\end{table} 
Table 1: Baseline characteristics according to smoking status.