## 2 Materials and Methods
### Data Collection  
A comprehensive set of baseline measurements was performed on all participants, regardless of the study of origin. Thus, a total of 13 variables potentially related to arterial stiffness were measured. Age, gender, and smoking status were obtained directly from participants by healthcare professionals during structured clinical interviews. Smoking status was subsequently categorized into five distinct groups: current smoker, former smoker (quit within the last year), former smoker (quit within 1-5 years), former smoker (quit more than 5 years ago), and non-smoker. Furthermore, measurements of weight, height, and waist circumference (WC) were taken twice using the appropriate equipment, with averages used for analysis. Finally, the body mass index was calculated by dividing the weight in kilograms by the square of the height in meters (kg/m\({}^{2}\)).  
Blood pressure measurements were performed in a tranquil environment after a rest period of five minutes using the Omron(r) M5-I monitor (Omron Healthcare UK Ltd., Milton Keynes, UK), with the appropriate cuff size chosen based on the participant's arm circumference. Systolic and diastolic blood pressures (SBP and DBP) were determined by averaging two separate readings taken five minutes apart. Additionally, pulse pressure (PP) was calculated as the difference between the SBP and DBP averaged pressures. Resting heart  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Dataset** & **N** & **Men (n, \%)** & **Women (n, \%)** & **Age Mean** & **Age SD** \\ \hline EVasCu & 389 & 143 (36.8\%) & 246 (63.2\%) & 42.0 & 13.1 \\ VascuNET & 276 & 115 (41.7\%) & 161 (58.3\%) & 56.8 & 18.9 \\ ExIC-FEp & 76 & 34 (44.7\%) & 42 (55.3\%) & 68.0 & 10.5 \\ \hline \hline \end{tabular} Abbreviations: N = total number of participants; n = number of individuals; % = percentage of participants; age SD = standard deviation of age.  
\end{table}
Table 1: Summary statistics of the datasets used in this study.  
rate (RHR) was also recorded during this assessment. Furthermore, glycated hemoglobin (HbAlc) was measured as a marker of arterial inflammatory alterations using the Roche Diagnostics(r) Cobas 8000 system (Roche Diagnostics GmbH, Mannheim, Germany). To assess arterial oxidative stress, advanced glycation end products (AGEs) were quantified through skin autofluorescence using the AGE Reader(r) device (Diagnoptics Technologies B.V., Groningen, The Netherlands).  
The primary outcome variable aPWV was measured using the Mobil-O-Graph(r) (IEM GmbH, Aachen, Germany) oscillometric device. In this study, two aPWV measurements were taken five minutes apart, and their average was used as the final value. To ensure accuracy, these measurements were performed in a quiet setting after a five-minute rest period. The appropriate cuff size was used, selected based on the circumference of the participant's arm or lower limb.  
It is important to note that although the Mobil-O-Graph(r) is capable of simultaneously measuring blood pressure parameters, in this study, it was used exclusively for aPWV estimation. All blood pressure values (SBP, DBP, and PP) included in the models were obtained using the Omron(r) M5-I monitor. This decision reflects the aim of developing a predictive tool tailored for real-world primary care scenarios, where conventional blood pressure monitors are routinely available, but advanced equipment such as the Mobil-O-Graph(r) is often inaccessible, particularly in low-resource or underserved healthcare settings.