Figure 1.(1) Blood and biometric data, in addition to biological sex, were used to construct a neural network aimed to predict chronological age; (2) The age predicted by the model, hereby denoted as “biological age” was tested in healthy and ill participants to identify conditions interpreted as accelerated aging; (3) Then, regressive analysis was performed using an elastic net to quantify the total contribution of demographic, lifestyle, and psychological factors, hereby denoted as “psychological state,” to biological age; (4) The weight of each variable was understood as age acceleration, with the aggregate effect of one’s psychological state being able to accelerate biological aging by 1.65 years.
