In 2022, a retrospective study of 2,567 obese individuals aged ≤ 18 years in Italy employed machine learning models to identify clinical and biochemical predictors of metabolic health status, revealing that the IGF-1 z-score standard deviation (zSDS) was a significant marker for distinguishing metabolically healthy obesity (MHO) from metabolically unhealthy obesity (MUO), thereby underscoring its utility in clinical risk assessment and personalized obesity management27. This evidence concerns the gene IGF1 and obesity due to melanocortin 4 receptor deficiency.