SPISE INDEX (Single point insulin sensitivity estimator): indicator of insulin resistance in children and adolescents with overweight and obesity

Background: Insulin resistance in children and adolescents with obesity is linked to increased risk of type 2 diabetes mellitus and cardiovascular disease. The SPISE index, based on values of fasting triglycerides (mg/dL), HDL cholesterol (mg/dL), and BMI (kg/m2), shows promise in predicting insulin resistance in children. Methods: This study aimed to identify a SPISE cut-off for detecting insulin resistance and evaluate its relationship with pubertal development, anthropometrics, and glycometabolic profile in 232 children and adolescents, 105 males and 127 females (median age 13.2 years) with overweight (n=48) and obesity (n=184). SPISE index was calculated with the formula: 600 x HDL Cholesterol0,185/Triglycerides0,2x BMI1,338, and patients were categorized based on Tanner stages [(Group 1 (18.8%) Tanner 1, Group 2 (44.6%) Tanner 2-3-4, Group 3 (36.6%) Tanner 5)]. Results: A SPISE cut-off ≤ 6.92 or ≤ 6.13 (based on the method used for insulin resistance detection), in subjects with Tanner stages I and II, showed good sensitivity and specificity as a marker of insulin resistance. SPISE index decreased significantly with the advancement of pubertal status (P < 0.0001) and with worsening severity of obesity (P < 0.0001). While no significant differences in SPISE marker were observed between patients with normal and abnormal glucose tolerance during OGTT within any pubertal stage, SPISE values were significantly lower in patients with confirmed insulin resistance (total sum of insulin OGTT ≥ 535 µu/mL) in all three pubertal groups (Group 1: P=0.008; Group 2: P=0.0008 and Group 3: P=0.002, respectively). Conclusions: In children and adolescents with obesity the SPISE index can be proposed as an alternative to OGTT and other insulin-based methods for evaluating insulin resistance. Its advantage lies in using readily available and inexpensive laboratory tests, making it suitable for large-scale studies and follow-up monitoring across diverse populations.