Endocrinology & Metabolic Syndrome
Open Access
ISSN: 2161-1017
ISSN: 2161-1017
Ali Nabavizadeh
Maseno University, Kenya
Scientific Tracks Abstracts: Endocrinol Metab Syndr
Statement of the Problem: Thyroid dysfunction, encompassing hypothyroidism, hyperthyroidism, and their subclinical counterparts, affects millions globally and has significant metabolic implications. Insulin resistance (IR), a precursor to type 2 diabetes and cardiovascular disease, is often assessed using insulin-based indices. The Metabolic Score for Insulin Resistance (METS-IR), a novel non-insulin based marker, offers a practical alternative. However, the relationship between thyroid function and METS-IR remains unexplored. Methodology & Theoretical Orientation: We conducted a cross-sectional analysis of 6,507 adults aged â?Â¥ 20 years from the National Health and Nutrition Examination Survey (NHANES) 2007â??2012. Participants were categorized into five thyroid function states using thyroid-stimulating hormone (TSH) and free thyroxine (FT4) levels. METS-IR was calculated from fasting glucose, triglycerides, HDL-C, and BMI. Multivariate regression models adjusted for demographic, lifestyle, and clinical covariates were employed to investigate associations. Findings: Higher TSH levels were positively associated with METS-IR (ÃÂ?² = 0.003, 95% CI 0.001â??0.004, p = 0.021). Subclinical hypothyroidism in males and subclinical hyperthyroidism in females were significantly linked to elevated METS-IR. Thyroid peroxidase antibody positivity amplified the association between overt hypothyroidism and METS-IR. These findings suggest that thyroid dysfunctionâ?? even in subclinical formsâ??may predispose individuals to higher insulin resistance risk. Conclusion & Significance: This study is the first to demonstrate a significant relationship between thyroid function and METS-IR. The results highlight the potential role of thyroid status as an early marker of insulin resistance. Incorporating thyroid function assessments into routine metabolic evaluations could improve early detection and prevention strategies for IR-related diseases. Further research is warranted to explore underlying mechanisms and longitudinal outcomes.
Ali Nabavizadeh, Director of Imaging at DÃÂ?³b and Assistant Professor at the University of Pennsylvania, specializes in advanced MRI and PET imaging to study pediatric brain tumors. His research integrates structural, physiologic, and molecular imaging with bioinformatics to improve diagnosis, monitor treatment, and distinguish progression from treatment effects. He completed fellowships in pediatric neuroradiology, neuroradiology, and nuclear radiology in Philadelphia.