Abstract:
Obesity, characterized by excessive fat accumulation, arises from an imbalance between energy consumption and expenditure. It is a major risk factor for cardiovascular diseases, type 2 diabetes, and metabolic syndrome. In this retrospective case-control study, we examined the relationship between obesity and iris features frequently utilized in iridology, a practice that studies iris features to assess health conditions. We analyzed the correlation between iris markers and obesity obesity-related test results in 197 adults (99 obese, 98 normal-weight) using anonymized medical records and iris images. Obesity was defined as a BMI of 25 or higher. Trained practitioners examined iris images for markers such as lacunae around the autonomic nerve wreath (ANW), toxic spots around ANW, protrusion around ANW, and lacunae in the cardiac region. They evaluated each marker using a 0-2 grading system. Obese individuals showed more pronounced features, including lacunae and toxic spots around ANW. Normal-weighted individuals showed thicker and more protruded ANW (suggesting increased sympathetic nervous system activity). These markers correlated with clinical measurements of obesity such as waist and hip circumference, visceral fat area, body fat mass, and percent body fat. Each iris marker tended to correlate with different test items. The results suggest that iridology could be utilized to identify obesity-related detailed pathophysiological factors. Iridology combined with advanced technologies such as deep learning and artificial intelligence may further improve early detection and personalized treatment approaches for obesity-related health issues, potentially making iridology a useful component in comprehensive obesity management programs.
Authors: Authors Kim Ha-kwon Choi Jeong-eun Yoo Ho-ryong Choi Seong-hwan Park Seong-il Park Hyeon-jeong Park Mi-so
Korean Society of Oriental Medical Pathology Journal of Oriental Physiology and Pathology
Reference: https://scholar.kyobobook.co.kr/article/detail/4040070853964
