Association and Prediction of Hypertension and Diabetes Mellitus Using Dermatoglyphic Parameters: A Cross-sectional Study from Southwest, Nigeria

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Background and Aim: Dermatoglyphics, the study of fingerprints, has long been utilized in criminology. However, its application has expanded into the fields of medical and genetic diagnosis. This study investigated the relationship between dermatoglyphic parameters and hypertension and diabetes mellitus, potentially aiding in the early identification and management of these conditions. Methods: The study included 214 from Yoruba ethnicity including 70 hypertensive and 140 diabetic with 70 T2DM patients (59 females, 11 males, aged 47-85) from UNIMEDTH and 70 non-diabetic controls (51 females, 19 males, aged between 18-26 years participants from the University of Medical Sciences Teaching Hospital in Ondo and Akure, Ondo state, Nigeria. Dermatoglyphic patterns were analyzed with gender differences. Logistic regression models were used to predict diabetes mellitus and hypertension based on dermatoglyphic parameters, demonstrating high accuracy. Results: The results revealed that ulnar loops and whorl patterns were more prevalent among hypertensive (57.8 and 40.9%) and normotensive (37% and 24.9%) individuals, respectively. Significant differences in dermatoglyphic parameters were observed between diabetics and controls, with higher total finger ridge count (p=0.012) and lower ATD angle (p=0.028) in diabetics. There was a significant difference in dermatoglyphic parameters between male and female study participants. Additionally, the model fit statistics and classification accuracy of the logistic regression models show that finger patterns outperform palmar patterns in classifying hypertension accuracy. Conclusion: In conclusion, the findings suggest a potential association between dermatoglyphics and hypertension and diabetes and higher accuracy in finger pattern classification, which suggests its potential as an efficient predictor of hypertension for practical clinical applications.

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