Adamu et al., J Biomed & App Sci FUD (2022) 1:2
Keywords: Body composition, Fingerprints ridge density, sexual dimorphism
2022-11-10 DOI: JOBASFUD_2022_1_1_011
Background: The evolution of fingertip ridges over the years is to allow humans to grasp and grip objects as well as in sex identifications. Fingerprint ridges form through a combination of genetic and environmental factors as a results, no two individuals have same pattern. Aim: The study aimed at determining sexual dimorphism and relationship between body composition and adjacent digit fingerprint ridge density difference (adj. DFRDD). Materials and Methods: The study design was prospective cross-sectional type which involves a total number of 300 students (150 males and 150 females). Bioelectric impedance machine was used for measurements of body composition parameters. A direct sensing method was used for fingerprint capturing. Ridge density was determined from the count of ridges found diagonally within a 25mm2 in ulnar and radial areas. The Adj. DFRDD was determined by subtracting the ridge density from adjacent digits. Results: The results showed a significant sexual dimorphism in ridge density with females having significantly higher median values. A significant difference was also observed between Adj. DFRDD of right 2nd and 4th digits (Rd24), right 3rd and 4th digits (Rd34), left 2nd and 3rd digits Ld23) and left 2nd and 4th digit (Ld24), with males having higher adj. DFRDD. A significant correlation was observed while % body fat, muscle mass and resting metabolism correlated significantly with adj. DFRDD of Rd12, Rd13, Rd15, Rd24, Ld12, Ld13, Ld15 and Ld24 digits. The adj. DFRDD of Rd14 and Ld45 correlated only with % body fat and muscle mass. The muscle mass and resting metabolism in other hand correlated only with the adj. DFRDD of Rd45 and Ld23. However, the resting metabolism additionally correlated with the adj. DFRDD of Rd34, Ld14 and Ld35. Conclusion: The best predictors of % body fat and muscle mass was found to be Rd12. Whereas the Ld12 was found to be the best predictor of resting metabolism. In conclusion, a significant sexual dimorphism and relationship was established between the Adj. DFRDD with body composition, hence, the adj. DFRDD may be used a tool for estimation of some body composition parameters.