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The present study attempted to identify sex of an individual using a fingerprint ridge density at three topological areas in the North Indian population. The study population consisted of 134 males and 136 females aged 17 to 25 years (mean age 19.34±2.12). Ridge density (RD) at radial, ulnar and proximal topological areas of the distal phalanges were determined on the surface area of 25mm . Fingerprint ridge density in a defined area was significantly higher among females as compared to their male counterparts at radial, ulnar and proximal topological areas for both hands. Sexual dimorphic ratio also supported this trend for all three counting areas in right and left hands. Univariate discriminant function analysis explained that the left 2 radial (L2R) (88.1%) had the highest percentage of accuracy for sex identification, followed by the left 3 ulnar (L3U) (82.1%) and the right 2 ulnar (R2U) (81.6%). Multivariate discriminant function analysis showed that the radial topological area of the left hand was the best predictor of sex with the overall accuracy of 84.4%with following discriminant function equation −8.263 − 0.236(L1R) + + 0.321(L2R) + 0.269(L3R) + 0.268(L4R) − 0.067(L5R). It can be inferred that ridge density in the radial topological area of left hand is the most reliable tool for identifying the sex of an individual.

The present study intends to analyse sex distinction in digital dermatoglyphic patterns in convicted prisoners and compare them with a normal control group. For this purpose, a sample of 184 prisoners (149 males, 35 females) as well as 240 normal participants (male 120, female 120) were selected. The prisoner cohort group selected for the study was convicted for the following offences: Section 302 IPC, 307 IPC, 376IPC, 363-364 IPC, 366 IPC, 323-26 IPC. Galton's system of classification was followed to classify various dermatoglyphic patterns. In the male criminal cohort group, the overall frequency of loop patterns (56.51%) was maximum compared to the frequency of whorls (38.79%) and arches (4.7%), while males in the control group exhibited the highest frequency of whorls (48.25%) followed by loops (47.67%) and arches (4.08%). In females, loops were the most frequently occurring pattern, whereas arches were the least frequently seen pattern in both the criminal and cohort group. The frequency of arches was lowest in both the hands with higher fractional percentage in the radial side (thumb and index finger) of distoproximal axis as compared to ulnar side (ring finger and little finger) in both the groups. Pattern intensity index (13.40 vs 13.05), and furuhata's index (69.35 vs 68.47) of the criminal males and females were found to be comparable, but the Dankmeijer's index (12.11 vs 18.93) of the male criminals was lower than their female counterparts, thereby indicating a higher occurrence of arches in the female criminal cohort group.

The analysis of dermal ridges and their configuration on fingertips has been of considerable interest due to their inimitable, permanent and unique characteristics. The present cross-sectional study is an attempt to assess sex as well as topological differences in fingerprint ridge density among adult population of Nahan, Himachal Pradesh, North India. The data comprised of 240 subjects (120 males and 120 females), aged between 18 to 24 years. The results obtained in the study revealed significantly (p<0.001) higher fingerprint ridge density in females than males at radial, ulnar and proximal topological areas. Both the sexes revealed a disto-proximal gradient of fingerprint ridge density i.e proximal < ulnar < radial in both the hands. In regard to radial area fingerprint ridge density of ≤11 ridges and ≥13 ridges had more possibility of male and female origin respectively. Fingerprint ridge density of ≤11 ridges and ≥12 ridges was more likely of male and female origin respectively in the ulnar regions. In proximal region, fingerprint ridge density of ≤8 ridges and fingerprint ridge density of ≥10 ridges had more probability of being male and female origin respectively. Results of discriminant function analysis further strengthen the conclusion of significant gender differences in the ridge density at all the counting areas, thereby confirming fingerprint ridge density as a potential tool for sex distinction.