Background and Aim: Fingerprints are a unique identification tool useful in the forensic investigation for detection of crimes. The probability of two people having an identical pattern of fingerprints is one in 64,000 million. The ridge pattern of fingerprints developed during fetal period do not change throughout their life until skin decomposes. The pattern of fingerprints differ widely with blood group variation. Therefore, the present study aimed to correlate the pattern of fingerprints with blood groups. Methodology: This prospective study was conducted on 178 medical students (MBBS and BDS) in the Department of Forensic Medicine, District Headquarters Hospital and Benazir Bhutto Hospital, Rawalpindi for the period from November 2021 to April 2022. Prior to study conduction, ethical approval was taken from the institutes research and ethical committee. Written informed consent was obtained from each individual. Participants with known blood groups having age range from 17 to 23 years were enrolled. Ink method was used for taking fingerprints. Patterns of fingerprints were categorized as loops, whirl, arches, and composite. SPSS version 25 was used for data analysis. Results: Of the total 178 medical students, there were 48 (27%) male and 130 (73%) females. The overall mean age was 21.6 ± 1.4 years with an age range from 17 to 23 years. Out of total medical students, the incidence of blood group A, B, AB, and O was 53 (29.8%), 31 (17.4%), 19 (10.7%), and 75 (42.1%) respectively. The prevalence of Rh-positive was 90.4% (n=161) among the studied cases. Loop pattern was the most prevalent fingerprints pattern observed in 95 (53.4%) cases. Majority of loop patterns were seen in blood group O participants. Other fingerprints pattern such as whorls, arches, and composite were found in 49 (27.5%), 24 (13.5%), and 10 (5.6%) respectively. Conclusion: The present study concluded that blood group “O” was the most prevalent group followed by A, B, and AB. Loop was the most common pattern of fingerprints among blood groups especially in blood group O. The prevalence of Rh-positive was found higher among the study cases. Keywords: Pattern, Fingerprints, Blood group.

Objective: Aim of this study was to find out correlation between arm span length and height. The regression equation obtained will be used to estimate height from arm span length. Method: Study design: cross sectional study. Study sample: 108 male students of Sialkot medical college. Sampling Technique: Non probability purposive sampling technique was used to select the samples. Selection criteria: Male students of Sialkot medical college having no deformity of limbs and vertebral column were selected. Collection of data: Standing height was measured in inches. Arm span length was measured by extending arms. Statistical analysis: SPSS version 25 was used to perform statistical analysis. Correlation coefficient and regression equation was obtained. Tables and graphs were made. Results: The value of Pearson correlation coefficient was 0.846. A statistically positive very strong and significant correlation was found between height and arm span length. Conclusion: The results of this study indicate that arm span length can be used to estimate standing height. The regression equation can be used to predict standing height in a person who can not stand up. Keywords: Arm span length, height, Pearson correlation coefficient. How to cite: Maria G, Asif M, Farid N, Khattak A, Masood R, Ahmed A. Correlation Between Arm Span Length and Height. Esculapio - JSIMS 2022;18(01):52-55.