Dermatoglyphics, the study of epidermal ridges on palm, sole, and digits, is considered as most effective and reliable evidence of identification. The fingerprints were studied in 300 Nepalese of known blood groups of different ages and classified into primary patterns and then analyzed statistically. In both sexes, incidence of loops was highest in ABO blood group and Rh +ve blood types, followed by whorls and arches, while the incidence of whorls was highest followed by loops and arches in Rh −ve blood types. Loops were higher in all blood groups except “A –ve” and “B –ve” where whorls were predominant. The fingerprint pattern in Rh blood types of blood group “A” was statistically significant while in others it was insignificant. In middle and little finger, loops were higher whereas in ring finger whorls were higher in all blood groups. Whorls were higher in thumb and index finger except in blood group “O” where loops were predominant. This study concludes that distribution of primary pattern of fingerprint is not related to gender and blood group but is related to individual digits.

Background: Prehypertension in adolescents is an important risk for developing hypertension in later years of life. Hypertension is one of the major cardiovascular problems in urban and suburban areas of Nepal and is increasing among the young population. There are not many studies reported in Nepal which estimates the prevalence of hypertension among medical students. Hence, this study aimed to assess the prevalence of prehypertension and its association with body mass index so that it would assist in developing strategies for control of hypertension and cardiovascular diseases in later years of life Methods: This cross-sectional study included 250 medical students. Anthropometric variables of the subjects were recorded. Height and weight were measured on calibrated scales and body mass index was calculated. Waist and hip measurements were obtained and waist-hip ratio was calculated. Blood pressure was measured with a mercury sphygmomanometer. The data obtained was divided into different groups according to blood pressure and BMI. Descriptive statistics, chi-square test was used for presenting data and testing the significance and P<0.05 was considered as statistically significant. Results: The prevalence of normotensive, prehypertensive and hypertensive students was found to be 75.2%, 20.8% and 4% respectively. Mean BMI was found to be 21.59±3.39. In general, 75.2% of the students had ideal waist hip ratio, 15.2% were underweight, 70 % had normal weight, 12 % were overweight, and 2.8% were found to be obese. Moreover, 51.4% of prehypertensives had BMI more than 25. Prehypertension was significantly higher among males (χ2=16.385, p<0.001) and among the obese medical students (χ2=16.416,p<0.001). Conclusions: Prehypertension is prevalent in about a third of medical students and BMI is found to be significantly associated with pre-hypertension.

Background: Medical students are normally under extreme pressure due to the vast syllabus they have to cover within few years of their student life. The stress due to academic pressure and sudden change in lifestyle tend to affect their sleeping habits, which is considered as one of the potential risk factors for obesity. This study aimed to observe the association between sleep duration, sleep quality and body mass index in medical students. Methods: This is a cross-section study conducted among 269 medical students. Self-reported sleep duration was noted, sleep quality was assessed with Pittsburgh Sleep Quality Index (PSQI) ques­tionnaire. Height in cm and weight in kg was recorded and BMI was calculated. The data obtained was divided into different groups according to sleep duration, sleep quality and BMI. ANOVA and independent t-test was done using Statistical Package for the Social Sciences version 25 for statisti­cal analysis. p< 0.05 was considered statistically significant. Results: In general, 24 (8.9%) of students were underweight, 187 (69.5%) had normal weight, 51 (19%) were overweight and 7 (2.6%) were obese. 94 (34.9%) students reported to spent <7 hours in bed and 98 (36.4%) students had poor sleep quality. Mean BMI was significantly higher in students with short sleep (p-value=0.001, ANOVA) and in students with poor sleep quality (p-value=0.000, independent t-test). Conclusions: Higher BMI was observed in the group of students having poor sleep quality and short sleep duration. Furthermore, poor sleep quality was more prominent in women than in men.