BACKGROUND Frequent use of Facebook and other social networks is thought to be associated with certain behavioral changes, and some authors have expressed concerns about its possible detrimental effect on mental health. In this work, we investigated the relationship between social networking and depression indicators in adolescent population. SUBJECTS AND METHODS Total of 160 high school students were interviewed using an anonymous, structured questionnaire and Back Depression Inventory - second edition (BDI-II-II). Apart from BDI-II-II, students were asked to provide the data for height and weight, gender, average daily time spent on social networking sites, average time spent watching TV, and sleep duration in a 24-hour period. RESULTS Average BDI-II-II score was 8.19 (SD=5.86). Average daily time spent on social networking was 1.86 h (SD=2.08 h), and average time spent watching TV was 2.44 h (SD=1.74 h). Average body mass index of participants was 21.84 (SD=3.55) and average sleep duration was 7.37 (SD=1.82). BDI-II-II score indicated minimal depression in 104 students, mild depression in 46 students, and moderate depression in 10 students. Statistically significant positive correlation (p<0.05, R=0.15) was found between BDI-II-II score and the time spent on social networking. CONCLUSIONS Our results indicate that online social networking is related to depression. Additional research is required to determine the possible causal nature of this relationship.

It is often necessary to estimate the exposure rate at a distance from radionuclide emitting gamma or X rays. Such calculations may be required for planning radiation protection measures around radioactive sources, for calibration radiation monitoring instruments, for patient containing radionuclides or for estimating the absorbed dose to patients receiving brachytherapy. The factor relating activity and exposure rate has been various names: the k factor (Johns, 1961), the specific gamma ray constant (ICRU Rep. 10a, 1962), exposure rate constant (Parker et al., 1978) and gamma rate constant (Kereiakes & Rosenstein, 1980). Conversion to SI units required that this factor be replaced by the air kerma rate constant which is now defined as:  = 2 l A ( air dK dt )  (1)

Cardiovascular diseases (CVD) remain a major burden for public health worldwide. Pivotal concern of primary prevention is identification of individuals that are at risk for developing cardiovascular disease. The use of different algorithms for an assessment of cardiovascular risk allows physicians to identify and treat in a simple and cost-effective manner individuals that may be at high long-term cardiovascular risk.

Significant increase in noncommunicable diseases, in particular cardiovascular disease, in the past few decades worldwide represents one of the major health challenges in the overall global and social development of society. Cardiovascular conditions have the highest impact on lost years of life, lost quality of life, but also on the differences in longevity in different population groups. Global statistics show that cardiovascular conditions are responsible for one third of global deaths, while coronary heart conditions are the leading cause of death worldwide. (1,2) Many population research studies corroborated that high blood pressure is an independent and significant risk factor of cardiovascular disease and coronary heart disease and most significant determinant of morbidity and mortality in developed countries. (2,3)