Background Depression is commonest psychiatric disorder in elderly; it is often misdiagnosed and undertreated. People with depression suffer from impairment of all major areas of functioning ranging from personal care to social capability, which in turn decreases individuals’ quality of life and increases dependency on others Elderly patients with depression are more prone in developing chronic diseases like ischemic heart disease, diabetes mellitus, hypertension. This problem may be more severe in rural population. Objective of this study is to find out the magnitude of depression and its correlates among a rural geriatric population. Materials and Methods Population based cross sectional study was done in Singur, West Bengal with a sample size of 85 with the help of a pretested semi structured schedule and a geriatric depression scale (short form). Results Majority 61.2(%) of the study population were in the age group of 60 to 69 years and most belonged to joint Hindu family. Cardiovascular disease (67.05%) especially hypertension followed by musculoskeletal problems (42.35%) were the two major health related conditions suffered by this population and they usually made avail of government health facilities during illness. About 58.8% of the population suffered from depression and this was associated with nuclear family AOR(95%CI)=8.625(1.697-43.831), with poor income AOR(95%CI)=7.628(1.862-31.847), financial dependence AOR(95%CI)=4.948 (1.044-23.554)and living without spouse AOR(95%CI)=7.422 (1.513-36.418) and also presence of disease OR =5.423 (1.348-21.81). Conclusion Alarmingly, the prevalence of depression was observed to be quite high in this rural population and so was prevalence of different morbidities. All these will hasten the isolation of this vulnerable population from general community and increase burden on younger generation. DOI: http://dx.doi.org/10.3126/nje.v3i4.9515 Keywords:
Road traffic injuries nowadays take the place as a major public health problem constituting leading cause of mortality and morbidity globally and in India, more than a million are injured annually and about a lakh are killed in road traffic accidents. Road traffic accidents are defined as a collision involving at least one vehicle in motion on a public or private road that results in at least one person being injured or killed. In this context, an epidemiological study was conducted in a teaching hospital of West Bengal for last one year for better understanding of the factors involved in road traffic accidents. The study population comprised of all the victims of road traffic accidents attending the emergency department during the study period. Total 355 gave full response with written informed consent and included in the study. Every one out of five subjects was male. Most were from 10-29years age group. Students (18.3%), skilled (21.9%) and unskilled worker (23.7%) by profession were found to be the major victims. More than half (55.5%) of the victims were involved in the two Wheeler accident. Among the all victims 25.92% were released after given first-aid and 48.73% were hospitalized. Half of the accident occurred in July -August and between 6 p.m. to 11p.m. The results ch. can be corroborated with further studies with more robust hypothesis.
Background: Smartphones are now an important gadget for us, but the many are getting addicted to it. Researchers showed that smartphone addiction and late-night usage affects sleep quality. Indian nurses are already facing a heavy burden of depression and present position of nurses is quite insecure. Very few studies were performed over nursing students and that leads to the selection of this topic for my research. Methodology: It was a cross-sectional, observational, and questionnaire-based study, performed over B.Sc. Nursing students of University College of Nursing, WBUHS. The questionnaire has three parts. The first part was for sociodemographic variables, the second part measures the addictive phenomena associated with smartphone overuse using a Smartphone Addiction Scale (SAS), the last part was intended to measure the sleep quality by using Pittsburgh Sleep Quality Index (PSQI). Collected data was compiled and analyzed with the help of MS-Excel from Microsoft Office Package-2016. Results: Out of 91 students, 46 students were found to be not addicted, while 45 were addicted to smartphone, as measured by SAS. On PSQI, 17.58% students were found to be good sleepers, while 82.42% came out to be poor sleepers. Significant association was found between age and smartphone addiction (p=0.000031) and between daily calls and sleep quality (p=0.025333). Conclusion: It can be finally concluded that increase in smartphone usage is now a serious matter of concern and lower age groups are more susceptible towards it. Broad-spectrum studies involving multiple institutions is needed to reveal the bigger picture
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