Evaluation of Stress among Dental Undergraduates and Postgraduates Using Salivary Cortisol as a

Background: Stress is a non?specific response of the body to any demand. Professional education has a certain level of stress inherent in it. Dental students have been reported in the literature to experience more stress than medical students. Objective: To evaluate the stress levels of dental students: first?year undergraduates, house surgeons, and final?year postgraduates, using salivary cortisol as a stress biomarker. Materials and Methods: Dental students above 18 years of age and without any systemic illness were included in the study. Those students with a drug history of corticosteroids, anti?depressants, and oral contraceptives were excluded from the study. Female participants experiencing pre?menstrual symptoms, pregnancy, and familial stressor issues were excluded from the study. First?year undergraduates, house surgeons, and final?year postgraduates were enrolled in the study. Unstimulated whole saliva was collected in the morning and evening between 9:00 and 10:00 am and between 3:00 and 4:00 pm. Salivary cortisol levels were assessed by chemiluminescence immuno?assay (CLIA). Results: Paired sample t?test was used to compare the diurnal variation among morning and afternoon samples within the groups. The salivary cortisol levels were found to be significant within the groups. One?way ANOVA was used to compare the salivary cortisol levels between the groups. The salivary cortisol levels within the groups were not statistically significant. Conclusion: Salivary cortisol is a non?invasive biomarker of stress. Postgraduates had higher salivary cortisol levels than other study groups.

Prevalence and correlates of tobacco use among urban adult men in India: A comparison of slum dwellers vs non-slum dwellers.

Background: Tobacco use is reported to be rampant in urban slums in developing countries. Demographical variations in tobacco use between males living in urban slums vs those living in non-slum areas in India has not been reported, and this study was undertaken to address this issue. Materials and Methods: Secondary data analysis of National Family Health Survey-3 (NFHS-3) was undertaken to study demographical variations in tobacco use between urban slum dwellers and non-slum dwellers in eight Indian cities. Demographic determinants for use of smoking and chewing forms of tobacco in the two groups were analyzed. SPSS® version 16.0 (SPSS Inc., IL, USA) was used for statistical analysis. Result: The study population comprised 6887 (41.8%) males from slum areas and 9588 (58.2%) from non-slum areas of eight urban cities. Cigarette/beedi smoking was the commonest form of tobacco use among the study population. Pan masala use was the least common form of smokeless tobacco use, next only to snuff. There was a high statistical significance observed within the various demographic parameter studied in both the slum and non-slum dwelling males in study population. However, on studying the differences between the two groups, it was observed that statistical significance of P≤.001 was observed with age (15-49), secondary education, religion, household structure and marital status. The difference between the two groups in the mean number of cigarettes/beedis smoked was not statistically significant (P=.598). Discussion and Conclusion: Male slum dwellers are a distinct urban population, whose health needs assessment requires a different approach than that for non-slum dwellers who often can afford the services that an urban Indian city can offer.

Concepts in sample size determination.

Investigators involved in clinical, epidemiological or translational research, have the drive to publish their results so that they can extrapolate their findings to the population. This begins with the preliminary step of deciding the topic to be studied, the subjects and the type of study design. In this context, the researcher must determine how many subjects would be required for the proposed study. Thus, the number of individuals to be included in the study, i.e., the sample size is an important consideration in the design of many clinical studies. The sample size determination should be based on the difference in the outcome between the two groups studied as in an analytical study, as well as on the accepted p value for statistical significance and the required statistical power to test a hypothesis. The accepted risk of type I error or alpha value, which by convention is set at the 0.05 level in biomedical research defines the cutoff point at which the p value obtained in the study is judged as significant or not. The power in clinical research is the likelihood of finding a statistically significant result when it exists and is typically set to >80%. This is necessary since the most rigorously executed studies may fail to answer the research question if the sample size is too small. Alternatively, a study with too large a sample size will be difficult and will result in waste of time and resources. Thus, the goal of sample size planning is to estimate an appropriate number of subjects for a given study design. This article describes the concepts in estimating the sample size.