Methods: This was a cross-sectional questionnaire-based study conducted in a medical school over a period of 3 months (Nov 2018-Jan 2019), where 400 medical undergraduates who use social media participated in the study. Data collected from the questionnaire included the academic performance in terms of university examination marks, the duration of social media use per day and the social media addiction score. Data correlation was done using the Pearson's correlation factor.
Results: 41.5% of students used social media for upto 3 h per day. Whatsapp (98.25%) and Youtube (91.75%) were the most commonly used social media applications. 73.5% used social media to read health-related news, 71.5% used it to complete assignments and more than 50% used it for seminar preparation, test preparation and research-related purposes. Academic performance of female students was better than male students. There was a significantly higher use of social media among academically low-performing medical students compared with high-performing medical students. There was a weak negative correlation between academic performance and social media usage and a strong positive correlation between social media usage and the social media addiction score.
Conclusions: Social media has a negative impact on the academic performance of 21st-century undergraduate medical students.
METHODS: A community-based survey was conducted among families residing in the field practice area of an outreach centre for more than a year. Data were collected using a questionnaire administered to adults aged >18 years. Collected data were entered into and analysed using the Statistical Package for the Social Sciences version 16.0.
RESULTS: Approximately 65.1% of the respondents were aged 31-59 years, and 67.4% were women. Among 126 surveyed households, 50.7% had utilised services from the outreach centre. The facilitators of utilisation among 64 households included proximity to their area of residence (90.6%) and availability of good-quality services (40.6%). The most common barriers included a lack of awareness (30.9%) and inconvenient timings (18.2%) of the healthcare centre. The respondents aged <18 years (odds ratio [OR]=7.64; 95% confidence interval [CI]=4.37-13.37) and >45 years (OR=2.65; 95% CI=1.57-4.47) had higher odds of utilising services than those aged 18-45 years. The female respondents (OR=2.89; 95% CI=1.86-4.51) were more likely to utilise services than the male respondents.
CONCLUSION: Creating awareness regarding the outreach healthcare centre and designing services based on the observed needs of the community can further improve the utilisation of services provided at the healthcare centre.
MATERIAL AND METHODS: In this cross-sectional study, 102 patients with suspected OSA underwent standard polysomnography. All patients with an apnea-hypopnea index (AHI) of ≥5 with symptoms were diagnosed as having OSA. A fasting blood sample was collected from all patients. Blood levels of triglycerides (TGs), total cholesterol (TC), high-density lipoprotein cholesterol (HDL), and low-density lipoprotein cholesterol (LDL) were measured. The relationship between the AHI and lipid profiles was analyzed, and linear regression analysis was performed to evaluate the effect of dyslipidemia on OSA.
RESULTS: The patients with OSA had a significantly higher TG level and a significantly lower HDL level than did those without OSA. The lipid abnormalities increased with OSA severity. The mean serum TG level was higher in the severe OSA group (175±46.5 vs. 153±42.45, mg/dl P = 0.048), and the mean serum HDL level was lower in the severe OSA group (38.43 ± 5.19 vs. 45.73 ± 4.98, mg/dl P = 0.004). Serum TG, cholesterol, and LDL levels were correlated with a BMI of <30 and a BMI of >30 in the OSA group. Linear regression analysis indicated that only age (β = 0.301, P = 0.000), BMI (β = 0.455, P = 0.000), serum HDL level (β = -0.297, P = 0.012), and serum LDL level (β = 0.429, P = 0.001) were the independent predictors of OSA.
CONCLUSION: OSA and obesity are potential risk factors for dyslipidemia. The diagnosis of hyperlipidemia was linked to OSA, and the association was more significant with OSA severity. Hyperlipidemia was well recognized in patients with OSA. LDL and HDL are the independent predictors of OSA.