Determinants, risk factors and spatial analysis of multi-drug resistant pulmonary tuberculosis in Jodhpur, India.

This study was planned to estimate the proportion of confirmed multi-drug resistance pulmonary tuberculosis (TB) cases out of the presumptive cases referred to DTC (District Tuberculosis Center) Jodhpur for diagnosis; to identify clinical and socio-demographic risk factors associated with the multidrug-resistant pulmonary TB and to assess the spatial distribution to find out clustering and pattern in the distribution of pulmonary TB with the help of Geographic Information System (GIS). In the Jodhpur district, 150 confirmed pulmonary multi-drug resistant tuberculosis (MDR-TB) cases, diagnosed by probe-based molecular drug susceptibility testing method and categorized as MDR in DTC's register (District Tuberculosis Center), were taken. Simultaneously, 300 control of confirmed non-MDR or drug-sensitive pulmonary TB patients were taken. Statistical analysis was done with logistic regression. In addition, for spatial analysis, secondary data from 2013-17 was analyzed using Global Moran's I and Getis and Ordi (Gi*) statistics. In 2012-18, a total of 12563 CBNAAT (Cartridge-based nucleic acid amplification test) were performed. 2898 (23%) showed M. TB positive but rifampicin sensitive, and 590 (4.7%) showed rifampicin resistant. Independent risk factors for MDR TB were ≤60 years age (AOR 3.0, CI 1.3-7.1); male gender (AOR 3.4, CI 1.8-6.7); overcrowding (AOR 1.6, CI 1.0-2.7); using chulha (smoke appliance) for cooking (AOR 2.5, CI 1.2-4.9), past TB treatment (AOR 5.7, CI 2.9-11.3) and past contact with MDR patient (AOR 10.7, CI 3.7-31.2). All four urban TUs (Tuberculosis Units) had the highest proportion of drug-resistant pulmonary TB. There was no statistically significant clustering, and the pattern of cases was primarily random. Most of the hotspots generated were present near the administrative boundaries of TUs, and the new ones mostly appeared in the area near the previous hotspots. A random pattern seen in cluster analysis supports the universal drug testing policy of India. Hotspot analysis helps cross administrative border initiatives with targeted active case finding and proper follow-up.

Exploring internet addiction and its associated factors among college students in Western Rajasthan, India: A mixed-methods study.

Background: With near universal use of internet by college students, there is propensity for internet addiction (IA) among them. This study aimed to estimate the prevalence and predict the factors for internet addiction among college students in Jodhpur, Rajasthan, India, and qualitatively explore the factors associated with internet addiction. Materials and Methods: Explanatory sequential (QUAN-QUAL) mixed-methods design was used. A cross-sectional questionnaire-based survey was conducted among three streams of undergraduate colleges (health, engineering, and others). Survey instruments included Young's internet addiction test (IAT), Pittsburgh Sleep Quality Index (PSQI), and Depression, Anxiety, and Stress Scale-21 (DASS-21) Items. Focus group discussions (FGDs) and in-depth interviews (IDIs) among the students with mild-to-moderate levels of addiction were conducted to understand the reasons for excessive internet use. Results: The prevalence of internet addiction (IA) among the college students was 51% and the rates for mild, moderate, and severe addiction were 31.8%, 18.5%, and 0.7%, respectively. Predictors of IA were male gender, age in years, age of first internet use in years, urban origin, accessing internet at college, mobile internet use, using internet to make online friendship, sleep disturbance, depression, anxiety, and stress. Qualitative study identified five major themes related to situations initiating internet use for nonacademic purpose, content of internet use, triggers for internet overuse/addiction (IA), perceived impact of IA, and measures to overcome IA. Conclusions: Internet addiction was found to be highly prevalent in college students across various streams. Qualitative results provide deeper insights into IA among college students. It is imperative to screen for IA among the students and devise suitable preventive interventions, which can be easily implemented at community level.

Adding life to years: Role of gender and social and family engagement in geriatric depression in rural areas of Northern India.

BACKGROUND: Depression among elderly population is a major public health issue affecting nearly 5% to 7% of the world's elderly. In the coming years, a major share will be contributed by developing countries like India. In the rural areas of Allahabad district of Uttar Pradesh, there is scarce data on the depression. METHODOLOGY: A community-based cross-sectional study was conducted in rural Allahabad. A total of 411 elderly persons were selected from 2 blocks-Jasra and Bahadurpur-through multistage random sampling method. Short form of geriatric depression scale (GDS) was used to assess depression. RESULTS: The prevalence of depression among elderly was 19.7%. On binary logistic regression, depression had significant association with female sex [aOR = 2.4, 95% CI 1.1-5.1], having less-than-good relationship with family members [aOR = 2.7, 95% CI 1.2-6.0], not being cared for during illness by family members [aOR = 3.9, 95% CI 1.2-12.9], not being involved in leisure time activities [aOR = 2.5, 95% CI 1.3-4.9], and not regularly meeting relatives and friends [aOR = 4.7, 95% CI 1.9-11.6]. CONCLUSIONS: The prevalence of depression in elderly was high in rural areas of Allahabad. Female sex and social and family engagement are the important predictors of depression among them.