In the current COVID-19 pandemic there are reports of deteriorating psychological conditions among university students in lower-middle-income countries (LMICs), but very little is known about the gender differences in the mental health conditions on this population. This study aims to assess generalized anxiety disorder (GAD) among university students using a gender lens during the COVID-19 pandemic. A cross-sectional study was conducted using web-based Google forms between May 2020 and August 2020 among 605 current students of two universities in Bangladesh. Within the total 605 study participants, 59.5% (360) were female. The prevalence of mild to severe anxiety disorder was 61.8% among females and 38.2% among males. In the multivariable logistic regression analysis, females were 2.21 times more likely to have anxiety compared to males [AOR: 2.21; CI 95% (1.28–53.70); p-value: 0.004] and participants’ age was negatively associated with increased levels of anxiety (AOR = 0.17; 95% CI = 0.05–0.57; p = 0.001). In addition, participants who were worried about academic delays were more anxious than those who were not worried about it (AOR: 2.82; 95% CI 1.50–5.31, p = 0.001). These findings of this study will add value to the existing limited evidence and strongly advocate in designing gender-specific, low-intensity interventions to ensure comprehensive mental health services for the young adult population of Bangladesh.

Background: Self-rated health (SRH) is a globally recognized measure of health status. Both impaired sleep (IS) and the presence of multimorbidity are related to poorer SRH, but the precise nature of these associations remains unclear. This study explored the association between IS, multimorbidity, and SRH among Canadian adults. Method: We used 2017-18 Canadian Community Health Survey (CCHS) data for this study. The main variable of interest, self-rated health (SRH), measured participants' health on a 5-point Likert scale, later categorized as “good or better” vs. “fair or poor”. The primary predictor, IS, was derived from two variables and categorized into four groups: no sleep issues; fewer sleeping hours (<7 hours) only; trouble sleeping only; and fewer hours & trouble sleeping. Multimorbidity was present (yes/no) if a participant indicated being diagnosed with two or more chronic conditions. Results: Just over one in ten Canadians reported fair/poor SRH and approximately one-quarter had multimorbidity or experienced few sleep hours in combination with trouble sleeping. The adjusted model indicated greater odds of fair/poor SRH associated with the 40-64 years age group, male sex, and lower socio-economic status. It also suggested the presence of multimorbidity (AOR= 4.63, 95% CI: 4.06-5.28) and a combination of fewer sleep hours and troubled sleep (AOR= 4.05, 95% CI: 2.86-5.74) is responsible for poor SRH. Forty-four percent of the total effect of IS on SRH was mediated by multimorbidity. Conclusion: This unique finding highlights the mediating role of multimorbidity, emphasizing the importance of addressing it alongside sleep issues for optimal health outcomes.

In a try to understand the pathogenesis, evolution and epidemiology of the SARS-CoV-2 virus, scientists from all over the world are tracking its genomic changes in real-time. Genomic studies can be helpful in understanding the disease dynamics. We have downloaded 324 complete and near complete SARS-CoV-2 genomes submitted in GISAID database from Bangladesh which were isolated between 30 March to 7 September, 2020. We then compared these genomes with Wuhan reference sequence and found 4160 mutation events including 2253 missense single nucleotide variations, 38 deletions and 10 insertions. The C>T nucleotide change was most prevalent (41% of all muations) possibly due to selective mutation pressure to reduce CpG sites to evade CpG targeted host immune response. The most frequent mutation that occurred in 98% isolates was 3037C>T which is a synonymous change that almost always accompanied 3 other mutations that include 241C>T, 14408C>T (P323L in RdRp) and 23403A>G (D614G in spike protein). The P323L was reported to increase mutation rate and D614G is associated with increased viral replication and currently most prevalent variant circulating all over the world. We identified multiple missense mutations in B-cell and T-cell predicted epitope regions and/or PCR target regions (including R203K and G204R that occurred in 86% of the isolates) that may impact immunogenicity and/or RT-PCR based diagnosis. Our analysis revealed 5 large deletion events in ORF7a and ORF8 gene products that may be associated with less severity of the disease and increased viral clearance. Our phylogeny analysis identified most of the isolates belonged to the Nextstrain clade 20B (86%) and GISAID clade GR (88%). Most of our isolates shared common ancestors either directly with European countries or jointly with middle eastern countries as well as Australia and India. Interestingly, the 19B clade (GISAID S clade) was unique to Chittagong which was originally prevalent in China. This reveals possible multiple introduction of the virus in Bangladesh via different routes. Hence more genome sequencing and analysis with related clinical data is needed to interpret functional significance and better predict the disease dynamics that may be helpful for policy makers to control the COVID-19 pandemic in Bangladesh.

Using the Canadian Housing Survey, 2018–2019, we examined self-reported general and mental health among tenants residing in various housing types, including cooperative, non-profit, government, and private housing. Adjusting for confounders, we discovered that tenants in not-for-profit housing reported the highest odds, over four and half times (odds ratio 4.63), of poor general health compared to tenants in privately owned housing in Canada. On the other hand, the odds were reversed for tenants in cooperative housing and government housing, with 24% and 33% lower odds of poor general health, respectively, compared to tenants in privately owned housing. Moreover, we found that tenants in not-for-profit (1.26) and government housing (1.43) reported higher odds of poor mental health. On the other hand, tenants in cooperative housing reported 42% lower odds of poor mental health than tenants in privately owned housing. Furthermore, we observed variations in the odds of poor general and poor mental health among tenants from different equity-seeking groups across different housing types. These findings highlight the importance of considering housing type and equity factors in understanding health outcomes among tenants.