Predictive factors of anxiety and depression in COVID-19 survivors: A cross-sectional study.

Background: Depression and anxiety are among the most critically recognized psychological complication of the COVID-19 pandemic. Aim: This study aimed to examine the two predictors among COVID-19 survivors in Ahvaz, Iran, in 2022. Methodology: Using a descriptive-analytical design, 347 COVID-19 survivors referred to hospitals in Ahvaz were meticulously examined. The database of the COVID-19 registration system contained primary information about the samples. For data collection, questionnaires, including the Beck Anxiety and Depression Inventory and a demographic questionnaire, were utilized. Results: The results revealed a significant relationship between anxiety score and family size (p = 0.019), education level (p < 0.001), occupation (p = 0.015), household income status (p = 0.017), disease history (p = 0.017), ethnicity (p < 0.001), disease severity (p < 0.001), and quarantine period (p < 0.001). Furthermore, a significant correlation was observed between the average depression score and gender (p = 0.023), number of family households (p = 0.009), level of education (p < 0.001), occupation (p < 0.001), household income (p < 0.001), disease severity (p < 0.001), disease history (p < 0.001), and quarantine period (p < 0.001). Moreover, linear regression analysis indicated only a significant relationship between depression scores and the quarantine period variable (p < 0.001), among others. The simultaneous examination of all variables on depression disorder highlighted a meaningful relationship between depression score and disease history (p = 0.013), occupation (p = 0.002), household income status (p = 0.002), and family size (p = 0.039). Conclusions: This study revealed a significant relationship between certain demographic variables, such as quarantine period, disease history, employment status, household income status, and the number of family households, and an increase in the average depression and anxiety score.

Association between the incidence and mortality rates for corpus uteri cancer and human development index (HDI): a global ecological study.

OBJECTIVE: The aim of this study was to determine the association between the incidence of and mortality due to corpus uteri cancer (CUC) and the human development index (HDI) across the world. METHODS: This was an ecological study. The incidence and mortality rates of CUC along with HDI data were extracted from the Global Cancer Data in 2018. Subsequently, correlation coefficient and linear regression model were used to determine the association between the incidence and mortality rates of CUC and the HDI. STATA-14 was used for data analysis. RESULTS: There was a positive and significant correlation between the incidence (r=0.693; P<0.001) and mortality (r=0.284; P<0.001) rates of uterine cancer and the HDI. A positive and significant correlation was also observed between the incidence rate and the gross national income per 1,000 capita (r=0.440; P<0.001), mean years of schooling (MYS) (r=0.740; P<0.001), life expectancy at birth (LEB) (r=0.590; P<0.001), and expected years of schooling (r=0.650; P<0.001). The results of the linear regression model showed a significant statistical association between MYS and the incidence of CUC (ß=1.10; 95% confidence interval [CI], 0.60-1.70) and LEB and mortality due to uteri cancer (ß=0.40; 95% CI, 0.10-0.90). CONCLUSION: The results of this study suggest a significant statistical association between the incidence and mortality rates of CUC and the HDI.

Prevalence of Risky Behaviors and Related Factors among Students of Dezful.

Objective: There is a likelihood of risky behaviors such as drug abuse, risky sexual behavior, and adaptability issues in young ages. The present study aimed at investigating the prevalence of risky behaviors among students of Dezful University of Medical Sciences in 2014. Method: This was a descriptive-analytical cross sectional study, with a random sampling approach. Scale of measuring risky behaviors was used to measure the risky behaviors (high speed driving, maim, drug use, and sexual behaviors) and related factors. The mean, standard deviation, Chi-square tests, t tests, and ANOVA were used for data analysis. Results: The study was conducted on 150 (50%) female and 150 (50%) male students. Most of the participants aged 20 to 24 years. A statistically significant difference was obtained between the average scores of risky behaviors among female and male students (p˂0.05). The results of the present study revealed that the prevalence of risky behaviors, high speed driving, and drug consumption was different among the students of various study fields (p˂0.05). Conclusion: The prevalence of risky behaviors among students of Dezful University was relatively low, and the prevalence of these behaviors in female students was far less than in male students. Risky behaviors were associated with background variables, except for mother's occupation.