Psychological distress during pandemic Covid-19 among adult general population: Result across 13 countries.

The COVID-19 pandemics caused an unprecedented mortality, distress, and globally poses a challenge to mental resilience. To our knowledge, this is the first study that aimed to investigate the psychological distress among the adult general population across 13 countries. This cross-sectional study was conducted through online survey by recruiting 7091 respondents. Psychological distress was evaluated with COVID-19 Peritraumatic Distress Index (CPDI). The crude prevalence of psychological distress due to COVID-19 is highest in Vietnam, followed by Egypt, and Bangladesh. Through Multivariate Logistic Regression Analysis, the respondents from Vietnam holds the highest level of distress, while the respondents from Sri Lanka holds the lowest level of distress with reference to Nepal.Female respondents had higher odds of having reported psychological distress, and those with tertiary education were less likely to report psychological distress compared to those with lower level of education. The findings indicate that psychological distress is varies across different countries. Therefore, different countries should continue the surveillance on psychological consequences through the COVID-19 pandemic to monitor the burden and to prepare for the targeted mental health support interventions according to the need. The coping strategies and social support should be provided especially to the lower educational attainment group.

A survey of psychological distress among Bangladeshi people during the COVID-19 pandemic.

INTRODUCTION: Previous studies conducted on the psychological impact of infectious outbreaks have found heavy psychological burdens among general population with more severe affect in the current pandemic. The main aim of this study is to examine the level of psychological distress during COVID-19 in Bangladesh and explore factors associated with higher psychological distress. METHODS: An internet-based, cross-sectional survey was conducted from March to April 2020 in Bangladesh among adults 18 years old and above using structured online questionnaires distributed through emails and other social media throughout Bangladesh with an overall response rate of 34%. Modified version of the Covid19 peritraumatic distress index (CPDI) was used to measure distress. Univariate and Bivariate analysis was used to estimate prevalence of CPDI symptoms and test for the associations between CPDI and the exposure variables. Logistic regression analyses were used to estimate the odds ratios of our outcome variable by exposure variables. RESULTS: Overall, 44.3% of respondents were suffering from mild to moderate distress and 9.5% were suffering from severe distress. Female respondents were 2.435 times more likely to suffer from CPDI mild to severe distress than males. As compared to Dhaka and Mymensing region of Bangladesh, odds of distress was 1.945 times more in Chittagong/Sylhet region (p-value = 0.035). CONCLUSION: Large proportion of adult population in Bangladesh are experiencing psychological distress, with level of distress varies by different symptoms and predictors. This study suggest the need to develop comprehensive crisis prevention system including epidemiological monitoring, screening, and referral with targeted intervention to reduce psychological distress.

Score based risk assessment of lung cancer and its evaluation for Bangladeshi people.

BACKGROUND: The problem of cancer, especially lung cancer, is very acute in Bangladesh. The present study was conducted to evaluate the risk of lung cancer among Bangladeshi people based on hereditary, socio-economic and demographic factors. MATERIALS AND METHODS: This study was carried out in 208 people (patients-104, controls-104) from January 2012 to September 2013 using a structured questionnaire containing details of lung cancer risk factors including smoking, secondhand smoke, tobacco leaf intake, age, gender, family history, chronic lung diseases, radiotherapy in the chest area, diet, obesity, physical activity, alcohol consumption, occupation, education, and income. Descriptive statistics and testing of hypotheses were used for the analysis using SPSS software (version 20). RESULTS: According to this study, lung cancer was more prevalent in males than females. Smoking was the highest risk factor (OR=9.707; RR=3.924; sensitivity=0.8872 and P<0.0001) followed by previous lung disease (asthma, tuberculosis etc.) (OR=7.095; RR=1.508; sensitivity=0.316 and P<0.0001)) for male patients. Highly cooked food (OR=2.485; RR=1.126; sensitivity=0.418 and P=0.004)) and also genetic inheritance (OR=1.93; RR=1.335; sensitivity=0.163 and P=0.138) demonstrated significant correlation with lung cancer as risk factors after these two and alcohol consumption was not prevalent. On the other hand, for female patients, tobacco leaf intake represented the highest risk (OR=2.00; RR=1.429; sensitivity= 0.667 and P=0.5603) while genetic inheritance and highly cooked food also correlate with lung cancer but not so significantly. Socio- economic status and education level also play important roles in causing lung cancer. Some 78.5% male and 83.3% of female cancer patients were rural residents, while 58.2% lived at the margin or below the poverty line. Most male (39.8%) and female (50.0%) patients had completed only primary level education, and 27.6% male and 33.3% female patients were illiterate. Smoking was found to be more prevalent among the less educated persons. CONCLUSIONS: The results obtained in this study indicate the importance of creating awareness about lung cancer risk factors among Bangladeshi people and making appropriate access to health services for the illiterate, poor, rural people.

Early detection of lung cancer risk using data mining.

BACKGROUND: Lung cancer is the leading cause of cancer death worldwide Therefore, identification of genetic as well as environmental factors is very important in developing novel methods of lung cancer prevention. However, this is a multi-layered problem. Therefore a lung cancer risk prediction system is here proposed which is easy, cost effective and time saving. MATERIALS AND METHODS: Initially 400 cancer and non-cancer patients' data were collected from different diagnostic centres, pre-processed and clustered using a K-means clustering algorithm for identifying relevant and non-relevant data. Next significant frequent patterns are discovered using AprioriTid and a decision tree algorithm. RESULTS: Finally using the significant pattern prediction tools for a lung cancer prediction system were developed. This lung cancer risk prediction system should prove helpful in detection of a person's predisposition for lung cancer. CONCLUSIONS: Most of people of Bangladesh do not even know they have lung cancer and the majority of cases are diagnosed at late stages when cure is impossible. Therefore early prediction of lung cancer should play a pivotal role in the diagnosis process and for an effective preventive strategy.