Survey In Bangladesh Research Articles

Prevalence and risk factors of stroke in Bangladesh: A nationwide population-based survey.

BackgroundA paucity of high-quality epidemiological survey on stroke in Bangladesh emphasizes the need for a drastic effort at the national level to study the burden of stroke in Bangladesh. Therefore, this community survey was conducted with to estimate the prevalence of stroke and its associated common risk factors among Bangladeshi population.MethodsThis was a population-based cross-sectional study, carried out in 8 administrative divisions and 64 districts to estimate the prevalence of stroke throughout the country. The study adopted a two-stage cluster random sampling approach. The calculated sample size was 25,287. A semi-structured questionnaire was used to identify suspected stroke patients who were subsequently confirmed by consultant neurologists.ResultIn the first stage, a total number of 25,287 respondents were interviewed throughout the country. Interviewers identified 561 respondents as suspected stroke through the Questionnaire for Verifying Stroke Free Status (QVSFS) system in 64 districts. Of the 25,287 respondents 13,878 (54.9%) were male and 11,409 (45.1%) were female. Mean age was 39.9 years. In the second stage, all suspected stroke cases (561) were further examined by neurologists and finally 288 patients were confirmed as stroke which provided a prevalence of 11.39 per 1000 population. The highest stroke prevalence (14.71 per thousand) were found in Mymensingh division and lowest (7.62 per thousand) found in Rajshahi division. The stroke prevalence varied in different age groups. It was 30.10 per thousand in the age group of >60 years and 4.60 in the age group below 40 years. The prevalence of stroke among male was twice that of female (13.62 versus 8.68 per thousand). The prevalence was slightly higher in rural areas (11.85 versus 11.07). About 50.4% respondents had some idea about stroke.Out of a total of 288 cases, 79.7% (213) patients had an ischemic stroke, 15.7% (42) had hemorrhagic, and 4.6% (12) were diagnosed as subarachnoid hemorrhage. The majority of the stroke patients had hypertension (79.2%), followed by dyslipidemia (38.9%), tobacco use in any form (37.2%), diabetes (28.8%), ischemic heart disease (20.1%).ConclusionWe have found a stroke prevalence of 11.39 per 1000 population, the highest being in the Mymensingh division. The prevalence was much higher in the elderly and male population. More than three fourth had an ischemic stroke. Hypertension, dyslipidemia, tobacco use, diabetes, ischemic heart disease are the most common risk factors observed among stroke patients.

Pattern of Antibiotic Use among Hospitalized Patients according to WHO Access, Watch, Reserve (AWaRe) Classification: Findings from a Point Prevalence Survey in Bangladesh.

For supporting antibiotic stewardship interventions, the World Health Organization (WHO) classified antibiotics through the AWaRe (Access, Watch, and Reserve) classification. Inappropriate use of antimicrobials among hospital-admitted patients exposes them to the vulnerability of developing resistant organisms which are difficult to treat. We aimed to describe the proportion of antibiotic use based on the WHO AWaRe classification in tertiary and secondary level hospitals in Bangladesh. A point prevalence survey (PPS) was conducted adapting the WHO PPS design in inpatients departments in 2021. Among the 1417 enrolled patients, 52% were female and 63% were from the 15–64 years age group. Nearly 78% of patients received at least one antibiotic during the survey period. Third-generation cephalosporins (44.6%), penicillins (12.3%), imidazoles (11.8%), aminoglycosides (7.2%), and macrolides (5.8%) were documented as highly used antibiotics. Overall, 64.0% of Watch, 35.6% of Access, and 0.1% of Reserve group antibiotics were used for treatment. The use of Watch group antibiotics was high in medicine wards (78.7%) and overall high use of Watch antibiotics was observed at secondary hospitals (71.5%) compared to tertiary hospitals (60.2%) (p-value of 0.000). Our PPS findings underscore the need for an urgent nationwide antibiotic stewardship program for physicians including the development and implementation of local guidelines and in-service training on antibiotic use.

Exploring hot spots of short birth intervals and associated factors using a nationally representative survey in Bangladesh

Short Birth Interval (SBI, defined as < 33 months interval between the two most recent births or < 24 months between one live birth to the next pregnancy) is a public health problem in most low- and lower-middle-income countries. Understanding geographic variations in SBI, particularly SBI hot spots and associated factors, may help intervene with tailored programs. This study identified the geographical hot spots of SBI in Bangladesh and the factors associated with them. We analyzed women’s data extracted from the 2017/18 Bangladesh Demographic and Health Survey and the healthcare facility data extracted from the 2017 Service Provision Assessment. SBI was the outcome variable, and it was defined as an interval between consecutive births of 33 months or less, as recommended by the World Health Organization. The characteristics of mothers and their partners were the explanatory variables. Moran’s I was used to examine the spatial variation of SBI in Bangladesh whereas the Getis-Ord {G}_{i}^{*}(d) was used to determine the hot spots of SBI. The Geographical Weighted Regression (GWR) was used to assess the predictors of SBI at the enumeration areas’ level. The variables included in the GWR were selected using the exploratory regression and ordinary least square regression model. Data of 5941 women were included in the analyses. Around 26% of the total births in Bangladesh had occurred in short intervals. A majority of the SBI hot spots were found in the Sylhet division, and almost all SBI cold spots were in the Rajshahi and Khulna divisions. No engagement with formal income-generating activities, high maternal parity, and history of experiencing the death of a child were significantly associated with SBI in the Sylhet division. Women’s age of 34 years or less at the first birth was a protective factor of SBI in the Rajshahi and Khulna divisions. The prevalence of SBI in Bangladesh is highly clustered in the Sylhet division. We recommend introducing tailored reproductive health care services in the hot spots instead of the existing uniform approach across the country.

Weighting National Survey Data in Bangladesh: Why, How and Which weight?

Background: Weighting of national survey data enables the sample to be more representative of the target population. Weighting procedure is a thorough exercise and yields several types of weights. However, considerable variation exists among authors on which weight to use leaving the researchers baffled. As a result, survey data are often used by researchers without the weights leading to erroneous conclusions. In addition, despite availability of powerful yet costly statistical software•• researchers from developing countries are mostly unable to use those due to high cost. In this article, we share our experience on weighting for recent national surveys in Bangladesh using Microsoft Excel. Objectives: Overall objective was to perform sample weighting of a national survey of Bangladesh using Excel. As specific objective, the study was aimed at creating different weighting variables, describe their features and identify the appropriate weight to be used for analysis. Methods: We generated four types of weights: the base weight calculated from probabilities of selection, and non-response adjusted, population calibration adjusted, and trimmed weights. We compared the distribution of the population by sex and age by unweighted and four types of weighted numbers. Finally, we calculated weighted means, medians, ranges, standard errors, confidence intervals, variances, multiplicative effects and design effects with these four weights. In addition, we compared the weighted prevalence of a key variable of the survey using these four weights. Results: We compared unweighted distribution with weighted ones and identified that weighting makes the sample distribution to conform to the target population. Among the four calculated weights, the trimmed weight had narrow standard error and variance, and smallest design and multiplicative effects. It yielded an acceptable prevalence and distribution of prevalence of mental disorder. Conclusion: Among the four weights, we show that the trimmed weight met all parameters of good quality and precision. We performed this complex exercise using Microsoft Excel which is largely available to researchers in Bangladesh. Therefore, we recommend using the trimmed weight for national level surveys in Bangladesh in a similar context. Bangladesh Med Res Counc Bull 2021; 47(2): 118-126

Internet addiction during COVID-19 restricted movement period: A cross-sectional study from Bangladesh

Background: The restricted movement period related to COVID-19 has presumably contributed to the deterioration of the Internet addiction crisis. Therefore, this study aimed to determine the prevalence of Internet addiction and identify the factors associated with the increase in severity of Internet addiction among the general population of Bangladesh during the COVID-19 related restricted movement period. Methods: We conducted a cross-sectional online survey in Bangladesh from September 20 to October 5, 2020, and 315 Bangladeshi adults were included in the study. We used Young’s Internet Addiction Scale to assess the prevalence of Internet addiction and identified the factors associated with the increase in severity of Internet addiction during the restricted movement period using multivariable logistic regression analysis. Results: The overall prevalence of Internet addiction was 39.7% among the general population of Bangladesh during the restricted movement period. Almost 75% of the respondents reported increased time spent on recreational use of the Internet during the period of interest, and 48.5% of the respondents reported increases in the severity of Internet addiction. In logistic regression analyses, the increase in severity of Internet addiction was found to be significantly associated with social class, occupation, sleeping hours, and increased time spent on recreational use of the internet (p &lt; 0.05). Watching movies/series was the main activity of the respondents during the restricted movement period. Conclusion: Our study reported an increase in the prevalence of Internet addiction among the general population of Bangladesh during the restricted movement period. Social class, occupation, sleeping hours, and increased time spent on recreational use were the significant determinants of the increase in severity of Internet addiction. The policymakers should undertake tailored policies to prevent people from being victims of the consequences of psychological issues in the long run.

Consumers' intention toward buying ethically produced products in Bangladesh

PurposeWhile many companies begin to promote ethically produced products, much remains to be known about consumers' buying intention toward these products. This paper attempts to integrate the theory of planned behavior and the Hunt–Vitell theory of marketing ethics to explore the buying intention toward ethically produced food products in a developing economy.Design/methodology/approachData were collected through a questionnaire survey in Bangladesh. Structural equation modeling technique was used to test the research model.FindingsResearch findings showed that deontological evaluation and teleological evaluation have significantly positive effects on perceived behavioral control and subjective norm. Perceived behavioral control, subjective norm, attitude, hedonic and utilitarian value have significantly positive effects on buying intention toward ethically produced foods.Originality/valueThe results are practically and theoretically meaningful because the integrated model holds well explanatory power to predict consumers' intention toward buying ethical foods and thereby understand consumers' ethical decision-makings.

Machine Learning Approaches for Predicting Hypertension and Its Associated Factors Using Population-Level Data From Three South Asian Countries

BackgroundHypertension is the most common modifiable risk factor for cardiovascular diseases in South Asia. Machine learning (ML) models have been shown to outperform clinical risk predictions compared to statistical methods, but studies using ML to predict hypertension at the population level are lacking. This study used ML approaches in a dataset of three South Asian countries to predict hypertension and its associated factors and compared the model's performances.MethodsWe conducted a retrospective study using ML analyses to detect hypertension using population-based surveys. We created a single dataset by harmonizing individual-level data from the most recent nationally representative Demographic and Health Survey in Bangladesh, Nepal, and India. The variables included blood pressure (BP), sociodemographic and economic factors, height, weight, hemoglobin, and random blood glucose. Hypertension was defined based on JNC-7 criteria. We applied six common ML-based classifiers: decision tree (DT), random forest (RF), gradient boosting machine (GBM), extreme gradient boosting (XGBoost), logistic regression (LR), and linear discriminant analysis (LDA) to predict hypertension and its risk factors.ResultsOf the 8,18,603 participants, 82,748 (10.11%) had hypertension. ML models showed that significant factors for hypertension were age and BMI. Ever measured BP, education, taking medicine to lower BP, and doctor's perception of high BP was also significant but comparatively lower than age and BMI. XGBoost, GBM, LR, and LDA showed the highest accuracy score of 90%, RF and DT achieved 89 and 83%, respectively, to predict hypertension. DT achieved the precision value of 91%, and the rest performed with 90%. XGBoost, GBM, LR, and LDA achieved a recall value of 100%, RF scored 99%, and DT scored 90%. In F1-score, XGBoost, GBM, LR, and LDA scored 95%, while RF scored 94%, and DT scored 90%. All the algorithms performed with good and small log loss values <6%.ConclusionML models performed well to predict hypertension and its associated factors in South Asians. When employed on an open-source platform, these models are scalable to millions of people and might help individuals self-screen for hypertension at an early stage. Future studies incorporating biochemical markers are needed to improve the ML algorithms and evaluate them in real life.

Determinants of multimorbidity of infectious diseases among under-five children in Bangladesh: role of community context

BackgroundThe presence of more than one morbid condition among children has become a global public health concern. Studies carried out in Bangladesh have primarily focused on diarrhoea and acute respiratory tract infections independently without considering their co-occurrence effect. The present study examines the multimorbid conditions of infectious diseases in under-five Bangladeshi children. It explores multimorbidity determinants and the role of community context, which are often overlooked in previous literature.MethodsUtilizing the most recent Demographic and Health Survey of Bangladesh (2017–18), we used mixed-effects random-intercept Poisson regression models to understand the determinants of multimorbidity of infectious diseases in under-five Bangladeshi children considering the community-level characteristics.Results The present study found that 28% of the children experienced multimorbidity two weeks prior to the survey. Community-level variability across all the statistical models was statistically significant at the 5% level. On average, the incidence rate of multimorbidity was 1.34 times higher among children from high-risk communities than children from low-risk communities. Moreover, children residing in rural areas and other urban areas involved 1.29 [CI: 1.11, 1.51] and 1.28 [CI: 1.11, 1.47] times greater risk of multimorbidity respectively compared to children from city corporations. Additionally, the multimorbidity incidence was 1.16 times [CI: 1.03, 1.30] higher among children from high-altitude communities than children living in low-altitude communities.ConclusionThe significant effect of public handwashing places suggests community-based interventions among individuals to learn hygiene habits among themselves, thus, the severity of coexistence nature of infectious diseases. A higher incidence of coexistence of such infectious diseases in the poor and semi-urban populace further recommends a targeted awareness of a clean environment and primary healthcare programmes.

Households’ Socioeconomic Vulnerability Assessment Due to COVID-19 Outbreak: A Web-Based Survey in Bangladesh

Aim: COVID-19, which can be considered a disastrous event, has created not only a public health emergency but also a major socio-economic crisis in Bangladesh. This study, therefore, aimed to assess households’ socioeconomic vulnerability due to the COVID-19 outbreak in the country. Methods: A quantitative cross-sectional survey was performed among 404 households from different districts in Bangladesh. The socioeconomic vulnerability index (SeVI) was developed using data collected from participants via an online-based self-reported questionnaire that included demographic, social, economic, and physical characteristics as well as exposure to COVID-19. Results: The socioeconomic vulnerability index (SeVI) was calculated as an index score of 0.405 where social, economic, and COVID-19 exposure were reported to be the more impactful components of adaptive capacity, sensitivity, and exposure, respectively. Furthermore, the economic options for households were greatly limited by the consequences of the COVID-19 pandemic. Practical implications: This study may help to identify the socioeconomic issues that resulted from the COVID-19 outbreak in the country and instruct the policymakers and corresponding authorities on which areas to emphasize for policy implementation so that households become socially and economically less susceptible to the COVID-19 outbreak as well as related infectious diseases and disastrous events in the upcoming years. Conclusion: This study found socioeconomic vulnerability among Bangladeshi households. The corresponding authorities should adopt policy initiatives to minimize the socioeconomic vulnerability due to the COVID-19 outbreak in the country.

Prevalence and Demographic, Socioeconomic, and Behavioral Risk Factors of Self-Reported Symptoms of Sexually Transmitted Infections (STIs) among Ever-Married Women: Evidence from Nationally Representative Surveys in Bangladesh.

Sexually transmitted infections (STI) symptoms (e.g., abnormal genital discharge and genital sores/ulcers) are a major public health concern in Bangladesh because the symptoms can indicate an STI and cause sexual and reproductive health complications in women of reproductive age. To our knowledge, no study examined the prevalence and risk factors of STI symptoms using a nationally representative sample. This study investigates the prevalence of STI symptoms among ever-married women in Bangladesh and the associations of STI symptoms with various demographic, socioeconomic, and behavioral risk factors using the most recent available data (2007, 2011, and 2014) of the Bangladesh Demographic and Health Surveys (BDHS). The BDHS employs a two-stage stratified sampling technique. The analytic sample comprised 41,777 women of reproductive age (15–49 years). Outcome variables included STI symptoms: abnormal genital discharge and genital sores/ulcers. Multivariate logistic regression was employed to find the adjusted odds ratio with a 95% confidence interval to assess the associations of outcome measures with explanatory variables. The study found that the prevalence of abnormal genital discharge and genital sores/ulcers among ever-married women aged 15–49 years was 10% and 6%, respectively. Multivariable analysis revealed that for women aged 25–34 years, those who used contraceptives and married earlier had an increased likelihood of STI symptoms. Furthermore, women from the wealthiest wealth quintile and couple’s joint decision-making were less likely to have STI symptoms. Findings have implications for interventions efforts aiming to improve women’s sexual and reproductive health in Bangladesh.

The Situation of Female Overseas Migrant Workers: Data Analysis Based on the Household Survey in Bangladesh

The Situation of Female Overseas Migrant Workers: Data Analysis Based on the Household Survey in Bangladesh

Demographic and Regional Differences in Household Dietary Diversity in Bangladesh: Evidence from the 2010 Household Income and Expenditure Survey

The dietary diversity score is now being widely accepted as a tool to see the dietary intake pattern qualitatively. This tool can be used for a rapid proxy measure of household food access of the population. As the Household Income and Expenditure Survey of Bangladesh (HIES) are done routinely in many developing countries, this can be a good source of dietary data for the field of nutrition research. The study endeavoured to measure household dietary diversity scores (HDDs, 0-12) from a nationally representative population and frequency of food group consumption for the Bangladeshi population at different spatial levels from the HIES, 2010 dataset. The study found HDDs (Mean±SD) of 6.16±1.91 for Bangladeshi households. Households from Small Municipality Area(SMA) showed the highest HDDs of 6.95±2.34 followed by municipality (6.61±2.04) and rural areas (5.87±1.72).Chittagong and Sylhet division’s households’ diet is more diversified (7.09±2.12 and 6.95±1.83, respectively),whereas the lowest HDDs are found in Rajshahi (5.71±1.68). Mean differences of HDDs significantly vary by the education level of the mother, family size, number of earners, and religious status of the household. Overall, the percentages of households with no intake of meat and poultry, fruits, and milk and milk products were43.1%, 28.2%, and 48.6%, respectively, in the survey period of 14 days. HDDs varies significantly by region and household characteristics. Animal-sourced foods (meat and poultry, milk and milk products, and eggs) and fruits should be made more accessible through policies and programs at the household level across divisions where consumption is low. Bangladesh J. Nutr. Vol. 34, December 2020, P: 87-98

How does autonomy of women influence maternal high-risk fertility? Evidence from a nationwide cross-sectional survey in Bangladesh

ABSTRACT This study provides evidence on the principal determinants of high-risk fertility – a level of fertility, which is measured through maternal age (less than 20 years and/or more than 34 years), a large number of children (more than 3), and short birth interval (less than 18 months) in Bangladesh. More specifically, this study explores the influences of women’s autonomy in decision-making, physical mobility and economic matters on high-risk fertility. Also, the socioeconomic attributes of women are used to explain this relationship. To identify the amount of variations in high-risk fertility at different geographic units across the country, a multilevel approach is applied considering individual, community and district levels by using a large nationwide dataset (BDHS 2017–2018). The findings of the present study indicate women’s autonomy in decision-making have strong significant effects on high-risk fertility; however, freedom of movement and economic autonomy do not have any significant effects. Furthermore, women’s education, religion and place of residence are found to be strong determinants of high-risk fertility, which also partially mediate the relationship between high-risk fertility and decision-making autonomy. High-risk fertility also varies at district level across Bangladesh.

Consumers’ willingness to pay for GLOBALG.A.P. certified chicken: Empirical evidence from a consumer survey in Bangladesh

Concern regarding chicken meat safety and quality has increased in recent years due to frequent exposure of food-safety-related incidents in Bangladesh. In order to boost consumer confidence, the government of Bangladesh has taken a number of policy measures to improve the safety and quality of fresh foods. Among them, the introduction of fresh food certification is regarded as a critical tool for mitigating threats to food safety. However, little is known about whether Bangladeshi consumers are willing to pay a price premium for certified fresh foods, or what factors influence their willingness to pay (WTP). We particularly investigated consumers' WTP for two types of GLOBALG.A.P. (good agricultural practices) certified chicken (broiler and Sonali chicken) by using contingent valuation method (CVM). A survey was conducted on 384 consumers of Dhaka. Payment card method was employed to elicit WTP. Our findings reveal that consumers are willing to pay a premium of 45.87 BDT/kg (36.69%) for GLOBALG.A.P. certified live broiler and 51.98 BDT/kg (25.99%) for GLOBALG.A.P. certified live Sonali chicken. Interval data regression model was used. The result shows that consumers’ age, education, monthly family income, chicken consumption per month and meat safety risk perception had a significant impact on their WTP for both types of chicken while taste was a significant factor only for broiler chicken. Nevertheless, gender, marital status and shopping responsibility had no significant impact on WTP. The findings on WTP for GLOBALG.A.P. certified chicken confirm that the government should introduce certification to meet increasing consumer demand for safe meat.

Investigating Poor Sleep Quality and Associated Factors During the COVID-19 Pandemic: A Population-Based Survey in Bangladesh.

Background: The coronavirus disease 2019 (COVID-19) pandemic has adversely affected the sleep quality of individuals, and is a poorly investigated area. This study aimed to investigate the prevalence estimate of poor sleep quality and its associated factors among Bangladeshi residents during the COVID-19 pandemic.Methods: An online cross-sectional survey was carried out from July 20 to August 5, 2020, involving 975 Bangladeshi residents (male: 54.2%; mean age: 26.7 ± 9.4 years; age range: 18–75 years). A self-reported questionnaire was answered by the respondents, covering information on demographic characteristics, perceived physical health status, COVID-19-related factors, COVID-19-induced anxiety assessment, and sleep quality. To assess sleep quality, the Bangla version of the Pittsburgh Sleep Quality Index was used. Logistic regression models were performed to analyze the factors associated with sleep quality.Results: The prevalence estimate of poor sleep quality was 55.1% among the Bangladeshi people during the COVID-19 pandemic. As per the multiple regression analysis, poor sleep quality was significantly higher among respondents who reported female gender, moderate/poor health status, indirect contact with COVID-19 infected patients, decreased household income due to the COVID-19 pandemic, fear of infection, and COVID-19-induced anxiety.Conclusion: Poor sleep quality was slightly prevalent among general people in Bangladesh during the COVID-19 pandemic. The findings indicate an immediate response for this vulnerable group to improve the sleep quality during the public health emergency of COVID-19.

Perceived e-learning stress as an independent predictor of e-learning readiness: Results from a nationwide survey in Bangladesh.

BackgroundE-learning is a relatively trending system of education that has been placed over conventional campus-based learning worldwide, especially since the emergence of the COVID-19 pandemic. This study aimed to assess e-learning readiness among university students of a developing country like Bangladesh and identify the independent predictors of e-learning readiness.MethodsFrom 26 December 2020 to 11 January 2021, a total of 1162 university students who had enrolled for e-learning completed a semi-structured questionnaire. Data were collected online via “Google Form” following the principles of snowball sampling through available social media platforms in Bangladesh. A multivariable linear regression model was fitted to investigate the association of e-learning readiness with perceived e-learning stress and other independent predictor variables.ResultsA total of 1162 university students participated in this study. The results indicated that with the increase of students’ perceived e-learning stress score, the average e-learning readiness score was significantly decreased (β = -0.43, 95% CI: -0.66, -0.20). The students did not seem ready, and none of the e-learning readiness scale items reached the highest mean score (5.0). The age, gender, divisional residence, preference of students and their parents, devices used, and having any eye problems were significantly associated with the students’ e-learning readiness.ConclusionDuring the prolonged period of the COVID-19 pandemic, e-learning implication strategies are needed to be assessed systematically with the level of readiness and its’ impacts among students for the continuation of sound e-learning systems. The study findings recommend evaluating the e-learning readiness of university students and the mental health outcomes during the COVID-19 catastrophe in Bangladesh.

Knowledge, attitudes and perceptions towards COVID-19 vaccinations: a cross-sectional community survey in Bangladesh

BackgroundSeveral vaccines have been approved for use against coronavirus disease (COVID-19) and distributed globally in different regions. However, general community knowledge, attitudes and perceptions towards COVID-19 vaccinations are poorly understood. Thus, the study aimed to investigate community knowledge, attitudes and perceptions towards COVID-19 vaccinations in Bangladesh.MethodsAn exploratory and anonymous population-based e-survey was conducted among 1658 general individuals (55.6% male; mean age = 23.17 ± 6.05 years; age range = 18–65 years). The survey was conducted using a semi-structured and self-reported questionnaire containing informed consent along with four sections (i.e., socio-demographics, knowledge, attitudes, and perceptions). Multiple linear regression was performed to determine the variables predicting knowledge, and attitudes towards COVID-19 vaccinations.ResultsThe mean scores of knowledge and attitudes were 2.83 ± 1.48 (out of 5) and 9.34 ± 2.39 (out of 12) respectively. About a quarter of participants thought that the COVID-19 vaccination available in Bangladesh is safe, only 60% will have the vaccination and about two-thirds will recommend it to family and friends. In the multiple regression model, higher SES, having university/ higher levels of education, having nuclear families and having previous history of essential vaccines uptake were associated with knowledge; whilst attitudes were significantly associated with being female and having previous history of essential vaccines uptake. Just over half of the participants thought that everyone should be vaccinated and 61% responded that health workers should be vaccinated first on priority basis. 95% of respondents believed the vaccine should be administered free of charge in Bangladesh and almost 90% believed that the COVID-19 vaccine used in Bangladesh may have side effects.ConclusionsThe findings reflect inadequate knowledge but more positive attitudes towards COVID-19 vaccine among the general population in Bangladesh. In order to improve knowledge, immediate health education programs need to be initiated before mass vaccination are scheduled.

Health-Related Quality of Life among Rural-Urban Migrants Living in Dhaka Slums: A Cross-Sectional Survey in Bangladesh.

Background: The study aimed to assess the health-related quality of life (HRQoL) and its associated factors among urban slum dwellers who migrated from different rural parts of Bangladesh. Methods: The present study analyzed data from a Migration and Mobility Determinants on Health survey and was conducted in 2017 among 935 migrant slum dwellers of Dhaka city (North & South) and Gazipur City Corporations, as a part of the icddr,b’s Urban Health and Demographic Surveillance System (UHDSS). The face-to-face interviews were conducted with the adult population by using a semi-structured questionnaire that included variables related to socio-demographics, migration, occupation, and HRQoL (SF-12). Bivariate and multiple linear regression analyses were performed to determine the factors associated with HRQoL. Results: The mean (±SD) scores of physical component summary (PCS), and mental component summary (MCS) were 57.40 ± 22.73 and 60.77 ± 22.51, respectively. As per multiple regression analysis, lower PCS scores were associated with having older age, being female, and not having any job. Mean MCS scores were significantly lower among participants who reported having older age, not having any job, not working/ less working hours (≤8 h/day), as well as increased work-related stress in the current urban slum. Conclusions: The findings suggest that available urban social protection programs should include a comprehensive social safety net for the improvement of the slum infrastructure as well as proper health care and risk mitigation plans at workplaces.

Depression and anxiety among individuals with medical conditions during the COVID-19 pandemic: Findings from a nationwide survey in Bangladesh

BackgroundCoronavirus disease 2019 (COVID-19) disproportionately impacts individuals with medical conditions, including with respect to their mental health. The present study investigated depression and anxiety and their correlates among individuals with medical conditions in Bangladesh. MethodsSubjects were recruited to participate in an internet-based survey. Data were collected from November 2020 to January 2021 using convenience sampling by a semi-structured questionnaire through online platforms. Multiple regression analyses were performed to determine associations applying Bonferroni correction (p < 0.004). The Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) measured depression and anxiety, respectively. ResultsNine-hundred-and-seventy-one participants (50.1% male; mean age = 42.29 ± 15.86 years; age range = 18-80 years) with medical conditions were included in final analyses. The most frequently reported conditions were diabetes, hypertension, obesity, heart disease, asthma, and anemia. Estimates of moderate to severe depression and anxiety were 38.9% and 35.2%, respectively. The mean depression and anxiety scores were significantly higher among participants who reported having hypertension, obesity, heart disease, asthma, anemia, cancer and chronic obstructive pulmonary disease (COPD). Using Bonferroni correction (p < 0.004), depression was associated with being female and a student, having poorer quality of life, poorer health status and greater numbers of co-morbidities, not engaging in physical exercise and tobacco smoking. Anxiety was associated with being female and a student, having lower socioeconomic status, poorer quality of life, poorer health status and greater numbers of co-morbidities, less sleep and tobacco smoking. ConclusionsDepression and anxiety are prevalent among individuals with medical conditions and correlate with sociodemographic, quality-of-life and smoking measures. Interventions targeting vulnerable groups should be employed and investigated.

Understanding the determinants of COVID-19 vaccination intention and willingness to pay: findings from a population-based survey in Bangladesh

BackgroundSeveral coronavirus disease (COVID-19) vaccines have already been authorized and distributed in different countries all over the world, including Bangladesh. Understanding public acceptance of such a novel vaccine is vital, but little is known about the topic.ObjectivesThis study aimed to investigate the determinants of intention to receive a COVID-19 vaccine and willingness to pay (WTP) among people in Bangladesh.MethodsAn anonymous and online-based survey of Bangladeshi people (mean age = 29.96 ± 9.15 years; age range = 18–60 years) was conducted using a self-reported questionnaire consisting of socio-demographics, COVID-19 experience, and vaccination-related information as well as the health belief model (HBM). Multivariable logistic regression was performed to determine the factors influencing COVID-19 vaccination intent and WTP.ResultsOf the 894 participants, 38.5% reported a definite intention to receive a COVID-19 vaccine, whereas 27% had a probable intention, and among this intent group, 42.8% wanted to get vaccinated as soon as possible. Older age, feeling optimistic about the effectiveness of COVID-19 vaccination, believing that vaccination decreases worries and risk of COVID-19 infection, and being less concerned about side effects and safety of COVID-19 vaccination under the HBM construct were found to be significant factors in COVID-19 vaccination intention. Most of the participants (72.9%) were willing to pay for a COVID-19 vaccine, with a median (interquartile range [IQR]) amount of BDT 400/US$ 4.72 (IQR; BDT 200–600/US$ 2.36–7.07) per dose. Factors associated with higher WTP were younger age, being male, having higher education, residing in an urban area, having good self-rated health status, positivity towards COVID-19 vaccination's effectiveness, and being worried about the likelihood of getting infected with COVID-19. Participants who were COVID-19 vaccination intent preferred an imported vaccine over a domestically-made vaccine (22.9% vs. 14.8%), while 28.2% preferred a routine immunization schedule.ConclusionThe findings indicate a considerable proportion of Bangladeshi people intended to get vaccinated and had WTP for the COVID-19 vaccine. However, urgent education and awareness programs are warranted to alleviate public skepticism regarding the COVID-19 vaccination.