An Empirical Analysis of the Factors Associated with Mushroom Cultivation: A Case of Dhaka

The analysis aimed to identify mushroom production and marketing problems by different stakeholders in Bangladesh, specifically in the Dhaka district. It also seeks to improve the mushroom marketing system for domestic markets. The research was carried out in the Savar Upazila, located in the Dhaka district. One hundred twenty-one farmers were randomly picked and asked questions using an interview schedule to collect data. Pearson's chi-squared test was utilized to investigate the degree to which socio-demographic factors and the response variable are related. In the end, a multivariate method known as logistic regression analysis is used to study the relationships between each predictor variable and the result variable that pertains to the respondents. The result revealed significant effects of gender, farmer's education, and information sources for intermediate and experienced mushroom cultivators. However, land size, scientific cultivation, sources of capital, packaging, and sale were stronger among expert mushroom farmers than the new and mediocre mushroom farmers. This research provides valuable insights to improve the mushroom marketing system for domestic markets

Individual-level preventive measures during the first wave of COVID-19 pandemic among Bangladeshi residents

COVID-19 causes mild to severe respiratory illness in humans. Government and non-government authorities along with telecommunication, print and electronic media undertook extensive advertising campaign regarding protective measures against COVID-19 to raise the public awareness. Therefore, this web-based cross-sectional study was conducted to evaluate peoples' responses towards COVID-19 during the first wave of COVID-19 in Bangladesh. We performed univariate and multivariate analyses to estimate the association between demographic characteristics, awareness, and individual preventive measures. The overall awareness level of the majority of the respondents (89%, n=920) was good, but the overall score for individual-level preventive measures during lockdown was poor to moderate. The relation between a good level of awareness and a higher level of educational status was found statistically significant (aOR 5.87, 95% CI: 1.58-21.86). Service holders were two times more likely to follow COVID-19 prevention practices than students (aOR 2.08, 95% CI: 1.24-3.51). Despite having adequate knowledge on awareness, many respondents were reluctant to follow preventive measures during the lockdown. The outcomes of this study highlight the requirement for stringent execution of preventative measures by law enforcement agencies to stop the transmission of the COVID-19 virus

Gender differences in child nutrition status of Bangladesh: a multinomial modeling approach

Purpose – Malnutrition is one of the serious public health problems especially for children and pregnant women in developing countries such as Bangladesh. This study aims to identify the risk factors associated with child nutrition for both male and female children in Bangladesh. Design/methodology/approach – This study was conducted among 23,099 mothers or caretakers of children under five years of age from a nationally representative survey named Bangladesh Multiple Indicator Cluster Survey, 2019. This study used chi-square test statistic for bivariate analysis and multinomial logistic regression was used to evaluate the adjusted effects of those covariates on child nutritional status. Findings – The prevalence of severely malnourished, nourishment was higher for males than females (5.3% vs 5.1%, 77.4% vs 76.8%) while moderately malnourished were higher for females (18.1% vs 17.4%). The findings from the multinomial model insinuated that the mother’s education level, wealth index, region, early child development, mother’s functional difficulties, child disability, reading children's books and diarrhea had a highly significant effect on moderate and severe malnutrition for male children. For the female children model, factors such as mother’s education level, wealth index, fever, child disability, rural, diarrhea, early child development and reading less than three books were significant for moderate and severe malnutrition. Originality/value – There is a solution to any kind of problem and malnutrition is not an exceptional health problem. So, to overcome this problem, policymakers should take effective measures to improve maternal education level, wealth status, child health

Sociodemographic Factors on Contraceptive Use among Ever-Married Women of Reproductive Age: Evidence from Three Demographic and Health Surveys in Bangladesh

Contraceptive use among married women of reproductive age has showed a substantial progress over the last few decades in Bangladesh. This study explores the sociodemographic factors associated with contraceptive use among ever-married women of reproductive age in Bangladesh by utilizing the information extracted from three of the Bangladesh Demographic and Health Surveys (BDHSs) in 1993–1994, 2004 and 2014. Bivariate analysis was conducted by performing chi-squared test of independence to explore the relationship between selected sociodemographic factors and dependent variables. To know the adjusted effects of covariates, a popular binary logistic regression model was considered. Respondents’ current age, place residence, division religion, education, age at first marriage, family planning (FP) media exposure, ideal number of children and fertility preferences are the significant determinants according to the most recent survey, BDHS 2014. However, wealth index and a respondent’s current working status were found to be significant factors only in BDHS 2004. The results of the study strongly recommend efforts to increase the education level among poor people, particularly among women in Bangladesh. Program interventions, including health behavior education and family planning services and counselling, are especially needed for some categories of the population, including those living in rural areas, Sylhet, Chittagong and Dhaka divisions, as well as illiterate and Muslim ever-married women

Factors Associated with Cultivation of Tobacco in Bangladesh: A Multilevel Modelling Approach

An increasing number of studies provide evidence on the serious negative consequences of tobacco farming on economic livelihoods, human health and the environment. There is, however, only limited research on tobacco farming in Bangladesh, a significant producer of tobacco leaf. It is not yet well understood why many farmers choose to grow tobacco considering the challenging context. Accordingly, this study examines the factors that influence farmers’ decisions to grow tobacco in Bangladesh. Socio-demographic and economic information was collected from 220 tobacco farmers and 117 non-tobacco farmers from the major tobacco-growing district of Kushtia, for a total sample of 337. These farmers were recruited from two sub-districts (or upazilla—Daulatpur and Mirpur) using a stratified random sampling. A two-level logistic regression model was applied for the identification of the variables that condition farmers’ decisions to cultivate tobacco leaf. Almost two-thirds of the sampled farmers (65.3%) chose to farm tobacco. The results demonstrate that the following variables shape most farmers’ decisions to cultivate tobacco: older age, less education, tobacco firms’ short-term financial support of growing tobacco, greater ease of selling tobacco products at market, better access to credit (also provided by the tobacco companies), and farmer’s perception about higher profits from tobacco cultivation compared to other crops. This study strongly suggests that the government and others working on tobacco control should consider engaging in initiatives to increase farmers’ education, perhaps particularly for older farmers, and provide meaningful financial support in part by helping to increase access to credit and ensuring a better market facility to sell their other healthier agricultural crops, goods and services

Machine Learning Algorithm-Based Contraceptive Practice among Ever-Married Women in Bangladesh: A Hierarchical Machine Learning Classification Approach

Contraception enables women to exercise their human right to choose the number and spacing of their children. The present study identified the best model selection procedure and predicted contraceptive practice among women aged 15–49 years in the context of Bangladesh. The required information was collected through a well-known nationally representative secondary dataset, the Bangladesh Demographic and Health Survey (BDHS), 2014. To identify the best model, we applied a hierarchical logistic regression classifier in the machine learning process. Seven well-known ML algorithms, such as logistic regression (LR), random forest (RF), naïve Bayes (NB), least absolute shrinkage and selection operation (LASSO), classification trees (CT), AdaBoost, and neural network (NN) were applied to predict contraceptive practice. The validity computation findings showed that the highest accuracy of 79.34% was achieved by the NN method. According to the values obtained from the ROC, NN (AUC = 86.90%) is considered the best method for this study. Moreover, NN (Cohen’s kappa statistic = 0.5626) shows the most extreme discriminative ability. From our research, we suggest using the artificial neural network technique to predict contraceptive use among Bangladeshi women. Our results can help researchers when trying to predict contraceptive practice

Inequalities in adequate maternal healthcare opportunities: evidence from Bangladesh Demographic and Health Survey 2017–2018

Objectives This study investigated the inequalities in access to maternal healthcare services in Bangladesh.Design and setting This study used cross-sectional data from the nationally representative Bangladesh Demographic and Health Survey conducted in 2017–2018. The survey encompassed diverse regions and households across Bangladesh. The study used the Human Opportunity Index (HOI) and Shapley’s decomposition technique to measure the inequality in access to maternal healthcare opportunities.Participants This study included 20 127 women aged 15–49 years. Among them, 5012 women had live births in the preceding 3 years of the survey, forming the study sample.Primary and secondary outcome measures This study has no secondary outcome variable. The primary dependent variable is ‘adequate maternal healthcare’, a dichotomous variable.Results Household wealth status contributed the highest to inequality in accessing adequate maternal healthcare services (41.4%) such as receiving at least four antenatal care (ANC) visits (39.7%), access to proper ANC (50.7% and 44.0%) and health facility birth (43.4%). Maternal educational status contributes the second highest inequality among all factors in accessing adequate maternal healthcare (29.5%). Adequate maternal healthcare presented the lowest coverage rate and opportunity index among all (approximately 24% with HOI=17.2).Conclusions We found that attained adequate maternal healthcare had the lowest coverage and widest dissimilarity, while wealth index, education and place of residence are the major factors that contribute to inequalities in accessibility to maternal healthcare services in Bangladesh. These findings underscore a need for pro-poor interventions to narrow the economic inequalities between the poor and rich in terms of accessibility to maternal healthcare services. The results indicate the need for the Bangladeshi government and its health department to strengthen their commitment to improving female education. Investments should be made in initiatives that facilitate the proximity of maternal healthcare services to women in rural areas