Controlling population expansion and reducing unintended pregnancies through the use of modern contraceptives is a cost-effective strategy. In recent years, the rate of modern contraceptive use in ...Bangladesh has been declining. So, this study aimed to investigate the associated factors of the deterioration in modern contraceptive usage.
This study used data from two successive Bangladesh Demographic and Health Surveys (2014 and 2017-18) and applied the Blinder-Oaxaca decomposition analysis to understand the drivers. A popular binary logistic regression model is fitted to determine the factors that influence the use of modern contraceptive methods over the years.
This study revealed that highly educated women were more likely to use modern contraception methods, and their use increased by 3 percent over the years. Factors such as women's working status, husband's education, number of living children, and fertility preference were found significantly associated with decreased usage of modern contraception methods over years. The result of the Blinder-Oaxaca (BO) decomposition analysis found a significant decrease between 2014 and 2018. Respondent's age, working status, husband's age, opinion on decision making, region, and media exposure were the most significant contributors to explaining the shift between 2014 and 2018. The two factors that contributed most to narrowing the difference between the two surveys were women's decision on own health (26%), and employment status (35%).
The factors that influence modern contraceptive prevalence are important to know for policy implication purposes in Bangladesh. The findings indicate the need for further improvement of factors for balancing the usage of modern contraception methods.
Research on children's dietary diversity plays a crucial role in designing effective health interventions. Thus, this study aimed to identify the factors contributing to minimum dietary diversity ...failure (MDDF) among male and female children aged 6–23 months in Bangladesh. The data for this study was obtained from the Bangladesh Multiple Indicator Cluster Survey, 2019, which included children currently breastfed within a specific age range. Multivariable binary logistic regression was employed to assess the strength and significance of the association. The findings revealed that approximately 59⋅4 % of children in Bangladesh experienced MDDF, with 57⋅8 % of male children and 61 % of female children affected. Proportion test uncovered a significant gender disparity (χ2=6⋅58, P-value = 0⋅01) among children aged 6–23 months. However, the multivariable binary logistic regression analysis revealed that both male and female children shared common risk factors for MDDF, which included child age, maternal educational status, wealth status, number of antenatal care visits, and division. In our study, we observed varied spatial patterns in minimal dietary diversity. Sherpur, Netrokona, Sunamganj, and Sylhet districts showed the highest failure rates. Notably, all are flood-affected areas, impacting food availability and diversity. For targeted regional development programmes, district mapping results may offer valuable insights to policymakers, especially in areas with a high prevalence of dietary diversity failure. By understanding these risk factors, policymakers and stakeholders can implement targeted strategies to improve dietary diversity among children, promoting better health and well-being for the young population in Bangladesh.
Early marriage is a form of violation of child rights to grow and develop. The Sustainable Development Goals had included early marriage in target 5.3, aiming to eliminate by 2030. This study ...examines the socio-demographic factors associated with women's early marriage in Bangladesh, Ghana, and Iraq using information extracted from 2019, 2017–2018, and 2018 Multiple Indicator Cluster Surveys (MICSs) of Bangladesh, Ghana, and Iraq, respectively. The chi-square test examined the association between socio-demographic factors and early marriage separately in all three countries. In logistic regression, key factors were primarily evaluated for determining effects on early marriage separately in all three countries. The mean age of the mother at first marriage was found to be 16.86, 20.23, and 20.05 years in Bangladesh, Ghana, and Iraq successively. According to surveys conducted in Bangladesh, Ghana, and Iraq, education levels of household heads and women, wealth status, mass media, number of household members, and residence were significant factors linked to early marriage. The odds of getting married early were significantly higher among women with no formal education and primary education than women with secondary or higher education in all three countries. In terms of economic status, a negative association was found between wealth status and early marriage in both Bangladesh and Ghana. Based on the findings, the study recommended that government take the necessary steps to reduce child marriage in all three countries by raising women's education and campaigning women by media to harmful effects of early marriage, particularly women from low-income families.
Early marriage, Low weight, Nutritional, Mortality, Unintended pregnancies.
Introduction: Handwashing practice is an effective way to minimize severe infectious diseases such as COVID-19, diarrhea, and pneumonia. The study aimed to explore the prevalence of handwashing ...behavior and associated determinants in rural and urban areas of Bangladesh. Methods: The research was performed using cross-sectional survey data from the 2019 Bangladesh Multiple Indicator Cluster Survey, and 61,242 household members were the sample for this study. The Chi-square test was applied for the bivariate analysis. A generalized linear mixed-effects model was used to identify the risk factors of practicing handwashing in both urban and rural areas of Bangladesh. Results: Only 65% of the country's households had access to handwashing facilities (place, water, and materials). While urban dwellers were more likely to wash their hands, rural dwellers were only 63% likely to do so. The level of education of household heads, wealth status, division, number of family members, sanitation facilities, and water source were the key factors associated with handwashing behavior. This study revealed that the odds were significantly lower among illiterate respondents compared to those with secondary and above-secondary education in both areas of Bangladesh, and a positive association was found between wealth status and handwashing behavior practiced in both urban and rural areas. In this study, the size of the family was statistically significant for both rural and urban areas of Bangladesh. Conclusion: Handwashing is the most prominent consideration for controlling COVID-19. Policymakers are striving to improve handwashing facilities by increasing awareness-raising programs, especially among rural residents of Bangladesh.
With the proliferation of mobile devices and wireless technologies, location based services (LBSs) are becoming popular in smart cities. Two important classes of LBSs are Nearest Neighbor (NN) ...queries and range queries that provide user information about the locations of point of interests (POIs) such as hospitals or restaurants. Answers of these queries are more reliable and satisfiable if they come from trustworthy crowd instead of traditional location service providers (LSPs). We introduce an approach to evaluate NN and range queries with crowdsourced data and computation that eliminates the role of an LSP. In our crowdsourced approach, a user evaluates LBSs in a group. It may happen that group members do not have knowledge of all POIs in a certain area. We present efficient algorithms to evaluate queries with accuracy guarantee in incomplete databases. Experiments show that our approach is scalable and incurs less computational overhead.
Information visualization uses various types of representations to encode data into graphical formats. Prior work on visualization techniques has evaluated the accuracy of perceived numerical data ...values from visual data encodings such as graphical position, length, orientation, size, and color. Our work aims to extend the research of graphical perception to the use of motion as data encodings for quantitative values. We present two experiments implementing multiple fundamental aspects of motion such as type, speed, and synchronicity that can be used for numerical value encoding as well as comparing motion to static visual encodings in terms of user perception and accuracy. We studied how well users can assess the differences between several types of motion and static visual encodings and present an updated ranking of accuracy for quantitative judgments. Our results indicate that non-synchronized motion can be interpreted more quickly and more accurately than synchronized motion. Moreover, our ranking of static and motion visual representations shows that motion, especially expansion and translational types, has great potential as a data encoding technique for quantitative value. Finally, we discuss the implications for the use of animation and motion for numerical representations in data visualization.
Background. Most maternal deaths occur during childbirth and after childbirth. This study was aimed at determining the trends of health facilities during delivery in Bangladesh, as well as their ...influencing factors. Methods. This study used secondary data from three Bangladesh Multiple Indicator Cluster Surveys (MICSs) in 2006, 2012–13, and 2019. The study’s target sample was those women who gave birth in the last two years of the survey. A two-level logistic regression was applied to determine the effects on health facility delivery separately in these two survey points (MICSs 2012–13 and 2019). Results. The results show that the delivery of health facilities has increased by almost 37.4% in Bangladesh, from 16% in 2006 to 53.4% in 2019. The results of two-level logistic regression show that the total variation in health facility delivery across the community has decreased over recent years. After adding community variables, various individual-level factors such as women with secondary education (OR=0.55 in 2012-13 vs. OR =0.60 in 2019), women from middle wealth status (OR=0.49 in 2012-13 vs. OR=0.65 in 2019), religion, and child ever born showed a strong relationship with health facility delivery in both survey years. At the community level, residents showed significant association only in the 2012-13 survey and indicated a 43% (OR=1.43 for 2012-13) greater availability of health facilities in urban residences than in rural residences. Using media showed a highly significant connection with health facility delivery in both years as well as an increasing trend over the years in Bangladesh (OR=1.19 in 2012-13 vs. OR=1.38 in 2019). However, division, prenatal care, and skilled services all contribute greatly to increasing the delivery of health facilities in Bangladesh. Conclusions. The results of this study suggest that policymakers need to pay attention to individual and community-level factors, especially women’s education, poverty reduction, and adequate prenatal care provided by well-trained caregivers.
The advancement of internet technology and growing involvement in the cyber world have made us prone to cyber-attacks inducing severe damage to individuals and organizations, including financial ...loss, identity theft, and reputational damage. The rapid emergence and evolution of new networks and new opportunities for businesses and technologies are increasing threats to security vulnerabilities. Hence cyber-crime analysis is one of the wide range applications of Data Mining that can be eventually used to predict and detect crime. However, there are several constraints while analyzing cyber-attacks, which are yet to be resolved for more accurate cyber security inspection.Although there are many strategies for intrusion detection, predicting upcoming cyber threats remains an open research challenge. Hence, this thesis seeks to utilize temporal correlations among attack frequencies within specific time periods to predict the future severity of cyber incidents. The research aims to address the current research limitations by introducing a real-time data collection framework that will provide up-to-date cyber-attack data. Furthermore, a platform for cyber-attack trend analysis has been developed using Power BI to provide insight into the current cyber-attack trend. A correlation was identified in the reported attack volume across consecutive time frames through collected attack data analysis. This thesis introduces a predictive model that forecasts the frequency of cyber-attacks within a specified time window, using solely a historical record of attack counts. The research includes various machine learning and deep learning methods to develop a prediction system based on multiple time frames with an over 15% improvement in accuracy compared to the conventional baseline model. Namely, our research demonstrates that cyber incidents are not entirely random, and by analyzing patterns and trends in past incidents, developed AI techniques can be used to improve cybersecurity measures and prevent future attacks.
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