Survival analysis of early intention of antenatal care among women in Bangladesh.

This study focuses on the importance of early and regular Antenatal Care (ANC) visits in reducing maternal and child mortality rates in Bangladesh, a country where such health indicators are a concern. The research utilized data from the Bangladesh Demographic and Health Survey (BDHS) conducted in 2017-18 and employed the Cox proportional hazard model to identify factors influencing women's intention of ANC services. The results revealed that 40.4% of women engaged in at least one ANC activity during the first trimester, which, although higher than in other countries, falls below the global average. Notably, women between the aged of 25 and 29 years took 15% less time for their first ANC visit compared to their younger counterparts, suggesting higher awareness and preparedness in this age group. Education, both for women and their partners, had a significant influence on the intention to visit ANC early. Women in the poor wealth quantile exhibited lower odds of seeking timely ANC, whereas those with a planned pregnancy were more likely to do so. Moreover, access to mass media decreased the timing of ANC visits by 26% compared to women who were not exposed. Moreover, living in rural areas was linked to a 17% delay in the timing of the first ANC visit compared to urban areas. These findings underscore the importance of addressing these determinants to improve the timeliness and accessibility of ANC services, thereby enhancing maternal and child health outcomes in Bangladesh.

Individual- and community-level factors associated with the presence of adequate iodized salt in households in Bangladesh: a multilevel modelling approach.

BACKGROUND: The aim of this study is to estimate the factors at both the individual and community levels related to the adequacy of iodized salt in households in Bangladesh. METHODS: For this study we utilized the 2019 Multiple Indicator Cluster Survey data. A total of 61 242 households were chosen as samples from Bangladesh. In our study of socio-economic disparities, we applied a concentration indexing method. To identify the factors associated with the adequacy of iodine in salt at both the individual and community levels, we employed multilevel logistic regression. Aside from the multilevel regression used in the study, we also applied spatial analysis. RESULTS: The results indicated that the prevalence of iodine adequacy in household salt was found to be 57.8% (95% confidence interval 57.4 to 58.2). Rural areas have a higher concentration of iodine than urban areas. According to the multilevel model, younger women (adjusted odds ratio [aOR] 0.70), Muslim women (aOR 0.89), illiterate women (aOR 0.80) and those from poor households (aOR 0.33) were found to be less likely to consume iodine in concentrated salt compared with their counterparts. Disabled women and those with low media exposure have a lower likelihood of iodine adequacy in salt compared to their reference group. Furthermore, households in urban areas exhibited higher odds of having iodine adequacy in salt compared with households in rural areas. Barisal, Chattogram, Dhaka, Khulna, Mymensingh, Rajshahi and Rangpur Divisions have lower iodine adequacy in salt compared with Sylhet Division. CONCLUSIONS: The findings reveal that religion, physical disability and exposure to media exert an equal influence on the presence of iodized salt intake. Moreover, women's age, wealth status, education level and the educational background of the household head positively contribute to the adequacy of iodine in household salt. In light of these results, policymakers are advised to prioritize efforts aimed at enhancing iodine concentration, with a particular focus on mass media advertising, especially in rural areas (excluding Sylhet Division).

Determinants of household adoption of clean energy with its rural-urban disparities in Bangladesh.

This study aims to investigate factors influencing the adoption of clean energy among households in Bangladesh, using Blinder-Oaxaca decomposition and extended probit regression model with data from the 2019 Bangladesh multiple indicator cluster survey. Small households, primarily Muslim and urban dwellers, who speak the Bengali language and are Internet and mobile users, were likelier to adopt cleaner fuels than their counterparts. On the contrary, households residing in the Barisal, Khulna, Rajshahi, and Rangpur divisions, belonging to poor and middle-class households, with household heads aged 15-64 and without formal education, were less likely to adopt cleaner fuels than their counterparts. The concentration curve revealed socioeconomic inequality in the adoption of clean energy, particularly favouring richer households in urban and rural areas. Further analysis using the Blinder-Oaxaca decomposition showed that urban residents showed a higher probability of adopting clean energy, with a significant difference of 0.508 compared to rural areas. Regarding the endowment effect, poor wealth quintile contributed the most, followed by the ownership of rented dwellings and the middle wealth quintile. The Bengali differential effect made the largest contribution to this aspect of the disparity, followed by the exposure of the Internet and the influence of the Dhaka and Chattogram divisions. The detailed analysis provides valuable insights for policymakers and practitioners on the issue of disparities in the adoption of clean energy between urban and rural areas in Bangladesh.

Rural-urban disparities in nutritional status among ever-married women in Bangladesh: A Blinder-Oaxaca decomposition approach.

This study aims to investigate socioeconomic disparities in nutritional status among ever-married women in Bangladesh and to break down urban-rural differences in the underlying causes of undernutrition. We utilized data from the Bangladesh Demographic and Health Survey 2017-18, a sample size of 18328 ever-married women, including 5170 from urban residences, and 13159 from rural residences. To explore socioeconomic inequality, we employed a concentration indexing measure, while a multiple binary logistic regression model was carried out to identify the determinants associated with the outcome variable. A Blinder-Oaxaca decomposition analysis was performed to decompose the urban-rural gap in women's nutritional status using associated factors. The prevalence of undernutrition among ever-married women in Bangladesh was 12 percent. Notably, this percentage varied by region, with urban residents accounting for 8.6% and rural residents accounting for 13.3%. Our findings confirmed that undernutrition was more prevalent among women with lower wealth indexes in Bangladesh, as indicated by the concentration index (CIX = -0.26). The multivariable analysis investigating the determinants of undernutrition status among ever-married women, with a focus on residence revealed significant associations with respondent age, education, marital status, mass media access, wealth status, and division. According to the Blinder-Oaxaca decomposition and its extension, the prevalence was significantly higher in rural residences of Bangladesh than in urban residences, and the endowment effect explained 86 percent of the total urban-rural difference in undernutrition prevalence. The results of this study indicate that the factors that influence women's nutritional status in rural areas play a significant role in the gap, and the majority of the gap is caused by education and economic position. In order to effectively promote maternal health policies in Bangladesh, intervention techniques should be created that are aimed at the population, that is, the poorest and least educated.

Application of a count regression model to identify the risk factors of under-five child morbidity in Bangladesh.

BACKGROUND: Bangladesh has seen a significant decline in child mortality in recent decades, but morbidity among children <5 y of age remains high. The aim of this analysis was to examine trends and identify risk factors related to child morbidity in Bangladesh. METHODS: This analysis is based on data from four successive cross-sectional Bangladesh Demographic and Health Surveys for the years 2007, 2011, 2014 and 2017-18. Several count regression models were fitted and the best model was used to identify risk factors associated with morbidity in children <5 y of age. RESULTS: According to the results of the trend analysis, the prevalence of non-symptomatic children increased and the prevalence of fever, diarrhoea and acute respiratory infections (ARIs) decreased over the years. The Vuong's non-nested test indicated that Poisson regression could be used as the best model. From the results of the Poisson regression model, child age, sex, underweight, wasted, stunting, maternal education, wealth status, religion and region were the important determinants associated with the risk of child morbidity. The risk was considerably higher among women with a primary education compared with women with a secondary or greater education in Bangladesh. CONCLUSIONS: This analysis concluded that child morbidity is still a major public health problem for Bangladesh. Thus it is important to take the necessary measures to reduce child morbidity (particularly fever, diarrhoea and ARI) by improving significant influencing factors.

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.

Individual and community-level factors associated with discrimination among women aged 15-49 years in Bangladesh: Evidence based on multiple indicator cluster survey.

BACKGROUND: This research aimed to examine the factors at both the individual and community levels that are linked to discrimination experienced by women aged 15-49 in Bangladesh. METHODS: The relevant data was taken from the 2019 Multiple Indicator Cluster Survey in Bangladesh. The risk factors for discrimination against women in Bangladesh were determined using multilevel logistic regression models. RESULTS: The overall prevalence of discrimination against women was found to be 10.4% (95% CI: 10.1-10.6). Based on the final model (Model 1V), at the individual level higher odds of discrimination were observed among women from poor (AOR:1.21,95%CI: 1.12-1.32) and middle income households (AOR:1.12, 95%CI:1.02-1.22) compared to those from rich households etc. Women who have never used ICT were 1.27 times (AOR = 1.27, 95% CI = 1.07-1.51) higher odds of discrimination when compared with women who were ICT exposed. Respondents who married before 18 years 10% more likely to (AOR = 1.10, 95% CI:1.02-1.19) discriminated than women married aged 18 years old or above. Women from urban communities were 15% less likely to experience discrimination than their rural counterparts. In comparison to the Sylhet Division, women in the Barisal, Chattogram, Dhaka, Khulna Mymensingh, Rajshahi, and Rangpur Divisions were respectively 3.02, 1.84, 1.68, 2.06, 4.97, 4.06, and 1.74 times more likely to experience discrimination. CONCLUSION: Findings revealed that various individual-level factors such as wealth index, CEB, ICT exposure, marital status, functional difficulty, age, women's happiness, magazine and radio exposure, age at marriage, current contraceptive use, polygamy, husband beating, place of attack, and household head age were found to have a significant association with women discrimination. Community-level factors such as residence and division were also found to have a notable impact on discrimination. Policymakers should incorporate substantial components targeting both individual and community levels into intervention programs with the goal of raising awareness about women's discrimination.

Pharmacological effect of Heritiera fomes on Long Evans rats against Postprandial Hyperglycemia and adsorption in vitro.

Background: Natural restoratives from traditional medicinal plants are considered to be a convenient, potent, and risk-free substitute treatment for hyperglycaemia. Our objective was to explore the activity of the crude extract of Heritiera fomes on postprandial hyperglycaemia by assessing relative measurements in a laboratory animal model. Methods: The Streptozotocin induced diabetic rat (n = 88, twenty-two per group) was used for the glucose tolerance test as an initial support for the study. BaSO4 was administered orally as a marker to measure gut motility after one hour of methanolic extract (500 mg/kg body weight) administration where, only purified water (10 ml/kg) was used to treat the control group (n = 12) and a dose (500 mg/kg) of H. fomes extract was used for the test group (n = 12 in each group). After 60 min of incubation of the mixture of extract and glucose with 10% (v/v) yeast cell suspension, the absorbance was measured to determine the capacity of glucose absorption by yeast cells. Sixty Long Evans rats (n = 12 in each group) were used to assess disaccharidase enzyme activity as µmol/mg protein per hour by Lowry's protein estimation method. The carbohydrate absorption investigation was executed to evaluate the leftover sucrose content in the gastrointestinal system (n = 64). Results: After oral administration of MHFL (71.84%), MHFB (71.41%), and MHFR (72.55%), GI motility (%) increased significantly (p < 0.001) compared to the control group (59.06%). A significant increase in glucose uptake and adsorption capacity measured by different concentrations of glucose ensures the decrease of glucose bound rate and a significant drop in blood glucose concentration. The significant (p < 0.001) decrease in intestinal disaccharidase activity of MHFL (1.40), MHFB (1.36), and MHFR (1.20) in comparison to the control group (1.50) indicates that the presence of H. fomes may reduce glucose absorption in the small bowel. Significant (p < 0.001 & p < 0.05) accumulation of sucrose content in the six different parts of the GI tract suggests the absorption of sucrose was decreased. Conclusions: The findings of this study provide evidence on probable mechanisms for the anti-diabetic characteristics of H. fomes, and it is predicted that this plant will be studied further for the development of strong anti-hyperglycemic medicines.

Knowledge, attitudes, and factors determining the willingness for COVID-19 vaccination among students in Bangladesh: An online-based cross-sectional study.

Aim: The most effective way to avoid COVID-19 is through immunization against the virus that causes the disease. The primary objective of this study was to assess the extent of knowledge, attitudes, acceptability, and factors influencing COVID-19 vaccination acceptance among higher secondary and university students in Bangladesh. Subject and methods: A structured questionnaire-based online survey was conducted among 451 students residing in Khulna and Gopalganj cities from February to August, 2022. The willingness to accept the COVID-19 vaccine was compared with a few covariates using the chi-square test, and we then used binary logistic regression to identify the determinants that led Bangladeshi students to receive the COVID-19 vaccine. Results: During the study period, almost 70% of the students obtained immunizations, with 56% of men and 44% of women reporting having done so. The age range of 26-30 years had the highest percentage of students who had received vaccinations, and 83.9% of students agreed that the COVID-19 vaccine is crucial for students. The results of the binary logistic regression clearly show that gender, degree of education, and respondents' willingness, encouragement, and beliefs have a significant impact on students' eagerness to receive COVID-19 vaccination. Conclusion: The rising trend in vaccination status among Bangladeshi students is highlighted by this study. Additionally, our results eloquently demonstrate that vaccination status varies by gender, education level, willingness, encouragement, and respondent's viewpoint. The outcomes of this study are essential for health policy makers and other interested parties to successfully organize their immunization program for young adults and children at various levels.

Dynamic changes in prevalence of type 2 diabetes along with associated factors in Bangladesh: Evidence from two national cross-sectional surveys (BDHS 2011 and BDHS 2017-18).

BACKGROUND AND AIMS: Prevalence of type 2 diabetes has been rising rapidly especially in low- and middle-income countries. The purpose of this study is to analyze the prevalence of type 2 diabetes in 2011 and 2017-18, and the risk factors based on the Bangladesh Demographic and Health Surveys (BDHS). METHODS: The study comprised of data from the BDHS 2011 and the BDHS 2017-18 with 7565 (50.6% female) and 12,299 respondents (56.9% female) respectively. The plasma blood glucose was classified into normal, pre-diabetes, and diabetes categories. While univariate analysis was performed to determine the data, Chi-square and gamma analyses were used for bivariate estimation of the correlation between diabetes status and other comorbidities. Multinomial and ordinal logistic regression were also performed to trace the link between diabetes and various risk factors. RESULTS: The 2011 BDHS survey indicated that nearly half of the participants (47.6%) had pre-diabetic condition, while 10.2% were diagnosed with diabetes. On the other hand, the BDHS 2017-18 demonstrated that 28.6% and 8.6% of participants had pre-diabetes and diabetes, respectively. Results of inferential statistics showed that gender (p<0.05), age, wealth status, physical activity, BMI (p<0.01), and caffeinated beverages (p<0.05), were significantly linked with diabetes status. CONCLUSION: According to our findings, older people and people with lower education are more likely to develop diabetes. BMI` Physically active, wealth status, diet and lifestyle were significant predictors of type 2 diabetes. Healthy lifestyle, physical activities, proper knowledge and awareness can reduce the risk of T2D.

Socioeconomic correlates of Adequate Maternal Care in Bangladesh: Analysis of the Bangladesh Demographic and Health Survey 2017-18.

Introduction: In recent times, Bangladesh has made significant improvements in various health outcomes, but not so much in maternal death. The current flat trend in reducing maternal mortality in Bangladesh has been mainly due to the lower coverage of maternal health care. To improve the coverage, it is essential to find biosocial factors related to adequate maternal health care. Therefore, this study is aimed at finding out the socioeconomic correlates of adequate maternal health care in Bangladesh. Methods: The study used data from the Bangladeshi demographic and health survey 2017-18. The total unweighted sample of 4012 women who reported pregnancy before three years of the survey was analyzed. A composite binary indicator of adequate maternal care has been constructed using the variables-access to maternal care service, four antenatal care visits, at least one visit with qualified providers, and institutional delivery. A binary logistic regression model was employed to find out the socioeconomic correlate of adequate maternal care. Results: Only 24.4% percent of sample women received adequate maternal care. The result of the logistic regression model shows that urban, Khulna, Rajshahi, and Rangpur were associated with an increase in the odds of having adequate maternal care. High education and health care decisions taken by the partner or husband were also associated with an increased odd of adequate maternal care. Islam and lower wealth status were associated with a lower probability of adequate maternal care. Conclusions: Policymakers and health administration should pay attention to the variation in the utilization of maternal health care across residence, region, religion, education, and wealth status to ensure safe motherhood.

Determinants and Trends of Health Facility Delivery in Bangladesh: A Hierarchical Modeling Approach.

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.

Performance Evaluation of Machine Learning Algorithm for Classification of Unintended Pregnancy among Married Women in Bangladesh.

Intended pregnancy is one of the significant indicators of women's well-being. Globally, 74 million women become pregnant every year without planning. Unintended pregnancies account for 28% of all pregnancies among married women in Bangladesh. This study aimed to investigate the performance of six different machine learning (ML) algorithms applied to predict unintended pregnancies among married women in Bangladesh. From BDHS 2017-18, only 1129 pregnant women aged 15-49 were eligible for this study. An independent χ 2 test had performed before we considered six popular ML algorithms, such as logistic regression (LR), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), naïve Bayes (NB), and elastic net regression (ENR) to predict the unintended pregnancy. Accuracy, sensitivity, specificity, Cohen's Kappa statistic, and area under curve (AUC) value were used as model evaluation. The bivariate analysis result showed that women aged 30-49 years, poor, not educated, and living in male-headed households had a higher percentage of unintended pregnancy. We found various performance parameters for the classification of unintended pregnancy: LR accuracy = 79.29%, LR AUC = 72.12%; RF accuracy = 77.81%, RF AUC = 72.17%; SVM accuracy = 76.92%, SVM AUC = 70.90%; KNN accuracy = 77.22%, KNN AUC = 70.27%; NB accuracy = 78%, NB AUC = 73.06%; and ENR accuracy = 77.51%, ENR AUC = 74.67%. Based on the AUC value, we can conclude that of all the ML algorithms we investigated, the ENR algorithm provides the most accurate classification for predicting unwanted pregnancy among Bangladeshi women. Our findings contribute to a better understanding of how to categorize pregnancy intentions among Bangladeshi women. As a result, the government can initiate an effective campaign to raise contraception awareness.

Prediction of COVID-19 Pandemic in Bangladesh: Dual Application of Susceptible-Infective-Recovered (SIR) and Machine Learning Approach.

The outbreak of COVID-19 is a global problem today, and, to reduce infectious cases and increase recovered cases, it is relevant to estimate the future movement and pattern of the disease. To identify the hotspot for COVID-19 in Bangladesh, we performed a cluster analysis based on the hierarchical k-means approach. A well-known epidemiological model named "susceptible-infectious-recovered (SIR)" and an additive regression model named "Facebook PROPHET Procedure" were used to predict the future direction of COVID-19 using data from IEDCR. Here we compare the results of the optimized SIR model and a well-known machine learning algorithm (PROPHET algorithm) for the forecasting trend of the COVID-19 pandemic. The result of the cluster analysis demonstrates that Dhaka city is now a hotspot for the COVID-19 pandemic. The basic reproduction ratio value was 2.1, which indicates that the infection rate would be greater than the recovery rate. In terms of the SIR model, the result showed that the virus might be slightly under control only after August 2022. Furthermore, the PROPHET algorithm observed an altered result from SIR, implying that all confirmed, death, and recovered cases in Bangladesh are increasing on a daily basis. As a result, it appears that the PROPHET algorithm is appropriate for pandemic data with a growing trend. Based on the findings, the study recommended that the pandemic is not under control and ensured that if Bangladesh continues the current pattern of infectious rate, the spread of the pandemic in Bangladesh next year will increase.

Biosocial correlates of adolescent's knowledge on pubertal changes in rural Bangladesh: A structural equation model.

BACKGROUND: The present study aimed to identify factors that are associated with puberty knowledge among school-going rural adolescents in Bangladesh. METHODS: This cross-sectional study was conducted on 2724 school-going (grades VI-IX) adolescents who were aged between 10-24 years. The adolescents resided only in rural areas of Bangladesh. In this study, relationship between socio-demographic factors and controlling behaviour was assessed considering Bronfenbrenner's bioecological model. Considering the complex nature of Bronfenbrenner's bioecological model the structural equation model to explore factors related to the Adolescents' knowledge of pubertal changes. RESULTS: The structural equation model result showed a significant association among gender, education, age, and parental limit setting on daily activities with student's knowledge on pubertal changes. peer connection, and peer regulation were associated with adolescent knowledge on puberty directly as well as through the mediator variables year of schooling, academic performance and, parental behavioural control. CONCLUSION: Adolescents Age, years of schooling, and teachers concerns are positively associated with adolescents' knowledge on puberty. Whereas, parents' and peers' controlling behaviors are negatively associated with adolescents' understanding of pubertal changes. Therefore, there is needed an effective plan to raise the attention of parents and teachers on adolescents' pubertal issues to ensure adolescents' informed pubertal period.

Prevalence of Child Functional Difficulties and Its Associated Factors in Bangladesh: An Application of Count Regression Model.

Children that are mentally and physically healthy have a higher quality of life and are better able to function in their daily lives. Therefore, this study is aimed at investigating associated factors causing functional difficulties in male and female children ages 5-17 years. This study used data from a nationally representative cross-sectional household survey named the Multiple Indicator Cluster Survey (MICS) Bangladesh 2019. A total of 58,746 children aged 5-17 were selected for the study, where 30,300 children were male, and 28,446 were female. To deal with overdispersed count data, the study used a negative binomial regression model to find the associated factors. The results show that 39.3% of the male children and 40.9% of the female children were from the age group of 10-14. Educated children had a lower risk of dysfunction. Among male children, women with a total number of children ever born of 4 or more were 1.21 times (incidence rate ratios (IRR) = 1.21) more likely to have a dysfunctional child. Children of dysfunctional mothers are more likely to be dysfunctional themselves. The incidence rate ratio for children functional difficulty among Muslim girls was 36 percent higher than non-Muslim girls in Bangladesh. When compared to the Barisal Division, female children in the Mymensingh Division had a 16% higher risk of functional problems. Based on the findings, the Bangladesh government and other development partners should initiate policies and programs to minimize the impact of functional dysfunction in children.

Determinants of the Early Childhood Development Index among children aged < 5 years in Bangladesh, Costa Rica and Ghana: a comparative study.

BACKGROUND: Early child development is a crucial factor for children that controls health and well-being in later life. AIMS: To determine the influence of sociodemographic factors on the Early Child Development Index (ECDI) among children aged < 5 years. METHODS: The analysis was performed using cross-sectional survey data from 2019, 2017-2018 and 2018 Multiple Indicator Cluster Surveys from Bangladesh, Ghana and Costa Rica, respectively. We used the χ2 test for bivariate analysis and binary logistic regression model for multivariate analysis for all 3 countries. All the statistical analyses were performed with IBM SPSS version 25 and R version 4.0.0. RESULTS: Child age and sex, followed by maternal education level, economic status, child nutritional status, reading children's books, and maternal functional difficulties had the greatest effect on ECDI. Children aged 36-47 months had lower odds of development than those aged 48-59 months, and boys had lower odds of development than girls in Bangladesh, Costa Rica and Ghana. Urban children had lower odds of development than rural children in Costa Rica but higher odds in Ghana. CONCLUSION: We recommend that governments should take the necessary steps to enhance children's early development and well-being in all 3 countries by raising education, improving economic conditions and providing balanced nutrition.

Sociodemographic factors and early marriage among women in Bangladesh, Ghana and Iraq: An illustration from Multiple Indicator Cluster Survey.

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.

Regional variations of child development index in Bangladesh.

Early development is a vital phase in childhood life. The study aimed to identify factors that were associated with the early development of 36-59 months children in Bangladesh. The findings of this study will formulate the design of appropriate policy and programmed responses. Utilizing Multiple Indicator Cluster Survey data, influencing components of child development status were evaluated for both rural and urban areas of Bangladesh. A total of 23,099 children under the age of five were included in this analysis. Chi-square analysis was conducted to assess the association between outcome variables and selected covariates. At the same time, this study uses two separate multivariate binary logistics regression models (respectively for urban areas and rural areas) to determine the risk factors that are primarily related to child development. Our research estimates that more than 70 percent of children develop early throughout the country. The multivariate analysis on the determinants of child development index among children aged between 36 and 59 months old regarding residence discovered a significant impact on child age and sex, maternal education, child education, wealth status, reading children's books. The adjusted odds of child nutrition status, playthings, and maternal functional difficulties have had a major impact on early child development in rural Bangladesh. Based on the findings, educational status, nutritional status, wealth-status, and some determinants of children care the most noteworthy findings in this study. Hence, policymakers should emphasize on such factors for improving children's development in residence.

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.