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Malnutrition among adolescents is often associated with inadequate dietary diversity (DD). We aimed to explore the prevalence of inadequate DD and its socio-economic determinants among adolescent girls and boys in Bangladesh. A cross-sectional survey was conducted during the 2018–19 round of national nutrition surveillance in Bangladesh. Univariate and multivariable logistic regression was performed to identify the determinants of inadequate DD among adolescent girls and boys separately. This population-based survey covered eighty-two rural, non-slum urban and slum clusters from all divisions of Bangladesh. A total of 4865 adolescent girls and 4907 adolescent boys were interviewed. The overall prevalence of inadequate DD was higher among girls (55⋅4 %) than the boys (50⋅6 %). Moreover, compared to boys, the prevalence of inadequate DD was higher among the girls for almost all socio-economic categories. Poor educational attainment, poor maternal education, female-headed household, household food insecurity and poor household wealth were associated with increased chances of having inadequate DD in both sexes. In conclusion, more than half of the Bangladeshi adolescent girls and boys consumed an inadequately diversified diet. The socio-economic determinants of inadequate DD should be addressed through context-specific multisectoral interventions.

ObjectiveTo assess the prevalence of and factors associated with depression among adolescent boys and girls.DesignWe conducted a nationwide cross-sectional study.SettingThis study was carried out in 82 randomly selected clusters (57 rural, 15 non-slum urban and 10 slums) from eight divisions of Bangladesh.ParticipantsWe interviewed 4907 adolescent boys and 4949 adolescent girls.Primary and secondary outcome measuresThe primary outcome measure was ‘any depression’ and the secondary outcome measures were types of depression: no or minimal, mild, moderate, moderately severe and severe.ResultsThe overall prevalence of no or minimal, mild, moderate, moderately severe and severe depression was 75.5%, 17.9%, 5,4%, 1.1% and 0.1%, respectively. Across most of the sociodemographic, lifestyle and anthropometric strata, the prevalence of any depression was higher among adolescent girls. In both sexes, depression was associated with higher age, higher maternal education, paternal occupation e.g., business, absence of a 6–9-year-old member in the household, food insecurity, household consumption of unfortified oil, household use of non-iodised salt, insufficient physical activity (adjusted odds ratio, AOR: 1.24 for boys, 1.44 for girls) and increased television viewing time e.g., ≥121 minute/day (AOR: 1.95 for boys, 1.99 for girls). Only among boys, depression was also associated with higher paternal education e.g., complete secondary and above (AOR: 1.42), absence of another adolescent member in the household (AOR: 1.34), household use of solid biomass fuel (AOR: 1.39), use of any tobacco products (AOR: 2.17), and consumption of processed food (AOR: 1.24). Only among girls, non-slum urban residence, Muslim religion, and household size ≤4 were also associated with depression.ConclusionThe prevalence of depression among adolescent boys and girls is high in Bangladesh. In most sociodemographic, lifestyle and anthropometric strata, the prevalence is higher among girls. In this age group, depression is associated with a number of sociodemographic and lyfestyle factors. The government of Bangladesh should consider these findings while integrating adolescent mental health in the existing and future programmes.

ObjectiveWe aimed to estimate the gender-specific prevalence and associated factors of hypertension among elderly people in Bangladesh.Design and methodWe analysed data from the food security and nutrition surveillance round 2018–2019. The multistage cluster sampling method was used to select the study population. Hypertension was defined as systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg and/or having a history of hypertension. We carried out the descriptive analysis, bivariate and multivariable logistic regression to report the weighted prevalence of hypertension as well as crude and adjusted ORs with 95% CI. A p value<0.05 was considered statistically significant.SettingThe study was conducted in 82 clusters (57 rural, 15 non-slum urban and 10 slums) in all eight administrative divisions of Bangladesh.ParticipantsA total of 2482 males and 2335 females aged ≥60 years were included in this analysis.ResultsThe weighted prevalence of hypertension was 42% and 56% among males and females, respectively. The prevalence was higher among females across all sociodemographic, behavioural and clinical strata. Factors associated with higher odds of hypertension (adjusted OR (AOR) (95% CI) for males and females, respectively) were age ≥70 years (1.32 (1.09, 1.60) and 1.40 (1.15, 1.71)); insufficient physical activity (1.50 (1.25, 1.81) and 1.38 (1.15, 1.67)); higher waist circumference (2.76 (2.22, 3.43) and 2.20 (1.82, 2.67)); and self-reported diabetes (1.36 (1.02, 1.82) and 1.82 (1.35, 2.45)). Additionally, living in slums decreased (0.71 (0.52, 0.96)) and education >10 years increased odds of hypertension (1.83 (1.38, 2.44)) among males.ConclusionIn Bangladesh, half of the elderly persons were hypertensive, with a higher prevalence in females. In both sexes, odds of hypertension was higher among persons with older age (≥70 years), insufficient physical activity, higher waist circumference and self-reported diabetes. The Ministry of Health of Bangladesh should consider these findings while designing and implementing health programmes for elderly population.

Security of the software system is a prime focus area for software development teams. This paper explores some data science methods to build a knowledge management system that can assist the software development team to ensure a secure software system is being developed. Various approaches in this context are explored using data of insurance domain-based software development. These approaches will facilitate an easy understanding of the practical challenges associated with actual-world implementation. This paper also discusses the capabilities of language modeling and its role in the knowledge system. The source code is modeled to build a deep software security analysis model. The proposed model can help software engineers build secure software by assessing the software security during software development time. Extensive experiments show that the proposed models can efficiently explore the software language modeling capabilities to classify software systems’ security vulnerabilities.