Prevalence and determinants of hypertension in South-Asian Urban Communities: findings from Demographic and Health Surveys (DHS) data of South Asian countries.

Hypertension increases risk of stroke and other cardiovascular diseases, however, its prevalence and determinants in South Asian urban communities using country representative community-based datasets is lacking. This study evaluated prevalence of hypertension and it's determinants among urban residents of three South Asian countries. Urban population data from demographic and health surveys in Bangladesh, India, and Nepal were extracted. Hypertension prevalence was defined as systolic/diastolic blood pressure ≥ 140/ 90 mmHg. Age, education, wealth, physical activity, alcohol, BMI were considered as risk factors associated with the increased risk of hypertension. We performed binary logistic regression and calculated adjusted Odds Ratios (AOR) with 95% confidence interval (CI) to assess factors related to hypertension. Hypertension prevalence was 37.4% in India, 25.1% in Bangladesh and 18.4% in Nepal. Prevalence increased with age in all settings. Females had reduced odds of hypertension in Bangladesh (AOR 0.75; CI: 0.69, 0.81) and Nepal (AOR 0.62; CI: 0.54, 0.71), but higher risk in India (AOR 2.54; CI: 2.45, 2.63). Low education, caffeine consumption, obesity was associated with higher prevalence of hypertension in all three countries. Smokers had increased odds of hypertension in India (AOR 1.11; CI: 1.06, 1.15) and Nepal (AOR 1.23; 1.02, 1.47). Overall, hypertension prevalence is high in all three countries. Modifiable socioeconomic and lifestyle factors (education, wealth index, smoking status, caffeine consumption and BMI) associated with hypertension. Comprehensive hypertension pacific and sensitive interventions (including behavioral modification treatments and timely screening and access to health care) are urgently needed to prevent and control hypertension among urban populations in South Asia.

A comparative study of machine learning algorithms for predicting domestic violence vulnerability in Liberian women.

Domestic violence against women is a prevalent in Liberia, with nearly half of women reporting physical violence. However, research on the biosocial factors contributing to this issue remains limited. This study aims to predict women's vulnerability to domestic violence using a machine learning approach, leveraging data from the Liberian Demographic and Health Survey (LDHS) conducted in 2019-2020. We employed seven machine learning algorithms to achieve this goal, including ANN, KNN, RF, DT, XGBoost, LightGBM, and CatBoost. Our analysis revealed that the LightGBM and RF models achieved the highest accuracy in predicting women's vulnerability to domestic violence in Liberia, with 81% and 82% accuracy rates, respectively. One of the key features identified across multiple algorithms was the number of people who had experienced emotional violence. These findings offer important insights into the underlying characteristics and risk factors associated with domestic violence against women in Liberia. By utilizing machine learning techniques, we can better predict and understand this complex issue, ultimately contributing to the development of more effective prevention and intervention strategies.

Implementation of jute-based nose holder in surgical masks to reduce plastic contamination.

Plastic, in all its forms, always harms the environment, humans, and other living organisms. The coronavirus situation exacerbates the use of plastic products more than at any other time, of which surgical masks contribute to plastic pollution the most. These masks spread to terrestrial and aquatic environments, where they break down into even more noxious microplastics. These microplastics enter the human food chain through water and fish, causing severe damage to the lungs, kidneys, and intestines and even causing death. In this paper, a jute nose holder mask was prepared as an alternative to typical masks to reduce plastic pollution. The jute nose holder was produced with a modified jute flyer-spinning frame machine, where jute was used as the sheath and metal wire was applied as the core component. The nose holder was later coated with starch-based natural gum. Then, the non-woven fabric of 75 grams per square meter (GSM), and the jute nose holder were used to produce the alternative, environmentally friendly mask, which might reduce the 773 tons of plastic waste generated daily from the nose holder of the mask. This alternative mask was then distributed to 900 people for a survey to find out their opinion. From the results of the survey, it is seen that 82.6% of people felt no problem in the nose when they put on the given mask. 85.6% considered the mask more comfortable than the traditional mask, and it was rated above average by 79.8% of the surveyors. So, this study suggests that the given mask can be a sustainable alternative to traditional masks.

Trends and patterns of inequalities in using facility delivery among reproductive-age women in Bangladesh: a decomposition analysis of 2007-2017 Demographic and Health Survey data.

OBJECTIVES: The prime objectives of the study were to measure the prevalence of facility delivery, assess socioeconomic inequalities and determine potential associated factors in the use of facility delivery in Bangladesh.DesignCross-sectional. SETTING: The study involved investigation of nationally representative secondary data from the Bangladesh Demographic and Health Survey between 2007 and 2017-2018. PARTICIPANTS: The participants of this study were 30 940 (weighted) Bangladeshi women between the ages of 15 and 49. METHODS: Decomposition analysis and multivariable logistic regression were both used to analyse data to achieve the study objectives. RESULTS: The prevalence of using facility delivery in Bangladesh has increased from 14.48% in 2007 to 49.26% in 2017-2018. The concentration index for facility delivery utilisation was 0.308 with respect to household wealth status (p<0.001), indicating that use of facility delivery was more concentrated among the rich group of people. Decomposition analysis also indicated that wealth quintiles (18.31%), mothers' education (8.78%), place of residence (7.75%), birth order (5.56%), partners' education (4.30%) and antenatal care (ANC) seeking (8.51%) were the major contributors to the prorich socioeconomic inequalities in the use of facility delivery. This study found that women from urban areas, were overweight, had any level of education, from wealthier families, had ANC, and whose partners had any level of education and involved in business were more likely to have facility births compared with their respective counterparts. CONCLUSIONS: This study found a prorich inequality in the use of facility delivery in Bangladesh. The socioeconomic disparities in facility delivery must be addressed if facility delivery usage is to increase in Bangladesh.

Factors associated with age of mother at first birth in Albania: application of quantile regression model.

The objective of this study was to explore the risk factors that can determine the age of mother at first birth in Albania. The necessary information was extracted from a nationally representative sample survey, Albania Demographic and Health Survey, 2017-18 dataset. To identify the possible risk factors of the age of mother at first birth, we applied quantile regression model. The mean age of mother at first birth was found to be 22.38 years with standard deviation of 3.56 years. The minimum and maximum age was reported 15 and 45 years, respectively. From the result of quantile regression, respondent's current age, education level and partner's higher education level were found positive impact on age of the mother at first birth. However, rural area, partner's age and smoking status found negative impact on age of the mother at first birth. This study suggests that women's education should be more prioritized because it can interfere with the idea of early marriage. Awareness can also be raised by social activities since the improvement of social conditions and reduction of social deprivation can increase the age of mother at first birth.

Costus pictus D. Don leaf extract stimulates GLP-1 secretion from GLUTag L-cells and has cytoprotective effects in BRIN-BD11 ß-cells.

ETHNOPHARMACOLOGICAL RELEVANCE: Costus pictus D. Don, commonly known as insulin plant, is a traditional Indian antidiabetic herbal medicine with glucose-lowering and insulin secretory effects having been reported in animal models and humans with Type 2 diabetes. However, its effects on GLP-1 secretion from intestinal endocrine L-cells and potential metabolic and protective effects in insulin secreting pancreatic ß-cells are not yet fully understood. AIM OF THE STUDY: This study is aimed to elucidate the effects of Costus pictus D. Don leaf extract (CPE) on L-cell function and GLP-1 secretion using the established murine GLUTag L-cell model and to investigate its potential cytoprotective effects against detrimental effects of palmitate and cytokines in pancreatic ß-cells using BRIN-BD11 cells. METHODS: Costus pictus D. Don dried leaf powder was extracted by soxhlet method. Cell viability was determined by MTT assay. Changes in gene and protein expression were quantified by qPCR and western blotting, respectively. GLP-1 and insulin secretion were measured by ELISA. RESULTS: CPE significantly enhanced the percentage of viable BRIN-BD11 and GLUTag cells and protected BRIN-BD11 cells against palmitate- and proinflammatory cytokine-induced toxicity. CPE enhanced acute GLP-1 secretion 6.4-16.3-fold from GLUTag cells at both low (1.1 mM) and high (16.7 mM) glucose (P < 0.01) concentrations. Antioxidant (Nrf2, Cat & Gpx1) and pro-proliferative (Erk1 and Jnk1) gene expression were upregulated by 24 h culture with CPE, while proinflammatory transcription factor NF-κB was downregulated. CONCLUSION: Diminished postprandial GLP-1 secretion and loss of insulin secreting ß-cells are known contributors of T2DM. Our data suggests that CPE acutely stimulates GLP-1 secretion from L-cells. Long term exposure of the BRIN-BD11 cells to CPE enhances cell number and may protect against palmitate and proinflammatory cytokines by activating multiple pathways. Thus, the current study suggests that the possible antidiabetic properties of CPE may be linked to enhanced GLP-1 secretion and ß-cell protection which could be beneficial in the management of T2DM.