Determinants of developing cardiovascular disease risk with emphasis on type-2 diabetes and predictive modeling utilizing machine learning algorithms.

This research aims to enhance our comprehensive understanding of the influence of type-2 diabetes on the development of cardiovascular diseases (CVD) risk, its underlying determinants, and to construct precise predictive models capable of accurately assessing CVD risk within the context of Bangladesh. This study combined data from the 2011 and 2017 to 2018 Bangladesh Demographic and Health Surveys, focusing on individuals with hypertension. CVD development followed World Health Organization (WHO) guidelines.

Understanding and predicting pregnancy termination in Bangladesh: A comprehensive analysis using a hybrid machine learning approach.

Reproductive health issues, including unsafe pregnancy termination, remain a significant concern for women in developing nations. This study focused on investigating and predicting pregnancy termination in Bangladesh by employing a hybrid machine learning approach. The analysis used data from the Bangladesh Demographic and Health Surveys conducted in 2011, 2014, and 2017 to 2018.

Rural and urban differences in the prevalence and determinants of Type-2 diabetes in Bangladesh.

Objective: To estimate the prevalence of Type 2 Diabetes (T2D) in urban and rural settings and identify the specific risk factors for each location.

Method: We conducted this study using data from the 2017-18 Bangladesh Demographic and Health Survey (BDHS), sourced from the DHS website. The survey employed a stratified two-stage sampling method, which included 7,658 women and 7,048 men aged 18 and older who had their blood glucose levels measured.

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.

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.

Smoke-free status of homes and workplaces among Indian people: Evidence from Global Adult Tobacco SurveyData-2016/2017.

Aims: This study aimed to determine the impact of correlates on tobacco control/smoke-free status of homes and workplace among Indian people. To assess the magnitude of the problem, the relationship between smoke-free status and secondhand smoke (SHS) exposure was also explored.

Methods: Data was extracted from the Global Adult Tobacco Survey Data (GATS)-2017.

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.

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.

Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model.

Introduction: Anemia is indeed a significant risk factor for children's health as it affects growth retardation and has severe short and prolonged effects that follow in morbidity and death. Notwithstanding such ways to tackle anemia, the prevalence remains high in India and poses a severe public health concern.

Objectives: The primary focus of this study was to find the prevalence and to determine the factors associated with the anemia of children under five years of age in India.

Association Between Symptoms and Severity of Disease in Hospitalised Novel Coronavirus (COVID-19) Patients: A Systematic Review and Meta-Analysis.

Background: Symptoms of the novel coronavirus disease (COVD-19) are well known, although asymptomatic cases were also reported due to this rapidly evolving viral disease. However, there has been limited research with inconsistent findings on symptoms of COVID-19 and disease severity. We aimed to evaluate the association between symptoms and severity of disease in adult patients with confirmed COVID-19 by performing a meta-analysis.

Machine Learning Approaches for Predicting Hypertension and Its Associated Factors Using Population-Level Data From Three South Asian Countries.

Background: Hypertension is the most common modifiable risk factor for cardiovascular diseases in South Asia. Machine learning (ML) models have been shown to outperform clinical risk predictions compared to statistical methods, but studies using ML to predict hypertension at the population level are lacking. This study used ML approaches in a dataset of three South Asian countries to predict hypertension and its associated factors and compared the model's performances.

Knowledge, Attitudes, and Practices Concerning COVID-19 in Bangladesh: A Qualitative Study of Patients With Chronic Illnesses.

The novel coronavirus disease (COVID-19) has posed a serious risk with pre-existing health conditions. This study was conducted to understand the knowledge, attitude, and practices concerning COVID-19 among patients with chronic illnesses in Bangladesh during the pandemic. The study was conducted in Khulna city of Bangladesh following a qualitative research design.

Correction: Prevalence of unintended pregnancy and its associated factors: Evidence from six south Asian countries.

[This corrects the article DOI: 10.1371/journal.pone.

Machine Learning Approaches to Identify Patient Comorbidities and Symptoms That Increased Risk of Mortality in COVID-19.

Providing appropriate care for people suffering from COVID-19, the disease caused by the pandemic SARS-CoV-2 virus, is a significant global challenge. Many individuals who become infected may have pre-existing conditions that may interact with COVID-19 to increase symptom severity and mortality risk. COVID-19 patient comorbidities are likely to be informative regarding the individual risk of severe illness and mortality.

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.

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.

Does worriedness among the rural adults promote COVID-19 related awareness in Bangladesh?

People living in urban areas are usually more aware of their health issues due to the availability and accessibility of health care facilities. Several studies have illustrated anxiousness, attitudes, and perceptions among urban people during COVID-19. This research attempted to assess how worriedness among rural adults may promote COVID-19 related awareness in Bangladesh.

Mental Health of Physicians During COVID-19 Outbreak in Bangladesh: A Web-Based Cross-Sectional Survey.

There have been numerous studies about the health implication of COVID-19 on patients, but little attention has been paid to the impacts of the pandemic on physicians. Our paper attends to this gap by exploring the mental health of physicians in Bangladesh during the COVID-19 pandemic. This is particularly important since the mental health of physicians impacts not only on themselves, but also their professional performance and hence the care of patients.

Prevalence of unintended pregnancy and its associated factors: Evidence from six south Asian countries.

Aim: Unintended pregnancy is a significant public health concern in South Asian countries because of its negative association with the socioeconomic and health outcomes for both children and mothers. The present study aimed to explore the prevalence of unintended pregnancy and explore its determinants among women of reproductive age in six South Asian countries.

Methods: Nationwide latest demography and health survey data from six South Asian countries, including Bangladesh (2014), Pakistan (2017-2018), Nepal (2016), Afghanistan (2015), Maldives (2016-2017) and India (2015-2016) were pooled for the present study.

Prevalence and Risk Factors of Hypertension Among Young Adults in Albania.

Introduction: Hypertension is one of the major risk factors for cardiovascular disease and the leading cause of death worldwide. Hypertension was defined as systolic or diastolic blood pressure according to Joint National Committee 7 (JNC7) and 2017 American College of Cardiology/American Hypertension Association (ACC/AHA) rules.

Aim: The aims of this study was to determine the difference in hypertension prevalence and its risk factors using ACC/AHA rule, and compared its result with JNC7 rule.

Machine learning algorithms for predicting malnutrition among under-five children in Bangladesh.

Objective: The aim of this study was is to predict malnutrition status in under-five children in Bangladesh by using various machine learning (ML) algorithms.

Methods: For analysis purposes, the nationally representative secondary records from the 2014 Bangladesh Demographic and Health Survey (BDHS) were used. Five well-known ML algorithms such as linear discriminant analysis (LDA), k-nearest neighbors (k-NN), support vector machines (SVM), random forest (RF), and logistic regression (LR) have been considered to accurately predict malnutrition status among children.