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Objective: We explored automated concept-based indexing of unstructured figure captions to improve retrieval of images from radiology journals. Design: The MetaMap Transfer program (MMTx) was used to map the text of 84,846 figure captions from 9,004 peer-reviewed, English-language articles to concepts in three controlled vocabularies from the UMLS Metathesaurus, version 2006AA. Sampling procedures were used to estimate the standard information-retrieval metrics of precision and recall, and to evaluate the degree to which concept-based retrieval improved image retrieval. Measurements: Precision was estimated based on a sample of 250 concepts. Recall was estimated based on a sample of 40 concepts. The authors measured the impact of concept-based retrieval to improve upon keyword-based retrieval in a random sample of 10,000 search queries issued by users of a radiology image search engine. Results: Estimated precision was 0.897 (95% confidence interval, 0.857-0.937). Estimated recall was 0.930 (95% confidence interval, 0.838-1.000). In 5,535 of 10,000 search queries (55%), concept-based retrieval found results not identified by simple keyword matching; in 2,086 searches (21%), more than 75% of the results were found by concept-based search alone. Conclusion: Concept-based indexing of radiology journal figure captions achieved very high precision and recall, and significantly improved image retrieval. [ABSTRACT FROM AUTHOR]

Background: Respiratory syncytial virus (RSV) is the leading cause of acute lower respiratory infections (ALRIs) associated hospitalisations in children. It is unclear if hospitalized RSV-ALRI differs in clinically from other viral ALRIs. We aimed to compare the disease impact of hospitalised RSV with other viral ALRI in children under 2 years., Methods: We conducted a retrospective study using electronic medical records of children under 2 hospitalized with ALRIs at Sydney Children's Hospitals Network from 2020-2022. We compared demographics and clinical features between RSV-positive and RSV-negative (positive for other viruses) cases. Poisson quasi-likelihood regression was used to estimate adjusted prevalence ratios (aPRs) for three in-hospital outcomes: length of stay, need for respiratory support and intensive care., Results: We examined 330 children under 2 years hospitalized with RSV-positive ALRIs and 330 with RSV-negative ALRIs (positive for other viruses). RSV-positive cases were older (12 vs. 8 months, p<0.001) and more often presented with cough (99% vs. 92%), fever (80% vs. 58%), crackles (89% vs. 76%), hypoxia (50% vs. 36%), and lethargy (36% vs. 20%). They were also more likely to undergo chest x-rays (74% vs. 49%) and receive antibiotics (65% vs. 35%). Adjusted analysis showed RSV-positive children had a higher likelihood of LOS > 2 days (aPR 1.95, 95% CI 1.14-3.36).). However, there were no differences in the need for intensive care or respiratory support., Conclusion: Children with RSV-ALRI exhibited more severe symptoms, received more antibiotics, and had longer hospital stays compared to those with other viral ALRIs, underscoring the need for effective prevention and treatment strategies for RSV., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Objectives: The prevalence of low birth weight (LBW) is an important indicator of child health and wellbeing. However, in many countries, decisions regarding care and treatment are often based on mothers' perceptions of their children's birth size due to a lack of objective birth weight data. Additionally, birth weight data that is self-reported or recorded often encounters the issue of heaping. This study assesses the concordance between the perceived birth size and the reported or recorded birth weight. We also investigate how the presence of heaped birth weight data affects this concordance, as well as the relationship between concordance and various sociodemographic factors., Methods: We examined 4,641 birth records reported in the 2019 Bangladesh Multiple Indicator Cluster Survey. The sensitivity-specificity analysis was performed to assess perceived birth size's ability to predict LBW, while Cohen's Kappa statistic assessed reliability. We used the kernel smoothing technique to correct heaping of birth weight data, as well as a multivariable multinomial logistic model to assess factors associated with concordance., Results: Maternally-perceived birth size exhibited a low sensitivity (63.5%) and positive predictive value (52.6%) for predicting LBW, but a high specificity (90.1%) and negative predictive value (93.4%). There was 86.1% agreement between birth size and birth weight-based classifications (Kappa = 0.49, indicating moderate agreement). Smoothed birth weight data did not improve agreement (83.4%, Kappa = 0.45). Of the sociodemographic factors, early marriage was positively associated with discordance (i.e., overestimation)., Conclusions: An important consideration when calculating the LBW prevalence is that maternally perceived birth size is not an optimal proxy for birth weight. Focus should be placed on encouraging institutional births and educating community health workers and young mothers about the significance of measuring and recording birth weight., (© 2024. The Author(s).)

Background: Asthma is the most common chronic respiratory illness among children in Australia. While childhood asthma prevalence varies by region, little is known about variations at the small geographic area level. Identifying small geographic area variations in asthma is critical for highlighting hotspots for targeted interventions. This study aimed to investigate small area-level variation, spatial clustering, and sociodemographic risk factors associated with childhood asthma prevalence in Australia., Methods: Data on self-reported (by parent/carer) asthma prevalence in children aged 0-14 years at statistical area level 2 (SA2, small geographic area) and selected sociodemographic features were extracted from the national Australian Household and Population Census 2021. A spatial cluster analysis was used to detect hotspots (i.e., areas and their neighbours with higher asthma prevalence than the entire study area average) of asthma prevalence. We also used a spatial Bayesian Poisson model to examine the relationship between sociodemographic features and asthma prevalence. All analyses were performed at the SA2 level., Results: Data were analysed from 4,621,716 children aged 0-14 years from 2,321 SA2s across the whole country. Overall, children's asthma prevalence was 6.27%, ranging from 0 to 16.5%, with significant hotspots of asthma prevalence in areas of greater socioeconomic disadvantage. Socioeconomically disadvantaged areas had significantly higher asthma prevalence than advantaged areas (prevalence ratio [PR] = 1.10, 95% credible interval [CrI] 1.06-1.14). Higher asthma prevalence was observed in areas with a higher proportion of Indigenous individuals (PR = 1.13, 95% CrI 1.10-1.17)., Conclusions: We identified significant geographic variation in asthma prevalence and sociodemographic predictors associated with the variation, which may help in designing targeted asthma management strategies and considerations for service enhancement for children in socially deprived areas., (© 2024. The Author(s).)

Antibiotics, as a class of environmental pollutants, pose a significant challenge due to their persistent nature and resistance to easy degradation. This study delves into modeling and optimizing conventional Fenton degradation of antibiotic sulfamethoxazole (SMX) and total organic carbon (TOC) under varying levels of H 2 O 2 , Fe 2+ concentration, pH, and temperature using statistical and artificial intelligence techniques including Multiple Regression Analysis (MRA), Support Vector Regression (SVR) and Artificial Neural Network (ANN). In statistical metrics, the ANN model demonstrated superior predictive accuracy compared to its counterparts, with lowest RMSE values of 0.986 and 1.173 for SMX and TOC removal, respectively. Sensitivity showcased H 2 O 2 /Fe 2+ ratio, time and pH as pivotal for SMX degradation, while in simultaneous SMX and TOC reduction, fine tuning the time, pH, and temperature was essential. Leveraging a Hybrid Genetic Algorithm-Desirability Optimization approach, the trained ANN model revealed an optimal desirability of 0.941 out of 1000 solutions which yielded a 91.18% SMX degradation and 87.90% TOC removal under following specific conditions: treatment time of 48.5 min, Fe 2+ : 7.05 mg L -1 , H 2 O 2 : 128.82 mg L -1 , pH: 5.1, initial SMX: 97.6 mg L -1 , and a temperature: 29.8 °C. LC/MS analysis reveals multiple intermediates with higher m/z (242, 270 and 288) and lower m/z (98, 108, 156 and 173) values identified, however no aliphatic hydrocarbon was isolated, because of the low mineralization performance of Fenton process. Furthermore, some inorganic fragments like NH 4 + and NO 3 - were also determined in solution. This comprehensive research enriches AI modeling for intricate Fenton-based contaminant degradation, advancing sustainable antibiotic removal strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Altitude-related venous thrombosis (ARVT) is a condition of growing concern among individuals engaged in high-altitude travel and activities. This updated review explores the epidemiology, pathophysiological mechanisms, clinical presentations, and management of ARVT based on a thematic analysis and synthesis of the existing literature. ARVT's multifactorial etiology involves the interplay of hypobaric hypoxia and endothelial dysfunction, creating a procoagulant state and increasing the risk of thrombosis. Common clinical manifestations include pain, swelling, and redness in the extremities, necessitating accurate and timely diagnosis, particularly in remote settings. Thromboprophylaxis during high-altitude travel and activities plays a crucial role in reducing the risk of ARVT, while anticoagulation remains the mainstay of management. Further research is needed to optimize preventive and treatment strategies, enhancing patient outcomes and safety in high-altitude environments., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

This study investigated the associations between greenness and blood pressure (BP) metrics (systolic BP [SBP], diastolic BP [DBP], hypertension) among urban adults in Bangladesh and the potential mediation effects of body mass index (BMI) using 2011 Bangladesh Demographic and Health Survey data for 2360 urban adults (aged ≥35 years). The Enhanced Vegetation Index was used as a measure of residential area greenness. Associations between greenness and BP metrics were estimated using linear and binary logistic regression models. We also conducted mediation analyses. Greater area-level greenness was inversely associated with SBP (β -1.33, 95%CI: -2.46, -.20), DBP (β -.83, 95%CI: -1.64, -.02), and hypertension (adjusted odds ratio .87, 95%CI: .77, .98). BMI substantially mediated associations between greenness and BP metrics. Adopting urban greening policies could reduce the risk of hypertension, thus can contribute to reduction of non-communicable disease burden in Bangladesh. Longitudinal studies are required to further investigate the causal pathways.

This study explored the impacts of COVID-19 on the mental health (MH)-related visits to general practices (GPs) among children and young people (CYP) up to 18 years of age in Australia. This study analysed national-level data captured by the NPS MedicineWise program on monthly CYP MH-related visits per 10,000 visits to GPs from January 2014 to September 2021. We considered the pre-COVID-19 period (January 2014-February 2020) and the COVID-19 period (March 2020-September 2021). We used a Bayesian structural time series (BSTS) model to estimate the impact of COVID-19 on MH-related GP visits per 10,000 visits. A total of 103,813 out of 7,690,874 visits to GP (i.e., about 135 per 10,000 visits) were related to MH during study period. The BSTS model showed a significant increase in the overall MH-related visits during COVID-19 period (33%, 95% Credible Interval (Crl) 8.5%-56%), particularly, visits related to depressive disorders (61%, 95% Crl 29%-91%). The greatest increase was observed among females (39%, 95% Crl 12%-64%) and those living in socioeconomically least disadvantaged areas (36%, 95% Crl 1.2-71%). Our findings highlight the need for resources to be directed towards at-risk CYP to improve MH outcomes and reduce health system burden., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

Measuring COVID-19-related mortality is vital for making public health policy decisions. The magnitude of COVID-19-related mortality is largely unknown in low- and middle-income countries (LMICs), including Bangladesh, due to inadequate COVID-19 testing capacity and a lack of robust civil registration and vital statistics systems. Even with the lack of data, cemetery-based death records in LMICs may provide insightful information on potential COVID-19-related mortality rates; nevertheless, there is a dearth of research employing cemetery-based death records. This study aimed to assess the excess mortality during the COVID-19 pandemic in an urban setting in Bangladesh using a cemetery-based death registration dataset. A total of 6,271 deaths recorded between January 2015 and December 2021 were analysed using a Bayesian structural time series model. Exploratory analysis found that the average monthly number of deaths was 69 during the pre-COVID-19 period (January 2015-February 2020), but significantly increased to 92 during the COVID-19 period (March 2020-December 2021). The increase in male deaths was twice as large as the increase in female deaths. Model-based results were not statistically significant (relative effect 17%, 95% credible interval: -18%, 57%), but there was an overall increasing trend during the COVID-19 period, and specific months or shorter periods had a substantial increase. This first-of-its-kind study in Bangladesh has assessed the excess mortality in an urban community during the COVID-19 pandemic. Cemetery-based death registration appears to aid in tracking population mortality, especially in resource-limited countries where collecting data on the ground is challenging during crisis periods; however, additional large-scale research is required., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Hossain et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Urbanization is accelerating in developing countries, which are simultaneously experiencing a rise in the prevalence of overnutrition (i.e., overweight and obesity), specifically among women. Since urbanization is a dynamic process, a continuous measure may better represent it when examining its association with overnutrition. However, most previous research has used a rural-urban dichotomy-based urbanization measure. This study utilized satellite-based night-time light intensity (NTLI) data to measure urbanization and evaluate its association with body weight in reproductive-aged (15-49) women in Bangladesh. Multilevel models estimated the association between residential area NTLI and women's body mass index (BMI) or overnutrition status using data from the latest Bangladesh Demographic and Health Survey (BDHS 2017-18). Higher area-level NTLI was associated with a higher BMI and increased odds of being overweight and obese in women. Living in areas with moderate NTL intensities was not linked with women's BMI measures, whereas living in areas with high NTL intensities was associated with a higher BMI or higher odds of being overweight and obese. The predictive nature of NTLI suggests that it could be used to study the relationship between urbanization and overnutrition prevalence in Bangladesh, though more longitudinal research is needed. This research emphasizes the necessity for preventive efforts to offset the expected public health implications of urbanization., (© 2023. The New York Academy of Medicine.)

Objectives: To analyze Australian national data to examine the impact of the coronavirus disease 2019 (COVID-19) pandemic on mental health-related hospital presentations among children and adolescents during the pandemic period with restrictions, and the period after the restrictions eased., Methods: We analyzed the monthly mental health-related inpatient admissions and emergency department (ED) attendances data from 6 large pediatric hospitals across Australia, using the Bayesian structural time series models. The COVID-19 restriction period was from March 2020 to December 2021 and the COVID-19 restriction-eased period from January to June 2022., Results: A total of 130 801 mental health-related hospital admissions (54 907) and ED attendances (75 894) were analyzed. During the COVID-19 restriction period, there was a significant increase in inpatient admissions related to deliberate self-harm behaviors (82%, 95% credible interval [CrI], 7%-160%) and ED attendances related to overall mental health disorders (15%, 95% CrI, 1.1%-30%) and eating disorders (76%, 95% CrI, 36%-115%). The increase was higher among females and those living in the least socioeconomically disadvantaged areas, suggesting a widening gap between mental health-related presentations by sex and socioeconomic status. After the restrictions eased, there were slight declines in mental health-related hospital presentations; however, the numbers remained higher than the pre-COVID-19 levels., Conclusions: The increase in mental health-related hospital presentations during the COVID-19 period calls for additional support for pediatric mental health care, particularly for eating disorders and deliberate self-harm among female adolescents. It is important to monitor pediatric mental health service use as we enter "COVID-19 normal" period.

Mental health disorders are responsible for 125.3 million disability-adjusted life years (DALYs) lost globally, with depression in adolescents rising faster than in adults. In total, more than 90% of the 1.2 billion adolescents in the world live in low- and middle-income countries (LMICs). Despite the rise in teenage marriage and pregnancy in LMICs, there is a paucity of research on the role of pregnancy as a risk factor for adolescent mental health, and the role of spousal connectedness as a potential protective factor. This study aims to address this gap. A total of 2408 currently married adolescent (aged 15-19 years) women from the Bangladesh Adolescent Health and Wellbeing Survey 2019-2020 were analysed. Multivariable models were used to assess the factors associated with depression symptoms and major depressive disorder (MDD). The prevalence of moderate/severe depressive symptoms or MDD among adolescents was 14.6%, well ahead of south Asian levels. The odds of having moderate/severe depressive symptoms (adjusted odds ratio [AOR]=1.94, 95% confidence interval [CI] 1.37-2.76) or MDD (AOR=1.63, 95%CI 1.18-2.25) were higher in pregnant adolescent women than in non-pregnant adolescent women. A closer relationship with one's husband reduced the risk of developing moderate/severe depressive symptoms (AOR=0.90, 95% CI 0.84-0.96) or MDD (AOR=0.91, 95% CI 0.86-0.97). Pregnancy and connectedness had no statistically significant interaction effect on depression. There is an urgent need for affordable and scalable interventions to reduce the risk of mental health morbidity in pregnant adolescent women especially in low- and middle-income countries., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Background: Globally, the COVID-19 pandemic seriously affected both physical and mental health conditions. This study aims to assess changes in the prevalence of depression among older adults during the COVID-19 pandemic in Bangladesh and explore the correlates of depression in pooled data., Methods: This study followed a repeated cross-sectional design and was conducted through telephone interviews on two successive occasions during the COVID-19 pandemic (October 2020 and September 2021) among 2077 (1032 in 2020-survey and 1045 in 2021-survey) older Bangladeshi adults aged 60 years and above. Depression was measured using the 15-item Geriatric Depression Scale (GDS-15). The binary logistic regression model was used to identify the factors associated with depression in pooled data., Results: A significant increase in the prevalence of depression was noted in the 2021 survey compared to the 2020 survey (47.2% versus 40.3%; adjusted odds ratio (aOR): 1.40, 95% confidence interval (CI): 1.11-1.75). Depression was significantly higher among participants without a partner (aOR 1.92, 95% CI 1.45-2.53), with a monthly family income of <5000 BDT (aOR: 2.65, 95% CI 1.82-3.86) or 5000-10 000 BDT (aOR: 1.30, 95% CI 1.03-1.65), living alone (aOR 2.24, 95% CI 1.40-3.61), feeling isolated (aOR 3.15, 95% CI 2.49-3.98), with poor memory/concentration (aOR 2.02, 95% CI 1.58-2.57), with non-communicable chronic conditions (aOR 1.34, 95% CI 1.06-1.69), overwhelmed by COVID-19 (aOR 1.54, 95% CI 1.18-2.00), having difficulty earning (aOR 1.49, 95% CI 1.15-1.92) or obtaining food (aOR 1.56, 95% CI 1.17-2.09) during COVID-19 pandemic, communicating less frequently (aOR 1.35, 95% CI 1.07-1.70) and needing extra care (aOR 2.28, 95% CI 1.75-2.96) during the pandemic., Conclusions: Policymakers and public health practitioners should provide immediate mental health support initiatives for this vulnerable population during the COVID-19 pandemic and beyond. Policymakers should also invest in creating safe places to practise mindful eating, exercise, or other refuelling activities as a means of preventing and managing depression., (© 2022 The Authors. Psychogeriatrics published by John Wiley & Sons Australia, Ltd on behalf of Japanese Psychogeriatric Society.)

The disproportionate potency of dyes in textile wastewater is a global concern that needs to be contended. The present study comprehensively investigates the adsorption of Navy-Blue dye (NB) onto bentonite clay based geopolymer/Fe 3 O 4 nanocomposite (GFC) using novel statistical and machine learning frameworks in the following steps; (1) synthesis and characterization of GFC, (2) experimental testing and modelling of NB adsorption onto GFC following Box-Behnken design and three response surface prediction models namely stepwise regression analysis (SRA), Support vector regression (SVR) and Kriging (KR), (3) parametric, sensitivity, thermodynamic and kinetic analysis of pH, GFC dose and contact time on adsorption performance, and (4) finding global parametric solution of the process using Latin Hypercube, Sobol and Taguchi orthogonal array sampling and combining SRA-SVR-KR predictions with novel hybrid simulated annealing (SA)-desirability function (DF) approach. Under the given testing range, parametric/sensitivity analysis revealed the critical role of pH over others accounting ∼37% relative effect and primarily derived the NB adsorption. The statistical evaluation of models revealed that all models could be utilized for elucidating and predicting the NB removal using GFC, however, SVR accuracy was better among others for this particular work, as the overall computed root mean squared error was only 0.55 while the error frequency counts remained <1 for 90% predictions. GFC showed 86.29% NB removal for the given experimental matrix which can be elevated to 96.25% under optimum conditions. The NB adsorption was found to be physical, spontaneous, favorable and obeyed pseudo-2nd order kinetics. The results demonstrate the suitability of GFC as the promising cost-effective and efficient alternative for the decolourization of urban and drinking water streams and elucidate the potential of machine learning models for accurate prediction & elevation of adsorption processes with less experimentation in water purification applications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Despite advancements in the use of body mass index (BMI) to categorize obesity severity in pediatrics, its utility in guiding individual clinical decision making remains limited. The Edmonton Obesity Staging System for Pediatrics (EOSS-P) provides a way to categorize the medical and functional impacts of obesity according to the severity of impairment. The aim of this study was to describe the severity of obesity among a sample of multicultural Australian children using both BMI and EOSS-P tools., Methods: This cross-sectional study included children aged 2-17 years receiving obesity treatment through the Growing Health Kids (GHK) multi-disciplinary weight management service in Australia between January to December 2021. BMI severity was determined using the 95th percentile for BMI on age and gender standardized Centre for Disease Control and Prevention (CDC) growth charts. The EOSS-P staging system was applied across the four health domains (metabolic, mechanical, mental health and social milieu) using clinical information., Results: Complete data was obtained for 338 children (age 10.0 ± 3.66 years), of whom 69.5% were affected by severe obesity. An EOSS-P stage 3 (most severe) was assigned to 49.7% of children, the remaining 48.5% were assigned stage 2 and 1.5% were assigned stage 1 (least severe). BMI predicted health risk as defined by EOSS-P overall score. BMI class did not predict poor mental health., Conclusion: Used in combination, BMI and EOSS-P provide improved risk stratification of pediatric obesity. This additional tool can help focus resources and develop comprehensive multidisciplinary treatment plans., Competing Interests: The authors have no conflicts of interest to disclose., (© 2022 The Authors. Obesity Science & Practice published by World Obesity and The Obesity Society and John Wiley & Sons Ltd.)

Young adulthood is a crucial period for major physiological transitions. Environmental changes associated with these transitions can influence health behaviour and health (e.g. poor diet, high body weight and elevated blood pressure (EBP)). Excess body weight can lead to EBP; however, little is known about this relationship among young adults in developing countries. Focusing on Bangladesh, this study assessed the association between BMI and blood pressure (BP) metrics (systolic BP (SBP), diastolic BP (DBP) and BP class (optimal, normal/high normal and elevated)). Sex-specific analyses of these relationships were performed to assess any difference across sexes. Furthermore, associations of overweight/obesity with BP metrics were investigated. Young adults aged 18-24 years ( n 2181) were included from nationally representative cross-sectional Bangladesh Demographic and Health Survey 2017-2018. Multivariable linear and multinomial logistic regression models examined the relationships between BMI, overweight/obesity and BP metrics. Findings reveal that higher BMI was associated with higher SBP (0·83; 95 % CI 0·67, 0·99), DBP (0·66; 95 % CI 0·54, 0·74) and higher odds of having EBP (adjusted OR 1·24; 95 % CI 1·17, 1·31). These relationships were stronger among males than females. Moreover, overweight/obese individuals had higher SBP, DBP and higher odds of having EBP than individuals with normal BMI. Strategies to reduce body weight and to improve healthy lifestyle, and awareness and monitoring of BP may help to address these serious health problems, particularly at an early age.

Objectives: Despite a significant decline over time, maternal mortality remains high in Bangladesh. Institutional delivery during childbirth is crucial to reducing maternal mortality, but uptake of institutional delivery services (IDS) remains suboptimal in Bangladesh. Though women's education plays a crucial role in the use of IDS, the educational status of the household head and area-level literacy rate also appear to act as predictors of IDS uptake. This study aims to assess the effect of the educational status of women and household heads as well as district-level adult literacy rates on the use of IDS during childbirth among women in Bangladesh., Design: This study analyzed nationally representative cross-sectional survey data from the 2019 Bangladesh Multiple Indicator Cluster Survey., Setting: Bangladesh., Participants: 9,207 currently married women aged 15-49 years who had at least one live birth in the two years preceding the survey were included in the study. The outcome measure was women's use of IDS during their last childbirth. A multilevel logistic regression model was used to explore the association between education status of women and household heads, and district (i.e., area unit) adult literacy rates and uptake of IDS among women in Bangladesh by controlling for other sociodemographic covariates and clustering., Results: About 53% of women used IDS during childbirth. Adjusting for other factors and clustering, women with higher educational status, those living in households with higher-educated heads, and those in districts with greater adult literacy rates are more likely to use IDS, after controlling for key sociodemographic variables including wealth., Conclusions: Uptake of IDS in Bangladesh remains low, with education playing an important independent role in determining rates. The findings of the study provide empirical evidence for policymakers to design multi-modal educational programs targeted not only at literate women but also at household head (especially male) and communities where literacy (and equally importantly health literacy) may be variable or absent., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests., (Copyright © 2022. Published by Elsevier Ltd.)

Child undernutrition and natural disasters are major public health concerns in Bangladesh, but research into their relationship is lacking. This study assessed the association between residential district multi-hazard-risk and undernutrition among children aged less than 5 years (under-5) in Bangladesh. Data for 22,055 under-5 children were extracted from the 2019 Multiple Indicator Cluster Survey of Bangladesh. Multi-hazard risk was categorized as low (score<10), moderate (score 10-20), and high (score>20) using a combined score of four major hazards: tornado, cyclone, earthquake, and flood. We found that children from high multi-hazard risk districts were 19% more likely to be stunted and 23% more likely to be underweight compared to low-risk districts. However, wasting was not associated with multi-hazard risk. Strategies such as agricultural adaptation and coping mechanisms, long-term post-disaster nutritional response, extended periods of relief supports, and enhanced quality maternal and child care services may help to reduce undernutrition burdens in Bangladesh.

Faecal contamination (by Escherichia coli [E. coli]) of household drinking water can have adverse effects on child health, particularly increasing the episodes of childhood diarrhea; however, the evidence is scanty in Bangladesh. This study utilised data from the most recent nationally representative 2019 Multiple Indicator Cluster Survey to investigate the relationship between E. coli concentration in household drinking water and diarrheal episodes among children aged under-5 years in Bangladesh. Childhood diarrhea was identified by asking the children's mothers or caregivers if they had a diarrheal episode in the 2 weeks preceding the survey. E. coli colonies were counted as colony-forming units (CFUs) per 100 ml of water and classified into three risk groups (low: < 1 CFU/100 ml; moderate: 1-10 CFU/100 ml; and high: > 10 CFU/100 ml). The design-adjusted logistic regression was used to estimate the association between drinking water E. coli risk groups and childhood diarrhea, adjusting for potential confounders. We observed a significant association between household drinking water E. coli contamination and diarrheal episodes among under-5 children. Compared to the children from households with a low risk of E. coli contamination in drinking water, children from households with a moderate risk of E. coli contamination were 1.68 times more likely to have diarrhea, which was 2.28 times among children from households with a high risk of E. coli contamination. Findings of the study have significant policy implications and urge to ensure safe water supplies, improve water management practices and modify hygiene behaviours to reduce episodes of childhood diarrhea., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Coastal morphology makes Bangladesh vulnerable to environmental hazards and climate change. Therefore, environmental characteristics may shape population health, including child health. The prevalence of stunting among under-five aged (U5) children is high in Bangladesh. However, there is a lack of research on environmental predictors of stunting. This study aimed to assess the association between community-level environmental characteristics and stunting using pooled data from the three latest Bangladesh demographic and health surveys (BDHS). According to the multilevel model, rainfall, distance to protected areas, and vegetation index showed a nonlinear association with stunting. The temperature was inversely, and distance to water bodies was positively related to stunting. Overall, results evidence the environmental characteristics are predictive of stunting, and these characteristics should be taken into account during intervention design to minimise the negative effects of environmental change on child health. Further research is also necessary to comprehend the causal pathways between environmental characteristics and stunting in Bangladesh.

Number of children ever born to women of reproductive age forms a core component of fertility and is vital to the population dynamics in any country. Using Bangladesh Multiple Indicator Cluster Survey 2019 data, we fitted a novel weighted Bayesian Poisson regression model to identify multi-level individual, household, regional and societal factors of the number of children ever born among married women of reproductive age in Bangladesh. We explored the robustness of our results using multiple prior distributions, and presented the Metropolis algorithm for posterior realizations. The method is compared with regular Bayesian Poisson regression model using a Weighted Bayesian Information Criterion. Factors identified emphasize the need to revisit and strengthen the existing fertility-reduction programs and policies in Bangladesh., Supplementary Information: The online version contains supplementary material available at 10.1007/s44199-022-00044-2., Competing Interests: Conflict of InterestThe authors declare no potential conflict of interests., (© The Author(s) 2022.)

Childhood stunting is a serious public health concern in Bangladesh. Earlier research used conventional statistical methods to identify the risk factors of stunting, and very little is known about the applications and usefulness of machine learning (ML) methods that can identify the risk factors of various health conditions based on complex data. This research evaluates the performance of ML methods in predicting stunting among under-5 aged children using 2014 Bangladesh Demographic and Health Survey data. Besides, this paper identifies variables which are important to predict stunting in Bangladesh. Among the selected ML methods, gradient boosting provides the smallest misclassification error in predicting stunting, followed by random forests, support vector machines, classification tree and logistic regression with forward-stepwise selection. The top 10 important variables (in order of importance) that better predict childhood stunting in Bangladesh are child age, wealth index, maternal education, preceding birth interval, paternal education, division, household size, maternal age at first birth, maternal nutritional status, and parental age. Our study shows that ML can support the building of prediction models and emphasizes on the demographic, socioeconomic, nutritional and environmental factors to understand stunting in Bangladesh.

Breast cancer screening (BCS) participation rates are often suboptimal and vary geographically. Environmental features may influence BCS participation, but few studies have assessed this relationship. This study assessed the associations between BCS participation, residential area sociodemographic characteristics, distance to BCS venue, and venue location attributes. Data for 384,433 women residing in Greater Sydney, Australia, invited to BCS during 2011-2014 were spatially joined to their state suburb (SSC) (n = 800). SSC sociodemographic measures included women's median age, proportion women speaking English at home, full-time employed, and university educated; and proportion dwellings with motor-vehicles. Road network distance was calculated to each BCS venue. BCS venues were coded as co-located with bus-stop, train-station, hospital, general practitioner (GP), and shop. Hot spots were calculated to quantify spatial clustering of BCS participation. Multilevel logistic models were used to estimate the associations between environmental predictors and BCS participation, accounting for SSC-level clustering. BCS participation was 53.9% and spatially clustered. BCS was positively associated with SSC-level median age for women, proportions women speaking English and university educated, and dwellings with motor-vehicles. Distance to venue was inversely associated with BCS. Venue co-location with GP was positively associated and co-location with bus-stop, train-station, and shop, hospital were negatively associated with BCS. Residential sociodemographic features, geographic access, and venue location attributes are associated with BCS participation. These findings implicate the relevance of social and built environmental factors to programmatic aims to raise BCS participation. Additional research on venue location features is required to understand where best to site BCS venues., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Household air pollution from cooking fuel may have adverse health effects, particularly among women from countries like Bangladesh, where women participate in most household cooking activities. However, little is known about how cooking fuel influences adult women's blood pressure (BP) status in Bangladesh. This study assessed the association between household cooking fuel and women's BP in Bangladesh. Data of 6543 women (aged ≥18 years) from the latest nationally representative Bangladesh Demographic and health survey 2017-18 were used in this study. This survey collected data on various variables, including women's BP and cooking fuel. Multivariable regression models were used for this evaluation. About 82.3% of women were living in households using solid cooking fuel. Women's average systolic BP (SBP) and diastolic BP (DBP) were 121.5 mmHg and 80.7 mmHg, respectively, and 25% had elevated BP. Women residing in a household using solid fuel had significantly higher SBP (β 3.76 mmHg, 95 confidence interval (CI) 2.00, 5.51) and DBP (β 1.17 mmHg, 95% CI 0.17, 2.18) relative to women from households using clean fuel. The odds of elevated BP was 58% higher (adjusted odds ratio, 1.58, 95% CI 1.19, 2.11) among women residing in households using solid fuels compared to their counterparts. Usage of solid cooking fuel was predominantly high and negatively impacted women's BP status in Bangladesh. In addition to other lifestyle change interventions, improved cooking facilities and clean cooking fuel provision and monitoring could be important initiatives to reduce the burden of elevated BP among women., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Understanding environmental predictors of women's use of closest breast screening venue versus other site(s) may assist optimal venue placement. This study assessed relationships between residential-area sociodemographic measures, venue location features, and women's use of closest versus other venues. Data of 320,672 Greater Sydney screening attendees were spatially joined to residential state suburbs (SSCs) ( n = 799). SSC-level sociodemographic measures included proportions of: women speaking English at home; university-educated; full-time employed; and dwellings with motor-vehicles. A geographic information system identified each woman's closest venue to home, and venue co-location with bus-stop, train-station, hospital, general practitioner, and shop(s). Multilevel logistic models estimated associations between environmental measures and closest venue attendance. Attendance at closest venue was 59.4%. Closest venue attendance was positively associated with SSC-level women speaking English but inversely associated with SSC-level women university-educated, full-time employed, and dwellings with motor-vehicles. Mobile venue co-location with general practitioner and shop was positively, but co-location with bus-stop and hospital was inversely associated with attendance. Attendance was positively associated with fixed venue co-location with train-station and hospital but inversely associated with venue co-location with bus-stop, general practitioner, and shop. Program planners should consider these features when optimising service locations to enhance utilisation. Some counterintuitive results necessitate additional investigation.

Background and Aims: The coexistence of undernutrition and overnutrition creates a double burden of malnutrition (DBM) among women in Bangladesh. This study aimed to assess heterogeneous effects of sociodemographic factors on women's nutritional status using quantile regression (QR) models and to investigate the differences between the results of unconditional QR (UQR) and conditional QR (CQR) models., Methods: A sample of 17 285 nonpregnant women aged 15 to 49 years was extracted from the latest Bangladesh Demographic and Health Survey, 2017-2018. Women's nutritional status was determined using body mass index (BMI). The UQR and CQR were used to estimate the heterogeneous effects of sociodemographic factors on women's BMI., Results: Results show that the estimated effects of sociodemographic factors varied across the BMI distribution. For the same quantile, the effects differed between UQR and CQR. For instance, education was significantly positively associated with BMI. In UQR, secondary educated women achieved an increase of 0.996 and 1.720 in BMI at 10th and 90th quantiles, respectively, compared to noneducated women, whereas conditional effects were 1.336 and 1.492 at 10th and 90th quantiles, respectively, in CQR. These results also indicate secondary education appeared to have a lesser (or higher) impact in the lower (or upper) tail of BMI distribution, and unconditional and conditional effects for the same quantile varied notably. Other factors such as women's age, occupation, household wealth, number of children ever born and household size, religion, and place of residence were significantly associated with BMI and showed heterogeneous effects., Conclusion: Overall, there is a need to focus on heterogeneous effects of factors on women's nutritional status. Patterns of unconditional heterogeneous effects would be more informative than conditional heterogeneous effects while studying factors' effects. These findings may aid in developing strategies targeting high-risk groups to combat the double burden of malnutrition., Competing Interests: The authors have no conflict of interest to declare., (© 2021 The Authors. Health Science Reports published by Wiley Periodicals LLC.)

Residential area greenness may influence diabetes, but limited studies have explored this relationship in developing countries. This study assessed the association between residential area greenness and diabetes among urban adults in Bangladesh. The mediation effect of the body mass index (BMI) was also assessed. A total of 2367 adults aged ≥ 35 years were extracted from a nationally representative survey. Diabetes was characterised as fasting plasma glucose level be ≥ 7.0 mmol/L or taking prescribed medications to reduce blood sugar level. Residential area greenness was estimated by enhanced vegetation index. Binary logistic regression models were employed to estimate the association between residential area greenness and diabetes adjusting for sociodemographic factors. Mediation analysis was performed to assess whether BMI mediated the association between greenness and diabetes. Greater area greenness was associated with lower odds of diabetes (adjusted odds ratio 0.805, 95% confidence interval 0.693-0.935, p = 0.0052). BMI significantly mediated 36.4% of the estimated association between greenness and diabetes. Presence of areas of greenness adjacent to living area tends to be associated with lower diabetes prevalence. Findings emphasised the importance of preserving the local environment to tackle the growing diabetes prevalence in Bangladesh., (© 2021. The Author(s).)

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. Determining the degree to which comorbidities are associated with severe symptoms and mortality would thus greatly assist in COVID-19 care planning and provision. To assess this we performed a meta-analysis of published global literature, and machine learning predictive analysis using an aggregated COVID-19 global dataset. Our meta-analysis suggested that chronic obstructive pulmonary disease (COPD), cerebrovascular disease (CEVD), cardiovascular disease (CVD), type 2 diabetes, malignancy, and hypertension as most significantly associated with COVID-19 severity in the current published literature. Machine learning classification using novel aggregated cohort data similarly found COPD, CVD, CKD, type 2 diabetes, malignancy, and hypertension, as well as asthma, as the most significant features for classifying those deceased versus those who survived COVID-19. While age and gender were the most significant predictors of mortality, in terms of symptom-comorbidity combinations, it was observed that Pneumonia-Hypertension, Pneumonia-Diabetes, and Acute Respiratory Distress Syndrome (ARDS)-Hypertension showed the most significant associations with COVID-19 mortality. These results highlight the patient cohorts most likely to be at risk of COVID-19-related severe morbidity and mortality, which have implications for prioritization of hospital resources.

Aims: Overweight and obesity (OWOB) is a modifiable risk factor for both hypertension and diabetes. However, the association between OWOB and diabetes among Bangladeshi adults and how hypertension may mediate this relationship are not well explored. This study aimed to examine (1) whether OWOB is independently associated with diabetes among Bangladeshi adults, (2) whether this association is mediated by hypertension, and (3) the effect modification by wealth status and place of residence in the relationships., Research Design and Methods: We used data of 9305 adults aged ≥18 years from the most recent nationally representative cross-sectional study of Bangladesh Demographic and Health Survey 2017-2018. Design-based logistic regression was used to assess the association between OWOB and diabetes, and counterfactual framework-based weighting approach was used to evaluate the mediation effect of hypertension in the OWOB-diabetes relationship. We used stratified analyses for the effect modifications., Results: The prevalence of OWOB, diabetes and hypertension was 48.5%, 11.7% and 30.3%, respectively. We observed a significant association between OWOB and diabetes and a mediating role of hypertension in the OWOB-diabetes association. The odds of diabetes was 51% higher among adults with OWOB than those without OWOB (adjusted OR: 1.51, 95% CI 1.29 to 1.77). We observed that 18.64% (95% CI 9.84% to 34.07%) of the total effect of OWOB on the higher odds of diabetes was mediated through hypertension, and the mediation effect was higher among adults from non-poor households and from both rural and urban areas., Conclusions: Adult OWOB status is independently associated with diabetes in Bangladesh, and hypertension mediates this association. Therefore, prevention policies should target adults with both OWOB and hypertension, particularly those from non-poor households and from both rural and urban areas, to reduce the growing burden of diabetes and its associated risk., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: Participation in breast cancer screening (BCS) varies at the small-area level, which may reflect environmental influences. This study assessed small-area variation in BCS invitation response rates (IRRs) and associations between small-area BCS IRR, sociodemographic factors, BCS venue distance and venue location features in Greater Sydney, Australia., Methods: BCS IRR data for 2011-2012 were compiled for 9528 Australian Bureau of Statistics Statistical Area Level 1 (SA1) units (n=227 474 women). A geographial information system was used to extract SA1-level sociodemographic features (proportions of women speaking English at home, full-time employed and university educated, and proportion of dwellings with motor vehicles), SA1-level distance to closest venue(s) (expressed as quartiles), and closest venue(s) colocated with bus stops, train station, hospital, general practitioner and shops. Associations between area-level features, BCS venue distance, venue location features and IRR were estimated using ordinary least square-type spatial lag models including area education as a covariate., Results: BCS IRR varied across SA1s (mean=59.8%, range: 0%-100%), with notable spatial autocorrelation (Moran's I=0.803). BCS IRR was positively associated with greater SA1-level proportion of women speaking English at home (β=2.283, 95% CI 2.024 to 2.543), women's education (in the model including speaking English at home β=0.454, 95% CI 0.211 to 0.697), dwellings with motor vehicles (β=1.836, 95% CI 1.594 to 2.078), greater distance to venue (eg, most distant quartile compared with closest: β=6.249, 95% CI 5.489 to 7.008), and BCS venue colocated with shops (β=0.762, 95% CI 0.273 to 1.251). Greater SA1-level women employment (β=-0.613, 95% CI -0.898 to -0.328) and venue colocated with train station (β=-1.889, 95% CI -2.376 to -1.402) or hospital (β=-0.677, 95% CI -1.164 to -0.189) were inversely related to BCS IRR., Conclusions: Small-area variation in BCS IRR exists for Greater Sydney and is strongly related to sociodemographic factors that, together with BCS venue location features, could inform targeted attempts to improve IRR., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The rapid growth in cases of COVID-19 has challenged national healthcare capacity, testing systems at an advanced ICU, and public health infrastructure level. This global study evaluates the association between multi-factorial healthcare capacity and case fatality of COVID-19 patients by adjusting for demographic, health expenditure, population density, and prior burden of non-communicable disease. It also explores the impact of government relationships with civil society as a predictor of infection and mortality rates. Methods: Data were extracted from the Johns Hopkins University database, World Bank records and the National Civic Space Ratings 2020 database. This study used data from 86 countries which had at least 1,000 confirmed cases on 30th April 2020. Negative binomial regression model was used to assess the association between case fatality (a ratio of total number of confirmed deaths to total number of confirmed cases) and healthcare capacity index adjusting for other covariates. Findings: Regression analysis shows that greater healthcare capacity was related to lesser case-fatality [incidence rate ratio (IRR) 0.5811; 95% confidence interval (CI) 0.4727-0.7184; p < 0.001] with every additional unit increase in the healthcare capacity index associated with a 42% decrease in the case fatality. Health expenditure and civil society variables did not reach statistical significance but were positively associated with case fatalities. Interpretation: Based on preliminary data, this research suggests that building effective multidimensional healthcare capacity is the most promising means to mitigate future case fatalities. The data also suggests that government's ability to implement public health measures to a degree determines mortality outcomes., (Copyright © 2020 Khan, Awan, Islam and Muurlink.)

Reducing the mortality of children under-5 (U5) is an essential part of the Sustainable Development Goal (SDG). Although Bangladesh has made progress in reducing child mortality, there remain inequalities among different sociodemographic groups. Education is one particular key factor with a multidimensional impact on child health and survival. This study assessed the association between parental education and U5 mortality using repeated cross-sectional Bangladesh Demographic and Health Survey data. The risk of child death was substantially low among educated parents. Children of secondary or higher educated mother and father were about 30% (hazard ratio [HR] = 0.697, 95% confidence interval [CI] 0.596 to 0.815, p < .001) and 26% (HR = 0.738, 95% CI 0.635 to 0.858, p < .001), respectively, less likely to die early. Children from wealthier households and born to mothers with long birth spacings were less likely to face an early death. The study findings emphasize on imparting education to parents as an intervention strategy to continue the reduction of child mortality rate in Bangladesh, which could be a policy direction toward achieving the SDGs.

The Escherichia coli ( E. coli ) contamination in the household (HH) drinking water is often a public health concern. Very few studies explore the associated factors and spatial risk modeling together for E. coli contamination in Bangladesh, this research gap motivates to explore this fact further by utilizing Bangladesh Multiple Indicator Cluster Survey (MICS) 2012-13 data. A Bayesian spatial ordered logit model was used to examine the associated factors and spatial risks of the E. coli contamination. The results show that 62% of HH water samples were contaminated with E. coli . After controlling for different factors, a high level of E. coli contamination was observed among HHs who had access to non-improved water sources. Moreover, no significant rural-urban difference was observed. The spatial prediction of the high-risk contamination was prominent in districts like Dhaka and Bandarban. The study findings can provide insights into the planning of policy activities in Bangladesh.