University of Chicago Research Bangladesh

Heavy metals, including chromium (Cr), cadmium (Cd), lead (Pb), nickel (Ni), and arsenic (As), are pervasive environmental pollutants that accumulate in human lung tissue through inhalation from sources such as smoking, industrial emissions, and ambient air pollution. This systematic review synthesizes evidence on metal concentrations in lung tissues across diverse human populations and their associations with respiratory diseases. To systematically review and synthesize data from studies conducted between 1975 and 2025 on the concentrations of heavy metals in human lung tissues, their sources of exposure, and associated health implications. Adhering to PRISMA guidelines, a comprehensive search was conducted across databases including PubMed, Scopus, Web of Science, and Embase, utilizing keywords related to heavy metals and lung tissue. Inclusion criteria encompassed human studies reporting quantifiable metal concentrations and health outcomes. Two independent reviewers screened titles, abstracts, and full texts, with data extracted on population characteristics, metal concentrations, key findings, and study quality. From an initial pool of 1,256 records, 39 studies were included after excluding duplicates, animal studies, and those not meeting quality thresholds (32 human epidemiological/autopsy studies and 7 in vitro studies using human cell lines). Elevated levels of Cd and Pb were strongly associated with smoking and impaired lung function, including chronic obstructive pulmonary disease (COPD) with a pooled odds ratio from meta-analysis of 2.85 (95% CI: 1.34–6.10) for Cd (highest vs. lowest exposure quartile) and 1.73 (95% CI: 1.37–2.18) for Pb. Chromium and Ni exhibited significant correlations with occupational exposures and inflammatory responses. Combined metal exposures demonstrated amplified health risks. The accumulation of heavy metals in lung tissue contributes significantly to respiratory morbidity. Mitigation strategies, including regulatory measures and smoking cessation initiatives, are imperative. Further longitudinal research on the effects of mixed-metal exposures is warranted.

Background: Antibiotic resistance is a growing global health threat, causing treatment failures and increased healthcare costs. Objective: This study was aimed to investigate the knowledge, attitudes, and practices (KAP) surrounding antibiotic use among the general population of Dhaka city. Methodology: The cross-sectional descriptive study was conducted at the epidemiology department of the State University of Bangladesh, Dhaka, Bangladesh from July to December 2013 for a period of 6 months. They are above 18 years old; they are aware of the term "antibiotics". Participants were excluded if he/she refused to participate in the study and the participants who were unable to provide information due to physical or mental illness. Three selected wards in Dhaka city were included in this study, with a total sample size of 120. A self-administered pre-tested questionnaire prepared in English was used for data collection. Data were presented as mean ± SD, with prevalence rates as percentages. Tests of significance and cross-tabulation were used to determine the relation between socio-demographic characteristics and antibiotic use. Results: The study revealed that among the respondents, 68(56.7%) used antibiotics without a doctor’s prescription (self-medication). In this study, a total of 112(93.33%) respondents used antibiotics, while only 8(6.67%) did not use antibiotics. 32(47.1%) respondents selected antibiotics from a previous doctor’s prescription, and 30(44.1%) based their choice on the community pharmacist’s recommendation. Among the respondents, 85(71.4%) used antibiotics due to fever, 47(39.5%) due to cough, 39(32.8%) due to diarrhea, and 37(31.1%) due to aches and pains. Out of the 120 respondents, the majority, about 72(60%), had poor knowledge, followed by 40(33.3%) who had satisfactory knowledge, and only 8(6.7%) who had good knowledge. A statistically significant association was found between self-medication and the level of knowledge (P-value <0.05), level of attitude (P<0.05), and level of education (P<0.05), underscoring the profound impact of these factors on antibiotic use. Conclusion: In conclusion self-medication with antibiotics is prevalent among the general public in Dhaka city. We need to implement a robust educational program to increase awareness about the negative impacts of using antibiotics without a doctor's prescription. Bangladesh Journal of Infectious Diseases, June 2025;12(1):69-77

Postpartum care is a critical component of maternal health, as it helps prevent complications and ensures the well-being of both mother and newborn. Despite global improvements in maternal healthcare, disparities in postpartum care utilization remain a significant public health concern, particularly in low- and middle-income countries such as Bangladesh. This study aimed to examine the impact of caesarean section and place of delivery on the utilization of postpartum care among women in Bangladesh. A cross-sectional study was conducted using nationally representative survey data, analyzing women who had delivered at health facilities. Univariate analysis described the distribution of sociodemographic characteristics and delivery-related factors, while bivariate analysis employed Chi-square tests to examine associations between independent variables and postpartum care utilization. Multivariate analysis using binary logistic regression assessed the adjusted impact of caesarean section, place of delivery, prenatal care, and household wealth on postpartum care uptake. The results revealed that women who delivered by non-caesarean section were 55% less likely to utilize postpartum care compared to those delivered via caesarean section. Women who delivered at private health facilities were 1.22 times more likely to utilize postpartum care than those at public facilities. Not receiving prenatal care decreased the probability of postpartum care by 55%, while women from the fourth wealth quintile and richest households were 1.58 and 2.60 times more likely, respectively, to access postpartum services compared to the poorest households. These findings underscore the importance of promoting equitable access to postpartum care, particularly for women delivering vaginally, at public facilities, or from lower-income households. Targeted policies that train providers in standardized postpartum care, strengthen follow-up through digital reminders and community health workers, and expand access in underserved areas can reduce disparities and improve maternal health outcomes in Bangladesh.

There is conflicting research regarding the negative effects of electronic gaming and addictive social media use on psychological disorders and academic achievement. Therefore, we aimed to examine the association between social media use and electronic gaming addiction with depression and academic achievement. This investigation is cross-sectional. The selection process involved 800 adolescents enrolled in grades 9 and 10 across four public and private high schools in the Rajshahi City Corporation. The outcomes of interest were depression and academic performance. Addiction to playing electronic games and using social media (mainly Facebook) were exposure of interest. From the total sample, 9.3% and 28.3% reported that they were addicted to electronic games and social media use. The mean scores for depression and academic achievement were 10.2 and 3.2, respectively. For one unit increase in depression scores, the odds of addiction to playing electronic games and using social media increase by a factor of 1.14 and 1.12. Additionally, it was found that for one unit an increase in academic performance scores, the odds of addiction to playing electronic games and using social media decrease by a factor of 0.67 and 0.71. Adolescents who are more likely to engage in addictive behaviors such as playing electronic games or using social media should be the focus of public health initiatives, as they are more susceptible to depression along with poor academic accomplishment.

Telomere length is associated with chronic diseases and, in younger populations, may represent a biomarker of disease susceptibility. As growing evidence suggests that environmental factors, including metals, may impact telomere length. We investigated the association between 17 metals measured in toenail samples and leukocyte relative telomere length (RTL), among 472 5- to 7-year-old children enrolled in the Bangladesh Environmental Research in Children's Health (BiRCH) cohortIn single-exposure linear regression models, a doubling of arsenic (As) and mercury (Hg) (μg/g) were associated with a -0.21 (95% CI, -0.032 to -0.010; P=.0005) and -0.017 (95% CI, -0.029 to -0.004; P=.006) difference in RTL, respectively. In Bayesian Kernel Machine Regression (BKMR) mixture models, the overall metal mixture was inversely associated with RTL (P-for-trend < 0.001). Negative associations with RTL were observed with both log2-As and log2-Hg, while an inverted U-shaped association was observed for log2-zinc (Zn) with RTL. We found little evidence of interaction among metals. Sex-stratification identified stronger associations of the overall mixture and log2-As with RTL among females compared to males. Our study suggests that As and Hg may independently influence RTL in mid-childhood. Further studies are needed to investigate potential long-term impacts of metal-associated telomere shortening in childhood on health outcomes in adult life.

Exposure to inorganic arsenic (As) is recognized as a risk factor for non-melanoma skin cancer (NMSC). We followed up with 7000 adults for 6 years who were exposed to As. During follow-up, 2.2% of the males and 1.3% of the females developed basal cell carcinoma (BCC), while 0.4% of the male and 0.2% of the female participants developed squamous cell carcinoma (SCC). Using a panel of more than 400 cancer-related genes, we detected somatic mutations (SMs) in the first 32 NMSC samples (BCC = 26 and SCC = 6) by comparing paired (tissue-blood) samples from the same individual and then comparing them to the SM in healthy skin tissue from 16 participants. We identified (a) a list of NMSC-associated SMs, (b) SMs present in both NMSC and healthy skin, and (c) SMs found only in healthy skin. We also demonstrate that the presence of non-synonymous SMs in the top mutated genes (like PTCH1, NOTCH1, SYNE1, PKHD1 in BCC and TP53 in SCC) significantly affects the magnitude of differential expressions of major genes and gene pathways (basal cell carcinoma pathways, NOTCH signaling, IL-17 signaling, p53 signaling, Wnt signaling pathway). These findings may help select groups of patients for targeted therapy, like hedgehog signaling inhibitors, IL17 inhibitors, etc., in the future.

Background: Realizing the patients’ need and improving the quality of services, a satisfaction survey can effectively help management and the patient. The aim of this study was to investigate satisfaction level of multi-drug resistant tuberculosis (MDRTB) patients at tertiary level hospital in Bangladesh. Methods: A cross-sectional study conducted at Chest Disease Hospital (CDH), Rajshahi among 199 MDR-TB patients using random sampling technique. A semi-structured questionnaire was used to collect basic, socio-demographic, behavioral and satisfaction specific data with ensuring no any risk for providing right information. Five point “Likert Scale” was used to measure patients’ satisfaction level. The relevant data were carefully coded and recoded for statistical analysis, and independent samples t-test and multinomial logistic regression analysis were used to see the difference and association of influencing factors on satisfaction. Results: In this study, we observed that the mean age of MDR-TB patient admitted at CDH was 39.8 years with range from 16 to 62 years. About 90% patients were satisfied with behavior of care providers, and 50% and 29% patients were satisfied in hospital environment and supplied food respectively. We also found that old age group, male, less educated, smoker, diabetic, married, high income and less expenditure group, business or service holder and Muslim were more satisfied than their counterparts. The multinomial logistic regression analysis showed that young age group (≤40 years) was five times more dissatisfied than old age group (≥40 years) (OR=5.345; 95% CI: 1.123-25.448; p&lt;0.05). Receiving monthly money from the program positively impacted on satisfaction. Similarly, drug toxicity, length of stay and loneliness was negatively impacted on satisfaction. Conclusion: Considering the mentioned influencing factors can strengthen the national control program effort at CDH in Rajshahi division, Bangladesh. Similar study in other chest disease hospitals located mostly in different divisions in the country can also help comparing the factors for nationwide improvement.

An accident is the cry of a lifetime. The role of traffic signs is most important in preventing or mitigating accidents. In many cases, while driving, traffic signs are not visible in the conventional approach; if traffic sign detection and recognition can alert the driver of important sign guidance ahead, it will help in accident mitigation. Traffic sign recognition plays a monumental role in expert systems, such as traffic assistance driving systems and automatic driving systems. The prime purpose of this paper is to design and identify a computer-based system that can spontaneously detect the direction of a road sign. For this research work, we have created our own dataset, which is called the Bangladeshi Traffic Sign Recognition Benchmark (BTSRB) dataset. The dataset, BTSRB, was created by capturing images from different angles and under different parameters and conditions. A total of 7320 images were collected to create this comprehensive database. This dataset called BTSRB all the images collected from Bangladesh. In this paper, we used five different types of models (CNN, Inception V3, MobileNetV2, ResNet50, and VGG16), which are pre-trained on the ImageNet dataset. Later, we finetuned the pre-trained model and used transfer learning. The main challenge of this research is collecting datasets from a country like Bangladesh, where no recognized dataset is available. When compared to another model, the accuracy of this model is greater than 91%. This paper emphasizes the significance of traffic sign recognition in expert systems and the necessity for a well-established dataset in nations where such resources are not readily available.

Abstract Though large amounts of work with artificial intelligence are used in typhoon rainfall forecasting, the predictive skills of existing models are unsatisfactory. To address this problem, this study aims to propose an improved cluster‐wise typhoon rainfall forecasting model that integrates the grid‐search cross‐validation method with machine learning and deep learning (DL) models including support vector machine (SVM), random forest (RF), adaptive boosting (AdaBoost), convolutional neural network (CNN), and long short‐term memory (LSTM). Grid‐search cross‐validation is a modified parameterization technique that helps to find the best parameters for machine/DL models. In the first stage, a second‐order polynomial regression model was used to cluster the typhoon track; and in the second stage, cluster‐wise typhoon rainfall was recognized within a 500 km radius from each typhoon center. After that, a modified cluster‐wise typhoon rainfall forecasting model was proposed using cluster‐wise antecedent hourly typhoon rainfall within this distance for 1–6 hr lead time. Results show that the proposed model based on the SVM, RF, AdaBoost, CNN, and LSTM is capable of providing more accurate forecasts (the efficiency of the forecast is increased by 45%–90%) than the existing typhoon rainfall forecasting models that are based on SVM with a genetic algorithm, RF, artificial neural network, multilayer perceptron network, and deep neural network. Therefore, the current study recommends using cluster‐wise typhoon rainfall forecasting model with a grid‐search cross‐validation method for disaster prevention and mitigation.