Factors influencing delivery-related complications and their consequences in hard-to-reach areas of Bangladesh.

BACKGROUND AND OBJECTIVES: Bangladesh's high maternal mortality ratio is exacerbated by delivery-related complications, particularly in hard-to-reach (HtR) areas with limited healthcare access. Despite this, few studies have explored delivery-related complications and factors contributing to these complications among the disadvantaged population. This study aimed to investigate the factors contributing to delivery-related complications and their consequences among the mothers residing in the HtR areas of Bangladesh. METHODS: Data were collected using a cross-sectional study design from 13 HtR sub-districts of Bangladesh between September 2019 and October 2019. Data from 1,290 recently delivered mothers were analysed. RESULTS: Around 32% (95% CI: 29.7-34.8) of the mothers reported at least one delivery-related complication. Prolonged labour pain (21%) was the highest reported complication during the delivery, followed by obstructive labour (20%), fever (14%), severe headache (14%). Mothers with higher education, a higher number of antenatal care (ANC) visits, complications during ANC, employed, and first-time mothers had higher odds of reporting delivery-related complications. More than one-half (51%) of these mothers had normal vaginal delivery. Nearly one-fifth (20%) of mothers who reported delivery-related complications were delivered by unskilled health workers at homes. On the other hand, about one-fifth (19%) of the mothers without any complications during delivery had a caesarean delivery. Nine out of ten of these caesarean deliveries were done at the private facilities. CONCLUSION: Delivery-related complications are significantly related to a woman's reproductive history and other background characteristics. Unnecessary caesarean delivery is prominent at private facilities.

Trends and inequity in improved sanitation facility utilisation in Bangladesh: Evidence from Bangladesh Demographic and Health Surveys.

Improved sanitation is indispensable to human health. However, lack of access to improved sanitation remains one of the most daunting public health challenges of the twenty-first century in Bangladesh. The aim of the study was to describe the trends in access to improved sanitation facilities following the inequity gap among households in different socioeconomic groups in Bangladesh. Data from the Bangladesh Demographic and Health Survey (BDHS) 2007, 2011, 2014, and 2017-18 were extracted for this study. Inequity in access to improved sanitation was calculated using rich-poor ratio and concentration index to determine the changes in inequity across the time period. In Bangladesh, the proportion of households with access to improved sanitation increased steadily from 25.4% to 45.4% between 2007 and 2014, but slightly decreased to 44.0% in 2017-18. Age, educational status, marital status of household head, household wealth index, household size, place of residence, division, and survey year were significantly associated with the utilisation of improved sanitation. There is a pro-rich situation, which means that utilisation of improved sanitation was more concentrated among the rich across all survey years (Concentration Index ranges: 0.40 to 0.27). The government and other relevant stakeholders should take initiatives considering inequity among different socioeconomic groups to ensure the use of improved sanitation facilities for all, hence achieving universal health coverage.

Contribution of socio-economic and demographic factors to maternal and child malnutrition in Bangladesh: Insights from a nationwide survey.

Background: Malnutrition is a major global public health issue, especially for under five children and their mothers. Objective: This study examined the relationships between socio-economic and demographic characteristics and under- and over-nutrition in mothers and children of Bangladesh. Method: Using the Nationally representative Bangladesh Demographic and Health Survey (2017-18) data, we performed the multiple logistic regression analysis to assess the relationships between key outcome variables and predictors. The analysis included 8321 children aged 0-59 months and 7800 mothers aged 15-49 years. Findings: The prevalence of stunting, wasting, and overweight among children under five was 30.72%, 8.44%, and 2.21% respectively. About 2.74% of the children were both stunted and wasted, while 0.56% of the children were both stunted and overweight. The prevalence of underweight and overweight among mother was 14.09% and 26.35% respectively. Children who are stunted are significantly associated with the mother's BMI status, mothers' education, fathers' education, and wealth index, while children who are wasted are significantly associated with the mother's BMI status and the child's sex. A child's sex and birth order are significantly associated with children being overweight. Mother's age, mother's education, father's education, place of residence and wealth index are significant determinants for mothers being underweight, whereas mother's age, mother's occupation, father's education, father's occupation, place of residence and wealth index are significant determinants for mothers being overweight. Conclusion: In addition to essential nutrition interventions, it is vital to address the basic social-economic and demographic determinants.

Effect of an integrated maternal and neonatal health intervention on maternal healthcare utilisation addressing inequity in Rural Bangladesh.

BACKGROUND: Although Bangladesh has made significant improvements in maternal, neonatal, and child health, the disparity between rich and poor remains a matter of concern. OBJECTIVE: The study aimed to increase coverage of skilled maternal healthcare services while minimising the inequity gap among mothers in different socioeconomic groups. METHODS: We implemented an integrated maternal and neonatal health (MNH) intervention between 2009 and 2012, in Shahjadpur sub-district of Sirajganj district, Bangladesh. The study was quasi-experimental in design for the evaluation. Socioeconomic status was derived from household assets using principal component analysis. Inequity in maternal healthcare utilisation was calculated using rich-poor ratio and concentration index to determine the changes in inequity between the baseline and the endline time period. RESULT: The baseline and endline surveys included 3,158 (mean age 23.5 years) and 3,540 (mean age 24.3 years) recently delivered mothers respectively. Reduction in the rich-poor ratio was observed in the utilisation of skilled 4+ antenatal care (ANC) (2.4:1 to 1.1:1) and related concentration index decreased from 0.220 to 0.013 (p < 0.001). The rich-poor ratio for skilled childbirth reduced from 1.7:1 to 1.0:1 and the related concentration index declined from 0.161 to -0.021 (p < 0.001). A similar reduction was also observed in the utilisation of skilled postnatal care (PNC); where the rich-poor gap decreased from 2.5:1 to 1.0:1 and the related concentration index declined from 0.197 to -0.004 (p < 0.001). CONCLUSION: The MNH intervention was successful in reducing inequity in receiving skilled 4+ ANC, delivery, and PNC in rural Bangladesh.

Community-based integrated intervention for skilled maternal health care utilization in riverine remote areas, Bangladesh.

INTRODUCTION: Despite the decrease in maternal mortality ratio, many women in Bangladesh are still at high-risk of death due to pregnancy-related morbidities. Increasing the rate of skilled maternal healthcare service utilization is effective to reduce maternal mortality rate. This paper examines the intervention effect of an integrated community-based maternal healthcare project implemented by a non-government organization, Friendship, aiming to provide maternal health services to women living in the remote riverine regions of Bangladesh. METHODS: We examined the skilled maternal healthcare service utilization before and after project implementation of the mothers with birth experience of 0-6 months from the intervention (N = 1,304) and comparison areas (N = 1,304). A difference-in-differences logistic model measured the effect of the intervention. RESULTS: After the intervention, mothers were three times more likely to receive ≥ 4 ANC visits from skilled providers (AOR: 2.9; 95 % CI: 2.1-4.2), 1.5 times more likely to have skilled birth attendants during deliveries (AOR: 1.5; 95 % CI: 1.1-2.1) and 1.5 times more likely to seek at least one PNC within 42 days after delivery (AOR: 1.5; 95 % CI: 1.1-2.2) as compared to the comparison group. CONCLUSION: The intervention showed positive effect on improving the ANC coverage, skilled delivery, and PNC among the mothers residing the remote riverine areas. Therefore, it opens up the opportunity for adaptation of such integrated community and facility-based interventions by other LMICs.

A population-based serological survey of Vibrio cholerae antibody titers in Ouest Department, Haiti in the year prior to the 2022 cholera outbreak.

After three years with no confirmed cholera cases in Haiti, an outbreak of Vibrio cholerae O1 emerged in October 2022. Levels of pre-existing antibodies provide an estimate of prior immunologic exposure, reveal potentially relevant immune responses, and set a baseline for future serosurveillance. We analyzed dried blood spots collected in 2021 from a population-weighted representative cross-sectional serosurvey in two communes in the Ouest Department of Haiti. We found lower levels of circulating IgG and IgA antibodies against V. cholerae lipopolysaccharide (LPS, IgG and IgA p<0.0001) in those below 5 years of age compared to those five years and older. Among a subset of patients with higher titers of antibodies, we were unable to detect any functional (vibriocidal) antibodies. In conclusion, the lack of detectable functional antibodies, and age-discordant levels of V. cholerae LPS IgG, suggest that populations in Haiti may be highly susceptible to cholera disease, especially among young children.

Investigating problematic uses of Facebook and other Internet activities among university students in Bangladesh during the COVID-19 pandemic.

Problematic use of Internet (PUI) and problematic use of Facebook (PUF) has been linked to escalating behavioral health issues among university students and has increased during the COVID-19 pandemic. This study estimated the prevalence of and explored associated factors for PUI and PUF among Bangladeshi university students during the COVID-19 pandemic. A cross-sectional online survey was undertaken among 1101 Bangladeshi university students between November and December 2020. The Internet Addiction Test and Facebook Addiction Scale were used to assess PIU and PUF, respectively. A multiple linear regression analysis was performed to adjust for confounders. Among the participants, PUI and PUF were found in 39.3% and 37.1%, respectively. The multiple linear regression model indicated PUI was significantly associated with participants residing in a village, arts majors, those unsatisfied with their major, having mediocre parental relationships, failure in romantic relationships, physical comorbidities, longer use of the Internet, using the Internet for purposes other than education, using social media, and downloading movies/TV series. PUF was significantly associated with village residence, lower income, arts majors, failure in romantic relationships, longer use of the Internet, using the Internet for purposes other than education, and downloading movies/TV series. Both PUI and PUF have been prevalent among Bangladeshi university students during the COVID-19 pandemic. Longitudinal & exploratory studies are warranted in the future to identify causal factors for PUI and PUF and appropriate interventions should be designed quickly for this population.

Prevalence and associated factors of depression among Bangladeshi university students: A cross-sectional study.

Objective:  The study aimed to assess the prevalence of depression and its associated factors among university students in Bangladesh. Participants: A total of 403 undergraduate students from Patuakhali Science and Technology University, and Barisal University participated in the study. Method: A cross-sectional study was conducted using Beck's Depression Inventory (BDI). Result: The prevalence of depression (BDI ≥ 14) was 47.14%. Depression was 3.4 times (95% CI: 1.6-7.1), 3.8 times (95% CI: 1.7-8.6), and 3.9 times (95% CI: 1.5-8.9) higher among 2nd, 3rd, and 4th-year students, respectively than 1st-year students. Students with a history of stressful life events (aOR = 2.7, 95% CI: 1.7-4.4), suicidal attempts (aOR = 3.0, 95% CI: 1.2-7.9), and who received inadequate monthly allowance from their family (aOR = 0.53 95% CI: 0.3-0.9) were more likely to develop depressive symptoms. Conclusion: This study reports a high level of depression among university students which needs further discussion, exploration, and calls for designing appropriate interventions.

Detection of various lung diseases including COVID-19 using extreme learning machine algorithm based on the features extracted from a lightweight CNN architecture.

Around the world, several lung diseases such as pneumonia, cardiomegaly, and tuberculosis (TB) contribute to severe illness, hospitalization or even death, particularly for elderly and medically vulnerable patients. In the last few decades, several new types of lung-related diseases have taken the lives of millions of people, and COVID-19 has taken almost 6.27 million lives. To fight against lung diseases, timely and correct diagnosis with appropriate treatment is crucial in the current COVID-19 pandemic. In this study, an intelligent recognition system for seven lung diseases has been proposed based on machine learning (ML) techniques to aid the medical experts. Chest X-ray (CXR) images of lung diseases were collected from several publicly available databases. A lightweight convolutional neural network (CNN) has been used to extract characteristic features from the raw pixel values of the CXR images. The best feature subset has been identified using the Pearson Correlation Coefficient (PCC). Finally, the extreme learning machine (ELM) has been used to perform the classification task to assist faster learning and reduced computational complexity. The proposed CNN-PCC-ELM model achieved an accuracy of 96.22% with an Area Under Curve (AUC) of 99.48% for eight class classification. The outcomes from the proposed model demonstrated better performance than the existing state-of-the-art (SOTA) models in the case of COVID-19, pneumonia, and tuberculosis detection in both binary and multiclass classifications. For eight class classification, the proposed model achieved precision, recall and fi-score and ROC are 100%, 99%, 100% and 99.99% respectively for COVID-19 detection demonstrating its robustness. Therefore, the proposed model has overshadowed the existing pioneering models to accurately differentiate COVID-19 from the other lung diseases that can assist the medical physicians in treating the patient effectively.

Food addiction, orthorexia nervosa and dietary diversity among Bangladeshi university students: a large online survey during the COVID-19 pandemic.

PURPOSE: Maladaptive eating behaviors like food addiction (FA) are common among students, and orthorexia nervosa (ON) is being evaluated as a new condition among eating disorders (EDs). Moreover, dietary diversity (DD) is recognized as an important component of a healthy diet. Thus, the current study sought to examine the prevalence of ON and FA as well as the factors associated with ON, FA, and DD among university students in Bangladesh during the COVID-19 pandemic. METHODS: Four-thousand-and-seventy-six students were recruited and completed an online survey consisting of the Bratman Orthorexia test, the modified Yale Food Addiction Scale, and a questionnaire based on the Food and Agriculture Organizations' guidelines. Inferential statistics, bivariate and multivariable linear regression were used for analyzing data. RESULTS: ON and FA were observed in 1.7% and 7.5% of participants, respectively, with 43.8% exhibiting Health Fanatic eating attitude. The mean DD score was 5.96 (SD = 1.56). Students with ON consumed more legumes, nuts, seeds, and vegetables including dark green leafy vegetables whereas students with FA consumed more organ meats and eggs. Students who were older-aged, married, formerly smoked, had fitness goals, and had guilty feelings about violating food rules were more likely to have ON, whereas those who were female, were married, actively smoked, and were overweight and obese were more likely to have FA. CONCLUSIONS: The findings suggest that students from Bangladesh are at risk of FA, and less so for ON. These entities and low DD deserve more research attention in Bangladesh to increase awareness and ensure appropriate interventions.

Eating disorders, maladaptive eating behaviors, and low diversified diets are major public health issues amid the COVID-19 pandemic among university students. The current study aimed to address these issues by investigating Orthorexia Nervosa (ON), food addiction (FA), and dietary diversity. Four-thousand-and-seventy-six students completed an online questionnaire. It was found that being underweight was associated with ON. On the other hand, being overweight/obese was associated with having FA. Individuals who were former smokers and who had poor social interaction were significantly associated with having Orthorexia Nervosa. 1st-year university students are more likely to have FA compared to 5th-year/master's students. Active smokers were more likely to be food addicted. Students who had FA had less guilty feelings about violating food rules. Participants who had FA consumed more organ meats and eggs. Students who were from upper socio-economic status were more likely to have higher dietary diversity. Nutritional awareness programs focusing on DD and healthy eating habits should be implemented for students.

Nutritional and in vitro antioxidant activity analyses of formulated soymilk dessert.

Soymilk (SM) is nutritionally nearly equal to milk from cows and is free of cholesterol, gluten, and lactose. This study's objective was to formulate a cholesterol-free soymilk dessert (SOD) and compare it's to commercial desserts (CODs). Results indicated that the CODs contain substantial amounts of cholesterol while SOD does not. Soymilk dessert has more protein, and vitamin E than CODs, but less fat and calcium. In addition, the result also highlighted that SOD has higher number of amino acids compared to CODs. The total antioxidant, flavonoids and phenolics content of SOD were significantly higher than CODs. Furthermore, the in vitro antioxidant activity of SOD and CODs by DPPH and ABTS methods revealed that the IC50 of SODs significantly (p < 0.001) lower than CODs, and lower IC50 indicated the higher free radical scavenging power of SODs than CODs. These findings indicated that this non-dairy SOD may provide beneficial protein, as well as minerals, and antioxidants to support the body's various physiological functions.

Exploring the Factors Associated with Dietary Diversity of Children Aged 6-59 Months in Some Rural and Slum Areas of Bangladesh amid the COVID-19 Pandemic: A Mixed-Effect Regression Analysis.

Background: Dietary diversity (DD) is a key component of diet quality, and malnutrition due to poor diet quality leads to child morbidity and mortality. However, in Bangladesh, there is a lack of information on childhood DD (for children aged 6-59 mo) amid the coronavirus disease 2019 (COVID-19) pandemic. Objectives: The purpose of this study was to assess the minimum DD and its associated factors among children aged 6-59 mo during the COVID-19 pandemic in Bangladesh. Methods: A cross-sectional study was carried out in 6 districts of Bangladesh. A total of 1190 respondents were included using cluster random sampling. The Individual Dietary Diversity Score (IDDS) for children was used to assess the children's DD. Factors associated with DD of children were identified using a multilevel binary logistics regression model. Results: About 70% of the children aged 6-59 mo had minimum DD during the COVID-19 pandemic in Bangladesh. Children who belonged to slum areas [adjusted odds ratio (AOR): 0.45; 95% CI: 0.24, 0.83], family income 12,000-15,000 Bangladeshi taka (BDT) (AOR: 1.79; 95% CI: 1.06, 3.05) and >15,000 BDT (AOR: 2.59; 95% CI: 1.47, 4.57), mothers aged 26-30 y (AOR: 0.35; 95% CI: 0.20, 0.62) and >30 y (AOR: 0.43; 95% CI: 0.22, 0.85), respondents who had 2 children <5 y old (AOR: 0.43; 95% CI: 0.28, 0.66), and children aged 12-23 mo (AOR: 1.89; 95% CI: 1.14, 3.20) were significantly associated with DD among children aged 6-59 mo. Conclusions: The findings of this study highlight the need for food and nutrition-related intervention, particularly targeting mothers of younger age and with >2 children <5 y old, mothers from slum regions, and fathers who were unemployed, to improve children's DD practices.

Explainable Transformer-Based Deep Learning Model for the Detection of Malaria Parasites from Blood Cell Images.

Malaria is a life-threatening disease caused by female anopheles mosquito bites. Various plasmodium parasites spread in the victim's blood cells and keep their life in a critical situation. If not treated at the early stage, malaria can cause even death. Microscopy is a familiar process for diagnosing malaria, collecting the victim's blood samples, and counting the parasite and red blood cells. However, the microscopy process is time-consuming and can produce an erroneous result in some cases. With the recent success of machine learning and deep learning in medical diagnosis, it is quite possible to minimize diagnosis costs and improve overall detection accuracy compared with the traditional microscopy method. This paper proposes a multiheaded attention-based transformer model to diagnose the malaria parasite from blood cell images. To demonstrate the effectiveness of the proposed model, the gradient-weighted class activation map (Grad-CAM) technique was implemented to identify which parts of an image the proposed model paid much more attention to compared with the remaining parts by generating a heatmap image. The proposed model achieved a testing accuracy, precision, recall, f1-score, and AUC score of 96.41%, 96.99%, 95.88%, 96.44%, and 99.11%, respectively, for the original malaria parasite dataset and 99.25%, 99.08%, 99.42%, 99.25%, and 99.99%, respectively, for the modified dataset. Various hyperparameters were also finetuned to obtain optimum results, which were also compared with state-of-the-art (SOTA) methods for malaria parasite detection, and the proposed method outperformed the existing methods.

Biomarker identification by reversing the learning mechanism of an autoencoder and recursive feature elimination.

RNA-Seq has made significant contributions to various fields, particularly in cancer research. Recent studies on differential gene expression analysis and the discovery of novel cancer biomarkers have extensively used RNA-Seq data. New biomarker identification is essential for moving cancer research forward, and early cancer diagnosis improves patients' chances of recovery and increases life expectancy. There is an urgency and scope of improvement in both sections. In this paper, we developed an autoencoder-based biomarker identification method by reversing the learning mechanism of the trained encoders. We devised an explainable post hoc methodology for identifying influential genes with a high likelihood of becoming biomarkers. We applied recursive feature elimination to shorten the list further and presented a list of 17 potential biomarkers that are 99.93% accurate in identifying cancer types using support vector machine for the UCI gene expression cancer RNA-Seq dataset consisting of five cancerous tumor types. Our methodology outperforms all of the state-of-the-art methods, confirming the potential of the newly identified biomarkers as well as the efficacy of the biomarker identification procedure. Moreover, we have evaluated the performance of our methodology using six independent RNA-Seq gene expression datasets for several tasks, i.e., classification of tumors from non-tumors, detecting the origin of circulating tumor cells (CTCs), and predicting if metastasis occurs or not. Our methodology achieved stimulating results for these tasks as well. The source code of this project is available at https://github.com/fuad021/biomarker-identification.

Factors associated with household food insecurity and dietary diversity among day laborers amid the COVID-19 pandemic in Bangladesh.

BACKGROUNDS: Food insecurity and dietary diversity remain a public health concern in developing countries like Bangladesh which is exacerbated by the COVID-19 especially for day laborers' families in Bangladesh. This study aimed to determine factors associated with household food insecurity and household dietary diversity among day laborers during the COVID-19 pandemic in Bangladesh. METHODS: This cross-sectional study was conducted among 343 households of day laborers in Bangladesh using a semi-structured questionnaire. Household food security (HFS) and Household dietary diversity (HDD) scores were assessed using the HFS scale and household's 24-h recall of intake of 12 food groups, respectively. RESULTS: The overall mean scores of HFS and HDD were 26.80 (SD, 4.83) and 4.08 (SD, 1.15). Having household head aged > 40 years and monthly household income > 5000 Bangladeshi Taka (BDT) were positively associated with HDD scores. Having an education level above secondary, monthly household income > 5000 BDT, and having a refrigerator were associated with the higher HFS scores, whereas having family members > 5 was a potential determinant of lower HFS scores. Pandemic-induced work loss and food scarcity were also potential determinants of lower HFS and HDD scores. Approximately 94% of respondents reported their wages were reduced, and 76% were deprived of the same quantity of food as pre-pandemic periods. CONCLUSIONS: Lower socio-economic status and pandemic-induced work loss affect the HFS and HDD. Interventions with financial aid and complemented food distributions, particularly among the wage looser, may improve the HFS and HDD of day laborers.

High Prevalence of Hepatitis B and C Virus Infections Among Rohingya Refugees in Bangladesh: A Growing Concern for the Refugees and the Host Communities.

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Prevalence and correlates of diabetes distress and depressive symptoms among individuals with type-2 diabetes mellitus during Ramadan fasting: A cross-sectional study in Bangladesh amid the COVID-19.

AIMS: Psychological concerns relating to "diabetes distress" (DD) and depressive symptoms (DS) in individuals with type-2 diabetes mellitus (T2DM) may negatively impact adherence to medical treatments and overall mental health. Thus, this study was undertaken to investigate DS and DD in relation to fasting during the month of Ramadan. METHODS: A cross-sectional survey was conducted among 735 patients with T2DM in 2021. DD and DS were measured by the Problem Areas in Diabetes scale and Patient Health Questionnaire-9, respectively. Logistic regression and correlation analyses were executed. RESULTS: More than one-third of the participants (41.2%) had DD and DS (36.9%). DS was significantly higher in participants who did not fast (p = 0.027). Participants who had higher dietary diversity were less likely to have DD (p = 0.004) and DS (p = 0.001). Females (AOR = 1.89, 95% CI: 1.25-2.85) and those who lived alone (AOR = 1.89, 95% CI: 1.25-2.85) were more likely to have DS. Participants with diabetes-related complications were more likely to experience DS (AOR = 2.17; 95% CI: 1.5-3.13) and DD (AOR = 3.46; 95% CI: 2.42-4.95). DD was also associated with being younger (p = 0.003), having hypertension (p = 0.030), having heart disease (p = 0.012), and taking insulin (p = 0.010). CONCLUSIONS: Individuals with T2DM who were not fasting experienced more mental health concerns. Psychosocial support and other interventions from health professionals should be examined and empirical interventions should be implemented to promote the mental health and well-being of individuals with T2DM.

The impact of the COVID-19 pandemic on the mental health of the adult population in Bangladesh: a nationwide cross-sectional study.

The recent COVID-19 pandemic has imposed threats on both physical and mental health since its outbreak. This study aimed to explore the impact of the COVID-19 pandemic on mental health among a representative sample of home-quarantined Bangladeshi adults. A cross-sectional design was used with an online survey completed by a convenience sample recruited via social media. A total of 1,427 respondents were recruited, and their mental health was assessed by the DASS-21 measure. The prevalence of anxiety symptoms and depressive symptoms was 33.7% and 57.9%, respectively, and 59.7% reported mild to extremely severe levels of stress. Perceptions that the pandemic disrupted life events, affected mental health, jobs, the economy and education, predictions of a worsening situation, and uncertainty of the health care system capacities were significantly associated with poor mental health outcomes. Multivariate logistic regressions showed that sociodemographic factors and perceptions of COVID-19 significantly predict mental health outcomes. These findings warrant the consideration of easily accessible low-intensity mental health interventions during and beyond this pandemic.

Presence of toxic metals in rice with human health hazards in Tangail district of Bangladesh.

Rice is the staple food of Bangladeshi people and is consumed at least twice a day. Thus, the presence of toxic metals in rice grains has become a major public health concern in Bangladesh. The present research was conducted to investigate the concentrations of toxic metals in rice grains and their possible human health risks in the Tangail district of Bangladesh. Toxic metals were measured by using an inductively coupled plasma mass spectrometer (ICP-MS), and the mean concentrations of toxic metals in rice samples were found in order of Cr > Pb > Ni > As > Cu > Cd. The concentrations of Cr, Pb, As, and Cd in the studied rice grain samples exceeded the FAO/WHO standard values for food samples by 100%, whereas the Ni concentrations by 10%. The principal component analysis (PCA) revealed significant anthropogenic contributions of Cr, Ni, As, and Pb concentrations in rice grains. The metal concentrations in rice grain samples showed strong significant correlations by forming primary clusters with each other. The estimated daily intake (EDI) values of Cr, Ni, As, Cd, and Pb from all samples were higher than the maximum tolerable daily intake (MTDI) allowed. The total targeted hazard quotient (TTHQ) values of Cu, Ni, As, Cd, and Pb also exceeded the threshold value of 1.00, indicating a potential non-carcinogenic risk. The estimated target carcinogenic risk of As was higher than the USEPA threshold level 10-4 (0.0001) indicating increased risk of cancer for adults and children in the study area.

Factors associated with overweight and obesity among Bangladeshi university students: a case-control study.

Objectives: Overweight and obesity has an adverse effect on public health, and emerging adulthood (18-25 years) is recognized as a potential period for the onset of obesity, thus, this study aimed to explore risk factors associated with overweight and obesity in Bangladeshi university students. Participants: Bangladeshi university students (n = 280). Methods: A case-control study of 140 students with overweight and obesity and 140 students with normal weight. Results: Multiple logistic regression revealed having at least one overweight or obese parent (AOR = 4.2; 95% CI: 2.2-8.4) and participating in no physical activity (AOR = 3.2; 95% CI: 1.0-9.9) were potential risk factors. Reported consumption ≥4 meals in a day, junk food/fast food, and soft drinks for ≥3 days a week were potential determinants of overweight and obesity in this population. Conclusion: Increased awareness on the importance of regular physical activity and a healthy diet may reduce the risk of overweight and obesity among Bangladeshi university students.