Early childhood developmental status and its associated factors in Bangladesh: a comparison of two consecutive nationally representative surveys.

BACKGROUND: Inadequate cognitive and socio-emotional development in children leads to physical and mental illness. We aimed to investigate the status of early childhood development (ECD) and its associated factors. Additionally, aimed to compare the changes of significantly associated factors using two multiple indicator cluster surveys (MICS) in Bangladesh. METHODS: We used data from the Multiple Indicator Cluster Surveys (MICS) 2012 and 2019 nationally representative surveys. A total of 17,494 children aged 36-59 months were included in the analysis. The outcome variable was ECD status: either developmentally on-track or not. We used bivariable analysis and crude and adjusted multivariable logistic models to assess the ECD status and its associated factors. RESULTS: Comparing both MICS surveys, the overall and individual domains of ECD status improved from 2012 (65.46%) to 2019 (74.86%), and the indicators of child literacy-numeracy domain improved from 21.2 to 28.8%, physical domain improved from 92.2 to 98.4%, and social-emotional domain improved from 68.4 to 72.7%. The learning approach domain was 87.5% in 2012 and increased to 91.4% in 2019. According to the adjusted logistic model in both surveys (2012 and 2019), the age of 4 years had an adjusted odds ratio (AOR) of 1.61 and 1.78 times higher developmentally on track than the age of 3. Female children were 1.42 (in 2012) and 1.44 (in 2019) times more developmentally on track than males. Compared to mothers with only primary education, children raised by mothers with secondary or higher education were 1.77 and 1.50 times more on track in their development. Moreover, Children from affluent families had 1.32- and 1.26 times higher odds- on track than those from the poorest families. Families with books had 1.50 and 1.53 times higher developmentally on track than their counterparts. CONCLUSION AND RECOMMENDATION: In summary, our study shows that the overall ECD status improved between MICS 2012 and MICS 2019. Important factors influence ECD status, including early childhood education programs, families' possession of children's books, mothers' educational level, and wealth index. The findings of our study will help making necessary public health-related initiatives in Bangladesh to improve ECD program.

Potential association between allergenic food exposure and skin disease in Bangladesh: An application of principal component logistic regression (PCLR).

Background and Aim: Allergenic foods can trigger skin conditions, yet their impact in Bangladesh remains underexplored. This study aims to investigate the potential association between exposure to allergenic foods and the development of skin disease across Bangladesh. Methods: We conducted a cross-sectional survey with 970 respondents from the divisions of Dhaka, Sylhet, Rangpur, and Chattogram who self-reported skin disease triggered by food allergens. We analyzed the data using multiple response analysis and principal component logistic regression. Results: Approximately 64% of respondents had skin disease attributable to allergenic foods, with a relatively higher proportion among females (52%) than males (48%). Beef (67%), Brinjal (47.1%), Hilsa (45.8%), and Shrimp (23.7%) were the most frequently cited allergenic foods. Principal component logistic regression identified two highly significant principal components: the first representing Hilsa, Beef, and Brinjal (odds ratio = 2.256), and the sixth reflecting Corn (odds ratio = 1.342). Individuals who consumed foods with high loadings of the first principal component were 125.6% more likely to develop skin disease than nonconsumers, while those exposed to Corn had a 34.2% higher risk. Conclusion: The findings highlight prevalent allergenic foods in Bangladesh and their substantial impact on skin health, underscoring the need for dietary awareness and tailored interventions to mitigate allergic skin conditions in this population.

Forecasting COVID-19 situation in Bangladesh.

Forecasting the COVID-19 confirmed cases, deaths, and recoveries demands time to know the severity of the novel coronavirus. This research aims to predict all types of COVID-19 cases (verified people, deaths, and recoveries) from the deadliest 3rd wave data of the COVID-19 pandemic in Bangladesh. We used the official website of the Directorate General of Health Services as our data source. To identify and predict the upcoming trends of the COVID-19 situation of Bangladesh, we fit the Auto-Regressive Integrated Moving Average (ARIMA) model on the data from Mar. 01, 2021 to Jul. 31, 2021. The finding of the ARIMA model (forecast model) reveals that infected, deaths, and recoveries number will have experienced exponential growth in Bangladesh to October 2021. Our model reports that confirmed cases and deaths will escalate by four times, and the recoveries will improve by five times at a later point in October 2021 if the trend of the three scenarios of COVID-19 from March to July lasts. The prediction of the COVID-19 scenario for the next three months is very frightening in Bangladesh, so the strategic planner and field-level personnel need to search for suitable policies and strategies and adopt these for controlling the mass transmission of the virus.