Maternal Pregnancy Intention and Antenatal Care Seeking Behaviors in Bangladesh: Evidence From Bangladesh Demographic and Health Survey, 2018

Objective: This study aimed to examine the association between pregnancy intention and antenatal care (ANC)-seeking behaviors among women in Bangladesh.Methods: ANC-related data of 5,012 women, from the 2018 Bangladesh Demographic and Health Survey (BDHS), who had a live birth within 3 years preceding the survey were analyzed in the study. Multivariate logistic regression models were used to assess the association of pregnancy intention with ANC utilization.Results: Approximately one-fifth (20.9%) of the women had unintended pregnancy. Among all the women, 40.4% received their first ANC visit within the first three months of pregnancies, 47% had at least four ANC visits, 26.1% received all the components of ANC services, and 22.2% received an adequate dosage of supplementary iron-folic acid tablets/syrup. Women with unintended pregnancy were less likely to receive their first ANC visit within the first 3 months, four or more ANC visits, and all ANC services than those with intended pregnancy.Conclusion: Unintended pregnancy was inversely associated with the proper utilization of ANC among women in Bangladesh. Appropriate measures to reduce unintended pregnancy might foster the utilization of optimum antenatal care

Evaluation of performances and selection response of three indigenous chicken genotypes at seventh-generation

The present study was conducted to assessed the performances of three native chicken genotypes under intensive management. A total of 1042 day-old chicks comprising of 3 types of chicken, namely Naked Neck (NN-381), Hilly (HI-313), and Non-descript Deshi (ND-348), were Hatched for this study. The seventh generation, selection was practiced at 40 weeks of age according to 40-week body weight (BW), egg production (EP) up to 40-week, egg weight (EW) at 40 weeks, and age at maturity (ASM). The data were analyzed in a CRD. Day-old chick weight was significantly (P < 0.001) highest in HI (32.52 ± 0.32 g). Significant (P < 0.001) body weight differences among the genotypes were observed at the 12th week of age. Genotype had a significant effect on chick mortality. The average age at the first egg of ND 145.54days was 8.81 days earlier than that of HI 154.35days. Hatchability on fertile eggs differed significantly (P < 0.05) among the genotypes. The percentage of dead germ was affected (P < 0.001) by genotype. Feed consumption from 9 to 16 weeks showed a significant (P < 0.001) variation in feed intake among the native chicken genotypes. EP of ND, HI, and NN birds were expected to increase by 0.875, 1.585, and 0.255 %, respectively. The EW of ND, HI, and NN birds were expected to increase by 0.205, 0.250, and 0.015g, respectively. Responses to selection for EP and EW for three genotypes (ND, HI, and NN) were expected to be positive (increase). It is concluded that the Hilly genotype may be chosen for meat production and the Non-descript Deshi genotype for egg production

Association of clinico-epidemiological features with locally advanced stage of cervical cancer patients presenting at Bangabandhu Sheikh Mujib Medical University, Bangladesh

Cervical cancer is one of the most prevalent gynecological cancers in women in Bangladesh. The objective of this study was to assess the clincoepidemiological association with the histology of locally advanced cervical cancer. We have done this observational study in the department of Clinical Oncology at Bangabandhu Sheikh Mujib Medical University from July to December 2019. Sixty-six biopsy-proven locally advanced (stage IIB to IVA) squamous cell carcinoma of uterine cervix were included in this study. The mean age of patients at diagnosis was 48.5 (±8.6) years. Commonly observed epidemiological characteristics of locally advanced carcinoma cervix were illiteracy (46.9%), oral contraceptive use (62.1%), multi para (78.7%) and early marriage (74.2%). Most frequent clinical presentation was post-coital bleeding (37.87%). Most patients presented in stage IIB (65.1%). The association of the stages of the disease with age, parity, oral contraceptive use, age at marriage and clinical presentation were statistically nonsignificant, whereas illiteracy was statistically significant. Most women had poor awareness regarding their need for routine check-up and screening as indicated by the late medical care seeking. Social stigma might have played some role. Relevant programmes should create awareness among women, especially those with socioeconomic deprivation. BSMMU J 2022; 15(3): 175-17

Nutrient density of Bangladeshi foods and its application in planning diet for pregnant women.

Nutrient profiling is a method that classifies foods based on their nutrient content and identifies foods that are high in micronutrients both across and within food groups. This study aimed to identify foods that are rich sources of the seven micronutrients (iron, zinc, calcium, thiamine, riboflavin, vitamin A, and vitamin B12) of public health concern for the Bangladeshi population.. This study developed a metric termed "naturally nutrient-rich score 7 (NNR7)" specifically for third-trimester pregnant women to identify nutrient-dense foods. Further, it computed the nutrient adequacy score (NAS) of the top NNR7-scored foods for seven micronutrients to assess the extent (percent) to which foods can meet pregnant women's recommended dietary allowances (RDA). A linear programming technique was then used to construct a nutrient-adequate model diet for third-trimester pregnant women using the top ten NNR7-scored foods. According to the NNR7, food groups such as leafy vegetables, fish, meat, poultry and eggs, and vegetables are the richest sources of the problem micronutrients. Mutton liver (916.7%), soybean (39.3%), lamb liver (2160%) and duck liver (50.0%) were found to fulfill the highest percentage of the RDA of vitamin A, zinc, vitamin B12, and iron, respectively. In the formulated nutrient-adequate diets for pregnant women, rice, potato, brown wheat flour, and soya oil were universal to all three diets and Bengal gram, orange, Ganges River sprat, and duck liver were the most common ones. The study findings highlight the need for the consumption of foods such as leafy vegetables, fish, meat, poultry, eggs, pulses and vegetables to increase the intake of problematic micronutrients. Planning a nutrient-adequate diet for pregnant women using linear programming can be an alternative approach to optimize and shape food choices to meet their nutritional requirements

Validity of Food insecurity experience scale (FIES) for use in rural Bangladesh and prevalence and determinants of household food insecurity: An analysis of data from Bangladesh integrated household survey (BIHS) 2018-2019

“Access” dimension of Food insecurity (FI) is directly measured by the Food Insecurity Experience Scale (FIES). The current study assessed the appropriateness of the FIES for measuring FI in rural Bangladesh, followed by an assessment of FI prevalence and its correlates utilizing Bangladesh Integrated Household Survey (BIHS) data. The internal validity of the FIES and the prevalence of FI were investigated using the Rasch modeling approach. We utilized equating procedure to calibrate the study’s result to the global FIES reference scale and determined FI prevalence rates that were comparable across countries. The external validity of the FIES was evaluated by examining its association with other FI measures using Spearman’s rho correlation analysis. With an overall Rasch reliability of 0.84, the FIES met the Rasch model assumptions of conditional independence and equal discrimination, and as well as the fit statistics standards for all eight items. Infit statistics were within the allowed limit for all FIES items indicating good internal validity. However, we noted a high outfit (>2) for the “unable to eat healthy and nutritious food” item indicating the presence of some unusual response patterns. Our analysis found no significant (>0.4) correlation between FIES items. We also found a significant correlation between FIES and other FI proxies, e.g., the Household hunger scale (HHS), Food consumption score (FCS), and Household dietary diversity score (HDDS). Overall, the prevalence of moderate or severe FI was 18.92% in rural Bangladesh. Geographic areas, access to electricity, household ownership, access to sanitation, livestock ownership, family size, education level, and monthly per capita food expenditure significantly explained the variation in FI. Our analyses suggest that the FIES is internally and externally valid for FI measurement in rural Bangladesh. However, FIES questions may need to be reordered to more accurately evaluate lower levels of FI, and the item “unable to eat healthy and nutritious food” may need cognitive testing

Complementary feeding practices and their determinants among children aged 6–23 months in rural Bangladesh: evidence from Bangladesh Integrated Household Survey (BIHS) 2018–2019 evaluated against WHO/UNICEF guideline -2021

Abstract Background Appropriate Complementary feeding (CF) practices play a crucial role in determining child nutrition, growth, and development. This study seeks to examine CF practices and their predictors among children aged 6 to 23 months in rural Bangladesh according to the most recently updated WHO/UNICEF guidelines for CF. Methods A total of 665 children aged 6 to 23 months from the Bangladesh Integrated Household Survey (BIHS) 2018–2019 dataset were analyzed. The WHO/UNICEF guidelines for CF were followed to evaluate each of the nine CF practice indicators. We also examined the effect of the child, maternal, household, and community-level factors on different CF components using multiple logistic regression analyses. Results Approximately two-thirds of the children initiated complementary feeding on time (63.5%) but had zero vegetable or fruit consumption (63.2%). More than half (52.4%) and the majority (86.5%) of children had minimum meal frequency and minimum milk feeding frequency, respectively. On the other hand, the proportion of minimum dietary diversity was quite low (18.3%), as reflected in the alarming prevalence (16.3%) of minimum acceptable diet. Egg and/or flesh food, sweet beverage, and unhealthy food consumption were 23.3%, 2.5%, and 12.2%, respectively. Child age, mothers’ education level, antenatal care visit, household food security, monthly household income, and place of residence were found to be associated with CF practices. Conclusion When compared to results obtained using the previous guideline, the new one has resulted in a lower prevalence of Introduction of solid, semi-solid, or soft foods (ISSF), Minimum dietary diversity (MDD), Minimum meal frequency (MMF), and Minimum acceptable diet (MAD). It is crucial to convey the new knowledge for better child feeding and nutrition as the country prepares to apply the new guideline

Deep Learning Approaches to Predict Future Frames in Videos

Deep neural networks are becoming central in several areas of computer vision. While there have been a lot of studies regarding the classification of images and videos, future frame prediction is still a rarely investigated approach, and even some applications could make good use of the knowledge regarding the next frame of an image sequence in pixel-space. Examples include video compression and autonomous agents in robotics that have to act in natural environments. Learning how to forecast the future of an image sequence requires the system to understand and efficiently encode the content and dynamics for a certain period. It is viewed as a promising avenue from which even supervised tasks could benefit since labeled video data is limited and hard to obtain. Therefore, this work gives an overview of scientific advances covering future frame prediction and proposes a recurrent network model which utilizes recent techniques from deep learning research. The presented architecture is based on the recurrent decoder-encoder framework with convolutional cells, which allows the preservation of Spatio-temporal data correlations. Driven by perceptual-motivated objective functions and a modern recurrent learning strategy, it can outperform existing approaches concerning future frame generation in several video content types. All this can be achieved with fewer training iterations and model parameters