Fazley Amin* and Taj Uddin
Background: Malnutrition is a major health issue in underdeveloped nations like Bangladesh. This research aims to find out the prevalence of nutrition status and determine the associated factors influencing the nutrition status of children under the age of five (0-59 months) in Bangladesh using multiple indicator cluster survey data, 2019. To obtain the most recent prevalence of malnutrition and its associated factors we apply MICS-2019 data since this is the latest version of the available secondary data.
Methods: Body Mass Index (BMI) is used to measure the nutrition status of children. Descriptive statistical tools along with multiple linear regression model are used for data analysis in this study. We also performed an Analysis of Variance (ANOVA) and t-test to test the significance of different factors on under five children's nutritional status.
Results: The mean BMI of children is (15.01 ± 1.44 kg/m²). The mean BMI of urban area children (15.13 ± 1.47 kg/m²) is higher than rural area children (14.99 ± 1.43 kg/m²). The prevalence of underweight, overweight, and obese among under five children is 14.21%, 12.92%, and 2.94% respectively and the prevalence of underweight among girls (17.21%) is higher than that of boys (11.4%) while the prevalence of healthy or normal weight among boys (70.65%) is higher than that of girls (69.15%%). We also found that the prevalence of obesity among girls (2.48%) is lower than that of boys (3.38%) while the prevalence of overweight among boys (14.57%) is superior to that of girls (11.16%) for children of age under five. Also, the analysis shows that gender, age of children, wealth index, area of children, division, and mother’s education are significant (p<0.05) determinants of the nutrition status of children.
Conclusion: The government might consider creating specific nutrition intervention approaches to ensure that health education and information are readily available to parents, along with continuous initiatives aimed at enhancing child health. According to our findings, we observed that there are 30.07% of children are in a state of malnutrition. Special attention needs to be paid to the most vulnerable groups, such as children from the poorest socio-economic background or those residing in rural areas. Mothers should be prioritized when designing intervention programs.
Nazmin Akter * and Rezaul Karim
Count data are now extensively available in a wide range of disciplines. The Poisson distribution, the most used for modeling count data, assumes equidispersion (variance and mean are equal). Poisson models are less suitable for modeling since observed count data frequently display under dispersion or over dispersion. To handle a variety of dispersion levels alternative regression models including negative binomial regression, generalized Poisson regression, and most recently Conway Maxwell-Poisson (COM-Poisson) regression models are employed. Using dispersed data; we compared the COM-Poisson to all other regression models and illustrated how effective and better it is. We conducted a case study utilizing COVID-19 daily death data related to meteorological factors to show how models are applied to real domains.
Journal of Biometrics & Biostatistics received 3496 citations as per Google Scholar report
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