Mr. Henry Ratul Halder, MSc - Khulna University - Research Assistant

Mr. Henry Ratul Halder


Khulna University

Research Assistant

Khulna , Khulna | Bangladesh

Main Specialties: Epidemiology, Family Medicine, Family Practice, Infectious Disease, Public Health, Statistics

Additional Specialties: Health Data Analyst

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Mr. Henry Ratul Halder, MSc - Khulna University - Research Assistant

Mr. Henry Ratul Halder



Henry Ratul Halder is pursuing his MSc in Applied Statistics and Data Science at Jahangirnagar University, Bangladesh. He has a great interest in infectious diseases, public health, and community health sciences with the methodologies in meta-analysis, biostatistics, and machine learning. Currently, working on a project entitle "Machine Learning Algorithms for Pattern Recognition of Risk Factors among TB Patients of Bangladesh".

Primary Affiliation: Khulna University - Khulna , Khulna , Bangladesh


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View Mr. Henry Ratul Halder’s Resume / CV


May 2019
Jahangirnagar University
MSc in Applied Statistics and Data Science
Jun 2015
Khulna University
BSc in Statistics




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Impact of socioeconomic and demographic factors for underweight and overweight children in Bangladesh: A polytomous logistic regression model


Clinical Epidemiology and Global Health

Background: The level of development and quality of life for a country depends on its newborn. Bangladesh has failed to reduce the number of underweight children between 1990 and 2015, whereas overweight is one of the most visible yet neglected public health issues. Hence, immediate actions need to be taken to improve both cases. The objective of this study is to identify the influencing socioeconomic and demographic factors for the discrepancy in under-5 child's weight. Methods: The study is based on the Bangladesh Demographic and Health Survey (BDHS), 2014. Originally, the data was collected from 17,866 households. After extracting the variable from the sample weighted original dataset, this study covered 8092 respondents. The dependent variable, under-5 child's weight was settled by scheming weight-forage Z-score (WAZ) and Body Mass Index-forage Z-score (BAZ). Then, the polytomous logistic regression model was incorporated to get insight into the underweight and overweight categories relative to the normal weighted under-5 child. Results: The significant predictors for influencing under-5 child's weight are place of residence, mother's and father's education level, mother's body mass index, mother's current working status, mother's age at first birth, father's occupation, child's birth order, and region of residence. Conclusion: Parental education, mother's current working status, and place of residence have the most significant effect on under-5 child's weight. Public health officials and administrators of Bangladesh across sectors need to develop more effective programs and strategies for effective actions to adequately address the good nutrition and health of a child.

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May 2020
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