Fazley Amin* and Taj Uddin
DOI: 10.37421/2155-6180.2025.16.251
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
DOI: 10.37421/2155-6180.2025.16.252
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.
Aisha Verma
Jinwoo Park
Jinwoo Park
Liam OâConnor
Chen Li
Sara Ahmed
Nikhil Rao
Elena Petrova
Awoke Seyoum Tegegne*, Aschalew Dgoma, Shambel Molla, Tizita Lemma, Degwale Gebeyehu and Andargachew Moges
Background: The organizational context (structure, management, communication), working mechanisms (knowledge, shared ownership, commitment), outcomes of the quality culture (student and staff satisfaction, ongoing improvement of the teaching and learning process), and quality management interventions all interact with each other to create a successful organization. Examining the status of quality culture at Bahir Dar University was the major objective of this study.
Methods: A cross-sectional study design was conducted in current investigation. Data were collected from academic and administrative staffs. The technique of proportional cluster sampling was employed to select samples. As a result, 205 academic staff members, and 420 administrative staff members were proportionally chosen from each academic unit of the university. The t-test, ANOVA, and descriptive statistics were used to analyze the survey data.
Results: The study's findings show that there was no statistical evidence for the above-average existence of a quality culture as perceived by the university’s academic and admin staffs (mean value: 3.01; p-value: 0.551); and, the results further show that quality cultures within university differ from what the university’s vision and mission expected. Hence, there is significance, difference of effective communication, shared value, trust of employees on the system, employees’ attitude about leaders, admin process, infrastructure availability, service quality, change leadership, feeling of responsibility, and work commitment between colleges, facilities, schools and institutes.
Conclusion and recommendation: In order to improve the education quality culture in its system, the university should improve communication, simplify administrative procedures, and increase service delivery. Additionally, it is suggested that individual efforts will not produce the intended results if they cannot be transformed into a team and collaborative commitment to creating synergy. Thus, top leaders at the university should concentrate on developing a system of collaborative teamwork in order to achieve the university's goal of becoming one of the top research universities in Africa.
Hiroshi Tanaka
Fatima Al-Hassan
Lucas Silva
Olivia Johnson
Renée Dubois
Kwame Mensah
Anna Svensson
Miguel Torres
Elena Dimitrova
David Brown
Yuki Nakamura
Sara Nielsen
Jorge Martinez
Priya Singh
Tomas Novak
Emily Carter
Rajesh Kulkarni
Noor Al-Khaled
Peter van Dijk
Sun-Young Kim
Michael Weber
Ana Popescu
Samuel Adeyemi
Marco Bianchi
Laila Hassan
Andrés Munoz
Sophie Laurent
Vladimir Ivanov
Ling Wong
Paul Henderson
Beatriz Almeida
Journal of Biometrics & Biostatistics received 3496 citations as per Google Scholar report
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