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Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model
INTRODUCTION: Anemia is indeed a significant risk factor for children's health as it affects growth retardation and has severe short and prolonged effects that follow in morbidity and death. Notwithstanding such ways to tackle anemia, the prevalence remains high in India and poses a severe publ...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9159194/ https://www.ncbi.nlm.nih.gov/pubmed/35685513 http://dx.doi.org/10.1155/2022/2212624 |
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author | Islam, Md. Akhtarul Afroja, Sohani Khan, Md. Salauddin Alauddin, Sharlene Nahar, Mst. Tanmin Talukder, Ashis |
author_facet | Islam, Md. Akhtarul Afroja, Sohani Khan, Md. Salauddin Alauddin, Sharlene Nahar, Mst. Tanmin Talukder, Ashis |
author_sort | Islam, Md. Akhtarul |
collection | PubMed |
description | INTRODUCTION: Anemia is indeed a significant risk factor for children's health as it affects growth retardation and has severe short and prolonged effects that follow in morbidity and death. Notwithstanding such ways to tackle anemia, the prevalence remains high in India and poses a severe public health concern. OBJECTIVES: The primary focus of this study was to find the prevalence and to determine the factors associated with the anemia of children under five years of age in India. Problem Statement. The increasing prevalence of childhood anemia and the life-threatening consequences for millions of children in India are a major concern. Knowing the relevant associated factors with childhood anemia is essential to reduce the frequency and severity level. Study design. For analysis purposes, this study utilized a cross-sectional study design. Methodology. Using the Indian Demographic and Health Survey 2015–16 data, we used chi-squared and gamma tests to find the association. Then, we utilized multinomial logistic regression and ordinal logistic regression to find the better model and the influencing factors of anemia in India. RESULTS: In our study, we have found that children with highly educated mothers were 36.7% less likely (OR = 0.633, P ≤ 0.001, 95% CI: 0.608, 0.658) to be higher anemic than the children with not educated mother. Children with moderate and severe anemic mothers were 163.3% (OR = 2.633, P ≤ 0.001, 95% CI: 2.565, 7.704) more likely to be higher anemic than the children with not anemic mother. Not stunting children were 21.9% (OR = 0.781, P ≤ 0.001, 95% CI: 0 .764, 0.797) less likely to be higher anemic than the stunting children. Children aged 36–59 months were 73.9% (OR = 0.361, P ≤ 0.001, 95% CI: 0.353, 0.369) less likely to be higher anemic than the children aged 6–24 months. Again, the ACI value revealed that ordinal logistic regression was a better-fitted model for these data. CONCLUSION: and contribution. The variables such as stunting, underweight, wasting, child age, size of the child, and source of drinking water were the most critical indicators for child anemia in India. In summary, our study result indicated the major socioeconomic and demographic factors associated with childhood anemia in India, which can help the policymaker to take quick decision to reduce the severity level. |
format | Online Article Text |
id | pubmed-9159194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-91591942022-06-07 Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model Islam, Md. Akhtarul Afroja, Sohani Khan, Md. Salauddin Alauddin, Sharlene Nahar, Mst. Tanmin Talukder, Ashis Int J Clin Pract Research Article INTRODUCTION: Anemia is indeed a significant risk factor for children's health as it affects growth retardation and has severe short and prolonged effects that follow in morbidity and death. Notwithstanding such ways to tackle anemia, the prevalence remains high in India and poses a severe public health concern. OBJECTIVES: The primary focus of this study was to find the prevalence and to determine the factors associated with the anemia of children under five years of age in India. Problem Statement. The increasing prevalence of childhood anemia and the life-threatening consequences for millions of children in India are a major concern. Knowing the relevant associated factors with childhood anemia is essential to reduce the frequency and severity level. Study design. For analysis purposes, this study utilized a cross-sectional study design. Methodology. Using the Indian Demographic and Health Survey 2015–16 data, we used chi-squared and gamma tests to find the association. Then, we utilized multinomial logistic regression and ordinal logistic regression to find the better model and the influencing factors of anemia in India. RESULTS: In our study, we have found that children with highly educated mothers were 36.7% less likely (OR = 0.633, P ≤ 0.001, 95% CI: 0.608, 0.658) to be higher anemic than the children with not educated mother. Children with moderate and severe anemic mothers were 163.3% (OR = 2.633, P ≤ 0.001, 95% CI: 2.565, 7.704) more likely to be higher anemic than the children with not anemic mother. Not stunting children were 21.9% (OR = 0.781, P ≤ 0.001, 95% CI: 0 .764, 0.797) less likely to be higher anemic than the stunting children. Children aged 36–59 months were 73.9% (OR = 0.361, P ≤ 0.001, 95% CI: 0.353, 0.369) less likely to be higher anemic than the children aged 6–24 months. Again, the ACI value revealed that ordinal logistic regression was a better-fitted model for these data. CONCLUSION: and contribution. The variables such as stunting, underweight, wasting, child age, size of the child, and source of drinking water were the most critical indicators for child anemia in India. In summary, our study result indicated the major socioeconomic and demographic factors associated with childhood anemia in India, which can help the policymaker to take quick decision to reduce the severity level. Hindawi 2022-02-04 /pmc/articles/PMC9159194/ /pubmed/35685513 http://dx.doi.org/10.1155/2022/2212624 Text en Copyright © 2022 Md. Akhtarul Islam et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Islam, Md. Akhtarul Afroja, Sohani Khan, Md. Salauddin Alauddin, Sharlene Nahar, Mst. Tanmin Talukder, Ashis Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model |
title | Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model |
title_full | Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model |
title_fullStr | Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model |
title_full_unstemmed | Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model |
title_short | Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model |
title_sort | prevalence and triggering factors of childhood anemia: an application of ordinal logistic regression model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9159194/ https://www.ncbi.nlm.nih.gov/pubmed/35685513 http://dx.doi.org/10.1155/2022/2212624 |
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