Analysis of Under-Five Mortality by Diseases in Countries With Different Levels of Development: a Comparative Analysis

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Date

2023

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Journal ISSN

Volume Title

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Open Access Color

GOLD

Green Open Access

Yes

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52

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116

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No
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Average
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Average
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Abstract

Objectives: The right to health is critical for children because they are sensitive beings who are more susceptible to disease and health problems. It would be beneficial to compare child mortality rates in countries with different levels of development and to conduct studies to address them by taking into account their causes. This study aims to analyze the situation of developed, developing and least developed countries in terms of causes under-5 child mortality (U5CM) determined by World Health Organization and to identify the similarities or differences of under-five mortality. Methods: Child mortality rates per 1,000 live births between 2000 and 2017 years in between different age groups (0-27 days and 1-59 months) by causes (disease-specific) were obtained from World Health Organization for a total 15 countries including developed, developing and least developed countries. Regression analysis was performed to identify which causes have more impact on child mortality. In addition, the relationship between diseases was calculated using Euclidean distance, and diseases were clustered using k-means clustering algorithm for each country. Results: As a result of mathematical and statistical analysis, it was seen that causes of child mortality have a significant relation with the development level of country where a child was born. Conclusions: It has been observed that the causes of child mortality in countries with different levels of development vary depending on different factors such as geographical conditions, air quality population and access to medicine.

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Keywords

Nüfus İstatistikleri Bilimi, Klinik Tıp Bilimleri, Clinical Sciences, Sağlık Kurumları Yönetimi, World Health Organization, child mortality, World Health Organization;child mortality;Euclidean distance;linear regression;clustering, Health Care Administration, linear regression, Euclidean distance, clustering

Fields of Science

03 medical and health sciences, 0302 clinical medicine

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N/A

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OpenCitations Citation Count
1

Source

The European Research Journal

Volume

9

Issue

4

Start Page

652

End Page

664
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CrossRef : 1

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Mendeley Readers : 9

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7

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3

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3

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