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Classification of Death Rate due to Women’s Cancers in Different Countries
BACKGROUND: The two most frequently diagnosed cancers among women worldwide are breast and cervical cancers. The objective of the present study was to classify the different countries based on the death rates from sex specific cancers. METHODS: In this cross-sectional study, we used dataset regardin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Tehran University of Medical Sciences
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3468994/ https://www.ncbi.nlm.nih.gov/pubmed/23113194 |
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author | Farhadian, M Mahjub, H Moghimbeigi, A Poorolajal, J Sadri, GH |
author_facet | Farhadian, M Mahjub, H Moghimbeigi, A Poorolajal, J Sadri, GH |
author_sort | Farhadian, M |
collection | PubMed |
description | BACKGROUND: The two most frequently diagnosed cancers among women worldwide are breast and cervical cancers. The objective of the present study was to classify the different countries based on the death rates from sex specific cancers. METHODS: In this cross-sectional study, we used dataset regarding death rate from breast, cervical, uterine, and ovarian cancers in 190 countries worldwide reported by World Health Organization. Normal mixture models were fitted with different numbers of components to these data. The model’s parameters estimated using the EM algorithm. Then, appropriate number of components was determined and was selected the best-fit model using the BIC criteria. Next, model-based clustering was used to allocate the world countries into different clusters based on the distribution of women’s cancers. The MIXMOD program using MATLAB software was used for data analysis. RESULTS: The best model selected with four components. Then, countries were allocated into four clusters including 43 (23%) in the first cluster, 28 (14%) in the second cluster, 75 (39%) in the third cluster, and 44 (24%) in the fourth cluster. Most countries in South America were to the first cluster. In addition, most countries in Africa, Central, and Southeast Asia were located to the third cluster. Furthermore, the fourth cluster consisted of Pacific continent, North America and European countries. CONCLUSION: Considering the benefits of clustering based on normal mixture models, it seems that can be applied this method in wide variety of medical and public heath contexts. |
format | Online Article Text |
id | pubmed-3468994 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Tehran University of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-34689942012-10-30 Classification of Death Rate due to Women’s Cancers in Different Countries Farhadian, M Mahjub, H Moghimbeigi, A Poorolajal, J Sadri, GH Iran J Public Health Original Articles BACKGROUND: The two most frequently diagnosed cancers among women worldwide are breast and cervical cancers. The objective of the present study was to classify the different countries based on the death rates from sex specific cancers. METHODS: In this cross-sectional study, we used dataset regarding death rate from breast, cervical, uterine, and ovarian cancers in 190 countries worldwide reported by World Health Organization. Normal mixture models were fitted with different numbers of components to these data. The model’s parameters estimated using the EM algorithm. Then, appropriate number of components was determined and was selected the best-fit model using the BIC criteria. Next, model-based clustering was used to allocate the world countries into different clusters based on the distribution of women’s cancers. The MIXMOD program using MATLAB software was used for data analysis. RESULTS: The best model selected with four components. Then, countries were allocated into four clusters including 43 (23%) in the first cluster, 28 (14%) in the second cluster, 75 (39%) in the third cluster, and 44 (24%) in the fourth cluster. Most countries in South America were to the first cluster. In addition, most countries in Africa, Central, and Southeast Asia were located to the third cluster. Furthermore, the fourth cluster consisted of Pacific continent, North America and European countries. CONCLUSION: Considering the benefits of clustering based on normal mixture models, it seems that can be applied this method in wide variety of medical and public heath contexts. Tehran University of Medical Sciences 2012-06-30 /pmc/articles/PMC3468994/ /pubmed/23113194 Text en Copyright © Iranian Public Health Association & Tehran University of Medical Sciences http://creativecommons.org/licenses/by-nc/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0), which allows users to read, copy, distribute and make derivative works for non-commercial purposes from the material, as long as the author of the original work is cited properly. |
spellingShingle | Original Articles Farhadian, M Mahjub, H Moghimbeigi, A Poorolajal, J Sadri, GH Classification of Death Rate due to Women’s Cancers in Different Countries |
title | Classification of Death Rate due to Women’s Cancers in Different Countries |
title_full | Classification of Death Rate due to Women’s Cancers in Different Countries |
title_fullStr | Classification of Death Rate due to Women’s Cancers in Different Countries |
title_full_unstemmed | Classification of Death Rate due to Women’s Cancers in Different Countries |
title_short | Classification of Death Rate due to Women’s Cancers in Different Countries |
title_sort | classification of death rate due to women’s cancers in different countries |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3468994/ https://www.ncbi.nlm.nih.gov/pubmed/23113194 |
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