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...
| Published in: | Iranian Journal of Public Health Vol. 41; no. 6; pp. 58 - 65 |
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| Main Authors: | , , , , |
| Format: | research tables/charts Journal Article |
| Published: |
Tehran University of Medical Sciences
2012
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=77298824&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 77298824 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 22516085 6N6F jtl: Iranian Journal of Public Health issn: 22516085 maglogo: N pubinfo: dt: 2012 vid: 41 iid: 6 pid: 21783 pub: Tehran University of Medical Sciences artinfo: ui: 77298824 77298824 104467452 77298824 ppf: 58 ppct: 7 formats: fmt: @attributes: type: P tig: atl: Classification of Death Rate due to Women's Cancers in Different Countries. aug: au: Farhadian, M Mahjub, H Moghimbeigi, A Poorolajal, J Sadri, GH affil: Dept. of Biostatistics & Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran sug: subj: Neoplasms Mortality World Health Women's Health Evaluation Funding Source Human Female Cross Sectional Studies Descriptive Statistics Female ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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