Volume 9, Issue 1 (2018, Volume 9, Number 1 2018)
jdc 2018, 9(1): 35-45 |
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Ezimand K, Abdolahi Kakroodi A, Javanbakht M. Geographic distribution and incidence of skin cancer using the Geographically Weighted Regression model . jdc 2018; 9 (1) :35-45
URL: http://jdc.tums.ac.ir/article-1-5302-en.html
URL: http://jdc.tums.ac.ir/article-1-5302-en.html
1- Faculty of Geography, Tehran University, Tehran, Iran
2- Faculty of Geography, Tehran University, Tehran, Iran ,a.a.kakroodi@ut.ac.ir
2- Faculty of Geography, Tehran University, Tehran, Iran ,
Abstract: (4405 Views)
Background and Aim: Environmental and climatic conditions in different geographical areas provide the basis for certain diseases. Skin cancer is one of the most common types of cancer, with a different incidence rate in geographical areas. The aim of this study is to determine the effects of climate and environmental factors on skin cancer and to map the geographical distribution of skin cancer in Iran.
Methods: This study was performed using data of patients with skin cancer, population and data of climatic and environmental factors that affect skin cancer incidence. In this study, after calculating the incidence of skin cancer rate for the whole country, we used the Geographically Weighted Regression model to establish a regression relationship between climate and environmental data and the incidence of skin cancer. The coefficient of detection between the map of incidence of skin cancer and its model map was calculated.
Results: Correlation coefficients showed that sun UV and relative humidity had the highest positive and negative correlation with the incidence of skin cancer, respectively. The southern, eastern and central regions of Iran had the highest incidence of skin cancer rate and the northern and northwestern coasts of Iran had the lowest incidence rate. Validating of actual incidence rate map and the modeled incidence rate map indicated a coefficient of detection of 0.71.
Conclusion: All of the climate and environmental parameters in this study contributed to in the incidence of skin cancer.
Methods: This study was performed using data of patients with skin cancer, population and data of climatic and environmental factors that affect skin cancer incidence. In this study, after calculating the incidence of skin cancer rate for the whole country, we used the Geographically Weighted Regression model to establish a regression relationship between climate and environmental data and the incidence of skin cancer. The coefficient of detection between the map of incidence of skin cancer and its model map was calculated.
Results: Correlation coefficients showed that sun UV and relative humidity had the highest positive and negative correlation with the incidence of skin cancer, respectively. The southern, eastern and central regions of Iran had the highest incidence of skin cancer rate and the northern and northwestern coasts of Iran had the lowest incidence rate. Validating of actual incidence rate map and the modeled incidence rate map indicated a coefficient of detection of 0.71.
Conclusion: All of the climate and environmental parameters in this study contributed to in the incidence of skin cancer.
Type of Study: Research |
Subject:
Special
Received: 2018/06/18 | Accepted: 2018/06/18 | Published: 2018/06/18
Received: 2018/06/18 | Accepted: 2018/06/18 | Published: 2018/06/18
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