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伊朗非黑素瘤皮肤癌与气候变化的地理空间模式关系。

Geospatial Patterns of Non-Melanoma Skin Cancer in Relation to Climate Changes in Iran.

机构信息

Department of Dentistry, School of Dentistry, Medical University, Tehran, Iran.

出版信息

Asian Pac J Cancer Prev. 2024 Mar 1;25(3):1053-1063. doi: 10.31557/APJCP.2024.25.3.1053.

Abstract

OBJECTIVE

The purpose of this study is to examine the impact of climate change factors on the incidence of skin cancer in Iran.

METHODS

The statistical population for this study comprises skin cancer patients in Iran. All other data used in this research were extracted from Remote Sensing imagery, including Ultraviolet ray, Relative humidity, Cloud cover, incoming short-wave flux, elevation, and total hours of sunshine. Initially, spatial autocorrelation analysis and cluster patterns were calculated using General G and Moran's I indices. Subsequently, a Geographically Weighted Regression Model was used to establish a regression relationship between the climate change data and the detection and forecasting rate of skin cancer. Finally, the model's accuracy was evaluated by estimating the detection coefficient between the reality map and the forecasting map.

RESULTS

The study found that UV radiation and relative humidity exhibit the highest positive and negative correlation, respectively, with the skin cancer rate in Iran. Geostatistical analysis revealed a clustered spatial distribution of skin cancer rates, and the proposed GWR model demonstrated high accuracy in predicting the skin cancer rate. The results indicate the highest positive correlation (+0.51) for UV ray and the most negative correlation (-0.43) for relative humidity. The Geostatistical analysis reveals spatial autocorrelation, cluster patterns, and non-randomness of the data.

CONCLUSION

The detection rate of skin cancer increases from north to south and from west to east.

摘要

目的

本研究旨在探讨气候变化因素对伊朗皮肤癌发病率的影响。

方法

本研究的统计人群包括伊朗的皮肤癌患者。本研究中使用的所有其他数据均从遥感图像中提取,包括紫外线、相对湿度、云量、入射短波通量、海拔和总日照时数。首先,使用全局 G 和 Moran's I 指数计算空间自相关分析和聚类模式。然后,使用地理加权回归模型建立气候变化数据与皮肤癌检测和预测率之间的回归关系。最后,通过估计现实图和预测图之间的检测系数来评估模型的准确性。

结果

研究发现,紫外线辐射和相对湿度分别与伊朗皮肤癌发病率呈最高的正相关和负相关。地统计学分析显示皮肤癌发病率呈聚类空间分布,所提出的 GWR 模型在预测皮肤癌发病率方面具有很高的准确性。结果表明,紫外线的正相关最高(+0.51),相对湿度的负相关最大(-0.43)。地统计学分析揭示了数据的空间自相关、聚类模式和非随机性。

结论

皮肤癌的检出率从北到南、从西到东逐渐增加。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/24d4/11152402/fa270aaf4a53/APJCP-25-1053-g001.jpg

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