Paper
24 March 2023 High-risk regional distribution of gynecopathy in China in 2020
Zilun Cai, Zhiang Cui, Ruchen Duan, Yingxi Jin
Author Affiliations +
Proceedings Volume 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022); 1261126 (2023) https://doi.org/10.1117/12.2669001
Event: International Conference on Biological Engineering and Medical Science (ICBioMed2022), 2022, Oxford, United Kingdom
Abstract
This paper mainly focuses on studying the regional distribution of the prevalence of six gynecological diseases across 31 provinces in China in 2020, followed by the description of prevalence in three representative regions in 2018-2020. As a result, offer suggested planning and reference frameworks at the regional level for China's prevention and care of women's health. By summarizing data from the 2021 China Health Statistics Yearbook report, a systematic cluster analysis was completed by factor analysis. Thirty-one provinces in China in 2020 were divided into three major categories according to the regional significance of women's cancer prevalence, and the clustering results showed that the prevalence of gynecological diseases in China had significant regional differences. The distribution of Chinese gynecological diseases is nonuniform. Governments should take targeted measures according to the differences in cluster results, which will help to develop various disease prevention and treatment strategies for reducing the risk of gynecological diseases.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zilun Cai, Zhiang Cui, Ruchen Duan, and Yingxi Jin "High-risk regional distribution of gynecopathy in China in 2020", Proc. SPIE 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022), 1261126 (24 March 2023); https://doi.org/10.1117/12.2669001
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KEYWORDS
Diseases and disorders

Cancer

Ovarian cancer

Cervical cancer

Factor analysis

Breast cancer

Matrices

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