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. 2023 Jun 30;23:346. doi: 10.1186/s12905-023-02384-2

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 1 — Projected gynecological cancer cases in China, 2017–2030, in total population (A), in urban females (B), and in rural females (C). The figure contains three panels. The first (A) is a line graph of different projected gynecological cancer cases among the total population, with the case on the y-axis and year on the x-axis. The second (B) is a line graph of different projected gynecological cancer cases among urban females, with the case on the y-axis and year on the x-axis. The third (C) is a line graph of different projected gynecological cancer cases among rural females, with the case on the y-axis and year on the x-axis. The legend on the top displays the line shape and color of each gynecological cancer and the legend is commonly applied to all three panels in this figure. For the three panels in this figure, the cancer cases during 2007–2016 is calculated by multiplying age-specific rates with the estimated population size, while the cancer cases during 2017–2030 is projected using grey prediction model GM (1,1). More details on the data source and statistical methods of estimation and prediction can be referred to Materials and Methods section.