IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i5p784-d210801.html
   My bibliography  Save this article

Spatiotemporal Variations in Gastric Cancer Mortality and Their Relations to Influencing Factors in S County, China

Author

Listed:
  • Cheng Cui

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Baohua Wang

    (National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China)

  • Hongyan Ren

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Zhen Wang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Increasingly stricter and wider official efforts have been made by multilevel Chinese governments for seeking the improvements of the environment and public health status. However, the contributions of these efforts to environmental changes and spatiotemporal variations in some environmental diseases have been seldom explored and evaluated. Gastric cancer mortality (GCM) data in two periods (I: 2004–2006 and II: 2012–2015) was collected for the analysis of its spatiotemporal variations on the grid scale across S County in Central China. Some environmental and socioeconomic factors, including river, farmlands, topographic condition, population density, and gross domestic products (GDP) were obtained for the exploration of their changes and their relationships with GCM’s spatiotemporal variations through a powerful tool (GeoDetector, GD). During 2004–2015, S County achieved environmental improvement and socioeconomic development, as well as a clear decline of the age-standardized mortality rate of gastric cancer from 35.66/10 5 to 23.44/10 5 . Moreover, the GCM spatial patterns changed on the grid scale, which was spatially associated with the selected influencing factors. Due to the improvement of rivers’ water quality, the distance from rivers posed relatively larger but reversed impacts on the gridded GCM. In addition, higher population density and higher economic level (GDP) acted as important protective factors, whereas the percentage of farmlands tended to have adverse effects on the gridded GCM in period II. It can be concluded that the decline of GCM in S County was spatiotemporally associated with increasingly strengthened environmental managements and socioeconomic developments over the past decade. Additionally, we suggest that more attentions should be paid to the potential pollution caused by excessive pesticides and fertilizers on the farmlands in S County. This study provided a useful clue for local authorities adopting more targeted measures to improve environment and public health in the regions similar to S County.

Suggested Citation

  • Cheng Cui & Baohua Wang & Hongyan Ren & Zhen Wang, 2019. "Spatiotemporal Variations in Gastric Cancer Mortality and Their Relations to Influencing Factors in S County, China," IJERPH, MDPI, vol. 16(5), pages 1-13, March.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:5:p:784-:d:210801
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/5/784/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/16/5/784/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Luc Anselin & Sergio J. Rey, 2010. "Perspectives on Spatial Data Analysis," Advances in Spatial Science, in: Luc Anselin & Sergio J. Rey (ed.), Perspectives on Spatial Data Analysis, chapter 0, pages 1-20, Springer.
    2. Jialu Liu Streeter, 2017. "Socioeconomic Factors Affecting Food Consumption and Nutrition in China: Empirical Evidence During the 1989–2009 Period," Chinese Economy, Taylor & Francis Journals, vol. 50(3), pages 168-192, May.
    3. Yingru Li & Huixuan Li & Zhongwei Liu & Changhong Miao, 2016. "Spatial Assessment of Cancer Incidences and the Risks of Industrial Wastewater Emission in China," Sustainability, MDPI, vol. 8(5), pages 1-19, May.
    4. Cohen, Deborah A. & Farley, Thomas A. & Mason, Karen, 2003. "Why is poverty unhealthy? Social and physical mediators," Social Science & Medicine, Elsevier, vol. 57(9), pages 1631-1641, November.
    5. Jixia Huang & Jinfeng Wang & Yanchen Bo & Chengdong Xu & Maogui Hu & Dacang Huang, 2014. "Identification of Health Risks of Hand, Foot and Mouth Disease in China Using the Geographical Detector Technique," IJERPH, MDPI, vol. 11(3), pages 1-17, March.
    6. Hongyan Ren & Xia Wan & Fei Yang & Xiaoming Shi & Jianwei Xu & Dafang Zhuang & Gonghuan Yang, 2014. "Association between Changing Mortality of Digestive Tract Cancers and Water Pollution: A Case Study in the Huai River Basin, China," IJERPH, MDPI, vol. 12(1), pages 1-13, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cheng Cui & Hang Dong & Hongyan Ren & Guozhen Lin & Lu Zhao, 2020. "Characterization of Esophageal Cancer and Its Association with Influencing Factors in Guangzhou City, China," IJERPH, MDPI, vol. 17(5), pages 1-14, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cheng Cui & Hang Dong & Hongyan Ren & Guozhen Lin & Lu Zhao, 2020. "Characterization of Esophageal Cancer and Its Association with Influencing Factors in Guangzhou City, China," IJERPH, MDPI, vol. 17(5), pages 1-14, February.
    2. F. Marta L. Di Lascio & Andrea Menapace & Roberta Pappadà, 2024. "A spatially‐weighted AMH copula‐based dissimilarity measure for clustering variables: An application to urban thermal efficiency," Environmetrics, John Wiley & Sons, Ltd., vol. 35(1), February.
    3. John I. Carruthers & Selma Hepp & Gerrit-Jan Knaap & Robert N. Renner, 2012. "The American Way of Land Use," International Regional Science Review, , vol. 35(3), pages 267-302, July.
    4. Oumarou Zallé & Idrissa M. Ouédraogo, 2021. "Spillover effects of corruption and democracy on territorial attractiveness of foreign direct investment in sub‐Saharan Africa," African Development Review, African Development Bank, vol. 33(4), pages 756-769, December.
    5. Nijkamp Peter, 2012. "Behaviour of Humans and Behaviour of Models in Dynamic Space," Quaestiones Geographicae, Sciendo, vol. 31(2), pages 7-19, June.
    6. Han Yue & Tao Hu, 2021. "Geographical Detector-Based Spatial Modeling of the COVID-19 Mortality Rate in the Continental United States," IJERPH, MDPI, vol. 18(13), pages 1-16, June.
    7. Kang Hou & Xuxiang Li & Jing Zhang, 2015. "GIS Analysis of Changes in Ecological Vulnerability Using a SPCA Model in the Loess Plateau of Northern Shaanxi, China," IJERPH, MDPI, vol. 12(4), pages 1-14, April.
    8. repec:iab:iabjlr:v:55:i::p:art.11 is not listed on IDEAS
    9. Jose A. Salinas-Perez & Esteban Ruiz-Ballesteros & Auxiliadora González-Portillo, 2024. "Analysis of the funding of social services from a spatial approach in Andalusia (Spain)," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-8, December.
    10. Lee, Matthew R., 2010. "The protective effects of civic communities against all-cause mortality," Social Science & Medicine, Elsevier, vol. 70(11), pages 1840-1846, June.
    11. Stephen Matthews & Daniel M. Parker, 2013. "Progress in Spatial Demography," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(10), pages 271-312.
    12. Sunak, Yasin & Madlener, Reinhard, 2016. "The impact of wind farm visibility on property values: A spatial difference-in-differences analysis," Energy Economics, Elsevier, vol. 55(C), pages 79-91.
    13. Chuanglin Fang & Haimeng Liu & Guangdong Li & Dongqi Sun & Zhuang Miao, 2015. "Estimating the Impact of Urbanization on Air Quality in China Using Spatial Regression Models," Sustainability, MDPI, vol. 7(11), pages 1-23, November.
    14. Lechuga-Rodriguez, Eduardo Luis, 2022. "Clustering of food poverty among Mexican children: A spatial analysis," Children and Youth Services Review, Elsevier, vol. 138(C).
    15. Michael Manton & Evaldas Makrickas & Piotr Banaszuk & Aleksander Kołos & Andrzej Kamocki & Mateusz Grygoruk & Marta Stachowicz & Leonas Jarašius & Nerijus Zableckis & Jūratė Sendžikaitė & Jan Peters &, 2021. "Assessment and Spatial Planning for Peatland Conservation and Restoration: Europe’s Trans-Border Neman River Basin as a Case Study," Land, MDPI, vol. 10(2), pages 1-27, February.
    16. Yunlin He & Yanhua Mo & Jiangming Ma, 2022. "Spatio-Temporal Evolution and Influence Mechanism of Habitat Quality in Guilin City, China," IJERPH, MDPI, vol. 20(1), pages 1-15, December.
    17. Li,Yue - SARCE & Rama,Martin G., 2015. "Households or locations ? cities, catchment areas and prosperity in India," Policy Research Working Paper Series 7473, The World Bank.
    18. Zhensheng Wang & Ke Nie, 2017. "Measuring Spatial Distribution Characteristics of Heavy Metal Contaminations in a Network-Constrained Environment: A Case Study in River Network of Daye, China," Sustainability, MDPI, vol. 9(6), pages 1-11, June.
    19. Mkondiwa, Maxwell Gibson, 2015. "Whither Broad or Spatially Specific Fertilizer Recommendations?," Master's Theses and Plan B Papers 237344, University of Minnesota, Department of Applied Economics.
    20. Qin Liu & Tiange Shi, 2019. "Spatiotemporal Differentiation and the Factors of Ecological Vulnerability in the Toutun River Basin Based on Remote Sensing Data," Sustainability, MDPI, vol. 11(15), pages 1-19, August.
    21. Xinguang Chen & Peigang Wang & Rhiana Wegner & Jie Gong & Xiaoyi Fang & Linda Kaljee, 2015. "Measuring Social Capital Investment: Scale Development and Examination of Links to Social Capital and Perceived Stress," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 120(3), pages 669-687, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:16:y:2019:i:5:p:784-:d:210801. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.