IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i5p1498-d325265.html
   My bibliography  Save this article

Characterization of Esophageal Cancer and Its Association with Influencing Factors in Guangzhou City, 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 100190, China
    These authors contributed equally to this work.)

  • Hang Dong

    (Department of Biostatistics and Cancer Registration, Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China
    These authors contributed equally to this work.)

  • 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)

  • Guozhen Lin

    (Department of Biostatistics and Cancer Registration, Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China)

  • Lu Zhao

    (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 100190, China)

Abstract

Epidemiological features of esophageal cancer (EC), as well as their associations with potential influencing factors in a city, have seldom been seldom explored on a fine scale. The EC death cases in Guangzhou city during 2012−2017 were collected to describe the epidemiological characteristics such as EC mortality rate (ECMR) and health-seeking behaviors of deaths. Potential influencing factors, including socioeconomic conditions (population density, gross domestic product density), medical resources, and ageing degree were also gathered for exploring their relationships with the epidemiological characteristics of EC. A total of 2,409 EC deaths were reported during 2012−2017 in Guangzhou with an age-standardized ECMR of 3.18/10 5 . The prevalence of EC in Guangzhou was spatially featured and was divided into three regions with obvious differentiated ECMR (ECMR of 6.41/10 5 in region A, ECMR of 5.51/10 5 in region B, ECMR of 2.56/10 5 in region C). The street/town-level ECMR was spatially clustered in Guangzhou city, especially two clusters of streets/towns with high ECMR were highlighted in region A and B respectively. Meanwhile, demographic features including gender gap, death age, temporal interval between diagnosis and death, health-seeking behaviors were remarkably different among the three regions. Moreover, health-seeking behaviors (e.g., the proportion of hospital deaths) of the EC deaths were obviously influenced by medical institution occupancy rate and socioeconomic conditions at street/town level. In addition, the street/town-level ECMR was significantly associated with ageing degree across Guangzhou city (r = 0.466, p < 0.01), especially in region A (r = 0.565, p < 0.01). In contrast, the ECMR in region B was closely related to population density (r = −0.524, p < 0.01) and gross domestic product density (r = −0.511, p < 0.01) when the ageing degree was controlled, while these associations were weak in region C. The epidemiological characteristics of EC in Guangzhou city were spatially featured and potentially associated with socioeconomic conditions, medical resources and ageing degree on a fine scale across Guangzhou city. This study could provide scientific basis for local authorities to implement more targeted EC interventions.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:5:p:1498-:d:325265
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/5/1498/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/5/1498/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Anselin, Luc & Getis, Arthur, 1992. "Spatial Statistical Analysis and Geographic Information Systems," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 26(1), pages 19-33, April.
    2. 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.
    3. 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.
    4. 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.
    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. Zhen Wang & Hongyan Ren & An Zhang & Dafang Zhuang, 2021. "Spatiotemporal Hotspots of Study Areas in Research of Gastric Cancer in China Based on Web-Crawled Literature," IJERPH, MDPI, vol. 18(8), pages 1-14, April.

    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 & 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.
    2. Ye, Xinyue & Yue, Wenze, 2014. "Comparative analysis of regional development: Exploratory space-time data analysis and open source implementation," Economics Discussion Papers 2014-20, Kiel Institute for the World Economy (IfW Kiel).
    3. 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.
    4. Chibuzor Christopher Nnanatu & Glory Atilola & Paul Komba & Lubanzadio Mavatikua & Zhuzhi Moore & Dennis Matanda & Otibho Obianwu & Ngianga-Bakwin Kandala, 2021. "Evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in Nigeria using data from multiple surveys: A novel Bayesian hierarchical spatio-temporal model," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-31, February.
    5. Heba, Ines & Malin, Eric & Thomas-Agnan, Christine, 2002. "Exploratory spatial data analysis with GEOXP," ERSA conference papers ersa02p498, European Regional Science Association.
    6. Jianglong Chen & Jinlong Gao & Feng Yuan & Yehua Dennis Wei, 2016. "Spatial Determinants of Urban Land Expansion in Globalizing Nanjing, China," Sustainability, MDPI, vol. 8(9), pages 1-25, August.
    7. 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.
    8. Atílio Peixoto Soares Júnior & Cátia Regina Franco Zucoloto & Olívia André & Emerson Wagner Mainardes, 2019. "Healthy food purchasing behavior for children," International Review on Public and Nonprofit Marketing, Springer;International Association of Public and Non-Profit Marketing, vol. 16(1), pages 103-124, March.
    9. Cohen, Deborah A. & Finch, Brian K. & Bower, Aimee & Sastry, Narayan, 2006. "Collective efficacy and obesity: The potential influence of social factors on health," Social Science & Medicine, Elsevier, vol. 62(3), pages 769-778, February.
    10. Douven, W., 1992. "Urban and regional planning models and GIS," Serie Research Memoranda 0074, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    11. Fischer, Manfred M. & Openshaw, Stan, 1995. "A Framework for Research on Spatial Analysis Relevant to Geo-Statistical Informations Systems in Europe," MPRA Paper 77814, University Library of Munich, Germany.
    12. Gehendra Mahara & Chao Wang & Da Huo & Qin Xu & Fangfang Huang & Lixin Tao & Jin Guo & Kai Cao & Liu Long & Jagadish K. Chhetri & Qi Gao & Wei Wang & Quanyi Wang & Xiuhua Guo, 2016. "Spatiotemporal Pattern Analysis of Scarlet Fever Incidence in Beijing, China, 2005–2014," IJERPH, MDPI, vol. 13(1), pages 1-17, January.
    13. Liu, Gengyuan & Du, Shupan & Gao, Yuan & Xiong, Xiaoping & Lombardi, Ginevra Virginia & Meng, Fanxin & Chen, Yu & Chen, Caocao, 2024. "A study on energy-water-food-carbon nexus in typical Chinese northern rural households," Energy Policy, Elsevier, vol. 188(C).
    14. Yuying Tong & Weixiang Luo & Martin Piotrowski, 2015. "The Association Between Parental Migration and Childhood Illness in Rural China," European Journal of Population, Springer;European Association for Population Studies, vol. 31(5), pages 561-586, December.
    15. Mohamed Ayadi & Mohamed Amara, 2009. "Spatial Patterns and Geographic Determinants of Welfare and Poverty in Tunisia," Working Papers 478, Economic Research Forum, revised Mar 2009.
    16. Bjornstrom, Eileen E.S., 2011. "The neighborhood context of relative position, trust, and self-rated health," Social Science & Medicine, Elsevier, vol. 73(1), pages 42-49, July.
    17. McDade, Thomas W. & Koning, Stephanie M., 2021. "Early origins of socioeconomic inequalities in chronic inflammation: Evaluating the contributions of low birth weight and short breastfeeding," Social Science & Medicine, Elsevier, vol. 269(C).
    18. Nandi, Arijit & Galea, Sandro & Ahern, Jennifer & Bucciarelli, Angela & Vlahov, David & Tardiff, Kenneth, 2006. "What explains the association between neighborhood-level income inequality and the risk of fatal overdose in New York City?," Social Science & Medicine, Elsevier, vol. 63(3), pages 662-674, August.
    19. Guangyue Nian & Bozhezi Peng & Daniel (Jian) Sun & Wenjun Ma & Bo Peng & Tianyuan Huang, 2020. "Impact of COVID-19 on Urban Mobility during Post-Epidemic Period in Megacities: From the Perspectives of Taxi Travel and Social Vitality," Sustainability, MDPI, vol. 12(19), pages 1-29, September.
    20. van Hooijdonk, Carolien & Droomers, Mariël & van Loon, Jeanne A.M. & van der Lucht, Fons & Kunst, Anton E., 2007. "Exceptions to the rule: Healthy deprived areas and unhealthy wealthy areas," Social Science & Medicine, Elsevier, vol. 64(6), pages 1326-1342, March.

    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:17:y:2020:i:5:p:1498-:d:325265. 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.