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A Geographic Analysis about the Spatiotemporal Pattern of Breast Cancer in Hangzhou from 2008 to 2012

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  • Xufeng Fei
  • Zhaohan Lou
  • George Christakos
  • Qingmin Liu
  • Yanjun Ren
  • Jiaping Wu

Abstract

Background: Breast cancer (BC) is the most common female malignant tumor. Previous studies have suggested a big incidence disparity among different cities in China. The present work selected a typical city, Hangzhou, to study BC incidence disparity within the city. Methods: Totally, 8784 female breast cancer cases were obtained from the Hangzhou Center for Disease Control and Prevention during the period 2008–2012. Analysis of Variance and Poisson Regression were the statistical tools implemented to compare incidence disparity in the space-time domain (reference group: township residents during 2008, area: subdistrict, town, and township, time frame: 2008–2012), space-time scan statistics was employed to detect significant spatiotemporal clusters of BC compared to the null hypothesis that the probability of cases diagnosed at a particular location was equal to the probability of cases diagnosed in the whole study area. Geographical Information System (GIS) was used to generate BC spatial distribution and cluster maps at the township level. Results: The subdistrict populations were found to have the highest and most stable BC incidence. Although town and township populations had a relatively low incidence, it displayed a significant increasing trend from 2008 to 2012. The BC incidence distribution was spatially heterogeneous and clustered with a trend-surface from the southwest low area to the northeast high area. High clusters were located in the northeastern Hangzhou area, whereas low clusters were observed in the southwestern area during the time considered. Conclusions: Better healthcare service and lifestyle changes may be responsible for the increasing BC incidence observed in towns and townships. One high incidence cluster (Linping subdistrict) and two low incidence clusters (middle Hangzhou) were detected. The low clusters may be attributable mainly to developmental level disparity, whereas the high cluster could be associated with other risk factors, such as environmental pollution.

Suggested Citation

  • Xufeng Fei & Zhaohan Lou & George Christakos & Qingmin Liu & Yanjun Ren & Jiaping Wu, 2016. "A Geographic Analysis about the Spatiotemporal Pattern of Breast Cancer in Hangzhou from 2008 to 2012," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-13, January.
    • Handle: RePEc:plo:pone00:0147866
    DOI: 10.1371/journal.pone.0147866
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    References listed on IDEAS

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    1. Xufeng Fei & Jiaping Wu & Zhe Kong & George Christakos, 2015. "Urban-Rural Disparity of Breast Cancer and Socioeconomic Risk Factors in China," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-15, February.
    2. Martin Kulldorff, 2001. "Prospective time periodic geographical disease surveillance using a scan statistic," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(1), pages 61-72.
    3. Christakos, George & Lai, Jaim-Jou, 1997. "A study of the breast cancer dynamics in North Carolina," Social Science & Medicine, Elsevier, vol. 45(10), pages 1503-1517, November.
    4. Zahra Cheraghi & Jalal Poorolajal & Tahereh Hashem & Nader Esmailnasab & Amin Doosti Irani, 2012. "Effect of Body Mass Index on Breast Cancer during Premenopausal and Postmenopausal Periods: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-9, December.
    5. O'Malley, M.S. & Earp, J.A.L. & Hawley, S.T. & Schell, M.J. & Mathews, H.F. & Mitchell, J., 2001. "The association of race/ethnicity, socioeconomic status, and physician recommendation for mammography: Who gets the message about breast cancer screening?," American Journal of Public Health, American Public Health Association, vol. 91(1), pages 49-54.
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