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

• Published in: PloS one 2016-01, Vol.11 (1), p.e0147866-e0147866
• Main Authors: Fei, Xufeng, Lou, Zhaohan, Christakos, George, Liu, Qingmin, Ren, Yanjun, Wu, Jiaping
• Format: Article
• Language: English
• Subjects: Biology and Life Sciences; Breast cancer; Breast Neoplasms - epidemiology; Cancer; China - epidemiology; Cities; Cluster Analysis; Clusters; Demographic aspects; Disease control; Earth Sciences; Environmental pollution; Environmental risk; Female; Geographic Information Systems; Health care; Health risk assessment; Humans; Incidence; Mammography; Medicine and Health Sciences; Mortality; Null hypothesis; People and Places; Physical sciences; Poisson density functions; Pollution abatement; Populations; Prevalence studies (Epidemiology); Regression analysis; Research and analysis methods; Risk analysis; Risk Factors; Satellite navigation systems; Social Sciences; Socioeconomic factors; Spatial distribution; Statistical analysis; Variance analysis
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0147866

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. 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. 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. 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.