Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statistic
OBJECTIVES The aim of this study was to explore the spatial pattern of female breast cancer (BC) incidence at the neighborhood level in Tehran, Iran. METHODS The present study included all registered incident cases of female BC from March 2008 to March 2011. The raw standardized incidence ratio (SIR...
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Korean Society of Epidemiology
2017-05-01
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doaj-1832918366c2400896c7099c6ed1d2bd2020-11-24T21:42:05ZengKorean Society of Epidemiology Epidemiology and Health2092-71932017-05-013910.4178/epih.e2017021909Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statisticErfan Ayubi0Mohammad Ali Mansournia1Ali Ghanbari Motlagh2Alireza Mosavi-Jarrahi3Ali Hosseini4Kamran Yazdani5 Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Department of Radiotherapy, Shahid Beheshti University of Medical Sciences, Tehran, Iran Department of Health and Community Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran Department of Geography and Urban Planning, University of Tehran, Tehran, Iran Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, IranOBJECTIVES The aim of this study was to explore the spatial pattern of female breast cancer (BC) incidence at the neighborhood level in Tehran, Iran. METHODS The present study included all registered incident cases of female BC from March 2008 to March 2011. The raw standardized incidence ratio (SIR) of BC for each neighborhood was estimated by comparing observed cases relative to expected cases. The estimated raw SIRs were smoothed by a Besag, York, and Mollie spatial model and the spatial empirical Bayesian method. The purely spatial scan statistic was used to identify spatial clusters. RESULTS There were 4,175 incident BC cases in the study area from 2008 to 2011, of which 3,080 were successfully geocoded to the neighborhood level. Higher than expected rates of BC were found in neighborhoods located in northern and central Tehran, whereas lower rates appeared in southern areas. The most likely cluster of higher than expected BC incidence involved neighborhoods in districts 3 and 6, with an observed-to-expected ratio of 3.92 (p<0.001), whereas the most likely cluster of lower than expected rates involved neighborhoods in districts 17, 18, and 19, with an observed-to-expected ratio of 0.05 (p<0.001). CONCLUSIONS Neighborhood-level inequality in the incidence of BC exists in Tehran. These findings can serve as a basis for resource allocation and preventive strategies in at-risk areas.http://www.e-epih.org/upload/pdf/epih-39-e2017021.pdfBreast neoplasmsSpatial analysisHealth status disparitiesIran |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Erfan Ayubi Mohammad Ali Mansournia Ali Ghanbari Motlagh Alireza Mosavi-Jarrahi Ali Hosseini Kamran Yazdani |
spellingShingle |
Erfan Ayubi Mohammad Ali Mansournia Ali Ghanbari Motlagh Alireza Mosavi-Jarrahi Ali Hosseini Kamran Yazdani Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statistic Epidemiology and Health Breast neoplasms Spatial analysis Health status disparities Iran |
author_facet |
Erfan Ayubi Mohammad Ali Mansournia Ali Ghanbari Motlagh Alireza Mosavi-Jarrahi Ali Hosseini Kamran Yazdani |
author_sort |
Erfan Ayubi |
title |
Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statistic |
title_short |
Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statistic |
title_full |
Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statistic |
title_fullStr |
Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statistic |
title_full_unstemmed |
Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statistic |
title_sort |
exploring neighborhood inequality in female breast cancer incidence in tehran using bayesian spatial models and a spatial scan statistic |
publisher |
Korean Society of Epidemiology |
series |
Epidemiology and Health |
issn |
2092-7193 |
publishDate |
2017-05-01 |
description |
OBJECTIVES The aim of this study was to explore the spatial pattern of female breast cancer (BC) incidence at the neighborhood level in Tehran, Iran. METHODS The present study included all registered incident cases of female BC from March 2008 to March 2011. The raw standardized incidence ratio (SIR) of BC for each neighborhood was estimated by comparing observed cases relative to expected cases. The estimated raw SIRs were smoothed by a Besag, York, and Mollie spatial model and the spatial empirical Bayesian method. The purely spatial scan statistic was used to identify spatial clusters. RESULTS There were 4,175 incident BC cases in the study area from 2008 to 2011, of which 3,080 were successfully geocoded to the neighborhood level. Higher than expected rates of BC were found in neighborhoods located in northern and central Tehran, whereas lower rates appeared in southern areas. The most likely cluster of higher than expected BC incidence involved neighborhoods in districts 3 and 6, with an observed-to-expected ratio of 3.92 (p<0.001), whereas the most likely cluster of lower than expected rates involved neighborhoods in districts 17, 18, and 19, with an observed-to-expected ratio of 0.05 (p<0.001). CONCLUSIONS Neighborhood-level inequality in the incidence of BC exists in Tehran. These findings can serve as a basis for resource allocation and preventive strategies in at-risk areas. |
topic |
Breast neoplasms Spatial analysis Health status disparities Iran |
url |
http://www.e-epih.org/upload/pdf/epih-39-e2017021.pdf |
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