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Spatial Autocorrelation of Cancer Incidence in Saudi Arabia
Little is known about the geographic distribution of common cancers in Saudi Arabia. We explored the spatial incidence patterns of common cancers in Saudi Arabia using spatial autocorrelation analyses, employing the global Moran’s I and Anselin’s local Moran’s I statistics to detect nonrandom incide...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3881162/ https://www.ncbi.nlm.nih.gov/pubmed/24351742 http://dx.doi.org/10.3390/ijerph10127207 |
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author | Al-Ahmadi, Khalid Al-Zahrani, Ali |
author_facet | Al-Ahmadi, Khalid Al-Zahrani, Ali |
author_sort | Al-Ahmadi, Khalid |
collection | PubMed |
description | Little is known about the geographic distribution of common cancers in Saudi Arabia. We explored the spatial incidence patterns of common cancers in Saudi Arabia using spatial autocorrelation analyses, employing the global Moran’s I and Anselin’s local Moran’s I statistics to detect nonrandom incidence patterns. Global ordinary least squares (OLS) regression and local geographically-weighted regression (GWR) were applied to examine the spatial correlation of cancer incidences at the city level. Population-based records of cancers diagnosed between 1998 and 2004 were used. Male lung cancer and female breast cancer exhibited positive statistically significant global Moran’s I index values, indicating a tendency toward clustering. The Anselin’s local Moran’s I analyses revealed small significant clusters of lung cancer, prostate cancer and Hodgkin’s disease among males in the Eastern region and significant clusters of thyroid cancers in females in the Eastern and Riyadh regions. Additionally, both regression methods found significant associations among various cancers. For example, OLS and GWR revealed significant spatial associations among NHL, leukemia and Hodgkin’s disease (r² = 0.49–0.67 using OLS and r² = 0.52–0.68 using GWR) and between breast and prostate cancer (r² = 0.53 OLS and 0.57 GWR) in Saudi Arabian cities. These findings may help to generate etiologic hypotheses of cancer causation and identify spatial anomalies in cancer incidence in Saudi Arabia. Our findings should stimulate further research on the possible causes underlying these clusters and associations. |
format | Online Article Text |
id | pubmed-3881162 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-38811622014-01-06 Spatial Autocorrelation of Cancer Incidence in Saudi Arabia Al-Ahmadi, Khalid Al-Zahrani, Ali Int J Environ Res Public Health Article Little is known about the geographic distribution of common cancers in Saudi Arabia. We explored the spatial incidence patterns of common cancers in Saudi Arabia using spatial autocorrelation analyses, employing the global Moran’s I and Anselin’s local Moran’s I statistics to detect nonrandom incidence patterns. Global ordinary least squares (OLS) regression and local geographically-weighted regression (GWR) were applied to examine the spatial correlation of cancer incidences at the city level. Population-based records of cancers diagnosed between 1998 and 2004 were used. Male lung cancer and female breast cancer exhibited positive statistically significant global Moran’s I index values, indicating a tendency toward clustering. The Anselin’s local Moran’s I analyses revealed small significant clusters of lung cancer, prostate cancer and Hodgkin’s disease among males in the Eastern region and significant clusters of thyroid cancers in females in the Eastern and Riyadh regions. Additionally, both regression methods found significant associations among various cancers. For example, OLS and GWR revealed significant spatial associations among NHL, leukemia and Hodgkin’s disease (r² = 0.49–0.67 using OLS and r² = 0.52–0.68 using GWR) and between breast and prostate cancer (r² = 0.53 OLS and 0.57 GWR) in Saudi Arabian cities. These findings may help to generate etiologic hypotheses of cancer causation and identify spatial anomalies in cancer incidence in Saudi Arabia. Our findings should stimulate further research on the possible causes underlying these clusters and associations. MDPI 2013-12-16 2013-12 /pmc/articles/PMC3881162/ /pubmed/24351742 http://dx.doi.org/10.3390/ijerph10127207 Text en © 2013 by the authors; licensee MDPI, Basel, Switzerland. http://creativecommons.org/licenses/by/3.0/ This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Al-Ahmadi, Khalid Al-Zahrani, Ali Spatial Autocorrelation of Cancer Incidence in Saudi Arabia |
title | Spatial Autocorrelation of Cancer Incidence in Saudi Arabia |
title_full | Spatial Autocorrelation of Cancer Incidence in Saudi Arabia |
title_fullStr | Spatial Autocorrelation of Cancer Incidence in Saudi Arabia |
title_full_unstemmed | Spatial Autocorrelation of Cancer Incidence in Saudi Arabia |
title_short | Spatial Autocorrelation of Cancer Incidence in Saudi Arabia |
title_sort | spatial autocorrelation of cancer incidence in saudi arabia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3881162/ https://www.ncbi.nlm.nih.gov/pubmed/24351742 http://dx.doi.org/10.3390/ijerph10127207 |
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