Assessing the effect of environmental and socio-economic factors on skin melanoma incidence: an island-wide spatial study in Gran Canaria (Spain), 2007–2018
Introduction Skin melanoma incidence has risen in the last decades becoming a major public health problem in many regions of the world. Geographic variation of rates is not well understood. Purpose To assess the spatial distribution of skin melanoma in Gran Canaria Island (Canary Islands, Spain) and...
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| Veröffentlicht in: | Cancer causes & control 2022-10, Vol.33 (10), p.1261-1272 |
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| creator | Grau-Pérez, Mercè Borrego, Leopoldo Carretero, Gregorio Almeida, Pablo Cano, Jorge |
| description | Introduction
Skin melanoma incidence has risen in the last decades becoming a major public health problem in many regions of the world. Geographic variation of rates is not well understood.
Purpose
To assess the spatial distribution of skin melanoma in Gran Canaria Island (Canary Islands, Spain) and to evaluate the role of environmental, socio-economic, and demographic factors in this distribution.
Methods
We performed a small-area study with disease mapping at the census-tract level (CT) in Gran Canaria between 2007 and 2018. After testing for spatial autocorrelation, we integrated individual-level health data with census-based demographic and socio-economic indicators, and satellite-based environmental data. Finally, we assessed the role of demographic, socio-economic and environmental factors on skin melanoma incidence using a Bayesian analytical framework, with options for non-spatial and spatial random effects.
Results
1058 patients were diagnosed with invasive skin melanoma in the study period and geolocated to a CT (number of CT in Gran Canaria = 565). We found evidence of global spatial autocorrelation in skin melanoma incidence (Moran’s
I
= 0.09, pseudo
p
-value = 0.001). A few hotspots were detected, fundamentally in urban northern tracts. A radial pattern of high values was also observed in selected ravines with historical isolation. Multivariable conditional autoregressive models identified urbanicity, percent of females, and a high socio-economic status as risk factors for disease. Solar radiation did not show a significant role.
Conclusion
Urbanicity and a high socio-economic status were identified as the main risk factors for skin melanoma. These associations might reflect differential melanoma susceptibilities or be explained by health inequalities in detection. This study also uncovered high-risk areas in particular ravines. Future targeted research in these regions might help better understand the role of genetic and toxic factors in melanoma pathogenesis. |
| doi_str_mv | 10.1007/s10552-022-01614-6 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9427872</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2708087100</sourcerecordid><originalsourceid>FETCH-LOGICAL-c404t-855a02accaf1dee2961ea619104f6acd0f658d372140e78d5eb5b920b8539e613</originalsourceid><addsrcrecordid>eNp9kbFuFDEQhi0EIkfgBSiQJRqQWBh71-tdCqToFAJSJAqgtubs8cXh1j7svaB0vAN9Ho4nwXAhQENhWZr_n39m9DH2UMBzAaBfFAFKyQZkfaIXXdPfYguhdNtoKdVttoBR6UbJrj1g90o5BwDVS7jLDlo1StWN44JdHZVCpYS45vMZcfKe7MyT5xQvQk5xojjjhmN0vCQbUkM2xTQFyz3aOeXCU-TlU4h8og1WBXmINjiKll7WNh5KLbvmSy3xssU51LQy79xl9fGTXB1LjJgD8ifvtxji02dc1uO-f_0mQQz32R2Pm0IPrv9D9vH18Yflm-b03cnb5dFpYzvo5mZQCkGiteiFI5JjLwh7MQrofI_Wge_V4FotRQekB6dopVajhNWg2pF60R6yV_vc7W41kbP16owbs81hwnxpEgbzrxLDmVmnCzN2Ug9a1oDH1wE5fd5Rmc152uVYdzZSwwCDrsiqS-5dNqdSMvmbCQLMT6Zmz9RUpuYXU9PXpkd_73bT8htiNbR7Q6lSXFP-M_s_sT8Akxmu_A</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2708087100</pqid></control><display><type>article</type><title>Assessing the effect of environmental and socio-economic factors on skin melanoma incidence: an island-wide spatial study in Gran Canaria (Spain), 2007–2018</title><source>MEDLINE</source><source>SpringerLink Journals - AutoHoldings</source><creator>Grau-Pérez, Mercè ; Borrego, Leopoldo ; Carretero, Gregorio ; Almeida, Pablo ; Cano, Jorge</creator><creatorcontrib>Grau-Pérez, Mercè ; Borrego, Leopoldo ; Carretero, Gregorio ; Almeida, Pablo ; Cano, Jorge</creatorcontrib><description>Introduction
Skin melanoma incidence has risen in the last decades becoming a major public health problem in many regions of the world. Geographic variation of rates is not well understood.
Purpose
To assess the spatial distribution of skin melanoma in Gran Canaria Island (Canary Islands, Spain) and to evaluate the role of environmental, socio-economic, and demographic factors in this distribution.
Methods
We performed a small-area study with disease mapping at the census-tract level (CT) in Gran Canaria between 2007 and 2018. After testing for spatial autocorrelation, we integrated individual-level health data with census-based demographic and socio-economic indicators, and satellite-based environmental data. Finally, we assessed the role of demographic, socio-economic and environmental factors on skin melanoma incidence using a Bayesian analytical framework, with options for non-spatial and spatial random effects.
Results
1058 patients were diagnosed with invasive skin melanoma in the study period and geolocated to a CT (number of CT in Gran Canaria = 565). We found evidence of global spatial autocorrelation in skin melanoma incidence (Moran’s
I
= 0.09, pseudo
p
-value = 0.001). A few hotspots were detected, fundamentally in urban northern tracts. A radial pattern of high values was also observed in selected ravines with historical isolation. Multivariable conditional autoregressive models identified urbanicity, percent of females, and a high socio-economic status as risk factors for disease. Solar radiation did not show a significant role.
Conclusion
Urbanicity and a high socio-economic status were identified as the main risk factors for skin melanoma. These associations might reflect differential melanoma susceptibilities or be explained by health inequalities in detection. This study also uncovered high-risk areas in particular ravines. Future targeted research in these regions might help better understand the role of genetic and toxic factors in melanoma pathogenesis.</description><identifier>ISSN: 0957-5243</identifier><identifier>EISSN: 1573-7225</identifier><identifier>DOI: 10.1007/s10552-022-01614-6</identifier><identifier>PMID: 35925499</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Autocorrelation ; Autoregressive models ; Bayes Theorem ; Bayesian analysis ; Biomedical and Life Sciences ; Biomedicine ; Cancer Research ; Census ; Demographics ; Demography ; Economic Factors ; Economics ; Environmental effects ; Environmental factors ; Epidemiology ; Female ; Gene mapping ; Geographical variations ; Hematology ; Humans ; Incidence ; Mathematical models ; Melanoma ; Melanoma - epidemiology ; Melanoma - etiology ; Oncology ; Original Paper ; Public Health ; Ravines ; Risk analysis ; Risk factors ; Skin ; Skin cancer ; Social factors ; Socioeconomic Factors ; Socioeconomics ; Solar radiation ; Spain - epidemiology ; Spatial distribution</subject><ispartof>Cancer causes & control, 2022-10, Vol.33 (10), p.1261-1272</ispartof><rights>The Author(s) 2022</rights><rights>2022. The Author(s).</rights><rights>The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c404t-855a02accaf1dee2961ea619104f6acd0f658d372140e78d5eb5b920b8539e613</citedby><cites>FETCH-LOGICAL-c404t-855a02accaf1dee2961ea619104f6acd0f658d372140e78d5eb5b920b8539e613</cites><orcidid>0000-0002-0199-2756 ; 0000-0003-2608-0400 ; 0000-0002-2469-3417 ; 0000-0001-9864-5058 ; 0000-0002-7628-3495</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10552-022-01614-6$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10552-022-01614-6$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35925499$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Grau-Pérez, Mercè</creatorcontrib><creatorcontrib>Borrego, Leopoldo</creatorcontrib><creatorcontrib>Carretero, Gregorio</creatorcontrib><creatorcontrib>Almeida, Pablo</creatorcontrib><creatorcontrib>Cano, Jorge</creatorcontrib><title>Assessing the effect of environmental and socio-economic factors on skin melanoma incidence: an island-wide spatial study in Gran Canaria (Spain), 2007–2018</title><title>Cancer causes & control</title><addtitle>Cancer Causes Control</addtitle><addtitle>Cancer Causes Control</addtitle><description>Introduction
Skin melanoma incidence has risen in the last decades becoming a major public health problem in many regions of the world. Geographic variation of rates is not well understood.
Purpose
To assess the spatial distribution of skin melanoma in Gran Canaria Island (Canary Islands, Spain) and to evaluate the role of environmental, socio-economic, and demographic factors in this distribution.
Methods
We performed a small-area study with disease mapping at the census-tract level (CT) in Gran Canaria between 2007 and 2018. After testing for spatial autocorrelation, we integrated individual-level health data with census-based demographic and socio-economic indicators, and satellite-based environmental data. Finally, we assessed the role of demographic, socio-economic and environmental factors on skin melanoma incidence using a Bayesian analytical framework, with options for non-spatial and spatial random effects.
Results
1058 patients were diagnosed with invasive skin melanoma in the study period and geolocated to a CT (number of CT in Gran Canaria = 565). We found evidence of global spatial autocorrelation in skin melanoma incidence (Moran’s
I
= 0.09, pseudo
p
-value = 0.001). A few hotspots were detected, fundamentally in urban northern tracts. A radial pattern of high values was also observed in selected ravines with historical isolation. Multivariable conditional autoregressive models identified urbanicity, percent of females, and a high socio-economic status as risk factors for disease. Solar radiation did not show a significant role.
Conclusion
Urbanicity and a high socio-economic status were identified as the main risk factors for skin melanoma. These associations might reflect differential melanoma susceptibilities or be explained by health inequalities in detection. This study also uncovered high-risk areas in particular ravines. Future targeted research in these regions might help better understand the role of genetic and toxic factors in melanoma pathogenesis.</description><subject>Autocorrelation</subject><subject>Autoregressive models</subject><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Cancer Research</subject><subject>Census</subject><subject>Demographics</subject><subject>Demography</subject><subject>Economic Factors</subject><subject>Economics</subject><subject>Environmental effects</subject><subject>Environmental factors</subject><subject>Epidemiology</subject><subject>Female</subject><subject>Gene mapping</subject><subject>Geographical variations</subject><subject>Hematology</subject><subject>Humans</subject><subject>Incidence</subject><subject>Mathematical models</subject><subject>Melanoma</subject><subject>Melanoma - epidemiology</subject><subject>Melanoma - etiology</subject><subject>Oncology</subject><subject>Original Paper</subject><subject>Public Health</subject><subject>Ravines</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Skin</subject><subject>Skin cancer</subject><subject>Social factors</subject><subject>Socioeconomic Factors</subject><subject>Socioeconomics</subject><subject>Solar radiation</subject><subject>Spain - epidemiology</subject><subject>Spatial distribution</subject><issn>0957-5243</issn><issn>1573-7225</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp9kbFuFDEQhi0EIkfgBSiQJRqQWBh71-tdCqToFAJSJAqgtubs8cXh1j7svaB0vAN9Ho4nwXAhQENhWZr_n39m9DH2UMBzAaBfFAFKyQZkfaIXXdPfYguhdNtoKdVttoBR6UbJrj1g90o5BwDVS7jLDlo1StWN44JdHZVCpYS45vMZcfKe7MyT5xQvQk5xojjjhmN0vCQbUkM2xTQFyz3aOeXCU-TlU4h8og1WBXmINjiKll7WNh5KLbvmSy3xssU51LQy79xl9fGTXB1LjJgD8ifvtxji02dc1uO-f_0mQQz32R2Pm0IPrv9D9vH18Yflm-b03cnb5dFpYzvo5mZQCkGiteiFI5JjLwh7MQrofI_Wge_V4FotRQekB6dopVajhNWg2pF60R6yV_vc7W41kbP16owbs81hwnxpEgbzrxLDmVmnCzN2Ug9a1oDH1wE5fd5Rmc152uVYdzZSwwCDrsiqS-5dNqdSMvmbCQLMT6Zmz9RUpuYXU9PXpkd_73bT8htiNbR7Q6lSXFP-M_s_sT8Akxmu_A</recordid><startdate>20221001</startdate><enddate>20221001</enddate><creator>Grau-Pérez, Mercè</creator><creator>Borrego, Leopoldo</creator><creator>Carretero, Gregorio</creator><creator>Almeida, Pablo</creator><creator>Cano, Jorge</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-0199-2756</orcidid><orcidid>https://orcid.org/0000-0003-2608-0400</orcidid><orcidid>https://orcid.org/0000-0002-2469-3417</orcidid><orcidid>https://orcid.org/0000-0001-9864-5058</orcidid><orcidid>https://orcid.org/0000-0002-7628-3495</orcidid></search><sort><creationdate>20221001</creationdate><title>Assessing the effect of environmental and socio-economic factors on skin melanoma incidence: an island-wide spatial study in Gran Canaria (Spain), 2007–2018</title><author>Grau-Pérez, Mercè ; Borrego, Leopoldo ; Carretero, Gregorio ; Almeida, Pablo ; Cano, Jorge</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c404t-855a02accaf1dee2961ea619104f6acd0f658d372140e78d5eb5b920b8539e613</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Autocorrelation</topic><topic>Autoregressive models</topic><topic>Bayes Theorem</topic><topic>Bayesian analysis</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Cancer Research</topic><topic>Census</topic><topic>Demographics</topic><topic>Demography</topic><topic>Economic Factors</topic><topic>Economics</topic><topic>Environmental effects</topic><topic>Environmental factors</topic><topic>Epidemiology</topic><topic>Female</topic><topic>Gene mapping</topic><topic>Geographical variations</topic><topic>Hematology</topic><topic>Humans</topic><topic>Incidence</topic><topic>Mathematical models</topic><topic>Melanoma</topic><topic>Melanoma - epidemiology</topic><topic>Melanoma - etiology</topic><topic>Oncology</topic><topic>Original Paper</topic><topic>Public Health</topic><topic>Ravines</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Skin</topic><topic>Skin cancer</topic><topic>Social factors</topic><topic>Socioeconomic Factors</topic><topic>Socioeconomics</topic><topic>Solar radiation</topic><topic>Spain - epidemiology</topic><topic>Spatial distribution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Grau-Pérez, Mercè</creatorcontrib><creatorcontrib>Borrego, Leopoldo</creatorcontrib><creatorcontrib>Carretero, Gregorio</creatorcontrib><creatorcontrib>Almeida, Pablo</creatorcontrib><creatorcontrib>Cano, Jorge</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancer causes & control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Grau-Pérez, Mercè</au><au>Borrego, Leopoldo</au><au>Carretero, Gregorio</au><au>Almeida, Pablo</au><au>Cano, Jorge</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing the effect of environmental and socio-economic factors on skin melanoma incidence: an island-wide spatial study in Gran Canaria (Spain), 2007–2018</atitle><jtitle>Cancer causes & control</jtitle><stitle>Cancer Causes Control</stitle><addtitle>Cancer Causes Control</addtitle><date>2022-10-01</date><risdate>2022</risdate><volume>33</volume><issue>10</issue><spage>1261</spage><epage>1272</epage><pages>1261-1272</pages><issn>0957-5243</issn><eissn>1573-7225</eissn><abstract>Introduction
Skin melanoma incidence has risen in the last decades becoming a major public health problem in many regions of the world. Geographic variation of rates is not well understood.
Purpose
To assess the spatial distribution of skin melanoma in Gran Canaria Island (Canary Islands, Spain) and to evaluate the role of environmental, socio-economic, and demographic factors in this distribution.
Methods
We performed a small-area study with disease mapping at the census-tract level (CT) in Gran Canaria between 2007 and 2018. After testing for spatial autocorrelation, we integrated individual-level health data with census-based demographic and socio-economic indicators, and satellite-based environmental data. Finally, we assessed the role of demographic, socio-economic and environmental factors on skin melanoma incidence using a Bayesian analytical framework, with options for non-spatial and spatial random effects.
Results
1058 patients were diagnosed with invasive skin melanoma in the study period and geolocated to a CT (number of CT in Gran Canaria = 565). We found evidence of global spatial autocorrelation in skin melanoma incidence (Moran’s
I
= 0.09, pseudo
p
-value = 0.001). A few hotspots were detected, fundamentally in urban northern tracts. A radial pattern of high values was also observed in selected ravines with historical isolation. Multivariable conditional autoregressive models identified urbanicity, percent of females, and a high socio-economic status as risk factors for disease. Solar radiation did not show a significant role.
Conclusion
Urbanicity and a high socio-economic status were identified as the main risk factors for skin melanoma. These associations might reflect differential melanoma susceptibilities or be explained by health inequalities in detection. This study also uncovered high-risk areas in particular ravines. Future targeted research in these regions might help better understand the role of genetic and toxic factors in melanoma pathogenesis.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>35925499</pmid><doi>10.1007/s10552-022-01614-6</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-0199-2756</orcidid><orcidid>https://orcid.org/0000-0003-2608-0400</orcidid><orcidid>https://orcid.org/0000-0002-2469-3417</orcidid><orcidid>https://orcid.org/0000-0001-9864-5058</orcidid><orcidid>https://orcid.org/0000-0002-7628-3495</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Autocorrelation Autoregressive models Bayes Theorem Bayesian analysis Biomedical and Life Sciences Biomedicine Cancer Research Census Demographics Demography Economic Factors Economics Environmental effects Environmental factors Epidemiology Female Gene mapping Geographical variations Hematology Humans Incidence Mathematical models Melanoma Melanoma - epidemiology Melanoma - etiology Oncology Original Paper Public Health Ravines Risk analysis Risk factors Skin Skin cancer Social factors Socioeconomic Factors Socioeconomics Solar radiation Spain - epidemiology Spatial distribution |
| title | Assessing the effect of environmental and socio-economic factors on skin melanoma incidence: an island-wide spatial study in Gran Canaria (Spain), 2007–2018 |
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