County level mortality and morbidity associated with PM2.5-related cancers in China based on satellite-derived PM2.5 data from 1998 to 2016: a forecasting and spatial analysis

County level mortality and morbidity associated with PM2.5-related cancers in China based on satellite-derived PM2.5 data from 1998 to 2016: a forecasting and spatial analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research County level mortality and morbidity associated with PM2.5-related cancers in China based on satellite-derived PM2.5 data from 1998 to 2016: a forecasting and spatial analysis Ke Ju, WeiBin Liao, Qian Zhou, YaMin Gao, Jay Pan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.2.18389/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Ambient fine particulate matter (PM2.5) pollution is becoming increasingly serious in China, and is a major risk factor for various cancers. Moreover, recent studies have indicated that there is an impact of PM2.5 from regional transport. We aimed to predict spatial distribution of cancers related to PM2.5, and draw a series of forecasting maps of these cancers. Methods: A 1000-loops simulation was done to choose the optimal forecasting model between five alternative models: ridge regression, partial least square regression, regression tree, model tree, and the combined forecasting model. Then a kriging interpolation method was used to draw the forecasted cancer maps. Results: The trend showed a gradual increase in the mortality and morbidity of breast cancer, pancreatic cancer, and all-cause cancer. We found a significant spatial autocorrelation between cancer incidence and PM2.5. Our results from forecasting showed a constant growth in mortality and morbidity of all cancers, and the kriging method suggested a similar spatial pattern. High morbidity and mortality areas were mainly in central-east and south-east China. We found a similar distribution pattern between PM2.5 concentration and mortality and morbidity associated with PM2.5-related cancers. Conclusions: These findings serve as a valuable reference for the development of effective policies to reduce air pollution emissions, with the efforts from governments in high-risk areas. Toxicology Epidemiology PM2.5-related cancers regional transport forecast spatiotemporal analysis China. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Full Text Table Year No. of registries No. of urban areas No. of rural areas Population(10 thousands) 2006 34 15 19 5956 2007 38 17 21 5980 2008 41 20 21 6613 2009 72 31 41 8447 2010 145 58 87 12465 2011 177 77 100 14575 2012 193 73 120 19806 2013 255 88 167 22649 2014 339 129 210 28824 Table 1. Descriptions for cancer registration areas from 2006 to 2014 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9009","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":241012,"identity":"642bf010-ae18-47b2-bc6d-8c32744c8a08","order_by":1,"name":"Ke Ju","email":"","orcid":"","institution":"Sichuan University West China School of Public Health","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ke","middleName":"","lastName":"Ju","suffix":""},{"id":241013,"identity":"57b50a25-ed07-4bdf-b9f9-a0fa7a9ffb9c","order_by":2,"name":"WeiBin Liao","email":"","orcid":"","institution":"Sichuan University West China School of Public Health","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"WeiBin","middleName":"","lastName":"Liao","suffix":""},{"id":241014,"identity":"34812226-f0ed-45ea-8546-f89f9805a2cb","order_by":3,"name":"Qian Zhou","email":"","orcid":"","institution":"Sichuan University West China Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Zhou","suffix":""},{"id":241015,"identity":"871d3381-e702-4457-a41b-7ce92b96e3d2","order_by":4,"name":"YaMin Gao","email":"","orcid":"","institution":"Northwest Minzu University College of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"YaMin","middleName":"","lastName":"Gao","suffix":""},{"id":241016,"identity":"9ccf8373-57c0-43e4-a55d-901aeeacbc93","order_by":5,"name":"Jay Pan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYJACgwQGBmYgOgDhHiBeC1sC8VqggMeAOC3m7GcPFDyoYGDnn5Hz+cPPNgY5vhsJjJ8L8Gix7MlLMEg4w8AscSN3m2RvG4Ox5I0EZukZeLQYHMgxMEhsA/oFqIWZsY0hccONBDZmHnxazr8BavnHwCx/I+fxZ6CWesJaboBsaWBgBjIYpIFaEgwIabGcAbQl4ZgEs+GZZ2aSPeckDGeeedgsjU+LOX+OmeGPGptkuePJjz/8KLOR5zuefPAzXocBoxCIJZIZBBJAfAkgZmzAowGshfkBkLZj4D+AV+EoGAWjYBSMYAAALnxJYHxhl9kAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-8040-8978","institution":"Sichuan University West China School of Public Health","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Jay","middleName":"","lastName":"Pan","suffix":""}],"badges":[],"createdAt":"2019-12-05 11:37:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.2.18389/v1","doiUrl":"https://doi.org/10.21203/rs.2.18389/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":239877,"identity":"662e41c2-eb5c-49b7-89db-32393b9b0386","added_by":"auto","created_at":"2019-12-10 23:08:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":366614,"visible":true,"origin":"","legend":"The spatial distribution of cancer registries in 2014. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/553ebaa7-3edb-45cb-8e7c-c828c3849946/v1/Fig1.png"},{"id":239879,"identity":"db4986ed-5d27-46cf-8da2-bd41cfedca18","added_by":"auto","created_at":"2019-12-10 23:08:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":365798,"visible":true,"origin":"","legend":"The spatial distribution of nineteen-year-long mean PM2.5 concentration in China. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/553ebaa7-3edb-45cb-8e7c-c828c3849946/v1/Fig2.png"},{"id":239881,"identity":"abb06d6b-10da-4027-bd19-6192d64140b5","added_by":"auto","created_at":"2019-12-10 23:08:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3497937,"visible":true,"origin":"","legend":"The spatial distribution of morbidity and mortality of different cancers in 2014 across 307 registries. A and B for all cancer, C and D for breast cancer, E and F for pancreatic cancer. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/553ebaa7-3edb-45cb-8e7c-c828c3849946/v1/Fig3.png"},{"id":239883,"identity":"6f2f1f41-4424-40ef-9baf-ead55b726284","added_by":"auto","created_at":"2019-12-10 23:08:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":391694,"visible":true,"origin":"","legend":"The Moran’s I statistics of different cancers mortality and morbidity in 2014. A and B for all cancer, C and D for breast cancer, E and F for pancreatic cancer.","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/553ebaa7-3edb-45cb-8e7c-c828c3849946/v1/Fig4.png"},{"id":239885,"identity":"12d7b950-cff0-4115-8d8e-16c702418161","added_by":"auto","created_at":"2019-12-10 23:08:29","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1898389,"visible":true,"origin":"","legend":"The Moran’s I statistics of PM2.5 from 2006 to 2014.","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/553ebaa7-3edb-45cb-8e7c-c828c3849946/v1/Fig5.png"},{"id":239887,"identity":"7753a28a-ad7d-478e-94e8-aaf5b26a0fb3","added_by":"auto","created_at":"2019-12-10 23:08:30","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1381576,"visible":true,"origin":"","legend":"Predicted annual all cancer mortality and morbidity over China in 2015 and 2016. A and B for morbidity, C and D for mortality. A and C denotes the morbidity and mortality prediction in 2015, respectively. B and D denotes the morbidity and mortality prediction in 2016, respectively. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/553ebaa7-3edb-45cb-8e7c-c828c3849946/v1/Fig6.png"},{"id":239889,"identity":"feaca39b-de8a-4d47-9917-1ba6d2c6c1e7","added_by":"auto","created_at":"2019-12-10 23:08:30","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1421577,"visible":true,"origin":"","legend":"Predicted annual breast cancer mortality and morbidity over China in 2015 and 2016. A and B for morbidity, C and D for mortality. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/553ebaa7-3edb-45cb-8e7c-c828c3849946/v1/Fig7.png"},{"id":239891,"identity":"4c8eb177-cf83-4304-be4c-ab03d66d17fe","added_by":"auto","created_at":"2019-12-10 23:08:31","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1402154,"visible":true,"origin":"","legend":"Predicted annual pancreatic cancer mortality and morbidity over China in 2015 and 2016. A and B for morbidity, C and D for mortality. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig8.png","url":"https://assets-eu.researchsquare.com/files/553ebaa7-3edb-45cb-8e7c-c828c3849946/v1/Fig8.png"},{"id":785063,"identity":"2197ba7d-cfea-4e75-8ec4-83b4bcfe4d1e","added_by":"auto","created_at":"2020-03-30 23:22:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4236470,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9009/v1/manuscript.pdf"},{"id":240446,"identity":"740f4219-e211-4c72-b299-e6cd79344bb0","added_by":"auto","created_at":"2019-12-11 11:23:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":507813,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptEH.pdf","url":"https://assets-eu.researchsquare.com/files/553ebaa7-3edb-45cb-8e7c-c828c3849946/v1/Manuscript-EH.pdf"},{"id":239916,"identity":"622cfadf-d05d-453a-8dfb-ee46055aa4ab","added_by":"auto","created_at":"2019-12-10 23:08:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":562882,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptEH.pdf","url":"https://assets-eu.researchsquare.com/files/553ebaa7-3edb-45cb-8e7c-c828c3849946/v1/Manuscript.pdf"},{"id":13481323,"identity":"4c473a66-9c87-4149-ae0f-b7fe94547537","added_by":"auto","created_at":"2021-09-16 21:46:42","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1087274,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptEH.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9009/v1_covered.pdf"}],"financialInterests":"","formattedTitle":"County level mortality and morbidity associated with PM2.5-related cancers in China based on satellite-derived PM2.5 data from 1998 to 2016: a forecasting and spatial analysis","fulltext":[{"header":"Full Text","content":"\u003cp\u003eThis preprint is available for \u003ca href='/article/rs-9009/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e.\u003c/p\u003e"},{"header":"Table","content":"\u003cdiv style=\"display: flex; flex-direction: column\"\u003e\n\u003ctable align=\"left\" border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.701923076923077%\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\"\u003e\n \u003cp\u003eNo. of registries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.432692307692307%\"\u003e\n \u003cp\u003eNo. of urban areas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003eNo. of rural areas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.596153846153847%\"\u003e\n \u003cp\u003ePopulation(10 thousands)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.701923076923077%\"\u003e\n \u003cp\u003e2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.432692307692307%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.596153846153847%\"\u003e\n \u003cp\u003e5956\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.701923076923077%\"\u003e\n \u003cp\u003e2007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.432692307692307%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.596153846153847%\"\u003e\n \u003cp\u003e5980\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.701923076923077%\"\u003e\n \u003cp\u003e2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.432692307692307%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.596153846153847%\"\u003e\n \u003cp\u003e6613\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.701923076923077%\"\u003e\n \u003cp\u003e2009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.432692307692307%\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.596153846153847%\"\u003e\n \u003cp\u003e8447\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.701923076923077%\"\u003e\n \u003cp\u003e2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.432692307692307%\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.596153846153847%\"\u003e\n \u003cp\u003e12465\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.701923076923077%\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\"\u003e\n \u003cp\u003e177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.432692307692307%\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.596153846153847%\"\u003e\n \u003cp\u003e14575\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.701923076923077%\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.432692307692307%\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.596153846153847%\"\u003e\n \u003cp\u003e19806\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.701923076923077%\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\"\u003e\n \u003cp\u003e255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.432692307692307%\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.596153846153847%\"\u003e\n \u003cp\u003e22649\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.701923076923077%\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.26923076923077%\"\u003e\n \u003cp\u003e339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.432692307692307%\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.596153846153847%\"\u003e\n \u003cp\u003e28824\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 1. Descriptions for cancer registration areas from 2006 to 2014\u003c/p\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"PM2.5-related cancers, regional transport, forecast, spatiotemporal analysis, China.","lastPublishedDoi":"10.21203/rs.2.18389/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.2.18389/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Ambient fine particulate matter (PM2.5) pollution is becoming increasingly serious in China, and is a major risk factor for various cancers. Moreover, recent studies have indicated that there is an impact of PM2.5 from regional transport. We aimed to predict spatial distribution of cancers related to PM2.5, and draw a series of forecasting maps of these cancers. \u003c/p\u003e\u003cp\u003eMethods: A 1000-loops simulation was done to choose the optimal forecasting model between five alternative models: ridge regression, partial least square regression, regression tree, model tree, and the combined forecasting model. Then a kriging interpolation method was used to draw the forecasted cancer maps. \u003c/p\u003e\u003cp\u003eResults: The trend showed a gradual increase in the mortality and morbidity of breast cancer, pancreatic cancer, and all-cause cancer. We found a significant spatial autocorrelation between cancer incidence and PM2.5. Our results from forecasting showed a constant growth in mortality and morbidity of all cancers, and the kriging method suggested a similar spatial pattern. High morbidity and mortality areas were mainly in central-east and south-east China. We found a similar distribution pattern between PM2.5 concentration and mortality and morbidity associated with PM2.5-related cancers. \u003c/p\u003e\u003cp\u003eConclusions: These findings serve as a valuable reference for the development of effective policies to reduce air pollution emissions, with the efforts from governments in high-risk areas.\u0026nbsp;\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","manuscriptTitle":"County level mortality and morbidity associated with PM2.5-related cancers in China based on satellite-derived PM2.5 data from 1998 to 2016: a forecasting and spatial analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2019-12-10 23:08:25","doi":"10.21203/rs.2.18389/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e461e4d0-3951-4e13-9801-88f3988916b1","owner":[],"postedDate":"December 10th, 2019","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":41248,"name":"Toxicology"},{"id":41249,"name":"Epidemiology"}],"tags":[],"updatedAt":"","versionOfRecord":[],"versionCreatedAt":"2019-12-10 23:08:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9009","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-9009","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}