Green space exposure and mortality in the Florentine plain: preventable deaths at the census tract level and uncertainty analysis 

Green space exposure and mortality in the Florentine plain: preventable deaths at the census tract level and uncertainty 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 Article Green space exposure and mortality in the Florentine plain: preventable deaths at the census tract level and uncertainty analysis Michela Baccini, Giorgia Burbui, Daniela Nuvolone, Costanza Borghi, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7968253/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Stochastic Environmental Research and Risk Assessment → Version 1 posted 9 You are reading this latest preprint version Abstract Background Proximity to vegetation is linked to lower mortality, making urban greening a key public health strategy. This study quantified preventable deaths associated with green-space exposure in the Florentine plain (Tuscany, Italy), integrating population, deprivation, and satellite data while accounting for model uncertainty. Methods Exposure was measured in 2015 as the mean NDVI within 300 m of each census tract. Deaths in 2021 were redistributed from municipalities to tracts by age–sex structure and adjusted for deprivation. Mortality impacts among adults over 35 were estimated under counterfactual scenarios: NDVI thresholds (0.5, 0.7), + 0.1 absolute and + 20% relative NDVI increases, and compliance with the World Health Organization’s greenness target converted to NDVI. The exposure–response function came from a Bayesian meta-analysis. Uncertainty was propagated through Monte Carlo simulations, and a Global Sensitivity Analysis identified main sources of variance. Results We estimated 346 avoidable deaths for NDVI ≥ 0.5 and 877 for NDVI ≥ 0.7. Increases of + 0.1 and + 20% NDVI would have prevented 310 and 25 deaths, while the WHO target corresponded to 47. Although uncertainty was high, the probability of a nonzero impact exceeded 90%. Sensitivity analysis identified the NDVI–mortality hazard ratio as the dominant source of uncertainty, while deprivation and stochastic death redistribution had minimal effects. Conclusions Increasing urban greenness could have reduced mortality. The integrated Monte Carlo–sensitivity framework demonstrated both the potential health gains and the need for refined exposure measures and local cohorts to support equitable, evidence-based planning. Green space exposure Preventable mortality Health Impact Assessment Monte Carlo simulation Global Sensitivity Analysis Uncertainty analysis. Full Text Additional Declarations No competing interests reported. Supplementary Files ESM1.pdf Cite Share Download PDF Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Stochastic Environmental Research and Risk Assessment → Version 1 posted Editorial decision: Revision requested 22 Dec, 2025 Reviews received at journal 17 Dec, 2025 Reviews received at journal 02 Dec, 2025 Reviewers agreed at journal 26 Nov, 2025 Reviewers agreed at journal 14 Nov, 2025 Reviewers invited by journal 10 Nov, 2025 Editor assigned by journal 31 Oct, 2025 Submission checks completed at journal 28 Oct, 2025 First submitted to journal 28 Oct, 2025 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-7968253","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":545108790,"identity":"51a1e93a-2959-4450-8bbe-b64a1bb8ff44","order_by":0,"name":"Michela 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","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"stochastic-environmental-research-and-risk-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"serr","sideBox":"Learn more about [Stochastic Environmental Research and Risk Assessment](https://www.springer.com/journal/477)","snPcode":"477","submissionUrl":"https://submission.nature.com/new-submission/477/3","title":"Stochastic Environmental Research and Risk Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Green space exposure, Preventable mortality, Health Impact Assessment, Monte Carlo simulation, Global Sensitivity Analysis, Uncertainty analysis.","lastPublishedDoi":"10.21203/rs.3.rs-7968253/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7968253/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eProximity to vegetation is linked to lower mortality, making urban greening a key public health strategy. This study quantified preventable deaths associated with green-space exposure in the Florentine plain (Tuscany, Italy), integrating population, deprivation, and satellite data while accounting for model uncertainty.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eExposure was measured in 2015 as the mean NDVI within 300 m of each census tract. Deaths in 2021 were redistributed from municipalities to tracts by age\u0026ndash;sex structure and adjusted for deprivation. Mortality impacts among adults over 35 were estimated under counterfactual scenarios: NDVI thresholds (0.5, 0.7), +\u0026thinsp;0.1 absolute and +\u0026thinsp;20% relative NDVI increases, and compliance with the World Health Organization\u0026rsquo;s greenness target converted to NDVI. The exposure\u0026ndash;response function came from a Bayesian meta-analysis. Uncertainty was propagated through Monte Carlo simulations, and a Global Sensitivity Analysis identified main sources of variance.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eWe estimated 346 avoidable deaths for NDVI\u0026thinsp;\u0026ge;\u0026thinsp;0.5 and 877 for NDVI\u0026thinsp;\u0026ge;\u0026thinsp;0.7. Increases of +\u0026thinsp;0.1 and +\u0026thinsp;20% NDVI would have prevented 310 and 25 deaths, while the WHO target corresponded to 47. Although uncertainty was high, the probability of a nonzero impact exceeded 90%. Sensitivity analysis identified the NDVI\u0026ndash;mortality hazard ratio as the dominant source of uncertainty, while deprivation and stochastic death redistribution had minimal effects.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eIncreasing urban greenness could have reduced mortality. The integrated Monte Carlo\u0026ndash;sensitivity framework demonstrated both the potential health gains and the need for refined exposure measures and local cohorts to support equitable, evidence-based planning.\u003c/p\u003e","manuscriptTitle":"Green space exposure and mortality in the Florentine plain: preventable deaths at the census tract level and uncertainty analysis ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-20 16:41:18","doi":"10.21203/rs.3.rs-7968253/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-22T11:14:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-18T01:05:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-02T13:32:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"304933382389362951539516976178149609267","date":"2025-11-26T09:55:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"305014325380720299414768300684267718454","date":"2025-11-14T12:42:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-10T13:47:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-31T14:37:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-28T14:58:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Stochastic Environmental Research and Risk Assessment","date":"2025-10-28T11:01:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"stochastic-environmental-research-and-risk-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"serr","sideBox":"Learn more about [Stochastic Environmental Research and Risk Assessment](https://www.springer.com/journal/477)","snPcode":"477","submissionUrl":"https://submission.nature.com/new-submission/477/3","title":"Stochastic Environmental Research and Risk Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3de04db6-95ce-4bf5-8d81-8d111466888f","owner":[],"postedDate":"November 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T16:03:00+00:00","versionOfRecord":{"articleIdentity":"rs-7968253","link":"https://doi.org/10.1007/s00477-026-03217-y","journal":{"identity":"stochastic-environmental-research-and-risk-assessment","isVorOnly":false,"title":"Stochastic Environmental Research and Risk Assessment"},"publishedOn":"2026-04-29 15:58:11","publishedOnDateReadable":"April 29th, 2026"},"versionCreatedAt":"2025-11-20 16:41:18","video":"","vorDoi":"10.1007/s00477-026-03217-y","vorDoiUrl":"https://doi.org/10.1007/s00477-026-03217-y","workflowStages":[]},"version":"v1","identity":"rs-7968253","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7968253","identity":"rs-7968253","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}