Self-reported mental distress in the United States:a Bayesian analysis of the spatial structure over the COVID-19 pandemic across age groups

Self-reported mental distress in the United States:a Bayesian analysis of the spatial structure over the COVID-19 pandemic across age groups | 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 Self-reported mental distress in the United States:a Bayesian analysis of the spatial structure over the COVID-19 pandemic across age groups Carles Comas Rodríguez, Albert Martínez Puig, Angel Blanch Plana This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7093711/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Oct, 2025 Read the published version in International Journal of Health Geographics → Version 1 posted 9 You are reading this latest preprint version Abstract Background The COVID-19 had an outstanding impact on well-being and mental health, which might have elicited geographical variations over time. This study examines the eventual impact of COVID-19 on self-reported mental distress in the mainland USA. Aims There were two main aims. First, to evaluate the pre-pandemic (2019) and post-pandemic (2021) mental distress spatial distribution. Second, to contrast spatial data across three age groups, young (18-44 years), middle-aged (45-65 years), and old (older than 65 years). Method We considered a the Bayesian modified Besag–York–Molli`e (BYM2) model, which is a Bayesian hierarchical model. Mental distress was the response variable function of age group, year and spatially structured and unstructured effects. Results The main findings indicate a positive spatial dependence between states of general mental distress before and after the COVID-19 and across age groups with substantial unstructured component. Moreover, younger individuals reported higher levels of mental distress and suffered the major worsening due to the pandemic. Conclusions COVID-19 had a detrimental impact on mental health across the population, with consistent evidence of positive spatial dependence across states. Notably, young adults emerged as particularly vulnerable, exhibiting concerning levels of mental distress problems and being more sensitive to the effects of the pandemic. Mental health Mental distress age groups COVID-19 INLA Gaussian model Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 27 Oct, 2025 Read the published version in International Journal of Health Geographics → Version 1 posted Editorial decision: Revision requested 12 Aug, 2025 Reviews received at journal 11 Aug, 2025 Reviews received at journal 23 Jul, 2025 Reviewers agreed at journal 21 Jul, 2025 Reviewers agreed at journal 18 Jul, 2025 Reviewers invited by journal 16 Jul, 2025 Editor assigned by journal 14 Jul, 2025 Submission checks completed at journal 14 Jul, 2025 First submitted to journal 10 Jul, 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-7093711","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":486839018,"identity":"9904147c-5bc4-4bf7-80fc-76eb2478f85a","order_by":0,"name":"Carles Comas Rodríguez","email":"","orcid":"","institution":"University of Lleida","correspondingAuthor":false,"prefix":"","firstName":"Carles","middleName":"Comas","lastName":"Rodríguez","suffix":""},{"id":486839019,"identity":"021a6650-982b-4dbf-bf8e-03b81f613a47","order_by":1,"name":"Albert Martínez Puig","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIie3PMQrCMBSA4VcKukRd61Kv0CLo4k1cKgWdAo4KIgHBSZ0VQa9Qb2AI2CXo6qh4AhGkgohJHMQh1dEhPwQSyEfyAEymfyyL3vu1WC5ASNKJLUmgdoqUARqSeL8Rmbj/hRQGOXrqJlAvzHeUtTv9VhQLkvTuWuKwfOjzAPB0GwKb8gyO+JFYo03KxxiqFIkghNvAckOEo32D2JDRkxJD1ZskS0UeTstT5KEnnnjFkiRShHiBItZQT3wxS5E0HbzituCbwJ+JWeh4UtYSNx7TM6nV8IJbpwvq9Uv5OKSH5Orqx3/lfB7X3+6bTCaTKb0n4SNVWcfzTyUAAAAASUVORK5CYII=","orcid":"","institution":"University of Lleida","correspondingAuthor":true,"prefix":"","firstName":"Albert","middleName":"Martínez","lastName":"Puig","suffix":""},{"id":486839020,"identity":"a3918593-9817-4dcb-b16e-322037084923","order_by":2,"name":"Angel Blanch Plana","email":"","orcid":"","institution":"University of Lleida","correspondingAuthor":false,"prefix":"","firstName":"Angel","middleName":"Blanch","lastName":"Plana","suffix":""}],"badges":[],"createdAt":"2025-07-10 13:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7093711/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7093711/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12942-025-00418-6","type":"published","date":"2025-10-27T15:57:14+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":95039864,"identity":"7913d33c-0f62-4571-901d-e60b26c2c51c","added_by":"auto","created_at":"2025-11-03 16:05:00","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":485803,"visible":true,"origin":"","legend":"","description":"","filename":"USAMentalHealth.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7093711/v1_covered_383c4ca9-b885-4c93-bd11-eea0e86a37b4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Self-reported mental distress in the United States:a Bayesian analysis of the spatial structure over the COVID-19 pandemic across age groups","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":"international-journal-of-health-geographics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijhg","sideBox":"Learn more about [International Journal of Health Geographics](http://ij-healthgeographics.biomedcentral.com/)","snPcode":"12942","submissionUrl":"https://submission.nature.com/new-submission/12942/3","title":"International Journal of Health Geographics","twitterHandle":"@IJHGeo","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mental health, Mental distress, age groups, COVID-19, INLA, Gaussian model","lastPublishedDoi":"10.21203/rs.3.rs-7093711/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7093711/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe COVID-19 had an outstanding impact on well-being and mental health, which might have elicited geographical variations over time. This study examines the eventual impact of COVID-19 on self-reported mental distress in the mainland USA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAims\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were two main aims. First, to evaluate the pre-pandemic (2019) and post-pandemic (2021) mental distress spatial distribution. Second, to contrast spatial data across three age groups, young (18-44 years), middle-aged (45-65 years), and old (older than 65 years).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe considered a the Bayesian modified Besag–York–Molli`e (BYM2) model, which is a Bayesian hierarchical model. Mental distress was the response variable function of age group, year and spatially structured and unstructured effects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main findings indicate a positive spatial dependence between states of general mental distress before and after the COVID-19 and across age groups with substantial unstructured component. Moreover, younger individuals reported higher levels of mental distress and suffered the major worsening due to the pandemic.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCOVID-19 had a detrimental impact on mental health across the population, with consistent evidence of positive spatial dependence across states. Notably, young adults emerged as particularly vulnerable, exhibiting concerning levels of mental distress problems and being more sensitive to the effects of the pandemic.\u003c/p\u003e","manuscriptTitle":"Self-reported mental distress in the United States:a Bayesian analysis of the spatial structure over the COVID-19 pandemic across age groups","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-18 18:24:15","doi":"10.21203/rs.3.rs-7093711/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-12T19:23:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-12T02:22:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-23T09:04:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"11240403683456243939310796280531341444","date":"2025-07-21T15:42:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269837821736398052667498559617186805226","date":"2025-07-18T16:44:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-16T15:31:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-15T00:12:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-15T00:11:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Health Geographics","date":"2025-07-10T13:45:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-health-geographics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijhg","sideBox":"Learn more about [International Journal of Health Geographics](http://ij-healthgeographics.biomedcentral.com/)","snPcode":"12942","submissionUrl":"https://submission.nature.com/new-submission/12942/3","title":"International Journal of Health Geographics","twitterHandle":"@IJHGeo","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dfa9962e-ae74-4513-916c-844aa21f4d81","owner":[],"postedDate":"July 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-03T15:59:59+00:00","versionOfRecord":{"articleIdentity":"rs-7093711","link":"https://doi.org/10.1186/s12942-025-00418-6","journal":{"identity":"international-journal-of-health-geographics","isVorOnly":false,"title":"International Journal of Health Geographics"},"publishedOn":"2025-10-27 15:57:14","publishedOnDateReadable":"October 27th, 2025"},"versionCreatedAt":"2025-07-18 18:24:15","video":"","vorDoi":"10.1186/s12942-025-00418-6","vorDoiUrl":"https://doi.org/10.1186/s12942-025-00418-6","workflowStages":[]},"version":"v1","identity":"rs-7093711","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7093711","identity":"rs-7093711","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}