Sociodemographic Determinants of Mental Health Burden and Healthcare Affordability Among U.S. Adults: A Regression Analysis of the 2023 Behavioral Risk Factor Surveillance System

Sociodemographic Determinants of Mental Health Burden and Healthcare Affordability Among U.S. Adults: A Regression Analysis of the 2023 Behavioral Risk Factor Surveillance System | 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 Sociodemographic Determinants of Mental Health Burden and Healthcare Affordability Among U.S. Adults: A Regression Analysis of the 2023 Behavioral Risk Factor Surveillance System Olakunle Daniel Olorunkemi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8889436/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 Mental health disorders and barriers to healthcare access remain major public health challenges in the United States, with substantial disparities across socioeconomic and demographic groups. Population-level evidence on how sociodemographic factors influence mental health burden and healthcare affordability is essential for informing equitable public health interventions and policy. This cross-sectional study analyzed data from the 2023 Behavioral Risk Factor Surveillance System (BRFSS), a nationally representative survey of U.S. adults. Survey-weighted linear regression models were used to examine predictors of the number of mentally unhealthy days reported in the past 30 days. Survey-weighted logistic regression models assessed associations with inability to afford medical care in the past 12 months and lifetime diagnosis of depression. Explanatory variables included age, sex, income, employment status, and marital status. All analyses accounted for the complex survey design. Lower income and unemployment were consistently associated with poorer mental health outcomes and reduced healthcare access. Respondents in lower income categories reported significantly more mentally unhealthy days and had higher odds of being unable to afford medical care compared with higher-income respondents. Unemployed individuals exhibited increased odds of both depression diagnoses and cost-related barriers to care. Unmarried respondents also demonstrated higher odds of depression and inability to afford healthcare. Female respondents had higher odds of reporting a depression diagnosis, while younger adults experienced a greater mental health burden compared with older adults. All associations remained statistically significant after adjustment for covariates. Sociodemographic characteristics, particularly income, employment status, age, sex, and marital status, are important predictors of mental health burden and healthcare affordability among U.S. adults. These findings highlight persistent socioeconomic disparities and support the need for population-level public health strategies that address social determinants of health to improve mental health outcomes and equitable access to care. Epidemiology Full Text Additional Declarations The authors declare no competing interests. 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-8889436","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":591836122,"identity":"008024b0-96de-4fe9-8493-3a3e2acde52c","order_by":0,"name":"Olakunle Daniel Olorunkemi","email":"data:image/png;base64,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","orcid":"","institution":"Georgia Southern University","correspondingAuthor":true,"prefix":"","firstName":"Olakunle","middleName":"Daniel","lastName":"Olorunkemi","suffix":""}],"badges":[],"createdAt":"2026-02-16 03:59:16","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8889436/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8889436/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102963887,"identity":"50e4fc7a-b3ec-40b2-a1f1-5a753bdc2d99","added_by":"auto","created_at":"2026-02-19 04:20:48","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":273801,"visible":true,"origin":"","legend":"","description":"","filename":"BRFSSDATAANALYSISREPORT.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8889436/v1_covered_24ad00ac-3bd1-4004-a47d-aac3ac887f98.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eSociodemographic Determinants of Mental Health Burden and Healthcare Affordability Among U.S. Adults: A Regression Analysis of the 2023 Behavioral Risk Factor Surveillance System\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Georgia Southern University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-8889436/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8889436/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMental health disorders and barriers to healthcare access remain major public health challenges in the United States, with substantial disparities across socioeconomic and demographic groups. Population-level evidence on how sociodemographic factors influence mental health burden and healthcare affordability is essential for informing equitable public health interventions and policy.\u003c/p\u003e\n\u003cp\u003eThis cross-sectional study analyzed data from the 2023 Behavioral Risk Factor Surveillance System (BRFSS), a nationally representative survey of U.S. adults. Survey-weighted linear regression models were used to examine predictors of the number of mentally unhealthy days reported in the past 30 days. Survey-weighted logistic regression models assessed associations with inability to afford medical care in the past 12 months and lifetime diagnosis of depression. Explanatory variables included age, sex, \u0026nbsp;income, employment status, and marital status. All analyses accounted for the complex survey design.\u003c/p\u003e\n\u003cp\u003eLower income and unemployment were consistently associated with poorer mental health outcomes and reduced healthcare access. Respondents in lower income categories reported significantly more mentally unhealthy days and had higher odds of being unable to afford medical care compared with higher-income respondents. Unemployed individuals exhibited increased odds of both depression diagnoses and cost-related barriers to care. Unmarried respondents also demonstrated higher odds of depression and inability to afford healthcare. Female respondents had higher odds of reporting a depression diagnosis, while younger adults experienced a greater mental health burden compared with older adults. All associations remained statistically significant after adjustment for covariates.\u003c/p\u003e\n\u003cp\u003eSociodemographic characteristics, particularly income, employment status, age, sex, and marital \u0026nbsp;status, are important predictors of mental health burden and healthcare affordability among U.S. adults. 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