{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["6(1)"],"submitter":["Linde S"],"pubmed_abstract":["<h4>Importance</h4>Prior research has identified associations between housing insecurity and poor health outcomes.<h4>Objective</h4>To evaluate the association between US state Medicaid expansions and reductions in eviction; to examine the persistence of these associations and how they vary across US states and counties.<h4>Design, setting, and participants</h4>This cohort study of 25 398 county-year observations (across 40 states) used US eviction and census data for the years 2002 through 2018 (ie, 17 years). County-level associations were estimated using interactive fixed effects counterfactual estimators, and models were selected using cross validation. Across-county treatment association heterogeneities were assessed using multivariable regression methods. Analyses were performed in J"],"journal":["JAMA network open"],"pagination":["e2249361"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9857591"],"repository":["biostudies-literature"],"pubmed_title":["Association Between State-Level Medicaid Expansion and Eviction Rates."],"pmcid":["PMC9857591"],"pubmed_authors":["Linde S","Egede LE"],"additional_accession":[]},"is_claimable":false,"name":"Association Between State-Level Medicaid Expansion and Eviction Rates.","description":"<h4>Importance</h4>Prior research has identified associations between housing insecurity and poor health outcomes.<h4>Objective</h4>To evaluate the association between US state Medicaid expansions and reductions in eviction; to examine the persistence of these associations and how they vary across US states and counties.<h4>Design, setting, and participants</h4>This cohort study of 25 398 county-year observations (across 40 states) used US eviction and census data for the years 2002 through 2018 (ie, 17 years). County-level associations were estimated using interactive fixed effects counterfactual estimators, and models were selected using cross validation. Across-county treatment association heterogeneities were assessed using multivariable regression methods. Analyses were performed in J","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Jan","modification":"2025-04-06T19:14:52.006Z","creation":"2025-04-06T19:14:52.006Z"},"accession":"S-EPMC9857591","cross_references":{"pubmed":["36630137"],"doi":["10.1001/jamanetworkopen.2022.49361"]}}