ORIGINAL RESEARCH article
Front. Stroke
Sec. Stroke Recovery and Rehabilitation
This article is part of the Research TopicPerson and Community Centred Approaches to Transitions of CareView all 9 articles
Neighborhood Economic and Demographic Landscape as Predictors of 90-Day Outcomes Post-Stroke Hospitalization
Provisionally accepted
Farya Fakoori
Karlon H. Johnson
Hannah Gardener
Carolina M. Gutierrez
Negar AsdaghiLauri Bishop
Scott Brown
Iszet Campo-BustilloGillian Gordon PerueEmir VeledarHao YingLili Zhou
Jose Romano
Tatjana Rundek
Erika Marulanda*- Leonard M. Miller School of Medicine, University of Miami, Miami, United States
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
An in-depth exploration of neighborhood environmental impact on post-discharge stroke outcomes is lacking yet essential for identifying populations at high risk. We assess neighborhood economic and demographic characteristics associated with 90-day death or readmission post-stroke hospitalization. Methods We prospectively analyzed 1,329 acute stroke survivors in the Florida Stroke Registry's Transition of Care Stroke Disparities Study (91% ischemic, 56% male, 52% non-Hispanic White, 23% non-Hispanic Black, 22% Hispanic, median age 64). Neighborhood characteristics at the ZIP+4 level, including socioeconomic status (NSES), racial/ethnic composition, and business densities (food, tobacco/alcohol, gyms, medical services), were analyzed using factor analysis to generate four factors with eigenvalues greater than 1. Outcomes (death or readmission) were assessed through structured telephone interviews 90 days post-discharge. Logistic regression evaluated associations between neighborhood characteristics and outcomes, adjusting for demographics (race/ethnicity, sex, age), vascular risk factors, stroke severity from Get With The Guidelines-Stroke®, and social or economic conditions such as insurance, support, and living arrangements. Results Within 90 days, 208 patients experienced death or readmission. Four factors explained 59% of the variance in 24 neighborhood characteristics. Factor 1, defined by lower NSES, higher population density, and urbanization (RUCA code 1, greater densities of tobacco/alcohol outlets, restaurants, grocery stores, gyms, and pharmacies), was associated with a 20% increased risk. Conclusions Living in densely populated, highly urbanized neighborhoods with lower SES and greater commercial density predicted poor stroke outcomes independent of individual health or SES. These findings can guide community interventions to reduce stroke mortality and readmission.
Keywords: Community Health, Neighborhood SES, stroke outcomes, stroke readmission, Transitions of care
Received: 03 Nov 2025; Accepted: 16 Feb 2026.
Copyright: © 2026 Fakoori, Johnson, Gardener, Gutierrez, Asdaghi, Bishop, Brown, Campo-Bustillo, Gordon Perue, Veledar, Ying, Zhou, Romano, Rundek and Marulanda. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Erika Marulanda
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.