Your browser doesn't support javascript.
loading
Correlations of Socioeconomic and Clinical Determinants with United States County-Level Stroke Prevalence.
Stulberg, Eric L; Lisabeth, Lynda; Schneider, Andrea L C; Skolarus, Lesli; Kershaw, Kiarri N; Zheutlin, Alexander R; Harris, Benjamin R E; Sarpong, Daniel; Wong, Ka-Ho; Sheth, Kevin N; de Havenon, Adam.
Afiliação
  • Stulberg EL; Department of Neurology, University of Utah, Salt Lake City, UT, USA.
  • Lisabeth L; Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
  • Schneider ALC; Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Skolarus L; Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
  • Kershaw KN; Department of Epidemiology, Biostatistics and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
  • Zheutlin AR; Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
  • Harris BRE; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
  • Sarpong D; Department of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
  • Wong KH; Department of Pulmonary and Critical Care Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA.
  • Sheth KN; Department of General Internal Medicine, Center for Brain and Mind Health, Yale University School of Medicine, New Haven, CT, USA.
  • de Havenon A; Department of Neurology, University of Utah, Salt Lake City, UT, USA.
Ann Neurol ; 2024 Jul 26.
Article em En | MEDLINE | ID: mdl-39056317
ABSTRACT
Socioeconomic status (SES) is a multi-faceted theoretical construct associated with stroke risk and outcomes. Knowing which SES measures best correlate with population stroke metrics would improve its accounting in observational research and inform interventions. Using the Centers for Disease Control and Prevention's (CDC) Population Level Analysis and Community Estimates (PLACES) and other publicly available databases, we conducted an ecological study comparing correlations of different United States county-level SES, health care access and clinical risk factor measures with age-adjusted stroke prevalence. The prevalence of adults living below 150% of the federal poverty level most strongly correlated with stroke prevalence compared to other SES and non-SES measures (correlation coefficient = 0.908, R2 = 0.825; adjusted partial correlation coefficient 0.589, R2 = 0.347). ANN NEUROL 2024.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article