Abstract WP233: Socioeconomic Status And Comorbidity Variance In Ischemic Stroke

Abstract

Introduction: Socioeconomic status (SES) is an upstream determinant of cerebrovascular disease comorbidities and subsequently ischemic stroke. Here we examined the association of SES and modifiable ischemic stroke risk factors. Methods: Hospitalized ischemic stroke patient data from 10/1/2015 - 12/31/2018 was obtained via the Healthcare Cost and Utilization Project Nationwide Inpatient Sample (NIS). Demographic characteristics of age, sex, race, US region, SES (defined as median household income range by zip code) and ischemic stroke risk factors of atrial fibrillation/flutter (AF), type II diabetes (DM), hypertension (HTN), hyperlipidemia (HLD), tobacco use, and obesity were identified using published ICD-10 codes. Multivariable logistic regression was used to assess each condition individually and identify which comorbidities were associated with specific socioeconomic quartiles (Q1, Q4) when adjusted for the abovementioned demographics. Results: Of the 382,734 adult ischemic stroke patients identified, mean age was 70 ±14.2 years and 50.3% were female. Socioeconomic status quartiles ranged from <$43,749 (Q1) to >$73,000 (Q4); 30.9% of ischemic stroke patients were in SES Q1 (vs 19.1% in SES Q4). Patients in Q1 experienced ischemic stroke at a younger age (67.9 ±14.1) as compared to patients in Q4 (72.4 ±14), p<0.001. In adjusted models with Q4 as reference, Q1 patients had increased odds for DM [OR 1.27, p<0.001, 95% CI 1.24 - 1.29], obesity [OR 1.05, p<0.004, CI 1.02 - 1.08], and tobacco use [OR 1.66, p<0.001, CI 1.51 - 1.83]. Conversely, Q1 patients had decreased odds of AF [OR 0.91, p<0.001, CI 0.89 - 0.93] and HLD [OR 0.81, p<0.001, CI 0.79 - 0.82]. There was no significant association between SES quartile and HTN. Conclusion: Lower SES was associated with higher odds of specific ischemic stroke risk factors. While the etiology of the risk factor variance is beyond the scope of current data analysis, the cause is likely multifactorial and influenced by underlying detection bias, income inequity, and level of education/health literacy. Further research and subgroup analysis is warranted as it may impact future preventative measures and treatment protocols.