Negar Morovatdar1, Amanda G Thrift2, Saverio Stranges3,4,5, Moira Kapral6, Reza Behrouz7, Amin Amiri8, Abbas Heshmati8, Amirali Ghahremani9, Mohammad Taghi Farzadfard8, Naghmeh Mokhber10,11, Mahmoud Reza Azarpazhooh12,13,14,15. 1. Clinical Research Unit, Mashhad University of Medical Sciences, Mashhad, Iran. 2. Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia. 3. Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada. 4. Department of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada. 5. Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg. 6. Department of Medicine and Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada. 7. Department of Neurology, Lozano-Long School of Medicine, University of Texas Health, Tyler, Texas, USA. 8. Department of Neurology, Mashhad University of Medical Sciences, Mashhad, Iran. 9. Department of Neurology, North Khorasan University of Medical Sciences, Bojnord, Iran. 10. Department of Psychiatry and Behavioral Neurosciences, Western University, London, Ontario, Canada. 11. Department of Psychiatry, Mashhad University of Medical Sciences, Mashhad, Iran. 12. Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada, reza.azarpazhooh@lhsc.on.ca. 13. Department of Neurology, Mashhad University of Medical Sciences, Mashhad, Iran, reza.azarpazhooh@lhsc.on.ca. 14. Stroke Prevention and Atherosclerosis Research Centre, Robarts Research Institute, Western University, London, Ontario, Canada, reza.azarpazhooh@lhsc.on.ca. 15. Department of Clinical Neurological Sciences, Western University, London, Ontario, Canada, reza.azarpazhooh@lhsc.on.ca.
Abstract
BACKGROUND: Little is known about the association between socioeconomic status and long-term stroke outcomes, particularly in low- and middle-income countries. METHODS: Patients were recruited from the Mashhad Stroke Incidence Study in Iran. We identified different socioeconomic variables including the level of education, occupation, household size, and family income. Residential location according to patient's neighbourhood was classified into less privileged area (LPA), middle privileged area and high privileged area (HPA). Using Cox regression, competing risk analysis and logistic regression models, we determined the association between socioeconomic status and 1- and 5-year stroke outcomes. Generalized linear model was used for adjusting associated variables for stroke severity. RESULTS: Six hundred twenty-four patients with first-ever stroke were recruited in this study. Unemployment prior to stroke was associated with an increased risk of 1- and 5-year post-stroke mortality (1 year: adjusted hazard ratio [aHR] 3.3; 95% CI 1.6-7.06: p = 0.001; 5 years: aHR 2.1; 95% CI 1.2-3.6: p = 0.007). The 5-year mortality rate was higher in less educated patients (<12 years) as compared to those with at least 12 years of schooling (aHR 1.84; 95% CI 1.05-3.23: p = 0.03). Patients living in LPA compared to those living in HPAs experienced a more severe stroke at admission (aB 3.84; 95% CI 0.97-6.71, p = 0.009) and disabling stroke at 1 year follow-up (OR 6.1; 95% CI 1.3-28.4; p = 0.02). CONCLUSION: A comprehensive stroke strategy should also address socioeconomic disadvantages.
BACKGROUND: Little is known about the association between socioeconomic status and long-term stroke outcomes, particularly in low- and middle-income countries. METHODS:Patients were recruited from the Mashhad Stroke Incidence Study in Iran. We identified different socioeconomic variables including the level of education, occupation, household size, and family income. Residential location according to patient's neighbourhood was classified into less privileged area (LPA), middle privileged area and high privileged area (HPA). Using Cox regression, competing risk analysis and logistic regression models, we determined the association between socioeconomic status and 1- and 5-year stroke outcomes. Generalized linear model was used for adjusting associated variables for stroke severity. RESULTS: Six hundred twenty-four patients with first-ever stroke were recruited in this study. Unemployment prior to stroke was associated with an increased risk of 1- and 5-year post-strokemortality (1 year: adjusted hazard ratio [aHR] 3.3; 95% CI 1.6-7.06: p = 0.001; 5 years: aHR 2.1; 95% CI 1.2-3.6: p = 0.007). The 5-year mortality rate was higher in less educated patients (<12 years) as compared to those with at least 12 years of schooling (aHR 1.84; 95% CI 1.05-3.23: p = 0.03). Patients living in LPA compared to those living in HPAs experienced a more severe stroke at admission (aB 3.84; 95% CI 0.97-6.71, p = 0.009) and disabling stroke at 1 year follow-up (OR 6.1; 95% CI 1.3-28.4; p = 0.02). CONCLUSION: A comprehensive stroke strategy should also address socioeconomic disadvantages.