BACKGROUND: Low socioeconomic status (low education and income level) has been found to be associated with increased stroke mortality. However, findings from previous studies on the association between socioeconomic status and case fatality (survival) after stroke have been inconsistent. AIMS: The study aims to explore the association between socio-economic status and survival after stroke using Riks-Stroke, the Swedish Stroke Register, with emphasis on changes in survival (in)equality with time after stroke. METHODS: All 76 hospitals in Sweden admitting acute stroke patients participate in Riks-Stroke. Riks-Stroke data on 18- to 74-year-old patients with onset of first stroke during the years 2001-2009 were combined with data from other official Swedish registers. Case fatality was analyzed by socioeconomic status (education, income, country of birth, and cohabitation) and other patient characteristics. RESULTS: Of the 62,497 patients in the study, a total of 6094 (9.8%) died within the first year after stroke. Low income, primary school education, and living alone were independently associated with higher case fatality after the acute phase. Differences related to income and cohabitation were present already early, at 8-28 days after stroke, with the gaps expanding thereafter. The association between education and case fatality was not present until 29 days to one-year after stroke. Dissimilarities in secondary preventative medications prescribed on discharge from hospital had only a minor impact on these differences. CONCLUSIONS: Socioeconomic status had only a limited effect on acute phase case fatality, indicating minor disparities in acute stroke treatment. The survival inequality, present already in the subacute phase, increased markedly over time since the stroke event. The socioeconomic differences could not be explained by differences in secondary prevention at discharge from hospital. Large socioeconomic differences in long-term survival after stroke may exist also in a country with limited income inequity.
BACKGROUND: Low socioeconomic status (low education and income level) has been found to be associated with increased stroke mortality. However, findings from previous studies on the association between socioeconomic status and case fatality (survival) after stroke have been inconsistent. AIMS: The study aims to explore the association between socio-economic status and survival after stroke using Riks-Stroke, the Swedish Stroke Register, with emphasis on changes in survival (in)equality with time after stroke. METHODS: All 76 hospitals in Sweden admitting acute strokepatients participate in Riks-Stroke. Riks-Stroke data on 18- to 74-year-old patients with onset of first stroke during the years 2001-2009 were combined with data from other official Swedish registers. Case fatality was analyzed by socioeconomic status (education, income, country of birth, and cohabitation) and other patient characteristics. RESULTS: Of the 62,497 patients in the study, a total of 6094 (9.8%) died within the first year after stroke. Low income, primary school education, and living alone were independently associated with higher case fatality after the acute phase. Differences related to income and cohabitation were present already early, at 8-28 days after stroke, with the gaps expanding thereafter. The association between education and case fatality was not present until 29 days to one-year after stroke. Dissimilarities in secondary preventative medications prescribed on discharge from hospital had only a minor impact on these differences. CONCLUSIONS: Socioeconomic status had only a limited effect on acute phase case fatality, indicating minor disparities in acute stroke treatment. The survival inequality, present already in the subacute phase, increased markedly over time since the stroke event. The socioeconomic differences could not be explained by differences in secondary prevention at discharge from hospital. Large socioeconomic differences in long-term survival after stroke may exist also in a country with limited income inequity.
Authors: Xun Tang; Daniel T Laskowitz; Liu He; Truls Østbye; Janet Prvu Bettger; Yang Cao; Na Li; Jingrong Li; Zongxin Zhang; Jianjiang Liu; Liping Yu; Haitao Xu; Yonghua Hu; Larry B Goldstein Journal: Int J Stroke Date: 2014-08-04 Impact factor: 5.266
Authors: Lars Kellert; Armin Grau; Alessandro Pezzini; Stéphanie Debette; Didier Leys; Valeria Caso; Vincent N Thijs; Anna Bersano; Emmanuel Touzé; Turgut Tatlisumak; Christopher Traenka; Philippe A Lyrer; Stefan T Engelter; Tiina M Metso; Caspar Grond-Ginsbach; Manja Kloss Journal: J Neurol Date: 2018-02-24 Impact factor: 4.849
Authors: Suhang Song; Gaoting Ma; Michael G Trisolini; Kenneth A Labresh; Sidney C Smith; Yinzi Jin; Zhi-Jie Zheng Journal: JAMA Netw Open Date: 2021-05-03