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dc.contributor.authorPan, Yuesong
dc.contributor.authorSong, Tian
dc.contributor.authorChen, Ruoling
dc.contributor.authorLi, Hao
dc.contributor.authorZhao, Xingquan
dc.contributor.authorLiu, Liping
dc.contributor.authorWang, Chunxue
dc.contributor.authorWang, Yilong
dc.contributor.authorWang, Yongjun
dc.date.accessioned2014-12-29
dc.date.available2016-09-06T14:40:00Z
dc.date.issued2015-01-30
dc.identifier.citationSocioeconomic deprivation and mortality in people after ischemic stroke: The China National Stroke Registry. 2016, 11 (5):557-64 Int J Stroke
dc.identifier.issn1747-4949
dc.identifier.pmid27012272
dc.identifier.doi10.1177/1747493016641121
dc.identifier.urihttp://hdl.handle.net/2436/619886
dc.description.abstractBackground Previous findings of the association between socioeconomic deprivation (SED) and mortality after ischemic stroke are inconsistent. There is a lack of data on the association with combined low education, occupational class and income. We assessed the associations of three indicators with mortality. Methods We examined data from the China National Stroke Registry, recording all stroke patients occurred between September 2007 and August 2008. Baseline SED was measured using low levels of education at <6 years, occupation as manual laboring and average family income per capita at ≤¥1,000 per month. 12,246 patients with ischemic stroke were analyzed. Results In a 12-month follow-up 1640 patients died. After adjustment for age, sex, cardiovascular risk factors, severity of stroke and pre-hospital medications, odds ratio (OR) for mortality in patients with low education was 1.25(95%CI 1.05-1.48), manual laboring 1.37(1.09-1.72) and low income 1.19(1.03-1.37). Further adjustment for acute care and medications in and after hospital made no substantial changes in these ORs, except a marginal significant OR for low income (1.15, 0.99-1.33). The OR for low income was 1.27(1.01-1.60) within patients with high education. Compared with no SED, the OR in patients with SED determined by any 1 indicator was 1.33(1.11-1.59), by any 2 indicators 1.36(1.10-1.69) and by all 3 indicators 1.56(1.23- 1.97). Conclusions There are significant inequalities in survival after ischemic stroke in China in terms of social and material forms of deprivation. General socioeconomic improvement, targeting groups at high risk of mortality is likely to reduce inequality in survival after stroke.
dc.description.sponsorshipThe Ministry of Science and Technology of the People’s Republic of China (2006BAI01A11, 2011BAI08B01, 2011BAI08B02, 2012ZX09303-005-001, and 2013BAI09B03), The Beijing Biobank of Cerebral Vascular Disease (D131100005313003), Beijing Institute for Brain Disorders (BIBD-PXM2013_014226_07_000084)
dc.language.isoen
dc.publisherSAGE Journals
dc.relation.urlhttp://wso.sagepub.com/
dc.subjecteconomics
dc.subjectmortality
dc.subjectoutcomes
dc.subjectsocioeconomic deprivation
dc.subjectsocioeconomic factors
dc.subjectstroke
dc.titleSocioeconomic deprivation and mortality in people after ischemic stroke: The China National Stroke Registry.
dc.typeArticle
dc.identifier.journalInternational journal of stroke : official journal of the International Stroke Society
refterms.dateFOA2018-07-18T13:48:37Z
html.description.abstractBackground Previous findings of the association between socioeconomic deprivation (SED) and mortality after ischemic stroke are inconsistent. There is a lack of data on the association with combined low education, occupational class and income. We assessed the associations of three indicators with mortality. Methods We examined data from the China National Stroke Registry, recording all stroke patients occurred between September 2007 and August 2008. Baseline SED was measured using low levels of education at <6 years, occupation as manual laboring and average family income per capita at ≤¥1,000 per month. 12,246 patients with ischemic stroke were analyzed. Results In a 12-month follow-up 1640 patients died. After adjustment for age, sex, cardiovascular risk factors, severity of stroke and pre-hospital medications, odds ratio (OR) for mortality in patients with low education was 1.25(95%CI 1.05-1.48), manual laboring 1.37(1.09-1.72) and low income 1.19(1.03-1.37). Further adjustment for acute care and medications in and after hospital made no substantial changes in these ORs, except a marginal significant OR for low income (1.15, 0.99-1.33). The OR for low income was 1.27(1.01-1.60) within patients with high education. Compared with no SED, the OR in patients with SED determined by any 1 indicator was 1.33(1.11-1.59), by any 2 indicators 1.36(1.10-1.69) and by all 3 indicators 1.56(1.23- 1.97). Conclusions There are significant inequalities in survival after ischemic stroke in China in terms of social and material forms of deprivation. General socioeconomic improvement, targeting groups at high risk of mortality is likely to reduce inequality in survival after stroke.


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