Department of Medicine, University of Toronto, Toronto, Canada.
Neurology. 2012 Sep 18;79(12):1200-7. doi: 10.1212/WNL.0b013e31826aac9b. Epub 2012 Aug 15.
To evaluate factors that may contribute to the increased stroke case fatality rates observed in individuals from low-income areas.
We conducted a cohort study on a population-based sample of all patients with stroke or TIA seen at 153 acute care hospitals in the province of Ontario, Canada, between April 1, 2002, and March 31, 2003, and April 1, 2004, and March 31, 2005. Socioeconomic status measured as income quintiles was imputed from median neighborhood income. In the study sample of 7,816 patients we determined 1-year mortality by grouped income quintile and used multivariable analyses to assess whether differences in survival were explained by cardiovascular risk factors, stroke severity, stroke management, or other prognostic factors.
There was no significant gradient across income groups for stroke severity or stroke management. However, 1-year mortality rates were higher in those from the lowest income group compared to those from the highest income group, even after adjustment for age, sex, stroke type and severity, comorbid conditions, hospital and physician characteristics, and processes of care (adjusted hazard ratio for low- vs high-income groups, 1.18; 95 confidence interval 1.03 to 1.29).
In Ontario, 1-year survival rates after an index stroke are higher for those from the richest compared to the least wealthy areas, and this is only partly explained by age, sex, comorbid conditions, and other baseline risk factors.
评估可能导致低收入地区人群中风病死率升高的因素。
我们对 2002 年 4 月 1 日至 2003 年 3 月 31 日和 2004 年 4 月 1 日至 2005 年 3 月 31 日期间在加拿大安大略省 153 家急性护理医院就诊的所有中风或 TIA 患者进行了一项基于人群的队列研究。采用收入五分位数来衡量社会经济地位,从中位数社区收入中推断得出。在 7816 例患者的研究样本中,我们根据收入五分位数确定了 1 年死亡率,并使用多变量分析评估生存差异是否可以通过心血管风险因素、中风严重程度、中风管理或其他预后因素来解释。
收入组之间的中风严重程度或中风管理没有显著差异。然而,与收入最高的组相比,收入最低的组 1 年死亡率更高,即使在调整了年龄、性别、中风类型和严重程度、合并症、医院和医生特征以及护理过程后也是如此(低 vs 高收入组的调整后危险比,1.18;95%置信区间 1.03 至 1.29)。
在安大略省,与最富有的地区相比,中风指数后的 1 年生存率更高,而最贫困地区的患者,且这种情况仅部分可以通过年龄、性别、合并症和其他基线风险因素来解释。