SES IMPACT ON RACIAL DIFFERENCES IN STROKE MORTALITY

美国黑人人群的中风死亡率通常被认为是 大约是美国白色人群的1.5倍。 越来越多的人意识到， 这可能主要是由于社会经济地位（SES）的差异。 中风 死亡率与收入、教育水平和其他因素有关。 SES的措施。 由于美国种族之间明显的SES差异， 这可能是种族评估中的混淆因素， 中风的差异。 此外，黑人中风死亡率过高， 在人口的所有组成部分中并不一致。 例如，在一个示例中， 45岁时黑人中风死亡率比白色人高出4倍， 但到85岁时，黑人对白色人的风险大致相同。 不仅 是识别出黑人的亚群， 利益，但也可以合理地假设，社会经济地位的影响可能 不同的功能，人口和其他社会支持因素。 该项目将使用国家纵向死亡率研究的数据 （NLMS），以评估中风死亡率在 美国黑人人口，可归因于SES的种族差异。 次要目标是评估其他人口、地理、 社会支持因素对脑卒中死亡率种族差异的影响。 这些因素将被视为潜在的影响修饰符， 评估SES在卒中死亡率种族差异中的作用。 此外，还将进行二次分析，以检查 数据集中的其它因素（即，死亡率的地域差异 率）和SES对其他疾病的影响（即，缺血性心脏 疾病）。

Stroke mortality in the U.S. black population is generally recognized to be approximately 1.5 times that observed in the U.S. white population. There is a growing awareness that observed ethnic differences in mortality may be largely due to differences in socio-economic status (SES). Stroke mortality has been related to income, educational level, and other measures of SES. Because of the clear SES differences between U.S. racial groups, this may be acting as a confounder in the assessment of racial differences in stroke. In addition, the black excess stroke mortality is not consistent across all components of the population. For example, there is a four-fold black-to-white excess in stroke mortality at age 45, but by age 85 the black-to-white risk is approximately the same. Not only is identification of subgroups of blacks at extraordinary risk of great interest, but also it is reasonable to assume that the impact of SES may differ as a function of demographic, and other social support factors. This project will use data from the National Longitudinal Mortality Study (NLMS) to evaluate the proportion of the excess stroke mortality among the U.S. black population that is attributable to racial differences in SES. Secondary aims are to assess the impact of other demographic, geographic, and social support factors on racial differences in stroke mortality. These factors will be considered as a potential effect modifiers in the assessment of the role of SES on racial differences in stroke mortality. In addition, secondary analyses will be conducted to examine the impact of other factors in the data set (i.e., geographic variations in mortality rates) and the impact of SES on other diseases (i.e., ischemic heart disease).