Factors Explaining Excess Stroke Prevalence in the US Stroke Belt
Factors Explaining Excess Stroke Prevalence in the US Stroke Belt
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DOI：
10.1161/strokeaha.109.561688
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发表时间：
2009-10-01
期刊：
影响因子：
8.3
通讯作者：
Giles, Wayne H.
中科院分区：
文献类型：
--
作者：
Liao, Youlian;Greenlund, Kurt J.;Giles, Wayne H.
背景和目的：与美国其他地区相比，在东南部各州（卒中带）观察到较高的卒中风险和负担。我们使用来自全国横断面研究的大型数据集来检查这些差异的原因。方法：采用2005年和2007年行为风险因素监测系统的自我报告数据（n = 765 368）。自我报告的卒中患病率（n = 27962）的潜在影响因素是人口统计学（年龄、性别、地理位置和种族/民族）、社会经济地位（教育和收入）、常见危险因素（吸烟和肥胖）和慢性疾病（高血压、糖尿病和冠心病）。采用多元逻辑回归进行分析。结果：比较11个州卒中带与非卒中带地区自我报告的卒中患病率的年龄和性别调整OR为1.25 （95% CI， 1.19至1.31）。在脑卒中带中，不平等的黑人/白人分布占了20%的超额患病率（OR降至1.20；1.15至1.26）。大约三分之一（32%）的过度流行是由社会经济地位或风险因素和慢性病单独造成的（or, 1.12）。在完全调整的logistic模型中，OR进一步降低到1.07(1.02至1.13)，降低了72%。结论：脑卒中患病率的地区差异主要是社会经济状况、危险因素和常见慢性病患病率的差异造成的。(中风。2009;40:3336 - 3341)。
Background and Purpose-Higher risk and burden of stroke have been observed within the southeastern states (the Stroke Belt) compared with elsewhere in the United States. We examined reasons for these disparities using a large data set from a nationwide cross-sectional study.Methods-Self-reported data from the 2005 and 2007 Behavioral Risk Factor Surveillance System were used (n = 765 368). The potential contributors for self-reported stroke prevalence (n = 27 962) were demographics (age, sex, geography, and race/ethnicity), socioeconomic status (education and income), common risk factors (smoking and obesity), and chronic diseases (hypertension, diabetes, and coronary heart disease). Multivariate logistic regression was used in the analysis.Results-The age-and sex-adjusted OR comparing self-reported stroke prevalence in the 11-state Stroke Belt versus non-Stroke Belt region was 1.25 (95% CI, 1.19 to 1.31). Unequal black/white distribution by region accounted for 20% of the excess prevalence in the Stroke Belt (OR reduced to 1.20; 1.15 to 1.26). Approximately one third (32%) of the excess prevalence was accounted either by socioeconomic status alone or by risk factors and chronic disease alone (OR, 1.12). The OR was further reduced to 1.07 (1.02 to 1.13) in the fully adjusted logistic model, a 72% reduction.Conclusions-Differences in socioeconomic status, risk factors, and prevalence of common chronic diseases account for most of the regional differences in stroke prevalence. (Stroke. 2009;40:3336-3341.)