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首页> 外文期刊>Annals of epidemiology >County-level socioeconomic status and survival after HIV diagnosis, United States.
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County-level socioeconomic status and survival after HIV diagnosis, United States.

机译：美国，艾滋病诊断后，县级社会经济地位和生存率。

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摘要

PURPOSE: To estimate relative survival (RS) after human immunodeficiency virus (HIV) diagnosis, by race/ethnicity and county-level socioeconomic status (SES). METHODS: We estimated 5-year RS by age, race/ethnicity, transmission category, sex, diagnosis year, CD4 count, and by county-level SES variables from the U.S. Census. Data, from the national HIV/AIDS Reporting System, were for HIV-infected persons ages > or =13 years (diagnosis during 1996-2003 and follow-up through 2005). We calculated RS proportions by using a maximum likelihood algorithm and modeled the relative risk of excess death (RR) using generalized linear models, with poverty as a random effect. RESULTS: For men, RS was worse in counties with larger proportions of people living below the 2000 U.S. poverty level (87.7% for poverty of > or =20% vs. 90.1% for poverty of <5.0%) and where unemployment was greater (87.8% where unemployment > 7.1% vs. 90.5% where unemployment < 4.0%). The effects of county-level SES on RS of women were similar. In multilevel multivariate models, RR for men and women within 5 years after an HIV diagnosis was significantly worse in counties where 10.0-19.9% (compared with <5.0%) lived below the poverty level (RR = 1.3 [95% CI 1.2-1.5] and RR = 1.8 [95% CI 1.4-2.2], respectively). CONCLUSIONS: RS was worse in lower SES areas. To help address the impact of county-level SES, resources for HIV testing, care, and proven economic interventions should be directed to areas with concentrations of economically disadvantaged people.
机译：目的：通过种族/族裔和县级社会经济地位（SES）评估人类免疫缺陷病毒（HIV）诊断后的相对生存（RS）。方法：我们根据年龄，种族/民族，传播类别，性别，诊断年份，CD4计数以及美国人口普查县级SES变量估算了5年RS。来自国家艾滋病毒/艾滋病报告系统的数据适用于年龄大于或等于13岁的艾滋病毒感染者（1996-2003年诊断，2005年随访）。我们使用最大似然算法计算RS比例，并使用广义线性模型（以贫困为随机效应）对超额死亡的相对风险（RR）进行建模。结果：对于男性，在生活在2000年美国贫困线以下的人口比例较大的县，RS较差（贫困率>或= 20％的贫困人口占87.7％，贫困率<5.0％的贫困人口占90.1％），而失业率更高（失业率> 7.1％时为87.8％，而失业率<4.0％则为90.5％）。县级SES对女性RS的影响相似。在多变量多变量模型中，在艾滋病毒诊断后的5年内，男女之间的RR显着恶化，这些县的贫困水平低于10.0-19.9％（而<5.0％）（RR = 1.3 [95％CI 1.2-1.5] ]和RR = 1.8 [95％CI 1.4-2.2]。结论：在低SES地区RS较差。为了帮助解决县级SES的影响，应该将艾滋病毒检测，护理和经过验证的经济干预措施的资源用于经济弱势人群集中的地区。

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