美国全国的结构性种族主义与 HIV 暴露前预防措施的使用:县级分析。

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Fanghui Shi, Tianyue Mi, Xiaoming Li, Huan Ning, Zhenlong Li, Xueying Yang
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引用次数: 0

摘要

背景:结构性种族主义造成了美国暴露前预防疗法(PrEP)覆盖率的地域不平等。本研究旨在从结构性种族主义的不同层面调查县级 PrEP 利用率的差异:方法:从 AIDSVu 获取 2013-2021 年全国县级 PrEP 率和 PrEP 需求比 (PNR) 数据。PrEP 率定义为每 10 万人口中 PrEP 使用者的数量,PNR 定义为每一日历年 PrEP 使用者与新确诊 HIV 感染者的比率。采用线性混合效应回归法来确定美国全国范围内县级结构性种族主义(如住房和社会经济地位方面的结构性种族主义)与 PrEP 率和 PNR 的关联:从 2013 年到 2021 年,平均 PrEP 率和 PNR 分别从 3.62 上升到 71.10 和从 0.39 上升到 10.20。在住房方面存在更多结构性种族主义的县,PrEP 率更有可能偏低(调整后 β = - 5.80,95% CI [- 8.84, - 2.75])。在社会经济地位结构性种族主义较低的县,PNR 较高(调整后 β = - 2.64,95% CI [- 3.68, - 1.61])。从地区来看,与中西部地区相比,西部地区的县更有可能拥有较高的 PrEP 率(调整后 β = 30.99,95% CI [22.19,39.80]),而南部地区的县拥有较低的 PNR(调整后 β = - 1.87,95% CI [- 2.57,- 1.17]):县级结构性种族主义在理解扩大 PrEP 覆盖面所面临的挑战方面起着至关重要的作用。研究结果强调了在不同地区采取有针对性的策略的重要性,并为未来优化 PrEP 实施的干预措施提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Structural Racism and HIV Pre-exposure Prophylaxis Use in the Nationwide US: A County-Level Analysis.

Structural Racism and HIV Pre-exposure Prophylaxis Use in the Nationwide US: A County-Level Analysis.

Background: Structural racism contributes to geographical inequalities in pre-exposure prophylaxis (PrEP) coverage in the United States (US). This study aims to investigate county-level variability in PrEP utilization across diverse dimensions of structural racism.

Methods: The 2013-2021 nationwide county-level PrEP rate and PrEP-to-need ratio (PNR) data were retrieved from AIDSVu. PrEP rate was defined as the number of PrEP users per 100,000 population, and PNR was defined as the ratio of PrEP users to new HIV diagnoses per calendar year. Linear mixed effect regression was employed to identify associations of county-level structural racism (e.g., structural racism in housing and socioeconomic status) with PrEP rate and PNR on a nationwide scale of the US.

Results: From 2013 to 2021, the mean PrEP rate and PNR increased from 3.62 to 71.10 and from 0.39 to 10.20, respectively. Counties with more structural racism in housing were more likely to have low PrEP rates (adjusted β =  - 5.80, 95% CI [- 8.84, - 2.75]). Higher PNR was found in counties with lower structural racism in socioeconomic status (adjusted β =  - 2.64, 95% CI [- 3.68, - 1.61]). Regionally, compared to the Midwest region, counties in the West region were more likely to have higher PrEP rate (adjusted β = 30.99, 95% CI [22.19, 39.80]), and counties in the South had lower PNR (adjusted β =  - 1.87, 95% CI [- 2.57, - 1.17]).

Conclusions: County-level structural racism plays a crucial role in understanding the challenges of scaling up PrEP coverage. The findings underscore the importance of tailored strategies across different regions and provide valuable insights for future interventions to optimize PrEP implementation.

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CiteScore
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