Abstract：
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.
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.
摘要：
背景：结构性种族主义导致美国（US）暴露前预防（PrEP）覆盖范围的地域不平等。本研究旨在调查结构性种族主义各个维度中PrEP利用的县级差异。
方法：从AIDSVu检索2013-2021年全国县级PrEP率和PrEP与需求比（PNR）数据。PrEP率定义为每100,000人口的PrEP用户数量，PNR定义为每个日历年的PrEP使用者与新诊断HIV的比率。线性混合效应回归被用来识别县级结构种族主义的关联(例如，住房和社会经济地位中的结构性种族主义)，在美国全国范围内具有PrEP率和PNR。
结果：从2013年到2021年，平均PrEP率和PNR分别从3.62增加到71.10和从0.39增加到10.20。住房结构性种族主义较多的县更有可能有较低的PrEP率（调整后的β=-5.80，95%CI[-8.84，-2.75]）。在社会经济地位较低的结构性种族主义县发现较高的PNR（调整后的β=-2.64，95％CI[-3.68，-1.61]）。区域,与中西部地区相比，西部地区的县更有可能有更高的PrEP率(调整后的β=30.99，95%CI[22.19，39.80])，南部各县的PNR较低(调整后的β=-1.87，95%CI[-2.57，-1.17])。
结论：县级结构性种族主义在理解扩大PrEP覆盖范围的挑战方面发挥着至关重要的作用。研究结果强调了不同地区量身定制策略的重要性，并为未来干预措施提供了有价值的见解，以优化PrEP的实施。
方法：从AIDSVu检索2013-2021年全国县级PrEP率和PrEP与需求比（PNR）数据。PrEP率定义为每100,000人口的PrEP用户数量，PNR定义为每个日历年的PrEP使用者与新诊断HIV的比率。线性混合效应回归被用来识别县级结构种族主义的关联(例如，住房和社会经济地位中的结构性种族主义)，在美国全国范围内具有PrEP率和PNR。
结果：从2013年到2021年，平均PrEP率和PNR分别从3.62增加到71.10和从0.39增加到10.20。住房结构性种族主义较多的县更有可能有较低的PrEP率（调整后的β=-5.80，95%CI[-8.84，-2.75]）。在社会经济地位较低的结构性种族主义县发现较高的PNR（调整后的β=-2.64，95％CI[-3.68，-1.61]）。区域,与中西部地区相比，西部地区的县更有可能有更高的PrEP率(调整后的β=30.99，95%CI[22.19，39.80])，南部各县的PNR较低(调整后的β=-1.87，95%CI[-2.57，-1.17])。
结论：县级结构性种族主义在理解扩大PrEP覆盖范围的挑战方面发挥着至关重要的作用。研究结果强调了不同地区量身定制策略的重要性，并为未来干预措施提供了有价值的见解，以优化PrEP的实施。
