Chen Wen, Zhou Fangjing, Hall Brian J, Tucker Joseph D, Latkin Carl, Renzaho Andre M N, Ling Li
Faculty of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
Center for Migrant Health Policy, Sun Yat-sen University, Guangzhou, Guangdong, China.
PLoS One. 2017 Jul 20;12(7):e0180801. doi: 10.1371/journal.pone.0180801. eCollection 2017.
Achieving high coverage of HIV testing services is critical in many health systems, especially where HIV testing services remain centralized and inconvenient for many. As a result, planning the optimal spatial distribution of HIV testing sites is increasingly important. We aimed to assess the relationship between geographic distance and uptake of HIV testing services among the general population in Guangzhou, China. Utilizing spatial epidemiological methods and stratified household random sampling, we studied 666 adults aged 18-59. Computer-assisted interviews assessed self-reported HIV testing history. Spatial scan statistic assessed the clustering of participants who have ever been tested for HIV, and two-level logistic regression models assessed the association between uptake of HIV testing and the mean driving distance from the participant's residence to all HIV testing sites in the research sites. The percentage of participants who have ever been tested for HIV was 25.2% (168/666, 95%CI: 21.9%, 28.5%), and the majority (82.7%) of participants tested for HIV in Centres for Disease Control and Prevention, public hospitals or STIs clinics. None reported using self-testing. Spatial clustering analyses found a hotspot included 48 participants who have ever been tested for HIV and 25.8 expected cases (Rate Ratio = 1.86, P = 0.002). Adjusted two-level logistic regression found an inverse relationship between geographic distance (kilometers) and ever being tested for HIV (aOR = 0.90, 95%CI: 0.84, 0.96). Married or cohabiting participants (aOR = 2.14, 95%CI: 1.09, 4.20) and those with greater social support (aOR = 1.04, 95%CI: 1.01, 1.07) were more likely to be tested for HIV. Our findings underscore the importance of considering the geographical distribution of HIV testing sites to increase testing. In addition, expanding HIV testing coverage by introducing non-facility based HIV testing services and self-testing might be useful to achieve the goal that 90% of people living with HIV knowing their HIV status by the year 2020.
在许多卫生系统中，实现艾滋病毒检测服务的高覆盖率至关重要，尤其是在艾滋病毒检测服务仍集中化且对许多人来说不方便的地方。因此，规划艾滋病毒检测点的最佳空间分布变得越来越重要。我们旨在评估中国广州普通人群中地理距离与艾滋病毒检测服务接受率之间的关系。利用空间流行病学方法和分层家庭随机抽样，我们研究了666名年龄在18 - 59岁的成年人。通过计算机辅助访谈评估自我报告的艾滋病毒检测史。空间扫描统计评估了曾经接受过艾滋病毒检测的参与者的聚集情况，两级逻辑回归模型评估了艾滋病毒检测接受率与参与者住所到研究地点所有艾滋病毒检测点的平均驾车距离之间的关联。曾经接受过艾滋病毒检测的参与者比例为25.2%（168/666，95%置信区间：21.9%，28.5%），大多数（82.7%）接受艾滋病毒检测的参与者是在疾病预防控制中心、公立医院或性传播感染诊所进行检测的。没有人报告使用自我检测。空间聚集分析发现一个热点地区包括48名曾经接受过艾滋病毒检测的参与者和25.8例预期病例（率比 = 1.86，P = 0.002）。调整后的两级逻辑回归发现地理距离（公里）与曾经接受艾滋病毒检测之间存在负相关关系（调整后比值比 = 0.90，95%置信区间：0.84，0.96）。已婚或同居的参与者（调整后比值比 = 2.14，95%置信区间：1.09，4.20）以及社会支持度较高的参与者（调整后比值比 = 1.04，95%置信区间：1.01，1.07）更有可能接受艾滋病毒检测。我们的研究结果强调了考虑艾滋病毒检测点的地理分布以增加检测的重要性。此外，通过引入非设施基础的艾滋病毒检测服务和自我检测来扩大艾滋病毒检测覆盖范围，可能有助于实现到2020年90%的艾滋病毒感染者知晓自己感染状况的目标。
