莫桑比克高 HIV 阳性率的预测因素:复杂样本逻辑回归建模和空间映射方法。
Predictors of high HIV+ prevalence in Mozambique: A complex samples logistic regression modeling and spatial mapping approaches.
机构信息
Department of Family Health Care Nursing, School of Nursing, University of California, San Francisco, California, United States of America.
East Surrey Hospital, Redhill, England, United Kingdom.
出版信息
PLoS One. 2020 Jun 4;15(6):e0234034. doi: 10.1371/journal.pone.0234034. eCollection 2020.
INTRODUCTION
The burden of HIV infection in southern Africa is a public health concern with an increasing number of new infections. This study sought to investigate the predictors of HIV prevalence in Mozambique through a complex samples logistic regression and spatial mapping approach using nationally representative data.
METHODS
We conducted a secondary data analysis using the 2015 Mozambique Demographic and Health Survey and AIDS Indicator Survey. The analysis performed in four stages while incorporating population survey sampling weights did the following: i) created a complex sample plan file in SPSS, ii) performed the weighted estimate of HIV prevalence, iii) performed complex sample chi-square test of independence, and then iv) performed complex sample logistic regression modeling.
RESULTS
Out of 11,270 participants, 1,469 (13.0%) tested positive for HIV. The prevalence of HIV infection was higher in females (15.1%) than males (10.2%). We found that urban dwellers were more likely to be HIV-positive compared to rural dwellers (AOR: 1.70; CI: 1.27, 2.27). We observed provincial variations in HIV prevalence, with Maputo Cidade (17.4%), Maputo Provincia (22.6%), Gaza (25.2%) recording higher prevalence above the national estimate. Other independent predictors of HIV infection in Mozambique included age, education level, marital status, total lifetime sexual partners, and having had an STI in the last 12 months.
CONCLUSIONS
The study revealed associations between high-risk sexual behavior and HIV infection. Results from our spatial mapping approach can help health policy makers to better allocate resources for cost-effective HIV/AIDS interventions. Pre-Exposure Prophylaxis (PrEP) campaigns among high-risk groups should be pursued to lower the reservoir of HIV among high-risk groups.
简介
南部非洲的艾滋病毒感染负担是一个公共卫生关注点,新感染人数不断增加。本研究旨在通过复杂样本逻辑回归和空间映射方法,利用全国代表性数据,探讨莫桑比克艾滋病毒流行的预测因素。
方法
我们使用 2015 年莫桑比克人口与健康调查和艾滋病指标调查进行了二次数据分析。在纳入人口调查抽样权重的情况下,分析分四个阶段进行:i)在 SPSS 中创建复杂样本计划文件,ii)进行艾滋病毒流行率的加权估计,iii)进行复杂样本卡方独立性检验,然后 iv)进行复杂样本逻辑回归建模。
结果
在 11270 名参与者中,有 1469 人(13.0%)艾滋病毒检测呈阳性。女性(15.1%)艾滋病毒感染率高于男性(10.2%)。我们发现,与农村居民相比,城市居民更有可能感染艾滋病毒(优势比:1.70;95%置信区间:1.27,2.27)。我们观察到艾滋病毒流行率在各省之间存在差异,马普托市(17.4%)、马普托省(22.6%)和加扎(25.2%)的流行率高于全国估计值。莫桑比克艾滋病毒感染的其他独立预测因素包括年龄、教育程度、婚姻状况、终生性伴侣总数和过去 12 个月中是否患有性传播感染。
结论
该研究揭示了高危性行为与艾滋病毒感染之间的关联。我们空间映射方法的结果可以帮助卫生政策制定者更好地分配资源,以进行具有成本效益的艾滋病毒/艾滋病干预。应在高危人群中开展暴露前预防(PrEP)运动,以降低高危人群中艾滋病毒的储存量。