Sia Drissa, Onadja Yentéma, Nandi Arijit, Foro Anne, Brewer Timothy
Institute for Health and Social Policy, McGill University, 1130 Pine Avenue West, Montréal, QC, H3A 1A3, Canada, Department of Demography, Université de Montréal, 3150 rue Jean-Brillant, Montréal, QC, H3C 3J7, Canada, École Nationale D'adminstration Publique, 4750 avenue Henri-Julien, 5e étage, Montréal, QC, H2T 3E5, Canada and Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, 1020 Pine Avenue West, Montréal, QC, H3A 1A2, Canada
Institute for Health and Social Policy, McGill University, 1130 Pine Avenue West, Montréal, QC, H3A 1A3, Canada, Department of Demography, Université de Montréal, 3150 rue Jean-Brillant, Montréal, QC, H3C 3J7, Canada, École Nationale D'adminstration Publique, 4750 avenue Henri-Julien, 5e étage, Montréal, QC, H2T 3E5, Canada and Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, 1020 Pine Avenue West, Montréal, QC, H3A 1A2, Canada.
Health Policy Plan. 2014 Oct;29(7):938-49. doi: 10.1093/heapol/czt075. Epub 2013 Dec 17.
Within sub-Saharan Africa, women are disproportionately at risk for acquiring and having human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS). It is important to clarify whether gender inequalities in HIV prevalence in this region are explained by differences in the distributions of HIV risk factors, differences in the effects of these risk factors or some combination of both. We used an extension of the Blinder-Oaxaca decomposition approach to explain gender inequalities in HIV/AIDS in Kenya, Lesotho and Tanzania using data from the demographic and health and AIDS indicator surveys. After adjusting for covariates using Poisson regression models, female gender was associated with a higher prevalence of HIV/AIDS in Kenya [prevalence ratio (PR) = 1.73, 95% confidence interval (CI) = 1.33, 2.23 in 2003] and Lesotho (PR = 1.39, 95% CI = 1.20, 1.62 in 2004/05), but not in Tanzania. Decomposition analyses demonstrated two distinct patterns over time. In Tanzania, the gender inequality in HIV/AIDS was explained by differences in the distributions of HIV risk factors between men and women. In contrast, in Kenya and Lesotho, this inequality was partly explained by differences in the effects across men and women of measured HIV/AIDS risk factors, including socio-demographic characteristics (age and marital status) and sexual behaviours (age at first sex); these results imply that gender inequalities in HIV/AIDS would persist in Kenya and Lesotho even if men and women had similar distributions of HIV risk factors. The production of gender inequalities may vary across countries, with inequalities attributable to the unequal distribution of risk factors among men and women in some countries and the differential effect of these factors between groups in others. These different patterns have important implications for policies to reduce gender inequalities in HIV/AIDS.
在撒哈拉以南非洲地区，女性感染和患人类免疫缺陷病毒（HIV）/获得性免疫缺陷综合征（AIDS）的风险极高。重要的是要弄清楚，该地区HIV流行率方面的性别不平等是由HIV风险因素分布差异、这些风险因素影响程度的差异，还是两者的某种组合造成的。我们运用扩展的布林德-奥克分解法，利用人口与健康调查及艾滋病指标调查的数据，来解释肯尼亚、莱索托和坦桑尼亚在HIV/AIDS方面的性别不平等问题。在使用泊松回归模型对协变量进行调整后，在肯尼亚（2003年患病率比（PR）=1.73，95%置信区间（CI）=1.33，2.23）和莱索托（2004/05年PR = 1.39，95% CI = 1.20，1.62），女性性别与更高的HIV/AIDS患病率相关，但在坦桑尼亚并非如此。分解分析显示了随时间变化的两种不同模式。在坦桑尼亚，HIV/AIDS方面的性别不平等是由男女之间HIV风险因素分布的差异来解释的。相比之下，在肯尼亚和莱索托，这种不平等部分是由已测量的HIV/AIDS风险因素（包括社会人口学特征（年龄和婚姻状况）以及性行为（初次性行为年龄））在男女之间的影响差异来解释的；这些结果意味着，即便男女的HIV风险因素分布相似，HIV/AIDS方面的性别不平等在肯尼亚和莱索托仍将持续存在。性别不平等的产生在不同国家可能有所不同，在一些国家，不平等归因于男女之间风险因素的不平等分布，而在另一些国家，则归因于这些因素在不同群体之间的差异影响。这些不同模式对于减少HIV/AIDS方面性别不平等的政策具有重要意义。
