Related Experiment Video
Updated: Dec 26, 2025

Comprehensive & Cost Effective Laboratory Monitoring of HIV/AIDS: an African Role Model
Published on: October 31, 2010
The effect of gender inequality on HIV incidence in Sub-Saharan Africa
D Sia1, É Nguemeleu Tchouaket1, M Hajizadeh2
1Départment des sciences infirmières, Université du Québec en Outaouais, Saint-Jérôme, Canada.
Objective:
We aimed to quantify the extent to which country-level trends in HIV incidence in Sub-Saharan Africa (SSA) were influenced by gender inequalities, measured by gender gaps in educational attainment, income, and a Gender Inequality Index (GII).
Study Design:
We examined the relation between gender inequality and HIV incidence using country-level panel data from 24 SSA countries for the period between 2000 and 2016.
Methods:
Our goal was to estimate the relation between within-country changes in gender inequality and HIV incidence. We compared results from fixed effects and random effects models for estimating the effect of gender inequalities on changes in HIV incidence. Based on the results of the Hausman test, the fixed effects model was selected as the preferred approach.
Results:
HIV incidence decreased by nearly one-half over the period from 2000 to 2016. We estimated that a one percent increase in the GII was associated with a 1.6 percent increase in HIV incidence (95% confidence interval = [0.21%; 3.00%]), after adjusting by country-level socio-economic and governance variables.
Conclusions:
Our study suggests that addressing gender inequalities is a potential strategy to reduce HIV incidence in the SSA region. To control HIV infection, policymakers and public health practitioners should support relevant interventions for promoting gender equality. Further work is needed to identify specific interventions to improve gender inequality and to examine their impacts on changes in HIV incidence.
Related Concept Videos
Sexually Transmitted Infections
Two-Way ANOVA
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
Bias in Epidemiological Studies
Factors Affecting the Risk of Infection
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
Retrovirus Life Cycles
X-linked Traits

