Table 2.
Results from Blinder-Oaxaca decomposition analysis of gender inequalities in HIV/AIDS prevalence
| Countries | Survey year | Gender inequality in HIV/AIDS prevalence (women-men) | Composition effectf | Response effectg | ||||
|---|---|---|---|---|---|---|---|---|
| Beta (SE) | p-value | Percentd | Beta (SE) | p-value | Percente | |||
| Cameroonc | 2011 | 2.69 | 0.012 (0.004) | 0.001 | 44.2 | 0.015 (0.005) | 0.002 | 55.8 |
| Congo Brazzavillea | 2009 | 2.07 | −0.003 (0.005) | 0.478 | −15.6 | 0.024 (0.007) | 0.000 | 115.6 |
| Côte d’Ivoirea | 2005 | 3.10 | 0.005 (0.007) | 0.514 | 16.2 | 0.024 (0.010) | 0.013 | 83.8 |
| Ethiopiaa | 2011 | 0.88 | 0.001 (0.003) | 0.698 | 13.3 | 0.007 (0.004) | 0.039 | 86.7 |
| Ghanab | 2003 | 1.08 | 0.01 (0.003) | 0.000 | 91.9 | 0.001 (0.004) | 0.811 | 8.1 |
| Guineac | 2005 | 0.79 | −0.014 (0.007) | 0.05 | −176.5 | 0.023 (0.008) | 0.006 | 276.5 |
| Liberia | 2007 | 0.68 | −0.008 (0.008) | 0.314 | −111.1 | 0.014 (0.009) | 0.094 | 211.1 |
| Malawic | 2010 | 4.50 | 0.022 (0.006) | 0.000 | 48.8 | 0.023 (0.008) | 0.006 | 51.2 |
| Mozambiquea | 2009 | 3.63 | 0.006 (0.011) | 0.583 | 18.5 | 0.026 (0.013) | 0.051 | 81.5 |
| D.R. Congo | 2007 | 0.70 | −0.001 (0.004) | 0.852 | −10.6 | 0.008 (0.005) | 0.106 | 110.6 |
| Rwandaa | 2010 | 1.30 | 0.002 (0.004) | 0.524 | 18.6 | 0.01 (0.005) | 0.028 | 81.4 |
| Swazilandc | 2006/07 | 11.45 | 0.021 (0.009) | 0.015 | 18.7 | 0.093 (0.012) | 0.000 | 81.3 |
| Ugandab | 2011 | 2.10 | 0.018 (0.003) | 0.000 | 83.7 | 0.003 (0.005) | 0.476 | 16.3 |
| Zambiaa | 2007 | 3.80 | 0.005 (0.008) | 0.522 | 13.9 | 0.031 (0.01) | 0.003 | 86.1 |
| Zimbabwea | 2010/11 | 5.05 | 0.009 (0.007) | 0.188 | 17.7 | 0.044 (0.010) | 0.000 | 82.3 |
Note: using this method, the net percent contribution of both components always equals to 100. A contribution may be negative (less than zero) or positive and can even exceed 100. A positive contribution indicates that the component contributes to the greater prevalence of HIV/AIDS among women relative to men, whereas a negative contribution indicates the opposite
SE: Standard Error
aCountries where the difference between men and women in the response to risk factors mainly explains the gender gap at p-value = 5 %
bCountries where the difference in the distribution of risk factors between men and women mainly explains the gender gap at p-value = 5 %
cCountries where difference in both the response to factors and the distribution of factors between men and women explains the gender gap at p-value = 5 %
dPart of gender inequality in HIV/AIDS prevalence attributable to differences in the distribution of risk factors
ePart of gender inequality in HIV/AIDS prevalence attributable to differences in the effects of risk factors
fRepresent the contribution to gender inequalities in HIV/AIDS prevalence due to gender differences in the distributions of observable HIV/AIDS risk factors between women and men
gReflect the contribution to gender inequalities in HIV/AIDS due to gender differences in the effects of measured HIV/AIDS risk factors, as well as unmeasured factors not included in the model