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Table 2 Results from Blinder-Oaxaca decomposition analysis of gender inequalities in HIV/AIDS prevalence

From: What explains gender inequalities in HIV/AIDS prevalence in sub-Saharan Africa? Evidence from the demographic and health surveys

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
  1. 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
  2. SE: Standard Error
  3. aCountries where the difference between men and women in the response to risk factors mainly explains the gender gap at p-value = 5 %
  4. bCountries where the difference in the distribution of risk factors between men and women mainly explains the gender gap at p-value = 5 %
  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 %
  6. dPart of gender inequality in HIV/AIDS prevalence attributable to differences in the distribution of risk factors
  7. ePart of gender inequality in HIV/AIDS prevalence attributable to differences in the effects of risk factors
  8. 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
  9. 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