Table 3 Binary logistic regression analysis on the factors associated with self-reported STIs among sexually active men in sub-Saharan Africa
Variable | Model I cOR[95%CI] | Model II aOR[95%CI] |
|---|---|---|
Age | ||
 15–24 | 2.382***[2.156,2.632] | 1.414***[1.255,1.593] |
 25–34 | 2.200***[1.999,2.420] | 1.768***[1.600,1.953] |
 35–44 | 1.549***[1.397,1.717] | 1.449***[1.307,1.608] |
 45+ | Ref | Ref |
Residence | ||
 Rural | 0.808***[0.763,0.855] | 0.930*[0.876,0.991] |
 Urban | Ref | Ref |
Educational level | ||
 Second/higher | 1.574***[1.455,1.704] | 1.008[0.912,1.114] |
 Primary | 1.317***[1.207,1.436] | 1.095[0.994,1.206] |
 No education | Ref | Ref |
Marital status | ||
 Not married | Ref | Ref |
 Married | 0.487***[0.460,0.515] | 0.971[0.890,1.058] |
Occupation | ||
 Working | 0.857** [0.782,0.940] | 1.242***[1.122,1.376] |
 Not working | Ref | Ref |
Age at first sex | ||
 < =19 | 2.052***[1.920,2.193] | 1.196***[1.111,1.288] |
 20+ | Ref | Ref |
Number of sex partners excluding spouse in the last 12 months | ||
 0 | 0.219***[0.203,0.235] | 0.315***[0.285,0.349] |
 1 | 0.439***[0.407,0.473] | 0.512***[0.474,0.552] |
 2+ | Ref | Ref |
Paid for sex | ||
 No | 0.405***[0.380,0.432] | 0.548***[0.511,0.588] |
 Yes | Ref | Ref |
Condom usage | ||
 No | 0.915** [0.856,0.978] | 1.348***[1.245,1.459] |
 Yes | Ref | Ref |
Comprehensive HIV and AIDS knowledge | ||
 No | 1.232***[1.163,1.305] | 1.143***[1.075,1.216] |
 Yes | Ref | Ref |
Exposure to newspaper | ||
 No | 0.881***[0.832,0.934] | 0.926*[0.864,0.993] |
 Yes | Ref | Ref |
Health insurance coverage | ||
 No | 1.105*[1.002,1.218] | 1.098[0.983,1.227] |
 Yes | Ref | Ref |
Country | ||
 Burkina Faso | 0.300***[0.182,0.493] | 0.380***[0.231,0.625] |
 Benin | 1.295[0.870,1.928] | 1.237[0.831,1.842] |
 Burundi | 1.072[0.710,1.618] | 1.648*[1.090,2.491] |
 Dr. Congo | 2.657***[1.821,3.877] | 2.109***[1.445,3.077] |
 Congo | 2.899***[1.976,4.252] | 1.882**[1.280,2.765] |
 Cote D’ivoire | 2.282***[1.543,3.375] | 1.951***[1.320,2.885] |
 Cameroon | 2.356***[1.606,3.456] | 2.078***[1.417,3.048] |
 Ethiopia | 0.686[0.457,1.029] | 0.901[0.601,1.349] |
 Gabon | 2.409***[1.638,3.542] | 2.021***[1.368,2.983] |
 Ghana | 2.669***[1.801,3.955] | 2.964***[1.996,4.402] |
 Gambia | 0.701[0.423,1.163] | 0.894[0.539,1.483] |
 Guinea | 3.309***[2.225,4.921] | 3.729***[2.509,5.542] |
 Kenya | 0.737[0.495,1.098] | 0.799[0.537,1.189] |
 Liberia | 6.665***[4.578,9.703] | 5.996***[4.117,8.731] |
 Lesotho | 1.401[0.879,2.235] | 1.185[0.743,1.890] |
 Mali | 1.677* [1.101,2.554] | 2.241***[1.470,3.416] |
 Malawi | 1.169[0.784,1.742] | 1.171[0.786,1.743] |
 Mozambique | 2.438***[1.657,3.589] | 2.169***[1.474,3.193] |
 Nigeria | 0.825[0.559,1.219] | 0.935[0.634,1.379] |
 Niger | 0.283***[0.152,0.528] | 0.447*[0.239,0.834] |
 Namibia | 1.738** [1.158,2.607] | 2.028***[1.347,3.053] |
 Sierra Leone | 4.839***[3.331,7.030] | 4.571***[3.145,6.642] |
 Senegal | 0.412** [0.241,0.704] | 0.466**[0.273,0.795] |
 Chad | 0.774[0.488,1.227] | 0.928[0.586,1.470] |
 Togo | 0.922[0.594,1.432] | 1.076[0.694,1.670] |
 Zambia | 1.876**[1.288,2.731] | 1.879***[1.292,2.732] |
 Zimbabwe | 1.307[0.881,1.939] | 1.275[0.860,1.891] |
 Comoros | Ref | Ref |
 N | 130,196 | 130,196 |