Coverage of HIV Testing Services

HIVAIDS-related Knowledge, Attitudes, and Behavior • 235 Table 13.9.1 Coverage of prior HIV testing: Women Percentage of ever-married women age 15-49 who know where to obtain an HIV test, percent distribution of women age 15-49 by testing status and by whether they received the results of the last test, the percentage of women ever tested, and the percentage of women age 15-49 who were tested in the past 12 months and received the results of the last test, according to background characteristics, Afghanistan 2015 Percentage who know where to get an HIV test Percent distribution of women by testing status and by whether they received the results of the last test Percentage who have been tested for HIV in the past 12 months and received the results of the last test Background characteristic Ever tested and received results Ever tested, did not receive results Never tested 1 Total Percentage ever tested Number of women Age 15-24 8.5 0.6 0.0 99.4 100.0 0.6 0.5 7,915 15-19 8.5 1.4 0.0 98.6 100.0 1.4 1.2 1,825 20-24 8.6 0.3 0.0 99.6 100.0 0.4 0.2 6,089 25-29 9.2 0.5 0.2 99.3 100.0 0.7 0.4 6,299 30-39 8.7 0.5 0.0 99.4 100.0 0.6 0.3 8,765 40-49 8.5 0.2 0.1 99.7 100.0 0.3 0.2 6,482 Marital status Married 8.8 0.5 0.1 99.4 100.0 0.6 0.4 28,671 DivorcedSeparated Widowed 6.3 0.0 0.0 100.0 100.0 0.0 0.0 790 Residence Urban 13.4 1.4 0.3 98.3 100.0 1.7 1.1 6,870 Rural 7.3 0.2 0.0 99.8 100.0 0.2 0.1 22,591 Province 2 Kabul 10.4 1.8 0.3 97.8 100.0 2.2 1.6 3,658 Kapisa 3.0 0.6 0.1 99.4 100.0 0.6 0.2 205 Parwan 4.5 0.0 0.2 99.8 100.0 0.2 0.0 625 Wardak 6.9 0.0 0.1 99.9 100.0 0.1 0.0 382 Logar 8.8 0.0 0.0 100.0 100.0 0.0 0.0 472 Nangarhar 9.0 0.3 0.4 99.3 100.0 0.7 0.0 794 Laghman 31.3 0.4 0.2 99.3 100.0 0.7 0.2 583 Panjsher 0.4 0.0 0.0 100.0 100.0 0.0 0.0 54 Baghlan 2.0 0.0 0.0 100.0 100.0 0.0 0.0 839 Bamyan 2.9 0.0 0.0 100.0 100.0 0.0 0.0 303 Ghazni 4.8 0.4 0.1 99.5 100.0 0.5 0.3 1,328 Paktika 0.1 0.0 0.0 100.0 100.0 0.0 0.0 792 Paktya 6.4 0.0 0.0 100.0 100.0 0.0 0.0 542 Khost 0.7 0.0 0.0 100.0 100.0 0.0 0.0 851 Kunarha 4.2 0.1 0.0 99.9 100.0 0.1 0.0 559 Nooristan 0.1 0.0 0.0 100.0 100.0 0.0 0.0 222 Badakhshan 1.5 0.1 0.0 99.9 100.0 0.1 0.0 1,004 Takhar 1.3 0.0 0.0 100.0 100.0 0.0 0.0 1,105 Kunduz 8.2 0.9 0.0 99.1 100.0 0.9 0.6 1,232 Samangan 1.4 0.0 0.0 100.0 100.0 0.0 0.0 330 Balkh 7.4 0.6 0.1 99.3 100.0 0.7 0.4 1,781 Sar-E-Pul 1.1 0.3 0.0 99.7 100.0 0.3 0.1 654 Ghor 15.1 0.0 0.0 100.0 100.0 0.0 0.0 715 Daykundi 0.2 0.0 0.0 100.0 100.0 0.0 0.0 329 Urozgan 0.2 0.0 0.0 100.0 100.0 0.0 0.0 230 Kandahar 5.9 0.2 0.0 99.8 100.0 0.2 0.1 2,227 Jawzjan 1.9 0.0 0.1 99.9 100.0 0.1 0.0 614 Faryab 13.6 0.2 0.0 99.8 100.0 0.2 0.2 2,114 Helmand 3.1 0.0 0.1 99.9 100.0 0.1 0.0 875 Badghis 0.4 0.0 0.0 100.0 100.0 0.0 0.0 650 Herat 34.7 0.9 0.0 99.1 100.0 0.9 0.7 2,316 Farah 2.6 0.6 0.0 99.4 100.0 0.6 0.4 777 Nimroz 3.2 0.0 0.0 100.0 100.0 0.0 0.0 278 Education No education 6.3 0.2 0.0 99.8 100.0 0.2 0.2 24,604 Primary 12.5 1.3 0.1 98.7 100.0 1.3 1.0 2,330 Secondary 25.1 1.6 0.3 98.0 100.0 2.0 1.1 1,971 More than secondary 43.6 5.4 0.4 94.1 100.0 5.9 3.8 556 Wealth quintile Lowest 4.6 0.0 0.0 100.0 100.0 0.0 0.0 5,904 Second 6.1 0.2 0.0 99.8 100.0 0.2 0.1 6,001 Middle 6.4 0.1 0.0 99.9 100.0 0.1 0.1 5,888 Fourth 10.8 0.4 0.1 99.5 100.0 0.5 0.3 6,010 Highest 15.9 1.8 0.3 97.9 100.0 2.1 1.3 5,657 Total 8.7 0.5 0.1 99.4 100.0 0.6 0.4 29,461 1 Includes dont knowmissing responses. 2 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 236 • HIVAIDS-related Knowledge, Attitudes, and Behavior Table 13.9.2 Coverage of prior HIV testing: Men Percentage of ever-married men age 15-49 who know where to obtain an HIV test, percent distribution of men age 15-49 by testing status and by whether they received the results of the last test, the percentage of men ever tested, and the percentage of men age 15-49 who were tested in the past 12 months and received the results of the last test, according to background characteristics, Afghanistan 2015 Percent distribution of womenmen by testing status and by whether they received the results of the last test Percentage who have been tested for HIV in the past 12 months and received the results of the last test Background characteristic Percentage who know where to get an HIV test Ever tested and received results Ever tested, did not receive results Never tested 1 Total Percentage ever tested Number of men Age 15-24 27.0 1.8 0.3 97.9 100.0 2.1 0.7 1,305 15-19 25.7 0.5 0.0 99.5 100.0 0.5 0.0 142 20-24 27.2 2.0 0.3 97.7 100.0 2.3 0.8 1,162 25-29 30.5 3.6 1.2 95.2 100.0 4.8 1.8 2,422 30-39 31.0 5.4 1.0 93.5 100.0 6.5 2.2 3,943 40-49 28.6 4.3 0.3 95.4 100.0 4.6 1.4 3,091 Marital status Married 29.7 4.3 0.7 95.0 100.0 5.0 1.7 10,679 DivorcedSeparated Widowed 26.5 0.0 3.0 97.0 100.0 3.0 0.0 81 Residence Urban 36.3 8.0 1.7 90.3 100.0 9.7 4.8 2,479 Rural 27.7 3.1 0.5 96.4 100.0 3.6 0.8 8,281 Province 1 Kabul 34.3 8.1 2.1 89.8 100.0 10.2 5.1 1,350 Kapisa 30.5 2.1 0.9 97.0 100.0 3.0 1.0 63 Parwan 39.1 0.5 0.0 99.5 100.0 0.5 0.0 220 Wardak 16.4 1.7 0.1 98.2 100.0 1.8 0.8 171 Logar 25.9 11.4 1.0 87.6 100.0 12.4 9.9 204 Nangarhar 37.0 4.2 0.0 95.8 100.0 4.2 1.1 273 Laghman 36.1 0.5 0.0 99.5 100.0 0.5 0.0 227 Panjsher 1.8 0.0 0.0 100.0 100.0 0.0 0.0 18 Baghlan 14.1 1.4 0.0 98.6 100.0 1.4 0.6 281 Bamyan 13.3 2.1 0.0 97.9 100.0 2.1 1.0 94 Ghazni 30.1 0.0 0.0 100.0 100.0 0.0 0.0 619 Paktika 11.9 0.6 0.0 99.4 100.0 0.6 0.2 322 Paktya 79.9 2.4 0.9 96.7 100.0 3.3 0.1 206 Khost 42.0 1.1 0.3 98.6 100.0 1.4 0.6 334 Kunarha 57.1 0.0 0.0 100.0 100.0 0.0 0.0 151 Nooristan 4.7 0.1 0.0 99.9 100.0 0.1 0.1 66 Badakhshan 11.5 0.0 0.0 100.0 100.0 0.0 0.0 316 Takhar 19.2 1.7 0.2 98.0 100.0 2.0 0.4 296 Kunduz 7.9 2.2 1.4 96.4 100.0 3.6 1.5 479 Samangan 10.4 0.1 0.0 99.9 100.0 0.1 0.1 125 Balkh 16.9 3.2 0.0 96.8 100.0 3.2 1.8 616 Sar-E-Pul 9.4 3.3 0.6 96.1 100.0 3.9 1.5 195 Ghor 29.9 2.3 0.0 97.7 100.0 2.3 1.1 322 Daykundi 3.6 0.2 0.0 99.8 100.0 0.2 0.2 77 Urozgan 0.2 0.0 0.0 100.0 100.0 0.0 0.0 92 Kandahar 25.3 2.1 0.4 97.4 100.0 2.6 1.0 874 Jawzjan 26.4 5.6 0.0 94.4 100.0 5.6 1.4 218 Faryab 67.8 15.8 3.3 80.8 100.0 19.2 1.4 706 Helmand 38.9 1.1 0.3 98.7 100.0 1.3 1.1 355 Badghis 19.8 0.0 0.0 100.0 100.0 0.0 0.0 231 Herat 33.7 10.5 1.1 88.4 100.0 11.6 3.4 863 Farah 27.5 1.2 0.1 98.7 100.0 1.3 0.3 295 Nimroz 14.9 0.0 0.0 100.0 100.0 0.0 0.0 93 Education No education 17.2 2.1 0.2 97.6 100.0 2.4 0.9 5,447 Primary 29.6 5.6 1.5 92.9 100.0 7.1 1.6 1,987 Secondary 46.0 5.9 1.2 92.8 100.0 7.2 2.6 2,632 More than secondary 66.1 10.7 0.9 88.4 100.0 11.6 5.1 695 Wealth quintile Lowest 18.2 2.8 0.1 97.1 100.0 2.9 1.0 2,029 Second 23.7 2.8 0.2 97.0 100.0 3.0 0.5 2,233 Middle 25.7 2.3 0.2 97.5 100.0 2.5 0.5 2,160 Fourth 36.4 3.5 1.1 95.4 100.0 4.6 1.2 2,260 Highest 44.3 10.2 2.1 87.7 100.0 12.3 5.5 2,078 Total 29.7 4.3 0.8 95.0 100.0 5.0 1.7 10,760 1 Includes dont knowmissing responses. 2 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. HIVAIDS-related Knowledge, Attitudes, and Behavior • 237 Table 13.10 Male circumcision Percentage of ever-married men age 15-49 who report having been circumcised, and percent distribution of circumcised men by type of practitioner who performed the circumcision, according to background characteristics, Afghanistan 2015 Among those circumcised who performed the circumcision Background characteristic Percentage circum- cised Number of men Traditional practitioner family friend Health worker profes- sional Other Dont know Missing Total Number of circum- cised men Age 15-19 99.6 142 32.9 26.7 26.9 13.6 0.0 100.0 142 20-24 99.3 1,162 37.2 28.1 19.6 15.0 0.1 100.0 1,154 25-29 99.1 2,422 39.0 25.7 18.4 16.8 0.1 100.0 2,401 30-34 99.2 2,008 43.9 19.8 21.4 14.7 0.3 100.0 1,992 35-39 99.1 1,935 42.4 21.4 20.0 16.1 0.1 100.0 1,918 40-44 99.0 1,402 46.5 13.2 22.3 18.0 0.0 100.0 1,388 45-49 99.0 1,688 50.6 12.3 21.8 15.3 0.0 100.0 1,671 Residence Urban 99.2 2,479 28.3 39.4 18.7 13.6 0.0 100.0 2,459 Rural 99.1 8,281 47.5 14.7 21.1 16.7 0.1 100.0 8,206 Province 1 Kabul 99.2 1,350 17.6 43.7 23.7 14.7 0.4 100.0 1,339 Kapisa 100.0 63 0.4 5.3 90.3 2.6 1.4 100.0 63 Parwan 99.1 220 2.1 7.5 89.0 1.2 0.2 100.0 218 Wardak 97.3 171 39.1 26.2 20.4 13.9 0.4 100.0 167 Logar 95.3 204 46.4 13.7 7.4 32.1 0.5 100.0 194 Nangarhar 99.3 273 41.6 49.8 1.2 7.2 0.2 100.0 271 Laghman 98.6 227 65.8 19.1 3.4 11.3 0.3 100.0 224 Panjsher 98.8 18 22.7 32.5 22.1 22.8 0.0 100.0 18 Baghlan 98.7 281 40.6 23.6 23.5 11.8 0.5 100.0 277 Bamyan 99.3 94 66.1 13.3 8.9 11.7 0.0 100.0 93 Ghazni 99.6 619 37.6 22.0 3.0 37.4 0.0 100.0 616 Paktika 98.9 322 30.8 36.8 14.1 18.2 0.0 100.0 319 Paktya 100.0 206 45.2 32.3 17.1 5.5 0.0 100.0 206 Khost 96.2 334 35.0 14.7 26.1 24.2 0.0 100.0 322 Kunarha 95.5 151 56.4 9.2 8.9 25.4 0.0 100.0 144 Nooristan 98.6 66 52.7 1.0 17.8 28.3 0.3 100.0 65 Badakhshan 99.8 316 48.5 2.2 24.1 25.2 0.0 100.0 315 Takhar 99.4 296 28.5 3.0 55.0 13.5 0.0 100.0 294 Kunduz 98.6 479 80.7 6.7 2.4 10.2 0.0 100.0 473 Samangan 100.0 125 88.4 6.6 1.4 3.6 0.0 100.0 125 Balkh 97.8 616 19.8 10.3 54.0 16.0 0.0 100.0 602 Sar-E-Pul 99.9 195 89.8 4.8 0.2 5.2 0.0 100.0 195 Ghor 99.7 322 41.9 13.3 43.0 1.8 0.0 100.0 321 Daykundi 100.0 77 32.5 8.7 17.6 41.3 0.0 100.0 77 Urozgan 99.2 92 36.1 4.8 0.0 59.1 0.0 100.0 91 Kandahar 99.8 874 54.2 31.3 0.0 14.5 0.0 100.0 872 Jawzjan 100.0 218 87.6 6.8 2.8 2.8 0.0 100.0 218 Faryab 100.0 706 83.8 1.2 14.2 0.8 0.0 100.0 706 Helmand 99.1 355 29.3 22.6 6.1 42.0 0.0 100.0 352 Badghis 100.0 231 64.0 2.0 33.8 0.2 0.0 100.0 231 Herat 100.0 863 24.1 26.4 35.3 14.2 0.0 100.0 863 Farah 99.9 295 54.0 15.6 1.2 29.2 0.0 100.0 295 Nimroz 99.6 93 16.1 19.3 37.2 27.4 0.0 100.0 93 Education No education 99.0 5,447 45.8 13.3 22.5 18.3 0.0 100.0 5,391 Primary 99.3 1,987 42.9 21.6 20.7 14.7 0.0 100.0 1,973 Secondary 99.2 2,632 40.7 27.8 17.6 13.6 0.3 100.0 2,611 More than secondary 99.6 695 30.8 43.3 15.5 10.2 0.2 100.0 692 Wealth quintile Lowest 99.2 2,029 48.0 8.8 28.4 14.8 0.0 100.0 2,013 Second 99.1 2,233 48.0 13.2 22.0 16.7 0.1 100.0 2,212 Middle 98.9 2,160 46.6 15.4 17.8 20.0 0.2 100.0 2,136 Fourth 99.1 2,260 44.4 21.5 16.4 17.7 0.0 100.0 2,241 Highest 99.3 2,078 27.8 43.2 18.6 10.2 0.2 100.0 2,064 Total 99.1 10,760 43.1 20.4 20.5 16.0 0.1 100.0 10,666 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 238 • HIVAIDS-related Knowledge, Attitudes, and Behavior Table 13.11 Place of circumcision Percent distribution of circumcised men age 15-49 by place of circumcision, according to background characteristics, Afghanistan 2015 Background characteristic Health facility Home of a health worker profes- sional Circum- cision done at home Ritual site Other home place Dont know missing Total Number of circum- cised men Age 15-19 30.2 8.0 49.2 0.0 0.0 12.7 100.0 142 20-24 22.1 14.1 46.9 0.4 2.6 13.8 100.0 1,154 25-29 16.8 13.3 54.4 0.5 2.0 13.0 100.0 2,401 30-34 13.6 13.8 57.6 0.3 1.7 13.0 100.0 1,992 35-39 13.0 12.8 57.5 0.2 4.2 12.3 100.0 1,918 40-44 6.8 15.9 60.3 0.8 1.5 14.6 100.0 1,388 45-49 7.8 10.4 65.0 0.6 2.7 13.4 100.0 1,671 Residence Urban 23.6 14.2 51.5 0.4 1.7 8.6 100.0 2,459 Rural 10.6 12.9 58.8 0.5 2.6 14.6 100.0 8,206 Province 1 Kabul 22.0 11.0 56.7 0.6 2.5 7.2 100.0 1,339 Kapisa 1.3 0.8 91.9 0.0 1.7 4.3 100.0 63 Parwan 0.7 1.3 93.4 0.4 2.1 2.1 100.0 218 Wardak 17.7 5.0 65.8 0.7 3.7 7.0 100.0 167 Logar 26.8 6.9 26.1 1.2 5.7 33.2 100.0 194 Nangarhar 35.2 37.5 20.6 0.2 0.2 6.2 100.0 271 Laghman 14.6 32.2 40.9 0.0 2.0 10.3 100.0 224 Panjsher 8.3 5.5 64.5 0.0 3.3 18.4 100.0 18 Baghlan 14.6 7.7 68.3 0.4 0.2 8.8 100.0 277 Bamyan 5.2 1.5 78.8 4.8 0.9 8.8 100.0 93 Ghazni 15.7 9.6 34.5 0.0 1.5 38.7 100.0 616 Paktika 33.3 35.3 17.0 0.0 0.9 13.5 100.0 319 Paktya 54.2 38.6 1.6 0.0 0.0 5.7 100.0 206 Khost 12.4 3.2 55.7 0.0 1.7 27.0 100.0 322 Kunarha 6.2 24.5 49.4 0.0 0.1 19.8 100.0 144 Nooristan 0.3 3.2 72.0 0.7 4.2 19.6 100.0 65 Badakhshan 0.3 6.9 73.8 0.1 3.2 15.7 100.0 315 Takhar 1.2 0.5 86.6 0.0 0.0 11.8 100.0 294 Kunduz 1.7 5.4 78.2 3.7 3.1 7.9 100.0 473 Samangan 2.1 4.0 86.5 0.5 1.5 5.4 100.0 125 Balkh 4.3 3.7 72.8 0.0 3.0 16.2 100.0 602 Sar-E-Pul 2.4 4.2 93.0 0.0 0.4 0.0 100.0 195 Ghor 8.7 3.5 83.9 0.4 1.5 2.0 100.0 321 Daykundi 2.7 0.2 62.7 0.0 0.6 33.8 100.0 77 Urozgan 4.2 37.0 0.5 0.0 0.0 58.3 100.0 91 Kandahar 30.7 50.3 5.6 0.0 4.2 9.1 100.0 872 Jawzjan 0.7 1.5 94.6 0.0 1.1 2.1 100.0 218 Faryab 0.4 0.6 89.9 0.0 8.7 0.3 100.0 706 Helmand 20.6 29.3 8.4 0.0 1.0 40.7 100.0 352 Badghis 1.3 1.2 97.4 0.0 0.1 0.0 100.0 231 Herat 7.8 3.3 78.3 0.0 1.1 9.6 100.0 863 Farah 10.1 7.1 48.7 2.7 2.1 29.2 100.0 295 Nimroz 5.2 5.1 56.6 2.0 3.5 27.5 100.0 93 Education No education 9.4 14.6 57.1 0.6 3.1 15.2 100.0 5,391 Primary 11.9 11.0 63.1 0.4 2.5 11.1 100.0 1,973 Secondary 18.3 13.6 54.8 0.3 1.0 11.8 100.0 2,611 More than secondary 33.3 6.6 48.6 0.1 2.0 9.5 100.0 692 Wealth quintile Lowest 4.1 4.2 76.7 0.7 2.5 11.8 100.0 2,013 Second 9.4 12.1 61.5 0.5 1.2 15.4 100.0 2,212 Middle 12.3 17.8 48.2 0.4 3.7 17.6 100.0 2,136 Fourth 15.6 17.9 50.0 0.1 2.5 13.9 100.0 2,241 Highest 26.4 13.4 50.3 0.6 2.3 7.1 100.0 2,064 Total 13.6 13.2 57.1 0.5 2.4 13.2 100.0 10,666 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. HIVAIDS-related Knowledge, Attitudes, and Behavior • 239 Table 13.12 Age at circumcision Percent distribution of circumcised men age 15-49 by age at circumcision, according to background characteristics, Afghanistan 2015 Background characteristic During childhood 5 years 5-13 ≥ 14 Dont know missing Total Number of circumcised men Age 15-19 65.8 24.7 0.0 9.5 100.0 142 20-24 60.6 26.3 0.0 13.0 100.0 1,154 25-29 53.9 33.1 1.0 11.9 100.0 2,401 30-34 52.3 35.0 0.2 12.5 100.0 1,992 35-39 54.0 33.7 0.0 12.3 100.0 1,918 40-44 51.8 33.3 0.1 14.8 100.0 1,388 45-49 47.0 39.8 0.2 13.0 100.0 1,671 Residence Urban 55.6 32.3 1.0 11.0 100.0 2,459 Rural 52.4 34.3 0.1 13.2 100.0 8,206 Province 1 Kabul 59.2 24.9 1.6 14.3 100.0 1,339 Kapisa 35.7 58.0 0.0 6.3 100.0 63 Parwan 54.0 42.8 0.0 3.2 100.0 218 Wardak 72.3 18.3 0.0 9.4 100.0 167 Logar 54.7 30.3 0.0 15.0 100.0 194 Nangarhar 68.9 26.5 0.0 4.6 100.0 271 Laghman 77.8 11.8 0.0 10.4 100.0 224 Panjsher 56.0 34.3 0.5 9.3 100.0 18 Baghlan 44.0 54.1 0.2 1.8 100.0 277 Bamyan 45.9 44.1 0.8 9.3 100.0 93 Ghazni 77.5 11.1 0.0 11.4 100.0 616 Paktika 86.5 3.5 0.0 10.0 100.0 319 Paktya 76.7 8.2 0.0 15.1 100.0 206 Khost 36.1 12.5 0.9 50.5 100.0 322 Kunarha 44.4 2.5 0.0 53.1 100.0 144 Nooristan 78.7 18.9 0.0 2.4 100.0 65 Badakhshan 24.2 59.6 0.0 16.2 100.0 315 Takhar 25.0 56.3 0.9 17.8 100.0 294 Kunduz 47.8 38.2 0.0 14.0 100.0 473 Samangan 40.1 56.7 0.2 3.1 100.0 125 Balkh 52.6 32.2 0.6 14.6 100.0 602 Sar-E-Pul 12.2 65.6 0.0 22.2 100.0 195 Ghor 45.3 52.7 0.0 2.0 100.0 321 Daykundi 45.2 48.9 1.1 4.9 100.0 77 Urozgan 40.3 0.6 0.0 59.1 100.0 91 Kandahar 65.4 29.9 0.0 4.7 100.0 872 Jawzjan 49.0 47.3 0.1 3.6 100.0 218 Faryab 11.6 87.2 0.1 1.0 100.0 706 Helmand 60.1 25.2 0.0 14.7 100.0 352 Badghis 76.5 22.7 0.0 0.8 100.0 231 Herat 41.8 38.6 0.0 19.6 100.0 863 Farah 91.0 2.3 0.0 6.7 100.0 295 Nimroz 71.5 10.4 0.0 18.1 100.0 93 Education No education 53.2 32.1 0.1 14.5 100.0 5,391 Primary 46.5 39.7 0.1 13.7 100.0 1,973 Secondary 55.6 33.9 0.9 9.6 100.0 2,611 More than secondary 62.4 29.8 0.1 7.7 100.0 692 Wealth quintile Lowest 44.9 43.7 0.2 11.2 100.0 2,013 Second 53.0 33.3 0.0 13.6 100.0 2,212 Middle 55.6 31.1 0.1 13.3 100.0 2,136 Fourth 55.9 30.0 0.1 14.0 100.0 2,241 Highest 55.9 31.6 1.2 11.3 100.0 2,064 Total 53.1 33.8 0.3 12.7 100.0 10,666 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 240 • HIVAIDS-related Knowledge, Attitudes, and Behavior Table 13.13 Self-reported prevalence of sexually-transmitted infections STIs and STI symptoms Among ever-married women and ever-married men age 15-49 who ever had sexual intercourse, the percentage reporting having an STI andor symptoms of an STI in the past 12 months, by background characteristics, Afghanistan 2015 Percentage of women who reported having in the past 12 months: Percentage of men who reported having in the past 12 months: Background characteristic STI Bad smelling abnormal genital discharge Genital soreulcer STI genital discharge sore or ulcer Number of women who ever had sexual intercourse STI Bad smelling abnormal discharge from penis Genital soreulcer STI abnormal discharge from penis sore or ulcer Number of men who ever had sexual intercourse Age 15-24 1.3 9.9 6.0 11.8 7,905 1.6 5.1 2.7 6.9 1,301 15-19 1.6 8.2 7.5 11.7 1,823 0.0 3.4 0.7 3.4 142 20-24 1.2 10.4 5.5 11.8 6,082 1.7 5.3 3.0 7.3 1,159 25-29 2.5 13.8 7.3 15.8 6,273 1.7 4.0 4.1 7.2 2,388 30-39 2.4 14.6 8.4 16.5 8,758 2.0 6.0 3.8 8.7 3,927 40-49 2.7 14.8 9.5 16.6 6,472 2.1 6.1 4.2 8.4 3,075 Marital status Married 2.2 13.5 7.9 15.4 28,631 1.9 5.5 3.9 8.1 10,612 DivorcedSeparated Widowed 0.8 3.5 2.0 3.9 777 0.7 0.1 0.9 0.9 79 Male circumcision Circumcised na na na na na 1.9 5.5 3.8 8.1 10,607 Not circumcised na na na na na 4.4 7.2 6.4 18.0 49 Don’t know na na na na na 1.4 3.5 1.2 4.7 35 Residence Urban 1.7 11.9 6.3 14.1 6,849 1.4 6.6 3.8 8.6 2,470 Rural 2.3 13.6 8.2 15.4 22,559 2.0 5.1 3.9 7.9 8,221 Province 1 Kabul 1.8 11.4 7.6 14.5 3,650 0.6 7.0 5.0 9.5 1,348 Kapisa 0.2 1.8 2.5 3.0 205 3.6 6.3 5.2 12.2 62 Parwan 4.4 25.9 23.8 30.5 624 1.4 0.1 0.3 1.7 219 Wardak 1.0 14.5 10.1 15.9 381 0.0 1.9 1.0 2.7 171 Logar 3.0 41.6 15.0 45.2 472 3.4 20.7 3.2 23.4 204 Nangarhar 0.5 13.3 12.2 19.1 793 0.8 2.1 1.7 3.0 273 Laghman 4.5 11.0 19.6 21.3 583 2.0 3.6 8.6 10.2 227 Panjsher 0.2 3.9 3.8 4.3 54 2.1 25.2 22.2 25.2 18 Baghlan 2.8 14.3 13.2 17.2 837 0.6 3.9 1.2 5.1 276 Bamyan 0.4 4.6 2.3 4.6 302 0.0 2.6 2.8 3.2 91 Ghazni 0.6 3.8 5.5 8.5 1,321 1.3 3.4 4.1 6.5 611 Paktika 1.7 16.6 8.0 18.4 786 3.1 6.8 3.4 9.1 321 Paktya 3.6 43.5 10.8 47.3 533 0.8 4.8 0.8 4.8 205 Khost 3.9 14.5 4.2 16.2 850 4.3 2.5 2.0 7.7 333 Kunarha 0.4 1.2 1.3 1.5 559 2.1 0.0 1.4 3.5 144 Nooristan 0.1 5.1 4.6 7.2 222 0.1 8.9 2.8 10.9 65 Badakhshan 0.1 0.2 0.3 0.3 1,004 0.1 1.5 0.0 1.6 316 Takhar 1.7 6.4 3.5 9.4 1,105 0.0 0.5 0.0 0.5 296 Kunduz 4.5 10.6 7.6 11.5 1,232 10.7 19.2 26.9 35.2 479 Samangan 2.2 3.2 1.7 3.4 330 3.6 14.1 13.3 15.0 125 Balkh 0.8 8.2 2.9 9.2 1,776 0.0 2.4 1.3 2.4 604 Sar-E-Pul 0.9 4.2 3.8 4.3 654 0.0 1.3 0.3 1.6 195 Ghor 6.3 42.6 41.9 42.7 715 3.8 3.5 3.5 5.8 322 Daykundi 0.0 0.2 0.0 0.2 328 0.0 2.3 1.6 2.3 77 Urozgan 0.0 7.7 4.0 10.6 229 0.0 2.2 1.6 3.4 90 Kandahar 0.2 33.5 9.7 33.8 2,225 1.8 11.0 1.2 12.4 874 Jawzjan 0.0 0.8 0.7 1.0 614 1.0 3.9 6.9 9.0 218 Faryab 0.2 0.6 1.0 1.8 2,113 0.0 0.5 0.7 1.2 686 Helmand 0.2 0.4 0.6 0.8 871 1.0 1.6 0.7 2.1 354 Badghis 0.0 3.1 2.8 3.1 650 0.0 1.1 0.5 1.1 231 Herat 8.6 25.8 13.4 26.8 2,316 3.7 5.0 2.5 8.7 860 Farah 1.3 7.9 5.5 8.6 776 4.6 11.4 9.0 15.8 295 Nimroz 13.2 15.0 5.8 16.8 276 0.0 0.4 0.0 0.4 93 Education No education 2.2 14.1 8.2 15.9 24,557 2.1 6.5 4.2 9.0 5,420 Primary 2.5 10.3 5.8 12.2 2,328 1.5 4.0 4.2 7.8 1,972 Secondary 1.7 7.7 5.7 10.6 1,969 2.0 4.6 2.6 6.5 2,606 More than secondary 2.6 6.8 4.2 10.4 554 1.3 4.6 4.3 7.6 693 Wealth quintile Lowest 2.0 12.0 8.6 12.7 5,898 3.7 5.6 5.1 9.3 2,021 Second 2.1 12.4 8.1 14.7 5,995 1.7 5.3 4.1 8.3 2,212 Middle 2.1 16.3 8.2 18.3 5,876 1.3 4.8 3.3 7.1 2,157 Fourth 2.7 12.9 6.9 14.7 6,003 1.3 5.5 3.2 7.3 2,227 Highest 2.0 12.5 6.9 15.2 5,636 1.5 6.3 3.6 8.6 2,073 Total 2.2 13.2 7.7 15.1 29,408 1.9 5.5 3.8 8.1 10,691 Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable. 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. HIVAIDS-related Knowledge, Attitudes, and Behavior • 241 Table 13.14 Prevalence of medical injections Percentage of ever-married women and ever-married men age 15-49 who received at least one medical injection in the last 12 months, the average number of medical injections per person in the last 12 months, and among those who received a medical injection, the percentage of last medical injections for which the syringe and needle were taken from a new, unopened package, by background characteristics, Afghanistan 2015 Women Men Background characteristic Percentage who received a medical injection in the last 12 months Average number of medical injections per person in the last 12 months Number of respondents For last injection, syringe and needle taken from a new, unopened package Number of respondents receiving medical injections in the last 12 months Percentage who received a medical injection in the last 12 months Average number of medical injections per person in the last 12 months Number of respondents For last injection, syringe and needle taken from a new, unopened package Number of respondents receiving medical injections in the last 12 months Age 15-24 29.9 2.1 7,915 89.6 2,364 26.8 1.8 1,305 95.4 350 15-19 27.3 1.6 1,825 90.1 498 17.1 0.7 142 94.4 24 20-24 30.6 2.2 6,089 89.4 1,865 28.0 1.9 1,162 95.5 326 25-29 34.9 2.4 6,299 88.6 2,199 26.5 2.6 2,422 94.9 641 30-39 37.1 3.5 8,765 90.6 3,256 31.9 2.5 3,943 94.1 1,258 40-49 38.1 4.0 6,482 91.3 2,469 34.5 3.2 3,091 91.4 1,067 Marital status Married 35.0 3.0 28,671 90.1 10,028 30.7 2.6 10,679 93.6 3,283 Divorced Separated Widowed 32.8 3.4 790 91.3 259 41.6 6.4 81 86.2 34 Residence Urban 40.0 3.9 6,870 91.1 2,748 29.1 2.6 2,479 94.7 722 Rural 33.4 2.7 22,591 89.7 7,539 31.3 2.7 8,281 93.2 2,594 Province 1 Kabul 35.1 3.8 3,658 82.5 1,284 31.1 2.5 1,350 96.4 420 Kapisa 41.6 3.3 205 85.4 85 32.3 3.3 63 92.3 20 Parwan 30.4 2.7 625 91.0 190 43.4 2.5 220 97.3 96 Wardak 34.7 5.5 382 82.2 133 12.9 1.0 171 97.2 22 Logar 24.7 1.1 472 51.6 116 40.8 1.9 204 89.1 83 Nangarhar 45.0 2.8 794 98.0 357 44.0 4.3 273 95.6 120 Laghman 47.9 1.7 583 85.9 279 41.4 2.2 227 98.6 94 Panjsher 12.2 1.4 54 93.5 7 10.4 0.7 18 2 Baghlan 33.7 4.0 839 80.6 283 65.8 4.8 281 99.7 185 Bamyan 26.0 1.9 303 74.6 79 19.2 2.6 94 92.0 18 Ghazni 35.1 3.1 1,328 94.8 466 14.1 1.2 619 98.7 87 Paktika 11.3 0.7 792 96.8 90 2.9 0.2 322 9 Paktya 37.2 3.1 542 86.2 202 56.6 3.6 206 97.8 116 Khost 39.0 3.2 851 40.3 332 55.1 5.1 334 87.5 184 Kunarha 35.7 4.8 559 89.5 199 42.4 3.0 151 87.0 64 Nooristan 16.6 0.2 222 89.7 37 12.9 0.4 66 65.9 9 Badakhshan 12.9 0.7 1,004 87.3 130 22.0 3.5 316 84.8 69 Takhar 30.8 3.2 1,105 94.6 341 20.6 2.5 296 100.0 61 Kunduz 29.0 2.5 1,232 86.7 357 39.0 4.7 479 75.9 187 Samangan 41.5 3.5 330 95.0 137 6.2 0.8 125 8 Balkh 44.3 3.0 1,781 98.8 788 20.0 1.3 616 100.0 123 Sar-E-Pul 33.7 6.3 654 97.9 220 29.9 1.9 195 95.9 58 Ghor 22.7 1.5 715 90.1 162 30.0 1.6 322 59.9 97 Daykundi 12.8 0.6 329 96.2 42 22.8 2.1 77 97.7 18 Urozgan 3.8 0.2 230 86.9 9 4.9 0.4 92 5 Kandahar 39.6 2.9 2,227 91.4 881 25.2 2.1 874 89.4 220 Jawzjan 17.6 2.7 614 95.6 108 12.9 1.0 218 96.2 28 Faryab 64.6 5.6 2,114 96.9 1,364 61.0 6.3 706 98.3 431 Helmand 18.8 3.3 875 95.7 165 19.3 1.1 355 98.8 69 Badghis 8.7 0.8 650 92.3 56 11.0 1.2 231 97.6 26 Herat 46.6 2.9 2,316 98.8 1,080 33.7 3.8 863 99.2 291 Farah 34.6 1.1 777 95.2 269 29.5 0.9 295 96.8 87 Nimroz 11.8 0.6 278 95.7 33 11.1 0.5 93 10 Education No education 34.2 3.0 24,604 89.8 8,425 29.1 2.7 5,447 92.4 1,584 Primary 38.2 3.1 2,330 91.7 889 36.2 2.6 1,987 92.7 720 Secondary 38.1 3.1 1,971 90.0 751 30.7 2.7 2,632 96.2 807 More than secondary 40.0 2.9 556 94.9 223 29.6 2.0 695 94.3 206 Wealth quintile Lowest 29.8 2.3 5,904 92.6 1,759 31.5 2.8 2,029 91.0 640 Second 31.1 2.4 6,001 91.5 1,868 27.5 2.1 2,233 91.8 615 Middle 33.9 2.9 5,888 89.0 1,996 30.8 2.5 2,160 94.1 665 Fourth 38.0 3.3 6,010 87.7 2,283 32.8 3.2 2,260 94.8 742 Highest 42.1 4.1 5,657 90.5 2,381 31.5 2.7 2,078 95.5 655 Total 34.9 3.0 29,461 90.1 10,287 30.8 2.6 10,760 93.5 3,316 Note: Medical injections are those given by a doctor, nurse, pharmacist, dentist, or other health worker. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 242 • HIVAIDS-related Knowledge, Attitudes, and Behavior Table 13.15 Comprehensive knowledge about AIDS and of a source of condoms among young people Percentage of ever-married women and ever-married men age 15-24 with comprehensive knowledge about AIDS and percentage with knowledge of a source of condoms, by background characteristics, Afghanistan 2015 Women Men Background characteristic Percentage with comprehensive knowledge of AIDS 1 Percentage who know a condom source 2 Number of respondents Percentage with comprehensive knowledge of AIDS 1 Percentage who know a condom source 2 Number of respondents Age 15-19 0.6 22.6 1,825 4.3 56.2 142 15-17 0.4 17.3 438 21 18-19 0.7 24.3 1,387 5.0 55.9 122 20-24 1.2 27.0 6,089 6.5 57.9 1,162 20-22 1.0 25.7 3,839 8.5 60.4 615 23-24 1.4 29.4 2,250 4.3 55.2 547 Residence Urban 1.7 30.9 1,794 12.6 70.2 205 Rural 0.8 24.6 6,120 5.1 55.4 1,100 Education No education 0.5 19.7 5,651 3.2 40.4 559 Primary 2.1 37.5 982 2.5 60.7 205 Secondary 1.9 42.8 1,075 8.0 72.2 439 More than secondary 5.5 58.1 206 23.6 84.6 101 Total 1.0 26.0 7,915 6.3 57.8 1,305 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the two most common local misconceptions about AIDS transmission or prevention of the AIDS virus. The components of comprehensive knowledge are presented in Tables 13.2, 13.3.1 and 13.3.2. 2 For this table, the following responses are not considered a source for condoms: friends, family members, and home. HIVAIDS-related Knowledge, Attitudes, and Behavior • 243 Table 13.16 Age at first sexual intercourse among young people Percentage of ever-married women and ever-married men age 15-24 who had sexual intercourse before age 15 and percentage of ever-married women and ever-married men age 18-24 who had sexual intercourse before age 18, by background characteristics, Afghanistan 2015 Women age 15-24 Women age 18-24 Men age 15-24 Men age 18-24 Background characteristic Percentage who had sexual intercourse before age 15 Number of respondents Percentage who had sexual intercourse before age 18 Number of respondents Percentage who had sexual intercourse before age 15 Number of respondents Percentage who had sexual intercourse before age 18 Number of respondents Age 15-19 10.7 1,825 na na 7.0 142 na na 15-17 15.9 438 na na 21 na na 18-19 9.1 1,387 74.8 1,387 5.8 122 48.2 122 20-24 10.0 6,089 46.6 6,089 1.6 1,162 19.5 1,162 20-22 9.1 3,839 47.8 3,839 2.2 615 23.1 615 23-24 11.5 2,250 44.5 2,250 0.8 547 15.5 547 Knows condom source 1 Yes 11.5 2,060 55.6 1,984 2.5 753 23.8 742 No 9.7 5,854 50.4 5,492 1.8 551 20.1 543 Residence Urban 10.0 1,794 50.2 1,718 2.2 205 23.4 204 Rural 10.2 6,120 52.3 5,758 2.1 1,100 22.0 1,080 Education No education 10.8 5,651 52.3 5,363 2.4 559 21.1 552 Primary 13.7 982 54.0 894 2.6 205 23.6 202 Secondary 4.8 1,075 49.3 1,013 2.2 439 23.7 428 More than secondary 2.9 206 40.4 206 0.0 101 19.6 101 Total 10.2 7,915 51.8 7,476 2.2 1,305 22.2 1,284 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not available. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. 244 • HIVAIDS-related Knowledge, Attitudes, and Behavior Table 13.17 Recent HIV tests among youth Among ever-married women and ever-married men age 15-24 who have had sexual intercourse in the past 12 months, the percentage who were tested for HIV in the past 12 months and received the results of the last test, by background characteristics, Afghanistan 2015 Women age 15-24 who have had sexual intercourse in the past 12 months: Men age 15-24 who have had sexual intercourse in the past 12 months: Background characteristic Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of women Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of men Age 15-19 1.2 1,783 0.0 142 15-17 0.0 423 21 18-19 1.6 1,360 0.0 121 20-24 0.2 5,956 0.8 1,152 20-22 0.3 3,754 0.8 611 23-24 0.2 2,203 0.7 540 Knows condom source 1 Yes 0.8 2,020 1.0 751 No 0.3 5,718 0.3 543 Residence Urban 1.4 1,754 1.9 202 Rural 0.2 5,985 0.5 1,092 Education No education 0.1 5,530 0.1 552 Primary 2.0 957 0.1 205 Secondary 0.5 1,049 1.6 436 More than secondary 3.0 203 1.2 101 Total 0.5 7,739 0.7 1,293 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. Adult and Maternal Mortality • 245 ADULT AND MATERNAL MORTALITY 14 Key Findings  Adult mortality: For women and men who have reached age 15, the probability of dying before age 50 is 12 and 8, respectively.  Pregnancy-related mortality: The pregnancy- related mortality ratio was 1,291 maternal deaths per 100,000 live births for the seven-year period before the survey.  Lifetime risk of maternal death: The lifetime risk of maternal death indicates that 1 in 14 women in Afghanistan will die from either pregnancy or childbearing. dult and maternal mortality indicators can assess the health status of a population, especially in developing countries such as Afghanistan. Estimation of these mortality rates requires complete and accurate data on adult and maternal deaths. In the 2015 AfDHS, data were collected on the survivorship of the respondents’ siblings to obtain an estimate of adult mortality. Questions that determine if deaths among female siblings were maternity-related facilitate the estimation of maternal mortality, a key indicator of maternal health and well-being. In agreement with the International Classification of Disease ICD-10 definition of maternal mortality, the 2015 AfDHS results reflect pregnancy-related mortality, which accounts for deaths of women while they are pregnant, during delivery, or within 42 days of termination of pregnancy, irrespective of the cause of death WHO 2011. The maternal mortality module used in the DHS surveys measures the timing of maternal deaths but does not have information on the cause of death. The data collected in the 2015 AfDHS questionnaire are based on information about deaths during the two months after a birth rather than the recommended 42 days following a birth. This chapter includes results estimated from sibling history data collected in the sibling survival module commonly referred to as the maternal mortality module that is part of the Woman’s Questionnaire. In addition to adult mortality rates for five-year age groups, the chapter includes a summary measure 35 q 15 that represents the probability of dying between exact ages 15 and 50—that is, between the women’s 15th and 50th birthdays.

14.1 D

ATA To obtain a sibling history, each respondent was asked to provide the total number of her mother’s live births. The respondent was then asked to provide a list of all of the children born to her mother, starting with the first born. The respondent was asked if each of these siblings was still alive at the time of the survey. The current age of living siblings was collected. For deceased siblings, the age at death and number of years since the person’s death were collected. Interviewers were instructed that when a respondent could not provide precise information on age at death or years since death, approximate but quantitative answers were acceptable. For sisters who died at age 12 or above, three questions were used to determine whether the death was maternity-related: “Was [NAME OF SISTER] pregnant when she died?” A 246 • Adult and Maternal Mortality and, if not, “Did she die during childbirth?” and, if not, “Did she die within two months after the end of a pregnancy or childbirth?” Estimation of adult and pregnancy-related mortality by either direct or indirect means requires reasonably accurate reporting of the respondent’s number of sisters and brothers, the number who have died, and for pregnancy-related mortality, the number of sisters who died of pregnancy- related causes. Table 14.1 shows the number of siblings reported by the respondents and the completeness of data on current age, age at death, and years since death. Overall, the sibling history data collected in the 2015 AfDHS were complete. For 99 of deceased siblings, the age at death, years since death or year of death were reported. There were very few siblings for whom survival status was not reported 0.05. Among surviving siblings, current age used to estimate exposure to death was reported for all but 278 siblings 0.2. Instead of excluding siblings with missing data from further analysis, information on the birth order of siblings was used in conjunction with other information to impute the missing data. 1 The sex ratio for enumerated siblings the ratio of brothers to sisters multiplied by 100 is 108.6 Appendix Table C.9

14.2 D

IRECT E STIMATES OF A DULT M ORTALITY Adult mortality rate The number of adult deaths per 1,000 population age 15-49. Adult mortality rates by 5-year age groups are calculated as follows: the number of deaths to respondent’s siblings in each age group is divided by the number of person- years of exposure to the risk of dying in that age group during a specified period prior to the survey. The number of deaths is the number of siblings brothers or sisters reported as having died within the specified period. The person-years of exposure in each age group are calculated for both surviving and dead siblings based on their current age living siblings or age at death and years since death dead siblings. Sample: Siblings both living and dead who were age 15-49 in the specified 7-year period preceding the survey by sex and 5-year age groups One way to assess the quality of the data used to estimate pregnancy-related mortality is to evaluate the plausibility and stability of overall adult mortality. If estimated rates of overall adult mortality are implausible, rates based on a subset of deaths pregnancy-related deaths in particular may have serious problems. The reported ages at death and years since death of the respondents’ brothers and sisters were used to make direct estimates of adult mortality. Because of the differentials in exposure to the risk of dying, age- and sex-specific death rates are presented in this report. Table 14.2 and Figure 14.1 show age-specific mortality rates among women and men age 15-49 for the 7 years before the 2015 AfDHS. To ensure a sufficiently large number of adult deaths to generate a robust estimate, the rates are calculated for the seven-year period before the survey mid-2008 to mid-2015. Nevertheless, age-specific mortality rates obtained in this manner are subject to considerable sampling variation. Use of this seven-year period was a compromise between the desire for the most recent data and the need to minimize the level of sampling error. 1 The imputation procedure was based on the assumption that the reported birth ordering of siblings in the history was correct. The first step was to calculate birth dates for each living sibling with a reported age and each dead sibling with complete information on both age at death and years since death. For a sibling missing these data, a birth date was imputed within the range defined by the birth dates of the bracketing siblings. In the case of living siblings, an age was then calculated from the imputed birth date. In the case of dead siblings, if either age at death or years since death were reported, that information was combined with the birth date to produce the missing information. If both pieces of information were missing, the distribution of the ages at death for siblings for whom years since death were not reported but age at death was reported was used as a basis for imputing age at death. Adult and Maternal Mortality • 247 Table 14.2 and Figure 14.1 show age-specific mortality rates for women and men age 15-49 for the seven-year period before the survey. The levels of adult mortality among women 3.53 deaths per 1,000 populations are higher than among men 2.43 deaths per 1,000 population. Generally, mortality is low among men and women age 15- 19, and increases steadily through age 35-39. A sudden increase in female mortality occurs after age 40. The highest mortality rate among women is for women age 40-44. The probability of dying between exact ages 15 and 50 35 q 15 is also much higher, at 119, for women than for men, at 84 Table 14.3. Here, 35 q 15 is the probability of a 15-year-old woman or man dying before age

50, if they experience the age specific deaths rates in Table 14.2.

14.3 D

IRECT E STIMATES OF P REGNANCY - RELATED M ORTALITY Pregnancy-related mortality rate The number of pregnancy-related deaths per 1,000 women age 15-49. Pregnancy-related mortality rates by 5-year age groups are calculated by dividing the number of pregnancy-related deaths to female siblings of respondents in each age group by the total person-years of exposure of the sisters to the risk of dying in that age group during the 7 years prior to the survey. The number of deaths is the number of sisters reported as having died during pregnancy or delivery, or in the 2 months following the delivery in the specified period by their age group at the time of death. The person-years of exposure in each age group are calculated for both surviving and dead sisters based on their reported current age living sisters or age at death and years since death dead sisters. Sample: Sisters both living and dead age 15-49 in the specified period, by 5-year age groups. Pregnancy-related mortality ratio The number of pregnancy-related deaths per 100,000 live births. The pregnancy-related mortality ratio is calculated by dividing the age-standardized pregnancy-related mortality rate for women age 15-49 for the specified period by the general fertility rate GFR for the same period. Pregnancy-related deaths are a subset of all female deaths, and are defined as any deaths that occur during pregnancy or childbirth, or within 2 months after the birth or termination of a pregnancy. Estimates of pregnancy-related mortality are therefore based solely on the timing of the death in relationship to the pregnancy. Two methods are used to estimate pregnancy-related mortality in developing countries: the indirect sisterhood method Graham et al. 1989 and a direct variant of the sisterhood method Rutenberg and Sullivan 1991; Stanton et al. 1997. Age-specific estimates of pregnancy-related mortality from reported survivorship of sisters are shown in Table 14.4 for the seven-year period before the 2015 survey. Table 14.4 shows that the pregnancy-related mortality rate among women age 15-49 is 2.36 deaths per 1,000 woman-years of exposure. By five-year age groups, the pregnancy-related mortality rate is highest Figure 14.1 Adult mortality rates among women and men age 15-49 0.5 1 1.5 2 2.5 3 3.5 4 4.5 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Deaths per 1,000 population Age in years Women Men 248 • Adult and Maternal Mortality among women age 25-29 2.90, followed by those age 30-34 2.81. The percentage of female deaths that are pregnancy-related deaths varies by age and ranges from 41.4 among women age 45-49 to79 among women age 25 -29. The estimated age-specific mortality rates display a plausible pattern, which is generally higher during the peak childbearing ages than in the younger and older age groups. The pregnancy-related mortality ratio PRM is estimated at 1,291 deaths per 100,000 live births during the seven-year period before the survey with a 95 confidence interval of 1,071 – 1,512. For every 1,000 live births in Afghanistan during the 7 years before the 2015AfDHS, approximately 13 women died during pregnancy, during childbirth, or within 2 months after childbirth. The lifetime risk of pregnancy-related death 0.073 indicates that of 1,000 women age 15, about 73 would die before age 50 during pregnancy, childbirth, or within two months of childbirth. The pregnancy-related mortality estimates appear to be higher than expected, given findings of other data sources from Afghanistan and its neighbors, as well as expert knowledge of the relationship of maternal mortality to overall adult mortality. In particular, the share of adult female deaths that are pregnancy related appear to be overestimated. Further analyses are being conducted to better understand these estimates, and additional analyses are encouraged. L IST OF T ABLES For more information on adult and pregnancy-related mortality, see the following tables:  Table 14.1 Completeness of information on siblings  Table 14.2 Adult mortality rates  Table 14.3 Adult mortality probabilities  Table 14.4 Pregnancy-related mortality rates Adult and Maternal Mortality • 249 Table 14.1 Completeness of information on siblings Completeness of data on survival status of sisters and brothers reported by interviewed women, age of living siblings, and age at death AD and years since death YSD of dead siblings unweighted, Afghanistan 2015 Sisters Brothers All siblings Number Percent Number Percent Number Percent All siblings 82,109 100.0 91,073 100.0 173,182 100.0 Living 73,037 89.0 81,368 89.3 154,405 89.2 Dead 9,031 11.0 9,662 10.6 18,693 10.8 Survival status unknown 41 0.0 43 0.0 84 0.0 Living siblings 73,037 100.0 81,368 100.0 154,405 100.0 Age reported 72,903 99.8 81,224 99.8 154,127 99.8 Age missing 134 0.2 144 0.2 278 0.2 Dead siblings 9,031 100.0 9,662 100.0 18,693 100.0 AD and YSD reported 8,948 99.1 9,536 98.7 18,484 98.9 Missing only AD 56 0.6 83 0.9 139 0.7 Missing only YSD 7 0.1 21 0.2 28 0.1 Missing AD and YSD 20 0.2 22 0.2 42 0.2 Table 14.2 Adult mortality rates Direct estimates of female and male mortality rates for the 7 years preceding the survey, by five-year age groups, Afghanistan 2015 Age Deaths Exposure years Mortality rates 1 FEMALE 15-19 233 75,899 3.07 20-24 323 87,485 3.69 25-29 299 81,903 3.65 30-34 245 66,445 3.68 35-39 170 49,870 3.40 40-44 130 31,288 4.16 45-49 69 18,444 3.73 15-49 1,467 411,334 3.53 a MALE 15-19 144 79,474 1.81 20-24 251 90,933 2.77 25-29 212 88,387 2.40 30-34 215 73,239 2.94 35-39 134 55,681 2.40 40-44 88 35,651 2.47 45-49 63 21,822 2.87 15-49 1,107 445,186 2.43 a 1 Expressed per 1,000 population. a Age-adjusted rate. Table 14.3 Adult mortality probabilities Probability of dying between the ages of 15 and 50 for women and men for the 7 years preceding the survey, Afghanistan 2015 Women Men Survey 35 q 151 35 q 151 2015 AfDHS 119 CI: 104 -135 84 CI: 76 - 93 CI: Confidence interval. 1 The probability of dying between exact ages 15 and 50, expressed per 1,000 persons at age 15. 250 • Adult and Maternal Mortality Table 14.4 Pregnancy-related mortality rates Direct estimates of pregnancy-related mortality rates for the 7 years preceding the survey, by 5-year age groups, Afghanistan 2015 Age Percentage of female deaths that are pregnancy-related Number of pregnancy- related deaths Exposure years Pregnancy- related mortality rate 1 15-19 64.2 149 75,899 1.97 20-24 69.9 225 87,485 2.58 25-29 79.4 237 81,903 2.90 30-34 76.2 186 66,445 2.81 35-39 61.3 104 49,870 2.08 40-44 60.5 79 31,288 2.51 45-49 41.4 28 18,444 1.54 15-49 68.8 1,009 411,334 2.36 a General fertility rate GFR 2 183 a CI: 176 - 189 Pregnancy-related mortality ratio 3 1,291 CI: 1,071-1,512 Lifetime risk of maternal death 4 0.073 CI: Confidence interval. 1 Expressed per 1,000 woman-years of exposure. 2 Expressed per 1,000 woman age 15-49. 3 Expressed per 100,000 live births; calculated as the age-adjusted pregnancy-related mortality rate multiplied by 100 divided by age-adjusted general fertility rate. 4 Calculated as 1-1-PRM ratio TFR where TFR represents the total fertility rate for the 7 years preceding the survey. a Age-adjusted rate. Women’s Empowerment • 251 WOMEN ’S EMPOWERMENT 15 Key Findings  Employment and control over earnings: Only 13 of currently married women are employed as compared with 97 of currently married men. About 2 in 5 currently married women who receive cash earnings report deciding for themselves how their own earnings will be used, and one- third say they decide on the use of their earnings with their husband.  Ownership of assets: Seventeen percent of women independently own a house and another 10 own land, while almost half of the men own a house and about a third own land.  Participation in decision making: Only 5 of women make decisions alone about their own health care, while 44 report that their husbands make the decisions for them.  Attitude towards wife beating: Eighty percent of women and 72 of men believe that a husband is justified in beating his wife in at least 1 of 5 specified circumstances, particularly if she goes out without telling her husband 67 and 61, respectively. his chapter explores women’s empowerment in terms of employment, earnings, control over earnings, and the magnitude of earnings relative to those of their partners. In addition, responses to specific questions are used to define two different indicators of women’s empowerment: women’s participation in household decision making and women’s attitudes towards wife beating.

15.1 M

ARRIED W OMEN ’ S AND M EN ’ S E MPLOYMENT Employment Respondents are considered employed if they have done any work other than housework in the 12 months before the survey. Sample: Currently married women and men age 15-49 Earning cash for employment Respondents are asked if they are paid for their labor in cash or in kind. Only those who receive payment in cash only or in cash and in kind are considered to have earned cash for their employment. Sample: Currently married women and men age 15-49 employed in the 12 months before the survey Men are more likely to be employed than women. Thirteen percent of currently married women reported being employed at any time in the 12 months before the survey compared with 97 of currently married men. Table 15.1. T 252 • Women’s Empowerment Not all women and men receive earnings for the work they do. However, among those who receive earnings, not all receive cash. Among the employed, cash cash and in-kind is the most common form of payment for both women and men 66 and 91, respectively. However, men are more likely to be paid cash for their work and women are most likely not to receive earnings for the work they do as compared with men 28 and 5, respectively. Patterns by background characteristics  Employment does not vary with age among currently married women and men. More than one in ten currently married women are employed in all age groups and more than nine in ten currently married men are employed in most age groups from 20-49. Figure 15.1.  Currently married women age 45-49 are more likely to be paid in cash 76, while younger women age 15-19 are the least likely to be paid in cash 54. More than 90 of currently married men age 20 and above are paid in cash, while younger men age 15-19 72 are slightly less likely to be paid in cash.

15.2 C

ONTROL OVER W OMEN ’ S E ARNINGS Control over one’s own cash earnings Respondents are considered to have control over their own earnings if they participate in decisions alone or jointly with their husband about how their own earnings will be used. Sample: Currently married women age 15-49 who received cash earnings for employment during the 12 months before the survey To assess women’s autonomy, currently married women who earned cash for their work in the 12 months before the survey were asked to identify the main decision maker for the use of their earnings. Women gain direct access to economic resources when they are paid for work in cash. However, this access is meaningless unless women can also participate in decisions about the use of their earnings. Forty-one percent of currently married women who receive cash earnings reported deciding for themselves about the use of their earnings, while one third reported that they decided jointly with their husband Table 15.2.1, Figure 15.2. Twenty-three percent of women reported that their husband decides how their earnings will be used. In couples in which both women and men earned cash, 65 of women reported that they earn less than their husbands and 8 report earning more Table 15.2.1. Figure 15.1 Womens and mens employment by age Figure 15.2 Control over womens earnings 10 13 13 11 15 14 13 87 94 97 98 98 98 96 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Percentage of currently married women and men who were employed at any time in the past 12 months Age in years Currently married men Currently married women Mainly wife 41 Wife and husband jointly 34 Mainly husband 23 Other 2 Percent distribution of currently married women with cash earnings in the last 12 months Women’s Empowerment • 253 Patterns by background characteristics  Women age 45-49 48 are more likely to make independent decisions about their earnings than women age 30-34 36, while women age 15-19 41 are more likely to make joint decisions with husbands on their earnings than women age 40-49 37.  Women with 3-4 children 51 are more likely to make independent decision on their earnings.  Making joint decisions increases with education, from 31 of women with no education to 54 of women with more than secondary education.  Women in the lowest wealth quintile are less likely to have independent control over their cash earnings than women in the higher wealth quintiles.

15.3 C

ONTROL OVER M EN ’ S E ARNINGS Among married men who receive cash earnings, 68 report that they decide alone how to spend those earnings. Only 23 reported that they decide jointly with their wives on how to spend their earnings. Married women were also asked who decides how their husband’s earnings are used; 62 reported that this decision was made alone by their husbands, while 31 reported that they make joint decisions about spending with their husband Table 15.2.2. When husbands have no cash earnings or the husbands are unemployed, women more often make the decisions on spending their earnings 49. For more details, see Table 15.3.

15.4 W

OMEN ’ S AND M EN ’ S O WNERSHIP OF A SSETS Ownership of a house or land Respondents who own a house or land, whether alone or jointly with someone else. Sample: Women and men age 15-49 Thirty-nine percent of women own a house, either alone or jointly with someone; similarly, 25 of women report that they own land, either alone or jointly Table 15.4.1, Figure 15.3. Joint ownership of these assets is more common among women than independent ownership: 19 of women own a house jointly and 13 of women own land jointly with someone. The vast majority of men 81 own a house, while more than half of men own land Table 15.4.2. Figure 15.3 Ownership of assets 31 10 49 17 23 13 30 19 2 2 2 4 44 74 19 61 Men Women LAND Men Women HOUSE Percent distribution of women and men age 15-49 by house and land ownership Alone Jointly Alone and jointly Do not own a house Own: 254 • Women’s Empowerment Patterns by background characteristics  Ownership of house and land alone increases with age for men. While 17 of men age 15-19 own a house alone, 70 of men age 45-49 own a house alone and 44 own land Table 15.4.2.  Women’s ownership of either asset, either alone or jointly, is higher in rural areas than in urban areas: 19 of rural women own a house alone compared with 11 of urban women. This pattern is similar for men’s ownership of a house or land Table 15.4.1 and Table 15.4.2.

15.5 W

OMEN ’ S P ARTICIPATION IN D ECISION M AKING Participation in major household decisions Women are considered to participate in household decisions if they make decisions alone or jointly with their husband in all three of the following areas: 1 the woman’s health care, 2 major household purchases, and 3 visits to the woman’s family or relatives. Sample: Currently married women age 15-49 The 2015 AfDHS sought information from currently married women on their participation in three types of household decisions: the respondent’s health care; major household purchases; and visits to family or relatives. Only 5 of women make decisions independently on their own heath care while the majority either decide with their husbands 43, only their husbands 44, or someone else 4 makes the decision for them Table 15.5. More than four in ten women participate in each individual decision jointly with their husband Table 15.6.1. More women participate in joint decisions to visit their family or relatives 54 than in decisions about their own health care 48. One third of women participate in all three decisions, while 36 do not participate in any of the three decisions Figure 15.4. The 2015 AfDHS also collected information from currently married men on their participation in two types of household decisions: their own health care and major household purchases. Information on men’s participation in decision making is shown in Table 15.6.2. Patterns by background characteristics  Participation in all three types of decision making, either solely or jointly with their husband, increases steadily with age, from 26 of women age 15-19 to 40 of women age 40-49.  Women’s participation in all three decisions increases substantially with education while the proportion participating in none of these decisions decreases with increasing levels of education. One in two currently married women with more than secondary education participate in all three decisions as compared with 31 of women with no education. Figure 15.4 Womens participation in decision making 48 42 54 33 36 Womans own health care Major household purchases Visits to family or relatives Participate in all 3 decisions Participate in none of these decisions Percentage of currently married women age 15-49 participating in select decisions Women’s Empowerment • 255  Women in the wealthiest households 29 are less likely to participate in all three decisions than women in the poorest households 41.

15.6 A

TTITUDES TOWARD W IFE B EATING Attitudes toward wife beating Respondents are asked if they agree that a husband is justified in hitting or beating his wife under each of the following five circumstances: she burns the food, she argues with him, she goes out without telling him, she neglects the children, and she refuses to have sex with him. If respondents answer “yes” in at least one circumstance, they are considered to have attitudes that justify wife beating. Sample: Women and men age 15-49 Eighty percent of women believe that a husband is justified in beating his wife for at least one of five specified circumstances Table 15.7.1 . This figure among men is 72 Table 15.7.2, Figure 15.5. For each of the specified circumstances, men were less likely than women to agree that wife beating was justified. Patterns by background characteristics  Among women and men, attitudes towards wife beating are more acceptable in rural areas 82 of women and 76 of men than in urban areas 74 of women and 60 of men where wife beating is justified for at least one of the specified reasons Table 15.7.1 and Table 15.7.2.  Women’s tolerance of wife beating decreases with education. About four in five women with no education or primary education agree with wife beating in at least one of five specified circumstances as compared with 61 of women with more than secondary education. The pattern among men is similar to the pattern among women Table 15.7.2. L IST OF T ABLES For more information on women’s empowerment and demographic and health outcomes, see the following tables:  Table 15.1 Employment and cash earnings of currently married women and men  Table 15.2.1 Control over womens cash earnings and relative magnitude of womens cash earnings  Table 15.2.2 Control over mens cash earnings  Table 15.3 Womens control over their own earnings and over those of their husbands  Table 15.4.1 Ownership of assets: Women  Table 15.4.2 Ownership of assets: Men Figure 15.5 Attitudes towards wife beating 18 59 67 48 33 80 9 46 61 26 20 72 Burns the food Argues with him Goes out without telling him Neglects the children Refuses sexual intercourse Any of these reasons Percentage of women and men age 15-49 who agree that a husband is justified in beating his wife for specific reasons Women Men 256 • Women’s Empowerment  Table 15.5 Participation in decision making  Table 15.6.1 Womens participation in decision making by background characteristics  Table 15.6.2 Mens participation in decision making by background characteristics  Table 15.7.1 Attitude toward wife beating: Women  Table 15.7.2 Attitude toward wife beating: Men  Table 15.8 Indicators of womens empowerment  Table 15.9 Current use of contraception by womens empowerment  Table 15.10 Ideal number of children and unmet need for family planning by womens empowerment  Table 15.11 Reproductive health care by womens empowerment  Table 15.12 Early childhood mortality rates by womens status Women’s Empowerment • 257 Table 15.1 Employment and cash earnings of currently married women and men Percentage of currently married women and men age 15-49 who were employed at any time in the past 12 months and the percent distribution of currently married women and men employed in the past 12 months by type of earnings, according to age, Afghanistan 2015 Among currently married respondents: Percent distribution of currently married respondents employed in the past 12 months, by type of earnings Age Percentage employed in past 12 months Number of respondents Cash only Cash and in-kind In-kind only Not paid Missing dont know Total Number of women WOMEN 15-19 10.0 1,812 45.7 7.8 4.2 42.2 0.1 100.0 182 20-24 12.9 6,028 46.7 8.2 4.4 40.2 0.6 100.0 779 25-29 13.1 6,193 63.4 4.8 6.6 24.8 0.4 100.0 809 30-34 11.3 4,226 62.6 8.8 6.7 21.7 0.2 100.0 476 35-39 14.8 4,375 65.5 5.3 4.1 24.3 0.8 100.0 646 40-44 14.2 2,977 62.8 5.3 3.6 26.9 1.4 100.0 424 45-49 12.7 3,060 67.2 8.5 4.2 19.6 0.4 100.0 389 Total 12.9 28,671 59.6 6.7 5.0 28.1 0.6 100.0 3,705 MEN 15-19 87.1 142 45.0 27.0 2.3 24.1 1.6 100.0 124 20-24 93.7 1,160 64.9 25.4 4.4 5.0 0.3 100.0 1,087 25-29 96.9 2,410 71.5 19.9 4.4 4.0 0.2 100.0 2,336 30-34 98.3 1,992 65.8 25.6 3.8 4.7 0.1 100.0 1,960 35-39 97.5 1,925 71.0 21.5 4.4 3.1 0.0 100.0 1,877 40-44 98.1 1,385 63.6 25.9 6.2 4.2 0.1 100.0 1,359 45-49 95.8 1,664 61.9 27.4 5.9 4.8 0.1 100.0 1,595 Total 96.8 10,679 66.8 23.9 4.7 4.5 0.1 100.0 10,337 258 • Women’s Empowerment Table 15.2.1 Control over womens cash earnings and relative magnitude of womens cash earnings Percent distribution of currently married women age 15-49 who received cash earnings for employment in the 12 months preceding the survey by person who decides how wifes cash earnings are used and by whether she earned more or less than her husband, according to background characteristics, Afghanistan 2015 Person who decides how the wifes cash earnings are used: Wifes cash earnings compared with husbands cash earnings: Background characteristic Mainly wife Wife and husband jointly Mainly husband Other Missing Total More Less About the same Husband has no earnings Dont know