Help Seeking Behavior to Stop the Violence Sources for Help

294 • Domestic Violence Table 16.11 Womens violence against their spouse by background characteristics Percentage of ever-married women age 15-49 who have committed physical violence against their current or most recent husband when he was not already beating or physically hurting her, ever and in the past 12 months, according to womens own experience of spousal violence and background characteristics, Afghanistan 2015 Percentage who have committed physical violence against their husband Number of ever- married women Background Characteristic Ever 1 In the past 12 months Womans experience of spousal physical violence Ever 1 1.7 1.4 10,762 In the past 12 months 1.8 1.4 9,757 Never 0.2 0.1 10,562 Age 15-19 0.6 0.5 1,280 20-24 0.7 0.6 4,434 25-29 0.9 0.6 4,525 30-39 1.1 0.9 6,388 40-49 1.1 0.9 4,696 Marital status Married 0.9 0.7 20,793 Divorcedseparated widowed 1.6 0.8 531 Employment 2 Employed for cash 1.2 1.0 1,852 Employed not for cash 1.1 0.7 951 Not employed 0.9 0.7 18,504 Number of living children 1.0 0.8 2,132 1-2 0.6 0.4 5,248 3-4 1.1 0.9 5,583 5+ 1.1 0.8 8,361 Residence Urban 1.3 1.0 4,735 Rural 0.9 0.7 16,589 Wealth quintile Lowest 0.6 0.4 4,345 Second 1.2 1.0 4,480 Middle 0.8 0.7 4,351 Fourth 0.8 0.6 4,234 Highest 1.4 1.0 3,914 Total 1.0 0.7 21,324 Note: Husband refers to the current husband for currently married women and the most recent husband for divorced, separated or widowed women. 1 Includes in the past 12 months. 2 Total includes 17 women with missing information on employment status. Domestic Violence • 295 Table 16.12 Womens violence against their spouse by husband’s characteristics and empowerment indicators Percentage of ever-married women age 15-49 who have committed physical violence against their current or most recent husband when he was not already beating or physically hurting her, ever and in the past 12 months, according their husbands characteristics, Afghanistan 2015 Percentage who have committed physical violence against their husband Number of ever- married women Background Characteristic Ever 1 In the past 12 months Husbands education No education 0.9 0.7 12,468 Primary 1.1 0.7 3,012 Secondary 1.1 0.7 4,312 More than secondary 1.1 1.0 1,344 Don’t know 1.0 0.7 187 Husbands alcohol consumption 2 Does not drink 0.9 0.7 21,124 Drinksnever gets drunk 12 Gets drunk sometimes 15.1 9.6 74 Gets drunk very often 19.8 19.8 46 Spousal age difference 3 Wife older 3.3 3.0 885 Wife is same age 1.0 0.6 941 Wifes 1-4 years younger 0.9 0.7 8,973 Wifes 5-9 years younger 0.9 0.6 6,182 Wifes 10+ years younger 0.6 0.5 3,720 Number of marital control behaviors displayed by husband 4 0.5 0.4 6,643 1-2 0.9 0.7 9,773 3-4 1.5 1.3 3,931 5 1.9 1.8 978 Number of decisions in which women participate 5 1.0 0.9 7,338 1-2 0.9 0.6 6,585 3 0.9 0.7 6,870 Number of reasons for which wife-beating is justified 6 1.3 1.1 4,192 1-2 1.0 0.8 7,333 3-4 0.7 0.5 7,222 5 0.8 0.7 2,577 Womans father beat her mother Yes 1.1 0.8 8,180 No 0.8 0.6 8,545 Don’t know 1.0 0.9 4,599 Woman afraid of husband 7 Most of the time afraid 1.2 0.9 7,872 Sometimes afraid 0.7 0.6 10,981 Never afraid 1.3 0.9 2,390 Total 1.0 0.7 21,324 Note: Husband refers to the current husband for currently married women and the most recent husband for divorced, separated, or widowed women. 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 Includes in the past 12 months. 2 Total includes 68 women with missing information on husband’s alcohol consumption. 3 Includes only currently married women who have been married only once. Total includes 92 currently married women with missing information on spousal age difference. 4 According to the wifes report. See 16.7 for list of behaviors. 5 According to the wifes report. Includes only currently married women. See Table 15.6.1 for list of decisions. 6 According to the wifes report. See Table 15.7.1 for list of reasons. 7 Total includes 80 women with missing information on whether they are afraid of their husband. 296 • Domestic Violence Table 16.13 Help seeking to stop violence Percent distribution of ever-married women age 15-49 who have ever experienced physical or sexual violence by their help-seeking behavior by type of violence and background characteristics, Afghanistan 2015 Background Characteristic Sought help to stop violence Never sought help but told someone Never sought help, never told anyone Missing dont know Total Number of women who have ever experienced any physical or sexual violence Type of violence experienced Physical only 18.2 16.3 61.9 3.6 100.0 9,733 Sexual only 9.2 11.2 75.2 4.5 100.0 52 Physical and sexual 32.8 8.0 57.0 2.1 100.0 1,551 Age 15-19 18.0 10.1 63.8 8.0 100.0 422 20-24 17.2 13.8 66.2 2.9 100.0 2,052 25-29 19.9 13.3 63.9 3.0 100.0 2,436 30-39 22.1 15.5 59.2 3.2 100.0 3,589 40-49 20.3 18.1 58.0 3.6 100.0 2,838 Marital status Married 19.9 15.3 61.5 3.3 100.0 11,024 Divorcedseparated widowed 30.2 9.6 53.4 6.9 100.0 312 Number of living children 16.0 8.1 70.5 5.4 100.0 662 1-2 19.2 12.1 65.3 3.4 100.0 2,670 3-4 22.1 13.9 60.8 3.3 100.0 3,091 5+ 20.0 18.7 58.3 3.1 100.0 4,913 Employment 1 Employed for cash 17.8 12.3 67.6 2.2 100.0 999 Employed not for cash 10.3 8.5 79.6 1.6 100.0 597 Not employed 21.0 15.9 59.5 3.6 100.0 9,731 Residence Urban 15.5 14.4 67.4 2.7 100.0 2,069 Rural 21.2 15.4 60.0 3.5 100.0 9,267 Province 2 Kabul 11.5 10.8 74.9 2.8 100.0 1,035 Kapisa 5.5 4.0 86.8 3.7 100.0 41 Parwan 14.7 6.8 70.9 7.6 100.0 279 Wardak 17.5 6.1 76.0 0.4 100.0 244 Logar 12.3 21.7 64.0 1.9 100.0 297 Nangarhar 18.9 11.5 64.9 4.6 100.0 365 Laghman 13.5 11.6 67.5 7.4 100.0 267 Panjsher 4.1 1.6 88.7 5.6 100.0 10 Baghlan 12.8 9.9 54.6 22.7 100.0 449 Bamyan 22.9 3.9 71.6 1.5 100.0 52 Ghazni 11.0 2.7 81.9 4.3 100.0 704 Paktika 9.9 13.7 66.6 9.8 100.0 291 Paktya 4.1 3.0 89.9 3.0 100.0 332 Khost 1.7 2.4 88.8 7.1 100.0 141 Kunarha 13.6 3.4 82.6 0.4 100.0 185 Nooristan 19.4 8.1 67.3 5.2 100.0 93 Badakhshan 22.1 2.7 67.4 7.9 100.0 54 Takhar 1.9 53.9 40.3 3.9 100.0 359 Kunduz 10.5 5.1 79.4 5.0 100.0 374 Samangan 5.5 9.0 82.9 2.5 100.0 81 Balkh 9.4 47.3 41.7 1.6 100.0 345 Sar-E-Pul 23.9 19.3 54.9 1.9 100.0 289 Ghor 58.6 1.6 39.2 0.5 100.0 492 Daykundi 9.0 17.1 70.4 3.5 100.0 43 Urozgan 19.7 19.2 58.9 2.2 100.0 78 Kandahar 4.0 38.7 56.3 1.1 100.0 1,166 Jawzjan 15.4 2.4 77.6 4.6 100.0 133 Faryab 11.7 11.4 76.4 0.6 100.0 920 Helmand 0.0 0.7 75.5 23.8 100.0 36 Badghis 25.5 14.3 58.3 1.9 100.0 231 Herat 53.0 13.1 33.7 0.2 100.0 1,598 Farah 44.2 9.7 46.1 0.0 100.0 313 Nimroz 30.8 1.8 64.8 2.6 100.0 38 Continued… Domestic Violence • 297 Table 16.13—Continued Background Characteristic Sought help to stop violence Never sought help but told someone Never sought help, never told anyone Missing dont know Total Number of women who have ever experienced any physical or sexual violence Education No education 20.2 15.5 61.0 3.4 100.0 9,973 Primary 19.7 14.3 63.5 2.6 100.0 739 Secondary 18.5 10.8 65.7 5.0 100.0 509 More than secondary 25.9 17.1 55.5 1.5 100.0 116 Wealth quintile Lowest 28.9 13.9 53.5 3.7 100.0 2,424 Second 21.9 15.4 58.8 3.9 100.0 2,460 Middle 17.3 18.1 61.8 2.7 100.0 2,545 Fourth 16.3 14.2 65.8 3.7 100.0 2,260 Highest 14.3 13.5 69.6 2.6 100.0 1,647 Total 20.1 15.2 61.3 3.4 100.0 11,336 1 Total includes 10 women with missing information on employment status. 2 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Table 16.14 Sources for help to stop the violence Percentage of ever-married women age 15-49 who have experienced physical or sexual violence and sought help by sources from which they sought help, according to the type of violence that women reported, Afghanistan 2015 Type of violence experienced Person Physical only Physical and sexual Total Own family 81.4 76.2 80.3 Husbands family 28.7 52.4 33.9 Husband 1.1 0.8 1.0 Friend 3.0 8.6 4.3 Neighbor 8.9 48.5 17.7 Religious leader 1.1 5.4 2.0 Doctormedical personnel 0.1 1.0 0.3 Police 0.0 0.9 0.2 Lawyer 0.0 0.6 0.2 Social work organization 0.0 0.3 0.1 Other 0.1 0.0 0.1 Number of women who have experienced violence and sought help 1,769 509 2,283 Note: Women can report more than one source from which they sought help. Total includes 5 women who experienced only sexual violence not shown separately. Fistula • 299 FISTULA 17 Key Findings  Fistula prevalence: Three percent of women reported having ever experienced symptoms of fistula.  Fistula prevalence by residence: Both urban and rural women reported having experienced symptoms of fistula 4 and 3.  Treatment for fistula: More than half of women 56 who reported ever suffering from symptoms of fistula did not seek treatment. bstetric fistula is a complication that arises from obstructed or prolonged labor that creates a hole or opening in the birth canal. Prolonged obstructed labor that does not receive prompt medical care stops the blood supply to the tissues of the vagina, bladder, andor rectum. Unrelieved obstructed labor can compress a woman’s bladder, urethra, rectum, and vaginal wall between the fetal head and maternal pubis. This compression and the resultant loss of blood supply produces necrosis of the compressed tissues. Necrosis then causes uncontrolled leakage of urine from the bladder through the vagina vesico-vaginal fistula and leakage of stool from the vagina recto-vaginal fistula HERA and ICRH 2010. The 2015 AfDHS included a series of questions on fistula that measured awareness levels, estimated the prevalence of fistula among Afghanistan women, and examined events that can precipitate fistula symptoms and access to treatment. This chapter explores women’s knowledge and experience of fistula symptoms and presents findings on women’s experiences among ever-married women of reproductive age 15-49.

17.1 W

OMENS ’ K NOWLEDGE OF F ISTULA All ever-married women age 15-49 interviewed in the 2015 AfDHS were asked if they have heard of fistula. Those who reported having knowledge of fistula were asked further questions. Twenty-three percent of ever-married women are aware of the symptoms of fistula Table 17.1. Patterns by background characteristics  There is substantial variation in knowledge of fistula among women by age: 17 of women age 15-19 have heard of fistula compared with 31 of women age 40-49 Figure 17.1 and Table 17.1.  Knowledge of fistula is higher among urban women 29 than rural women 22. O Figure 17.1 Knowledge of fistula by age 17 19 22 24 31 15-19 20-24 25-29 30-39 40-49 Percentage of ever-married women who have ever heard of fistula 300 • Fistula  Women with more than secondary education are the most likely to have heard about symptoms of fistula 34.  Women in the highest wealth quintile are more likely to be aware of fistula 31 than women in the other wealth quintiles 18-23.

17.2 S

ELF -R EPORTED S YMPTOMS AND T REATMENT

17.2.1 Self-reported Fistula Symptoms

All women who reported hearing about fistula were asked if they had ever experienced the condition. Three percent of women age 15-49 reported experiencing symptoms of fistula during their lifetime Table 17.1. Those who reported suffering from fistula were asked how the problem began. Two-thirds of women 66 believed that it began after delivery, 6 after having a stillbirth, and 7 after sexual assault; 17 were unable to cite a reason for developing such symptoms Figure 17.2. Among women who reported that the problem began after delivery or stillbirth, 37 reported that they had a very difficult labor and delivery. However, 58 of women who reported their symptoms began after delivery of a baby or a stillbirth reported having had a normal delivery. Twenty-nine percent of women reported that the symptoms started within 2 to 4 days after delivery, while 37 reported that the symptoms started 8 or more days after delivery Table 17.2. Patterns by background characteristics  Younger women age 15-19 and women age 30-39 more often reported having experienced symptoms of fistula than other women Table 17.1.  Both urban and rural women reported having experienced fistula 4 and 3.  Reports of fistula are high in Ghor 26 and Baghlan 13.  Women of all educational levels and wealth status report having experienced fistula.

17.2.2 Treatment Seeking for Fistula

Women who experienced the symptoms of fistula were asked if they sought treatment for this condition, from whom they sought treatment, and whether the treatment stopped the leakage.  A total of 4 in 10 women with symptoms of fistula sought treatment, 3 in 10 from a doctor 30, and 1 in 10 from a nurse or midwife 13 Table 17.3.  More than 5 in 10 women with fistula 56 did not seek any treatment.  Fifteen percent of women with fistula had an operation to attempt to fix the problem Table 17.4. Figure 17.2 Reported cause of fistula After delivery 66 After stillbirth 6 Sexual assault 7 Do not know 17 Other cause 4 Percent distribution among ever-married women reporting fistula symptoms Fistula • 301  Among all women who sought treatment, 47 reported the leakage stopped completely Figure 17.3.  One in 3 women who sought treatment had their leakage reduced but not stopped.  Twelve percent of women who sought treatment had no reduction in leakage.  Eight percent of women who sought treatment did not receive any medical support. Patterns by background characteristics  An overwhelming majority of rural women 63 did not seek treatment for fistula compared with urban women 37 Table 17.3.  Women in the lowest wealth quintile are more than three times less likely to seek treatment for fistula than those in the highest wealth quintile 76 versus 24.  Women age 20-34 who experienced the symptoms of fistula more often reported that the leakage stopped after treatment than women age 35-49 54 versus 46 Table 17.4.  Older women age 35-49 who experienced the symptoms of fistula were more likely than younger women age 20-34 to have had an operation to attempt to fix the problem 24 versus 8.  Rural women 24 were more likely than urban women 4 to have had an operation.  Rural women 54 were also more likely than urban women 38 to report that their leakage was completely stopped after having sought treatment. Women who did not seek treatment were asked for the reason for not getting treatment. The most common reason for not seeking treatment among women who reported fistula symptoms was their lack of awareness about the possibility of fixing the problem 46, followed by embarrassment 12 and their lack of knowledge about where to go for treatment 11 Table 17.5 and Figure 17.4. L IST OF T ABLES For more information on fistula, see the following tables:  Table 17.1 Fistula  Table 17.2 Characteristics of labor reported as cause of fistula symptoms  Table 17.3 Type of provider for treatment of fistula  Table 17.4 Outcome of treatment of fistula  Table 17.5 Reasons for not seeking treatment for fistula symptoms Figure 17.3 Outcome of fistula treatment Figure 17.4 Reason for not seeking treatment Leakage stopped completely 47 Not stopped but reduced 33 Not stopped at all 12 Did not receive medical support 8 Percent distribution among ever-married women reporting fistula symptoms 46 12 11 8 5 3 2 Did not know it can be fixed Embarrassment Did not know where to go Too expensive Too far Could not get permission Problem disappeared Percentage among ever-married women age 15-49 with fistula symptoms 302 • Fistula Table 17.1 Fistula Percentage of ever-married women who have ever heard of fistula and percentage who have experienced fistula, according to background characteristics, Afghanistan 2015 Percentage of women who: Background characteristic have ever heard of fistula have ever had fistula Number of women Age 15-19 16.9 3.6 1,825 20-24 18.5 1.9 6,089 25-29 21.8 2.6 6,299 30-39 23.9 3.7 8,765 40-49 30.6 3.2 6,482 Residence Urban 29.4 3.8 6,870 Rural 21.6 2.7 22,591 Province 1 Kabul 19.7 6.1 3,658 Kapisa 4.0 0.6 205 Parwan 18.2 1.6 625 Wardak 23.5 7.7 382 Logar 33.5 4.6 472 Nangarhar 20.9 2.3 794 Laghman 26.5 0.9 583 Panjsher 1.8 0.4 54 Baghlan 56.5 13.2 839 Bamyan 9.4 0.2 303 Ghazni 19.3 4.6 1,328 Paktika 7.1 0.8 792 Paktya 10.5 0.1 542 Khost 25.7 2.4 851 Kunarha 1.9 0.1 559 Nooristan 6.1 0.3 222 Badakhshan 7.3 0.3 1,004 Takhar 50.6 0.0 1,105 Kunduz 1.3 1.2 1,232 Samangan 1.9 0.2 330 Balkh 15.4 0.4 1,781 Sar-E-Pul 49.5 4.2 654 Ghor 35.4 26.0 715 Daykundi 2.2 2.4 329 Urozgan 3.2 0.9 230 Kandahar 62.0 2.6 2,227 Jawzjan 1.8 0.2 614 Faryab 11.2 0.2 2,114 Helmand 29.1 0.3 875 Badghis 28.2 0.6 650 Herat 21.0 1.6 2,316 Farah 17.0 1.7 777 Nimroz 56.3 0.1 278 Education No education 23.4 3.1 24,604 Primary 21.6 1.9 2,330 Secondary 22.5 3.5 1,971 More than secondary 33.8 1.8 556 Wealth quintile Lowest 22.8 4.1 5,904 Second 18.2 2.6 6,001 Middle 23.3 2.0 5,888 Fourth 22.2 2.9 6,010 Highest 30.9 3.2 5,657 Total 23.4 3.0 29,461 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Fistula • 303 Table 17.2 Characteristics of labor reported as cause of fistula symptoms Among ever-married women who reported labor as the cause of their fistula symptoms, the percent distribution by characteristics of labor and delivery and survival status of infant, and by the number of days after the delivery that symptoms began, Afghanistan 2015 Characteristic Percentage of women Characteristics of labor and delivery Normal labor and delivery, baby born alive 57.9 Normal labor and delivery, baby stillborn 0.9 Very difficult labor and delivery, baby born alive 30.6 Very difficult labor and delivery, baby stillborn 6.0 Missing 4.6 Number of days after the delivery that symptoms began 0-1 22.6 2-4 29.2 5-7 6.6 8 or more days 36.9 Missing 4.7 Total 100.0 Number 635 304 • Fistula Table 17.3 Type of provider for treatment of fistula Among ever-married women age 15-49 who experienced symptoms of fistula, the percent distribution by type of provider of the treatment, according to background characteristics, Afghanistan 2015 Type of health provider Background characteristic Doctor Nurse midwife Community health worker Other Missing No treatment Total Number of women Womens age at first birth 20 48.0 2.1 0.0 0.0 0.0 49.9 100.0 65 20-34 25.6 10.6 0.3 0.1 0.2 63.2 100.0 446 35-49 33.0 17.5 0.2 1.7 0.0 47.6 100.0 367 Residence Urban 44.1 18.5 0.0 0.0 0.0 37.4 100.0 259 Rural 24.6 10.5 0.4 1.1 0.2 63.3 100.0 619 Education No education 26.3 11.2 0.3 0.9 0.1 61.2 100.0 756 Primary 54.7 16.4 0.0 0.0 0.0 29.0 100.0 43 Secondary 58.1 21.6 0.0 0.0 0.0 20.3 100.0 69 More than secondary 100.0 10 Wealth quintile Lowest 14.1 6.8 0.6 2.4 0.0 76.1 100.0 242 Second 28.4 17.3 0.5 0.6 0.0 53.1 100.0 156 Middle 29.5 7.3 0.0 0.0 0.9 62.3 100.0 120 Fourth 29.3 12.5 0.0 0.0 0.0 58.2 100.0 175 Highest 54.9 20.8 0.0 0.0 0.0 24.2 100.0 184 Total 30.3 12.8 0.3 0.8 0.1 55.7 100.0 878 Note: 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. Table 17.4 Outcome of treatment of fistula Among ever-married women age 15-49 who experienced symptoms of fistula and sought treatment, the percent distribution by outcome of treatment, and the percentage who had an operation, according to background characteristics, Afghanistan 2015 Among those who sought treatment: Percentage of women who had an operation Background characteristic Leakage stopped completely Not stopped but reduced Not stopped at all Did not receive any treatment Missing Total Number of women Womens age at first birth 20 100.0 33 20-34 53.6 29.9 6.7 9.2 0.7 100.0 7.6 164 35-49 46.1 39.8 7.0 7.2 0.0 100.0 23.7 192 Residence Urban 37.6 36.2 17.6 8.6 0.0 100.0 3.9 162 Rural 53.9 29.8 7.9 8.0 0.5 100.0 23.7 227 Education No education 49.0 37.7 6.8 6.1 0.4 100.0 17.9 293 Primary 48.9 3.0 29.0 19.1 0.0 100.0 14.9 31 Secondary 29.4 27.1 30.3 13.3 0.0 100.0 4.2 55 More than secondary 82.3 0.0 9.0 8.6 0.0 100.0 7.1 10 Wealth quintile Lowest 35.2 39.7 12.6 12.6 0.0 100.0 31.0 58 Second 66.9 24.9 8.2 0.0 0.0 100.0 26.5 73 Middle 59.3 27.8 9.4 1.1 2.4 100.0 12.5 45 Fourth 42.3 36.0 4.0 17.6 0.0 100.0 18.1 73 Highest 40.1 33.2 18.6 8.2 0.0 100.0 2.7 139 Total 47.1 32.5 11.9 8.2 0.3 100.0 15.4 389 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Fistula • 305 Table 17.5 Reasons for not seeking treatment for fistula symptoms Among ever-married women who reported experiencing fistula but not seeking treatment, percentage by reasons for not seeking treatment, Afghanistan 2015 Reasons Percentage of women Did not know the problem can be fixed 46.3 Did not know where to go 11.4 Too expensive 7.9 Embarrassment 12.2 Too far 4.7 Problem disappeared 2.4 Could not get permission 2.9 Other 2.7 Number 489 References • 307 REFERENCES Afghanistan National Development Strategy Secretariat. 2010. Afghanistan National Development Strategy 2008-2013: An Interim Strategy for Security, Governance, Economic Growth, and Poverty Reduction, Volume 1. Kabul, Afghanistan: Islamic Republic of Afghanistan. Bradley, S. E. K., T. N. Croft, J. D. Fishel, and C. F. Westoff. 2012. Revising Unmet Need for Family Planning. DHS Analytical Studies No. 25. Calverton, Maryland, USA: ICF International. Graham, W., W. Brass, and R. W. Snow. 1989. “Indirect Estimation of Maternal Mortality: The Sisterhood Method,” Studies in Family Planning 203: 125-135. doi:10.23071966567. Health Research for Action HERA and International Center for Reproductive Health ICRH. 2010. Thematic Evaluation of National Programs and UNFPA Experience in the Campaign to End Fistula: Assessment of GlobalRegional Activities. “Volume I: GlobalRegional Report, Final Report – March 2010.” Reet, Belgium: HERA and ICRH. Ministry of Justice MoJ [Afghanistan]. 2009. Law on Elimination of Violence against Women EVAW. Afghanistan: Ministry of Justice. Ministry of Public Health MoPH [Afghanistan]. 2009. Afghanistan Annual Malaria Journal - Issue 1 April 2009. Kabul, Afghanistan: MoPH. Ministry of Public Health MoPH [Afghanistan]. 2010a. A Basic Package of Health Services for Afghanistan – 20101389. Kabul, Afghanistan: MoPH. Ministry of Public Health MoPH [Afghanistan]. 2010b. National Public Nutrition Policy and Strategy 1388-1392 2009-2013. Kabul, Afghanistan: MoPH. Ministry of Public Health MoPH, National Immunization Program [Afghanistan]. 2011. Comprehensive Multi-Year Plan cMYP for National Immunization Program NIP – 2011-2015. Kabul, Afghanistan: MoPH. Ministry of Public Health MoPH [Afghanistan], National Malaria Leishmaniasis Control Program. 2012. National Malaria Strategic plan 2013-2017. Kabul, Afghanistan: MoPH. Ministry of Public Health MoPH [Afghanistan]. 2013. Malaria Program Review 2013. Kabul, Afghanistan: MoPH. Ministry of Public Health MoPH [Afghanistan]. 2015a. National Health Policy 2015-2020. Kabul, Afghanistan: MoPH. Ministry of Public Health MoPH [Afghanistan]. 2015b. Call to Action 2015-2020. Kabul, Afghanistan: MoPH. Rutenberg, N., and J. Sullivan. 1991. “Direct and Indirect Estimates of Maternal Mortality from the Sisterhood Method,” Proceedings of the Demographic and Health Surveys World Conference 3: 1669- 1696. Columbia, Maryland, USA: IRDMacro International Inc. Saleem, Sarah, et al. 2014. “A Prospective Study of Maternal, Fetal and Neonatal Deaths in Low- and Middle-Income Countries.” Bulletin World Health Organization 92:605-612. 308 • References Stanton, C. N. Abderrahim, and K. Hill. 1997. DHS Maternal Mortality Indicators: An Assessment of Data Quality and Implications for Data Use. DHS Analytical Reports No. 4. Calverton, Maryland, USA: Macro International Inc. United Nations. 1993. Declaration on the Elimination of Violence against Women. ARES48104. General Assembly 85 th plenary meeting. New York: United Nations. United Nations. 2006. Secretary-General’s In-depth Study on All Forms of Violence against Women. New York: United Nations. United Nations Program on HIV and AIDS. 2015. HIV and AIDS Estimates 2015, UNAIDS Spectrum Estimates – 2015. http:www.unaids.orgenregionscountriescountriesafghanistan. World Health Organization WHO. 1998. Complementary Feeding of Young Children in Developing Countries: A Review of Current Scientific Knowledge. Geneva, Switzerland: World Health Organization. World Health Organization WHO. 2001. Putting Women First: Ethical and Safety Recommendations for Research on Domestic Violence against Women. Geneva, Switzerland: WHO. World Health Organization WHO. 2008. Indicators for Assessing Infant and Young Child Feeding Practices. Part I: Definitions. Conclusions of a Consensus Meeting held 6-8 November 2007 in Washington, DC, USA. http:whqlibdoc.who.intpublications20089789241596664_eng.pdf. World Health Organization WHO. 2011. International Statistical Classification of Diseases and Related Health Problems – 10 th Revision, 2010 Edition. Geneva, Switzerland: WHO. http:www.who.intclassificationsicdICD10Volume2_en_2010.pdf?ua=1. World Health Organization WHO. 2015a. WHO Statement on Caesarean Section Rates. Geneva: WHO. http:www.who.intreproductivehealthpublicationsmaternal_perinatal_healthcs-statementen WHORHR15.02. World Health Organization WHO.2015b. Postnatal Care for Mothers and Newborns, Highlights from the World Health Organization 2013 Guideline. Geneva: WHO http:www.who.intmaternal_child_adolescentpublicationsWHO-MCA-PNC-2014-Briefer_A4.pdf accessed August 21, 2016. Appendix A • 309 SAMPLE DESIGN APPENDIX A A.1 I NTRODUCTION he 2015 Afghanistan Demographic and Health Survey 2015 AfDHS is the first DHS survey conducted in Afghanistan. The main objective of the 2015 AfDHS is to provide up-to-date information on fertility and childhood mortality levels; fertility preferences; awareness, approval, and use of family planning methods; maternal and child health; and knowledge and attitudes toward HIVAIDS and other sexually transmitted infections STIs. The 2015 AfDHS calls for a nationally representative sample of 25,650 residential households; in all the sample households, all ever-married women age 15-49 who are usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed in the survey. In half of the sample households, all ever-married men age 15-49 who are usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed in the survey. In each household, one woman age 15-49 was randomly selected to be eligible for the Domestic Violence module. The 2015 AfDHS was designed to provide most of the key indicators for the country as a whole, for urban and rural areas separately, and for each of the 34 provinces in Afghanistan. These provinces are located in eight regions as follows:  The Northern region: Balkh, Faryab, Jawzjan, Samangan, and Sar-E-Pul  The North Eastern region: Badakhshan, Baghlan, Kunduz, and Takhar  The Western region: Badghis, Farah, Ghor, and Herat  The Central Highland region: Bamyan and Daykundi  The Capital region: Kabul, Kapisa, Logar, Panjsher, Parwan, and Wardak  The Southern region: Ghazni, Helmand, Kandahar, Nimroz, Urozgan, and Zabul  The South Eastern region: Khost, Paktika, and Paktya  The Eastern region: Kunarha, Laghman, Nangarhar, and Nooristan A.2 S AMPLE F RAME The sampling frame for the 2015 AfDHS is the updated version of the Household Listing Frame, prepared in 2003-2004 and updated in 2009, provided by the Central Statistical Organization CSO. The CSO disposes an electronic file consisting of 25,974 enumeration areas EAs that cover the entire country. An EA is a geographic area consisting of a convenient number of dwelling units that serve as counting units for the census. In urban areas, an EA is a city block; in rural areas, an EA is either a village, a group of small, adjacent villages, or a part of a large village. The frame file contains information about the location province, district, and control area, the type of residence urban or rural, and the estimated number of residential households for each of the 25,974 EAs. Also available for each EA are satellite maps, which delimit the geographic boundaries of the EA. The EA sizes are rough estimates and quite homogenous, with an average of 164.4 households per EA, as indicated in Table A.2. Administratively, Afghanistan is divided into 34 provinces; each province is subdivided into districts, with a total number of 458 districts, and each district is subdivided into Nahia’s in urban areas and villages in rural areas. The 34 provinces are regrouped to form eight geographical regions. Table A.1 below shows the household distribution by province and by type of residence. In Afghanistan, 23 of the households reside T 310 • Appendix A in urban areas, and 78 reside in rural areas. Among the 34 provinces, most of them have a very small area that is urban, and two of them, Nooristan and Panjsher, have no urban areas at all. The provinces are very different in size; with the largest province, Kabul, representing 13 of the total households of the country, and the smallest province, Panjsher, representing only 0.6. The percentage of urban areas is low in most of the 34 provinces, less than 10 in 22 provinces, between 10 and 20 in 4 provinces, and more than 20 in 8 provinces, where the highest percentage of urban areas is 80 in Kabul. Table A.1 Distribution of residential households by province and type of residence Households Households Distribution Province Urban Rural Total Province Urban Kabul 448,333 110,665 558,998 13.1 80.2 Kapisa 164 56,848 57,012 1.3 0.3 Parwan 8,569 85,408 93,977 2.2 9.1 Wardak 494 91,695 92,189 2.2 0.5 Logar 535 62,172 62,707 1.5 0.9 Nangarhar 26,163 207,439 233,602 5.5 11.2 Laghman 1,727 67,631 69,358 1.6 2.5 Panjsher 26,079 26,079 0.6 0.0 Baghlan 32,051 101,845 133,896 3.1 23.9 Bamyan 4,489 56,524 61,013 1.4 7.4 Ghazni 5,664 175,112 180,776 4.2 3.1 Paktika 295 109,220 109,515 2.6 0.3 Paktya 3,410 101,639 105,049 2.5 3.2 Khost 8,062 86,333 94,395 2.2 8.5 Kunarha 7,800 99,237 107,037 2.5 7.3 Nooristan 29,858 29,858 0.7 0.0 Badakhshan 9,270 136,065 145,335 3.4 6.4 Takhar 22,616 126,929 149,545 3.5 15.1 Kunduz 32,144 91,708 123,852 2.9 26.0 Samangan 5,037 55,706 60,743 1.4 8.3 Balkh 70,267 124,400 194,667 4.6 36.1 Sar-E-Pul 6,824 82,754 89,578 2.1 7.6 Ghor 3,467 127,929 131,396 3.1 2.6 Daykundi 1,609 86,305 87,914 2.1 1.8 Urozgan 5,092 58,855 63,947 1.5 8.0 Zabul 3,569 56,217 59,786 1.4 6.0 Kandahar 59,958 95,337 155,295 3.6 38.6 Jawzjan 19,644 53,613 73,257 1.7 26.8 Faryab 20,960 121,369 142,329 3.3 14.7 Helmand 35,246 193,332 228,578 5.4 15.4 Badghis 3,905 87,522 91,427 2.1 4.3 Herat 101,467 232,530 333,997 7.8 30.4 Farah 4,684 89,129 93,813 2.2 5.0 Nimroz 6,900 21,595 28,495 0.7 24.2 Afghanistan 960,415 3,309,000 4,269,415 100.0 22.5 Source: The updated version of the Household Listing Frame prepared in 2003-2004 and updated in 2009, provided by the Central Statistical Organization CSO. Table A.2 below indicates the distribution of EAs and their average size in number of households by province and by type of residence. There are a total 25,974 EAs; 4,340 EAs are in urban areas and 21,634 EAs are in rural areas. The average EA size is 164.4 households; the urban EAs have a larger size, with an average of 221.3 households per EA, and the rural EAs have a smaller size with an average of 153 households per EA. Appendix A • 311 Table A.2 Numbers of EAs and average size of EAs by province and type of residence Number of EAs Average number of households per EA Province Urban Rural Total Urban Rural Total Kabul 1,870 575 2,445 239.8 192.5 228.6 Kapisa 1 365 366 164.0 155.7 155.8 Parwan 46 464 510 186.3 184.1 184.3 Wardak 2 689 691 247.0 133.1 133.4 Logar 5 349 354 107.0 178.1 177.1 Nangarhar 139 1,459 1,598 188.2 142.2 146.2 Laghman 13 451 464 132.8 150.0 149.5 Panjsher 154 154 NA 169.3 169.3 Baghlan 173 684 857 185.3 148.9 156.2 Bamyan 19 410 429 236.3 137.9 142.2 Ghazni 24 1,327 1,351 236.0 132.0 133.8 Paktika 1 545 546 295.0 200.4 200.6 Paktya 15 662 677 227.3 153.5 155.2 Khost 28 599 627 287.9 144.1 150.6 Kunarha 31 657 688 251.6 151.0 155.6 Nooristan 181 181 NA 165.0 165.0 Badakhshan 46 950 996 201.5 143.2 145.9 Takhar 112 807 919 201.9 157.3 162.7 Kunduz 155 669 824 207.4 137.1 150.3 Samangan 21 344 365 239.9 161.9 166.4 Balkh 332 905 1,237 211.6 137.5 157.4 Sar-E-Pul 33 529 562 206.8 156.4 159.4 Ghor 10 754 764 346.7 169.7 172.0 Daykundi 5 581 586 321.8 148.5 150.0 Urozgan 22 324 346 231.5 181.7 184.8 Zabul 15 423 438 237.9 132.9 136.5 Kandahar 279 640 919 214.9 149.0 169.0 Jawzjan 95 403 498 206.8 133.0 147.1 Faryab 98 820 918 213.9 148.0 155.0 Helmand 185 1,233 1,418 190.5 156.8 161.2 Badghis 21 534 555 186.0 163.9 164.7 Herat 492 1,461 1,953 206.2 159.2 171.0 Farah 24 567 591 195.2 157.2 158.7 Nimroz 28 119 147 246.4 181.5 193.8 Afghanistan 4,340 21,634 25,974 221.3 153.0 164.4 Source: The updated version of the Household Listing Frame prepared in 2003-2004 and updated in 2009, provided by the Central Statistical Organization CSO. A.3 S AMPLE D ESIGN AND I MPLEMENTATION The sample for the 2015 AfDHS is a stratified sample selected in two stages from the sampling frame. Stratification was achieved by separating each province into urban and rural areas. In total, 66 sampling strata have been created because there are no urban areas in Nooristan and Panjsher. Samples were selected independently in each sampling stratum, by a two-stage selection. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels within a sampling stratum. This was done by sorting the sampling frame according to administrative units at different levels within each stratum and by using a probability proportional to size selection at the first stage of sampling. In the first stage, 950 EAs were selected, 260 EAs in urban areas and 690 EAs in rural areas, with probability proportional to the EA size and with independent selection in each sampling stratum, with the sample allocation given in Table A.3. It was recognized that some areas in the country might be difficult to reach because of ongoing security issues. Therefore, to mitigate the situation, replacement clusters were selected in rural areas for 101 clusters. Within each province, the number of the preselected replacement clusters did not exceed 10 percent of the selected clusters in the province. A household listing operation was carried out in all the selected EAs, and the resulting lists of households served as a sampling frame for the selection of households in the second stage. During the household listing activities, some of the selected EAs, 127 EAs, were found to be very large. To minimize the task of household listing in these EAs, each large EA was segmented into 2-3 segments. Only one segment was selected for the survey with probability proportional to the segment size. Household listing was conducted only in the selected segment. This means that a 2015 AfDHS cluster is either an EA or a segment of an EA. 312 • Appendix A During the household listing operation, more than 70 selected clusters were identified as insecure. Therefore, a decision was made to carry out the household listing operation in all of the 101 preselected replacement clusters. Overall, the survey was successfully carried out in 956 clusters. Because of extreme security issues in rural areas of Zabul, all selected clusters in rural areas were dropped; only seven clusters that were selected from urban areas could be covered. Consequently, it was not possible to provide provincial level estimates for Zabul; however, the information collected from this province is included in the national level estimates. In the second stage of selection, a fixed number of 27 households per cluster was selected with an equal probability systematic selection from the newly created household listing. The survey interviewer interviewed only the pre-selected households. No replacements and no changes of the pre-selected households were allowed in the implementing stages in order to prevent bias. All ever-married women age 15-49 who are usual members of the selected households or who spent the night before the survey in the selected households were eligible for the female survey. In about half of the selected households, all men age 15-49 who are usual members of the households or who spent the night before the survey in the households were eligible for the male survey. Table A.3 shows the allocation of EAs and households according to provinces and urban-rural areas, and Table A.4 shows the expected number of completed women’s interviews according to provinces and urban-rural areas. To ensure that the survey precision is comparable across provinces, the sample allocation figures a power allocation between provinces and between different types of residences within each province. The survey was expected to be conducted in 25,650 residential households, 7,020 in urban areas and 18,630 in rural areas. The sample was expected to result in about 29,541 completed interviews with ever-married women age 15-49: 7,878 interviews in urban areas and 21,663 interviews in rural areas. Also, the sample was expected to result in about 11,859 completed interviews with men age 15-49: 3,163 interviews in urban areas and 8,696 interviews in rural areas. Table A.3 Sample allocation of clusters and households by province and type of residence Number of clusters allocated Number of households allocated Province Urban Rural Total Urban Rural Total Kabul 21 12 33 567 324 891 Kapisa 1 27 28 27 729 756 Parwan 8 19 27 216 513 729 Wardak 2 27 29 54 729 783 Logar 3 23 26 81 621 702 Nangarhar 9 21 30 243 567 810 Laghman 5 21 26 135 567 702 Panjsher 26 26 702 702 Baghlan 11 17 28 297 459 756 Bamyan 7 19 26 189 513 702 Ghazni 6 23 29 162 621 783 Paktika 1 29 30 27 783 810 Paktya 6 22 28 162 594 756 Khost 8 20 28 216 540 756 Kunarha 8 20 28 216 540 756 Nooristan 26 26 702 702 Badakhshan 7 21 28 189 567 756 Takhar 10 19 29 270 513 783 Kunduz 12 16 28 324 432 756 Samangan 8 18 26 216 486 702 Balkh 13 16 29 351 432 783 Sar-E-Pul 8 20 28 216 540 756 Ghor 6 22 28 162 594 756 Daykundi 5 22 27 135 594 729 Urozgan 7 19 26 189 513 702 Zabul 7 19 26 189 513 702 Kandahar 13 16 29 351 432 783 Jawzjan 11 16 27 297 432 729 Faryab 10 19 29 270 513 783 Helmand 10 20 30 270 540 810 Badghis 6 21 27 162 567 729 Herat 13 18 31 351 486 837 Farah 7 21 28 189 567 756 Nimroz 11 15 26 297 405 702 Afghanistan 260 690 950 7,020 18,630 25,650 Appendix A • 313 Table A.4 Sample allocation of expected completed women’s and men’s interviews by province and type of residence Expected number of interviews with women age 15-49 Expected number of interviews with men age 15-49 Province Urban Rural Total Urban Rural Total Kabul 637 377 1,014 255 152 407 Kapisa 30 847 877 12 340 352 Parwan 242 597 839 98 239 337 Wardak 60 847 907 24 340 364 Logar 92 722 814 36 290 326 Nangarhar 273 660 933 109 265 374 Laghman 152 660 812 60 265 325 Panjsher 817 817 328 328 Baghlan 333 534 867 134 214 348 Bamyan 212 597 809 85 239 324 Ghazni 182 722 904 73 290 363 Paktika 30 910 940 12 365 377 Paktya 182 690 872 73 277 350 Khost 242 627 869 98 252 350 Kunarha 242 627 869 98 252 350 Nooristan 817 817 328 328 Badakhshan 212 660 872 85 265 350 Takhar 303 597 900 122 239 361 Kunduz 364 502 866 146 202 348 Samangan 242 565 807 98 227 325 Balkh 394 502 896 158 202 360 Sar-E-Pul 242 627 869 98 252 350 Ghor 182 690 872 73 277 350 Daykundi 152 690 842 60 277 337 Urozgan 212 597 809 85 239 324 Zabul 212 597 809 85 239 324 Kandahar 394 502 896 158 202 360 Jawzjan 333 502 835 134 202 336 Faryab 303 597 900 122 239 361 Helmand 303 627 930 122 252 374 Badghis 182 660 842 73 265 338 Herat 394 565 959 158 227 385 Farah 212 660 872 85 265 350 Nimroz 333 472 805 134 189 323 Afghanistan 7,878 21,663 29,541 3,163 8,696 11,859 The sample allocations were derived using information obtained from the 2010 Afghanistan Mortality Survey AMS; the average number of women age 15-49 per household is 1.2; the average number of men age 15-49 per household is 1; the household completion rate is 96 in urban areas and 98 in rural areas; the women individual completion rate is 97.5 in urban areas and 98.5 in rural areas. The same completion rates were used to calculate the expected number of completed interviews with men. A.4 S AMPLE P ROBABILITIES AND S AMPLING W EIGHTS Due to the nonproportional allocation of the sample across provinces and to their urban and rural areas, and the differential response rates, sampling weights must be used in all analyses of the 2015 AfDHS results to ensure that survey results are representative at both the national and domain level. Because the 2015 AfDHS sample is a two-stage stratified cluster sample, sampling weights are based on sampling probabilities calculated separately for each sampling stage and for each cluster where: P 1hi : first-stage sampling probability of the i th cluster in stratum h P 2hi : second-stage sampling probability within the i th cluster households The following describes the calculation of these probabilities: Let a h be the number of clusters selected in stratum h, M hi the number of households according to the sampling frame in the i th cluster, and M hi  the total number of households in the stratum. The probability of selecting the i th cluster in stratum h in the 2015 AfDHS sample is calculated as follows: 314 • Appendix A M M a hi hi h  Let hi b be the proportion of households in the selected segment compared with the total number of households in cluster i in stratum h if the cluster is segmented, otherwise 1  hi b . Then the probability of selecting cluster i in the sample is: hi hi hi h 1hi b M M a = P   Let hi L be the number of households listed in the household listing operation in cluster i in stratum h, and let hi g be the number of households selected in the cluster. The second stage’s selection probability for each household in the cluster is calculated as follows: hi hi hi L g P  2 The overall selection probability of each household in cluster i of stratum h in the 2015 AfDHS is therefore the product of the two stages’ selection probabilities: hi hi hi P P P 2 1   The design weight for each household in cluster i of stratum h is the inverse of its overall selection probability: hi hi P W 1  A spreadsheet containing all sampling parameters and selection probabilities was prepared to facilitate the calculation of the design weights. Design weights were adjusted for household nonresponse and individual nonresponse to obtain the sampling weights for households and for women and men, respectively. Nonresponse is adjusted at the sampling stratum level. For the household sampling weight, the household design weight is multiplied by the inverse of the household response rate, by stratum. For the women’s individual sampling weight, the household sampling weight is multiplied by the inverse of the women’s individual response rate, by stratum. For the men’s individual sampling weight, the household sampling weight for the male subsample is multiplied by the inverse of the men’s individual response rate, by stratum. After adjusting for nonresponse, the sampling weights are normalized to get the final standard weights that appear in the data files. The normalization process is aimed at obtaining a total number of unweighted cases equal to the total number of weighted cases using normalized weights at the national level, for the total number of households, women, and men. Normalization is done by multiplying the sampling weight by the estimated total sampling fraction obtained from the survey for the household weight, the individual woman’s weight, and the individual man’s weight. The normalized weights are relative weights that are valid for estimating means, proportions, ratios, and rates, but they are not valid for estimating population totals or for pooled data. Special weights for domestic violence were calculated that account for the selection of one woman per household. A pp en dix A • 315 Table A.5 Sample implementation: Women Percent distribution of households and eligible women by results of the household and individual interviews, and household, eligible women, and overall women’s response rates, according to urban-rural residence and