Calculation of sampling weights and post-stratiication

169 ANNEX V POPULATION BY AGE AND SEX ANNEX V POPULATION BY AGE AND SEX Table V.1.a: Population, by residence, sex, and by ive-year age groups in thousands Age Urban Rural Kuchi Total Male Female Both sexes Male Female Both sexes Male Female Both sexes Male Female Both sexes 0-4 452 419 871 1,779 1,708 3,486 166 135 301 2,396 2,262 4,658 5-9 459 418 877 1,844 1,670 3,514 138 140 278 2,442 2,228 4,670 10-14 425 402 826 1,425 1,275 2,700 112 83 194 1,962 1,759 3,721 15-19 400 428 828 971 976 1,947 65 57 121 1,436 1,461 2,897 20-24 333 282 616 727 769 1,496 45 53 98 1,105 1,105 2,209 25-29 233 220 453 651 714 1,365 54 61 115 939 995 1,933 30-34 161 161 322 534 521 1,055 38 36 74 733 718 1,451 35-39 141 153 294 452 448 900 34 37 71 628 638 1,265 40-44 120 111 232 356 344 700 25 23 49 501 479 981 45-49 92 89 181 283 254 536 22 18 40 396 361 757 50-54 83 110 193 257 303 559 20 21 41 359 434 793 55-59 60 68 128 198 153 351 13 9 22 271 230 502 60-64 54 53 107 188 142 330 11 9 20 252 205 457 65-69 49 30 79 102 64 166 6 6 12 157 100 257 70-74 40 24 64 92 48 140 7 4 11 140 75 215 75-79 14 10 24 37 15 52 2 3 5 53 28 81 80-84 14 6 20 32 13 45 4 - 4 50 19 69 85+ 11 ... 15 18 5 23 2 - 2 31 9 40 Total 3,141 2,989 6,130 9,945 9,420 19,365 764 696 1,459 13,850 13,105 26,955 Table V.1.b: Population, by residence, sex, and by ive-year age groups in percentages Age Urban Rural Kuchi Total Male Female Both sexes Male Female Both sexes Male Female Both sexes Male Female Both sexes 0-4 14.4 14.0 14.2 17.9 18.1 18.0 21.7 19.5 20.6 17.3 17.3 17.3 5-9 14.6 14.0 14.3 18.5 17.7 18.1 18.1 20.1 19.1 17.6 17.0 17.3 10-14 13.5 13.4 13.5 14.3 13.5 13.9 14.6 11.9 13.3 14.2 13.4 13.8 15-19 12.7 14.3 13.5 9.8 10.4 10.1 8.5 8.2 8.3 10.4 11.1 10.7 20-24 10.6 9.4 10.0 7.3 8.2 7.7 5.9 7.6 6.7 8.0 8.4 8.2 25-29 7.4 7.3 7.4 6.5 7.6 7.0 7.1 8.8 7.9 6.8 7.6 7.2 30-34 5.1 5.4 5.3 5.4 5.5 5.4 4.9 5.2 5.1 5.3 5.5 5.4 35-39 4.5 5.1 4.8 4.5 4.8 4.6 4.5 5.3 4.9 4.5 4.9 4.7 40-44 3.8 3.7 3.8 3.6 3.7 3.6 3.3 3.4 3.3 3.6 3.7 3.6 45-49 2.9 3.0 3.0 2.8 2.7 2.8 2.9 2.6 2.7 2.9 2.8 2.8 50-54 2.6 3.7 3.2 2.6 3.2 2.9 2.6 3.0 2.8 2.6 3.3 2.9 55-59 1.9 2.3 2.1 2.0 1.6 1.8 1.7 1.3 1.5 2.0 1.8 1.9 60-64 1.7 1.8 1.7 1.9 1.5 1.7 1.4 1.4 1.4 1.8 1.6 1.7 65-69 1.6 1.0 1.3 1.0 0.7 0.9 0.7 0.9 0.8 1.1 0.8 1.0 70-74 1.3 0.8 1.0 0.9 0.5 0.7 1.0 0.5 0.8 1.0 0.6 0.8 75-79 0.4 0.3 0.4 0.4 0.2 0.3 0.3 0.4 0.3 0.4 0.2 0.3 80-84 0.4 0.2 0.3 0.3 0.1 0.2 0.5 - 0.3 0.4 0.1 0.3 85+ 0.3 0.1 0.2 0.2 0.1 0.1 0.3 - 0.1 0.2 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 170 ANNEX VI MORTALITY ESTIMATION ANNEX VI MORTALITY ESTIMATION

VI.1 Methodology

The NRVA 2011-12 round did not foresee the production of fertility and mortality estimates. However, at last instance an abridged module was added to collect information about children ever born and children alive. Since no full birth histories were collected, it is not possible to estimate fertility in a way comparable to NRVA 2007-08. However, the data do allow the estimation of mortality indicators similar to the previous round. For the calculation of the Infant Mortality Rate IMR and the Under-ive Mortality Rate U5MR, the Brass method of indirect mortality estimation was applied, using the Trussell variant and the West model life tables of the Coale-Demeny model life tables United Nations 1983, United Nations 1990. The Brass method uses data on the total number of women by ive-year age group, their children ever born and children dead. In combination with coeficients that are estimated by regression analysis of simulated model cases, these data can be used to derive estimates of qx, the probability of dying between birth and age x, accounting for the duration of exposure to the risk of mortality, which is approximated by the women’s ages and the fertility pattern in the country. The number of women of each age group includes all women, regardless of marital status and parity, while the numbers of children ever born and dead refer to ever-married women between the ages of 15 and 49 in the female section of the NRVA questionnaire. This procedure has also been followed in the NRVA 2007-08 and MICS 2010 CSO and UNICEF 2012 and was one of the variants applied in the AMS 2010 APHIMoPH et al 2010. Women’s weights were calculated to adjust for women’s non-response to module 24 and large absence of information on children-ever-born and children dead from Zabul province.

VI.2 Sources of errors

There are several sources of error that must be considered when calculating child mortality estimates for Afghanistan from a household survey. This section focuses on non-sampling errors and does not examine sampling errors associated with taking a sample as opposed to collecting data on everyone in the population. One of the problems faced in survey taking in the Afghan population is age misreporting due to illiteracy, lack of birth registration and general ignorance the date of birth. Although the age accuracy has improved compared to NRVA 2007- 08, the Whipple index 223 and the Myers index 20.6 indicate highly inaccurate age reporting. The use of ive-year age groups helps mitigate age errors to some degree. A second source of errors relate to the reporting of the population by sex. As mentioned in section 3.2.1, the overall sex ratio in the survey population was 107, which is likely caused by underreporting of female household members. This is supported by the analysis of members that were added to the household listing after checking with the senior female household representative by female interviewers. This showed that detected omissions in the household roster for 79 percent referred to female household members. As for the sex ratio recorded for the total population, the sex ratio at birth suffers from a male bias. Whereas almost anywhere in the world the biological sex ratio at birth varies only between 105 and 106 boys per 100 girls UNFPA 2011, with most extreme estimates ranging from 104 to 107 boys per 100 girls Dubuc and Coleman 2007, the NRVA survey reported on average a sex ratio at birth of 113. Other surveys in Afghanistan collecting information of births experienced the same phenomenon. 1 The bias in NRVA 2011-12 is most pronounced in the mothers’ age group 20-24 Table VI.1. The skewed ratio is most likely resulting from one or both of two phenomena: intentional misclassiication of girls as boys for instance related to shame of having mostly or only girl children and underreporting of girl children under the assumption that the total number of boys reported is correct. The former would affect sex-speciic mortality ratio’s, but not the overall mortality ratio, while the latter would likely affect female mortality ratio’s as well as the overall mortality ratio. 1 E.g. The AMS 2010 found a sex ratio a t birth of 114, the MICS 2010 115 and NRVA 2007-08 110. 171 ANNEX VI MORTALITY ESTIMATION Table VI.1 Sex ratio of children ever born and children dead, by age group of the mother Age of mother Sex ratio Children ever born Children dead 15-19 110 110 20-24 127 145 25-29 113 98 30-34 109 108 35-39 109 104 40-44 111 101 45-49 124 106 Total 113 106 There is also some evidence of problems of reporting on deceased children by sex in the mothers’ age categories 20-24 and 25-29. However, the overall sex ratio of deceased children of 106 is plausible, given the biological higher mortality of boys compared to girls. A simulation was done to compensate for the alleged missing girls born. This simulation assumed a sex ratio at birth of 106 and a conservative estimate of the proportion dead among these missing girls of 25 percent. This procedure would raise the IMR from 48 to 54 and the U5MR from 91 to 92. The results, however, cannot be taken as an improvement as the assumptions are insuficiently substantiated.

VI.3 Mortality estimation

Table VI.2 represents the calculation of probabilities of dying before a speciied age x for all reported children born and separately for boys and girls. The estimates for the IMR and U5MR are, respectively 48 and 91 and refer to, respectively early 2011 and late 2005. The value for the IMR is unexpectedly low and given the problems encountered with age reporting, under-registration of girls born and sex ratios of deceased children of mothers in age group 20-29, there are good reasons to mistrust this result. The U5MR, on the other hand, suffers less from the age-speciic problems mentioned above. Moreover, the level of 91 deaths before reaching age 5 per thousand live births is well in line with results found in the MICS 2010 and the AMS 2010 respectively 102 and 97 2 , given time progressed, the 2007-08 NRVA benchmark of 161 death per thousand live births and sampling conidence intervals. Whereas, as expected, the IMR of boys is higher than that of girls 49 compared to 46 per thousand live births, the U5MR of girls is higher than that of boys: 92 against 89 per thousand live births. 2 Referring to the AMS estimate based on the Brass methodology and excluding the South zone, as this was considered the most reliable result. ALITY ESTIMA TION Table VI.2 Estimation of probability of dying and associated reference date, by sex a. Both sexes Womans age Index i Number of women Children ever born CEBi Parity Pi Children deceased CDi Proportion deceased Di Multiplier ki Age of children x Probability of dying before x qx Time of estimate ti Reference date Ti 15-19 1 1,460,995 218,977 0.1499 8,959 0.0409 1.1644 1 0.0476 0.9 2011.0 20-24 2 1,104,892 1,487,378 1.3462 124,592 0.0838 1.0843 2 0.0908 2.1 2009.9 25-29 3 994,606 3,151,085 3.1682 243,129 0.0772 1.0147 3 0.0783 3.9 2008.0 30-34 4 717,773 3,330,199 4.6396 297,055 0.0892 1.0165 5 0.0907 6.2 2005.8 35-39 5 638,012 3,767,540 5.9051 389,761 0.1035 1.0316 10 0.1067 8.7 2003.2 40-44 6 479,266 2,990,814 6.2404 342,509 0.1145 1.0172 15 0.1165 11.5 2000.5 45-49 7 361,014 2,258,664 6.2564 288,637 0.1278 1.0110 20 0.1292 14.4 1997.5 Total 5,756,558 17,204,657 1,694,642

b. Boys

Womans age Index i Number of women Boys ever born CEBi Parity Pi Boys deceased CDi Proportion deceased Di Multiplier ki Age of boys x Probability of dying before x qx 15-19 1 1,460,995 114,550 0.0784 4,701 0.0410 1.2014 1 0.0493 20-24 2 1,104,892 831,131 0.7522 73,807 0.0888 1.0821 2 0.0961 25-29 3 994,606 1,669,676 1.6787 120,492 0.0722 1.0045 3 0.0725 30-34 4 717,773 1,736,824 2.4197 154,463 0.0889 1.0050 5 0.0894 35-39 5 638,012 1,962,847 3.0765 198,577 0.1012 1.0191 10 0.1031 40-44 6 479,266 1,574,643 3.2855 171,955 0.1092 1.0042 15 0.1097 45-49 7 361,014 1,249,179 3.4602 148,293 0.1187 0.9984 20 0.1185 Total 5,756,558 9,138,850 872,288

c. Girls

Womans age Index i Number of women Girls ever born CEBi Parity Pi Girls deceased CDi Proportion deceased Di Multiplier ki Age of girls x Probability of dying before x qx 15-19 1 1,460,995 104,427 0.0715 4,258 0.0408 1.1201 1 0.0457 20-24 2 1,104,892 656,247 0.5939 50,785 0.0774 1.0864 2 0.0841 25-29 3 994,606 1,481,409 1.4894 122,637 0.0828 1.0262 3 0.0849 30-34 4 717,773 1,593,375 2.2199 142,592 0.0895 1.0298 5 0.0922 35-39 5 638,012 1,804,693 2.8286 191,184 0.1059 1.0460 10 0.1108 40-44 6 479,266 1,416,171 2.9549 170,554 0.1204 1.0321 15 0.1243 45-49 7 361,014 1,009,485 2.7962 140,344 0.1390 1.0254 20 0.1426 Total 5,756,558 8,065,807 822,354