Early age at marriage for women – and early widowhood – is closely related to the practice of polygamy, as a polygamous marriage market creates an unequal demand for male and female spouses. The NRVA data indicate that around 6 percent
of married women some 256 thousand are in union with a husband who has more than one wife. The incidence of polygamous marriages is higher over 10 percent among Kuchis and lower around 4 percent in the urban population.
The NRVA data also allows the observation of significant social change in marriage patterns. Whereas on average in the older age group 60-69 husbands are more than eight years older than their wives, this age difference consistently
declines to five years in the age group 15-24. Figure 3.4 shows that the share of couples with relatively small spousal age differences less than four years has dramatically increased for each younger age group of women from 16 percent
among women age 70 and over to 54 percent of those under 20. At the same time, the shares of couples with large 10-19 years and very large 20 years or more age differences has similarly declined from 47 percent in the oldest age
group to 12 percent in the youngest. This development toward a more balanced age pattern between spouses is likely to contribute to women’s empowerment within marriage and the family see also Section 10.2.1.
With respect to the female age at first marriage, a noticeable decline of very early marriages can be observed. Whereas the 30-34 age cohort reported 11 percent of marriages contracted before reaching age 15, this has steadily declined to
around three percent for the 15-19 age group. The percentage of women married before age 18 and 20 declined from, respectively 45 and 66 percent to 39 and 60 percent between the 30-34 and 20-24 age cohorts.
As can be observed in Figure 3.4, the cohort-related pattern of increasing spousal age difference by age seem to be curbed in the age group of over-70. At the same time the share of women with younger husbands is significantly larger
in this group. This phenomenon can be explained by the excess mortality of husbands who are much older, but probably also by the incidence of levirate marriage, a practice especially prevalent in the Pashtun population, whereby a widow is
required to marry a – possibly younger – relative of her late husband.
Figure 3.4 Spousal age difference, by current age of wife percentage distribution
3.4 Fertility and mortality
3.4.1 Total Fertility Rate
High fertility tends to increase poverty by slowing per capita economic growth and by skewing the distribution of consumption against the poor. It also has adverse effects to the health of mothers and children, and reduces female access to education,
gainful employment and other personal development opportunities. The determinants and compounding factors of high fertility are many, but generally include poor health services especially related to information about and provision of
family planning, limited knowledge of contraceptive methods cf. MRRD-CSO 2007
2
, low contraceptive prevalence see section 8.4.1 of this report, low education and limited empowerment of women see Section 10.2.1 on reproductive
decision making in the household. The Total Fertility Rate TFR was added to the Afghan Millennium Development Goals MDGs because of the particular importance of high fertility to Afghanistan Government of Afghanistan 2009.
__________________________________________________________________________________________ 2
The NRVA 2005 indicated that only 31 percent of married women had heard about methods to avoid pregnancies.
Population structure and change
15
Population structure and change
16
As noted in the box titled, “Quality of age reporting” in Section 3.2.1, reporting of ages is notoriously inaccurate in Afghanistan, and up to one million children may be erroneously omitted from estimates of the total Afghan population
derived from the NRVA survey. Therefore, caution must be used in interpreting estimates of fertility derived from the survey. For this reason, more than one method was used to calculate fertility to estimate a range of plausible fertility rates
for a detailed description of the applied methods, refer to Annex III.
The first method calculated fertility directly from information on recent deliveries since August 2005 and included a
correction for unreported births of children who later died. Table 3.5 indicates that for the full period from August 2005
until September 2008, the directly calculated Total Fertility Rate is 5.3 live births per woman column 2. Fertility rates in
the period since February 2007 were lower than the period up to then, suggesting that fertility rates have declined in the last
three years across all age categories.
Table 3.5 Fertility estimates
Mean Parity Fertility Rates
Age Indirect method, adjusted
Direct method 4
3 2
1 0.118
0.122 0.103
15-19 1.354
0.308 0.259
20-24 3.293
0.300 0.253
25-29 4.963
0.246 0.207
30-34 6.278
0.159 0.134
35-39 7.023
0.073 0.061
40-44 7.274
0.045 0.038
45-49 6.266
5.274 TFR
In an indirect method of fertility estimation, the age-specific fertility rates found by application of the direct method are reconciled with the level of fertility indicated by the average parity – the number of children born to a woman – of young
women. This procedure combines information about the observed age pattern of fertility with information that likely most accurately indicates the level of fertility, resulting in fertility rates that may be more reliable than either of the constituent
data components United Nations 1983, p. 33.
Application of the indirect method – in more detail described in Annex III – yields adjusted age-specific fertility rates as reported in Table 3.5 column 3, and a corresponding adjusted TFR of 6.27. While it is impossible to determine which
is the most accurate estimate of the total fertility rate in Afghanistan, given data quality issues and limitations in the estimation methods, it is most likely that the current overall TFR is close to 6. Therefore, we propose the current estimate
of TFR in Afghanistan is the adjusted rate of 6.27 over the last three years.
The calculation by age group of the ratio between average parity and ‘estimated parity equivalents’ derived from the direct approach provides an opportunity to identify recent fertility change. If this ratio increases with age, it is likely that
recently fertility has declined. Apparently, this is the case for Afghanistan see Table A.III.3 in Annex III. Fertility decline can also be deduced directly from parity information in Table 3.5 column 4 if the suggested TFR of 6.27 is compared
with the average parity of women aged 40-44 and 45-49. These women have nearly completed their reproductive careers and their parity is a measure of fertility in the past. The difference of around 0.9 with the current TFR is noticeable, but
relatively modest.
In international perspective, Afghan fertility is extremely high. Estimates of Afghanistan’s TFR by the UN Population Division amounted to 7.03, implying the third-highest fertility in the world after Niger 7.16 and Guinea-Bissau 7.04
Total Fertility Rate
The Total Fertility Rate TFR is a synthetic indicator and refers to the number of live births a woman could expect
to have during her reproductive years if she followed the levels of fertility currently observed at every age. The TFR is
calculated as the sum of average annual age-specific fertility rates for all reproductive age groups 15-49 in the three
years before the survey.
UNFPA 2008. The present – better evidence-based – NRVA estimate of 6.27 suggests a somewhat lower TFR, but still only ten countries rank higher in the UN list.
Within Afghanistan fertility is higher in rural areas with a TFR of 6.49 compared to urban ones 5.25, and highest among the Kuchi population, whose women have on average more than seven live births over the course of their lifetimes
see Table 3.6a. Education is also related to fertility levels, and women with primary schooling have on average one
fewer lifetime birth than women with no schooling a TFR of 5.49 compared to 6.53. Those with secondary schooling and college education have the lowest fertility levels, with an average of only four births during their lifetimes.
Table 3.6 Total Fertility Rate, by a residence, and b educational level of mother
a. Residence TFR
b. Education TFR
Urban 5.25
None 6.53
Rural 6.49
Primary 5.49
Kuchi 7.28
Secondary 4.01
College 4.10
Total 6.27
Total 6.27
The negative impact of high fertility and frequent or ill-timed pregnancies on maternal and child health and mortality is well documented. So is their effect on a variety of other development issues, including environmental degradation,
poverty at macro-economic level, as well as at levels of the community and family, malnutrition, and low educational attendance and attainment Moreland and Talbird 2006, UN Millennium Project 2006, World Bank 2007, Eastwood and
Lipton 2001. Consequently, progress on achieving many MDGs depend on addressing fertility in the implementation of Afghanistan’s development policies, particularly by reducing mortality, increasing education and improving access to
health services, especially those related to reproductive health and family planning.
3.4.2 Child mortality estimates
Infant- and under-five mortality rates are important factors in the explanation of natural population increase and are by far
the most important contributors to low life expectancy in most developing countries. In connection with this, they are also
among the most revealing indicators of the health status of a population and the functioning of a country’s health system.
The NRVA 20078 survey included an abbreviated birth history and child mortality section, as part of the women’s questionnaire. This section asked ever-married women of reproductive age about any births during their lifetimes, and
about their total number of children currently alive, as well as those dead, by sex. A full methodological elaboration is provided in Annex IV to this report.
Sources of error in mortality estimates
Annex IV discusses several sources of error that must be considered when calculating child mortality estimates for Afghanistan from a household survey. One of these related to reporting problems concerning the sex of the child. The
natural sex ratio at birth has been found in most settings to be approximately 105 boys for every 100 girls, and the most extreme estimates range from 104 to 107 boys per 100 girls Dubuc and Coleman 2007. As can be seen in Annex Table
A.III.2, the ratio of boys ever born to girls ever born is well above 1.05 for all age groups, at an average of 1.10. The ratio is particularly high among the younger age groups of women.
Sex ratios at birth that are highly skewed can be found in societies with a preference for sons, such as India and China, and may be due to sex-specific feticide. However, although there may be a preference for sons in Afghanistan, none
of these considerations can plausibly explain the too-high sex ratio at birth. The skewed ratio is most likely resulting from one or both of two phenomena: intentional misclassification of girls as boys e.g., due to the perceived 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 Ministry of Public Health 2008. The former would affect sex-specific mortality ratios, but not the
overall mortality ratio, while the latter would likely affect female mortality ratios as well as the overall mortality ratio.
Population structure and change
17
Infant- and Under-five Mortality Rate
The Infant Mortality Rate IMR is defined as number of deaths
to children under twelve months of age per 1,000 live births. The
Under-ive Mortality Rate U5MR relates to the number of deaths to children under five years of age per 1,000 live births.
