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education, water and sanitation supply, labour force, child labour and maternal health care are aligned with international practices. In addition, for internationally agreed indicators, and especially MDG indicators,
ALCS applies the standard conceptualisation and definitions. Therefore, many indicators produced in this report embody a high level of international comparability. The report text indicates if, for some reason,
applied definitions deviate from the internationally recommended ones. The annex with concepts and definitions provides the specifications applied in the present analysis Annex VIII.
Due to changes in national and international definitions and guidelines, as well as lessons learned in the history of ALCS and specific data limitations, some indicators in the present report are not directly
comparable to those in previous reports. These notably include the following:
Labour-market indicators: the abbreviated labour module of NRVA 2011-12 introduced a specific bias that prohibits a direct comparison with ALCS 2013-14. Also NRVA 2007-08 had specific
limitations that hamper straight comparison. However, chapter 5 includes a section that re-aligns NRVA 2007-08 data with ALCS 2013-14 in order to produce a trend indication.
In order to align with national and international definitions of improved sanitation, ALCS adopted a new classification. Consequently, the sanitation indicator presented in this report cannot be
compared with those in previous reports. However, the information gap for trend analysis is bridged by producing the indicator according to the new and old definition.
The difference in methodology to estimate food security between ALCS 2013-14 and previous NRVAs does not allow direct comparison.
2.11 Data limitations
The specific constraints in the Afghanistan context in terms of security problems, cultural barriers and local survey capacity induced some data limitations. The following observations should be taken into account
when interpreting the results in this report: In 152 out of 2,100 clusters 7.2 percent, originally sampled clusters could not be covered, in most
cases due to security reasons. For 148 of these cases, clusters were replaced. To the extent that the non- visited clusters may have profiles different from visited clusters, the final sample will give a bias in the
results. This effect will have been larger at the provincial level for provinces with relatively large numbers of replacement, such as Ghazni, Helmand and Badakhshan.
Analysis of the population structure by sex and age shows under-enumeration of women and girls, as well as young children in general, especially infants. Coverage of the youngest age group was much
better than in previous surveys, but significant numbers are still omitted. Cultural backgrounds related to the seclusion of women and high infant mortality are among likely reasons for these omissions.
The quality of age reporting in the Afghan population remains extremely poor, as indicated by large age heaping on ages with digits ending on 5 and 0.
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Due to alleged security problems, work by female interviewers in Zabul was not allowed by the authorities. Consequently, the information on general living conditions, maternal- and child health, and
gender is largely missing for this province. However, the food-security and child-labour modules in the female questionnaire were completed by male interviewers interviewing male respondents.
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The Myers Blended Index is 21.8 and the Whipples Index is 231.
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2.12 Reporting
The source of all information presented in this report is the ALCS 2013-14, unless otherwise specified. Presenting information from other sources than ALCS does not imply an endorsement by CSO, but should
merely be interpreted as a contextualisation of the present findings. Titles of tables presented in this report follow a standard convention to exactly define the table contents and
structure: first, the title states the universe of elements presented in the table, then it defines the variables presented in the column headings, then the variables presented in the row headings. In the title the universe
and the column variables are separated by a comma ‘,’; the column variables and the row variables
are separated by ‘, and by’. Titles of line and bar charts first specify the universe of elements presented in the figure, then the variable presented on the main axis, and then the variable presented in the legend if
any. When presenting rounded figures in tables or graphs, the presented total figure may not correspond to the sum of rounded figures.
In comparison to the report on the previous survey NRVA 2011-12, this report is enriched with a larger number of thematic maps, to provide more information on the geographical distribution of indicators at
provincial level, and to help the reader to quickly understand demographic and socioeconomic patterns across the country, as evinced by 2013-14 ALCS data. Indeed, maps are used not only for dissemination
purposes, but also to indicate spatial correlations, proposing further investigation in some subjects and geographical areas of the 2013-14 ALCS results.
Maps were prepared using Geographic Information System GIS software in which selected indicators of ALCS data were associated with their corresponding administrative units of the country, and presented with
different colours and gradients on the basis of their values registered at provincial level. The statistical method of data classification was the standard Jenks method called also
‘Natural breaks’ method. Class breaks were defined in order to maximise differences in data values between classes. A minimal
customisation was applied to round class breaks and to show in the legend the national average of the indicators presented at national level. An explanatory note was added below the legend when deemed
necessary to explain the mapped data. In order to allow the reader further insight into the value of the presented data, an annex Annex VII is
added to the report on quality assurance and quality assessment. For the ANDS and MDG indicators presented in this report, an overview of standard errors and 95 percent confidence limits are included in this
annex.
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3 POPULATION AND HOUSEHOLDS
Summary . The population of Afghanistan is characterised by a very young age structure. The proportion
of 47.5 percent of the population under age 15 is one of the highest in the world. This young age structure, driven by very high fertility, is the main component of the high dependency ratio of one dependent per
person in the most productive ages 15 to 64. The large number of young people pose formidable challenges to various sectors of society. In five years time there will be more than 5.5 million children of primary
school age, while presently the education system offers primary education to only 2.9 million children of this age. Similarly, in these next five years close to 4 million youth will reach working age in a labour
market that is already characterised by high levels of unemployment and underemployment. The typical pyramid shape of A
fghanistan’s population ensures that population growth will remain high for several decades.
The sex ratio by age shows a very a-typical pattern. Instead of a situation where at older age women tend to become more numerous compared to men, the opposite is observed in Afghanistan. Beyond age 70 men
outnumber women by 170 to 100. Likely explanations for this can be found in underreporting of women and high maternal mortality. Both causes reflect the vulnerable position of women in society.
The vulnerable position of women and gender inequality is also witnessed in specific marriage patterns. A sizable number of 388 thousand married women live in polygamous marriages, which places them in a
disadvantaged position. Polygamy also increases the age gap between spouses, which is again disadvantageous for women. However, a positive trend towards a smaller age gap can be observed. For
married women aged 40 and older, the age of the husband is on average more than 7 years higher, but for women aged 15 to 29, the difference is reduced to 4.6 years. Also the proportion of couples with a spousal
age gap of 10 years or more has declined from 36 percent among women 50 years and over, to 8 percent among women under 20.
A major issue of concern is the large share of child marriages in the country. The ALCS 2013-14 indicates that 34percent of female youth aged 20-24 were already married at age 18, the age that distinguishes child
marriage. Some 12 percent of these women were even already married at age 16, which is legally the minimum age at marriage. At the positive side, these high figures for marriage at a young age imply an
improvement compared to older women who married in an earlier period. Thus, more than 50 percent of women 30 and older were married at age 18 and more than 23 percent of them were even married at age
16.
The average household size in Afghanistan is 7.4 persons, of whom on average 3.5 persons – 48 percent –
are children under fifteen. On average, only one in five households has an elderly member of 65 years of age or older. Close to half the Afghan people live in households with nine or more household members.
Households with just one or two persons make up 3.5 percent of all households, but the share of the population that lives in these small households is less than 1 percent. The households are almost exclusively
headed by men. Female-headed households are only one percent of the total number.
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3.1 Introduction
