understanding vulnerability of afghans with disability - Handicap ...

Islamic Republic of Afghanistan 

UNDERSTANDING VULNERABILITY 

OF AFGHANS WITH DISABILITY 

LIVELIHOODS, EMPLOYMENT, INCOME 

NATIONAL DISABILITY SURVEY IN AFGHANISTAN 

2005

UNDERSTANDING VULNERABILITY 

OF AFGHANS WITH DISABILITY 

LIVELIHOODS, EMPLOYMENT, INCOME 

NATIONAL DISABILITY SURVEY IN AFGHANISTAN 

2005 

Definition and Context 

i

© Handicap International 2006 

ISBN : 978-2-909064-78-9 

Authors 

Parul Bakhshi, parulbakhshi@yahoo.com 

Jean-François Trani, jftrani@yahoo.fr 

Contributions from Jean-Luc Dubois jldubois@aol.com 

Editing, design and printing 

New Concept Information Systems Pvt. Ltd. 

New Delhi, India 

Published by 

Handicap International 

14, Avenue Berthelot 

69361 Lyon Cedex 07, France 

Tel +33 (0) 4 78 69 79 79 

Fax +33 (0) 4 78 69 79 94 

email: contact@handicap-international.org 

www.handicap-international.org 

Photographs 

Handicap International Afghanistan Programme 

House No. 133 

Qala-e-Fatullah, 5th street, 

Kabul, Afghanistan

Contents 

Acknowledgements 

Abbreviations 

Preface 

Executive Summary 

Introduction 

x 

xi 

xii 

xiii 

xiv 


A Few Definitions 1 

What is Poverty? 1 

From Vulnerability to Poverty: Facing Risk and Enduring Shocks 1 

Livelihood, Poverty and Disability from a Global Perspective 3 

Poverty and Disability in Afghanistan 3 

Poverty from a Gender Perspective 3 

Gathering Data for Poverty Analysis of a Small Population 

Group: a Major Challenge 4 

Poverty of Living Conditions: Identifying Benchmarks 

Inequality in the Access to Basic Goods 5 

Diffi cult Access to Drinking Water 5 

Sources of Light: Paucity of Resources 7 

Energy for Cooking: the Massive Use of Firewood a Cause for Concern? 9 

Access to Modern Toilet Facilities: a Benchmark for Wealth? 10 

Standards of Living: Main Features 10 

Size of Houses and Size of Households: Over Crowded Living Spaces 10 

Supply and Access to Food: Insuffi cient Quantity, Lack of Diversity 14 

Activity and Income: Struggling for Survival 17 

Activity and Unemployment in an Economy under Reconstruction 17 

Major Characteristics of the Labour Force and Market 18 

Activity and Disability 24 

Less Child Labour in Afghanistan? 26 

High Inequality of Income in Afghanistan 29 

Comparing Income of Persons with Disability and Non-Disabled 32 

Concluding Remarks 33 

Fewer Assets for Persons with Disability: a Vulnerability 

Issue 

Durable Goods: Relative Indicators of Well-Being 35 

Equipment of the House and Common Goods: Benchmarks for Wealth 35

Widespread Ownership of Livestock 38 

Land Ownership: Do Households of Persons with Disability have Smaller Land Holdings? 42 

Concluding on Durable Goods: Fighting Poverty in a Comprehensive Manner 44 

Debt and Donation: Assets or Factors of Vulnerability? 45 

Resort to Loan and Level of Debt: Higher for Persons with Disability 45 

Concluding on Borrowing Practices: Risk Factor or Capability Asset? 56 

Income through the Social Network: the Social Income 56 

Concluding on Social Income 58 

General Conclusions 

Disability: a Dormant Factor? 59 

Urban or Rural Settings: an Expected Difference 59 

Female-headed Households: the most Vulnerable 

and the Poorest 59 

Access to the Labour Market: a Matter of Perception 60 

The Way Forward: Mainstreaming, Empowerment, 

Participation of Persons with Disability 60 

Bibliography 61 

Annexure 63 

Tables Related to Water Supply 63 

Tables Related to Light Supply 65 

Tables Related to Cooking Energy Supply 67 

Tables Related to Toilet Facilities 68 

Tables Related to Housing 69 

Tables Related to Food Supply 71 

Tables Related to Activity and Employment 73 

Tables Related to Income 82 

Tables Related to Durable Goods 83 

Tables Related to Livestock Ownership 86 

Tables Related to Land Ownership 92 

Tables Related to Debt 95 

Tables Related to Social Income 103 

iv 

Understanding Vulnerability of Afghans with Disability

Lst of Tables 

Table 1. Distribution of Households according to Location and Gender of the 

Head of the Household 4 

Table 2. Distribution of Households of Persons with Disability and the Non-Disabled 

according to the Gender of the Head of the Household 4 

Table 3. Average Ratio of Number of Members by Room and Number of Household 

Members according to the Number of Rooms in the House 12 

Table 4. Distribution of Active People by Main Professions 22 

Table 5. Distribution of Active People by Sectors of Activity 23 

Table 6. Activities of Children Aged 6 to 14 28 

Table 7. Gini Coeffi cient for Income from Activity 30 

Table 8. Poverty and Inequality in the South Asia Region 30 

Table 9. Ownership of Livestock: Comparing NRVA 2003 and NDSA 2005 41 

Table 10. Gini Coeffi cient of Land Ownership 44 

Table 11. Average Amount of Loan for Urban and Rural Households 49 

Table 12. Distribution of Households according to the Location of Drinking Water 63 

Table 13. Distribution of Households according to the Time Needed to Fetch Drinking Water 63 

Table 14. Distribution of Households according to Types of Water Supply Available 64 

Table 15. Distribution of Households according to Location of Drinking Water in 

Urban and Rural Areas 64 

Table 16. Distribution of Households according to Location of Drinking Water Available in 

Urban and Rural Areas and Gender of the Head of Household. 65 

Table 17. Distribution of Households according to Sources of Light Supply Available 65 

Table 18. Distribution of Households according to Sources of Light Supply Available 

in Urban and Rural Areas 66 

Table 19. Distribution of Households according to Gender of the Head of the Household and 

Sources of Light Supply Available 66 

Table 20. Distribution of Households according to Sources of Energy for Cooking 67 

Table 21. Distribution of Households according to Sources of Energy for Cooking in 

Urban and Rural Settings 67 

Table 22. Distribution of Households according to Access to Types of Toilet Facilities 68 

Table 23. Distribution of Households according to Access to Types of Toilet Facilities in 


Table 24. Distribution of Households by Number of Rooms in the House 69 

Table 25. Distribution of Number of Household Members and Number of 

Rooms in the House 69 

Table 26. Distribution of People according to Number of Rooms in the House by 


Table 27. Distribution of Households according to Gender of the Head of the Household 

by Number of Rooms in the House 70 

Table 28. Distribution of Households according to Sources for Supply of Food 71 

Table 29. Distribution of Households in Urban and Rural Areas according to 

Sources of Supply of Food 71 

Table 30. Distribution of Households according to Suffi ciency of Food 72 

Table 31. Distribution of Households in Urban or Rural Settings according to 

Suffi ciency of Food 72 


and Suffi ciency of Food 73 

Table 33. Distribution of Persons with Disability and Non-disabled Aged 15-64 

according to the Employment Situation 73 

Table 34. Distribution of Household according to the Ratio of Employed Members 74 

Contents 

v

Table 35. Distribution of Persons with Disability and Non-Disabled Aged 15-64 

according to Employment Situation and Gender 74 

Table 36. Distribution of Persons with Disability and Non-Disabled Between 

14 and 65 according to Employment Situation and Gender 

(analysis on series of questions) 75 

Table 37. Distribution of People Above 14 according to Employment Situation 

Gender and the Situation in the Household 75 

Table 38. Distribution of People according to Profession 76 

Table 39. Distribution of Persons with Disability and Non-Disabled Above 14 

according to Activity Status 77 


according to Farmer Status 78 

Table 41. Distribution of Persons with Disability and Non-Disabled 

Age 15-64 according to Diffi culties Faced in the Workplace 78 

Table 42. Distribution of Children with Disability and Non-Disabled Children 

Aged 7 to 15 according to Activity and Gender 79 


Aged 7 to 15 according to Time Spent in Household Tasks and Gender 79 


Aged 7 to 15 according to Types of Household Tasks and Gender 80 

Table 45. Distribution of Boys with Disability and Non-Disabled Boys 

Aged 7 to 15 according to Types of Field Work 81 

Table 46. Distribution of Boys with Disability and Non-Disabled Boys 

Aged 7 to 15 according to Types of Jobs 81 

Table 47. Monthly Activity Income of Active People 82 

Table 48. Distribution of Active Persons Aged 15-64 with Disability and 

Non-Disabled according to Monthly Professional Income 82 

Table 49. Distribution of Active Males Aged 15-64 with Disability and Non-Disabled 

according to Monthly Professional Income 83 

Table 50. Distribution of Persons with Disability and Non-Disabled Living in 

Households Possessing the Following Goods 83 

Table 51. Distribution of Households Possessing the Following Goods and Equipments 84 

Table 52. Distribution of Households according to the Ownership of Goods 

and Equipments by Urban and Rural Settings 85 

Table 53. Distribution of Households according to Gender of the Head of the Household and 

Ownership of Goods and Equipments 86 

Table 54. Distribution of Persons with Disability and Non-Disabled Living in 

Households Possessing Livestock 86 

Table 55. Distribution of Households according to Ownership of Livestock 87 

Table 56. Distribution of People in Urban and Rural Areas Living in Households 

Possessing Livestock 87 

Table 57. Distribution of People according to Gender of the Head of the Household 

and Possession of Livestock 87 

Table 58. Distribution of Households of Persons with Disability and Non-Disabled 

according to Ownership of Livestock by Type of Animals 87 

Table 59. Distribution of Households according to Ownership of Different Types of Animals 89 

Table 60. Distribution of People according to Gender of the Head of the Household and 

Ownership of Animals by Types of Animals 91 

Table 61. Distribution of Households according to Ownership of Land 92 

Table 62. Distribution of Persons with Disability and Non-reporting Ownership of Land 92 

Table 63. Distribution of Household according to Ownership of Land by Urban 

and Rural Areas 93 

vi 



and Ownership of Land 93 


and Personal Ownership of Land 93 

Table 66. Distribution of Households according to the Size of the Land 93 

Table 67. Distribution of Households according to the Size of the Land which is Cultivable 94 

Table 68. Distribution of Households according to Gender of the Head of the Household and the 

Size of the Land of the Family 94 


and to the Size of the Land of the Family which is Cultivable 95 

Table 70. Distribution of Persons with Disability and Non-Disabled Above 14 Having 

Taken a Loan in the Last 5 Years according to Activity 95 

Table 71. Distribution of Persons with Disability and Non-Disabled above 14 Having 

Taken a Loan in the Last 5 Years according to Gender and Age 96 


Taken a Loan in the Last 5 Years according to the Area of Living 96 

Table 73. Distribution of Persons with Disability and Non-Disabled Above 14 Having Taken 

a Loan in the Last 5 Years according to Major Geographical Areas 97 

Table 74. Distribution of Persons with Disability and Non-Disabled above 14 according 

to Amounts of Loans 97 


to Amounts of Loans and Age Groups 98 


to Amounts of Loans and Gender 98 


to Amounts of Loans and Living Area 99 


to the Level of Debt 99 


to the Level of Debt by Age Group 100 


to the Level of Debt by Gender 100 

Table 81. Distribution of Persons with Disability and Non-disabled Above 14 according 

to the Level of Debt by Living Area 101 


to the Level of Debt and the Situation of Activity 101 


to the Purpose of Loan 102 


to the Money Lender 102 

Table 85. Distribution of Persons with Disability and Non-Disabled above 14 

Having Received Money according to Gender 103 


Received Money according to Donors 103 


Received Money according to the 3 Main Donors 104 


Received Money according to Donors and Gender 104 


Received Money according to Amounts 105 


Received Money according to Amounts and Gender 105 

Contents 

vii

List of Figures 

Figure 1. Distribution of Persons and Households Having Easy Access to Drinking Water 6 

Figure 2. Distribution of Households according to the Time Needed to Fetch Drinking Water 6 

Figure 3. Distribution of People according to the Time Needed to Fetch Water in 

Urban/Rural Areas 7 

Figure 4. Distribution of Household according to Sources of Light 8 

Figure 5. Distribution of Households according to Main Source of Light in Urban 


Figure 6. Distribution of Households according to Main Source of Light and Gender 

of the Head of the Household 8 

Figure 7. Distribution of Households according to Sources of Energy used for Cooking 9 

Figure 8. Distribution of Households according to Main Source of Energy for Cooking 

in Urban and Rural Settings 9 

Figure 9. Distribution of Households according to Access to Types of Toilet Facilities 10 

Figure 10. Distribution of Households according to the Number of Rooms in the House 11 

Figure 11. Distribution of People according to the Number of Rooms in the House and 

the Size of the Household 12 

Figure 12. Lorenz Curve of the Ratio of Number of Members by Room 13 

Figure 13. Distribution of People according to the Number of Rooms in the House by 


Figure 14. Distribution of People according to Gender of the Head of the Household and 

Number of Rooms in the House 14 

Figure 15. Distribution of Households regarding Sources for Supply of Food 14 

Figure 16. Distribution of Households Regarding Sources of Supply of Food in 

Urban and Rural Areas 15 

Figure 17. Distribution of Households regarding Amount of Food Available 16 

Figure 18. Distribution of People in Urban and Rural Areas regarding Amount 

of Food Available 16 

Figure 19. Distribution of People according to Gender of the Head of Household and 

Supply of Food 17 

Figure 20. Distribution of All Afghans Above 14 according to the Employment Situation 19 

Figure 21. Distribution of Persons Above 14 according to the Employment Situation 19 

Figure 22. Distribution of Households according to the Employment Ratio 20 

Figure 23. Distribution of Persons Aged 15-64 according to the Employment 

Situation and Gender 20 

Figure 24. Level of Employment Considering Additional Activities 21 

Figure 25. Distribution of Active People above 14 by Employment Status 22 

Figure 26. Distribution of Farmers by Types of Status 24 

Figure 27. Distribution of Active People by Types of Diffi culties Faced in the Workplace 25 

Figure 28. Distribution of Active Disabled and Non-Disabled Persons by Types of 

Diffi culties Faced in the Workplace 26 

Figure 29. Distribution of Children Between 7 and 14 Years Old according to 

Employment Situation 27 

Figure 30. Distribution of Afghan Children Between 7 and 14 Years Old according 

to the Activity Situation 27 

Figure 31. Distribution of Children Between 7 and 14 Years Old according to 

the Employment Situation 28 

Figure 32. Distribution of Monthly Activity Income for All Active People and Aged 15-64 31 

Figure 33. Distribution of Monthly Activity Income for Active Males Aged 15-64 31 

Figure 34. Distribution of Active Persons according to the Monthly Professional Income 32 

Figure 35. Distribution of Active Men above Aged 15-64 according to the Monthly 

Professional Income 32 

Figure 36. Distribution of Households regarding Ownership of Goods or Equipment 36 

viii Understanding Vulnerability of Afghans with Disability

Figure 37. Distribution of People Regarding Possess of Goods or Equipment in Urban 


Figure 38. Distribution of Households according to Gender of the Head of the Household 

for Ownership of Goods or Equipment 38 

Figure 39. Distribution of Households according to the Ownership of Livestock 39 

Figure 40. Distribution of Households according to the Gender of the Head of the Household 

and the Ownership of Livestock 40 

Figure 41. Distribution of Households regarding Ownership of Livestock in Urban and 

Rural Areas 41 

Figure 42. Distribution of Households regarding Ownership of Land 42 

Figure 43. Lorenz Curves of Land Ownership Inequalities 43 

Figure 44. Distribution of Persons with Disability and Non-Disabled Above 14 

with Loans Taken since 5 Years according to Situation of Activity 46 

Figure 45. Distribution of Persons with Disability and Non-disabled Above 14 

according to the Amount of Loans and Age Groups 46 

Figure 46. Distribution of Persons with Disability and Non-Disabled Above 14 with 

Loan Taken since 5 Years according to Gender 47 

Figure 47. Distribution of Persons with Disability and Non-Disabled Above 14 with Loan 

Taken since 5 Years according to the Area of Living 47 

Figure 48. Distribution of All Afghans Above 14 according to the Amount of Loans 48 

Figure 49. Distribution of Persons with Disability and Non-Disabled Above 14 according 

to the Amount of Loans 48 

Figure 50. Distribution of Persons with Disability and Non-disabled Above 14 according 

to the Amount of Loans and Age Group 49 


to the Amount of Loans and Gender 50 


to the Amount of Loans and the Living Area 50 

Figure 53. Distribution of All Afghans Above 14 according to the Amount of Debt 51 


to the Level of Debt and the Age Group 51 


to the Level of Debt and the Age Group 52 

Figure 56. Distribution of Persons with Disability and Non-Disabled Above 14 according to 

the Level of Debt and Gender 52 


the Level of Debt and the Living Area 53 


the Level of Debt and the Situation of Activity 53 

Figure 59. Distribution of All People Above 14 Having Taken Loans according to Purpose of 

Loan 54 


to the Purpose of Loan 54 

Figure 61. Distribution of all People above 14 according to the Lender 55 


to the Lender 56 

Figure 63. Distribution of Persons with Disability and Non-Disabled Above 14 receiving 

Money according to Gender 57 


to the 3 Main Donors 57 

Figure 65. Distribution of Persons with Disability and Non-Disabled Above 14 by 

Amount of Money Received and Gender 58 

Contents 

ix

Acknowledgements 

Firoz Ali Alizada (HI) 

Elena M. Andresen (University of Florida) 

Parween Azimi (NPAD) 

Mario Biggeri (University of Florence) 

Federica Biondi (INTERSOS) 

Tania Burchardt (London School of Economics) 

Alberto Cairo (ICRC) 

Sonia Cautin (HI) 

Fiona Gall (SGAA) 

Flavio Comin (Sd Edmonds College, Cambridge University) 

Heather Dawson (HI) 

Elias Hameedi (Afghan Human Right Commission) 

Peter Hansen (JHU) 

Susan Helseth (UNMACA) 

Chris Lang (NPAD) 

Ashraf Mashkoor (MoPH, HMIS) 

Kim Mikenis (HI) 

Dan Mont (World Bank) 

Sue McKey (HI) 

Cécile Rolland (HI) 

Bjorn Schranz (HI) 

Arnault Serra Horguelin (UNAMA) 

Lorella Terzi (University of London) 

Frederic Tissot (French Embassy) 

Erik Vandissel (MoLSA/UNICEF) 

Peter Ventevogel (Health Net International) 

Lakwinder P Singh (JHU Team) 

The Government of Afghanistan 

Ministry of Martyrs and Disabled and Social Affairs 

Ministry of Public Health 

Central Statistics Offi ce 

Non Governmental Organisations 

Afghan National Association for the Deaf 

Aide Médicale Internationale 

Afghan Research and Evaluation Unit 

Agroaction 

Community Center for Disabled 

CHA, Coordination of Humanitarian Assistance 

Handicap International Belgium 

Healthnet International 

IAM, International Assistance Mission 

ICRC, International Committee of the Red Cross 

INTERSOS Humanitairan Aid Organization 

MADERA 

Medecins du Monde 

National Afghan Disabled Women Association 

National Association for Disabled of Afghanistan 

National Disability Union 

National Programme for Action on Disability 

People in Need 

Sandy Gall’s Afghanistan Appeal 

SERVE, Serving Emergency Relief and Vocational 

Enterprises 

Swedish Committee of Afghanistan 

UNICEF 

World Bank, Disability Unit 

We are grateful to our donors: 

The European Commission 

UNOPS/UNDP 

UNMAS (Volunteer Trust Fund) 

Ambassade de France 

Swiss Agency for Development and Cooperation 

A special thank you to the Monitor and Master Trainers, 

the 200 surveyors without whom this survey would never 

have been carried out and the families who accepted to 

answer the questionnaire. 

The NDSA team consists of: 

Jean François Trani, NDSA Manager 

Parul Bakhshi, Consultant 

Layla Lavasani, Regional Manager 

Steffen Schwarz, Regional Manager 

Jean-Luc Dubois, Scientifi c Advisor 

Dominique Lopez, Statistics Advisor 

x 


Abbreviations 

AFAs 

BPDS 

BPHS 

CDAP 

CDC 

CI 

CSO 

DPO 

EU 

GoA 

HA 

HDI 

HH 

HI 

Hrs 

ICRC 

INGO 

LSP 

MDG 

MICS 

Mins 

MMDSA 

MoPH 

MoWA 

MoPW 

MRRD 

NDC 

NDS 

NDSA 

NDF 

NEEP 

NGO 

NPAD 

NRVA 

NSP 

NVP 

PIP 

PNA 

PTSD 

PwD 

SQ. MT. 

TOT 

UN 

UNAMA 

UNDP HDI 

UNDP 

UNICEF 

UNOPS 

WHO 

Afghanis 

Basic Package of Disability Services 

Basic Package of Health Services 

Comprehensive Disabled Afghans’ Program 

Central for Disease Control 

Confi dence Interval 

Central Statistics Offi ce 

Disabled People Organization 

European Union 

Government of Afghanistan 

Hectare 

Human Development Index 

Household 

Handicap International 

Hours 

International Committee of Red Cross 

International Non Government Organization 

Livelihoods and Social Protection 

Millennium Development Goals 

Multi Indicators Cluster Survey 

Minutes 

Ministry of Martyrs, Disabled and Social Affairs 

Ministry of Public Health 

Ministry of Women’s Affairs 

Ministry of Public Works 

Ministry for Reconstruction and Rural Development 

National Disability Commission 

National Disability Strategy 

National Disability Survey in Afghanistan 

National Development Framework 

National Emergency Employment Programme 

Non Governmental Organization 

National Programme for Action on Disability 

National Risk and Vulnerability Assessment 

National Strategic Plan 

National Vulnerability Programme 

Public Investment Programme 

Preliminary Needs Assessment 

Post Traumatic Stress Disorder 

Persons with Disability 

Square Meter 

Training of Trainers 

United Nations 

United Nations Assistance Mission for Afghanistan 

United Nations Development Programme Human Development Index 

United Nations Development Programme 

United Nation’s Children’s Fund 

United Nations Offi ce for Project Services 

World Health Organization 

Abbreviations 

xi

Preface 

Like many other organisations working in the disability sector in Afghanistan over the last 20 years, at SGAA we have become 

progessively aware that the medical model of physical rehabilitation is not enough. Yes, it is tremendously satisfying to see a small 

girl with polio walk for the fi rst time with callipers in our workshop or to see a paraplegic propel himself home in his new wheelchair, 

or to watch a young, strong, amputee stride out of the door with his new prosthesis, completely independent once more. But mobility 

and physical rehabilitation are only the beginning. Increasingly over the years the disabled have been asking us to provide them 

training, employment opportunities and loans to start their own businesses and we have tried to meet some of these needs. Mobility 

can be solved relatively easily, but social and economic integration is a lifelong challenge for the majority of our disabled friends in 

Afghanistan. We need to support and lobby the Government of Afghanistan to draw up labour laws that encourage employment of 

the disabled and include provisions in other laws to make sure that the disabled are provided equal access to health, education, skills 

training and public life. 

As this report documents, lack of clean drinking water, insuffi cient food and low income are diffi culties faced by a majority of poor 

households in Afghanistan. Poverty is a great leveller and affects equally families with able members as it does families with a disabled 

member. The report notes that women-headed households are particularly vulnerable among the low income groups. Within a poor 

family the burden of a member with a disability can negatively affect the coping strategy of the family. It is also much harder and more 

diffi cult for the individual with a disability to be valued in the family if he or she cannot participate in many of the domestic chores 

or employment generating activities of the family. Yet, if a person with a disability can receive education or learn a skill this can help 

provide them a specifi c role in the family and wider social acceptance. We can see great examples of men and women with disabilities 

fi nding work and becoming the bread-winners in their families around us today in Afghanistan. 

With the information and recommendations from this third report in the NSDA series all of us engaged in development in Afghanistan 

can identify the main priorites that need to be followed to improve liveliehoods for the disabled and other vulnerable groups – 

empowerment, mainstreaming and equalisation of opportunities. 

Fiona Gall 

Project Consultant 

Sandy Gall’s Afghanistan Appeal 

xii 



The National Disability Survey in Afghanistan was carried out by Handicap International for the Ministry of Martyrs and Disabled and 

Social Affairs (MMDSA) and the Ministry of Public Health (MoPH) and with the support of the Central Statistics Offi ce (CSO) of the 

Ministry of Economics. This survey aims at: 

Evaluating the prevalence of disability; 

Developing a general typology of persons with disability; 

Evaluating the access to public services mainly educational, social and medical services for persons with disability; 

Gathering quality information in order to further defi ne policy priorities aiming at mainstreaming persons with disability, capability 

development, autonomy and social integration. 

The methodology applied is based on the following rules: 

A probabilities proportional to population size sampling procedure with a national wide sample of 5250 households (all 34 

provinces) using pre-census data to control the sample size of clusters (little size variation); 

A screening questionnaire of 27 questions to identify “diffi culties” in terms of ability/inability (avoiding direct simple questions on 

disability) with a large reference to ICF and Sen`s Capabilities Approach adapted to the Afghan cultural context; 

A one and a half month training (theoretical and practical) of the team of monitors/supervisors and a three weeks training of 

all surveyors on all disability issues, cluster household survey principles, the questionnaire, the sampling but also security and 

organisational problems. 

A test of all tools, especially the questionnaire (elaborated by specialists and reviewed by experts, Afghan organisations of persons with 

disability), in both rural and urban areas. 

The present third volume of the NDSA results looks more closely at employment, income and livelihoods of persons with disability. A 

common belief is that persons with disability, suffering from discrimination and exclusion, are unable to access existing resources and 

are more at risk of poverty than non-disabled people. This report aims at identifying the differences between households of persons 

with and without disability in terms of livelihoods, to understand in what ways or on which specifi c aspects are disabled people among 

the poorest of the poor in Afghanistan in particular, as it seems to be the case across the world in general. 

The main fi nding of this analysis is the fact that when considering situations of severe or chronic poverty, disability is more of a 

‘dormant’ factor. In other words, households of persons with disability are not signifi cantly worse off than non-disabled households in 

terms of livelihoods, commodities and assets. The factors that do seem to play an important role on livelihood indicators are the living 

settings (urban or rural) and the gender of the head of the household. However, disability does have an impact on the livelihoods of 

the more advantaged sections of society, suggesting that disability does come into play once the living situation improves. As a result, 

the households that have a person with disability may not be poorer at this point, but they are defi nitely more vulnerable in the long 

term. This in turn leads to believe that if policies and programmes are not set up in order to target this vulnerable group, then they will 

be left behind in the development effort. 


xiii

Introduction Message 

There is ongoing worldwide debate over what poverty means in terms of everyday life and how it impacts 

the individual and the community. Looking at poverty in solely monetary terms is not suffi cient for assessing 

the situation. In the past decade focus has shifted from looking at poverty in terms of income and assets 

to including other factors that impact quality of life. These may include health and education indicators as 

well as the social and family resources that a person can rely upon. Moreover, poverty must be looked at in 

the long term if sustainable development is the goal. This implies that not only should the focus be on the 

present situation of persons (with disability in this case), but also on indicators of how this situation is likely to 

evolve in the medium and long-term. Looking at these aspects entails giving attention to the vulnerability of 

individuals and groups, to their ability to draw on various resources in order to deal with the unpredictable, on 

their social resources and support systems. For persons with disability, this aspect is crucial in order to assess 

their quality of life, as well as to identify the mechanisms that already do exist for them to fall back upon and 

to strengthen these, along with defi ning ways to fi ghting poverty and vulnerability in the long-run. 

The present third volume of the NDSA results looks more closely at employment, income and livelihoods 

of persons with disability. A common belief is that persons with disability, suffering from discrimination and 

exclusion, are unable to access existing resources and are more at risk of poverty than non-disabled people. 

This report aims at identifying the differences between households of people with and without disability in 

terms of livelihoods, in order to better understand in what ways or on which specifi c aspects persons with 

disability are in fact not only one of the poorest groups in Afghanistan, but also one of the most vulnerable. 

This report on employment, income and living conditions is closely related to the notion of poverty, as well 

as that of vulnerability. Even though Afghanistan still continues to rank among the lowest on the Human 

Development Index (HDI), it is relevant to think about what forms rapid development will take and 

who might get left behind. In the last fi ve years, Afghanistan has been benefi ting from the support of the 

international community with the aim to build sustainable infrastructures and systems . Considerable efforts 

have been made to improve the economic situation, and worldwide attention is currently focused on what is 

happening in the country. 

However, there remain a few domains where these efforts seem not to have met the expectations of the 

population. Many voices are now raising only to underline the lack of effectiveness and achievements of 

the various partners working on disability, but also the lack of fi nancial commitment of the international 

community after half a decade of support. More Afghans are showing disappointment as violence has 

increased sharply and the capacity to provide better service and facilities, including school, health facilities, 

clean water, sanitation, roads, and electricity for the population, still leaves a lot to be desired. A holistic and 

comprehensive view of the situation is a pre-requisite to defi ning and implementing programs that will be 

accepted by the benefi ciaries. 

The fi ndings related to livelihoods and living conditions have a unique characteristic in the series of reports 

of the NDSA. Whereas other reports are based upon the ‘individual’ perspective and compare answers given 

by persons in different situations, this report is based on answers regarding the household, as a unit. Thus, 

xiv 


this report looks at the impact of disability, not just on the individual, but also on the family as a whole. How 

exactly does disability of one member weigh upon their living conditions; does it impact the livelihoods of the 

entire household? Wherever it is possible, results will be compared to those of NRVA 2003 

Foreword 

1 for which reports 

are available. In fact, some of the questions, notably about possession of assets, were voluntarily identical 

with the NRVA questions in order to make comparison over time possible. 

1 

VULNERABILITY ANALYSIS AND MAPPING UNIT OF THE WORLD FOOD PROGRAMME AND THE VULNERABILITY ANALYSIS UNIT 

OF THE MINISTRY OF RURAL REHABILITATION AND DEVELOPMENT (2004), Report on Findings from the 2003 National Risk and 

Vulnerability Assessment (NRVA) in Rural Afghanistan, December 2004, 123 p., http://www.mrrd.gov.af/vau/. 

Introduction 

xv


This fi rst section attempts to defi ne a few concepts that will be referred to throughout this report: poverty and 

vulnerability, and the links with sustainable development. It will also look at some of the specifi cities of the 

context that the NDSA was carried out in. 

A Few Definitions 

What is Poverty? 

When travelling through Afghanistan, a general observation that can be made is the discernible diffi culty of 

ways of ensuring livelihoods, for a great majority of the population. What exactly is poverty? Defi nitions of 

poverty vary widely and as a consequence, ways of fi ghting poverty are multiple. 

Monetary Income Poverty 

Studying livelihoods of the Afghan population leads to taking into consideration monetary poverty. Absolute 

monetary poverty can be defi ned as the insuffi ciency of income to be able to get the daily food ratio. 

Poverty, in terms of livelihoods is the consequence of paucity of adequate nutrition, lack of clothes, of 

accommodation, etc. Poverty of potentiality is the lack of education, equipment, social networks and 

support systems. Thus, the most common and traditional way of defi ning poverty is in terms of monetary 

income poverty. The way chosen to measure poverty, on which experts continue to debate, is as essential 

as the multiple meanings this word encompasses. Currently, economic policy choices and the effi ciency of 

these choices depend on the accuracy and reliability of the tools used to collect relevant information. If only 

monetary poverty is taken into consideration, it is obvious that this aspect has varied greatly and increased 

during the last 25 years in Afghanistan. Focusing on poverty of resources and of choices available in the 

larger sense paint a different picture. On these aspects the country is characterised by shortage of basic social 

services: education, health, water sanitation, shelter. 

Poverty of Capabilities 

However, over the last decade, a more comprehensive view has emerged, mostly pushed forward by the 

Human Development reports and the theories of Amartya Sen to look at poverty in terms of capabilities. The 

Capabilities Approach 2 is based on “beings and doings that an individual has reason to value”, thus 

shifting the focus from the specifi cities of the disabling situation to how to look at establishing equality in 

terms of possibilities and choices. Amartya Sen’s Capabilities Approach looks at not what a person actually 

does (functionings) but at the range of possibilities that he/she chooses that specifi c functioning from – this 

is the capability set. Taking the view of the individual shifts the focus to the interaction between the person, 

with his/her limitations in functioning (which may or may not be permanent) and the context, which consists 

of a number of resources as well as expectations, stereotypes and often prejudice and discrimination. As a 

result, looking at poverty of capabilities does not stop at just what the person does but what his/her choices 

are. These choices are infl uenced by the social and human resources, especially in traditional contexts. 

From Vulnerability to Poverty: Facing Risk and Enduring Shocks 

Vulnerability is defi ned as “the probability of having his/her own situation worsens when facing a dramatic event. 

2 See SEN A., (1999) Development as Freedom, Oxford University Press, Oxford. 


1

A worsening, which can lead, depending on various factors, to poverty” 3 . In other words vulnerability refers 

to the incapability of people or households, or even the community at large, to transform assets and income 

into capabilities. It is the inability to resist an external or covariate 4 shocks or to face risks that threaten and 

reduce their well-being. External shocks such as violence or insecurity, drought, fl ood, late frosts are common in 

Afghanistan. During the fi eldwork in June 2005, a complete cluster in Faryab province has been destroyed by a 

fl ood. People were interviewed in front of ruins of their houses or in tents handed over by relief agencies. During 

the summer 2006, a drought has threatened the country due to inadequate rainfall in the months of April and 

May 2006 5 . In November 2006, fl oods killed 40 people and injured 20 others in Uruzgan province. Some 300 

houses and hundreds of acres of farmland were also destroyed in this province. 

Many factors determine the level of vulnerability. The ownership of goods, land or animals are assets against 

vulnerability. The benefi t of a large social network can also be of assistance in trying times. The level of activity 

measured by the number of active people inside the household and other income-generating activities have 

an impact on the level of vulnerability and, as a consequence, infl uence falling into a situation of poverty. If 

it is essential to measure the phenomenon through indicators such as proportion of people living below the 

poverty line or probability of occurrence of a shock, it is also important to look more closely at the factors 

which help a person stay out of poverty, and help him/her face risks in the long term. Fighting vulnerability 

by increasing capabilities to resist shocks is what can be called reducing the vulnerability of 

disadvantaged groups. 

The Human Development Report has put forward the Human Development Index (HDI) that examines the 

dynamic aspect of development by focusing on a variety of factors. It is very possible that a certain population 

does not seem worse off than another in terms of monetary poverty, but may be more vulnerable. This means 

that when faced with risks and challenges (such as illness, disease, unemployment…) these vulnerable 

groups are at a greater risk of falling (back) into poverty: their potentialities are weak and the way they 

adjust their livelihood strategies to cope with shocks might not be adapted or suffi cient to cope with them to 

escape from poverty. 

The NRVA 2003 has shown that years of war and drought have had a very negative impact on the rural 

average household’s ability to acquire and maintain assets as well as their ability to handle the adverse 

effects of multiple shocks to their livelihood 6 . The present report analyses attempt to present the features that 

determine the vulnerability of persons with disability as well as of the households they live in: what is the link 

between the number of people working, the assets of an household and poverty? What is the impact of the 

level of education or the state of unemployment of the head of household on the livelihoods of the household? 

How does disability impact the living conditions of the entire household unit? Answering these questions will 

in turn help to determine poverty and vulnerability of households that have a disabled member and look at 

ways of enhancing their capabilities. “These capabilities can be enhanced by public policy, but also, on 

the other side, the direction of public policy can be influenced by the effective use of participatory 

capabilities by the public. 7 ” 

3 See DUBOIS J.L., ROUSSEAU S., (2001),“Reinforcing Household’s Capabilities as a Way to Reduce Vulnerability and Prevent Poverty 

in Equitable Terms”, paper presented at the fi rst Conference on the Capability Approach, Justice and Poverty: Examining Sen’s Capability 

Approach, June 5th-7th 2001, Von Hugel Institute, St Edmund’s College, Cambridge University, http://www.st-edmunds.cam.ac.uk/vhi/. 

4 NRVA (2003) use the term of covariate shock for a shock independent of the family, to differentiate from idiosyncratic shocks which 

typically occur at a household level, like loss of employment or death of a member. See VULNERABILITY ANALYSIS AND MAPPING UNIT 

OF THE WORLD FOOD PROGRAMME AND THE VULNERABILITY ANALYSIS UNIT OF THE MINISTRY OF RURAL REHABILITATION AND 

DEVELOPMENT (2004), op. cit., p. 53. 

4 SEN A., (1999) , op. cit., p. 18. 

5 United Nations Assistance Mission in Afghanistan (UNAMA) July 25, 2006, To support the urgent needs of more than 2.5 million peopled 

affected by drought and food insecurity, the Government of Afghanistan and the United Nations today launched an appeal for nearly $76.4 

million, covering an initial period of six months. That is on top of the 6.5 million the World Food Programme estimates were already at 

risk of hunger. 

6 VULNERABILITY ANALYSIS AND MAPPING UNIT of the World Food Programme and the VULNERABILITY ANALYSIS UNIT of the Ministry 

of Rural Rehabilitation and Development (2004), op. cit. 

7 SEN A., (1999), op. cit, p 18. 

2 Understanding Vulnerability of Afghans with Disability

Livelihood, Poverty and Disability from a Global Perspective 

It is a widespread belief that persons with disability are among the more disadvantaged groups, especially in 

developing and transitional countries. Experts refer to exclusion and discrimination, less access to food or poor 

quality of food, inadequate health care and incapacity of the education system to include them. Finally, persons 

with disability are believed to have reduced capabilities for work. In Afghanistan, where 71.6% of inhabitants 

live in rural areas, livelihood is based largely on agricultural activities: “All (these reasons) contribute to 

less opportunities for disabled people and reduced income generating capabilities 8 ”. They are often 

considered as being more at risk of falling into poverty and thus being more vulnerable than the non-disabled 

population. On the other hand, people living in poverty are more likely to become disabled due to a lack of 

access to basic services, illness, malnutrition... This correlation between disability and risk of poverty has been 

described in a number of different studies. But from correlation to causality, it is diffi cult to conclude clearly on 

which factor is predominant in a certain situation and determines the others. Poor households, because they lack 

adequate food, basic sanitation, good housing or access to health services, particularly preventive health services, 

are more at risk of disabling diseases. Or, what could be a temporary and curable disease, might transform into 

a permanent disability. It is stated in the UN Compendium that “in many respects, the disability rate is a 

socioeconomic indicator, a type of poverty index, or index of development 9 ”. 

Poverty and Disability in Afghanistan 

The only mechanism of public policy that specifi cally addresses poverty of persons with disability in Afghanistan 

is the pension welfare system of the Ministry of Martyrs and Disabled and Social Affairs. This Ministry was 

established in the Soviet infl uenced era of Afghanistan as a pensions and welfare organisation catering 

specially to the war related disabled and the families of the martyrs. The role of the ministry was expanded in 

2002 under the Transitional Islamic State of Afghanistan to become the lead government agency to advocate, 

facilitate coordination and dissemination of information regarding persons with disability. Despite this role 

given to the MMDSA, line ministries were and still are responsible for integrating the needs of the disabled 

population in their policies and programs. An effi cient coordination body is still missing in order to bridge 

communication, coordination and cooperation gaps between the various ministries. 

According to NRVA 2003 10 , poverty is strongly correlated with the presence of disabled members in the 

household, among other attributes. It is also correlated with lack of access to infrastructures and services, 

lack of access to school and health centres, lack of capital assets such as land and livestock. Landownership 

also appears to be a good divider between rich and poor 11 . The present report tries to further investigate this 

possible link, emphasising the analysis by comparing the situation of households with a person with disability 

and those without any person with disability. 

Poverty from a Gender Perspective 

An interesting perspective to look at livelihood and poverty in Afghanistan is provided by the gender approach. 

It is often emphasised that women are in general more disadvantaged than men in Afghanistan, especially 

in terms of income and livelihoods. Therefore, it is relevant to assess the major differences in the livelihood 

situation between households according to the gender of the head of the household in order to determine if 

women with disability are more vulnerable to (chronic) poverty than men with disability. 

8 HOOGEVEEN J. G. (2005), Measuring Welfare for small Vulnerable Groups. Poverty and Disability in Uganda, Journal of African Economies, 

2005 14(4):603-631. 

9 STATISTICAL OFFICE, DEPARTMENT OF INTERNATIONA L ECONOMIC AND SOCIAL AFFAIRS, UNITED NATIONS (1990), “Disability 

Statistics Compendium”, Statistics on Special Population Groups, Series Y, No. 4, New York. 

10 VULNERABILITY ANALYSIS AND MAPPING UNIT OF THE WORLD FOOD PROGRAMME AND THE VULNERABILITY ANALYSIS UNIT OF 

THE MINISTRY OF RURAL REHABILITATION AND DEVELOPMENT (2004), op. cit. 

11 For a very interesting and clarifying analysis of land system in Afghanistan see ALDEN W. L. (2004),“Looking for Peace in the Pastures: 

Rural Land Relations in Afghanistan”, Afghanistan Research and Evaluation Unit, AREU, December 2004, 125 pp., p.14. 


3

Table 1. Distribution of Households according to Location and 

Gender of the Head of the Household 

Location of Household† 

Urban 

Man Head of 

the HH 

Woman Head of 

the HH 

Total 

Number 5323 427 5750 

% in location 24.0** (1) 38.4** (1) 24.7 

Number 16888 685 17573 

Rural 

% in location 76.0 61.6 75.3 

Total Number 22211 1112 23323 

Source: NDSA. Note: † Weighted by the number of household in the cluster without persons with disabilities 

living there. (1) Test of comparison between head of households` gender. ** Signifi cant at p

Poverty of Living Conditions: 

Identifying Benchmarks 

A study focusing on livelihoods of persons with disability compares the situation of this vulnerable group 

with that of the non-disabled, by taking into consideration a series of indicators and items. As discussed 

in the introduction, it appears that the livelihood picture is a complex one. The indicators considered in this 

report were those selected in the interview as valid benchmarks for comparison of well-being and quality of 

life. Three major fi elds are considered here: access to basic goods, standards of living and activity and main 

sources of income. 

Inequality in the Access to Basic Goods 

Access to basic commodities and utilities help characterise living conditions for households that include 

persons with disability as well as those with non-disabled persons as an expression of the level of poverty. It 

is a basic needs’ approach, which tries to evaluate the current situation of people regarding basic goods. These 

living conditions are assessed through the following items: 

Access to drinking water; 

Source of lighting; 

Energy used for cooking; 

Toilet facilities; 

Supply and access to food. 

For all these items, the report presents the situation of the two types of households in order to assess the 

impact of disability on the living conditions of the entire unit. It is important to state that questions regarding 

livelihoods were asked to one member of the family, as it was assumed that they would be valid for all 

members living under the same roof. 

Difficult Access to Drinking Water 

Access to drinking water is, needless to mention, essential. Sometimes, in the dry season, it is necessary 

to walk one entire day to go and catch water at a river. Inadequate access to drinking water constitutes a 

major burden and strongly infl uences standard of living. In 2003, according to NRVA results 12 , only 24% 

of households reported accessing water from safe sources. Figure 1 (and Table 12 in Annexure) looks at the 

distribution of persons with disability and the non-disabled on one hand, and the households that they live in 

on the other hand, regarding access to drinking water. The responses are similar for households with persons 

with disability and for non-disabled households. A large majority of people in Afghanistan (74.3%) 

have to go outside the compound to fetch water. Nevertheless, people living in households without 

any person with disability were signifi cantly slightly more (5.6% more) to declare having to go outside the 

compound. 




5

Figure 1. Distribution of Persons 

and Households Having Easy 

Access to Drinking Water 

35 

Non-Disabled Persons with Disability 

Households without Persons with Disability 

Households with Persons with Disability 

30 

25 

20 

15 

10 

5 

0 

Source of Water within the Compound/House 

A large majority of Afghans (95.6%, see Table 14 in the Annexure) do not have a pipe supply of water and 

need to walk more than 5 minutes to the nearest source of drinking water (63.7% of them, see Figure 2 and 

Table 13 in the Annexure). If a majority (54.5%) has to walk only 10 minutes to fetch water, in some villages, 

a small minority (6.8%) has to walk more than 2 hours. This is mainly due to drought that has made sources 

of water dry. The rest of the population (35%) needs between 10 minutes and 1 hour to fetch water: and this 

household task is carried out by children and women every day, along with number of other tasks. On the 

positive side, more households with a person with disability have less than 10 mins to go to fetch water than 

households without a person with disability. 

Figure 2. Distribution of Households according to the Time 

Needed to Fetch Drinking Water 

45 



40 

35 

30 

25 

20 

15 

10 

5 

0 

Less than 5 Mins 6 to 10 Mins 11 to 15 Mins 16 to 20 Mins 21 to 30 Mins 30 Mins and More 

Table 14 in the Annexure shows that a majority of Afghans have access to water that is not always drinkable, 

supporting the NRVA 2003 results. The use of water in hygiene is an important preventive measure; 

contaminated water remains an important cause of diarrhoea and other ailments. Cholera and dysentery 

cause severe, sometimes life threatening forms of diarrhoea, especially when it comes to very young children 

who get dehydrated at an alarming rate. 

Less than 8% of the population have access to a private or public tap, which do not reliably and systematically 

provide safe water. 23.8% have access to hand pumps and 29.5% to a well, among them, 9.4% of the wells 


are open well or Kariz 13 . 2.6% more households with a person with disability have access to a well in the 

residence compared to non-disabled households. Another 39.3% go to rivers, ponds, lakes, streams or fi nd a 

way to collect rainwater. In periods of drought, the level of wells and other natural sources can become so low 

that water provision becomes a challenge: this requires walking long distances to fi nd an alternative source 

of water. Use of water with mud in unsafe ponds with stagnant water where insects breed then becomes 

common. As a result, the drinking water supply, which is normally safe, becomes unreliable. Spreading of 

diseases, and widespread diarrhoea thus increase. Diarrhoea is a symptom of infection caused by a host of 

bacterial, viral and parasitic organisms most of which can be spread by contaminated water. All these are 

more common when there is a shortage of clean water for drinking, cooking and cleaning, and when basic 

hygiene is diffi cult to maintain 14 . 

Figure 3. Distribution of People according to the Time Needed to Fetch 

Water in Urban/Rural Areas 

70 

Urban 

Rural 

60 

50 

40 

30 

20 

10 

0 

Less than 5 Mins 6 to 10 Mins 11 to 15 Mins 16 to 20 Mins 21 to 30 Mins 30 Mins and More 

A statistically signifi cant higher proportion of urban households (56.5%) have access to water inside their 

compound than those in rural areas (15.5%) as shown in Table 15 in the Annexure. Such a result is expected, 

as it is easier to develop water sanitation supply in towns. The difference is also statistically signifi cant between 

households where the head is a woman compared to those where the head is a man: 63.2% of those headed 

by a woman have water inside the compound. This is explained by a relatively highly higher presence of 

women head of households in towns and cities than in villages. 

Sources of Light: Paucity of Resources 

Afghan households often use two or more sources of energy for light. Responses in following Figure 4 

in next page (and Tables 17 in the Annexure) are considering two possible answers. Among all sources of 

light, only a minority of Afghan households (12.3%) use main power. The large majority of these live in 

towns: 27.9% of those who live in towns and cities declare using main power as the major source of light, 

and only 4.3% of those who live in rural areas declare using it. These households are usually located in 

villages that are close to urban areas and not in remote areas (see Table 18 in the Annexure). But even for 

those households that are connected to electricity, the shortage of supply is recurrent. 

Taking into account only the fi rst answer given during the interview, thus considering only the main source of 

light, as in Figure 5 next page, 41% of households in urban areas use main power. However, they also need 

to rely on an alternate source of lighting (generator, kerosene lamps or candles) in case of power shortage, 

13 Kariz (also known as kareze or qanat) is an ancient underground channel irrigation system invented in Persia (Iran). It is a slopping 

tunnel that brings water from an underground source in a range of hills down to a dry plain at the foot of these hills. Its advantage over an 

open air aqueduct is that less water is lost by evaporation on its way from the hill to the plain. In the high and dry plains of Afghanistan, 

agriculture is often impossible without irrigation. The Afghans have put in place a system for harnessing the water: the kareze tunnels. Part 

of the network of kareze as been destroyed during the confl ict. 

14 World Health Organization, Water Sanitation and Health (WSH) Water-related diseases. 


7

Figure 4. Distribution of Household according to Sources of Light 


Households with Persons with a Disability 

80 

70 

60 

50 

40 

30 

20 

10 

0 

Main Power 

Generator/ 

Battery/Invertor 

Kerosene Petrol/ 

Gas 

Candles 

Others 

which remains frequent. This is why when one considers both answers, the percentage of households using 

main power within the total supply, decreases. Kerosene, petrol or gas lamps are mainly used in rural areas 

as the fi rst source of lighting. This was also true in towns in 2005. During winter, each block of Kabul received 

power only a few hours a day, at best. 

Figure 5. Distribution of Households according to Main Source of 

Light in Urban and Rural Areas 

90 

80 

Urban 

Rural 

70 

60 

50 

40 

30 

20 

10 

0 

Main Power 

Generator/ 



Gas 

Candles 

Others 

However, there is no statistically signifi cant difference between households with a person with disability 

and households without a person with disability for this indicator. 

Figure 6. Distribution of Households according to Main Source of Light 

and Gender of the Head of the Household 

80 

Man Head of the Household 

Woman Head of the Household 

70 

60 

50 

40 

30 

20 

10 

0 

Main Power 

Generator/ 



Gas 

Candles 

Others 


On the other hand, statistically signifi cant differences between households where the head is a woman 

to those where the head is a man are evident (Figure 6 and Table 19 in the Annexure): 

19.9% of female headed households have access to main power against only 11.9% for households 

headed by a man; 

16.3% of these use mainly a generator, battery or invertors against only 8.8% for households headed 

by a man. 

These results can be easily explained by a higher number of woman-headed households in urban areas where 

main power and generators are accessible than in rural areas. 

Energy for Cooking: the Massive Use of Firewood a Cause for Concern? 

The use of fi rewood (47.9% of all source of cooking used), or dung is still the main and most commonly 

used source of energy for cooking (Figure 7 and Table 20 in the Annexure). There is no signifi cant difference 

between households with a person with disability and households without a person with disability. 

Figure 7. Distribution of Households according to Sources of Energy used for Cooking 

50 



45 

40 

35 

30 

25 

20 

15 

10 

5 

0 

Gas 

Stove with 

Kerosene/Petrol 

Firewood Dung Charcoal Electricity Other 

It is only in towns and cities that 40% of households use gas as a main source of energy for cooking (See Figure 

8), but even there fi rewood is the major energy for cooking. Charcoal and electricity are rarely used even in towns 

for cooking (See Table 21 in the Annexure). Some research in developing countries has shown that if in the short 

term, deforestation is due to population growth and agricultural expansion, over the long-term deforestation is 

aggravated by wood harvesting for fuel and export 15 . This might be one of the challenges for the coming years. 

Figure 8. Distribution of Households according to Main Source of 

Energy for Cooking in Urban and Rural Settings 

80 

70 

Urban 

Rural 

60 

50 

40 

30 

20 

10 

0 

Gas 

Stove with 

Kerosene/Petrol 

Firewood Dung Charcoal Electricity Other 

15 ALLEN, J. C. & BARNES, D. F. (1985),“The Causes of Deforestation in Developing Countries”, Annals of the Association of American 

Geographers 75 (2), 163-184. 


9

Access to Modern Toilet Facilities: a Benchmark for Wealth? 

As shown in Figure 9 (and Table 22 in the Annexure), a very small proportion of people have access to modern 

toilet facilities (6.0%). A large majority of people have access to traditional types of latrines. The households of 

a majority of persons (47.7%) include a traditional Afghan open-backed latrine, with a statistically signifi cant 

difference between households with a person with disability and those without disability. This is followed by 

the 29.4% who make use of an open defecation fi eld outside their households. 

Figure 9. Distribution of Households according to Access to Types of 

Toilet Facilities 

60 



50 

40 

30 

20 

10 

0 

Private Flush 

Inside 

Private Flush 

Outside 

Shared Flush Traditional Pit Open Backed Open Defecation Other 

Field Outside the 

House 

As expected, Table 23 in the Annexure shows that Afghans have signifi cantly more access to fl ushes 

for their natural needs in urban areas, while open fi elds are naturally more used in rural places. These 

practices are a vector for several diseases related to lack of hygiene. 

Overall it can be concluded that there is a correlation of the disability factor with this particular indicator of living 

conditions. The overall lack of access to electricity and water supply is a plight that is shared by all Afghans. 

Standards of Living: Main Features 

In this sub-section, standards of living are studied through two key variables: size of housing and diversity 

and quality of food. There is a link between poverty and size of the house in which people live. The number of 

rooms in which the household lives is an interesting proxy for the level of wealth or poverty of a family unit. 

In fact, increasing the size of a house, building or acquiring a new one are important expenses that a family 

cannot easily make since they require a long period of savings or an important level of income. 

Size of Houses and Size of Households: Over Crowded Living 

Spaces 

According to the NDSA, the average size of a household is almost 8 people (7.9) living in the same house, 

under the same roof, preparing the food in the same kitchen, sharing the meals, the income and the expenses. 

A majority of people (57.1%) live in a space of 1 to 3 rooms as shown in Figure 10 (and Table 24 in the 

Annexure). Compared to the average size of a household, this means that the average living space is about 

one room for three people. Small size of households is more common when the head is a woman: 44.5% 

of households headed by a woman have less than 5 members; this fi gure is of 14.7% of those headed by 

a man. On the other hand, 36.8% of households headed by a man have more than 10 members. Similarly, 

households with a person with disability are more often larger in size: 44.9% live in households of more 

than 10 members. 

Figure 10 (and Table 24 in the Annexure) show that the difference of size of houses between households 

having a disabled member and households with none are limited, and significantly different for larger 


houses only. The fact that the number of persons with disability in wealthier families living in big houses 

is lower, can be explained by a number of factors: less exposure to certain types of risks such as endemic 

diseases, malnutrition, birth accidents due to lack of basic and maternal health care, limited exposure to 

mines and UXO due to less work in fi elds and distances covered on foot… 

In other words, the 2.2% difference of living spaces of one or two rooms between households with a member 

who is disabled and households without any disabled member is statistically signifi cant at 5% only. But 

this only represents 2.2% difference on an average of 15.2% of households living in such a limited space. 

One can conclude that poverty strikes almost equally in families with a disabled member and those without 

considering the indicator of small living spaces. 

On the other hand, there is no signifi cant difference between households with person with disability and nondisabled 

households regarding living spaces comprising of 3 to 5 rooms. The majority of households (57.1%) 

live in similar conditions, whether it includes a disabled member or not. The difference becomes statistically 

signifi cant for bigger size houses, but with opposite differences: 

For 6 rooms, the number of households without a person with disability is 4.8% higher than households 

with a person with disability. 

For 7 or more rooms, households with a person with disability are 3.1% more numerous than households 

without a person with disability. 

Generally, the size of houses is signifi cantly slightly different for households with a disabled member. This 

indicator does not show any major difference in the poverty situation between both groups: the poorest with 

small size houses are found in both groups and disability does not seem to be correlated with the size of living 

spaces in a signifi cant manner. 

Figure 10. Distribution of Households according to the Number of 

Rooms in the House 

25 



20 

15 

10 

5 

0 

1 or 2 Rooms 3 Rooms 4 Rooms 5 Rooms 6 Rooms 7 Rooms and More 

In fact, when one compares the size of the house using the number of rooms, and the size of the 

household, considering the number of inhabitants, as in Figure 11 and Table 3 next page (and Table 

25 in the Annexure), the following results are observed. Larger size families live in very limited spaces: 

10.3% of households of more than 5 members, 14.8% of households of 8 and 9.4% of households 

of 9 members and even 9.6% of households of more than 10 members live in houses of one or 

two rooms. 51.9 % and 41.8% respectively of households of more than 9 and 10 members live in 

houses of 1 to 4 rooms. 


11

Table 3. Average Ratio of Number of Members by Room and Number of Household Members According to 

the Number of Rooms in the House 

Number of 

Rooms 

Ratio Number 

of Members by 

Room 


Members in all 

Households 

Ratio Number of 

Members by Room 

in Households with 

PwDs 


members in 

Households with 

PwDs 

Ratio Number of 

Members by Room 

in Households 

without PwDs 


members in 

Households 

without PwDs 

1 Room 5.6 4.6 5.4 4.2 5.6 4.6 

2 Rooms 3.3 5.0 3.3 5.2 3.3 5.0 

3 Rooms 2.2 5.3 2.5 5.8 2.2 5.3 

4 Rooms 1.9 6.0 2.0 6.3 1.9 5.9 

5 Rooms 1.6 6.0 1.7 6.5 1.6 6.0 

6 Rooms 1.3 6.0 1.6 6.8 1.3 6.0 

7 Rooms 1.3 6.3 1.4 6.9 1.3 6.2 

8 Rooms 1.1 7.1 1.4 7.4 1.1 7.1 

9 Rooms and 

more 

0.9 6.1 1.1 7.1 0.9 6.1 

Total 2.0 5.7 2.2 6.2 2.0 5.7 

Source: NDSA 

Table 3 and Figure 11 lead to the following conclusions. 

There is a general proportionally positive relationship between the number of people in the household 

and size of the house. Households with persons with disability are a little bigger in size, but the general 

ratio is similar for both households with and without persons with disability. 

This leads to confi rm the fact that when there is a possibility, people do occupy the living space that is 

available. This is not the case in all traditional cultures. 

The curves in Figure 11 intersect for a household with a living space between 1 and 2 rooms and having 

a size of 4 to 5 people living together. This could be considered by convention as a relative poverty 

threshold. Below this point, houses can be considered as overcrowded. Above this point, the house can 

be considered as better off. This reference point can be used as a social norm for poverty reduction policy 

when considering housing policy in general. 

Figure 11. Distribution of People according to the Number of Rooms in the 

House and the Size of the Household 

8 

7 

6 

5 

4 

3 

2 

Ratio Number of Members by 

Room 

Number of Members in All 

Households 


Room in Households with Persons 

with Disability 

Number of Members in 

Households with Persons with 

Disability 


Room in Households without 


Number of Members in 

Households without Persons with 

Disability 

1 

0 

1 Room 2 Rooms 3 Rooms 4 Rooms 5 Rooms 6 Rooms 7 Rooms 8 Rooms 9 Rooms 

and More 


The Afghans, not considering the situation with regards to disability, are in very different conditions in terms 

of housing as shown in Figure 12. Figure 12 shows the Lorenz 16 curve for the proportion of households and 

the ratio of number of people by room. Globally, 50% of: 

All households have more than 1.6 people living by room; 

Households with persons with disability have more than 2 people living by room; 

Households without a person with disability have only more than 1.6 people living by room. 

This shows that additional living space that may be attributed to a member of a household where a person 

with disability lives is probably smaller than that for members of non-disabled households. This furthermore 

suggests that disability does impact living standards when these tend to improve. 

Figure 12. Lorenz Curve of the Ratio 

of Number of Members by Room 

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

0 10 20 30 40 50 60 70 80 90 100 

It is noteworthy to see how and to what extent the most disadvantaged households living in rural 

settings are living in small houses: 18% more of rural households (41.2%) live in houses of 1 to 3 rooms 

than urban households (23.2%). This occurs even if living spaces in large towns and cities are much more 

expensive than in villages. In contrast, 22.7% more of urban households (60.8%) live in houses of at least 5 

rooms compared with rural households (38.1%). This indicates higher standards of living in urban settings. A 

further calculation shows that the gap between households living in the largest houses (more than 7 rooms) 

is 17% when one compares the largest urban centres (Kabul, Herat, Jalalabad, Mazar-I-Sharif, Kandahar and 

Kunduz) to the rest of the country. Largest houses are found most often in major urban areas. 

Figure 13. Distribution of People according to the Number of Rooms in 

the House by Urban and Rural Settings 

25 

Urban 

Rural 

20 

15 

10 

5 

0 


16 The Lorenz curve, a cumulative frequency curve that compares the distribution of a specifi c variable (ratio of number of people per 

room) with the uniform distribution that represents equality. This equality distribution is represented by a diagonal line, and the greater the 

deviation of the Lorenz curves from this line, the greater the inequality. 


13

Comparing the size of households according to the gender of the head of household (Figure 14 and Table 

27 in the Annexure) shows signifi cant differences for small as well as big sizes of houses: 

22.4% of households with a woman at the head live within one or two rooms, while only 14.8% of 

those headed by a man; 

33.2% of households with a woman at the head live within 6 or more rooms, while this fi gure is of 

27.5% of those headed by a man. 

These results show that poor households headed by a woman more often live in worse conditions 

than poor households headed by a man, even considering that there are relatively more households 

headed by a woman in urban areas where size of houses are bigger than in villages. On the other hand, 

households headed by a man are strongly and signifi cantly more represented among houses of 4 rooms, 

which correspond to the average house size. If households headed by women with 6 rooms are more 

numerous, it is most probably because these less poor households are more present in urban areas 

where size of houses are bigger. But this conclusion has to be considered with caution as the number 

of households headed by a woman is rather low; and is much lower than those headed by a man in all 

categories considered. 

Figure 14. Distribution of People according to Gender of the Head of 

the Household and Number of Rooms in the House 

25 



20 

15 

10 

5 

0 


Supply and Access to Food: Insufficient Quantity, Lack of Diversity 

60% of Afghan households buy their food at the market. 31% both produce what they eat and buy part of their 

food requirements at the market. Only a minority (7.3%) relies solely on self-provided food (Figure 15). There is 

no statistically signifi cant difference between households with a member who is disabled and households without 

any disabled member for this indicator. Disability appears to have absolutely no infl uence on this distribution. 

Figure 15. Distribution of Households regarding Sources for Supply of Food 

70 

60 



50 

40 

30 

20 

10 

0 

Market/Bazar 

Self Provided/ 

Farm 

Combination of 

Market/Farm 

Food Aid 

From Family, 

Other Relatives 


Figure 16 shows that the proportion of people buying all their food at the bazaar is higher in urban areas. 

Only 2.3% rely only on their own fi eld production in urban areas. A larger minority buy part of their food at 

the bazaar, and produce food for their own needs in rural area. 

In urban areas, because only a minority of families have access to the land for farming activities, 85.5% of 

households rely on market for their food supply. Food aid in urban areas comes after market and farm supply, 

and represent a very small proportion of households relying on it. 

In rural areas, market provides food for only half (51.1%) of the households. Only a minority never go to 

the bazaar for food purchases (9%). But a large number of households (38.8%) declare both buying and 

producing food. Family outside the household very rarely provide food (0.8%). 

Figure 16. Distribution of Households Regarding Sources of Supply of 

Food in Urban and Rural Areas 

90 

80 

Urban 

Rural 

70 

60 

50 

40 

30 

20 

10 

0 

Market/Bazar 

Self Provided/ 

Farm 

Combination of 

Market/Farm 

Food Aid 

From Family, 

Other Relatives 

In terms of consumption of food, a majority of people (52.4%) report having food shortage. When one adds 

people who declare receiving enough food in quantity but with poor quality, insuffi cient quality or quantity of 

food affects the large majority (83.9%) of the Afghan population. These results are in accordance with NRVA 

2003 results and analysis 17 . The authors noticed that in 2003, the main coping strategy in case of shock was 

a reduction in diet quality or quantity. The fact that persons respond to a shock by curbing a basic survival 

need also shows vulnerability of the population. 

When the situation of households with a member who is disabled and households without any disabled 

member is compared, very limited and non signifi cant differences can be observed (Figure 17 in next page 

and Table 30 in the Annexure): 

52% and 52.5% respectively of households with a member who is disabled and households without 

any disabled member complain about food scarcity; 

87.1% and 83.6% respectively of households with a member who is disabled and households without 

any disabled member either lack food or receive enough food but of poor quality; 

The only signifi cant differences between the two types of households concerns those having enough to 

eat: 3.8% more among households without any disabled member report having enough to eat. 

Similarly, the difference is also statistically signifi cant for households having enough food but of poor quality: 

4.2%, but this time households with a member who is disabled are more to be in this situation. 




15

Figure 17. Distribution of Households Regarding Amount of Food 

Available 

40 



35 

30 

25 

20 

15 

10 

5 

0 

Always Enough 

Sometimes Not 

Enough 

Frequently Not 

Enough 

Always Not 

Enough 

Always Enough But 

with Poor Quality 

Thus, the food situation is poor for both groups and Afghans with disability are not necessarily in a worse 

situation regarding this indicator. In the NDSA health report 18 , it was concluded that the majority of persons 

reported that their household did not receive enough food in general. The results are similar in both groups’ 

answers. 

Figure 18. Distribution of People in Urban and Rural Areas 

regarding Amount of Food Available 

35 

Urban 

Rural 

30 

25 

20 

15 

10 

5 

0 

Always Enough 

Sometimes Not 

Enough 


Enough 

Always Not 

Enough 



But once again, there is a strong and statistically significant difference between urban and rural 

settings. While 27.0% of urban households declare eating enough and adequately, only 12.4% (which 

is 14.6% less) of rural households declare the same. On the other hand, 16.3% more rural households 

(40.1%) than urban ones (23.8%) declare eating always or frequently not enough as shown in Figure 18 

(and Table 31 in the Annexure). 

18 See BAKHSHI P., NOOR A. and TRANI J.F. (2006), “Towards Well-Being For Afghans With Disability: 

The Health Challenge”, Report to the Government of Afghanistan, Volume 2, Handicap International, Lyon and Kabul. 


Figure 19. Distribution of People according to Gender of the Head of 

Household and Supply of Food 

35 



30 

25 

20 

15 

10 

5 

0 

Always Enough 

Sometimes Not 

Enough 


Enough 

Always Not 

Enough 



Figure 19 (and Table 32 in the Annexure) show that households headed by a woman suffer more often from 

lack of quantity and of diversity of food supply. 8.4% more households headed by a woman (60.5%) than 

households headed by a man (52.1%) suffer from either permanent, frequent, periodic shortage of food, 

while 8.4% more households headed by man (48.0%) than households headed by a woman (39.6%) 

always get enough food, even if it is with insuffi cient diversity. 

The correlation between having a disabled member within the household unit and access to food is not 

signifi cant. As concluded for the previous section, it seems that the overall lack of food and widespread access 

to quality nutrition seems to affect all social categories in Afghanistan today. However, the disability aspect 

probably constitutes a vulnerability factor, which is not visible when the majority of the population 

is living in poor conditions. This is why there is a need to closely monitor the factors that infl uence the 

vulnerability of households and people. 

The next section explores the situation on the labour market. The proportion of people working in Afghanistan 

is a subject of controversy. Employment, under-employment, women’s and children’s activities are diffi cult to 

measure and closely rely upon how they are defi ned and considered. 

Activity and Income: Struggling for Survival 

Poverty can be a result of disability when the onset of disability results in loss of employment or loss of income 

for the family. A major hypothesis that could be put forward is that employment is a major way to autonomy 

for persons with disability, a vulnerable group at risk of dependency. Within a traditional context where family 

and community are the most important social groups, fi nancial contribution is also a means of increasing 

value and respect within the family, as persons with disability are then regarded as contributors and not 

as a ‘burden’, and further leads to changing their social image. Employment is a key to understanding the 

economic situation of persons with disability and their families. 

A major objective of this analysis is to assess the level of income-generating activity of the households of 

persons with disability (including services that are remunerated on a non monetary basis). An attempt is made 

in this section to establish a typology of activities including issues like unemployment, under-employment, 

satisfaction at work, constraints faced, and level of income. 

Activity and Unemployment in an Economy under Reconstruction 

After the long period of confl ict, the economic structures and mechanism have to be rebuilt in Afghanistan. 

Industry is almost inexistent, agriculture represents the largest sector for activity and services have been 


17

increasing at a high pace for the last fi ve years at least in urban areas. What is the situation of the labour 

market in Afghanistan? What exactly is the work offer? 

According to an International Rescue Committee survey carried out in 2003, the unemployment rate represents 

32% of the active population. But what does this fi gure stand for? Unemployment is considered as the 

situation of a person without an ‘income generating activity’, effectively looking for a job and 

ready to take it immediately if an opportunity occurs 19 . In large areas of the country, women are not 

allowed to work in the fi eld but carry out all the household tasks. In this case, the rate of unemployment is 

of 45.6% among the 15-65 years old of both sexes: it includes all women declaring that they undertake the 

household chores. But if one sticks strictly to the international ILO defi nition, only 2.4% of Afghans above 14 

are not working and effectively looking for a job. 

Another diffi culty is linked to the complexity of the land ownership system and the diversity of status of people 

working on this land: landowners, mortgagers, tenants who share the crops and those who pay a rent, simple 

labourers (Kargar), etc. Beyond this complexity of the land system in rural areas, the possessions of land and 

of a house remain reliable benchmarks for remaining out of poverty 20 . 

Assessing the level of income-generating activity of persons with disability (including services that are paid 

on a non monetary basis) will help establishing a typology of activities that includes unemployment, underemployment, 

work satisfaction, constraints to employment or in the workplace and levels of income. Lack 

of employment is a major obstacle to achieving self-suffi ciency and fi nancial independence, especially for 

persons with disability who are at high risk of lifetime dependency on others. Employment also modify the 

perception of the person considered as participating to the family welfare, thus enhancing her/his social 

image and status. Identifying differences of employment situation and strategies and the link with different 

kind of disabilities help to identify inequalities. One important belief in Afghanistan that must be assessed 

against scientifi c evidence is the idea that landmine and war survivors benefi t from a better situation than 

other persons with disability, especially when compared to those with intellectual disability or mental illness. 

The picture of the employment situation of persons with disability is characterised by diversity: the types of 

employment that they have, the duration in terms of hours, days and months, the stability of this work as 

well as the need for secondary jobs. Results will also be presented with regards to children’s work and their 

contribution to the family. 

Major Characteristics of the Labour Force and Market 

A High Level of Unemployment? 

Figure 20 shows that active people represent 40.4% of the population aged 15 and more, 21.5% of the 

entire population and 41.4% if one considers the population aged 15 to 64 years old. People in charge 

of household tasks, essentially women aged above 14 represent 43.2% of the population of working age 

(age 15 to 64 ). This means that the level of unemployment is high. But if is measured only the persons 

unemployed, immediately available for a work and effectively looking for a job, then the level of unemployment 

drops considerably to 2.4% of the population aged 15 to 64. In this case, women in charge of household 

tasks are not considered as unemployed. Measure of unemployment is thus a complex matter that relies on 

a defi nition that excludes work inside the house because not generating any income. 

19 For more information about unemployment measure see http://www.ilo.org/public/english/employment/strat/kilm/. 

20 See ALDEN W. L. (2004); op cit. 


Figure 20. Distribution of All Afghans Above 14 according 

to the Employment Situation 

9.1% 

2.6% 

0.9% 0.2% 

0.1% 

0.0% 

Working (41.4%) 

Seeking Job (2.4%) 

Persons in Change of the 

Household Tasks (43.3%) 

Student (9.1%) 

Too Old to Work (2.6%) 

Long Disease (0.9%) 

Not Working, Not Looking 

43.3% 

41.4% 

for a Job (0.2%) 

Too Young to Work (0.0%) 

Other (0.0%) 

2.4% 

Figure 21 (and Table 33 in the Annexure) show that the situation regarding employment is quite different for 

persons with disability and the non-disabled. The difference between the two groups is statistically signifi cant. 

The same observation goes for people in charge of household tasks. Disability impedes both professional 

activities and household tasks. In the fi rst case, men are a majority; in the second it is the women who are 

primarily concerned. 

Figure 21. Distribution of Persons Above 14 according to the Employment 

Situation 

Non-Disabled 


50 

45 

40 

35 

30 

25 

20 

15 

0 

Working 

Seeking 

Job 

Household 

Tasks 

Student/ 

Scholar 

Too Old to 

Work 

Too Young to 

Work 

Long Disease 

Not Working, 

Not Looking 

for a Job 

Other 

The proportion of active members in a household is a relevant indicator of vulnerability. The risk of shocks 

leading to poverty is lower when more active people can face the unexpected diffi culty. Only a minority of 

households do not have any working member. These households rely on relatives outside the household 

for their subsistence and they are most probably particularly at risk of falling into poverty. There is a 

signifi cant difference between households with persons with disability and households with non-disabled. 

A large majority of both groups of households reported having less than 25% of household members 

working. A higher proportion (62.6%) is observed for lower employment ratio among households with 

a person with disability than in non-disabled households (59.0%). Hence, this constitutes a distinct 

indicator of higher proportion of households at risk of unpredicted shocks. On the other hand, a signifi cant 

higher proportion of households without persons with disability reported having more than 25% of active 

members. 


19

Figure 22. Distribution of Households according to the 

Employment Ratio 

70 



60 

50 

40 

30 

20 

10 

0 

No One Less than 25% 25 to 50% 50% to 75% More than 75% 

The ratio of employment in the household does not provide the entire information about the level of vulnerability 

of the household. The existence of women and children working also gives insight for understanding of the 

level of welfare of the household. 

Level of Activity of Women: How to Measure the Work Carried out within the Household and the 

Compound? 

Men and women with disability have greater diffi culty to secure employment compared to non-disabled 

persons. But the situation is worse for women in general. In fact, Figure 23 (and Table 35 in the Annexure) 

show that women, disabled or not, are very scarcely present on the labour market (6% are active). This is 

due to string cultural norms and the fact that women are most often not allowed to go outside the house 

in the fi eld. But women are responsible of all household tasks: looking after children and elders, preparing 

meals, fetching wood and water if they are not too far, cleaning the house and the compound, etc. 90% 

of women aged 15 to 65 carry out all these tasks, which are physically demanding. The situation of work 

and employment is even worse for women with disability. Hence Figure 23 further shows that a majority 

of women with disability do not have the capacity to do chores that are expected of women due to their 

impairment. This in turn might jeopardise their chance of getting married, impact their position within the 

family and the community, and reduce their capabilities in Afghan society. 

Figure 23. Distribution of Persons Aged 15-64 according to the 

Employment Situation and Gender 

90 

80 

70 

Non-Disabled Men 

Disabled Men 

Non-Disabled Women 

Disabled Women 

60 

50 

40 

30 

20 

10 

0 

Working Not Working Household Tasks 


Sometimes alongside household chores, women have an income-generating activity or a few agricultural 

tasks: farming and herding livestock. Yet, in Pashto areas particularly, women are often not allowed to farm 

and herd livestock. Therefore, the fi gure of 6% probably underestimates the exact level of activity of women. 

In reality, when asked more in-depth questions 21 about income-generating activities, the rate of employment 

of women reaches 13% for non-disabled women and 10% for women with disability as shown in Figure 24 

(and Table 36 in the Annexure). 

Figure 24. Level of Employment 

Considering Additional Activities 

90 

80 

Non-Disabled 


70 

60 

50 

40 

30 

20 

10 

0 

Male Paid Employment 

Female Paid Employment 

The difference of level of employment, especially for women (as shown between Tables 35 and 36 in the 

Annexure) is due to two phenomena. Firstly, people tend to consider that women do not work when they have 

a small job with little and irregular income. When surveyors pursued and asked about the activity during the 

day, then it sometimes appeared that the interviewee was in fact carrying out some kind of work. Secondly, 

women declare their household activities: therefore they are not registered as having a paid employment in 

the family questionnaire. In the adult questionnaire, they are asked about both types of activities. 

The fact of being head of the household is closely linked to the employment situation, more so than age or 

status. Table 37 in the Annexure shows that both men and women, when they are head of their household, are 

most often active. Even if only 2.6% of women are at the head of the household, 30.6% of them are active, 

while only 6.0% of other women aged above 14 years old are active. A similar disparity exists between men 

heads of household: 87.6% of these have employment, whereas the proportion of active men is 59.7% 

among the other men in the household. 

Professions of Afghans: A Majority of Farmers 

Among those who are working, Figure 25 in next page shows that 35.7% of active Afghans are owners of the 

land they cultivate or have it under mortgage. In second position, people having another type of independent 

activity represent 18.6% of the active employed population. Considered together, it appears than more 

than half of the active employed population is composed of self-employed people. 15.6% are 

wageworkers, which is a more stable status. These persons usually benefi t from a monthly wage and they 

have (well) defi ned working conditions: fi xed working hours, fi xed wage, specifi c tasks and working location. 

The rest of the active employed people (30%) all have a precarious working status: family helpers, seasonal 

and occasional workers, and daily workers. Only 0.1% of Afghans employ other people in their business, 

which represents just a few thousand people. 

21 The questions in the adult questionnaire are: Do you currently have a (regular or irregular) work? Did you work or have a job for at least 

one hour per day during last week? Did you work or have a job for at least one day during last month? If you are not working, for what 

reason? Even if you stated that you have not worked last month, have you carried out one of the following activities to help? (and follow 

a list of occurrences of possible tasks). 


21

Figure 25. Distribution of Active People above 14 by 

Employment Status 

18.6% 

5.8% 

1.3% 

2.8% 

15.6% 

0.1% 

0.1% 

35.7% 

Landowner/ 

Mortgager 

Daily/Weekly Wage 

Worker 

Contract Worker 

Occasional Worker 

Apprentice 

Family Helper 

Self Employed 

Employer 

Other Status 

20.0% 

A multitude of professions exist in Afghanistan. Dozens of professions were identifi ed during the survey and 

were grouped into 68 types as shown in Table 38 in the Annexure and Table 4 below. The most common 

profession is farmer (39.7%). Farmers are usually owners of their land or rent a piece of land from someone 

against part of the crop or/and a rent. Shepherds and labourers are other professions of the agricultural 

sector, which represents almost 45% of all actives in Afghanistan (see Figure 26 p. 24). 

Table 4. Distribution of Active People by Main Professions 

Professions Number Percent by Category 

Shepherd 203310 3.8 

Craftsmen 107826 2.0 

Carpet/rag weaver 285803 5.3 

Driver 215651 4.0 

Electrician 16239 0.3 

Farmer 2126633 39.7 

Building worker 516394 9.7 

Labourers 388432 7.3 

Mechanic 98082 1.8 

Mollah 51315 1.0 

Policeman, soldier 97433 1.8 

Public employee 157192 2.9 

Teacher 170183 3.2 

Tailor 108475 2.0 

Shopkeeper 381287 7.1 

Street vendor and other street service providers 131859 2.5 

Intermediary professions 127962 2.4 

Higher status professions 76647 1.4 

Other little jobs 61058 1.1 

No answer 28580 0.5 

Source: NDSA 


Workers in the construction sector represent almost 10% of all active people. The considerable reconstruction 

effort since the end of 2001 explains the fact that many people fi nd a job in building activities. A number 

of people with a small capital open shops of various kinds and do small trade. The wealthiest open a shop 

(7.1% of actives); the poorest are street vendors (2.5%). Peace is also characterised by the revitalisation of 

travels and transport. A lot happens by road in a country where a majority of transportation is done by cars 

and trucks. As a result the profession of driver is quite common: 4.1% of the labour force. 

The State has become an important employer. The huge effort made in the education sector can be seen by 

the high number of teachers (3.2%). This profession is in rapid progression, not only in public schools, but 

also in a fl ourishing sector of private schools and vocational training centres (often run by NGOs) in various 

disciplines: languages (mainly English), computer studies, trade, craft, tailoring, secretarial work… 

The security needs in the country explain that security services represent almost 2% of the active labour 

force. Another 3% are civil servants in Ministries, provincial department, and other government offi ces. 

Table 5. Distribution of Active People by Sectors of 

Activities 

Sector of Activities Number % by Sector 

Agriculture (farming, etc.) 2399445.4 44.8 

Mining 22734.3 0.4 

Manufacturing (textile, crafts, carpet weaving, etc.) 341664.4 6.4 

Manufacturing (industry like carpentry) 59109.2 1.1 

Land and construction (house building) 606032.1 11.3 

Transport (taxi, bus, train, airplane) 229291.9 4.3 

Trade (sales, commerce, bazaar, shops) 795051.7 14.9 

Education or health 209805.3 3.9 

State and administration (offi ce, mullah, army) 379988.0 7.1 

Hunting or gathering 18837.0 0.4 

Banking services 8444.2 0.2 

Communication (Roshan, AWCC, AÏNA...) 5196.4 0.1 

Other services 270863.2 5.1 

No answer 3897.3 0.1 

Total 5350360.5 100.0 

Source: NDSA 

Distribution of the labour force according to sectors of activity as in Table 5 above refl ects the weight of the 

primary sector: 45.6% of the labour force works in the agricultural and mining sector. The industrial sector 

employs 18.8% of the labour force, including 11.3% in the building and construction segments. Finally, 

the tertiary sector, dominated by trade (almost 15% of all actives) also employs a large proportion of the 

labour force (35.5%). This distribution of the labour force by sectors of activities is the result of two main 

factors: absence of industry and development of public services such as education and health. Decades 

of confl ict had held up investment in the economic system, jeopardising the emergence of an industrial 

sector. Today a large proportion of manufactured goods come from nearby bordering countries such as 

Iran, Pakistan, China, Tajikistan and India. The public employees represent 7.1% of the labour force and 

this fi gure goes to 10% when part of the workers of the education and health sectors employed in public 

structures are included. 


23

Farmers: Heterogeneity and Diversity of Status 

What exactly is the status of the 44.9% of active people working in the agricultural sector? They are mainly 

in agriculture activities, the mining sector representing only 0.4% of employment. Heterogeneity is the norm 

for farmers’ status. 

Figure 26. Distribution of Farmers by Types of Status 

Landlord / Khan (4.8%) 

4.0% 

4.8% 

16.7% 

Landowner/Malik/ 

Zamindar/Mulkadar 

(16.7%) 

Farmer/Sharecropper/ 

Mortgager (39.8%) 

Tenant/Khistmand 

(7.3%) 

Labourer/Worker/Kargar 

(27.4%) 

Family Helper (4.0%) 

27.4% 

39.8% 

7.3% 

A major distinction can be made between those who own land and those who do not. A small group of 

farmers (4.8%) are landlords, owning more than 200 jeribs (40 ha). A second group of farmers (16.7%) 

is composed of landowners who have less than 200 jeribs. The majority of farmers are sharecroppers and 

mortgagers (39.8%) who own small land and are constrained to rent more land for farming. On the land they 

rent, they provide all materials needed (seeds, plough, animals and labour), however they keep only part of 

the crop (often less than 50%). They might have a garden but rent fi elds for wider cultivation such as food 

crops or poppy cultivation. 

A third group is composed of tenants who do not possess land but rent it according to different modalities: 

usually, in exchange of a part of the crop against the use of the land, payment of a rent, etc. Helpers are 

usually members of the family, mainly young boys, who help their father or brothers to cultivate the family 

land. 

The most vulnerable are undoubtedly the landless labourers who work for farmers and landowners on a 

daily, weekly or seasonal basis. Part of this group is also homeless and moves from village to village to offer 

their services. They have trouble fi nding work as villagers prefer to hire members of the family (who they 

sometimes do not have to pay) or other members of the village they know. Moreover, in case of natural 

disasters as it has been the case recently, this category of farmers is often without work. 

Activity and Disability 

To what extent are persons with disability working in Afghanistan? Figure 21 page 19 above (and Table 33 

in the Annexure) show that the rate of employment of persons with disability (33.8%) is a lot lower than the 

one of non-disabled people (41.7%). 

Different Types of Activities and More Precarious Status for Persons with Disability 

When they are active, persons with disability are in similar proportions and occupy jobs that have a more or 

less comparable status to those held by the non-disabled. Yet, as expected, persons with disability are less 

present in professions requiring physical strength and abilities: farmers, house-workers, drivers, mechanics… 

They are however, in signifi cantly higher proportion working as street vendors, shopkeepers and other small 


jobs. Non-disabled persons are a larger proportion of landowners or land mortgagers, while persons with 

disability are more often occasional workers. The latter are also slightly in higher proportion in self-employed 

activities which is often the status used for shopkeepers or street vendors. 

Table 40 in the Annexure shows that persons with disability are proportionally half the number of the nondisabled 

among wealthy landlords (2.7% against 5.7% for non-disabled). Nevertheless, the proportion 

of smaller landowners is the same for both categories (around 17%). On the other hand, persons with 

disability are proportionally more in the three most vulnerable statuses: tenants, labourers and family helpers. 

These results may lead to the same conclusion for Afghanistan as Erb and Harris-White made for India 22 : 

in an agrarian economy, only extreme disability is a barrier for employment in fi eldwork. But furthermore in 

Afghanistan, persons with disability are more vulnerable on the labour market. They occupy the most insecure 

employment status. 

Difficulties in the Workplace 

When asked about the diffi culties they face in their work place, a majority (58.8%) of active Afghans declared 

spontaneously facing no particular diffi culty. This is not the case for persons with disability who were only 

26.3% to report the same. 

Figure 27. Distribution of Active People by Types of 

Difficulties Faced in the Workplace 

58.8% 

10.4% 

17.3% 

0.0% 

5.1% 

0.2% 

2.8% 

5.3% 

Diffi cult to Reach my 

Work Place (10.4%) 

Work Painful/Dangerous 

(17.3%) 

Problem with Coworkers/ 

Employer (0.0%) 

Wage Problem (5.1%) 

Corruption (0.2%) 

Bad Weather (2.8%) 

Other/Dont Know (5.3%) 

No Diffi culty (58.8%) 

Persons with disability face far more often diffi culties in their workplace than non-disabled persons as shown 

in Table 41 in the Annexure and Figure 28 in next page. This is observed for all types of diffi culties directly 

related to the work situation. Accessibility of the workplace is a problem in a country with poor road networks: 

it is a key problem in 24.7% of cases for persons with disability and only in 11% of cases for non-disabled 

people. Diffi culties due to physical discomfort or pain as well as dangerous positions are also frequent for 

persons with disability (37.4%). But these problems also exist for non-disabled people (23.7%). Inequality 

of wages (14.6% and 7.5% respectively for persons with disability and non-disabled) and misunderstanding 

of the boss or co-workers (2.5% and 0.0%) are also more frequent for persons with disability than for nondisabled. 

The level of diffi culty is similar for both groups with regards to corruption (obligation to pay bribes) 

or bad weather. 

22 ERB S. and HARRIS-WHITE B. (2001), Outcast from Social Welfare: Adult Disability and Incapacity in Rural South India, Books for 

Change, Bangalore. 


25

Figure 28. Distribution of Active Disabled and Non-Disabled Persons by 

Types of Difficulties Faced in the Workplace 

70 

Non-Disabled 


60 

50 

40 

30 

20 

10 

0 

Diffi cult to 

Reach My Work 

Place 

Work Painful/ 

Dangerous 

Problem with 

Coworkers/ 

Employer 

Wage 

Problem 

Corruption 

Bad Weather 

Other/Don’t 

Know 

No Diffi culty 

In conclusion, the level of diffi culties is signifi cantly different between the non-disabled and persons with 

disability. Globally analysis shows that persons with disability experience a higher cost of working due to 

greater diffi culties faced in the workplace: securing employment requires greater efforts than for non-disabled 

people. There are a wide range of diffi culties: some are due to lack of adaptation of the work, inaccessibility 

of the place, stigma and misunderstanding of co-workers, unequal wage scales… 

Less Child Labour in Afghanistan? 

According to the International Labour Organization (ILO) 23 , “Economic activity is a statistical concept that 

encompasses most productive activities undertaken by children, whether for the market or not, paid or 

unpaid, for a few hours or full time, on a casual or regular basis, legal or illegal; it excludes chores undertaken 

in the child’s own household. To be economically active, a child must have worked for at least one hour on any 

day during a seven-day reference period.” 

The ILO states 24 that there were about 317 million economically active children aged 5 to 17 in 2004, of 

whom 218 million could be regarded as child labourers. Of the latter, 126 million were engaged in hazardous 

work. 165.8 million children between the ages of 5 and 14 are estimated to work in the world—at least 

74.4 million in hazardous work. The number of child labourers in both age groups of 5-14 and 5-17 fell by 

11% over the four years from 2000 to 2004. However, the decline was much greater for those engaged 

in hazardous work: the fi gure fell by 26% for the 5-17 age group, and 33% for the 5-4 age group. The 

incidence of child labour 25 (percentage of children working) in 2004 is estimated by ILO to be at 13.9% 

for the 5-17 age group, compared to 16% in 2000. The proportion of girls among child labourers, however, 

remained steady. The vast majority (70%) of these children are working in agriculture. Many children work as 

domestic help; urban children work in trade and services, with fewer in manufacturing and construction. Most 

of the active children are situated in Asia: 61% are in Asia, 32% in Africa, and 7% in Latin America. In Asia 

and the Pacifi c, the activity rate among children aged 5-14 was of 19.4% in 2000 and of 18.8% in 2004. 

The decline is limited, whereas it is massive in Latin America and the Caribbean 26 . 

23 See, INTERNATIONAL LABOR OFFICE (2006a), Out Of Work and in School: Our Development Challenge, Asia-Pacifi c Economic 

Cooperation, Publication of Project Experiences, 2001-2006 http://www.ilo.org/public/english/region/asro/bangkok/apec/download/ 

book.pdf, p. 15. 

24 See INTERNATIONAL LABOR OFFICE (2006b), The end of child labour: Within reach, International Labour Conference 95th Session 

2006 Report I (B), Geneva, http://www.ilo.org/public/english/standards/relm/ilc/ilc95/pdf/rep-i-b.pdf. 

25 To the international community, the term “child labour” does not encompass all work performed by children under the age of 18 years. 

The consensus view is that work that falls within the legal limits and does not interfere with children’s health and development or prejudice 

their schooling can be a positive experience. See Inter-PARLIAMENTARY UNION/ILO (2002), Eliminating the worst forms of child labour: 

A practical guide to ILO Convention No. 182, Handbook for parliamentarians No. 3-2002, (Geneva, p. 15. 

26 From 16.1% to 5.1% according to ILO (2006), op. cit., fi gure 1.2 p. 20. 


At fi rst glance, child labour does not seem as widespread in Afghanistan as it is in certain other countries of 

the Asia and Pacifi c region. Only 5% of children aged 7 to 14 years old were reported to be working by the 

head of household in the family questionnaire (Figure 29 below). This low number must be considered with 

caution due to the limited information given by the family questionnaire. Some of the children were declared 

as being scholars or student by the head of household (59.8% of the considered age group), but they may 

also work after their class, mainly during the harvest season helping the family in the fi eld. 

Figure 29. Distribution of Children Between 7 and 14 Years 

Old according to Employment Situation 

8.9% 0.6% 0.4% 

0.0% 5.0% 

25.4% 

Working (5.0%) 

Seeking Job (0.4%) 

Household Tasks (25.4%) 

Student (59.8%) 

Too Young to Work (8.9%) 

Long Disease (0.6%) 

No Working, Not Looking 

for a Job (0.0%) 

59.8% 

When all children who go to school but also do some work are considered together, 20.1% of children aged 

7 to 14 are working, 15.5% in the fi eld, and 4.6% in other types of jobs (Figure 30). 

Figure 30. Distribution of Afghan Children Between 7 

and 14 Years Old according to the Activity Situation 

15.5% 

Working in the Field 

Working in Other Job 

Not Working 

4.6% 

79.8% 

Table 6 gives an overview of children’s activities. 60.0% go to school and 76.6% help with all household 

tasks: cooking, taking care of elders and younger children, fetching water and cutting wood, etc. 20.2% also 

have a professional activity, mainly in the agricultural sector: animals husbandry, fi eldwork, etc. Days can be 

very long for children, especially in rural areas and for girls. 


27

Table 6. Activities of Children Aged 

6 to 14 

Children Activities Number % 

Going To School 3841451 59.8 

Working in the Field 1996463 15.5 

Working in Other Job 597198 4.6 

Household Tasks 10884804 76.6 

Source: NDSA. Note: some children have more than one activity, total not 

equal to 100%. 

The incidence of child labour in Afghanistan is thus above the regional average of 18.8%. But according to 

ILO 27 , “the labour force participation rate of children aged from 10 to 14 years is extremely high at 30-60% 

in countries with a per capita income of US$500 or less”. Afghanistan ranges at this category 28 , yet its level 

of child activity is slightly lower. 

Figure 31 shows that children with disability work less often than other children, especially for fi eldwork. They 

also help signifi cantly less within the house. This is explained by the physically demanding nature of the work 

both in the fi eld and in major household tasks such as fetching water, cleaning, cooking, cutting wood. The 

same trend is observed in town and in villages. 

Figure 31. Distribution of Children Between 6 and 14 

Years Old according to the Employment Situation 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

Help in the Field Other Work Help in the 

House 

Non Disabled 

Children with Disability 

No Activity 

The frequency of children working inside the house is attested in the Figure 31. 

Household Tasks 

Contribution of children to the household chores is very high. Tables 43 and 44 in the Annexure show that both 

boys and girls participate in household tasks and that for girls it is systematic: 91.5% of all girls carry out some 

of the household tasks. Even children with disability, especially girls (61.2%) participate in chores within the 

house. The large majority (58.7%) of children with disability work one or two hours while non-disabled children 

often work more than 3 hours (50.5% of them), especially girls (60.4% work more than 3 hours). If children 

with disability work less in terms of duration, and are a smaller proportion to do household chores, the proportion 

27 ILO (2006), op. cit., p. 22. 

28 Evaluations of per capita income for Afghanistan varies. Per capita income is evaluated at 822 USD in Purchasing Power Parity (PPP)- 

adjusted. UNDP (2004), “Security with a Human Face: Challenges and Responsibilities”, Afghanistan National Human Development 

Report, Kabul. According to DFID, average income would rather be about 300 USD per person, see http://www.dfi d.gov.uk/countries/ 

asia/afghanistan.asp. 


y types of tasks done is similar. Fewer boys with disability clean the house, fetch water or do the grocery than 

non-disabled boys, probably because of physical limitations of movement. Similarly, girls with disability are 

proportionately less to cook, clean, fetch water, do the laundry than non-disabled girls. 

Mainly Boys Help in the Fields 

Working in the fi eld is essentially a male affair. Girls do not frequently go out to work in the fi eld, except 

maybe in some Uzbek or Hazara regions. In Pashto areas and even in Tadjik ones, women and girls almost 

never work in the fi elds. When they do work in the fi eld, boys with disability work only one or two hours, 

whereas non-disabled boys can work up to eight or more hours when they do not go to school. A large 

majority, however, works less than four hours. It is mainly for harvesting, sowing and reaping that boys of 

the house are expected to help. Some of them are also in charge of an animal husbandry when the family 

possesses some livestock, and in this activity boys with disability are particularly present. 

Other Jobs 

Mainly in urban areas, a few boys have other types of jobs. A majority of young boys with disability are in 

apprenticeship (54.5%), more than the non-disabled boys (31.8%). The rest of the non-disabled active boys 

are equally distributed between fi xed jobs, helping someone, occasional jobs and independent jobs. A higher 

proportion of disabled boys also take on occasional and unstable jobs. 

A major benchmark to differentiate between poor people and those better off is the level of income. Yet, this 

information is not often reliable in surveys, especially in developing and transition countries and in traditional 

contexts. Whatever the context, people are reluctant to provide information pertaining to their income. As a 

result, income cannot be the only indicator to measure poverty but it can complement the analysis of basic 

goods and employment. 

High Inequality of Income in Afghanistan 

Measuring level of income is a challenge in many contexts. Earnings are taboo in many cultures and individuals 

do not easily reveal sources and amounts of their income. Nevertheless, economists and other specialists of 

poverty have developed several indicators based on income measures. These tools are useful for cross-country 

comparisons of distribution of income and other assets. 

Complexity of Measurement of Income 

Evaluation of income is a very complex issue. People always underestimate their income, sometimes because 

of lack of knowledge, sometimes in order to hide it. In fact, many activities generate irregular income. For a 

shopkeeper, the level of income is directly linked to the demand for his/her products. Farming income varies 

during the year, and is the highest after the harvest season. It also depends on the deal with the landowner 

for those who rent the land as well as landless labourers. Carpet weaving is also linked to the completion of 

a carpet. Thus, income may come in a household not on a monthly base: it may be seasonal, daily, weekly, 

quarterly… and very often irregular. The sale of newspapers or the repair of shoes is largely dependent each 

day on the number of clients. In all these cases, it becomes very diffi cult for the interviewees to give an 

estimation of their monthly income. 

Researchers have developed several techniques to evaluate income of households through surveys. The best 

way to measure activity income is to leave a notebook for accountability during a certain period of time, 

and then come to recollect it. But this was not possible during the NDSA, because of the cost of such a 

technique, the diffi cult access of some places and the security constraints. Another way to proceed is to collect 

information about expenses and savings. Doing so gives an idea of the income of an household. 

Moreover, very often, income is underestimated due to the fact that people tend to hide the real amount. 

Many reasons can explain this. Firstly some interviewees may have had hopes that the survey would bring 

some help: therefore, as already explained 29 , the team of survey always tried to make it clear that there 


29

would be no direct help linked to the survey. Secondly, people were not willing to openly claim their earnings 

for fear of being asked for money by their relatives or by the community if they found out about it and become 

the subject of envy and even jealousy. 

Lastly, income in Afghanistan is not systematically an individual indicator. Many people are working but earning 

little or no direct individual income in exchange for their work. All the men in the family may work in the fi eld 

but the crop will be sold by the head of the family who is in charge of the whole family and decides what 

expenditures need to be made. The same can be said for a shopkeeper working with his sons. The former will 

not grant a wage but will take care of all the needs of the latter. The same can be stated for a carpet weaver. The 

ladies and the children living in the household will all work on the carpet weaving but the income will usually 

be collected by the fi rst wife or the head of the household. Therefore, many working persons are considered as 

family helpers and do not directly earn any income. However, the NDSA team did not directly ask the amount of 

the household income since this does not always account for inequalities between family members. 

Measuring Inequality of Income 

A widespread measure of inequality is given by the Gini coeffi cient. The Gini coeffi cient is a measure of inequality 

of a distribution. It is defi ned as the ratio of area between the Lorenz curve of the distribution and the curve of the 

uniform distribution, and the area under the uniform distribution. It is often used to measure income inequality. 

In simple terms, experts use it to measure inequality regarding income. The Gini coeffi cient is measured 

between 0 (which corresponds to perfect equality e.g. everyone has the same income) and 1 (which corresponds 

to perfect inequality, e.g. one person gets all the income, and everyone else has no income). 

Table 7. Gini Coefficient for Income from Activity 

Estimated 

Value 

Standard 

Deviation Lower Bound Upper Bound 

Confi dence 

Level in (%) 

Actives Including Family Helpers 0.414 0.025 0.364 0.463 95 

Actives 0.404 0.026 0.354 0.455 95 

Source: NDSA. Note: DAD® Software. 

Inequality of income is rather high in Afghanistan, when measured with the Gini coeffi cient (See Table 7 

above). When family helpers working without earning a direct income are included in the analysis, the Gini 

coeffi cient for Afghanistan is of 0.41. On the other hand, if family helpers without direct income are excluded 

from the calculation, the Gini coeffi cient is of 0.40. Table 8 below provides an overview of inequality in the 

South Asia Region 

Table 8. Poverty and Inequality in the South Asia Region 

Inequality (Gini coeffi cient) 

Poverty headcount rate 

% Year % Year % Year % Year 

Notes 

Afghanistan n/a n/a 41.4 2005 n/a n/a n/a n/a For Gini coeffi cient, NDSA data. 

Bangladesh 25.9 1991-92 30.6 2000 58.8 91-92 49.8 2000 World Bank (2003) 

India (i) 29.0 93-94 32.0 1999-00 29.2 93-94 22.7 99-00 

Staff estimation and Deaton and Dreze (2002), the 

variance of the logarithm of per capita expenditure is 

used for inequality measure 

India (ii) n/a 93-94 33.0 1999-00 36.0 93-94 28.6 99-00 WDR 2006 

Nepal 34.2 1995-96 41.4 2003-04 41.8 95-96 30.9 2003-04 World Bank (2005) 

Pakistan 30.6 1998-99 28.4 2001-02 32.0 98-99 35.2 2001-02 Kijima, et.al. (2005) 

Sri Lanka 32 1990-91 40.0 2002 26.1 90-91 22.7 2002 Narayan and Yoshida (2004) 

Maldives n/a n/a 34.8 2002/03 n/a n/a 17.3 2002/03 Murgai (2004) 

Bhutan n/a n/a 41.6 2003 n/a n/a 31.7 2003 National Statistical Bureau, Bhutan (2004) 

Source:http://siteresources.worldbank.org/INTSAREGTOPPOVRED/Countries/20816264/regionaldataonpovertyandinequality.pdf 

Note: Poverty lines are defi ned differently across countries; so poverty headcount ratios are not comparable across countries. 

29 See BAKHSHI P. and al. (2006), op. cit. 


Comparing the Gini coeffi cient for Afghanistan and other countries in the South Asia region, shows that this 

indicator of inequality is almost the highest for Afghanistan. It comes just after Bhutan and is equal to Nepal. 

It is 13% above Pakistan, which presents the lowest level of inequality according to the Gini coeffi cient. It is 

not possible to compare present levels of inequality with the situation in the past as no data is available for 

Afghanistan. 

The level of inequality is also revealed by the distribution of monthly income as presented in Figure 32. 

Figure 32. Distribution of Monthly Activity Income for All Active People and Aged 15-64 

8.1% 

9.9% 

5.3% 1.1% 

6.0% 

26.5% 

15.1% 

11.1% 

12.5% 

10.3% 

16.9% 

O AFAs 

100 to 1000 AFAs 

1100 to 2000 AFAs 

2100 to 3000 AFAs 

3050 to 4000 AFAs 

4050AFAs to 5500 AFAs 

6000 AFAs and More 

Refuse or Don’t Know 

10.2% 

22.7% 

15.5% 

13.3% 

15.5% 

The distribution of monthly income explains why the number of people working but earning no income or 

less than 1000 AFAs is high (37.6% if no age group is considered and almost one quarter of all active people 

aged 14-65 according to Figure 32 and Table 47 in the Annexure). The proportion of family helpers earning 

no direct wage is higher at early and old ages. Working children, and, to a certain extend aged persons who 

are still active, do not receive any wage but are working to help other member of the family. It is not necessary 

a clear sign of inequality or a factor of deeper poverty in the Afghan society. Many children and elders help a 

member of the family in his activity and do not receive any direct wage, but benefi t from the general income 

of the household. 

Figure 33. Distribution of the Monthly Activity Income for 

Active Males Aged 15-64 

0 AFAs (8.8%) 

17.1% 

0.0% 

8.8% 

17.8% 

100 to 1000 AFAs (17.8%) 

1100 to 2000 AFAs (24.3%) 

2100 to 3000 AFAs (17.8%) 

3050 to 4000 AFAs (14.2%) 

4050 AFAs to 5500 AFAs (17.1%) 

6000AFAs and More (0.0%) 

14.2% 

24.3% 

17.8% 

Looking at the situation of males between 15 and 64 years old, the number of persons working but not earning 

any money decreases drastically (Figure 33). The average monthly income becomes 4187.6 AFAs and 17.1% 

earn more than 6000 AFAs a month. The median is 3,000 AFAs, which means that 50% of males above age 15 

and working earn less and 50 earn more. The upper decile – the 10% with the highest income – earns more 


31

than 7,500 AFAs a month. The 1% with the highest income earns more than 20,000 AFAs a month (400 USD), 

almost 7 times more than the median income and 4.8 times more than the average income. 

Comparing Income of Persons with Disability and Non-Disabled 

Comparing monetary income must be done with a lot of caution. Firstly, because, as already explained above, 

many active people do not receive an individual wage; it is included in the family income. According to Figure 

34 (and Table 48 in the Annexure), many active people are not paid, and there are probably more nondisabled 

persons in this case than persons with disability. This is explained by a higher rate of employment 

among non-disabled people who contribute to the family income by participating in a large array of activities 

for which the head of household is paid. In high ranges of income, the proportion of persons without disability 

is higher. But the level of disparity is not statistically signifi cant for higher levels of income; it is however 

signifi cant for the lowest levels (less than 2000 AFAs). Hence, persons with disability are signifi cantly a higher 

proportion to earn smaller wages than the non-disabled. 

Figure 34. Distribution of Active Persons according to the Monthly Professional Income 

Active All Ages 

Active Age 15-64 

30 

30 

Non-Disabled 


25 

25 

20 

20 

15 

15 

10 

10 

5 

5 

0 

0 AFAs 100 to 1100 

1000 to 2000 

AFAs AFAs 

2100 

to 3000 

AFAs 

3050 

to 4000 

AFAs 

4050 

AFAs to 

5500 

AFAs 

6000 

AFAs and 

More 

0 

0 AFAs 100 to 1100 

1000 to 2000 

AFAs AFAs 

2100 

to 3000 

AFAs 

3050 

to 4000 

AFAs 

4050 

AFAs to 

5500 

AFAs 

6000 

AFAs and 

More 

Focusing the analysis only on active men above age 15 as in Figure 35 (and Table 49 in the Annexure), clearly 

shows differences of level of income between disabled and non-disabled. Almost 50% of men with disability 

earn less than 2000 AFAs a month, while only 28.8% of non-disabled men earn the same. A proportion of 

46.3% of non-disabled men earns more than 3000 AFAs a month while only 28.1% of disabled men earn 

that much. 

Figure 35. Distribution of Active Men above Aged 15-64 according to 

the Monthly Professional Income 

30 


Non-Disabled 

25 

20 

15 

10 

5 

0 

0 AFAs 100 to 1000 1100 to 2000 

AFAs 

AFAs 

2100 to 3000 

AFAs 

3050 to 4000 

AFAs 

4050 AFAs to 

5500 AFAs 

6000 

AFAs and More 


Among higher monthly income, the difference of earnings is between non-disabled males and those with 

disability is statistically signifi cant. 

If professional income is concentrated among a few active people in the household, then redistribution of 

money and goods is also a widespread phenomenon inside the household and in the family. The individuals 

working usually give their income to the head of household, or to the woman in charge of expenditure. If 

any of them has specifi c requirements he/she requests the money from the head of the household. For this 

reason, disparity in earnings does not refl ect totally inequity among individuals as an important redistribution 

of resources takes place inside the household. 

Concluding Remarks 

The Afghan labour market is characterised by a dominant agricultural sector, which represents the majority of 

the Afghan work force. Men with disability have more diffi culty to work in the fi elds due to some impairments 

that make diffi cult to carry out physical tasks. It might be challenging in the near future to organise accessibility 

for farming. Yet, many other actions can be planed. 

Accessibility of women to the labour market is a fi rst important step to be taken. A large majority of women 

do not have income generating employment. 

On the other hand, children with disability aged 6-14 do work: they are just as many as non-disabled 

children in all jobs except fi eldwork. Almost half of them contribute to household tasks. Promoting school 

enrolment is the most effi cient way to reduce the most alarming child labour activities. By knowing to read 

and write, developing analytical skills and critical thinking, these children are more able to deal with their 

environment and get better working conditions in the future. 

Persons with disability, when they participate in the labour market, are present in the same professions as 

other Afghan workers. Yet, they occupy the most precarious positions: occasional workers, family helpers, 

etc. They also earn lower wages, especially women with disability. Equalisation of opportunities, promoting 

equal wages and fair labour conditions together with an employment obligation could be a signifi cant step 

forward. 

Disabled men do not work due to their impairment. Finding the way to allow them to contribute to the family 

welfare by their activity is a step towards alleviation of poverty. Access to employment for persons with 

disability is an effective way to fi ght poverty, reduce vulnerability, and strengthen social inclusion. Whenever 

a person contributes to the family welfare, her/his social status within the family improves. An obligation 

of employment, of at least 5% of persons with disability in the public sector, if correctly and effectively 

enforced, is a strong impetus towards ensuring that persons with disability have an equal access to the labour 

market. However, going a step ahead would mean including persons with disability in mainstream labour 

market programmes (private and public) and activities wherever it is possible, as a priority group. Persons 

with disability should also be offered equal opportunities and full participation in programmes such as cash 

for work or food for work or the National Solidarity Programme of Afghanistan, that aim to provide jobs in 

projects undertaken at the community level. 


33

Fewer Assets for Persons with 

Disability: a Vulnerability Issue 

Afghans are systematically at risk of falling into more severe poverty, especially in rural areas: this constitutes 

their vulnerability. These forms of vulnerability are studied through the evaluation of assets possessed by 

the household as a unit. As the NRVA 2003 puts it “those households with a fewer assets are more 

likely to report a worse economic situation 30 ”. At this point it seems essential to ask what the assets 

relevant in order to overcome unexpected external shocks are. Various ways of classifying durable goods can 

be suggested: 

Common goods, usually for consumption or production; 

Luxury goods which are sign of the social position: big size house, costly animals, TV set and car; 

Assets that can be used to fi ght against vulnerability and are useful to overcome shocks: equipment for 

agriculture and for the house. 

High amount of material possession is a relative indicator of well being of the household. Yet, possession of 

vast land on one hand and reliable and extensive social networks on the other, are invaluable assets useful to 

escape poverty and face risks, and not being vulnerable to unexpected shocks. Having more assets increases 

the capability to overcome diffi culties. It is a determinant factor in the capacity that individuals have for 

resilience. 

In this section, comparison with NRVA 2003 will be provided wherever it is relevant. Globally, it appears that 

major trends are similar in both surveys, even if fi gures can be different for some assets. 

Durable Goods: Relative Indicators of Well-Being 

One can considers different ways of classifying durable goods according to: 

Their function: equipment for production (tractor), or home appliances (radio, refrigerator, TV set...); 

The way they symbolise the standard of living of the house: a kerosene lamp is a major asset for a poor 

family, which is used for light, whereas it is basic equipment for the majority of Afghan families. 

In both cases, durable goods can be considered as assets for the household since they can be used to increase 

capability and therefore, reduce vulnerability. 

Equipment of the House and Common Goods: Benchmarks for 

Wealth 

During the survey, people were asked about the possession of goods and equipment by any member of the 

household or by the household as a whole. These include very basic and non-costly goods such as kerosene 

lamps, which almost all families own except the poorest strata (97.3% of households reported having one), 

pressure cooker or radio are respectively present in 62% and 68.9% of Afghan households. Other more costly 

goods or equipments such as cars or television sets are owned by 4% and 21.1% of Afghan households. 


THE MINISTRY OF RURAL REHABILITATION AND DEVELOPMENT (2004), op. cit. p.52. 

Fewer Assets for Persons with Disability: a Vulnerability Issue 

35

Another striking result is that 77.4% of Afghan families possess their house. The ownership of a house is an 

important asset to reduce vulnerability. 

These results are not very different for persons with disability and non-disabled. A statistically signifi cant difference 

of 5.3% exists for possession of a sewing machine between the two types of households; this difference is of 

4% for a radio. But for ownership of other goods and equipment there is little difference: ranging from 0.3% 

for cars or ovens, to 2.1% for generators or 2.2% for televisions. When calculated by referring to the number of 

households possessing these items, the difference is extremely limited and non-signifi cant. 

Figure 36 (and Table 51 in the Annexure) compares the situation of the two types of households for 

possession of material goods and equipment. It further explains the similarity between the two pertaining to 

the ownership of goods. With slightly different weighting between the two types of cross tabulations 31 , results 

are very similar. The statistically signifi cant differences are for: 

Radio (4.5% more households of non-disabled own one); 

Pressure cooker (4.8% more households with non-disabled members have one); 

Motorbike (3.2% more households with non-disabled members have one); 

Tractor (0.9% more households with non-disabled members have one); 

Sewing machine (6.7% more households with non-disabled members have one). 

Kerosene lamps and pressure cookers are not considered as luxury goods except for the extremely poor 

households, who cannot afford one. The figures above demonstrate that households with persons 

with disability consistently have fewer assets and are more vulnerable for all durable goods and 

equipment except for basic goods such as a pressure cooker. 

In the case of motorbikes, the hypothesis that some of these households do not have use of a motorbike if no 

one is able to drive it 32 , can be put forward. For ownership of other items, the variations are again very low: 

the highest is 1.7% for the motorbike. The lowest is 0.2% for ovens and hotplates, which are certainly not an 

expensive equipments characteristic of wealth, but the lack of electricity makes their use limited. For tractors, 

the difference is small but statistically signifi cant due to the low numbers of households having one: this 

might indicate that in very wealthy households differences between households with persons with disability 

and non-disabled households are signifi cant. 

Figure 36. Distribution of Households regarding Ownership of Goods or 

Equipment 

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

Radio 

Television 

Pressure 

Cooker 

Oven, 

Hotplate 

Refrigerator 

Bukhari 

31 

In Figure 36 and Table 51 the number of households without disabled members is weighted using the ratio of the number of households 

in the country divided by the number of households without a person with disability in the sample. The methodology used is based on 

the interview of one control non-disabled person every fi ve households without people with disability. Each of the non-disabled persons 

interviewed living in a household with non-disabled, represents all of them. See BAKHSHI P. et al. (2006b), “Conducting Surveys on 

Disability: a Comprehensive Toolkit”, Handicap International and Government of Afghanistan, Lyon and Kabul. 

32 

See BAKHSHI P. et al. (2006a), op. cit. for more about ability to drive a bicycle… 



Bicycle 

Motorbike 

Car 

Tractor 

Generator 

Kerosene 

Lamp 

Sewing 

Machine 

House or 

Apartment 


Figure 37 (and Table 52 in the Annexure) show strong statistically signifi cant differences between urban 

and rural settings, with an exception for kerosene lamps that are owned by almost all households. Rural 

households generally possess fewer assets than urban ones, except for houses: this might indicate that 

rural households are poorer but less vulnerable in case of an external shock. In fact, owning a house can 

avoid becoming homeless as a direct consequence of an external shock except in some cases of fl ood... It is 

probable that people who have a partial mortgage on the house also declare themselves as being owners. 

Figure 37. Distribution of People regarding Possess of Goods or Equipment in 

Urban and Rural Areas 

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

Radio 

Television 

Pressure 

Cooker 

Oven, 

Hotplate 

Refrigerator 

Bukhari 

Bicycle 

Motorbike 

Car 

Tractor 

Generator 

Kerosene 

Lamp 

Sewing 

Machine 

House or 

Apartment 

Urban 

Rural 

In rural areas, 67.7% of households owned a radio in 2005, and this result is consistent with NRVA 2003 33 

result, which found 65% of households. 86.7% of urban households own a radio. For sewing machines, the 

proportion of rural households owning one is higher than in the NRVA 2003. 46.2% of rural households 

own a sewing machine (64.3% of urban households) according to the NDSA data, while only 31% of rural 

households were reported owning one by the NRVA 2003 survey. The gap is diffi cult to explain and nothing 

indicates a sole valid reason that could explain the increase of more than 10% of acquisitions of such 

equipment during the two-year period between the surveys. Is the reason to be fi nd in the aid of INGOs ? 

Some distribute sewing machines through livelihood projects… 

The difference for tractors is signifi cant but almost nobody has one. It is probable that urban households 

owning one have fi elds just outside town. It is striking how much better off, in terms of possession of goods 

and equipment, urban households are: 

The highest difference is for television sets: 58.6% of urban households own one against only 9.8% of 

rural ones, which is understandable mostly because of lack of main power in rural areas and because 

of the still relatively high price of a TV set. There is also a concept of community televisions, which is 

widespread in these rural areas, where TV sets are usually in a shop or tea-house (Tchaikhana) and are 

watched by a number of people. 

Car (10.8% of households own one in town, 2.2% in rural areas; NRVA 2003 found 4% for ownership 

of car or truck in rural areas); 

Bicycle (respectively 53.8% urban and 24.6% rural; 25% in NRVA 2003 for rural households); 

Motorbike (respectively 15.7% urban and 8.2% rural, almost the same as in NRVA 2003: 8%); 

Refrigerator (respectively 20.6% urban and 0.3% rural); 

Generator (respectively 27.8% urban and 7.0% rural), etc. 

34 

VULNERABILITY ANALYSIS AND MAPPING UNIT OF THE WORLD FOOD PROGRAMME AND THE VULNERABILITY ANALYSIS UNIT OF 

THE MINISTRY OF RURAL REHABILITATION AND DEVELOPMENT (2004), op. cit., p. 41. 


37

The quantity of equipment possessed by rural households is very low, and this illustrates the high difference 

in livelihood assets and wealth between rural and urban Afghanistan. The only exception is for ownership of 

houses: rural households usually own their houses (82.3% of them). Renting of houses is far more common in 

towns where one-third of households rent their living spaces. The prices of real estate – especially in regional 

centres and above all in Kabul city where the international community is very present – are skyrocketing, this 

factor may also explain this difference. 

As shown in Figure 38, even if households headed by a woman are relatively more present in urban areas 

than those headed by a man, they systematically possess less goods, and equipments, with the exception of 

sewing machines that are often used by women for income generating activities. 

Figure 38. Distribution of Households according to Gender of the Head of the 

Household for Ownership of Goods or Equipment 

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

Radio 

Television 

Pressure 

Cooker 

Oven, 

Hotplate 

Refrigerator 

Bukhari 

Bicycle 



Motorbike 

Car 

Tractor 

Generator 

Kerosene 

Lamp 

Sewing 

Machine 

House or 

Apartment 

Thus, households headed by a woman are statistically signifi cantly less than men headed households to 

own: 

Radio set (52.5% against 73.2% for households headed by a man); 

Pressure cooker (50.8% against 59.0% for households headed by a man); 

Refrigerator (2.8% against 5.5% for households headed by a man); 

Car (0% against 4.5% for households headed by a man). 

If households headed by a woman owning a motorbike are as numerous as those headed by a man, a possible 

explanation might be that men living in the households headed by women buy it whenever they can for 

transportation. 

72% of households headed by a woman own their house, which is a strong warrantee against the risk of 

falling into poverty. Yet, the remaining third of these households are particularly vulnerable because they do 

not own their house and in fact, barely have anything to call their own. 

Overall, more than a third of all households do not possess anything except a kerosene lamp. 

Results further indicate that households headed by a woman are more at risk of poverty. Here 

again, the disability factor does not seem to have a strong impact on ownership of goods. 

Widespread Ownership of Livestock 

Results regarding the ownership of livestock are in line with the analysis above that indicates the general 

similarity of livelihood level between persons with disability and non-disabled. A high number of Afghan 

households possess at least one animal. Livestock is a good indicator of the ability to face unexpected 

shocks and of the decrease of vulnerability. 


The analysis in terms of households with persons with disability and households without persons with disability 

leads to similar conclusions. A large number of both groups of households possess livestock (See Figure 39 

and Table 58 in the Annexure). It is interesting to notice that households without persons with disability more 

often own livestock, which is expensive, and are considered more valuable such as cows, horses, donkeys, 

roosters and camels. This means that households with persons with disability are among the most vulnerable 

as they do not own as many useful assets. 

Figure 39. Distribution of Households according to the Ownership of 

Livestock 

80 

70 



60 

50 

40 

30 

20 

10 

0 

Owns 

Animals 

Sheeps Cows Goats Horses Donkeys Chickens Rooster Camles 

More in-depth analyses of ownership of livestock by type of animal yield no significant differences between 

persons with disability and non-disabled at the level of individuals. But at the households level, a few 

differences are signifi cant between the two types of households (see Table 59 in the Annexure). Nevertheless, 

the percentage of differences remains limited. 

The highest difference observed between households is a statistically signifi cant 4.7% for families not 

possessing goats: a higher proportion of households with persons with disability do not own goats. 

Statistically signifi cant differences are observed in two situations, but in both cases, the difference is a few 

percentages: 

On one hand, households with persons with disability own fewer animals that are most commonly 

owned such as poultry, sheep, cows, and goats; 

On the other hand, they less often own very expensive animals such as roosters (used among other 

things for fi ghting), horses or camels. 

As a conclusion, it can be noted that the difference between households is not significantly 

observable among poor households, but that it becomes more important among households, 

which are better off. This leads to believe that poverty is often chronic and multifaceted, infl uenced by a 

number of variables. Disability affects living conditions once all the other factors have been tackled, making 

persons with disability more vulnerable and more at risk of remaining in poverty. Policies geared towards 

fi ghting poverty must also focus on ensuring security and strengthening capability by reducing vulnerability 

of households that have a disabled member. 

As shown in Figure 40, the same conclusion can be made for households headed by men or women. Both 

possess livestock. To go one step further in the analysis, it is interesting to distinguish between types of 

animals owned: it is not the same to own a chicken or two own four horses for Buskachi! While households 


39

headed by a woman more often own chickens and birds, households headed by a man more often own 

expensive animals. For instance, 4.6% of the latter own a horse and 2% own camels whereas no household 

headed by a woman in the sample own any of these. 

Figure 40. Distribution of Households according to the Gender of the 

Head of the Household and the Ownership of Livestock 

80 

70 

Households Headed by a Man 

Households Headed by a Woman 

60 

50 

40 

30 

20 

10 

0 

Owns 

Animals 

Sheeps Cows Goats Horses Donkeys Chickens Rooster Camels 

The major statistically signifi cant and important differences are observed between households headed by a 

man and those headed by a woman. The latter never own livestock of great value such as horses or camels. 

They invariably possess fewer animals, except for the group of 1 to 3 chickens. Above 7 chickens, a larger 

number of households headed by men are observed. The relatively frequent ownership of chicken and birds by 

households headed by women is explained by the high number of women head of households that depend on 

chicken breeding for an income for the family, sometimes with the help of NGOs 34 . The recent epidemic of bird 

fl ue represents an important threat for these households. But a large number of animals as a sign of wealth 

or a security asset are mainly observed in households headed by man: 

0% of households headed by a woman against 7.1% of those headed by a man possess more than 6 

sheep; 

2.4% of households headed by a woman against 5% possess more than 4 cows; 

0% of households headed by a woman against 8.9% possess more than 2 donkeys; 

0% of households headed by a woman against 1.7% possess more than 2 roosters. We know that the 

value of roosters can be high when they are well trained for fi ghts. 

Again the possession of livestock by the households headed by women and the types of possession are among 

other indicators that show that these households are among the poorest. 

Not surprisingly, the main difference is observed between rural and urban areas. Twice more households own 

livestock in rural areas (84.3%) than in urban ones (46.0%) as shown in Figure 41. This result corroborates 

NRVA 2003 fi ndings: 86% of the sample households own at least poultry 35 . Yet, very slight differences can 

be noted. 

34 For instance, in Kabul province, chicken breeding support to women head of family is one major programme of Care International. 


THE MINISTRY OF RURAL REHABILITATION AND DEVELOPMENT (2004), op. cit., p. 48. 


Table 9. Ownership of Livestock: Comparing 

NRVA 2003 and NDSA 2005 

Types of Livestock 

NRVA 

NDSA 

Rural 

NDSA 

Urban 

Donkeys 55.0% 41.2% 11.4% 

Cows 45.0% 52.5% 20.0% 

Horses 4.0% 5.2% 0.9% 

Camels 2.0% 2.4% 0.4% 

NRVA 2003 found that 55% of rural households own donkeys, 45% milking cows, 4% at least one horse 

and 2% a camel. NDSA results show that in 2005: 

41.2% of rural households and 11.4% of urban households own at least one donkey; 

52.5% of rural households and 20% of urban households own at least one cow; 

5.2% of rural households and 0.9% of urban households own at least one horse; 

2.4% of rural households and 0.4% of urban households own at least one camel. 

Considering the confi dence interval for this data, the results appear to be similar with the exception of the 

proportion of households possessing donkeys. The difference in proportion of possession of cows might be 

explained by the fact that NDSA did not differentiate between milking and non-milking cows. 

Figure 41. Distribution of Households regarding Ownership of Livestock 

in Urban and Rural Areas 

90 

80 

Urban Households 

Rural Households 

70 

60 

50 

40 

30 

20 

10 

0 

Owns 

Animals 

Sheeps Cows Goats Horses Donkeys Chickens Rooster Camels 

Again livestock can be classifi ed into various different types: 

Some are considered as assets used for transportation, agricultural production (ploughing); 

Some are used for consumption: cows or chicken; 

Some directly provide an income when bred for selling: chicken, roosters. 

The degree to which they contribute to the reduction of vulnerability will depend upon other factors, but in 

general they all contribute to enhancing household capabilities. 


41

Land Ownership: Do Households of Persons with Disability Have 

Smaller Land Holdings? 

Half of the Households own Land 

Possession of land is more common in rural communities as already stated and even more so in Afghanistan. 

Movements of population due to the unending confl ict have transformed the issue of ownership of the land 

into a major source of dispute between people. The measure of land in Afghanistan is in biswa and jerib. 1 

biswa is the equivalent of 100 sq.mt. and there are 20 biswa in 1 jerib (2000 sq.mt.). 

According to Figure 42 (and Tables 61 to 65 in the Annexure), 55.2% of households own land, without any 

signifi cant difference between households with persons with disability and households with non-disabled 

people. 

Figure 42. Distribution of Households regarding Ownership of Land 

70 

60 

50 

40 

30 

20 



Non-Disabled 


Urban 

Rural 



Men 

Women 

Women in Urban Area 

Women in Rural Area 

10 

0 

Own Land 

Results regarding land owned by the interviewee herself or himself 36 as presented in Figure 42 (and Table 

65 in the Annexure), show that the difference between persons with disability and non-disabled is high and 

statistically signifi cant. But these results have to be considered with caution. In fact, the cultural tradition in 

Afghanistan is community-based. Therefore, the land is usually considered as belonging to the whole family. 

When NDSA surveyors insisted to know if part of the land belonged to the individual interviewed herself/ 

himself, the answer might have been affi rmative when in fact, a given land was considered as shared by all 

the (male) members of the family. This leads to a striking and statistically signifi cant result: almost 10% 

more of persons with disability declare owning part of the family land. 

The main disparity is between urban and rural households. Twice more people own land in rural areas 

than in urban zones. The land prices are a lot higher in urban areas, especially in major towns where fi elds are 

not available and property documents do not exist, reducing transactions made on lands. 

Another distinction that can be noted is between households headed by a woman and those headed by a 

man. The latter are a lot more often owner of lands (56.5%) than the former (30.5%). Nevertheless, when 

the interviewee was directly asked if he/she owned part of the family land the proportion was similar between 

both households, but slightly higher among households headed by a woman. 

36 

Their own answer to the question. 


The size of land also varies widely among households and families. The difference between households with 

persons with disability and households with non-disabled people regarding ownership of land is only statistically 

signifi cant for large size of lands (See Table 66 in the Annexure). This is even more striking for cultivable land 

(See Table 67 in the Annexure). If the proportion of households which do not own any land is the same for both 

types of households; the difference is of 2.5% more for households of non-disabled people only when the land 

considered is more than 40 biswas. This difference is of 3.4% for land which is cultivable. It can be assumed 

that if the difference between the two types of households is not important or significant when under 

or close to the poverty line, the difference becomes significant for wealthy family. Thus, among families 

owning land, the average size of land is respectively 102 and 120 biswa (between 1000 and 1200 sq. mt.) in 

urban and rural areas for family with a person with disability, and respectively 154 and 113 (between 1540 and 

1130 sq. mt.) in urban and rural areas for family without a person with disability. 

All together, the average size of land owned is 149 and 113.5 biswa (1490 and 1135 sq. mt.) respectively 

in urban and rural areas. It seems that wealthy families owning large size of lands often live in urban 

areas, even if the land is possessed in the village of origin. 

Tables 68 and 69 in the Annexure show that households headed by a woman are statistically signifi cantly 

a lower proportion to own land (30.5%) especially cultivable land (29.9%), than those headed by a 

man (respectively 56.5% and 54.3%). This result is different from NRVA 2003 that found that 56% 

of female headed of household own some land. But if only rural areas are considered, women head of 

households are a proportion of 44.5% owning land in their own right (but only 8% in urban areas). For 

larger size lands, almost fi ve times more of households headed by a man own fi elds of more than 40 

biswa. The gap is slightly less for cultivable land. 

Women heads of household own land, but other women also do (see Figure 42 in previous page). No 

law in Afghanistan prohibits women from possessing land. Of course, especially in Pashto tradition, 

women are scarcely landowners and rarely cultivate fi elds. Yet, some do. Women receive land through 

inheritance from their fathers or their husbands, even if their share is less important than the share of 

the men. Sometime, daughters give up their right on the land to their brother. Widows usually keep their 

land when they do not live with their sons, even if someone else is cultivating them. 

Measure of Inequality: Lorenz Curves and Gini Coefficients 

The Lorenz curve measures inequalities. It is a graphical representation of the proportionality of a distribution 

(the cumulative percentage of the values of land). The curves look at the distribution of land among individuals 

and households. 

Figure 43. Lorenz Curves of Land Ownership Inequalities 

Cumulative Distribution of Land 

1.00 

0.95 

0.90 

0.85 

0.80 

0.75 

0.70 

0.65 

0.60 

0.55 

0.50 

0.45 

0.40 

0.35 

0.30 

0.25 

0.20 

0.15 

0.10 

0.05 

0.00 

0.000 

0.025 

0.050 

0.075 

0.100 

0.125 

0.150 

0.175 

0.200 

0.225 

0.250 

0.275 

0.300 

0.325 

0.350 

0.375 

0.400 

0.425 

0.450 

0.475 

0.500 

0.525 

0.550 

0.575 

0.600 

0.625 

0.650 

0.675 

0.700 

0.725 

0.750 

0.775 

0.800 

0.825 

0.850 

0.875 

0.900 

0.925 

0.950 

0.975 

0.000 

Cumulative Distribution of Land 

Land Ownership Households without Persons with Disability Land Ownership Households with Persons with Disability 

Land Ownership All Households 

Cultivable Land Ownership All Households 

DAD ® Software. 


43

The four curves show the distribution of land among households. 

The fi rst one related to households without a person with disability owning land; 

The second one refers to family with a person with disability owning land; 

The third one refers to family in general owning land or not; 

The fourth one refers to cultivable land distribution for all families. 

As Figure 43 clearly shows, all four follow a similar slope. In all cases people who do not own land at all are 

included. It appears that inequality of ownership is quite significant: 

For instance, 49.6% of the population do not own land; 

30% of the landowners own only 20% of the land; 

Moreover, if one considers all the households, including those not possessing any land, then 90% of 

households own 30% of the land; 

10% of the population are major landlords who own 90% of the land; 

Households with persons with disability are not in a worse situation than those without any person with 

disability. 

Table 10. Gini Coefficients of Land Ownership 

Land Ownership 

Estimated 

Value 

Standard 

Deviation 

Lower 

Bound 

Upper 

Bound 

Confidence 

Level in (%) 

Land Ownership 0.775 0.011 0.754 0.796 95 

Cultivable Land Ownership 0.775 0.012 0.752 0.799 95 

Land Ownership HH of 

Non-Disabled 0.775 0.013 0.750 0.800 95 

Land Ownership HH of 

Persons with Disability 0.776 0.018 0.742 0.811 95 

Source: NDSA. Note: Use of DAD ® Software for calculation. 

The Gini coefficient for the land distribution in Afghanistan is of 0.78, and corresponds to a very 

high level of inequality. The Gini coeffi cient for cultivable land is almost identical. This confi rms fi ndings 

from other studies 37 showing a high concentration of land among a minority of Afghans who are major 

landlords. Landownership is a good indicator of wealth in Afghanistan: in rural areas, itinerant labourers 

are landless and often among the poorest. NRVA 2003 estimated that 21% to 24% (according to type of 

analysis) of rural Afghans are landless. Confi rming results of the Lorenz curve, the Gini coeffi cient analysis of 

inequality show no signifi cant difference between the two types of households. 

Concluding on Durable Goods: Fighting Poverty in a 

Comprehensive Manner 

A few conclusions can be made regarding household commodities and living conditions. 

The main fi nding of this section is that disability within a household does not strongly impact the factors that 

determine vulnerability except to a certain extent for landownership. 

The two major elements that do seem to have an infl uence on these factors is the settings in which the 

households live (urban or rural) and the gender of the head of the household. 

However, disability seems to have an infl uence once a certain number of basic needs have been satisfi ed. This 

is evident in the fact that the difference between households of disabled and non-disabled appears clearly in 

the more advantaged social strata, even though these remain few in number. These results suggest that 

37 

See again ALDEN W. L. (2004); op. cit., p.25. 


it is when the living conditions improve that the impact of disability is stronger as this weighs 

down on the entire household. Thus, once fi ght against monetary poverty is underway, the main challenge 

remains to reduce vulnerability in the long-term. Public action will need to be focused on increasing assets, 

improving functionings and generally empowering persons with disability ensuring that their concerns are 

mainstreamed and they do not remain at risk of falling back into poverty when faced with unexpected 

external shocks. 

Debt and Donation: Assets or Factors of Vulnerability? 

This section looks at a wider defi nition of income: income through the social capital, i.e. the network of an 

individual that is supporting her/him. Usually this term is related to the monetary amounts that a person 

receives. But in traditional structures such as Afghanistan, it is essential to also take into account the other 

goods (food and clothing for example) that a person receives. This aspect of income is crucial for persons with 

disability since it determines the consideration and support that he/she has within the household. Moreover, 

in such social and cultural structures, the salaries are often paid in non-monetary terms, or given to the head 

of household for an effort of the family unit. All these aspects of “income” make it diffi cult to assess in terms 

of “how much” exactly is received by the individual. 

However, income remains different from donation since the former is remuneration for an effort, some form 

of work. A donation is money, goods or presents that are given by solidarity for example. A donation is defi ned 

by the fact that nothing is (offi cially) expected in return 38 . Lastly, a donation differs from a loan, which not 

only is explicit in monetary terms but is also expected to be paid back. Questions regarding income are asked 

directly to the interviewee and donations are an evaluation of money and goods given. 

Resort to Loan and Level of Debt: Higher for Persons with 

Disability 

The level of debt can be a factor of risk of falling into poverty or a way of drawing on resources to achieve 

certain functionings and increase capabilities. In fact, as loan is often a family matter in Afghanistan, if a 

person or his/her relatives cannot face his/her obligations of repayment, there is a propensity of selling or 

mortgaging assets to pay back the debt. 35.8% of all Afghans aged over 14, female and male, had taken 

a loan, whatever the amount might be, in the 5 years preceding the interview. This fi gure refl ects a frequent 

practice, especially if one considers that the loan is often taken for a family need and is paid back by all the 

active members in the family. 

What are the characteristics of debt of Afghans today? Understanding these will help to evaluate the risk of 

falling into poverty for the people indebted and to assess how vulnerable they may be. One major aspect 

to keep in mind is that people who lend money do not often ask for interests to be paid. Even if usury is a 

forbidden practice in a Muslim country, it is important to note that mortgager gets back the amount lent, even 

if various generations have to pay it off. 

Diversity of Borrowers’ Profiles 

Since a loan needs to be paid back, a majority of active persons report having taken one (46.2%) as shown 

in Figure 44 (and Table 70 in the Annexure). Nevertheless, more than a quarter (27.6%) of inactive people 

have also taken loans in the last fi ve years. Among these, a large part of people looking for a job have 

taken loans (55.9%), this is also the case for a large proportion of old people (52.9%) who do not work 

anymore but have different sources of income coming from house rent, fi eld rent, etc. There is a statistically 

signifi cant difference between persons with disability taking a loan (36.1%) and the non-disabled (30.5%). 

This difference is even higher when active people are taken into account: active persons with disability are 

60% to be indebted while active non-disabled are only 45.7%. 

39 

Here we specify ‘offi cially’ because a donation always implies a relationship of dominance between giver and receiver. It aslo defi nes 

social and family dynamics and implies the authority of the donor. 


45

Figure 44. Distribution of Persons with Disability 

and Non-Disabled Above 14 with Loans taken since 

5 Years according to the Situation of Activity 

70 

60 


Non-Disabled 

50 

40 

30 

20 

10 

0 

Working 

Not Working 

Figures 44 and 45 (and Tables 70 and 71 in the Annexure) show that older Afghans take loans more often 

than youngsters. Moreover, men take loans a lot more often than women, regardless of the situation of 

disability. This is explained by the ability of older men to provide better security for paying back loans due to 

the fact they own more assets and benefi t from their social status and most often have family members who 

are also working. 


and Non-disabled Above 14 according to the 

Amount of Loans and Age Groups 

50 

45 

40 

35 

30 

25 

20 

15 

10 

5 


Non-Disabled 

0 

Less than 25 

26 and More 

The fact that women and youngsters provide little direct income to the family because they less often earn 

an income explains that they are less likely to go into debt. Often, the man who is head of the family is the 

person who goes into debt because he is the person who collects all the income of the household and is in 

charge of expenditures. Moreover, when a child is working but still living in the household, even married, he/ 

she gives his/her income to the head of household. But the need to repay the loan is shared by all members 

of the family. 



and Non-Disabled Above 14 with Loan taken 

since 5 Years According to Gender 

60 


Non-Disabled 

50 

40 

30 

20 

10 

0 

Males 

Females 

Figure 47 (and Table 72 in the Annexure) show that persons with disability take a loan more often when 

they live in urban areas than when they live in rural ones. This result is inversed for the non-disabled. The 

difference of proportion is statistically signifi cant between persons with disability and non-disabled taking a 

loan in urban areas; but not in rural ones. 


and Non-Disabled Above 14 with Loan taken 

since 5 Years According to the Area of Living 

50 

45 


Non-Disabled 

40 

35 

30 

25 

20 

15 

10 

5 

0 

Urban 

Rural 

Similar results, even more prominent, are found when taking into account only the major towns of the country 

such as Kabul, Herat, Jalalabad, Kandahar, Mazar-I-Sharif and Kunduz on one hand and the rest of the country on 

the other (see Table 73 in the Annexure). This is explained by various factors. There are a higher number of persons 

with disability in major towns, and they more often work than those living in villages. They also have a higher 

standard of living and probably a larger social network, making it easier to obtain a loan in such settings. 

High Amount of Loans Taken 

The amount of the loans taken is an interesting way of having an overview on income. In fact, people are 

less reluctant in Afghanistan to talk about the loans they take than the income they get. If 36.7% of Afghans 

contract a loan, they are only a small proportion to have taken more than one in the last 5 years. 17.5% took 

a second one, 7.2% a third one, 1.7% a fourth one and 0.7% a fi fth one. These fi gures must be interpreted 


47

with caution for two main reasons. First of all, it is well known that the capacity of remembering facts 

diminishes with time and interviewees might have forgot some of the loans they took in the past. Experts 

usually consider that asking an interviewee to remember events older than 6 months constitutes a challenge 

for their memory. Such a diffi culty is for example very frequent for recalling the date of a wedding, fi rst job, 

period of migration 39 , etc. A second limitation is due to the fact that some people might consider some loans 

taken in the relevant period as not worth quoting for various reasons: the loan has been completely paid 

back for instance or is considered too low an amount to be taken into consideration. Therefore, in this report, 

emphasis is given on the global amount of all the loans (up to 5 major loans during the previous 5 years 

preceding the interview) quoted by the interviewee as a good approximation of the level and characteristics 

of debt. 


to the Amount of Loans 

24.9% 

28.7% 

30 to 5000 AFAs 

5100 to 10000 AFAs 

10100 to 23000 AFAs 

24000 AFAs and Above 

23.9% 

22.5% 

Figure 48 shows that a large fi rst quartile (28.7%) contracts small loans, while another quartile (24.9%) 

contracts the highest loans. The 5% with highest loans contracted 75,000 AFAs or more in loans, and the 

2% with the highest loans more than 150,000 AFAs. At the other end of the spectrum, the 10% with lowest 

loan took less than 1,800 AFAs. The loan most frequently made is 10,000 AFAs (mode), and on average, 

loans amount to 22,800 AFAs. 

Figure 49. Distribution of Persons with Disability and Non- 

Disabled Above 14 according to the Amount of Loans 

35 


Non-Disabled 

30 

25 

20 

15 

10 

5 

0 

30 to 5000 AFAs 5100 to 12000 AFAs 

12100 to 30000 AFAs 31000 AFAs and Above 

39 For more information, see DEPARTMENT OF ECONOMIC AND SOCIAL AFFAIRS (2001), op. cit. 


Figure 49 (and Table 75 in the Annexure) show that persons with disability have a tendency to borrow more 

money than non-disabled Afghans. This might be explained by increased expenditure due to health cure as 

well as the need for support and devices, for instance. 

Table 11. Average Amount of Loan for Urban and Rural 

Households 

Households 

Urban Rural 

Mean (AFAs) Mean (AFAs) 

Households without Persons with Disability 23346.8 20581.2 

Households with Persons with Disability 41024.9 28508.0 

Source: NDSA 

Table 11 shows that the average loan is almost twice as high in urban areas for households with a person 

with disability, and almost 50% higher in rural areas than for households without a person with disability. 

Considering that the sources for livelihood of these households is not very different in terms of poverty level 

than households with only non-disabled, the need for money might be explained by specifi c expenses that 

non-disabled household do not face or face to a less extent, such as health expenses 40 . 

Figure 50. Distribution of Persons with Disability and Non-Disabled 

Above 14 according to the Amount of Loans and the Age Group 

100% 

80% 

5.9 

30.0 

28.0 

8.9 

28.9 

27.1 


12100 to 30000 AFAs 

5100 to 12000 AFAs 

30 to 5000 AFAs 

60% 

21.2 

25.3 

29.6 

22.2 

40% 

24.6 

24.0 

20% 

34.6 

26.2 

40.0 

23.6 

0% 

Non-Disabled26 

Persons with Disability26 

Figure 50 (and Table 75 in the Annexure) show that older Afghans, regardless of disability, are more likely to 

take high amount loans (27.5% of Afghans older than age 26 take loan of more than 31,000 AFAs) than 

younger people (only 7.3% of Afghans younger than age 26 take loans above 31,000 AFAs). The latter take 

loans most often of less than 5,000 AFAs: 37.3% among them versus a proportion of only 26.3% among 

older people. The probability of becoming indebted logically increases with age. 

40 See BAKHSHI P. et. al. (2006), op. cit. 


49


Above 14 according to the Amount of Loans and Gender 

100% 

80% 

60% 

23.5 

24.8 

12.7 

20.8 

20.3 

24.1 

30.2 

23.9 

14.1 


12100 to 30000 AFAs 

5100 to 12000 AFAs 

30 to 5000 AFAs 

23.9 

40% 

28.0 

23.6 

20% 

23.6 

46.1 

22.1 

38.0 

0% 

Non-Disabled Males 

Non-Disabled Females 

Persons with Disability Males Persons with Disability Females 

Figure 51 (and Table 76 in the Annexure) show that Afghan men do take loans of higher amount than women, 

but a notable result is that disabled women also take loans of high amounts: more than 23% of men 

and only 12.7% of women (but 23.9% of women with disability). The need to face high expenditures, 

particularly in the health sector, sometimes explains the necessity to borrow money. 


Above 14 according to the Amount of Loans and the Living Area 

100% 

80% 

60% 

24.2 

25.8 

20.0 

23.3 

31.1 

25.6 

20.6 

26.1 


12100 to 30000 AFAs 

5100 to 12000 AFAs 

30 to 5000 AFAs 

40% 

21.7 

27.7 

23.3 

23.9 

20% 

28.3 

29.0 

20.0 

29.4 

0% 

Non-Disabled Urban 

Non-Disabled Rural Persons with Disability Urban Persons with Disability Rural 

Figure 52 (and Table 77 in the Annexure) show that urban Afghan people take higher amount of loans, especially 

persons with disability: 31.1% of urban Afghans with disability and 24.2% of urban non-disabled Afghans took 

loans worth more than 31,000 AFAs whereas rural Afghans are respectively 20% of non-disabled and 20.6% 

of persons with disability to take loans of such high amounts. The difference between urban and rural Afghans 

for highest and lowest amounts of loans is statistically signifi cant for persons with disability. 

A Limited Level of Debt 

The level of debt is measured by the amount of money still owed by the borrower. It is the difference between 

the amount of money borrowed globally and the amount of money already paid back at the time of the 

interview. Figure 53 shows that 27.6% of all borrowers owe less than 1500 AFAs, and a further 20.2% owe 

nothing, having paid back all the money. This means, grouped with the 64.2% of Afghans over age 14 who 

did not take a loan in the last 5 years, 84.2% of the Afghan population of this age is not in debt or has loans 

older than 5 years. 



to the Amount of Debt 

20.5 

27.6 

0 to 1500 AFAs 

1800 to 7800 AFAs 

8000 to 20000 AFAs 

20500 AFAs and Abnove 

29.1 

22.8 

Among those who are in debt, 20.5% owe more than 20,500 AFAs. The 5% of Afghans who are most in 

debt owe more than 67,000 AFAs and the 2% who are the most in debt owe more than 90,000 AFAs (under 

2000 USD). 

Figure 54. Distribution of Persons with Disability and Non- 

Disabled Above 14 according to the Level of Debt and the 

Age Group 

35 


Non-Disabled 

30 

25 

20 

15 

10 

5 

0 

0 to 1500 AFAs 1800 to 7800 AFAs 

8000 to 20000 AFAs 20500 AFAs and Above 

Figure 54 shows a signifi cantly higher proportion of persons with disability with a high level of debt: while 

20% of non-disabled people have a debt of over 20,000 AFAs, this proportion is of 31% among persons with 

disability. If one assumes that the annual wage of a medical doctor working in a public hospital is 30,000 

AFAs, this is clearly a very high level of debt. 


51


Above 14 according to the Level of Debt and the Age Group 

100% 

80% 

6.9 

34.7 

26.0 

20.0 

33.3 


8000 to 20000 AFAs 

1800 to 7800 AFAs 


60% 

26.6 

31.1 

28.0 

23.9 

40% 

22.1 

33.3 

24.4 

20% 

0% 

34.6 

Non-Disabled


Above 14 according to the Level of Debt and the Living Area 

100% 

80% 

32.5 

16.0 

31.6 

38.9 

27.2 


8000 to 20000 AFAs 

1800 to 7800 AFAs 


60% 

21.6 

25.6 

30.0 

40% 

8.6 

27.2 

20% 

0% 

37.3 

Non-Disabled Urban 

25.2 

Non-Disabled Rural 

22.2 

13.3 

Persons with 

Disability Urban 

27.8 

15.0 


Disability Rural 

The situation is slightly different when comparing living areas. There is no signifi cant difference for level of 

debt between rural and urban areas for persons with disability, except for debts above 20,500 AFAs for which 

persons with disability are signifi cantly more numerous to be indebt in urban areas. Differences between 

non-disabled living in urban and rural areas are signifi cant at all levels. Urban people are in majority to be 

at the extremes: having high levels of debt (32.5% of them have a debt above 20,500 AFAs) or very low 

level (37.3% have less than 1,500 AFAs). Rural people are mainly around an average level of debt (58.8% 

between 1,800 AFAs and 20,000 AFAs). Few have very high debt and a quarter has low debt. This result 

corroborates the fact that households among the poorest and those among the wealthiest are present in 

towns. 


Above 14 according to the Level of Debt and the Situation of Activity 

100% 

80% 

3.1 

6.1 

5.6 

11.3 

14.8 

10.6 

9.1 

8.9 

7.4 

20.1 

17.2 


8000 to 20000 AFAs 

1800 to 7800 AFAs 


60% 

17.2 

40% 

85.2 

63.3 

74.7 

20% 

45.5 

0% 

Non-Disabled Not Active 

Non-Disabled Active 


Not Active 


Disability Active 

Figure 58 (and Table 82 in the Annexure) show that active people, especially among persons with disability, 

have a tendency to have higher debt. They take loans that they know they will be able to pay back. Nevertheless, 

the level of debt is not linked to the number of working people in the household; it does not increase according 

to the number of active people. 


53

Purpose of Loan: a Yardstick of Poverty? 

Why do Afghans need to take loans? 

The fi rst reason is food. Almost a third of Afghans took a loan at least once in the last 5 years to get some food 

for the family. Food and health requirements often constitute emergency expenditures: there is realisation of a 

risk, lack of food or accident, disease, etc. Suddenly the family faces an unexpected expenditure and is forced 

to take a loan. In these circumstances, taking a loan is clearly an indication of vulnerability. 

Figure 59. Distribution of All People Above 14 Having Taken 

Loans according to the Purpose of Loan 

1.5% 3.5% 

2.5% 1.5% 

0.6% 

11.8% 

16.5% 

31.4% 

2.9% 

Food (31.4%) 

School Expenditure (2.9%) 

Health Expenditure (17.8%) 

Professional Equipment (10.1%) 

House Equipment (16.5%) 

Ceremony (11.8%) 

Dowry (0.6%) 

Land Purchase/Rent (2.5%) 

Property Purchase (1.5%) 

Good Purchase for Business (1.5%) 

Other (3.5%) 

10.1% 

17.8% 

Is there a difference between persons with disability and non-disabled concerning the reasons why a loan 

has been taken? Actually, a major and statistically signifi cant difference is for health expenditures: persons 

with disability, because of their health needs, more often take a loan to cover such expenditures. On the other 

hand, non-disabled persons signifi cantly take loans more often to pay for professional equipment purchase 

or to cover ceremony expenditures. Persons with disability slightly more often use loans for food, while nondisabled 

use it more for professional reasons (15.8% of non-disabled, 6.7% of persons with disability) or 

house equipment (21.9% of Non-disabled, 17.0% of persons with disability). 


Above 14 according to the Purpose of Loan 

50 

45 


Non-Disabled 

40 

35 

30 

25 

20 

15 

10 

5 

0 

Food 

School Health Prof. 

Expenditure Expenditure Equipment 

House Ceremony Dowry Land Property 

Equipment 

Purchase/Rent purchase 

Good 

Purchase 

Other 

Purpose 


Whereas persons with disability usually use loans for emergency expenditures to cover basic needs such as 

nutrition and health, non-disabled have a tendency to use loans more for professional investment, equipment 

or social expenditure. It is a tool used to improve a personal or family situation. Thus, borrowing money and 

being indebted can be regarded as a factor of vulnerability in the case of persons with disability 

Loan is a Family and “Friendly” Matter 

Lenders are most often friends of the borrower (47.9% of all cases) and children or other relatives (37.3%). 

There is no wide “business” of loan in Afghanistan, except in the emerging banking system, which started only 

in the last years and is solely implemented in main towns. Mostly people rely on their community and family 

network. Borrowing does not exist inside the household. Husband and wife do not borrow money from each 

other either; this is logical as money is dealt in common within the household. 

Figure 61. Distribution of all People Above 14 according to 

the Lender 

47.9% 

2.5% 

0.4% 

0.1% 0.2% 0.4% 

0.9% 1.2% 1.7% 

7.3% 

37.3% 

Husband/Wife (7.3%) 

Father/Mother (37.3%) 

Brother/Sister (47.9%) 

Child/Other Relative 

(11.8%) 

Friend (0.1%) 

Local/Religious Leader 

(0.9%) 

Bank/Saving and Loans 

(2.5%) 

Boss (0.4%) 

Professional Money Lender 

NGOs 

Other People 

Figure 62 (and Table 84 in the Annexure) show that persons with disability and non-disabled both rely fi rst 

of all on friends to get money when they need it. But this phenomenon is statistically signifi cantly more 

common for the non-disabled. Non-disabled persons benefi t more often from the support of their social 

network. In other words, their social capital seems slightly more effi cient. On the other hand, persons with 

disability rely more on family: children especially (40.3% of them borrow from their children which is logical 

because persons with disability are older), but also siblings (11.3%) and parents (2%). Still, friends also are 

requested to lend money by 36.3% of persons with disability. Lenders who are not in the family are a higher 

proportion to lend money to persons with disability. This can be explained by the emergency of some needs. 

When a person needs to buy food or drugs, then he/she starts looking fi rst within the personal network, then, 

in case of lack of fund or sometime refusal, they seek the professional owners, employer, in some case banks. 

NGOs are mentioned as loans providers by 1.4% of persons with disability and by 0.15% of non-disabled. 


55


Above 14 according to the Lender 

50 

45 

40 

35 

30 

25 

20 

15 

10 

5 

0 


Non-Disabled 

Husband/ 

Wife 

Father/Mother 

Siblings 

Child/Other 

Relative 

Friend 

Local/Religious 

Leader 

Bank/Lender/ 

NGO/Other 

Concluding on Borrowing Practices: Risk Factor or Capability 

Asset? 

Loan can be consider both as a factor of risk and as a factor of empowerment. For some people it can 

constitute a capability asset, whereas it represents for others a transitional survival… 

The characteristics of loans also show the link with vulnerability. People who make the highest loans are not 

the poorest but the ones who need to invest for the future or cover a special need. They usually have the 

capacity to pay back. They use a larger social network of friends and relatives to cover their needs. Elder men 

offer more guarantee of security. The loan system seems to be based on the social capital. Reimbursement 

must be ensured, so higher income is also an asset. 

More vulnerable people such as persons with disability and women make loans but they cannot benefi t from 

the same network: they rely on parents or children (especially for women heads of household), and brothers (for 

persons with disability). Higher debt without the same capacity to pay back or to have someone able to help 

in case of need would become a major burden. In this case, debt might be a factor of higher vulnerability. This 

possibly explains why women without disability do not often take high loans. All together, it might also explain 

why women who are head of household or disabled women are particularly in debt: more vulnerable, with 

unexpected expenses, they try to meet urgent needs by taking loan and hoping to fi nd a way to pay back later. 

Income through the Social Network: the Social Income 

The social capital theory considers that the individual is at the centre of a social network that is as valuable 

as his/her own assets: this human capital is measured by level of education, level of income, ownership of 

goods, etc. The hypothesis is that each individual is part of a “social environment 41 ”, with which relations are 

maintained especially with regards to exchange of goods of services. 

Money Given: Family at the Basis of the Social Capital 

If income from activity is concentrated on a small proportion, redistribution within the family is a common practice, 

in both groups. Questions regarding monetary exchanges were asked during the survey. Figure 63 (and Table 85 in 

the Annexure) show that 42.2% of all adults above 14 received money from the social network, mainly family. There 

is not a huge difference between disabled and non-disabled when it comes to receiving money, even if persons with 

disability receive money more often (a proportion of 45.4% compared to a proportion of 38.9% for non-disabled). 

One difference, which is noticeable, is that women receive help more often than men. This is consistent with the fact 

that men are the ones who hold paid employment and bring the majority of money into the household. 

41 See BECKER G. S. (1976), Part 7: « Social Interactions », in The Economic Approach of Human Behavior, Chicago and London, the 

University of Chicago Press, 1976, pp. 251-282. 


Figure 63. Distribution of Persons with Disability and 

Non-Disabled Above 14 Receiving Money according to Gender 

80 

Received 

Not Received 

70 

60 

50 

40 

30 

20 

10 

0 



Males with Disability 

Females with Disability 

Figure 64 (and Table 86 in the Annexure) show a breakdown of persons with disability and non-disabled 

according to the donors. In both cases, a huge majority of the donors are from the family itself: 

For non-disabled persons, fi rst come the parents (28.9%) followed closely by the spouse (27.8%), 

then come brother and sister (23.2%) and children and other relatives in fourth position but far behind 

(10.9%); 

For persons with disability, fi rst come children and other relatives (24.6%), before brother and sister 

(22.6%), the spouse (19.7%) and parents (17.9%). 

The differences between both groups are highly statistically signifi cant. The major difference regarding the 

money received from children is probably due to the needs of persons with disability to get support. This is 

also in line with the NDSA results that show a high number of persons over the age of 45 among the persons 

with disability 42 . The children support their parents as they become disabled with age and/or disease. 

A minority of people receives money from persons outside the family. Friends are 5.4% to give money. Then 

other donors are quoted such as NGOs or employers mainly for persons with disability. 


Above 14 according to the 3 Main Donors 

30 


Non-Disabled 

25 

20 

15 

10 

5 

0 

Husband/Wife 

Father/Mother Brother/Sister 

Children and 

other Family 

Members 

Friends State Pension Local or 

Religious 

Leader 

Employer, 

NGOs or 

Other 

42 See BAKHSHI P. et. al. (2006), op. cit. 


57

If one considers the order of the answers separately as in Table 87 in the Annexure, one fi nds that: 

For non-disabled people, the spouse appears to be quoted as the main donor in the 3 possible answers 

and even represents 66.6% of all the donors in the third answer; 

For persons with disability, the children and other family members appear to be the major donor whatever 

the answer considered. 

If NGOs and employers are quoted in the fi rst answer for the few persons with disability they give money 

to, it is probably because the amount of money is signifi cant, particularly over the recent years. 

State pensions or leaders of the community are quoted mainly in the third answer. 

Table 88 in the Annexure gives an overview according to gender of who the main donors are. In both groups, 

persons with disability and non-disabled, women receive a lot more from their husbands, which is logical 

considering the general family dynamics. This also seems obvious given the social and cultural context and 

the gender dynamics. 

Amounts Donated: Higher for Men 

Figure 65 (and Tables 89 and 90 in the Annexure) show that males more often receive higher amounts of 

money than women, independently from the disability factor. 58.6% of non-disabled women and 58.3% 

of disabled women receive less than 3,200 AFAs a year whereas more than 25% of males disabled or not, 

receive more than 12,000 AFAs. 


above 14 by Amount of Money received and Gender 

40 

35 



Males with Disability 

Females with Disability 

30 

25 

20 

15 

10 

5 

0 

Less than 700 AFAs 

710 to 3200 AFAs 3300 to 12000 AFAs 12030 AFAs and Above 

Concluding on Social Income 

Men more often give money to the members of their social network, particularly to their spouses. If they are 

a lower proportion to receive money, they receive higher amounts than women. Donation of money is also 

part of the social control of men on women. Women are not allowed to work, especially in rural areas, so men 

provide the resources for their needs. If they inherit part of the family land, they hand it over to the male of 

the family (sister to a brother, widow to a son) against a commitment of the latter to cover her needs. 



Disability: a Dormant Factor? 

In Afghanistan, poverty appears as a “great leveller”. This is evident in some of the fi ndings of the present 

report and can be said with regards to commodities, living spaces as well as other assets. Disability does 

not have an impact when the general population is faced with severe and chronic poverty. The lack of water, 

electricity and general commodities of the overall population lead to a very minimal difference between 

households of persons with disability and non-disabled households. The persons with disability are not 

necessarily the poorest of the poor. On the contrary, the low level of life standard is shared on an equal basis 

by all. An exception is the case of women, especially isolated women, who suffer from more discrimination 

and appear to be among the poorest, and this is true both in towns and rural areas. 

However, it is also essential to focus upon the few results that have been found regarding the small proportion 

of the population that is better off than the majority. The trends observed lead to believe that with regards 

to livelihoods and living conditions, disability impacts the more advantaged social groups. This in turn led us 

to put forward the strong assumption that as conditions in general improve, the impact of disability 

on livelihoods becomes salient. In order words, as households get out of poverty, households that have 

a disabled member will have to face more diffi culties, need more resources in order to improve their living 

conditions. Disability is thus a ‘dormant’ factor that is not on the forefront when faced with extreme poverty. 

However, at the second stage, this factor may have a heavy impact by keeping certain households more 

vulnerable to poverty and less equipped to face risks in life. 

Urban or Rural Settings: an Expected Difference 

Urban livelihood seems to be a little wealthier: better access to water, main power, fl ush, diet diversity, more 

equipment, larger size of houses and household… Unlike Schutte 43 who found more widespread nuclear 

households in Herat, urban households seem to be more extended. But the picture is not always positive. 

Ownership of house is less important. In case of incapacity to pay a rent, or if the person who provides 

the housing needs the house back, the family loses a major asset. Unemployment, underemployment and 

precarious conditions are more frequent in urban areas. 

Female-headed Households: the most Vulnerable and the 

Poorest 

Households headed by a woman are both the poorest and the most vulnerable. This fi nding corroborates 

NRVA 2003 analysis that identifi ed such households among the poor and very poor wealth groups. As shown 

by the NRVA 2003, NDSA 2005 fi nds that women head of household are a higher proportion having an 

income generating activity. These households have lower assets ownership and poor dietary diversity. They 

also face more isolation, thus are not able to rely on a strong social capital in case of shock occurrence. 

Households headed by women are more present in urban areas, probably because of highest isolation from 

the rest of the family who is in the village. Acceptance of women heads of household might be also higher in 

43 SCHUTTE S, (2006), “Poverty amid Prosperity: Urban Livelihood in Herat”, Afghanistan Research and Evaluation Unit, AREU, May 

2006, 61 pp. 


59

major towns and the social expectations and control a little less salient. Hence Afghan society maintains a strict 

control on women who must conform to traditional rules. As Dupree writes, “the hierarchical structure within 

families leaves little room for individualism, for senior male members, the ultimate arbiters, maintain family 

honour and social status by ensuring all members conform to prescribed forms of acceptable behaviour 44 ”. 

Access to the Labour Market: a Matter of Perception 

The will to work is widespread among persons with disability and it is often a major claim they express. 

Opportunities of work are limited in an economy dominated by the agricultural sector, especially for the 

severely disabled and women with disability. Yet, the sector of services is rapidly growing stimulated by the 

reconstruction effort. Two major orientations could be followed in order to improve the situation. The fi rst one 

is the fi ght against stereotypes that lead to the belief that persons with disability, and especially women, 

cannot work due to their impairment. Sensitisation can also be achieved by mainstreaming persons with 

disability in the workplace; this is a fi rst step towards their inclusion on the labour market. Changing social 

attitudes and beliefs is the only way to enable persons with disability to participate in the labour market. 

Because sensitisation is not enough, a second set of action, complementary to the sensitisation process, is 

the passing and implementing of the law with a requirement for employment of persons with disability. This 

obligation imposed to all employers, both within the state administration and the private sector, is proactive 

and might decisively help persons with disability in their struggle for the right to employment. 

The Way Forward: Mainstreaming, Empowerment, 

Participation of Persons with Disability 

Gathering of knowledge on livelihood, vulnerability, risks and poverty provides understanding, information and 

insights necessary for policy formulation and strategic planning in the area of disability. A national disability 

strategy framework based on such principles as empowerment and mainstreaming aims at increasing access 

for persons with disability to social and economic opportunities. Designs of policies and strategies have to rely 

on scientifi c based knowledge and on participation of persons with disability themselves in the elaboration 

process. 

This view, which has been put forward by a number of disabled persons’ organisations, tends to look at 

the barriers that exist within the social context and that prevent a person from achieving the same level of 

functioning as that of a non-disabled person. In this perspective it is society that needs to be redesigned in 

order to take into account the disabled persons’ needs. Mainstreaming persons with disability is a progressive 

way of reshaping society in order to better include them. Equalization of opportunities is a major goal put 

forward by the new United Nations Convention on the Rights of Persons with Disabilities adopted by the 

General Assembly on the 13th December 2006. 

44 DUPREE N. H. (2004), The Family during Crisis in Afghanistan, Journal of Comparative Family Studies, Vol. 35, 311:332, 2004. 


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RAVALLION M. (1998), “Poverty Lines in Theory and Practice, Living Standards Measurement Study”, Working 

Paper 133, World Bank, Washington DC, 1998. 

RAVALLION M. (1994), “Poverty Comparisons”, Fundamentals of Pure and Applied Economics, volume 56, 

Harwood Academic Publishers, Switzerland, 1994. 

SCHUTTE S. (2006), “Poverty amid Prosperity: Urban Livelihood in Herat”, Afghanistan Research and 

Evaluation Unit, AREU, May 2006, 61 pp. 

TZEMACH G.(2006), Women Entrepreneurs in post-confl ict economies: A Look at Rwanda and Afghanistan, 

Washington D.C., Center fro International Private Entreprise, www.cipe.org. 

UNITED NATIONS, DEPARTMENT OF INTERNATIONAL ECONOMIC AND SOCIAL AFFAIRS, STATISTICAL 

OFFICE (1990), “Disability Statistics Compendium”, Statistics on Special Population Groups, Series Y, No. 4, 

New York, 1990. 

VULNERABILITY ANALYSIS AND MAPPING UNIT OF THE WORLD FOOD PROGRAMME AND THE 

VULNERABILITY ANALYSIS UNIT OF THE MINISTRY OF RURAL REHABILITATION AND DEVELOPMENT 

(2004), Reports on Findings from the 2003 National Risk and Vulnerability Assessment (NRVA) in Rural 

Afghanistan, December 2004, 123 p., http://www.mrrd.gov.af/vau/. 

WOOD, W. B. (1989), “Long Time Coming: The Repatriation of Afghan Refugees”, Annals of the Association of 

American Geographers, 79 (3), 345-369. 

WORLD BANK (2005), “Poverty, Vulnerability and Social Protection: an Initial Assessment.”, Afghanistan 

Report 29694-AF, 7 March 2005. 


Annexure 

Tables Related to Water Supply 

Table 12. Distribution of Households according to the Location of Drinking Water 

Location of Drinking Water Source† 

Within the compound/house 

Number 

% in location 

HH without 

Person with 

Disability† 

HH with at 

least One 


Disability 

Total 

5428 556 5984 

25.2** (1) 30.9** (1) 25.7 

Number 

16070 1244 17314 

Outside the compound/house 

% in location 74.8 69.1 74.3 

Total Number 21498 1800 23298 

Source: NDSA. Note: † Weighted by the number of household in the cluster without Persons with Disabilities living there. (1)Test of comparison 

of proportion between households with and without a Person with Disability. ** Signifi cant at p

Table 14. Distribution of Households according to Types of Water Supply 

Available 

Types of Water Supply 

Piped into residence/compound/plot 

Public tap 

Hand pump in residence/compound 

Public hand-pump 

Well in residence/compound 

Covered well 

Open well and kariz 

Spring 

River/stream 

Pond/lake 

Still water/dam 

Rain water 

Tanker, truck or other 



Disability† 

HH with at least 

One Person with 

Disability 

Total 

Number 1193 105 1298 

% in Type of water supply 4.4 4.7 4.4 

Number 817 54 871 


Number 1387 131 1518 


Number 5038 418 5456 


Number 3566 349 3915 

% in Type of water supply 13.2** (1) 15.8** (1) 13.4 

Number 1808 153 1961 


Number 2560 192 2752 

% 9.5 8.7 9.4 

Number 3976 262 4238 

% in Type of water supply 14.7** (1) 11.8** (1) 14.5 

Number 5692 430 6122 

% 21.0 19.4 20.9 

Number 563 57 620 


Number 102 12 114 


Number 346 38 384 


Number 9 11 20 


Total Number 27057 2212 29269** (2) 

Source: NDSA. Note: Up to three answers were possible. † Weighted by the number of household in the cluster without Persons with 

Disabilities living there. (1)Test of comparison of proportion between households with and without a Person with Disability. ** Signifi cant at 

p

Table 16. Distribution of Households according to Location of Drinking Water 

Available in Urban and Rural Areas and Gender of the Head of Household. 

Gender of Head of Household† Urban Rural Total 

Man 

Woman 


Number 2991 2683 5674 

% in location 

category 

56.2** (1) 15.9 25.6 

Number 2332 14155 16487 

Outside the compound/house % in location 

category 

43.8 84.1 74.4 

Total Number 5323 16838 22161 


Number 270 40 310 

% in location 

category 

63.2** (1) 5.8 27.9 

Number 157 645 802 

Outside the compound/house % in location 

category 

36.8 94.2 72.1 

Total Number 427 685 1112** (2) 


of proportion between households headed by men or women. ** Signifi cant at p

Table 18. Distribution of Households according to Sources of Light Supply 

Available in Urban and Rural Areas 

Sources of Light Supply Urban Rural Total 

Main power 

Generator/battery/invertors 

Kerosene/petrol/gas 

Candles 

Number 337 95 432 

% in source of light 27.9** (1) 4.3** (1) 12.6 

Number 165 140 305 


Number 669 1812 2481 


Number 15 141 156 


Number 21 25 46 

Other 

% in source of light 1.7 1.1 1.3 

Total Number 1207 2215 3422** (2) 

Source: NDSA. Note: Two answers were possible. (1)Test of comparison of proportion between households with and without a Person with 

Disability. ** Signifi cant at p

Tables Related to Cooking Energy Supply 

Table 20. Distribution of Households according to Sources of Energy for 

Cooking 

Sources of Energy for Cooking 

Gas 

Stove with kerosene/petrol 

Firewood 

Dung 

Charcoal 

Electricity 



Disability† 


One Person 


Total 

Number 3908 317 4262 

% in source of energy 10.3 10.2 10.4 

Number 668 38 706 


Number 18181 1476 19657 


Number 12975 998 13973 


Number 433 54 487 


Number 355 27 382 


Number 1407 150 1557 

Other 


Total Number 37927 3099 41026 

Source: NDSA. Note: Two answers were possible. † Weighted by the number of household in the cluster without Persons with Disabilities 

living there. (1)Test of comparison of proportion between households with and without a Person with Disability. ** Signifi cant at p

Tables Related to Toilet Facilities 

Table 22. Distribution of Households according to Access to Types of Toilet 

Facilities 

Kind of Toilet Facility 

Private fl ush inside 

Private fl ush outside 

Shared fl ush 

Traditional pit 

Open backed 

Open defecation fi eld outside the 

house 



Disability† 



Disability 

Total 

Number 658 96 754 

% in type of toilet facility 3.1** (1) 5.3** (1) 3.2 

Number 300 18 318 

% in type of toilet facility 1.4 1.0 1.4 

Number 292 34 326 


Number 3704 170 3874 


Number 10103 1006 11109 


Number 6368 473 6841 



Other 


Total Number 21468 1802 23270** (2) 



Tables Related to Housing 

Table 24. Distribution of Households by Number of Rooms in the House 

Number of Rooms 

1or 2 rooms 

3 rooms 

4 rooms 

5 rooms 

6 rooms 



Disability† 



Disability 

Total 

Number 3188 307 3495 

% in number of rooms 15.0 17.2 15.2 

Number 4610 351 4961 


Number 4134 373 4507 


Number 3400 287 3687 


Number 3129 178 3307 

% in number of rooms 14.7** (1) 10.0** (1) 14.3 

Number 2804 292 3096 

7 rooms and more 


Total Number 21265† 1788 23053 



Table 26. Distribution of People according to Number of Rooms in the House by 

Urban and Rural Settings 

Number of Rooms† Urban Rural Total 

1or 2 rooms 

3 rooms 

4 rooms 

5 rooms 

6 rooms 

Number 458 3037 3495 


Number 875 4086 4961 


Number 921 3586 4507 


Number 1074 2613 3687 


Number 1042 2265 3307 


Number 1381 1715 3096 

7 rooms and more 


Total Number 5751 17302 23053** (2) 



Tables Related to Food Supply 

Table 28. Distribution of Households according to Sources for Supply of Food 

Types of Supply of Food 

Market/bazaar 

Self provided/farm 

Combination of market/farm 

Food aid 



Disability† 


One Person 


Total 

Number 14198 1166 15364 

% in type of supply 60.3 60.2 60.3 

Number 1899 134 2033 


Number 7290 614 7904 




Number 75 16 91 

From family, other relatives 


Total Number 23564 1936 25500 

Source: NDSA. Note: Two answers were possible. † Weighted by the number of household in the cluster without Persons with Disabilities 

living there. (1)Test of comparison of proportion between households with and without a Person with Disability. ** Signifi cant at p

Table 30. Distribution of Households according to Sufficiency of Food 

Food Sufficiency† 

Always enough 

Sometimes not enough 

Frequently not enough 

Always not enough 

Always enough but with poor quality 



Disability† 

HH with a 


Disability 

Total 

Number 3498 227 3725 

% in quantity of food 16.4** (1) 12.6** (1) 16.1 

Number 3522 291 3813 

% in quantity of food 16.5 16.2 16.4 

Number 4267 350 4617 


Number 3425 294 3719 


Number 6671 636 7307 


Total Number 21383 1799 23182** (2) 



Table 32. Distribution of Households according to Gender of the Head of the 

Household and Sufficiency of Food 

Food Sufficiency† 

Always enough 

Sometimes not enough 

Frequently not enough 

Always not enough 

Always enough but with poor quality 


the HH 

Woman Head 

of the HH 

Total 

Number 3588 137 3725 


Number 3591 222 3813 


Number 4449 144 4593 


Number 3444 305 3749 


Number 7005 303 7308 


Total Number 22078 1111 23189** (2) 

Source: NDSA. Note:. † Weighted by the number of household in the cluster without Persons with Disabilities living there. (1)Test of comparison 

of proportion between households headed by a man or a woman. ** Signifi cant at p

Table 34. Distribution of Households according to the Ratio of Employed 

Members 

Share of Members in the HH Who Work † 

No one 

Less than 25% 

25 to 50% 

50% to 75% 



Disability 

HH with a Person 


Total 

Number 868451 288401 1156852 

% in ratio category 4.4 5.8 4.6 

Number 11736107 3132790 14868897 

% in ratio category 59.0** (1) 62.6** (1) 59.7 

Number 6196077 1355615 7551692 

% in ratio category 31.2** (1) 27.1** (1) 30.3 

Number 993165 221497 1214662 


Number 92236 6496 98732 

More than 75% 


Total Number 19886036** (2) 5004799** (2) 24890835 

Source: NDSA. Note: † Weighted by the population of the province. (1) Test of comparison of proportion between Persons with Disabilities 

and Non-Disabled. ** Signifi cant at p

Table 36. Distribution of Persons with Disability and Non-Disabled Between 14 

and 65 according to the Employment Situation and Gender (analysis on series 

of questions) 

Gender Employment Situation† Non-disabled 

Males 

Females 

Working 


disability 

Total 

Number 5055204 125364 5180568 

% in Employment situation 82.6** (1) 57.6** (1) 81.7 

Number 1064356 92236 1156592 

Not Working 

% in Employment situation 17.4 42.4 18.3 

Total Number 6119560** (2) 217600** (2) 6337160 

Working 

Number 598887 14290 613177 


Number 3948627 135756 4084383 

Not Working 


Total Number 4547514* (2) 150046* (2) 4697560 



76 Understanding Vulnerability of Afghans with Disability 

Table 38. Distribution of People according to Profession 

Code Profession† Number % 

Animal husbandry, shepherd, animal keeper 203309 3.8 

Architect/mohandes 14290 0.3 

Artist/singer/danser/writer/painter/rangmal 8444 0.2 

Baker/nalwa 16238 0.3 

Banker 4546 0.1 

Bookshop 1948 0.0 

Butcher/kassab 12991 0.2 

Carpenter 31178 0.6 

Carpet weaver, rag weaver 285802 5.3 

Car salesman 12991 0.2 

Cashier/ sharaf/ munshi/ clerk/ accountant 7794 0.1 

Chemist 5846 0.1 

Cleaner 388432 7.3 

Computer specialist/motakhasis computer 4546 0.1 

Cook 12341 0.2 

Doctor 25982 0.5 

Driver/pilot 215651 4.0 

Editor(newspaper, books) 3247 0.1 

Electrician/barki 3897 0.1 

Farmer 2126633 39.7 

Shopkeeper/dehkandar 347510 6.5 

Fortune tailor, palm reader(Kafbin) 1299 0.0 

Fruit and vegetables salesman 31828 0.6 

Gelkar/building worker 513146 9.6 

Guard/tchukidor 34426 0.6 

Hairdresser/barber/salmon 8444 0.2 

Hotelshi 10392 0.2 

Ingenior 13640 0.3 

Iron worker meldar/ahiingar 12341 0.2 

Jeweler/zargar 2598 0.0 

Journalist 649 0.0 

Judge 649 0.0 

Khatat/painter of banners 1299 0.0 

Lawyer 3247 0.1 

Lender of money/sutrur 649 0.0 

Mechanic/mestari 98082 1.8 

Megaran/work with driver, make people pay bus 3897 0.1 

Mullah, religious leader 51314 1.0 

Nurse 17537 0.3 

Other service provider 8444 0.2 

Plumber/naldawa 2598 0.0 

Policeman 58459 1.1 

Professor at the university 3247 0.1 

Public employee/military offi cer 157191 2.9 

Public announcer(jar zan) 1299 0.0 

Real estate agent /rahnamaia mamalat 3247 0.1 

Repairer/khabarnagar 1948 0.0 

Shoemaker/muchi 9743 0.2 

(Table 38 contd. on next page)

(Table 38 contd. from previous page) 

Code Profession† Number % 

Businessman 34426 0.6 

Soldier/mudjahidin 38973 0.7 

Stone mason 3247 0.1 

Street vendor (newspaper, shoe cleaner, etc.) 44169 0.8 

Tailor/khayat, fl ower sewer/hat maker 108475 2.0 

Tchofrosh/wood-cutter 16238 0.3 

Teacher 170182 3.2 

Translator 4546 0.1 

Waiter/garsun 5846 0.1 

Macon/steel maker 21435 0.4 

Repair man for electronics 7794 0.1 

De-miner 2598 0.0 

Owner of industry 1299 0.0 

Renter of houses and other services and goods 4546 0.1 

Coolie/porter 31828 0.6 

Little jobs not mentioned elsewhere 54562 1.0 

Veterinarian 2598 0.0 

Surveyor 4546 0.1 

Other 649 0.0 

Total 5343215 99.9 

Source: NDSA. † Weighted by the population of the province. 


according to the Activity Status 

Status of Activity† 

Landowner/mortgager 

Daily/weekly wage worker 

Contract worker 

Occasional worker 

Apprentice 

Family helper 

Self employed 

Employer 

Non-Disabled 


Disability 

Total 

Number 1760286 38324 1798610 

% in status 35.9* (1) 28.9* (1) 35.7 

Number 982123 27281 1009404 

% in status 20.0 20.6 20.0 

Number 761275 22085 783360 

% in status 15.5 16.7 15.6 

Number 133808 8444 142252 

% in status 2.7** (1) 6.4** (1) 2.8 

Number 63007 650 63657 

% in status 1.3 0.5 1.3 

Number 285153 5196 290349 

% in status 5.8 3.9 5.8 

Number 908723 27931 936654 

% in status 18.5 21.1 18.6 

Number 5196 0 5196 

% in status 0.1 0.0 0.1 

Number 3897 2598 6495 

Other status 

% in status 0.1 2.0 0.1 

Total Number 4903468 132509 5035977 

Source: NDSA. Note: † Weighted by the population of the province. (1) Test of comparison of proportion between Person with Disability and 

Non-Disabled. ** Signifi cant at p


according to the Farmer Status 

Status of Farmers † 

Landlord/khan 

Landowner/malik/zamindar/mulkdar 

Farmer/sharecropper/mortgager 

Tenant/khistmand 

Labourer/worker/kargar 

Non-Disabled 


Disability 

Total 

Number 187201 1949 189150 

% in status 5.7 2.7 5.6 

Number 551859 12341 564200 

% in status 16.8 17.0 16.8 

Number 1562043 27281 1589324 

% in status 47.5 37.5 47.3 

Number 192138 6496 198634 

% in status 5.8 8.9 5.9 

Number 733344 20786 754130 

% in status 22.3 28.6 22.5 

Number 59759 3897 63656 

Family helper 

% in status 1.8 5.4 1.9 

Total Number 3286344 72750 3359094 

Source: NDSA. Note: † Weighted by the population of the province. (1) Test of comparison of proportion between Person with Disability and 



Aged 7 to 15 according to Activity and Gender 

Type of Activity Gender† Non-Disabled 

Household tasks 

Fieldwork 

Other work 

Male 

Female 

Male 

Female 

Male 

Female 

Children with 

Disability 

Total 

Number 5361403 39623 5401026 

% in activity type 75.2** (1) 42.4** (1) 74.8 

Number 5088461 40922 5129383 


Number 1757168 13641 1770809 


Number 423248 1299 424547 


Number 470406 7145 477551 

% in activity type 6.6 7.6 6.6 

Number 119647 0 119647 

% in activity type 2.2 0.0 2.1 

Source: NDSA. Note: † Weighted by the population of the province. (1)Test of comparison of proportion between Non-Disabled and Person 

with Disability. ** Signifi cant at p


Aged 7 to 15 according to Types of Household Tasks and Gender 

Gender 

Boys 

Girls 

Types of Tasks† 

Cooking 

Cleaning 

Fetching water/fi ll tanker 

Taking care of other member of family 

Laundry 

Doing the grocery shopping 

Non- 

Disabled 


Disability 

Total 

Number 71061 0 71061 

% in task type 1.3 0.0 1.3 

Number 1275591 5197 1280788 

% in task type 23.8 13.1 23.7 

Number 4750044 30530 4780574 

% in task type 88.6 77.1 88.5 

Number 1228953 8444 1237397 

% in task type 22.9 21.3 22.9 

Number 108864 1299 110163 

% in task type 2.0 3.3 2.0 

Number 3835735 22085 3857820 

% in task type 71.5 55.7 71.4 

Number 505871 5197 511068 

Other 

% in task type 9.4 13.1 9.5 

Total Number 5361403 39623 5401026 

Cooking 

Cleaning 

Fetching water/fi ll tanker 

Taking care of other member of family 

Laundry 

Doing the grocery shopping 

Number 1597509 8445 1605954 

% in task type 31.4 20.6 31.3 

Number 4036186 29880 4066066 

% in task type 79.3 73.0 79.3 

Number 3448992 24033 3473025 

% in task type 67.8 58.7 67.7 

Number 643576 7145 650721 

% in task type 12.6 17.5 12.7 

Number 2026212 11043 2037255 

% in task type 39.8 27.0 39.7 

Number 582907 5197 588104 

% in task type 11.5 12.7 11.5 

Number 87170 650 87820 

Other 

% in task type 1.7 1.6 1.7 

Total Number 5088461 40922 5129383 

Source: NDSA. Note: † Weighted by the population of the province. Some fi gures should be considered with caution due to low number of 

observations. 


Table 45. Distribution of Boys with Disability and Non-Disabled Boys Aged 7 to 

15 according to Types of Field Work 

Types of Field Work† 

Work the soil, harvest 

Look after animals 

Fetch and carry things 

Guarding the products 

Non-disabled 


Disability 

Total 

Number 1060069 9743 1069812 

% in task type 60.2 71.4 60.3 

Number 1259872 12342 1272214 

% in task type 71.6 90.5 71.7 

Number 1109564 5847 1115411 

% in task type 63.1 42.9 62.9 

Number 732955 1950 734905 

% in task type 41.7 14.3 41.4 

Number 176288 1300 177588 

Other, specify 

% in task type 10.0 9.5 10.0 

Total Number 1759766 13641 1773407 

Source: NDSA. Note: † Weighted by the population of the province. 3 Responses possible. 

Table 46. Distribution of Boys with Disability and Non-Disabled Boys Aged 7 to 

15 according to Types of Jobs 

Types of Jobs† 

Odd jobs (rag-picking, bottle collecting...) 

Help someone we know in his/her work 

Employed in a fi xed job 

Employed in occasional job 

Independent small job (shoe polish, 

newspaper vendor...) 

Non-Disabled 


Disability† 

Total 

Number 7145 0 7145 

% in job type 1.5 0.0 1.5 

Number 70411 650 71061 

% in job type 15.0 9.1 14.9 

Number 86261 650 86911 

% in job type 18.3 9.1 18.2 

Number 80415 2599 83014 

% in job type 17.1 36.4 17.4 

Number 76647 0 76647 

% in job type 16.3 0.0 16.0 

Number 149527 3897 153424 

Other, apprentice 

% in job type 31.8 54.5 32.1 

Total Number 470406 7146 477552 

Source: NDSA. Note: † Weighted by the population of the province. Some fi gures should be considered with caution due to low number of 

observations. 

Annexure 

81

Tables Related to Income 

Table 47. Monthly Activity Income of Active People 

For Adults 15-64 

Classes of Income† Number % by Class Valid % 

Cumulate 

% 

For All Population 

Number % by Class Valid % 

Cumulate 

% 

0 AFAs 329063 2.9 6.0 6.0 2252906 8.7 26.5 26.5 

100 to 1000 AFAs 561863 5.0 10.3 16.3 946267 3.7 11.1 37.6 

1100 to 2000 AFAs 924053 8.2 16.9 33.1 1134378 4.4 13.3 51.0 

2100 to 3000 AFAs 1241554 11.0 22.7 55.8 1321189 5.1 15.5 66.5 

3050 to 4000 AFAs 846886 7.5 15.5 71.3 867022 3.3 10.2 76.7 

4050AFAs to 5500 AFAs 686966 6.1 12.5 83.8 691513 2.7 8.1 84.9 

6000 AFAs and more 824671 7.3 15.1 98.9 840261 3.2 9.9 94.7 

Refuse or don’t know 60278 0.5 1.1 100.0 447282 1.7 5.3 100.0 

Total 5475334 48.5 100.0 8500818 32.8 100.0 

Do not work 5825573 51.5 17424105 67.2 

Total 11300907 100.0 25924922 100.0 

Source: NDSA. Note: Some fi gures should be considered with caution due to low number of observations.† Weighted by the number of inhabitants in the province. 

Table 48. Distribution of Active Persons Aged 15-64 with Disability and 

Non-Disabled according to the Monthly Professional Income 

Classes of Income 

0 AFAs 

100 to 1000 AFAs 

1100 to 2000 AFAs 

2100 to 3000 AFAs 

3050 to 4000 AFAs 

4050AFAs to 5500 AFAs 

6000 AFAs and more 

0 AFAs 


Disability 

Non-Disabled† 

Total 

Number 12341 316722 329063 

% in income 9.3 5.9 6.0 

Number 20786 541077 561863 

% in income 15.6 10.1 10.3 

Number 35725 888327 924052 

% in income 26.8** 16.6** 16.9 

Number 25982 1215572 1241554 

% in income 19.5 22.8 22.7 

Number 12341 834545 846886 

% in income 9.3 15.6 15.5 

Number 8444 678522 686966 

% in income 6.3* 12.7* 12.5 

Number 14940 809732 824672 

% in income 11.2 15.2 15.1 

Number 2598 57680 60278 

Refuse or don’t know 

% of income 2.0 1.1 1.1 

Total Number 133157 5342177 5475334 



Table 49. Distribution of Active Males Aged 15-64 with Disability and Non- 

Disabled according to the Monthly Professional Income 

Classes of Income 

Males with 

disability 

Non-disabled 

Males † 

Total 

0 AFAs Number 12341 249428 261769 

% in income 9.9 5.2 5.3 

100 to 1000 AFAs Number 15589 401813 417402 

% in income 12.5 8.4 8.5 

1100 to 2000 AFAs Number 33127 781801 814928 

% in income 26.6** (1) 16.3** (1) 16.5 

2100 to 3000 AFAs Number 25982 1090728 1116710 

% in income 20.8 22.7 22.6 

3050 to 4000 AFAs Number 11692 809082 820774 

% in income 9.4* (1) 16.8* (1) 16.6 

4050AFAs to 5500 AFAs Number 8444 645655 654099 

% in income 6.8* (1) 13.4* (1) 13.3 

6000 AFAs and more 

0 AFAs 

Refuse or don’t know 

Number 14940 773357 788297 

% in income 12.0 16.1 16.0 

Number 2598 57680 60278 

% of income 2.1 1.2 1.2 

Total Number 124713 4809544 4934257 

Source: NDSA. Note: Some fi gures should be considered with caution due to low number of observations.† Weighted by the population of 

the province. (1) Test of comparison of proportion between Persons with Disabilities and Non-Disabled. ** Signifi cant at p

(Table 50 Contd. from previous page) 

List of Goods 

Tractor 

Generator 

Kerosene lamp 

Sewing machine 

House or apartment 

Non-Disabled 


Disability† 

Total 

Number 37 16 53 

% in type of good 2.1 1.7 1.9 

Number 192 86 278 


Number 1674 926 2600 


Number 839 411 1250 

% in type of good 48.6** (1) 43.3** (1) 46.0 

Number 1346 727 2073 


Source: NDSA. Note: †Some fi gures should be considered with caution due to low number of observations. (1) Test of comparison of proportion 

between Persons with Disabilities and Non-Disabled. ** Signifi cant at p

Table 52. Distribution of Households according to the Ownership of Goods and 

Equipments by Urban and Rural Settings 

List of Goods and Equipments† Urban Rural Total 

Radio 

Television 

Pressure cooker 

Oven, hotplate 

Refrigerator 

Bukhari 

Bicycle 

Motorbike 

Car 

Tractor 

Generator 

Kerosene lamp 



Number 4949 11831 16780 


Number 3383 1712 5095 


Number 4783 8827 13610 


Number 514 968 1482 


Number 1190 60 1250 


Number 3503 7929 11432 

% in type of good 60.7** 45.4** 53.0 

Number 3104 4284 7388 


Number 907 1431 2338 


Number 623 382 1005 


Number 111 487 598 


Number 1604 1220 2824 

Percent 27.8** (1) 7.0** (1) 17.4 

Number 5527 16911 22438 


Number 3698 8076 11774 


Number 3846 14396 18242 


Source: NDSA. Note: † Weighted by the number of household in the cluster without Persons with Disabilities living there. (1) Test of comparison 

of proportion between Persons with Disabilities and Non-Disabled. ** Signifi cant at p

Table 53. Distribution of Households according to Gender of the Head of 

Household and Ownership of Goods and Equipments 

Goods and Equipments 

Radio 

Television 

Pressure cooker 

Oven, hotplate 

Refrigerator 

Bukhari 

Bicycle 

Motorbike 

Car 

Tractor 

Generator 

Kerosene lamp 




the HH 

Woman Head 


Total 

Number 16186 569 16755 


Number 4863 207 5070 


Number 13045 540 13585 


Number 1422 60 1482 


Number 1220 30 1250 


Number 10984 423 11407 


Number 7109 254 7363 


Number 2213 100 2313 


Number 1005 0 1005 


Number 596 2 598 


Number 2677 147 2824 


Number 21379 1034 22413 


Number 11197 577 11774 


Number 17462 780 18242 


Source: NDSA. Note: † Weighted by the number of household in the cluster without Persons with Disabilities living there. (1) Test of comparison 

of proportion between Persons with Disabilities and Non-Disabled. ** Signifi cant at p

Table 55. Distribution of Households according to Ownership of Livestock 

Ownership of Livestock 

Owns livestock 



Disability† 



Disabilities 

Total 

Number 15413 1297 16710 

% in ownership category 73.6 73.2 73.5 

Number 5536 475 6011 

Do not own livestock 


Total Number 20949 1772 22721 

Source: NDSA. Note:† Weighted by the number of household in the cluster without Persons with Disabilities living there. (1)Test of comparison 



Types of Animals 

No cow 

1 cows 

2 cows 

3 cows 

Non- 

Disabled 

Persons 

with 

Disability 

Total 

Number 987 573 1560 

% in animal category 56.8 59.8 57.9 

Number 330 172 502 


Number 272 141 413 


Number 73 36 109 


Number 76 36 112 

4 Cows and more 


Total Number 1738 958 2696 

No goats 

1 to 5 Goats 

Number 1345 760 2105 


Number 313 156 469 


Number 80 42 122 

6 Goats and more 



No horses 

1 horse 

Number 1672 931 2603 


Number 49 23 72 



2 Horses and more 



No donkey 

1 donkey 

Number 1158 654 1812 


Number 441 237 678 


Number 139 67 206 

2 donkeys and more 



No chicken 

1 to 3 chickens 


Number 785 451 1236 


Number 382 197 579 


Number 300 162 462 


Number 271 148 419 

7 chickens and more 



No rooster 

Number 1656 924 2580 


(Table 60 contd. on next page) 




1 rooster 

Non- 

Disabled 

Persons 


Disability 

Total 

Number 62 28 90 



2 roosters and more 



No camel 

Number 1715 951 2666 



1 camels and more 



Source: NDSA. 

Table 59. Distribution of Households according to Ownership of Different Types 

of Animals 


0 sheep 

1 to 5 sheep 

HH without Person 

with Disability† 



Disabilities 

Total 

Number 16370 1409 17779 

% in animal category 76.0* (1) 78.0* (1) 76.1 

Number 3735 264 3999 

% in animal category 17.3** (1) 14.6** (1) 17.1 

Number 1437 133 1570 

6 sheep and more 


Total Number 21542 1806 23348 

0 cow 

1 cows 

2 cows 

3Cows 

Number 11907 1056 12963 


Number 4206 330 4536 


Number 3351 281 3632 


Number 1018 69 1087 


Number 1060 70 1130 

4 cows and more 


Total Number 21542 1806 23348 

0 goats 

1 to 5 goats 

Number 16101 1434 17535 


Number 4343 293 4636 


Number 1098 79 1177 

6 goats and more 


Total Number 21542 1806 23348 


Annexure 

89



0 horses 

1 horse 

HH without Person 

with Disability† 



Disabilities 

Total 

Number 20581 1752 22333 


Number 628 46 674 


Number 333 8 341 

2 horses and more 


Total Number 21542 1806 23348 

0 donkey 

1 donkey 

Number 14237 1218 15455 


Number 5457 458 5915 


Number 1848 130 1978 



Total Number 21542 1806 23348 

0 chicken 



Number 9884 823 10707 


Number 4549 386 4935 


Number 3809 311 4120 


Number 3300 286 3586 



Total Number 21542 1806 23348 

0 Rooster 

1 Rooster 

Number 20498 1734 22232 


Number 668 61 729 


Number 376 11 387 

2 Roosters and More 


Total Number 21542 1806 23348 

0 Camel 

Number 21109 1793 22902 


Number 433 13 446 

1 Camels and More 


Total Number 21542 1806 23348 

Source: NDSA. Note:† Weighted by the number of household in the cluster without persons with disabilities living there. (1)Test of comparison 

of proportion between households with and without a persons with disability. ** Signifi cant at p

Table 60. Distribution of People according to Gender of the Head of the Household 

and Ownership of Animals by Types of Animals 

Types of Animals Man Head of the HH Woman Head of the HH Total 

0 sheep 

1 to 5 sheep 

Number 16776 978 17754 


Number 3865 134 3999 


Number 1570 0 1570 

6 sheep and more 


Total Number 22211 1112 23323 

0 cow 

1 cows 

2 cows 

3cows 

Number 12064 874 12938 


Number 4409 127 4536 


Number 3550 82 3632 


Number 1085 2 1087 


Number 1103 27 1130 

4 cows and more 


Total Number 22211 1112 23323 

0 Goats 

1 to 5 goats 

Number 16606 904 17510 


Number 4503 133 4636 


Number 1102 75 1177 

6 goats and more 


Total Number 22211 1112 23323 

0 horses 

1 horse 

Number 21196 1112 22308 


Number 674 0 674 


Number 341 0 341 

2 horses and more 


Total Number 22211 1112 23323 

0 donkey 

1 donkey 

Number 14482 948 15430 


Number 5751 164 5915 


Number 1978 0 1978 



Total Number 22211 1112 23323 

0 chicken 


Number 10239 468 10707 


Number 4567 343 4910 



Annexure 

91


Types of Animals Man Head of the HH Woman Head of the HH Total 


Number 3932 188 4120 


Number 3473 113 3586 



Total Number 22211 1112 23323 

0 rooster 

1 rooster 

Number 21122 1085 22207 


Number 702 27 729 


Number 387 0 387 

2 roosters and more 


Total Number 22211 1112 23323 

0 camel 

Number 21765 1112 22877 


Number 446 0 446 

1 camels and more 


Total Number 22211 1112 23323** (2) 

Source: NDSA. Note: (1)Test of comparison of proportion between households with and without a persons with disabilities. ** Signifi cant at 

p

Table 63. Distribution of Households according to Ownership of Land by Urban 

and Rural Areas 

Ownership of Land† Urban Rural Total 

Own land 

Number 1766 11010 12776 

% in ownership category 30.8** (1) 63.3** (1) 55.2 

Number 3964 6393 10357 

Do not own land 


Total Number 5730 17403 23133** (2) 

Source: NDSA. Note:† Weighted by the number of household in the cluster without persons with disabilities living there. (1) Test of comparison 

of proportion between Urban and Rural. ** Signifi cant at p

Table 67. Distribution of Households according to the Size of the Land which is 

Cultivable 

Size of the Land Belonging to the Family† 



Disability 

HH with a Persons 


Total 

No land 

0.01 to 0.5 jerib 

Number 9466182 2250048 11716230 

% in land size 45.2 46.4 45.4 

Number 1243113 246180 1489293 

% in land size 5.9 5.1 5.8 

0.51 to 1 jerib 

Number 1867982 461182 2329164 

% in land size 8.9 9.5 9.0 

1.05 to 2 jerib Number 2108576 538479 2647055 

% in land size 10.1 11.1 10.3 


Number 2808014 546273 3354287 

% in land size 13.4 11.3 13.0 

Number 3466010 809991 4276001 

4 to 140 jerib 

% in land size 16.5 16.7 16.6 

Total Number 20959877 4852153 25812030 

Source: NDSA. Note: † Weighted by the population of the province. (1) Test of comparison of proportion between household with and without 

Persons with Disabilities. ** Signifi cant at p

Table 69. Distribution of Households according to Gender of the Head of the 

Household and to the Size of the Land of the Family which is Cultivable 

Size of the Land Belonging to the Family† 

No land cultivable 

0.01 to 0.5 jerib 





the HH 

Woman Head 


Total 

Number 11190223 493530 11683753 

% in land size 44.8** (1) 60.1** (1) 45.3 

Number 1467988 21305 1489293 

% in land size 5.9 2.6 5.8 

Number 2286034 43130 2329164 

% in land size 9.2 5.3 9.0 

Number 2485186 161868 2647054 

% in land size 10.0** (1) 19.7** (1) 10.3 

Number 3278289 75998 3354287 

% in land size 13.1 9.3 13.0 

Number 4251059 24943 4276002 

4 to 140 jerib 

% in land size 17.0** (1) 3.0** (1) 16.6 

Total Number 24958779** (2) 820774** (2) 25779553 

Source: NDSA. Note: † Weighted by the population of the province. (1) Test of comparison of proportion between Men and women head of 

household. ** Signifi cant at p


Having Taken a Loan in the Last 5 Years according to Gender and Age 

Disability† Gender Loan Less than 25 26 or More Total 

Non-Disabled 


Males 

Females 

Males 

Females 

Loan 

Number 1015510 2071681 3087191 

% in category 38.7** (1) 51.4** (1) 46.4 

Number 1608421 1959179 3567600 

No Loan 

% in category 61.3 48.6 53.6 

Total Number 2623931 4030860 6654791 

Loan 

Number 225265 701127 926392 

% in category 9.8** (1) 30.1** (1) 20.0 

Number 2079476 1628557 3708033 

No Loan 

% in category 90.2 69.9 80.0 

Total Number 2304741** (2) 2329684 4634425 

Loan 

Number 20786 108475 129261 

% in category 32.7** (1) 55.3** (1) 49.8 

Number 42870 87690 130560 

No Loan 

% in category 67.3 44.7 50.2 

Total Number 63656 196165 259821 

Loan 

Number 8444 37674 46118 

% in category 18.8** (1) 29.4** (1) 26.7 

Number 36375 90288 126663 

No Loan 

% in category 81.2 70.6 73.3 

Total Number 44819** (2) 127962 172781 

Source: NDSA. Note: † Weighted by the population of the province. (1) test of comparison of proportion between Persons with Disabilities 

and Non-Disablities. ** Signifi cant at p

Table 73. Distribution of Persons with Disability and Non-Disabled Above 14 Having Taken a Loan in the 

Last 5 Years according to the Major Geographical Areas 

Disability† 

Non-Disabled 


Disability 

Loan 

Loan 

Central 

Region 

Western 

Region 

Eastern 

Region 

Southern 

Region 

North Western 

Region 

North Eastern 

Region 

Number 1143991 691903 631105 389471 531983 667350 4055803 

% in category 34.4** (1) 42.6 35.9 34.7** (1) 32.0* (1) 37.0** (1) 35.9 

No Number 2178857 930418 1125544 732435 1131650 1134508 7233412 

Loan % in category 65.6 57.4 64.1 65.3 68.0 63.0 64.1 

Total Number 3322848** (2) 1622321 1756649 1121906 1663633 1801858 11289215 

Loan 

Number 65605 32478 20136 17538 20136 19487 175380 

% in category 45.1** (1) 40.7 35.2 35.5** (1) 35.2* (1) 42.9** (1) 40.4 

No Number 79245 46768 37024 31828 37024 25333 257222 

Loan % in category 54.5 58.5 64.8 64.5 64.8 55.7 59.2 

Total Number 145500** (2) 79896 57160 49366 57160 45470 434552 

Total 

Source: NDSA. Note: † Weighted by the population of the province. (1) test of comparison of proportion between Persons with Disabilities and Non-Disablities by region. ** Signifi cant at 

p


according to the Amounts of Loans and Age Groups 

Disability† Amount of Loan Less than 25 26 or More Total 

Non-Disabled 


Disability 

30 to 5000 AFAs 

5100 to 12000 AFAs 

12100 to 30000 AFAs 

Number 429224 726589 1155813 

% in amount category 34.6** (1) 26.2** (1) 28.8 

Number 366867 682030 1048897 

% in amount category 29.6 24.6 26.2 

Number 371674 587195 958869 


Number 73010 774396 847406 

31000 AFAs and above 


Total Number 1240775** (2) 2770210** (2) 4010985 

30 to 5000 AFAs 

5100 to 12000 AFAs 

12100 to 30000 AFAs 

Number 11692 34426 46118 


Number 6496 35076 41572 


Number 8444 37024 45468 


Number 2598 39623 42221 



Total Percent 29230* (2) 146149* (2) 175379 

Source: NDSA. Note: † Weighted by the population of the province. (1) test of comparison of proportion between less and more than 25 

years old. ** Signifi cant at p


according to the Amounts of Loans and Living Area 

Disability† Amount of Loan Urban Rural Total 

Non-Disabled 


Disability 

30 to 5000 AFAs 

5100 to 12000 AFAs 

12100 to 30000 AFAs 

Number 279827 875986 1155813 


Number 214482 837662 1052144 

% in amount category 21.7* (1) 27.7* (1) 26.2 

Number 255274 703595 958869 


Number 239165 604993 844158 



Total Number 988748 3022236 4010984 

30 to 5000 AFAs 

5100 to 12000 AFAs 

12100 to 30000 AFAs 

Number 11692 34426 46118 

% in amount category 20.0* 29.4* 26.3 

Number 13641 27931 41572 


Number 14940 30529 45469 


Number 18187 24033 42220 



Total Number 58460 116919 175379 

Source: NDSA. Note: † Weighted by the population of the province. (1) test of comparison of proportion between urban and rural areas. ** 

Signifi cant at p


according to the Level of Debt by Age Group 

Disability or Not Debt in Quartiles† Less than 25 26 or More Total 

Non-Disabled 


Disability 


1800 to 7800 AFAs 

8000 to 20000 

AFAs 

Number 428964 702685 1131649 

% in debt amount category 34.6** (1) 25.3** (1) 28.2 

Number 295936 611618 907554 

% in debt amount category 23.9 22.1 22.6 

Number 430393 738411 1168804 


20500 AFAs and Number 85481 720093 805574 

above 


Total Number 1240774* (2) 2772807* (2) 4013581 


1800 to 7800 AFAs 

8000 to 20000 

AFAs 

Number 4547 20786 25333 


Number 9743 35725 45468 


Number 9094 40922 50016 


20500 AFAs and Number 5846 48716 54562 

above 


Total Number 29230 146149 175379 

Source: NDSA. Note: † Weighted by the population of the province. (1) test of comparison of proportion between less and more than 25 

years old. ** Signifi cant at p

Table 81. Distribution of Persons with disability and Non-disabled Above 14 

according to the Level of Debt by Living Area 

Disability or Not Debt in Quartiles† Urban Rural Total 

Non-Disabled 


Disability 


1800 to 7800 

AFAs 

8000 to 20000 

AFAs 

Number 370115 761535 1131650 


Number 84961 822593 907554 


Number 213962 954842 1168804 


20500 AFAs Number 322308 483267 805575 

and above % in debt amount category 32.5** (1) 16.0** (1) 20.1 

Total Number 991346** (2) 3022237** (2) 4013583 


1800 to 7800 

AFAs 

8000 to 20000 

AFAs 

Number 7795 17538 25333 


Number 12991 32478 45469 


Number 14940 35076 50016 


20500 AFAs Number 22734 31828 54562 

and above % in debt amount category 38.9** (1) 27.2** (1) 31.1 

Total Number 58460 116920 175380 

Source: NDSA. Note: † Weighted by the population of the province. (1) test of comparison of proportion between urban and rural areas. ** 

Signifi cant at p


according to the Purpose of Loan 

Purpose of Loan† 

Food 

School expenditure 

Health expenditure 

Professional equipment 

House equipment 

Ceremony 

Dowry 

Land purchase/rent 

Property purchase 

Good purchase 

Other purpose 

Non-Disabled 


Disability 

Total 

Number 1597249 82493 1679742 

% in purpose of loan category 39.8** (1) 47.0** (1) 40.1 

Number 181225 1949 183174 

% in purpose of loan category 4.5 1.1 4.4 

Number 829868 81194 911062 


Number 634353 11692 646045 

% in purpose of loan category 15.8* (1) 6.7* (1) 15.4 

Number 880923 29879 910802 


Number 670598 13641 684239 


Number 35595 1949 37544 


Number 137445 6496 143941 


Number 82363 3897 86260 


Number 88469 5196 93665 


Number 199153 9743 208896 




Tables Related to Social Income 


Having Received Money according to Gender 

Disability or Not Gender† Received Not Received Total 

Non-Disabled 


Males 

Females 

Total 

Males 

Females 

Total 

Number 1820565 4780184 6600749 

% in gender 27.6** (1) 72.4 100.0 

Number 2533513 2044530 4578043 

% in gender 55.3 44.7 100.0 

Number 4354078 6824714 11178792 

% in Non-Disabled 38.9** (2) 61.1** (2) 100.0 

Number 111723 148098 259821 

% in gender 43.0** (1) 57.0 100.0 

Number 85091 88339 173430 

% in gender 49.1 50.9 100.0 

Number 196814 236437 433251 

% in Persons with 

Disabilities 

45.4** (2) 54.6** (2) 100.0 

Source: NDSA. Note: † Weighted by the population of the province. (1) Test of comparison of proportion between Persons with Disabilities and 


Table 87. Distribution of Persons with Disability and Non-Disabled above 14 Having Received Money 

according to the 3 Main Donors 

Donors† 

Husband/wife 

Father/mother 

Brother/sister 

Child or other 

family member 

Non- 

Disabled 

First Answer Second Answer Third Answer 

Persons 


Disability 

Total 

Non- 

Disabled 

Persons 


Disability 

Total 

Non- 

Disabled 

Persons 


Disability 

Number 1596339 43520 1639859 334000 10393 344393 230981 3248 234229 

% in donor category 36.7 21.9 36.0 22.3 14.0 21.9 66.6 18.5 64.3 

Number 1126583 42221 1168804 214872 6496 221368 20786 3248 24034 


Number 848185 40272 888457 513926 21435 535361 19616 3897 23513 


Number 403632 42221 445853 276449 24033 300482 57290 5196 62486 


Friends 

Number 254495 9743 264238 72230 5846 78076 8444 0 8444 


State pension 

Number 13641 1949 15590 0 0 0 0 650 650 

% in donor category 0.3 1.0 0.3 0 0 0 0.0 3.7 0.2 

Local leader 

Number 0 3897 3897 7145 1949 9094 0 1299 1299 


NGOs, Number 111203 14290 125493 79375 3897 83272 9743 0 9743 

employer 

or other % in donor category 2.6 7.2 2.8 5.3 5.3 5.3 2.8 0.0 2.7 

Total Number 4354078 198763 4552841 1497997 74049 1572046 346860 17538 364398 


Table 88. Distribution of Persons with Disability and Non-Disabled above 14 Having Received Money 

according to the Donors and Gender 

Total 

Disability 

Gender† 

Husband/ 

Wife 

Father 

/Mother 

Brother/ 

Sister 

Child 

Friends 

State 

Pension 

Local or 

Religious 

Leader 

NGO or 

Other 

Total 

Non-Disabled 


Disability 

Males 

Females 

Total 

Males 

Females 

Number 76647 909113 648773 355044 260989 13641 43520 638249 2945976 

% in gender 2.6 30.9 22.0 12.1 8.9 0.5 1.5 21.7 100.0 

Number 2084673 453128 732955 382326 74179 7145 35855 980694 4750955 

% in gender 43.9 9.5 15.4 8.0 1.6 0.2 0.8 20.6 100.0 

Number 2161320 1362241 1381728 737370 335168 20786 79375 1618943 7696931 

% in Non- 

Disabled 

28.1 17.7 18.0 9.6 4.4 0.3 1.0 21.0 100.0 

Number 6496 34426 44170 39623 13640 3898 7795 50665 200713 

% in gender 3.2 17.2 22.0 19.7 6.8 1.9 3.9 25.2 100.0 

Number 50665 17537 21435 31827 1949 650 1950 37675 163688 

% in gender 31.0 10.7 13.1 19.4 1.2 0.4 1.2 23.0 100.0 

Number 57161 51963 65605 71450 15589 4548 9745 88340 364401 

Total % in Person 


15.7 14.3 18.0 19.6 4.3 1.2 2.7 24.2 100.0 

Total Number 2218481 1414204 1447333 808820 350757 25334 89120 1707283 8061332 




Having Received Money according to Amounts 

Money Received by Year in Quartiles† 

Less than 700 AFAs 

710 to 3200 AFAs 

3300 to 12000 AFAs 

Non-Disabled 


Disability 

Total 

Number 1110214 50665 1160879 


Number 1048377 48716 1097093 


Number 1147629 46118 1193747 


Number 1007715 41571 1049286 



Total Number 4313935 187070 4501005 



The National Disability Survey in Afghanistan was carried out in 2005. It is the fi rst study that covered the entire 

territory. Based on the International Classifi cation of Functioning, Disability and Health of the World Health 

Organization, and the Capabilities Approach of Amartya Sen, the NDSA aims to provide insight into the living 

conditions, needs and hopes of Afghans with disability and their families. 

The present volume of the NDSA results looks more closely at employment, income and livelihoods of persons with 

disability. A common belief is that persons with disability, suffering from discrimination and exclusion, are unable 

to access existing resources and are more at risk of poverty than non-disabled people. Comparing the situation 

of families living with persons with disability to those composed only of persons considered as non-disabled; the 

present report examines vulnerability of Afghans to shocks, and tries to identify signs and indicators of poverty. 

A major result is that access to basic commodities, adequate housing conditions, labour market or even social 

participation is not inevitably worse for households with a person with disability. The situation concerning livelihood 

dimensions is particularly diffi cult for families headed by a woman. 

European Union 

United Nations

understanding vulnerability of afghans with disability - Handicap ...

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