Demographic and Health Survey 2015
Afghanistan, 2015 - 2016
Central Statistics Organization (CSO), Ministry of Public Health (MoPH)
Last modified
May 23, 2017
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Metadata
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Identification
IDNO
AFG_2015_DHS_v01_M
Title
Demographic and Health Survey 2015
Countries
| Name | Code |
|---|---|
| Afghanistan | AFG |
Study notes
The 2015 Afghanistan Demographic and Health Survey (2015 AfDHS) is the first DHS survey conducted in Afghanistan. The main objective of the 2015 AfDHS is to provide up-to-date information on fertility and childhood mortality levels; fertility preferences; awareness, approval, and use of family planning methods; maternal and child health; and knowledge and attitudes toward HIV/AIDS and other sexually transmitted infections (STIs). The 2015 AfDHS calls for a nationally representative sample of 25,650 residential households; in all the sample households, all ever-married women age 15-49 who are usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed in the survey. In half of the sample households, all ever-married men age 15-49 who are usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed in the survey. In each household, one woman age 15-49 was randomly selected to be eligible for the Domestic Violence module.
The 2015 AfDHS was designed to provide most of the key indicators for the country as a whole, for urban and rural areas separately, and for each of the 34 provinces in Afghanistan. These provinces are located in eight regions as follows:
- The Northern region: Balkh, Faryab, Jawzjan, Samangan, and Sar-E-Pul
- The North Eastern region: Badakhshan, Baghlan, Kunduz, and Takhar
- The Western region: Badghis, Farah, Ghor, and Herat
- The Central Highland region: Bamyan and Daykundi
- The Capital region: Kabul, Kapisa, Logar, Panjsher, Parwan, and Wardak
- The Southern region: Ghazni, Helmand, Kandahar, Nimroz, Urozgan, and Zabul
- The South Eastern region: Khost, Paktika, and Paktya
- The Eastern region: Kunarha, Laghman, Nangarhar, and Nooristan
The 2015 AfDHS was designed to provide most of the key indicators for the country as a whole, for urban and rural areas separately, and for each of the 34 provinces in Afghanistan. These provinces are located in eight regions as follows:
- The Northern region: Balkh, Faryab, Jawzjan, Samangan, and Sar-E-Pul
- The North Eastern region: Badakhshan, Baghlan, Kunduz, and Takhar
- The Western region: Badghis, Farah, Ghor, and Herat
- The Central Highland region: Bamyan and Daykundi
- The Capital region: Kabul, Kapisa, Logar, Panjsher, Parwan, and Wardak
- The Southern region: Ghazni, Helmand, Kandahar, Nimroz, Urozgan, and Zabul
- The South Eastern region: Khost, Paktika, and Paktya
- The Eastern region: Kunarha, Laghman, Nangarhar, and Nooristan
Kind of data
Sample survey data [ssd]
Coverage
Geographic coverage
National coverage
Geographic unit
Northern region North Eastern region Western region Central Highland region Capital region Southern region South Eastern region Eastern region
Unit of analysis
- Household
- Individual
- Woman age 15-49
- Man age 15-49
- Individual
- Woman age 15-49
- Man age 15-49
Universe
The survey covered all de jure household members (usual residents), and all ever-women aged 15-49 years resident in the household.
Producers and sponsors
Authoring entity
| Name | Affiliation |
|---|---|
| Central Statistics Organization (CSO) | Government of Islamic Republic of Afghanistan |
| Ministry of Public Health (MoPH) | Government of Islamic Republic of Afghanistan |
Producer(s)
| Name | Role |
|---|---|
| ICF International | Provided technical assistance through the DHS Program |
Funding agencies
| Name | Abbreviation | Role |
|---|---|---|
| Government of Islamic Republic of Afghanistan | GovAFG | Funded the study |
| United States Agency for International Development | USAID | Funded the study |
| United Nations Children’s Fund | UNICEF | Funded the study |
Sampling
Sampling procedure
The sampling frame used for the 2015 AfDHS is an updated version of the Household Listing Frame, prepared in 2003-04 and updated in 2009, provided by the Central Statistics Organization (CSO). The sampling frame had information on 25,974 enumeration areas (EAs). An EA is a geographic area consisting of a convenient number of dwelling units that serve as counting units for the census. The sampling frame contained information about the location (province, district, and control area), the type of residence (urban or rural), and the estimated number of residential households for each of the 25,974 EAs. Satellite maps were also available for each EA, which delimited the geographic boundaries of the area. The sampling frame excluded institutional populations such as persons in hotels, barracks, and prisons.
The 2015 AfDHS followed a stratified two-stage sample design and was intended to allow estimates of key indicators at the national level, in urban and rural areas, and for each of the 34 provinces of Afghanistan. The first stage involved selecting sample points (clusters) consisting of EAs. A total of 950 clusters were selected, 260 in urban areas and 690 in rural areas. It was recognized that some areas of the country might be difficult to reach because of ongoing security issues. Therefore, to mitigate the situation, reserve clusters were selected in all of the provinces to replace the inaccessible clusters. The 101 reserve clusters that were preselected did not exceed 10% of the selected clusters in the province.
The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 27 households per cluster were selected through an equal probability systematic selection process, for a total sample size of 25,650 households. Because of the approximately equal sample size in each province, the sample is not self-weighting at the national level, and weighting factors have been calculated, added to the data file, and applied so that results are representative at the national level.
All ever-married women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. In half of the households, all ever-married men age 15-49 who were either residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed.
During the household listing operation, more than 70 selected clusters were identified as insecure. Therefore, a decision was made to carry out the household listing operation in all of the 101 preselected reserve clusters, which also accounted for the possibility of identifying more insecure clusters during data collection. Household listing was successfully completed in 976 of 1,051 clusters. Overall, the survey was successfully carried out in 956 clusters.
For further details on sample selection, see Appendix A of the final report.
The 2015 AfDHS followed a stratified two-stage sample design and was intended to allow estimates of key indicators at the national level, in urban and rural areas, and for each of the 34 provinces of Afghanistan. The first stage involved selecting sample points (clusters) consisting of EAs. A total of 950 clusters were selected, 260 in urban areas and 690 in rural areas. It was recognized that some areas of the country might be difficult to reach because of ongoing security issues. Therefore, to mitigate the situation, reserve clusters were selected in all of the provinces to replace the inaccessible clusters. The 101 reserve clusters that were preselected did not exceed 10% of the selected clusters in the province.
The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 27 households per cluster were selected through an equal probability systematic selection process, for a total sample size of 25,650 households. Because of the approximately equal sample size in each province, the sample is not self-weighting at the national level, and weighting factors have been calculated, added to the data file, and applied so that results are representative at the national level.
All ever-married women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. In half of the households, all ever-married men age 15-49 who were either residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed.
During the household listing operation, more than 70 selected clusters were identified as insecure. Therefore, a decision was made to carry out the household listing operation in all of the 101 preselected reserve clusters, which also accounted for the possibility of identifying more insecure clusters during data collection. Household listing was successfully completed in 976 of 1,051 clusters. Overall, the survey was successfully carried out in 956 clusters.
For further details on sample selection, see Appendix A of the final report.
Response rate
A total of 25,741 households were selected for the sample, of which 24,941 were occupied during the survey fieldwork. Of the occupied households, 24,395 were successfully interviewed, yielding a response rate of 98%.
In the interviewed households, 30,434 ever-married women age 15-49 were identified for individual interviews; interviews were completed with 29,461 of these women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 11,778 ever-married men age 15-49 were identified and 10,760 were successfully interviewed, yielding a response rate of 91%. The lower response rate for men was likely due to their more frequent and longer absences from the household.
The response rates are lower in urban areas than in rural areas. The difference is more prominent for men than women, as men in the urban areas are often away from their households for work. Moreover, given the security situation in the country, the field teams could not carry out interviews in the late evenings when more men are at home.
In the interviewed households, 30,434 ever-married women age 15-49 were identified for individual interviews; interviews were completed with 29,461 of these women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 11,778 ever-married men age 15-49 were identified and 10,760 were successfully interviewed, yielding a response rate of 91%. The lower response rate for men was likely due to their more frequent and longer absences from the household.
The response rates are lower in urban areas than in rural areas. The difference is more prominent for men than women, as men in the urban areas are often away from their households for work. Moreover, given the security situation in the country, the field teams could not carry out interviews in the late evenings when more men are at home.
Weighting
A spreadsheet containing all sampling parameters and selection probabilities was prepared to facilitate the calculation of the design weights. Design weights were adjusted for household nonresponse and individual nonresponse to obtain the sampling weights for households and for women and men, respectively. Nonresponse is adjusted at the sampling stratum level. For the household sampling weight, the household design weight is multiplied by the inverse of the household response rate, by stratum. For the women’s individual sampling weight, the household sampling weight is multiplied by the inverse of the women’s individual response rate, by stratum. For the men’s individual sampling weight, the household sampling weight for the male subsample is multiplied by the inverse of the men’s individual response rate, by stratum. After adjusting for nonresponse, the sampling weights are normalized to get the final standard weights that appear in the data files. The normalization process is aimed at obtaining a total number of unweighted cases equal to the total number of weighted cases using normalized weights at the national level, for the total number of households, women, and men. Normalization is done by multiplying the sampling weight by the estimated total sampling fraction obtained from the survey for the household weight, the individual woman’s weight, and the individual man’s weight. The normalized weights are relative weights that are valid for estimating means, proportions, ratios, and rates, but they are not valid for estimating population totals or for pooled data. Special weights for domestic violence were calculated that account for the selection of one woman per household.
Data Collection
Dates of collection
| Start | End |
|---|---|
| 2015-06 | 2016-02 |
Mode of data collection
Face-to-face [f2f]
Questionnaires
Three questionnaires were used for the 2015 AfDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires, based on the DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Afghanistan. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors. After all questionnaires were finalized in English, the questionnaires were translated into Dari and Pashto. The survey protocol and the questionnaires were approved by the ICF Institutional Review Board (IRB) and the Ministry of Public Health of Afghanistan.
Data collector(s)
| Name | Abbreviation | Affiliation |
|---|---|---|
| Central Statistics Organization | CSO | Government of Islamic Republic of Afghanistan |
Data Processing
Data editing
All completed questionnaires were edited in the field and dispatched to the data processing center at the CSO central office in Kabul. CSPro data processing software was used to enter the data. All the data were entered twice for 100% verification.
Data Appraisal
metadata.study_desc.method.analysis_info.sampling_error_estimates
The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions by either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2015 Afghanistan Demographic and Health Survey (2015 AfDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2015 AfDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.
If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2015 AfDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed by SAS programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
The Taylor linearization method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration.
Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2015 AfDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.
If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2015 AfDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed by SAS programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
The Taylor linearization method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration.
Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.
Other forms of data appraisal
Data Quality Tables
- Household age distribution
- Age distribution of eligible and interviewed women
- Age distribution of eligible and interviewed men
- Completeness of reporting
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
- Sibship size and sex ratio of siblings
Note: See detailed data quality tables in APPENDIX C of the report.
- Household age distribution
- Age distribution of eligible and interviewed women
- Age distribution of eligible and interviewed men
- Completeness of reporting
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
- Sibship size and sex ratio of siblings
Note: See detailed data quality tables in APPENDIX C of the report.
Data access
Access authorities
| Name | URI | |
|---|---|---|
| The DHS Program | archive@dhsprogram.com | http://www.DHSprogram.com |
Access conditions
Request Dataset Access
The following applies to DHS, MIS, AIS and SPA survey datasets (Surveys, GPS, and HIV).
To request dataset access, you must first be a registered user of the website. You must then create a new research project request. The request must include a project title and a description of the analysis you propose to perform with the data.
The requested data should only be used for the purpose of the research or study. To request the same or different data for another purpose, a new research project request should be submitted. The DHS Program will normally review all data requests within 24 hours (Monday - Friday) and provide notification if access has been granted or additional project information is needed before access can be granted.
DATASET ACCESS APPROVAL PROCESS
Access to DHS, MIS, AIS and SPA survey datasets (Surveys, HIV, and GPS) is requested and granted by country. This means that when approved, full access is granted to all unrestricted survey datasets for that country. Access to HIV and GIS datasets requires an online acknowledgment of the conditions of use.
Required Information
A dataset request must include contact information, a research project title, and a description of the analysis you propose to perform with the data.
Restricted Datasets
A few datasets are restricted and these are noted. Access to restricted datasets is requested online as with other datasets. An additional consent form is required for some datasets, and the form will be emailed to you upon authorization of your account. For other restricted surveys, permission must be granted by the appropriate implementing organizations, before The DHS Program can grant access. You will be emailed the information for contacting the implementing organizations. A few restricted surveys are authorized directly within The DHS Program, upon receipt of an email request.
When The DHS Program receives authorization from the appropriate organizations, the user will be contacted, and the datasets made available by secure FTP.
GPS/HIV Datasets/Other Biomarkers
Because of the sensitive nature of GPS, HIV and other biomarkers datasets, permission to access these datasets requires that you accept a Terms of Use Statement. After selecting GPS/HIV/Other Biomarkers datasets, the user is presented with a consent form which should be signed electronically by entering the password for the user's account.
Dataset Terms of Use
Once downloaded, the datasets must not be passed on to other researchers without the written consent of The DHS Program. All reports and publications based on the requested data must be sent to The DHS Program Data Archive in a Portable Document Format (pdf) or a printed hard copy.
Download Datasets
Datasets are made available for download by survey. You will be presented with a list of surveys for which you have been granted dataset access. After selecting a survey, a list of all available datasets for that survey will be displayed, including all survey, GPS, and HIV data files. However, only data types for which you have been granted access will be accessible. To download, simply click on the files that you wish to download and a "File Download" prompt will guide you through the remaining steps.
The following applies to DHS, MIS, AIS and SPA survey datasets (Surveys, GPS, and HIV).
To request dataset access, you must first be a registered user of the website. You must then create a new research project request. The request must include a project title and a description of the analysis you propose to perform with the data.
The requested data should only be used for the purpose of the research or study. To request the same or different data for another purpose, a new research project request should be submitted. The DHS Program will normally review all data requests within 24 hours (Monday - Friday) and provide notification if access has been granted or additional project information is needed before access can be granted.
DATASET ACCESS APPROVAL PROCESS
Access to DHS, MIS, AIS and SPA survey datasets (Surveys, HIV, and GPS) is requested and granted by country. This means that when approved, full access is granted to all unrestricted survey datasets for that country. Access to HIV and GIS datasets requires an online acknowledgment of the conditions of use.
Required Information
A dataset request must include contact information, a research project title, and a description of the analysis you propose to perform with the data.
Restricted Datasets
A few datasets are restricted and these are noted. Access to restricted datasets is requested online as with other datasets. An additional consent form is required for some datasets, and the form will be emailed to you upon authorization of your account. For other restricted surveys, permission must be granted by the appropriate implementing organizations, before The DHS Program can grant access. You will be emailed the information for contacting the implementing organizations. A few restricted surveys are authorized directly within The DHS Program, upon receipt of an email request.
When The DHS Program receives authorization from the appropriate organizations, the user will be contacted, and the datasets made available by secure FTP.
GPS/HIV Datasets/Other Biomarkers
Because of the sensitive nature of GPS, HIV and other biomarkers datasets, permission to access these datasets requires that you accept a Terms of Use Statement. After selecting GPS/HIV/Other Biomarkers datasets, the user is presented with a consent form which should be signed electronically by entering the password for the user's account.
Dataset Terms of Use
Once downloaded, the datasets must not be passed on to other researchers without the written consent of The DHS Program. All reports and publications based on the requested data must be sent to The DHS Program Data Archive in a Portable Document Format (pdf) or a printed hard copy.
Download Datasets
Datasets are made available for download by survey. You will be presented with a list of surveys for which you have been granted dataset access. After selecting a survey, a list of all available datasets for that survey will be displayed, including all survey, GPS, and HIV data files. However, only data types for which you have been granted access will be accessible. To download, simply click on the files that you wish to download and a "File Download" prompt will guide you through the remaining steps.
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Data collection locations
The DHS Program
Original archive where collection stored
The DHS Program
http://dhsprogram.com/data/available-datasets.cfm
Cost: None
http://dhsprogram.com/data/available-datasets.cfm
Cost: None
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Contacts
Contact(s)
| Name | Affiliation | URI | |
|---|---|---|---|
| Information about The DHS Program | The DHS Program | reports@DHSprogram.com | http://www.DHSprogram.com |
| General Inquiries | The DHS Program | info@dhsprogram.com | http://www.DHSprogram.com |
| Data and Data Related Resources | The DHS Program | archive@dhsprogram.com | http://www.DHSprogram.com |
Metadata production
IDNo
DDI_AFG_2015_DHS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | The World Bank | Documentation of the DDI |
Version
Version 01 (February 2017). Metadata is excerpted from "Afghanistan Demographic and Health Survey 2015" Report.