Demographic and Health Survey 2014
Lesotho, 2014
Lesotho Ministry of Health (MOH)
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Identification
Survey ID Number
LSO_2014_DHS_v01_M
Title
Demographic and Health Survey 2014
Country/Economy
| Name | Country code |
|---|---|
| Lesotho | LSO |
Study type
Demographic and Health Survey (Standard) - DHS VII
Series Information
The 2014 Lesotho Demographic and Health Survey (2014 LDHS) is the third DHS conducted in Lesotho and follows surveys carried out in 2004 and 2009. The 2014 LDHS was designed to provide up-to-date information on key indicators needed to track progress in Lesotho’s population and health programmes. These indicators include fertility and child mortality levels, maternal mortality, fertility preferences and contraceptive use, utilisation of maternal and child health services, women’s and children’s nutrition status and knowledge, and attitudes and behaviours relating to HIV/AIDS and other sexually transmitted diseases.
The survey was designed to provide representative estimates for main demographic and health indicators for the country as a whole, for the urban and rural areas separately, for each of the four ecological zones, and for each of the ten administrative districts.
The survey was designed to provide representative estimates for main demographic and health indicators for the country as a whole, for the urban and rural areas separately, for each of the four ecological zones, and for each of the ten administrative districts.
Abstract
The primary objective of the 2014 LDHS project is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the LDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutrition, childhood and maternal mortality, maternal and child health, awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health issues such as smoking, knowledge of breast cancer, and male circumcision. In addition, the 2014 LDHS provides estimates of anaemia prevalence among children age 6-59 months and adults, and gives estimates of hypertension, HIV prevalence and HIV incidence among adults. The 2014 LDHS is a follow-up to the 2004 and 2009 LDHS surveys.
The information collected through the LDHS is intended to assist policy makers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.
The information collected through the LDHS is intended to assist policy makers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Household
- Individual
- Children age 0-5
- Woman age 15-49
- Man age 15-59
- Individual
- Children age 0-5
- Woman age 15-49
- Man age 15-59
Scope
Notes
The 2014 Lesotho Demographic and Health Survey covered the following topics:
HOUSEHOLD
• Identification
• Usual members and visitors in the selected households
• Background information on each person listed, such as relationship to head of the household, age, sex, marital status, survivorship and residence of bilogical parents, highest educational attainment, and birth registration
• Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, type of fuel used for cooking, materials used for the floor, roof and walls of the house, and ownership of various durable goods (these items are used as proxy indicators of the household's socioeconomic status)
BIOMARKER
• Weight, height, MUAC, and hemoglobin measurement for children age 0-5
• Weight, height, hemoglobin measurements and HIV testing for women age 15-49
• Weight, height, hemoglobin measurements and HIV testing formen age 15-59
INDIVIDUAL WOMAN
• Background characteristics (age, education, media exposure, and so on)
• Birth history and child mortality
• Knowledge and use of family planning methods
• Fertility preferences
• Antenatal, delivery, and postnatal care
• Breastfeeding and infant feeding practices
• Vaccinations and childhood illnesses
• Marriage and sexual activity
• Women’s work and husbands’ background characteristics
• Knowledge, awareness, and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs)
• Adult mortality, including maternal mortality
• Knowledge, attitudes, and behaviour related to other health issues (for example, tuberculosis, diabetes, breast and cervical cancer)
INDIVIDUAL MAN
• Respondent background
• Reproduction
• Contraception
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS
• Other health issues
• Averaging blood pressure measures
HOUSEHOLD
• Identification
• Usual members and visitors in the selected households
• Background information on each person listed, such as relationship to head of the household, age, sex, marital status, survivorship and residence of bilogical parents, highest educational attainment, and birth registration
• Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, type of fuel used for cooking, materials used for the floor, roof and walls of the house, and ownership of various durable goods (these items are used as proxy indicators of the household's socioeconomic status)
BIOMARKER
• Weight, height, MUAC, and hemoglobin measurement for children age 0-5
• Weight, height, hemoglobin measurements and HIV testing for women age 15-49
• Weight, height, hemoglobin measurements and HIV testing formen age 15-59
INDIVIDUAL WOMAN
• Background characteristics (age, education, media exposure, and so on)
• Birth history and child mortality
• Knowledge and use of family planning methods
• Fertility preferences
• Antenatal, delivery, and postnatal care
• Breastfeeding and infant feeding practices
• Vaccinations and childhood illnesses
• Marriage and sexual activity
• Women’s work and husbands’ background characteristics
• Knowledge, awareness, and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs)
• Adult mortality, including maternal mortality
• Knowledge, attitudes, and behaviour related to other health issues (for example, tuberculosis, diabetes, breast and cervical cancer)
INDIVIDUAL MAN
• Respondent background
• Reproduction
• Contraception
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS
• Other health issues
• Averaging blood pressure measures
Coverage
Geographic Coverage
National coverage
Universe
Target population for 2014 Lesotho DHS was women (age 15-49) and men (age 15-59) of reproductive age and their young children living in households.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Lesotho Ministry of Health (MOH) | Government of Lesotho |
Producers
| Name | Role |
|---|---|
| ICF International | Provided technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Government of Lesotho | GovLSO | Funded the study |
| United States Agency for International Development | USAID | Funded the study |
| United States President’s Emergency Plan for AIDS Relief | PEPFAR | Funded the study |
| United Nations Population Fund | UNFPA | Funded the study |
| United Nations Children's Fund | UNICEF | Funded the study |
| Global Fund to Fight AIDS, Tuberculosis and Malaria | GF | Funded the study |
| World Bank | WB | Funded the study |
| World Health Organization | WHO | Funded the study |
Sampling
Sampling Procedure
Sample Design
The sampling frame used for the 2014 LDHS is an updated frame from the 2006 Lesotho Population and Housing Census (PHC) provided by the Lesotho Bureau of Statistics (BOS). The sampling frame excluded nomadic and institutional populations such as persons in hotels, barracks, and prisons.
The 2014 LDHS followed a two-stage sample design and was intended to allow estimates of key indicators at the national level as well as in urban and rural areas, four ecological zones, and each of Lesotho's 10 districts. The first stage involved selecting sample points (clusters) consisting of enumeration areas (EAs) delineated for the 2006 PHC. A total of 400 clusters were selected, 118 in urban areas and 282 in rural areas.
The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected EAs in July 2014, and households to be included in the survey were randomly selected from these lists. About 25 households were selected from each sample point, for a total sample size of 9,942 households. Because of the approximately equal sample sizes in each district, the sample is not self-weighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level.
For further details on sample selection, see Appendix A of the final report.
The sampling frame used for the 2014 LDHS is an updated frame from the 2006 Lesotho Population and Housing Census (PHC) provided by the Lesotho Bureau of Statistics (BOS). The sampling frame excluded nomadic and institutional populations such as persons in hotels, barracks, and prisons.
The 2014 LDHS followed a two-stage sample design and was intended to allow estimates of key indicators at the national level as well as in urban and rural areas, four ecological zones, and each of Lesotho's 10 districts. The first stage involved selecting sample points (clusters) consisting of enumeration areas (EAs) delineated for the 2006 PHC. A total of 400 clusters were selected, 118 in urban areas and 282 in rural areas.
The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected EAs in July 2014, and households to be included in the survey were randomly selected from these lists. About 25 households were selected from each sample point, for a total sample size of 9,942 households. Because of the approximately equal sample sizes in each district, the sample is not self-weighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level.
For further details on sample selection, see Appendix A of the final report.
Response Rate
A total of 9,942 households were selected for the sample, of which 9,543 were occupied. Of the occupied households, 9,402 were successfully interviewed, yielding a response rate of 99%. This compares favourably to the 2009 LDHS response rate (98%).
In the interviewed households, 6,818 eligible women were identified for individual interviews; interviews were completed with 6,621 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 3,133 eligible men were identified and 2,931 were successfully interviewed, yielding a response rate of 94%. The lower response rate for men was likely due to their more frequent and longer absences from the household.
In the interviewed households, 6,818 eligible women were identified for individual interviews; interviews were completed with 6,621 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 3,133 eligible men were identified and 2,931 were successfully interviewed, yielding a response rate of 94%. The lower response rate for men was likely due to their more frequent and longer absences from the household.
Weighting
Due to the nonproportional allocation of the sample across districts and the differential response rates, sampling weights must be used in all analyses of the 2014 LDHS results to ensure that survey results are representative at both the national and domain level.
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 normalised to get the final standard weights that appear in the data files. The normalisation process is aimed at obtaining a total number of unweighted cases equal to the total number of weighted cases using normalised weights at the national level, for the total number of households, women, and men. Normalisation 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 normalised 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. The sampling weights for HIV testing are calculated in a similar way, but the normalization of the HIV weights is different. The individual HIV testing weights are normalized at the national level for women and men together so that HIV prevalence estimates calculated for women and men together are valid.
For further details on sampling weight, see Appendix A.4 of the final report.
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 normalised to get the final standard weights that appear in the data files. The normalisation process is aimed at obtaining a total number of unweighted cases equal to the total number of weighted cases using normalised weights at the national level, for the total number of households, women, and men. Normalisation 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 normalised 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. The sampling weights for HIV testing are calculated in a similar way, but the normalization of the HIV weights is different. The individual HIV testing weights are normalized at the national level for women and men together so that HIV prevalence estimates calculated for women and men together are valid.
For further details on sampling weight, see Appendix A.4 of the final report.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2014-09-22 | 2014-12-07 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
TRAINING OF FIELD STAFF
The MOH recruited and trained 100 people for the main fieldwork to serve as supervisors, interviewers, secondary editors, and reserve interviewers. The field staff main training took place over four weeks (6-29 August 2014) at the Khotsong Lodge in Thaba-Bosiu, Lesotho. The training course consisted of instruction regarding interviewing techniques and field procedures, a detailed review of questionnaire content, instruction on how to administer the paper and electronic questionnaires, instruction in weighing and measuring children and adults, mock interviews between participants in the classroom, practice biomarker collection between participants, and practice interviews with real respondents in areas outside the 2014 sample points. In addition, participants completed limited field practice in blood pressure measurement, anthropometry, anaemia testing, and blood collection for HIV testing.
FIELDWORK
Data collection was carried out by 15 field teams, each consisting of one team supervisor, two or three female interviewers, two or three male interviewers, and one driver. All interviewers on each team also served as biomarker technicians. Electronic data files containing interview results were transferred from each interviewer’s PDA to the team supervisor’s tablet each day. Six senior staff members from the MOH coordinated and supervised fieldwork activities. Electronic data files were transferred to the central office every few days via the secured Internet File Streaming System (IFSS). Participants in fieldwork monitoring also included two survey technical specialists from The DHS Program.
Data collection took place over a 2.5-month period, from 22 September 2014 through 7 December 2014. The substantial gap between the end of the main training and the start of fieldwork was due to concerns about team safety following political disturbances on 30 August 2014. Immediately prior to the launch, the MOH conducted a two-day refresher training course for interviewers and supervisors at MOH headquarters.
The MOH recruited and trained 100 people for the main fieldwork to serve as supervisors, interviewers, secondary editors, and reserve interviewers. The field staff main training took place over four weeks (6-29 August 2014) at the Khotsong Lodge in Thaba-Bosiu, Lesotho. The training course consisted of instruction regarding interviewing techniques and field procedures, a detailed review of questionnaire content, instruction on how to administer the paper and electronic questionnaires, instruction in weighing and measuring children and adults, mock interviews between participants in the classroom, practice biomarker collection between participants, and practice interviews with real respondents in areas outside the 2014 sample points. In addition, participants completed limited field practice in blood pressure measurement, anthropometry, anaemia testing, and blood collection for HIV testing.
FIELDWORK
Data collection was carried out by 15 field teams, each consisting of one team supervisor, two or three female interviewers, two or three male interviewers, and one driver. All interviewers on each team also served as biomarker technicians. Electronic data files containing interview results were transferred from each interviewer’s PDA to the team supervisor’s tablet each day. Six senior staff members from the MOH coordinated and supervised fieldwork activities. Electronic data files were transferred to the central office every few days via the secured Internet File Streaming System (IFSS). Participants in fieldwork monitoring also included two survey technical specialists from The DHS Program.
Data collection took place over a 2.5-month period, from 22 September 2014 through 7 December 2014. The substantial gap between the end of the main training and the start of fieldwork was due to concerns about team safety following political disturbances on 30 August 2014. Immediately prior to the launch, the MOH conducted a two-day refresher training course for interviewers and supervisors at MOH headquarters.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Lesotho Ministry of Health (MOH) | MOH | Government of Lesotho |
Questionnaires
Questionnaires
Three questionnaires were used for the 2014 LDHS: 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 Lesotho. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. After the preparation of the definitive questionnaires in English, the questionnaires were translated into Sesotho.
Data Processing
Data Editing
In this survey, instead of using paper questionnaires, interviewers used personal digital assistants (PDAs) to record responses during interviews, and team supervisors managed the data using tablet computers. The PDAs and tablets were equipped with Bluetooth technology to enable remote electronic transfer of files (e.g., transfer of assignment sheets from team supervisors to interviewers and transfer of completed questionnaires from interviewers to supervisors). The computer-assisted personal interviewing (CAPI) data collection system employed in the 2014 LDHS was developed by The DHS Program using the mobile version of CSPro.
The data processing operation included secondary editing, which involved resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by one person who took part in the main fieldwork training. Data editing was accomplished using CSPro software. Secondary editing and data processing were initiated in October 2014 and completed in February 2015.
The data processing operation included secondary editing, which involved resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by one person who took part in the main fieldwork training. Data editing was accomplished using CSPro software. Secondary editing and data processing were initiated in October 2014 and completed in February 2015.
Data Appraisal
Estimates of Sampling Error
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 on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2014 Lesotho Demographic and Health Survey (2014 LDHS) 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 2014 LDHS 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 2014 LDHS 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 International. These programs use the Taylor linearisation 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 linearisation 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 estimate of sampling error is 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 2014 LDHS 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 2014 LDHS 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 International. These programs use the Taylor linearisation 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 linearisation 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 estimate of sampling error is presented in APPENDIX B of the survey report.
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
- Sibship size and sex ratio of siblings
Note: See detailed data quality tables in APPENDIX D 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
- Sibship size and sex ratio of siblings
Note: See detailed data quality tables in APPENDIX D of the report.
Access policy
Access authority
| Name | URL | |
|---|---|---|
| The DHS Program | archive@dhsprogram.com | http://www.DHSprogram.com |
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| 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 |
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
Location of Data Collection
The DHS Program
Archive where study is originally 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.
Metadata production
DDI Document ID
DDI_LSO_2014_DHS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | The World Bank | Documentation of the DDI |
DDI Document version
Version 01 (July 2016). Metadata is excerpted from "Lesotho Demographic and Health Survey 2014" Report.