Demographic and Health Survey 2017 - 2018
Albania, 2017 - 2018
Get Microdata
Reference ID
ALB_2017_DHS_v01_M
Producer(s)
Institute of Public Health (IPH), National Institute of Statistics (INSTAT)
Collection(s)
Metadata
Created on
Jan 16, 2019
Last modified
Jan 16, 2019
Page views
156250
Downloads
1077
Identification
Survey ID Number
ALB_2017_DHS_v01_M
Title
Demographic and Health Survey 2017 - 2018
Country/Economy
| Name | Country code |
|---|---|
| Albania | ALB |
Study type
Demographic and Health Survey (Standard) - DHS VII
Series Information
Demographic and Health Surveys (DHS) are nationally-representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health, and nutrition.
The 2017-18 Albania Demographic and Health Survey (ADHS) is the second DHS conducted in Albania. The first ADHS was conducted in 2008-09.
The 2017-18 Albania Demographic and Health Survey (ADHS) is the second DHS conducted in Albania. The first ADHS was conducted in 2008-09.
Abstract
The 2017-18 Albania Demographic and Health Survey (2017-18 ADHS) is a nationwide survey with a nationally representative sample of approximately 17,160 households. All women age 15-49 who are usual residents of the selected households or who slept in the households the night before the survey were eligible for the survey. Women 50-59 years old were interviewed with an abbreviated questionnaire that only covered background characteristics and questions related to noncommunicable diseases.
The primary objective of the 2017-2018 ADHS was to provide estimates of basic sociodemographic and health indicators for the country as a whole and the twelve prefectures. Specifically, the survey collected information on basic characteristics of the respondents, fertility, family planning, nutrition, maternal and child health, knowledge of HIV behaviors, health-related lifestyle, and noncommunicable diseases (NCDs). The information collected in the ADHS will assist policymakers and program managers in evaluating and designing programs and in developing strategies for improving the health of the country’s population.
The sample for the 2017-18 ADHS was designed to produce representative results for the country as a whole, for urban and rural areas separately, and for each of the twelve prefectures known as Berat, Diber, Durres, Elbasan, Fier, Gjirokaster, Korce, Kukes, Lezhe, Shkoder, Tirana, and Vlore.
The primary objective of the 2017-2018 ADHS was to provide estimates of basic sociodemographic and health indicators for the country as a whole and the twelve prefectures. Specifically, the survey collected information on basic characteristics of the respondents, fertility, family planning, nutrition, maternal and child health, knowledge of HIV behaviors, health-related lifestyle, and noncommunicable diseases (NCDs). The information collected in the ADHS will assist policymakers and program managers in evaluating and designing programs and in developing strategies for improving the health of the country’s population.
The sample for the 2017-18 ADHS was designed to produce representative results for the country as a whole, for urban and rural areas separately, and for each of the twelve prefectures known as Berat, Diber, Durres, Elbasan, Fier, Gjirokaster, Korce, Kukes, Lezhe, Shkoder, Tirana, and Vlore.
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
Version
Version Notes
The data dictionary was generated from hierarchical data that was downloaded from the The DHS Program website (http://dhsprogram.com).
Scope
Notes
The 2017-18 Albania 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, health insurance, birth registration, survivorship and residence of biological parents, migration, school attendance, and birth registration
• Characteristics of the household's dwelling unit, such as main source of water, time taken to get water and come back, type of toilet facility and location, type of fuel used for cooking, materials used for the floor, roof and walls of the house, and possessions of durable goods (including land and livestock)
• Migration
• Child discipline
• Weight, height and hemoglobin measurement for children age 0-5
• Anthropometric and hemoglobin measurement for women 15-59
• Weight, height and hemoglobin measurement for men 15-59
INDIVIDUAL WOMAN
• Identification
• Respondent's background
• Reproduction
• Contraception
• Pregnancy and postnatal care
• Child immunization
• Child health and nutrition
• Marriage and sexual activity
• Fertility preferences
• Husband's background and woman's work
• HIV/AIDS
• Other health issues
• Lifestyle
INDIVIDUAL MAN
• Identification
• Respondent's background
• Reproduction
• Contraception
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS
• Other health issues
• Lifestyle
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, health insurance, birth registration, survivorship and residence of biological parents, migration, school attendance, and birth registration
• Characteristics of the household's dwelling unit, such as main source of water, time taken to get water and come back, type of toilet facility and location, type of fuel used for cooking, materials used for the floor, roof and walls of the house, and possessions of durable goods (including land and livestock)
• Migration
• Child discipline
• Weight, height and hemoglobin measurement for children age 0-5
• Anthropometric and hemoglobin measurement for women 15-59
• Weight, height and hemoglobin measurement for men 15-59
INDIVIDUAL WOMAN
• Identification
• Respondent's background
• Reproduction
• Contraception
• Pregnancy and postnatal care
• Child immunization
• Child health and nutrition
• Marriage and sexual activity
• Fertility preferences
• Husband's background and woman's work
• HIV/AIDS
• Other health issues
• Lifestyle
INDIVIDUAL MAN
• Identification
• Respondent's background
• Reproduction
• Contraception
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS
• Other health issues
• Lifestyle
Coverage
Geographic Coverage
National coverage
Universe
The survey covered all de jure household members (usual residents), children age 0-4 years, women age 15-49 years and men age 15-59 years resident in the household.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Institute of Public Health (IPH) | Government of Albania |
| National Institute of Statistics (INSTAT) | Government of Albania |
Producers
| Name | Affiliation | Role |
|---|---|---|
| IFC | The DHS Program | Provided technical assistance to ensure survey quality and to build local capacity |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Government of Albania | GovALB | Funded the survey |
| Swiss Agency for Development and Cooperation | SDC | Funded the survey |
| United Nations Population Fund | UNFPA | Funded the survey |
| United Nations Children’s Fund | UNICEF | Funded the survey |
| United Nations Entity for Gender Equality and the Empowerment of Women | UN Women | Funded the survey |
Sampling
Sampling Procedure
The ADHS surveys were done on a nationally representative sample that was representative at the prefecture level as well by rural and urban areas. A total of 715 enumeration areas (EAs) were selected as sample clusters, with probability proportional to each prefecture's population size. The sample design called for 24 households to be randomly selected in every sampling cluster, regardless of its size, but some of the EAs contained fewer than 24 households. In these EAs, all households were included in the survey. The EAs are considered the sample's primary sampling unit (PSU). The team of interviewers updated and listed the households in the selected EAs. Upon arriving in the selected clusters, interviewers spent the first day of fieldwork carrying out an exhaustive enumeration of households, recording the name of each head of household and the location of the dwelling. The listing was done with tablet PCs, using a digital listing application. When interviewers completed their respective sections of the EA, they transferred their files into the supervisor's tablet PC, where the information was automatically compiled into a single file in which all households in the EA were entered. The software and field procedures were designed to ensure there were no duplications or omissions during the household listing process. The supervisor used the software in his tablet to randomly select 24 households for the survey from the complete list of households.
All women age 15-49 who were usual residents of the selected households or who slept in the households the night before the survey were eligible for individual interviews with the full Woman's Questionnaire. Women age 50-59 were also interviewed, but with an abbreviated questionnaire that left out all questions related to reproductive health and mother and child health. A 50% subsample was selected for the survey of men. Every man age 15-59 who was a usual resident of or had slept in the household the night before the survey was eligible for an individual interview in these households.
For further details on sample design, see Appendix A of the final report.
All women age 15-49 who were usual residents of the selected households or who slept in the households the night before the survey were eligible for individual interviews with the full Woman's Questionnaire. Women age 50-59 were also interviewed, but with an abbreviated questionnaire that left out all questions related to reproductive health and mother and child health. A 50% subsample was selected for the survey of men. Every man age 15-59 who was a usual resident of or had slept in the household the night before the survey was eligible for an individual interview in these households.
For further details on sample design, see Appendix A of the final report.
Response Rate
A total of 16,955 households were selected for the sample, of which 16,634 were occupied. Of the occupied households, 15,823 were successfully interviewed, which represents a response rate of 95%. In the interviewed households, 11,680 women age 15-49 were identified for individual interviews. Interviews were completed for 10,860 of these women, yielding a response rate of 93%. In the same households, 4,289 women age 50-59 were identified, of which 4,140 were successfully interviewed, yielding a 97% response rate. In the 50% subsample of households selected for the male survey, 7,103 eligible men age 15-59 were identified, of which 6,142 were successfully interviewed, yielding a response rate of 87%.
Response rates were higher in rural than in urban areas, which is a pattern commonly found in household surveys because in urban areas more people work and carry out activities outside the home.
Response rates were higher in rural than in urban areas, which is a pattern commonly found in household surveys because in urban areas more people work and carry out activities outside the home.
Weighting
All the survey weights were normalized in order to give a total number of weighted cases that equals the total number of unweighted cases at the national level. Normalization is done by multiplying the survey weight by the estimated total sampling fraction obtained from the survey for the household weight, the individual woman’s weight, the individual man’s weight, and the child discipline weight. The normalized weights are relative weights, which are valid for estimating means, proportions, and ratios, but not valid for estimating population totals and pooled data.
For further details on sampling weights, see Appendix A.4 of the final report.
For further details on sampling weights, see Appendix A.4 of the final report.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2017-09-11 | 2018-02-20 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
TRAINING OF FIELD STAFF
The training session started August 7, 2017, in Tirana. Seventy-two women, 42 men and 17 senior staff from INSTAT and IPH, participated. The INSTAT and IPH staff were trained to be part of the quality control teams during fieldwork, so they needed to be familiar with the questionnaires and measurement procedures. During the first 2 weeks of training, interviewers were instructed on household listing procedures, using the printed version of household and individual questionnaires with explanations on the purpose and relevance of the questions and their logical flow through the questionnaires. After the interviewers were familiar with the content and use of printed questionnaires, they started the training on the use of questionnaires in digital CAPI format on August 21.
Various specialists participated in the training. Thus, INSTAT’s cartography specialist trained interviewers on map interpretation, location of EAs, and identification of their boundaries; IPH’s coordinator of the vaccination program covered the section on vaccination and described the vaccination registration forms that the team supervisor had to obtain to record data. The training on anthropometry and collection of biomarkers also was carried out by senior IPH staff. As for the pretest, interviewers were also trained in measurement of height and weight, measurement of hemoglobin levels using a Hemocue hemoglobinometer, and use of sphygmomanometers and stethoscopes to manually measure blood pressure.
FIELDWORK
Fieldwork lasted approximately 6 months, from September 11, 2017, to February 20, 2018. Upon completion of training, 27 teams were formed, each team consisting of two female interviewers, one male interviewer, and one supervisor. Several layers of supervision were used to ensure data quality. First, team supervisors were required to closely monitor interviewers in the field and make sure their performance complied with expectations. Second, quality control teams, composed of IPH and INSTAT senior staff, visited teams in the field on a regular basis to observe their performance and offer guidance when needed. In addition, field check tables were produced every few weeks to assess the quality of the data being gathered.
The training session started August 7, 2017, in Tirana. Seventy-two women, 42 men and 17 senior staff from INSTAT and IPH, participated. The INSTAT and IPH staff were trained to be part of the quality control teams during fieldwork, so they needed to be familiar with the questionnaires and measurement procedures. During the first 2 weeks of training, interviewers were instructed on household listing procedures, using the printed version of household and individual questionnaires with explanations on the purpose and relevance of the questions and their logical flow through the questionnaires. After the interviewers were familiar with the content and use of printed questionnaires, they started the training on the use of questionnaires in digital CAPI format on August 21.
Various specialists participated in the training. Thus, INSTAT’s cartography specialist trained interviewers on map interpretation, location of EAs, and identification of their boundaries; IPH’s coordinator of the vaccination program covered the section on vaccination and described the vaccination registration forms that the team supervisor had to obtain to record data. The training on anthropometry and collection of biomarkers also was carried out by senior IPH staff. As for the pretest, interviewers were also trained in measurement of height and weight, measurement of hemoglobin levels using a Hemocue hemoglobinometer, and use of sphygmomanometers and stethoscopes to manually measure blood pressure.
FIELDWORK
Fieldwork lasted approximately 6 months, from September 11, 2017, to February 20, 2018. Upon completion of training, 27 teams were formed, each team consisting of two female interviewers, one male interviewer, and one supervisor. Several layers of supervision were used to ensure data quality. First, team supervisors were required to closely monitor interviewers in the field and make sure their performance complied with expectations. Second, quality control teams, composed of IPH and INSTAT senior staff, visited teams in the field on a regular basis to observe their performance and offer guidance when needed. In addition, field check tables were produced every few weeks to assess the quality of the data being gathered.
Questionnaires
Questionnaires
Four questionnaires were used in the ADHS, one for the household and others for women age 15-49, for women age 50-59, and for men age 15-59. In addition to these four questionnaires, a form was used to record the vaccination information for children born in the 5 years preceding the survey whose mothers had been successfully interviewed.
Data Processing
Data Editing
Supervisors sent the accumulated fieldwork data to INSTAT’s central office via internet every day, unless for some reason the teams did not have access to the internet at the time. The data received from the various teams were combined into a single file, which was used to produce quality control tables, known as field check tables. These tables reveal systematic errors in the data such as omission of potential respondents, age displacement, inaccurate recording of date of birth and age at death, inaccurate measurement of height and weight, and other key indicators of data quality. These tables were reviewed and evaluated by ADHS senior staff, which in turn provided feedback and advice to the teams in the field.
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 2017-18 Albania Demographic and Health Survey (ADHS) 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 2017-18 ADHS 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 2017-18 ADHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using 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.
A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017-18 ADHS 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 2017-18 ADHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using 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.
A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final 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
- Reporting of age at death in months
See details of the data quality tables in Appendix C of the survey final 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
See details of the data quality tables in Appendix C of the survey final report.
Access policy
Contacts
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
Access authority
| Name | URL | |
|---|---|---|
| The DHS Program | archive@dhsprogram.com | Link |
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_ALB_2017_DHS_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
DDI Document version
Version 01 (January 2019). Metadata is excerpted from "Albania Demographic and Health Survey 2017-18" Report.