Albania - Demographic and Health Survey 2017 - 2018

Primary tabs

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.

Acronym: 
DHS / ADHS 2017-18
Type: 
Microdata
Topics: 
Topic not specified
Languages Supported: 
English
Geographical Coverage: 
Albania
Reference ID: 
ALB_2017_DHS_v01_M
Release Date: 
January 16, 2019

Harvest Source

Harvest Source: 
Microdata

Harvest Source ID

Harvest Source ID: 
10303

Last Updated

Last Updated: 
January 16, 2019
Study Type: 

Demographic and Health Survey [hh/dhs]

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.
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.
Primary Investigator Name, Affiliation: 
Institute of Public Health (IPH) - Government of Albania; National Institute of Statistics (INSTAT) - Government of Albania
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.
Response Rates: 
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.
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.
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.
Unit of Analysis: 
- Household - Individual - Children age 0-5 - Woman age 15-49 - Man age 15-59
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.
Version Notes: 
The data dictionary was generated from hierarchical data that was downloaded from the The DHS Program website (http://dhsprogram.com).
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.

No Visualizations Available.

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 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.

FieldValue
Modified Date
2019-01-17
Release Date
Identifier
c74824e2-5f76-4913-b0b1-861cf9daac3a
License
License Not Specified
Contact Email
Public Access Level
Public
Rating: 
0
No votes yet
Reference ID: 
ALB_2017_DHS_v01_M
Acronym: 
DHS / ADHS 2017-18
Type: 
Languages Supported: 
Access Authority Name, Affiliation, Email: 
The DHS Program, [email protected], http://www.DHSprogram.com
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.
Response Rates: 
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.
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.
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.
Primary Investigator Name, Affiliation: 
Institute of Public Health (IPH) - Government of Albania; National Institute of Statistics (INSTAT) - Government of Albania
Unit of Analysis: 
- Household - Individual - Children age 0-5 - Woman age 15-49 - Man age 15-59
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.
Geographical Coverage: 
Data Classification of a Dataset: 
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.
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.
Release Date: 
Wednesday, January 16, 2019
Last Updated Date: 
Wednesday, January 16, 2019
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.
Harvest Source: 
Harvest Source ID: 
10303
Version Notes: 
The data dictionary was generated from hierarchical data that was downloaded from the The DHS Program website (http://dhsprogram.com).
Citation Text: 
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
Modified date: 
17912
Study Type: 
Demographic and Health Survey [hh/dhs]
Primary Dataset: 
Yes

Data Access and Licensing

This dataset is classified as Public under the Access to Information Classification Policy. Users inside and outside the Bank can access this dataset.

This dataset is available from an external third-party website. Visit the website to obtain license information. More information

Share Metadata

The information on this page (the dataset metadata) is also available in these formats.

PRINT EMAIL JSON RDF