Tanzania - Demographic and Health Survey and Malaria Indicator Survey 2015-2016

Primary tabs

The primary objective of the 2015-16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) is to provide up-to-date estimates of basic demographic and health indicators. This survey 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, malaria, and other health-related issues. In addition, the 2015-16 TDHS-MIS provided estimates of anaemia prevalence among children age 6-59 months and women age 15-49 years, estimates of malaria prevalence among children age 6-59 months, and estimates of iodine concentration in household salt and women’s urine. The information collected through the 2015-16 TDHS-MIS is intended to assist policy makers and programme managers in evaluating and designing programmes and strategies to improve the health of the country’s population.

Type: 
Microdata
Acronym: 
DHS-MIS 2015-16 / TDHS-MIS 2015-16
Languages Supported: 
English
Topics: 
Topic not specified
Geographical Coverage: 
Tanzania
Economy Coverage: 
Economy Coverage not specified
Release Date: 
December 16, 2016

Last Updated

Last Updated: 
October 1, 2019

Harvest System ID

Harvest System ID: 
Microdata

Harvest Source ID

Harvest Source ID: 
9158
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.
Version Description: 
Version 01 (December 2016). Metadata is excerpted from "Tanzania Demographic and Health Survey and Malaria Indicator Survey 2015-2016" Report.
Publisher Name: 

Development Data Group; The World Bank

Funding Name, Abbreviation, Role: 
Government of Tanzania, United States Agency for International Development, Global Affairs Canada, Irish Aid, United Nations Children’s Fund, United Nations Population Fund
Study Type: 
Demographic and Health Survey (Standard) - DHS VII
Series Information: 
The 2015-16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) is the ninth in a series of national sample surveys conducted in Tanzania to measure levels, patterns, and trends in demographic and health indicators. The first TDHS, conducted in 1991-92, was followed by the 1994 Tanzania Knowledge, Attitudes, and Practices Survey (TKAPS), the 1996 TDHS, the 1999 Tanzania Reproductive and Child Health Survey (TRCHS), the 2003-04 Tanzania HIV/AIDS Indicator Survey (THIS), the 2004-05 TDHS, the 2007-08 Tanzania HIV/AIDS and Malaria Indicator Survey (THMIS), and the 2010 Tanzania Demographic and Health Survey (TDHS 2010).
Primary Investigator Name, Affiliation: 
National Bureau of Statistics (NBS); Government of Tanzania, Office of the Chief Government Statistician (OCGS); Zanzibar
Sampling Procedure: 
Sample Design The sample design for the 2015-16 TDHS-MIS was done in two stages and was intended to provide estimates for the entire country, for urban and rural areas in Tanzania Mainland, and for Zanzibar. For specific indicators such as contraceptive use, the sample design allowed the estimation of indicators for each of the 30 regions (25 regions from Tanzania Mainland and 5 regions from Zanzibar). The first stage involved selecting sample points (clusters), consisting of enumeration areas (EAs) delineated for the 2012 Tanzania Population and Housing Census. A total of 608 clusters were selected. In the second stage, a systematic selection of households was involved. A complete households listing was carried out for all 608 selected clusters prior to the fieldwork. From the list, 22 households were then systematically selected from each cluster, yielding a representative probability sample of 13,376 households for the 2015-16 TDHS-MIS. To estimate geographic differentials for certain demographic indicators, Tanzania was divided into nine geographic zones. Although these zones are not official administrative areas, this classification system is also used by the Reproductive and Child Health Section of the MoHCDGEC. Grouping the regions into zones allowed a relatively large number of people in the denominator and a reduced sampling error. Note that the zones, defined below, differ slightly from the zones used in previous DHS surveys. Therefore, comparisons across the zones and from survey to survey should be made with caution. The zones are as follows: Western Zone: Tabora, Kigoma Northern Zone: Kilimanjaro, Tanga, Arusha Central Zone: Dodoma, Singida, Manyara Southern Highlands Zone: Iringa, Njombe, Ruvuma Southern Zone: Lindi, Mtwara South West Highlands Zone: Mbeya, Rukwa, Katavi Lake Zone: Kagera, Mwanza, Geita, Mara, Simiyu, Shinyanga Eastern Zone: Dar es Salaam, Pwani, Morogoro Zanzibar: Kaskazini Unguja, Kusini Unguja, Mjini Magharibi, Kaskazini Pemba, Kusini Pemba All women age 15-49 who were either usual residents or visitors in the household on the night before the survey were included in the 2015-16 TDHS-MIS and were eligible to be interviewed. In a subsample of one-third of all the households selected for the survey, all men age 15-49 were eligible to be interviewed if they were either usual residents or visitors in the household on the night before the survey. In all households, with the parent's or guardian's consent, children age 6-59 months were tested for anaemia and malaria. All interviewed women were tested for anaemia. In the households selected for interviews with men, interviewed women were asked to provide a urine sample and a sample of household salt for laboratory testing to detect the presence of iodine. For further details of sample design and implementation, see Appendix A of the final report.
Response Rates: 
A total of 13,360 households were selected for the survey, of which 12,767 were occupied. Of the occupied households, 12,563 were successfully interviewed, yielding a response rate of 98%. In the interviewed households, 13,634 eligible women were identified for individual interviews; interviews were completed with 13,266 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 3,822 eligible men were identified and 3,514 were successfully interviewed, yielding a response rate of 92%. There is little variation in household response rates between rural and urban residences.
Weighting: 
The final sampling weights are normalized in order to give the total number of unweighted cases equal to the total number of weighted cases at the national level, for both household weights and individual weights, respectively. The normalized weights are relative weights, which are valid for estimating means, proportions, and ratios, but are not valid for estimating population totals and for pooled data. Sampling weights for the domestic violence surveys are calculated based on the number of eligible respondents in the households selected for the domestic violence module, for male and female surveys, respectively. A large number of sets of weights are calculated: - One set for all households selected for the survey - One set for women selected for the individual survey - One set for households selected for the male survey - One set for the male individual survey It is important to note that the normalized weights are relative weights, which are valid for estimating means, proportions, and ratios, but not for estimating population totals and for pooled data. Also the number of weighted cases resulting from using the normalized weight has no direct relation to the survey precision because it is relative; especially for oversampled areas, the number of weighted cases will be much smaller than the number of unweighted cases, which are directly related to survey precision.
Questionnaires: 
Four questionnaires were used for the 2015-16 TDHS-MIS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. These questionnaires were based on the DHS Program’s standard Demographic and Health Survey (DHS) questionnaires. They were adapted to reflect the population and health issues relevant to Tanzania. Inputs were solicited from various stakeholders representing government ministries, departments, and agencies; non-governmental organizations; and development partners. After the preparation of the definitive questionnaires in English, the questionnaires were translated into Kiswahili.
Data Collector(s) Name: 
National Bureau of Statistics
Data Editing: 
In the 2015-16 TDHS-MIS the first data entry was done concurrently with data collection in the field. After the paper questionnaires were completed, edited, and checked by both the field editor and the supervisor, the data was entered into a tablet equipped with a data entry programme. This was done by the editor. Completed questionnaires were then sent to NBS headquarters, where they were entered for the second time and edited by data processing personnel who were given special training for this task. ICF International provided technical assistance during the entire data processing period. Processing the data concurrently with data collection allowed for regular monitoring of team performance and data quality. Field check tables were generated regularly during data processing to check various data quality parameters. As a result, feedback was given on a regular basis, encouraging teams to continue in areas of good performance and to correct areas in need of improvement. Feedback was individually tailored to each team. Data entry, which included 100% double entry to minimise keying errors, and data editing, were completed on March 21, 2016. Data cleaning and finalization were completed on April 22, 2016.
Other Processing: 
The 2015-16 Tanzania Demographic and Health and Malaria Indicator Survey covered the following topics: HOUSEHOLD • Identification • Background information on each person listed, such as relationship to head of the household, age, sex, highest educational attainment, and health insurance coverage • Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, main source of energy for lighting, main source of fuel for cooking, materials used for the floor, roof and walls of the dwelling, ownership of land and livestock, and ownership of various durable goods (these items are used as proxy indicators of the household's socioeconomic status) • Mosquito nets • Inpatient health expenditures • Outpatient health expenditures INDIVIDUAL WOMAN • Identification • Respondent's background (age, education, etc.) • 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 • Malaria • Other health issues • Female genital cutting/mutilation • Maternal mortality • Domestic violence INDIVIDUAL MAN • Identification • Respondent's background (age, education etc.) • Reproduction • Contraception • Marriage and sexual activity • Fertility preferences • Employment and gender roles • Other health issues • Malaria BIOMARKER • Identification • Weight, height, hemoglobin measurement and malaria testing for children age 0-5 years • Weight and height measurement, hemoglobin and urine (for iodine) test for women age 15-49
Estimates of Sampling Error: 
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) 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 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 2015 Tanzania Demographic and Health Survey (TDHS) 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 TDHS is only one of many samples that could have been selected from the same population, using the same design and identical 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 between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results. A 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 percent 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 TDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2015 TDHS is a SAS program. This program used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method was 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. For further details on sampling error calculations see Appendix B of the final report.
Other Forms of Data Appraisal: 
Data quality tables were produced to review the quality of the data: - 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 Note: The tables are presented in Appendix C of the final report.
Time Periods: 
August, 2017

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 primary objective of the 2015-16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) is to provide up-to-date estimates of basic demographic and health indicators. This survey 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, malaria, and other health-related issues. In addition, the 2015-16 TDHS-MIS provided estimates of anaemia prevalence among children age 6-59 months and women age 15-49 years, estimates of malaria prevalence among children age 6-59 months, and estimates of iodine concentration in household salt and women’s urine. The information collected through the 2015-16 TDHS-MIS is intended to assist policy makers and programme managers in evaluating and designing programmes and strategies to improve the health of the country’s population.

FieldValue
Modified Date
2020-04-15
Release Date
Identifier
61c6e7aa-37b3-4a0d-b08f-ae9778962819
License
License Not Specified
Contact Email
Rating: 
0
No votes yet
Acronym: 
DHS-MIS 2015-16 / TDHS-MIS 2015-16
Type: 
Languages Supported: 
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 13,360 households were selected for the survey, of which 12,767 were occupied. Of the occupied households, 12,563 were successfully interviewed, yielding a response rate of 98%. In the interviewed households, 13,634 eligible women were identified for individual interviews; interviews were completed with 13,266 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 3,822 eligible men were identified and 3,514 were successfully interviewed, yielding a response rate of 92%. There is little variation in household response rates between rural and urban residences.
Weighting: 
The final sampling weights are normalized in order to give the total number of unweighted cases equal to the total number of weighted cases at the national level, for both household weights and individual weights, respectively. The normalized weights are relative weights, which are valid for estimating means, proportions, and ratios, but are not valid for estimating population totals and for pooled data. Sampling weights for the domestic violence surveys are calculated based on the number of eligible respondents in the households selected for the domestic violence module, for male and female surveys, respectively. A large number of sets of weights are calculated: - One set for all households selected for the survey - One set for women selected for the individual survey - One set for households selected for the male survey - One set for the male individual survey It is important to note that the normalized weights are relative weights, which are valid for estimating means, proportions, and ratios, but not for estimating population totals and for pooled data. Also the number of weighted cases resulting from using the normalized weight has no direct relation to the survey precision because it is relative; especially for oversampled areas, the number of weighted cases will be much smaller than the number of unweighted cases, which are directly related to survey precision.
Estimates of Sampling Error: 
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) 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 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 2015 Tanzania Demographic and Health Survey (TDHS) 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 TDHS is only one of many samples that could have been selected from the same population, using the same design and identical 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 between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results. A 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 percent 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 TDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2015 TDHS is a SAS program. This program used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method was 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. For further details on sampling error calculations see Appendix B of the final report.
Time Periods: 
August, 2017
Other Forms of Data Appraisal: 
Data quality tables were produced to review the quality of the data: - 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 Note: The tables are presented in Appendix C of the final report.
Economy Coverage: 
Primary Investigator Name, Affiliation: 
National Bureau of Statistics (NBS); Government of Tanzania, Office of the Chief Government Statistician (OCGS); Zanzibar
Publisher Name: 
Development Data Group; The World Bank
Version Description: 
Version 01 (December 2016). Metadata is excerpted from "Tanzania Demographic and Health Survey and Malaria Indicator Survey 2015-2016" Report.
Geographical Coverage: 
Data Classification of a Dataset: 
Series Information: 
The 2015-16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) is the ninth in a series of national sample surveys conducted in Tanzania to measure levels, patterns, and trends in demographic and health indicators. The first TDHS, conducted in 1991-92, was followed by the 1994 Tanzania Knowledge, Attitudes, and Practices Survey (TKAPS), the 1996 TDHS, the 1999 Tanzania Reproductive and Child Health Survey (TRCHS), the 2003-04 Tanzania HIV/AIDS Indicator Survey (THIS), the 2004-05 TDHS, the 2007-08 Tanzania HIV/AIDS and Malaria Indicator Survey (THMIS), and the 2010 Tanzania Demographic and Health Survey (TDHS 2010).
Sampling Procedure: 
Sample Design The sample design for the 2015-16 TDHS-MIS was done in two stages and was intended to provide estimates for the entire country, for urban and rural areas in Tanzania Mainland, and for Zanzibar. For specific indicators such as contraceptive use, the sample design allowed the estimation of indicators for each of the 30 regions (25 regions from Tanzania Mainland and 5 regions from Zanzibar). The first stage involved selecting sample points (clusters), consisting of enumeration areas (EAs) delineated for the 2012 Tanzania Population and Housing Census. A total of 608 clusters were selected. In the second stage, a systematic selection of households was involved. A complete households listing was carried out for all 608 selected clusters prior to the fieldwork. From the list, 22 households were then systematically selected from each cluster, yielding a representative probability sample of 13,376 households for the 2015-16 TDHS-MIS. To estimate geographic differentials for certain demographic indicators, Tanzania was divided into nine geographic zones. Although these zones are not official administrative areas, this classification system is also used by the Reproductive and Child Health Section of the MoHCDGEC. Grouping the regions into zones allowed a relatively large number of people in the denominator and a reduced sampling error. Note that the zones, defined below, differ slightly from the zones used in previous DHS surveys. Therefore, comparisons across the zones and from survey to survey should be made with caution. The zones are as follows: Western Zone: Tabora, Kigoma Northern Zone: Kilimanjaro, Tanga, Arusha Central Zone: Dodoma, Singida, Manyara Southern Highlands Zone: Iringa, Njombe, Ruvuma Southern Zone: Lindi, Mtwara South West Highlands Zone: Mbeya, Rukwa, Katavi Lake Zone: Kagera, Mwanza, Geita, Mara, Simiyu, Shinyanga Eastern Zone: Dar es Salaam, Pwani, Morogoro Zanzibar: Kaskazini Unguja, Kusini Unguja, Mjini Magharibi, Kaskazini Pemba, Kusini Pemba All women age 15-49 who were either usual residents or visitors in the household on the night before the survey were included in the 2015-16 TDHS-MIS and were eligible to be interviewed. In a subsample of one-third of all the households selected for the survey, all men age 15-49 were eligible to be interviewed if they were either usual residents or visitors in the household on the night before the survey. In all households, with the parent's or guardian's consent, children age 6-59 months were tested for anaemia and malaria. All interviewed women were tested for anaemia. In the households selected for interviews with men, interviewed women were asked to provide a urine sample and a sample of household salt for laboratory testing to detect the presence of iodine. For further details of sample design and implementation, see Appendix A of the final report.
Release Date: 
Friday, December 16, 2016
Last Updated Date: 
Tuesday, October 1, 2019
Questionnaires: 
Four questionnaires were used for the 2015-16 TDHS-MIS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. These questionnaires were based on the DHS Program’s standard Demographic and Health Survey (DHS) questionnaires. They were adapted to reflect the population and health issues relevant to Tanzania. Inputs were solicited from various stakeholders representing government ministries, departments, and agencies; non-governmental organizations; and development partners. After the preparation of the definitive questionnaires in English, the questionnaires were translated into Kiswahili.
Data Editing: 
In the 2015-16 TDHS-MIS the first data entry was done concurrently with data collection in the field. After the paper questionnaires were completed, edited, and checked by both the field editor and the supervisor, the data was entered into a tablet equipped with a data entry programme. This was done by the editor. Completed questionnaires were then sent to NBS headquarters, where they were entered for the second time and edited by data processing personnel who were given special training for this task. ICF International provided technical assistance during the entire data processing period. Processing the data concurrently with data collection allowed for regular monitoring of team performance and data quality. Field check tables were generated regularly during data processing to check various data quality parameters. As a result, feedback was given on a regular basis, encouraging teams to continue in areas of good performance and to correct areas in need of improvement. Feedback was individually tailored to each team. Data entry, which included 100% double entry to minimise keying errors, and data editing, were completed on March 21, 2016. Data cleaning and finalization were completed on April 22, 2016.
Other Processing: 
The 2015-16 Tanzania Demographic and Health and Malaria Indicator Survey covered the following topics: HOUSEHOLD • Identification • Background information on each person listed, such as relationship to head of the household, age, sex, highest educational attainment, and health insurance coverage • Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, main source of energy for lighting, main source of fuel for cooking, materials used for the floor, roof and walls of the dwelling, ownership of land and livestock, and ownership of various durable goods (these items are used as proxy indicators of the household's socioeconomic status) • Mosquito nets • Inpatient health expenditures • Outpatient health expenditures INDIVIDUAL WOMAN • Identification • Respondent's background (age, education, etc.) • 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 • Malaria • Other health issues • Female genital cutting/mutilation • Maternal mortality • Domestic violence INDIVIDUAL MAN • Identification • Respondent's background (age, education etc.) • Reproduction • Contraception • Marriage and sexual activity • Fertility preferences • Employment and gender roles • Other health issues • Malaria BIOMARKER • Identification • Weight, height, hemoglobin measurement and malaria testing for children age 0-5 years • Weight and height measurement, hemoglobin and urine (for iodine) test for women age 15-49
Harvest Source: 
Harvest System ID: 
9158
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: 
18170
Study Type: 
Demographic and Health Survey (Standard) - DHS VII
Primary Dataset: 
Yes
Mode of Data Collection: 

Face-to-face

Data Collector(s) Name: 

National Bureau of Statistics

Funding Name, Abbreviation, Role: 

Government of Tanzania, United States Agency for International Development, Global Affairs Canada, Irish Aid, United Nations Children’s Fund, United Nations Population Fund

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