Demographic and Health Survey, Special [hh/dhs-sp]
The 2017 Ghana Maternal Health Survey (2017 GMHS) was the second of its kind following the original conducted in 2007 (2007 GMHS). The survey was planned to collect information on maternal health and mortality in Ghana through data collection at the household and individual woman’s level. As in the 2007 GMHS, the 2017 GMHS collected data from a nationally representative sample. The 2017 GMHS sample consisted of 900 clusters and 27,000 households randomly selected from the entire country.
The 2017 Ghana Maternal Health Survey (2017 GMHS) was designed to produce representative estimates for maternal mortality indicators for the country as a whole, and for each of the three geographical zones, namely Coastal (Western, Central, Greater Accra and Volta), Middle (Eastern, Ashanti and Brong Ahafo) and Northern (Northern, Upper East and Upper West). For other indicators such as maternal care, fertility and child mortality, the survey was designed to produce representative results for the country as whole, for the urban and rural areas, and for each of the country’s 10 administrative regions.
The primary objectives of the 2017 GMHS were as follows:
• To collect data at the national level that will allow an assessment of the level of maternal mortality in Ghana for the country as a whole and for three zones: Coastal (Western, Central, Greater Accra, and Volta regions), Middle (Eastern, Ashanti, and Brong Ahafo regions), and Northern (Northern, Upper East, and Upper West regions)
• To identify specific causes of maternal and non-maternal deaths, in particular deaths due to abortionrelated causes, among adult women
• To collect data on women’s perceptions of and experiences with antenatal, maternity, and emergency obstetrical care, especially with regard to care received before, during, and following the termination or abortion of a pregnancy
• To measure indicators of the utilisation of maternal health services, especially post-abortion care services
• To allow follow-on studies and surveys that will be used to observe possible reductions in maternal mortality as well as abortion-related mortality
The information collected through the 2017 GMHS is intended to assist policymakers 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
- Woman age 15-49
A new version of the Ghana 2017 dataset has been exported and released. The differences between version 7I and 7J are as follows:
• Added QWSEC04 (Pregnancy & Postnatal Care), QWSEC05 (Abortion) and QWSEC06 (Miscarriage) to the woman files: GHIQ7JFL.
• Added QWSEC05 (Abortion) to the Children and Kids files: GHBQ7JFL & GHCH7JFL
• Added district labels to the files.
The data dictionary was generated from hierarchical data that was downloaded from the DHS website (http://dhsprogram.com).
The 2017 Ghana Maternal Health Survey covered the following topics:
• 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, and education
• Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, type of fuel used for cooking, number of rooms, materials used for the floor, roof and walls of the house, possessions of livestock and durable goods.
• Background characteristics
• Pregnancy history: number, outcome (live birth, stillbirth, miscarriage, abortion), and timing of all pregnancies
• Family planning: knowledge of contraception, current use and current source of contraception
• Pregnancy and postnatal care for most recent live birth or stillbirth: antenatal, delivery, and postnatal care; complications experienced and treatment sought during any of these stages
• Abortion: method used, complications experienced, and care sought for abortion; knowledge of abortion
• Miscarriage: perceived cause, complications experienced, and care sought for miscarriage Marriage and sexual activity: marital status, age at first marriage, number of unions, and age at first sexual intercourse
• Adult and maternal mortality
• Health care access, insurance, and disability
• Narrative of illness/events leading to death
• History of injuries/accidents: details of any injury/accident sustained by the deceased
• History of diagnoses: whether the deceased had been diagnosed with any of a list of specific illnesses/conditions
• General signs/symptoms: whether the deceased exhibited particular signs/symptoms (coughing, night sweats, fever, rash, etc.)
• Signs/symptoms associated with pregnancy: detailed questions on signs/symptoms associated with maternal causes of death
• Risk factors: consumption of alcohol and tobacco
• Treatment received: treatment/medical details of the deceased’s contact with health services before death
• Access to and quality of services: contextual information about the deceased’s contact with health services before death
• Death certificate and burial permit: information on timing and cause of death from the death certificate and burial permit (if available)
Producers and sponsors
Ghana Statistical Service (GSS)
Government of Ghana
Ghana Health Service (GHS)
Government of Ghana
Provided technical assistance through The DHS Program
Government of Ghana
Funded the survey
United States Agency for International Development
Funded the survey
Funded the survey
United Nations Population Fund
Funded the survey
The sample for the 2017 GMHS was designed to provide estimates of key reproductive health indicators for the country as a whole, for urban and rural areas separately, for three zonal levels (Coastal, Middle, and Northern), and for each of the 10 administrative regions in Ghana (Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East, and Upper West).
The sampling frame used for the 2017 GMHS is the frame of the 2010 Population and Housing Census (PHC) conducted in Ghana. The 2010 PHC frame is maintained by GSS and updated periodically as new information is received from various surveys. The frame is a complete list of all census enumeration areas (EAs) created for the PHC.
The 2017 GMHS sample was stratified and selected from the sampling frame in two stages. Each region was separated into urban and rural areas; this yielded 20 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before the sample selection, according to administrative units at different levels, and by using a probability proportional to size selection at the first stage of sampling.
In the first stage, 900 EAs (466 EAs in urban areas and 434 EAs in rural areas) were selected with probability proportional to EA size and with independent selection in each sampling stratum. A household listing operation was implemented from 25 January to 9 April 2017 in all of the selected EAs. The resulting lists of households then served as a sampling frame for the selection of households in the second stage. The household listing operation included inquiring of each household if there had been any deaths in that household since January 2012 and, if so, the name, sex, and age at time of death of the deceased person(s).
Some of the selected EAs were very large. To minimise the task of household listing, each large EA selected for the 2017 GMHS was segmented. Only one segment was selected for the survey with probability proportional to segment size. Household listing was conducted only in the selected segment. Thus, in the GMHS, a cluster is either an EA or a segment of an EA. As part of the listing, the field teams updated the necessary maps and recorded the geographic coordinates of each cluster. The listing was conducted by 20 teams that included a supervisor, three listers/mappers, and a driver.
For further details on sample design, see Appendix A of the final report.
A total of 27,001 households were selected for the sample, of which 26,500 were occupied at the time of fieldwork. Of the occupied households, 26,324 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 25,304 eligible women were identified for individual interviews; interviews were completed with 25,062 women, yielding a response rate of 99%.
A spreadsheet containing all the sampling parameters and selection probabilities were prepared to facilitate the calculation of the design weights. Design weights were adjusted for household non-response and as well as for women individual non-response to get the sampling weights, for households and for women individuals, respectively. The differences of the household sampling weights and the women individual sampling weights are introduced by women individual non-response. The final sampling weights were normalized in order to achieve the total number of un-weighted cases equal to the total number of weighted cases at 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 not valid for estimating population totals and for pooled data.
The design weight for the verbal autopsy indicators were the inverse of the cluster selection probability for the first stage selection. Correction of cluster level non-response as well as case level nonresponse may apply if there was non-response, either at cluster level or at case level.
For further details on sampling weight, see Appendix A.4 of the final report.
Dates of Data Collection
Data Collection Mode
Data Collection Notes
Data collection was carried out by 25 field teams, each consisting of one supervisor (male or female), four interviewers (all female), and one driver. Electronic data files were transferred from each interviewer’s tablet computer to the team supervisor’s tablet computer every day. Field supervisors transferred data to the central data processing office via the IFSS. Senior staff from GSS coordinated and monitored fieldwork activities. Data collection took place over a 4-month period, from 15 June through 12 October 2017.
Ghana Statistical Service
Government of Ghana
Three questionnaires were used in the 2017 GMHS: the Household Questionnaire, the Woman’s Questionnaire, and the Verbal Autopsy Questionnaire.
All electronic data files for the 2017 GMHS were transferred via the IFSS to the GSS central office in Accra, where they were stored on a password-protected computer. The data processing operation included registering and checking for any inconsistencies and outliers. Data editing and cleaning included structure and consistency checks to ensure completeness of work in the field. The central office also conducted secondary editing, which required resolution of computer-identified inconsistencies and coding of openended questions. The data were processed by five GSS staff members. Data editing was accomplished using CSPro software. Secondary editing and data processing were initiated in June and completed in November 2017.
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 Ghana Maternal Health Survey (2017 GMHS) 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 GMHS is only one of many samples that could have been selected from the same population, using the same design and sample 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 in. For example, for any given statistic calculated from a sample survey, the true 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 by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2017 GMHS sample is the result of a multi-stage stratified sampling, 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 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 Quality Tables
- Household age distribution
- Age distribution of eligible and interviewed women
- Completeness of reporting
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
- Completeness of information on siblings
- Sibship size and sex ratio of siblings
- Pregnancy-related mortality trends
See details of the data quality tables in Appendix C of the survey final report.
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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.
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DDI Document ID
Development Economics Data Group
The World Bank
Documentation of the DDI
DDI Document version
Version 01 (September 2018). Metadata is excerpted from "Ghana Maternal Health Survey 2017" Report.