Abstract

The 2022 Ghana Demographic and Health Survey (2022 GDHS) is the seventh in the series of DHS surveys conducted by the Ghana Statistical Service (GSS) in collaboration with the Ministry of Health/Ghana Health Service (MoH/GHS) and other stakeholders, with funding from the United States Agency for International Development (USAID) and other partners.

The primary objective of the 2022 GDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the GDHS collected information on: - Fertility levels and preferences, contraceptive use, antenatal and delivery care, maternal and child health, childhood mortality, childhood immunisation, breastfeeding and young child feeding practices, women’s dietary diversity, violence against women, gender, nutritional status of adults and children, awareness regarding HIV/AIDS and other sexually transmitted infections, tobacco use, and other indicators relevant for the Sustainable Development Goals - Haemoglobin levels of women and children - Prevalence of malaria parasitaemia (rapid diagnostic testing and thick slides for malaria parasitaemia in the field and microscopy in the lab) among children age 6–59 months - Use of treated mosquito nets - Use of antimalarial drugs for treatment of fever among children under age 5

The information collected through the 2022 GDHS is intended to assist policymakers and programme managers in designing and evaluating programmes and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

• 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), all women aged 15-49, men aged 15-59, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

To achieve the objectives of the 2022 GDHS, a stratified representative sample of 18,450 households was selected in 618 clusters, which resulted in 15,014 interviewed women age 15–49 and 7,044 interviewed men age 15–59 (in one of every two households selected).

The sampling frame used for the 2022 GDHS is the updated frame prepared by the GSS based on the 2021 Population and Housing Census.1 The sampling procedure used in the 2022 GDHS was stratified two-stage cluster sampling, designed to yield representative results at the national level, for urban and rural areas, and for each of the country’s 16 regions for most DHS indicators. In the first stage, 618 target clusters were selected from the sampling frame using a probability proportional to size strategy for urban and rural areas in each region. Then the number of targeted clusters were selected with equal probability systematic random sampling of the clusters selected in the first phase for urban and rural areas. In the second stage, after selection of the clusters, a household listing and map updating operation was carried out in all of the selected clusters to develop a list of households for each cluster. This list served as a sampling frame for selection of the household sample. The GSS organized a 5-day training course on listing procedures for listers and mappers with support from ICF. The listers and mappers were organized into 25 teams consisting of one lister and one mapper per team. The teams spent 2 months completing the listing operation. In addition to listing the households, the listers collected the geographical coordinates of each household using GPS dongles provided by ICF and in accordance with the instructions in the DHS listing manual. The household listing was carried out using tablet computers, with software provided by The DHS Program. A fixed number of 30 households in each cluster were randomly selected from the list for interviews.

For further details on sample design, see APPENDIX A of the final report.

Mode of data collection

Face-to-face computer-assisted interviews [capi]

Research instrument

Four questionnaires were used in the 2022 GDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Ghana. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers.

The GSS organized a questionnaire design workshop with support from ICF and obtained input from government and development partners expected to use the resulting data. The DHS Program optional modules on domestic violence, malaria, and social and behavior change communication were incorporated into the Woman’s Questionnaire. ICF provided technical assistance in adapting the modules to the questionnaires.

Cleaning operations

DHS staff installed all central office programmes, data structure checks, secondary editing, and field check tables from 17–20 October 2022. Central office training was implemented using the practice data to test the central office system and field check tables. Seven GSS staff members (four male and three female) were trained on the functionality of the central office menu, including accepting clusters from the field, data editing procedures, and producing reports to monitor fieldwork.

From 27 February to 17 March, DHS staff visited the Ghana Statistical Service office in Accra to work with the GSS central office staff on finishing the secondary editing and to clean and finalize all data received from the 618 clusters.

Response rate

A total of 18,540 households were selected for the GDHS sample, of which 18,065 were found to be occupied. Of the occupied households, 17,933 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 15,317 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 15,014 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 7,263 men age 15–59 were identified as eligible for individual interviews and 7,044 were successfully interviewed.

Sampling error estimates

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 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 2022 Ghana Demographic and Health Survey (2022 GDHS) 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 2022 GDHS 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% 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 2022 GDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the GDHS 2022 is an SAS program. This program used 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 report.

Data appraisal

Data Quality Tables

• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Standardisation exercise results from anthropometry training
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Interference in height and weight measurements of children
• Interference in height and weight measurements of women and men
• Heaping in anthropometric measurements for children (digit preference)
• Observation of mosquito nets
• Observation of handwashing facility
• School attendance by single year of age
• Vaccination cards photographed
• Number of

Abstract

The population and housing census (PHC) is the unique source of reliable and comprehensive data about the size of population and also on major socio-economic & socio-demographic characteristics of the country. It provides data on geographic and administrative distribution of population and household in addition to the demographic and socio-economic characteristics of all the people in the country. Generally, it provides for comparing and projecting demographic data, social and economic characteristics, as well as household and housing conditions at all levels of the country’s administrative units and dimensions: national, regional, districts and localities. The data from the census is classified, tabulated and disseminated so that researchers, administrators, policy makers and development partners can use the information in formulating and implementing various multi-sectorial development programs at the national and community levels. Data on all key variables namely area, household, population, economic activity, literacy and education, fertility and child survival, housing conditions and sanitation are collected and available in the census data. The 2021 PHC in Ghana had an overarching goal of generating updated demographic, social and economic data, housing characteristics and dwelling conditions to support national development planning activities.

Geographic coverage

National Coverage , Region , District

Analysis unit

• Individuals
• Households
• Emigrants
• Absentee population
• Mortality
• Type of residence (households and non household)

Universe

All persons who spent census night (midnight of 27th June 2021) in Ghana

Kind of data

Census/enumeration data [cen]

Sampling procedure

This 10% sample data for the 2021 PHC is representative at the district/subdistrict level and also by the urban rural classification.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

GSS developed two categories of instruments for the 2021 PHC: the listing form and the enumeration instruments. The listing form was only one, while the enumeration instruments comprised six questionnaires, designated as PHC 1A, PHC 1B, PHC 1C, PHC 1D, PHC 1E and PHC 1F. The PHC 1A was the most comprehensive with the others being its subsets.

1. Listing Form: The listing form was developed to collect data on type of structures, level of completion, whether occupied or vacant and use(s) of the structures. It was also used to collect information about the availability, number and types of toilet facilities in the structures. It was also used to capture the number of households in a structure, number of persons in households and the sex of the persons residing in the households if occupied. Finally, the listing form was used to capture data on non-household populations such as the population in institutions, floating population and sex of the non-household populations.

2. PHC 1A: The PHC 1A questionnaire was used to collect data from all households in the country. Primarily, it was used to capture household members and visitors who spent the Census Night in the dwelling of the household, and their relationship with the head of the household. It was also used to collect data on homeless households. Members of the households who were absent were enumerated at the place where they had spent the Census Night. The questionnaire was also used to collect the following household information: emigration; socio-demographic characteristics (sex, age, place of birth and enumeration, survival status of parents, literacy and education; economic activities; difficulty in performing activities; ownership and usage of information, technology and communication facilities; fertility; mortality; housing characteristics and conditions and sanitation.

3. PHC 1B: The PHC 1B questionnaire was used to collect data from persons in stable institutions comprising boarding houses, hostels and prisons who were present on Census Night. Other information that was captured with this instrument are socio-demographic characteristics, literacy and education, economic activities, difficulty in performing activities; ownership and usage of information, technology and communication facilities; fertility; mortality; housing characteristics and conditions and sanitation.

4. PHC 1C: The PHC 1C questionnaire was used to collect data from persons in “unstable” institutions such as hospitals and prayer camps who were present at these places on Census Night. The instrument was used to capture only the socio-demographic characteristics of individuals.

5. PHC 1D: The PHC 1D questionnaire was used to collect data from the floating population. This constitutes persons who were found at airports, seaports, lorry stations and similar locations waiting for or embarking on long-distance travel, as well as outdoor sleepers on Census Night. The instrument captured the socio-demographic information of individuals.

6. PHC 1E: All persons who spent the Census Night at hotels, motels and guest houses were enumerated using the PHC 1E. The content of the questionnaire was similar to that of the PHC 1D.

7. PHC 1F: The PHC 1F questionnaire was administered to diplomats in the country.

Cleaning operations

The Census data editing was implemented at three levels: 1. data editing by enumerators and supervisors during data collection 2. data editing was done at the regional level by the regional data quality monitors during data collection 3. Final data editing was done at the national level using the batch edits in CSPro and STATA Data editing and cleaning was mainly digital.

Response rate

100 percent

Data appraisal

A post Enumeration Survey (PES) was conducted to assess the extent of coverage and content error.

Abstract

The 2000 Census was undertaken to update current information on the size, sex, age, composition and other characteristics of Ghana's population and to ascertain the specific changes in these characteristics which had taken place since the last census was conducted in 1984. The Census was expected to ensure the continuation of a time series of demographic and socio-economic benchmark data at the national and sub-national levels and enhance the capability-building programme of the Statistical Service.

The main objective of the 2000 Population and Housing Census was to update the statistical information on the characteristics of the population of Ghana.

The 2000 Population and Housing Census is the first time a full-scale housing census was conducted with a population census in one single operation.

Geographic coverage

National

Analysis unit

households, individuals and houses

Universe

The 2000 census covered de-facto population of Ghana on Census Night (26 March 2000). These were all usual reidents,inmates of institutions, out-door sleepers immediately after midnight Census Night Enumeration of the semi-stable floating population. Enumeration on Census Night of fishermen and other persons at sea and other persons in Field Camps and all types of housing structures

Kind of data

Census/enumeration data [cen]

Sampling procedure

Total coverage

Mode of data collection

Face-to-face [f2f]

Research instrument

Consultation with Users Work on the census questionnaire started in 1998 bearing in mind the data needs of the country. A simple questionnaire was sent to the ministries, relevant government departments, research institutions, relevant departments in the universities, private business associations and other users seeking information on the following: · whether the organization had used any previous census data · the specific census data used · what use the census data were put · any data that were needed but had not been provided in previous censuses · general comments on population censuses. Response to the questionnaire was encouraging; some respondents sent in the completed forms while others came over to discuss their data needs.

Selection of Topics Selecting topics for inclusion in the questionnaire involved the review and consideration of the following: · topics covered in the 1984 population census, · recommended topics from the United Nations Principles and Recommendations for the 2000 round of Population and Housing Censuses, · data requests and suggestions from users based on the answers to the questionnaire sent to them, · list of users' requests compiled by the Statistical Service over a period of time.

A number of meetings were held at both the Census Secretariat and the Technical Advisory Committee levels to discuss the topics and requests. Decisions on topics for inclusion were based on the relevance of topics and the data needs of the country as well as practical considerations of application of concepts.

The final questionnaire consisted of 15 questions on housing characteristics and 20 questions on population covering the following areas: · household characteristics · geographical location and internal migration · demographic and social characteristics · economic characteristics · literacy and education · fertility and mortality.

All the population topics investigated in 1970 and 1984 censuses were maintained, because they were considered as still relevant to the country's data needs, especially in terms of maintaining a time series of socio-economic data. The questionaires were published in English.

Cleaning operations

The Census data editing was implemented at three levels:

1. Field editing by interviewers and supervisors
2. Office editing and coding
3. Data cleaning and imputation

Data editing was partly manual and partly automatic.

Editing of the census data involved correcting errors from the field and those introduced during the capturing process. Both Structural Edits and Within Record Edits were used to clean the census data.

a) Structural Edits

• Structure edits check coverage and relationships between different units: persons, households, housing units, enumeration areas, etc. Specifically, they checked that: · all households and collective quarters records within an enumeration area were present and were in the proper order; · all occupied housing units have person records, but vacant units have no person records; · households have neither duplicate person records, nor missing person records; · enumeration areas have neither duplicate nor missing housing records.

• Each EA have the right geographic codes (region, district, locality, EA number, etc.)

• Every housing unit in an EA is entered and every record has a valid EA code

  The Structural edit looked at the following situations:

· Geography edits · Hierarchy of records · Correspondence between housing and population records · Editing relationships in a household · Family nuclei

b) Within Record Edits: This consisted of validity checks and consistency edits.

· Validity checks: were performed to see if the values of individual variables are plausible or lie with a reasonable range.

· Consistency edits were performed to ensure that there is coherence between two or more variables.

The Top-down editing approach, which starts by editing top priority variables, (such as age, sex, etc.) and moves sequentially through all variables in decreasing priority was used to edit the census data.

The Hot Deck or Dynamic Imputation was also used for both missing data and inconsistent/invalid items.

The Census Secretariat carefully developed Editing and Imputation rules with written sets of consistency rules and corrections. These rules were translated into three CONCOR editing applications (Pop-Edit.exe, Hse-Edit.exe and Fertility.exe), which were used to 'clean' the data. This was done at the Regional level.

Response rate

100 per cent

Sampling error estimates

No sampling errors

Data appraisal

A post Enumeration Survey (PES) was conducted to assess the extent of coverage and content error. ( See Adminstration Report )

Abstract

Since 1987, the Ghana Statistical Service (GSS) has been conducting the Ghana Living Standards Survey (GLSS) with the aim of measuring the living conditions and well-being of the population. The GLSS has been useful to policy makers and other stakeholders as it provides timely and reliable information about trends in poverty and helps identify priority areas for policy interventions that aim at improving the lives of the population. It has, over the years, served as one of the primary tools used in monitoring progress on poverty reduction strategies in the country. Monitoring poverty is an essential part of the struggle to end it.

The survey provides the required data at the regional and urban/rural levels for examining poverty and associated indicators for households and the population. The data also allow for decomposition of poverty changes between different groups: urban/rural, locality, region, and socioeconomic status.

Since the fifth round of the Ghana Living Standards Survey (GLSS5) in 2005, the Ghanaian economy benefited from the production of crude oil in commercial quantities and strong economic growth in 2011, leading to the achievement of lower-middle-income status for the country. Economic growth decreased thereafter to a low of 3.7 percent in 2016 but increased in 2017. However, it remains to be seen whether this growth has benefitted all sections of society, including the poorest. Several social intervention programs, including the Livelihood Empowerment Against Poverty (LEAP), Capitation Grant and School Feeding Programme, and now the Free Senior High School Programme started in 2017, have been implemented with the aim of alleviating poverty among the vulnerable population.

Poverty has many dimensions and is characterized by low income, malnutrition, ill-health, illiteracy, and insecurity, among others. The impact of the different factors could combine to keep households, and sometimes whole communities, in abject poverty. To address these, reliable information is required to develop and implement policies that would have an impact on the lives of the poor and vulnerable.

Geographic coverage

National Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling employed a two-stage stratified sampling design. One thousand (1,000) enumeration areas (EAs) were selected to form the Primary Sampling Units (PSUs). The PSUs were allocated into the 10 administrative regions using probability proportional to population size (PPS). The list of EAs from which the samples were drawn was based on the 2010 Population and Housing Census. The EAs were further divided into urban and rural localities of residence. A complete listing of households in the selected PSUs was undertaken to form the Secondary Sampling Units (SSUs). At the second stage, 15 households from each PSU were systematically selected. The total sample size came to 15,000 households nationwide. The sampling is discussed in detail in the appendix of the reports attached as documentation/external resources.

Cleaning operations

The application system for the collection of data was developed in CSPro software. All electronic data files for the GLSS7 were transferred remotely from the field (data collection locations) to GSS Head Office in Accra. Various levels of data protection measures were employed to ensure confidentiality of respondents' identification details and security of the data. Data editing, cleaning, coding and processing all started soon after data collected from the field were transferred to Head Office. The editing and cleaning included structure and consistency checks to ensure completeness of work in the field. It also included identification of outliers. Any inconsistencies identified in completed questionnaire from a particular EA were documented and reported to the team responsible to correct before they left the EA. Secondary editing, which required resolution of computer-identified inconsistencies was also undertaken. Even though most sections of the questionnaire were pre-coded some sections required coding in the office. This involved the assignment of numbers (codes) to the occupation and industry in which eligible household members worked using the detailed descriptions provided by the interviewer. Cleaning and aggregation of data were on-going as data were transferred from the field. The data processing including cleaning and aggregation started in October, 2017 and was completed in February, 2018.

Response rate

The response rate was 93.3%.