The number of male smokers in Ghana was forecast to continuously increase between 2024 and 2029 by in total 0.1 million individuals (+13.51 percent). After the sixth consecutive increasing year, the number of male smokers is estimated to reach 0.79 million individuals and therefore a new peak in 2029. Shown is the estimated number of male smokers in a given region or country. According to the WHO and World bank, smoking refers to the use of cigarettes, pipes or other types of tobacco, be it on a daily or non-daily basis.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of male smokers in countries like Senegal and Nigeria.

The number of female smokers in Ghana was forecast to continuously decrease between 2024 and 2029 by in total 0.01 million individuals (-50 percent). The number of female smokers is estimated to amount to 0.01 million individuals in 2029. Shown is the estimated number of female smokers in a given region or country. According to the WHO and World bank, smoking refers to the use of cigarettes, pipes or other types of tobacco, be it on a daily or non-daily basis.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of female smokers in countries like Senegal and Nigeria.

This research delves into the intricate dynamics of Ghana's demographic landscape and public health infrastructure amidst the backdrop of the COVID-19 pandemic. It explores how the pandemic has magnified existing challenges and exacerbated demographic trends, shedding light on critical issues such as mortality rates, healthcare accessibility, and infrastructure deficits.The study is driven by a clear purpose and set of objectives aimed at understanding the multifaceted impact of COVID-19 on Ghana's population and healthcare system. By delving into existing literature, the research contextualizes its investigation within the broader framework of global health challenges, emphasizing the significance of robust public health infrastructure in combating infectious diseases.Methodologically, the research adopts a qualitative approach, utilizing corpus construction and secondary data analysis to comprehensively examine demographic effects and health infrastructure deficits. This approach allows for a nuanced exploration of the complex interplay between COVID-19 dynamics and Ghana's demographic trends, providing valuable insights into the challenges faced by the country.The findings of the study illuminate the profound disruptions caused by COVID-19, particularly in terms of increased mortality rates and barriers to accessing healthcare services. Additionally, the research sheds light on systemic issues such as under funding and underproduction of global health resources, further highlighting the need for strategic interventions to address these challenges.In conclusion, the study underscores the imperative for international cooperation and strategic alliances in tackling the multifaceted challenges posed by pandemics. It offers practical recommendations aimed at prioritizing vaccine distribution, strengthening international health systems, improving service quality, and increasing financial investments in public health infrastructure. Overall, this research provides valuable insights that can inform policy and decision-making processes to enhance Ghana's resilience in the face of future health crises.

The number of smokers in Ghana was forecast to continuously increase between 2024 and 2029 by in total 0.04 million individuals (+5.26 percent). The number of smokers is estimated to amount to 0.8 million individuals in 2029. Shown is the estimated share of the adult population (15 years or older) in a given region or country, that smoke. According to the WHO and World bank, smoking refers to the use of cigarettes, pipes or other types of tobacco, be it on a daily or non-daily basis.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smokers in countries like Nigeria and Senegal.

The total consumer spending on healthcare in Ghana was forecast to continuously increase between 2024 and 2029 by in total 459.6 million U.S. dollars (+38.63 percent). After the seventh consecutive increasing year, the healthcare-related spending is estimated to reach 1.6 billion U.S. dollars and therefore a new peak in 2029. Consumer spending, in this case healthcare-related spending, refers to the domestic demand of private households and non-profit institutions serving households (NPISHs). Spending by corporations and the state is not included. The forecast has been adjusted for the expected impact of COVID-19.Consumer spending is the biggest component of the gross domestic product as computed on an expenditure basis in the context of national accounts. The other components in this approach are consumption expenditure of the state, gross domestic investment as well as the net exports of goods and services. Consumer spending is broken down according to the United Nations' Classification of Individual Consumption By Purpose (COICOP). The shown data adheres broadly to group 06. As not all countries and regions report data in a harmonized way, all data shown here has been processed by Statista to allow the greatest level of comparability possible. The underlying input data are usually household budget surveys conducted by government agencies that track spending of selected households over a given period.The data is shown in nominal terms which means that monetary data is valued at prices of the respective year and has not been adjusted for inflation. For future years the price level has been projected as well. The data has been converted from local currencies to US$ using the average exchange rate of the respective year. For forecast years, the exchange rate has been projected as well. The timelines therefore incorporate currency effects.Find more key insights for the total consumer spending on healthcare in countries like Ivory Coast and Nigeria.

Abstract

The 2008 Ghana Demographic and Health Survey (GDHS) is a national survey covering all ten regions of the country. The survey was designed to collect, analyse, and disseminate information on housing and household characteristics, education, maternal health and child health, nutrition, family planning, gender, and knowledge and behaviour related to HIV/AIDS. It included, for the first time, a module on domestic violence as one of the topics of investigation.

The 2008 GDHS is designed to provide data to monitor the population and health situation in Ghana. This is the fifth round in a series of national level population and health surveys conducted in Ghana under the worldwide Demographic and Health Surveys programme. Specifically, the 2008 GDHS has the primary objective of providing current and reliable information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood mortality, maternal and child health, domestic violence, and awareness and behaviour regarding AIDS and other sexually transmitted infections (STIs). The information collected in the 2008 GDHS will provide updated estimates of basic demographic and health indicators covered in the earlier rounds of 1988, 1993, 1998, and 2003 surveys.

The long-term objective of the survey includes strengthening the technical capacity of major government institutions, including the Ghana Statistical Service (GSS). The 2008 GDHS also provides comparable data for long-term trend analysis in Ghana, since the surveys were implemented by the same organisation, using similar data collection procedures. It also adds to the international database on demographic and health–related information for research purposes.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-59

Kind of data

Sample survey data

Sampling procedure

The 2008 GDHS was a household-based survey, implemented in a representative probability sample of more than 12,000 households selected nationwide. This sample was selected in such a manner as to allow for separate estimates of key indicators for each of the 10 regions in Ghana, as well as for urban and rural areas separately.

The 2008 GDHS utilised a two-stage sample design. The first stage involved selecting sample points or clusters from an updated master sampling frame constructed from the 2000 Ghana Population and Housing Census. A total of 412 clusters were selected from the master sampling frame. The clusters were selected using systematic sampling with probability proportional to size. A complete household listing operation was conducted from June to July 2008 in all the selected clusters to provide a sampling frame for the second stage selection of households.

The second stage of selection involved the systematic sampling of 30 of the households listed in each cluster. The primary objectives of the second stage of selection were to ensure adequate numbers of completed individual interviews to provide estimates for key indicators with acceptable precision and to provide a sample large enough to identify adequate numbers of under-five deaths to provide data on causes of death.

Data were not collected in one of the selected clusters due to security reasons, resulting in a final sample of 12,323 selected households. Weights were calculated taking into consideration cluster, household, and individual non-responses, so the representations were not distorted.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used for the 2008 GDHS: the Household Questionnaire, the Women’s Questionnaire and the Men’s Questionnaire. The content of these questionnaires was based on model questionnaires developed by the MEASURE DHS programme and the 2003 GDHS Questionnaires.

A questionnaire design workshop organised by GSS was held in Accra to obtain input from the Ministry of Health and other stakeholders on the design of the 2008 GDHS Questionnaires. Based on the questionnaires used for the 2003 GDHS, the workshop and several other informal meetings with various local and international organisations, the DHS model questionnaires were modified to reflect relevant issues in population, family planning, domestic violence, HIV/AIDS, malaria and other health issues in Ghana. These questionnaires were translated from English into three major local languages, namely Akan, Ga, and Ewe. The questionnaires were pre-tested in July 2008. The lessons learnt from the pre-test were used to finalise the survey instruments and logistical arrangements.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor and roof of the house, ownership of various durable goods, and ownership and use of mosquito nets. The Household Questionnaire was also used to record height and weight measurements, consent for, and the results of, haemoglobin measurements for women age 15-49 and children under five years. The haemoglobin testing procedure is described in detail in the next section.

The Household Questionnaire was also used to record all deaths of household members that occurred since January 2003. Based on this information, in each household that reported the death of a child under age five years since January 2005,3 field editors administered a Verbal Autopsy Questionnaire. Data on child mortality based on the verbal autopsy will be presented in a separate publication.

The Women’s Questionnaire was used to collect information from all women age 15-49 in half of selected households. These women were asked questions about themselves and their children born in the five years since 2003 on the following topics: education, residential history, media exposure, reproductive history, knowledge and use of family planning methods, fertility preferences, antenatal and delivery care, breastfeeding and infant and young child feeding practices, vaccinations and childhood illnesses, marriage and sexual activity, woman’s work and husband’s background characteristics, childhood mortality, awareness and behaviour about AIDS and other sexually transmitted infections (STIs), awareness of TB and other health issues, and domestic violence.

The Women’s Questionnaire included a series of questions to obtain information on women’s exposure to malaria during their most recent pregnancy in the five years preceding the survey and the treatment for malaria. In addition, women were asked if any of their children born in the five years preceding the survey had fever, whether these children were treated for malaria and the type of treatment they received.

The Men’s Questionnaire was administered to all men age 15-59 living in half of the selected households in the GDHS sample. The Men’s Questionnaire collected much of the same information found in the Women’s Questionnaire, but was shorter because it did not contain a reproductive history or questions on maternal and child health or nutrition.

Cleaning operations

The processing of the GDHS results began shortly after the fieldwork commenced. Completed questionnaires were returned periodically from the field to the GSS office in Accra, where they were entered and edited by data processing personnel who were specially trained for this task. Data were entered using CSPro, a programme specially developed for use in DHS surveys. All data were entered twice (100 percent verification). The concurrent processing of the data was a distinct advantage for data quality, because GSS had the opportunity to advise field teams of problems detected during data entry. The data entry and editing phase of the survey was completed in February 2009.

Response rate

A total of 12,323 households were selected in the sample, of which 11,913 were occupied at the time of the fieldwork. This difference between selected and occupied households occurred mainly because some of the selected structures were found to be vacant or destroyed. The number of occupied households successfully interviewed was 11,778, yielding a household response rate of 99 percent.

In the households selected for individual interview in the survey (50 percent of the total 2008 GDHS sample), a total of 5,096 eligible women were identified; interviews were completed with 4,916 of these women, yielding a response rate of 97 percent. In the same households, a total of 4,769 eligible men were identified and interviews were completed with 4,568 of these men, yielding a response rate of 96 percent. The response rates are slightly lower among men than women.

The principal reason for non-response among both eligible women and men was the failure to find individuals at home despite repeated visits to the household. The lower response rate for men reflects the more frequent and longer absences of men from the household

Note: See summarized response rates by place of residence in Table 1.1 of the survey report.

Sampling error

The current healthcare spending in Ghana was forecast to continuously increase between 2024 and 2029 by in total 1.1 billion U.S. dollars (+33.4 percent). After the fifth consecutive increasing year, the spending is estimated to reach 4.2 billion U.S. dollars and therefore a new peak in 2029. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. The spending refers to current spending of both governments and consumers.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current healthcare spending in countries like Senegal and Ivory Coast.

Abstract

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.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Woman age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

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.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used in the 2017 GMHS: the Household Questionnaire, the Woman’s Questionnaire, and the Verbal Autopsy Questionnaire.

Cleaning operations

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.

Response rate

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%.

Sampling error estimates

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 appraisal

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.

BackgroundGlobally, growth monitoring and promotion (GMP) of infants and young children is a fundamental component of routine preventive child health care; however, programs have experienced varying degrees of quality and success with enduring challenges. The objective of this study was to describe implementation of GMP (growth monitoring, growth promotion, data use, and implementation challenges) in two countries, Ghana and Nepal, to identify key actions to strengthen GMP programs.MethodsWe conducted semi-structured key informant interviews with national and sub-national government officials (n = 24), health workers and volunteers (n = 40), and caregivers (n = 34). We conducted direct structured observations at health facilities (n = 10) and outreach clinics (n = 10) to complement information from interviews. We coded and analyzed interview notes for themes related to GMP implementation.ResultsHealth workers in Ghana (e.g., community health nurses) and Nepal (e.g., auxiliary nurse midwives) had the knowledge and skills to assess and analyze growth based on weight measurement. However, health workers in Ghana centered growth promotion on the growth trend (weight-for-age over time), whereas health workers in Nepal based growth promotion on measurement from one point in time to determine whether a child was underweight. Overlapping challenges included health worker time and workload. Both countries tracked growth-monitoring data systematically; however, there was variation in growth monitoring data use.ConclusionThis study shows that GMP programs may not always focus on the growth trend for early detection of growth faltering and preventive actions. Several factors contribute to this deviation from the intended goal of GMP. To overcome them, countries need to invest in both service delivery (e.g., decision-making algorithm) and demand generation efforts (e.g., integrate with responsive care and early learning).

BackgroundGlobally, growth monitoring and promotion (GMP) of infants and young children is a fundamental component of routine preventive child health care; however, programs have experienced varying degrees of quality and success with enduring challenges. The objective of this study was to describe implementation of GMP (growth monitoring, growth promotion, data use, and implementation challenges) in two countries, Ghana and Nepal, to identify key actions to strengthen GMP programs.MethodsWe conducted semi-structured key informant interviews with national and sub-national government officials (n = 24), health workers and volunteers (n = 40), and caregivers (n = 34). We conducted direct structured observations at health facilities (n = 10) and outreach clinics (n = 10) to complement information from interviews. We coded and analyzed interview notes for themes related to GMP implementation.ResultsHealth workers in Ghana (e.g., community health nurses) and Nepal (e.g., auxiliary nurse midwives) had the knowledge and skills to assess and analyze growth based on weight measurement. However, health workers in Ghana centered growth promotion on the growth trend (weight-for-age over time), whereas health workers in Nepal based growth promotion on measurement from one point in time to determine whether a child was underweight. Overlapping challenges included health worker time and workload. Both countries tracked growth-monitoring data systematically; however, there was variation in growth monitoring data use.ConclusionThis study shows that GMP programs may not always focus on the growth trend for early detection of growth faltering and preventive actions. Several factors contribute to this deviation from the intended goal of GMP. To overcome them, countries need to invest in both service delivery (e.g., decision-making algorithm) and demand generation efforts (e.g., integrate with responsive care and early learning).

Abstract

The 1993 Ghana Demographic and Health Survey (GDHS) is a nationally representative survey of 4,562 women age 15-49 and 1,302 men age 15-59. The survey is designed to furnish policymakers, planners and program managers with factual, reliable and up-to-date information on fertility, family planning and the status of maternal and child health care in the country. The survey, which was carried out by the Ghana Statistical Service (GSS), marks Ghana's second participation in the worldwide Demographic and Health Surveys (DHS) program.

The principal objective of the 1993 GDHS is to generate reliable and current information on fertility, mortality, contraception and maternal and child health indicators. Such data are necessary for effective policy formulation as well as program design, monitoring and evaluation. The 1993 GDHS is, in large measure, an update to the 1988 GDHS. Together, the two surveys provide comparable information for two points in time, thus allowing assessment of changes and trends in various demographic and health indicators over time.

Long-term objectives of the survey include (i) strengthening the capacity of the Ghana Statistical Service to plan, conduct, process and analyze data from a complex, large-scale survey such as the Demographic and Health Survey, and (ii) contributing to the ever-expanding international database on demographic and health-related variables.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-59

Kind of data

Sample survey data

Sampling procedure

The 1993 GDHS is a stratified, self-weighting, nationally representative sample of households chosen from 400 Enumeration Areas (EAs). The 1984 Population Census EAs constituted the sampling frame. The frame was first stratified into three ecological zones, namely coastal, forest and savannah, and then into urban and rural EAs. The EAs were selected with probability proportional to the number of households. Households within selected EAs were subsequently listed and a systematic sample of households was selected for the survey. The survey was designed to yield a sample of 5,400 women age 15-49 and a sub-sample of males age 15-59 systematically selected from one-third of the 400 EAs.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face

Research instrument

Survey instruments used to elicit information for the 1993 GDHS are 1) Household Schedule 2) Women's Questionnaire and 3) Men's Questionnaire.

The questionnaires were structured based on the Demographic and Health Survey Model B Questionnaire designed for countries with low levels of contraceptive use. The final version of the questionnaires evolved out of a series of meetings with personnel of relevant ministries, institutions and organizations engaged in activities relating to fertility and family planning, health and nutrition and rehabilitation of persons with disabilities.

The questionnaires were first developed in English and later translated and printed in five major local languages, namely: Akan, Dagbani, Ewe, Ga, and Hausa. In the selected households, all usual members and visitors were listed in the household schedule. Background information, such as age, sex, relationship to head of household, marital status and level of education, was collected on each listed person. Questions on economic activity, occupation, industry, employment status, number of days worked in the past week and number of hours worked per day was asked of all persons age seven years and over. Those who did not work during the reference period were asked whether or not they actively looked for work.

Information on the health and disability status of all persons was also collected in the household schedule. Migration history was elicited from all persons age 15 years and over, as well as information on the survival status and residence of natural parents of all children less than 15 years in the household.

Data on source of water supply, type of toilet facility, number of sleeping rooms available to the household, material of floor and ownership of specified durable consumer goods were also elicited.

Finally, the household schedule was the instrument used to identify eligible women and men from whom detailed information was collected during the individual interview.

The women's questionnaire was used to collect information on eligible women identified in the household schedule. Eligible women were defined as those age 15-49 years who are usual members of the household and visitors who spent the night before the interview with the household. Questions asked in the questionnaire were on the following topics:

• Background Characteristics
• Reproductive History
• Contraceptive Knowledge and Use
• Pregnancy and Breastfeeding
• Immunization and Health
• Marriage
• Fertility Preferences
• Maternal Mortality
• Husband's Background and Women's Work
• Knowledge of AIDS and Other Sexually Transmitted Diseases (STDs).

All female respondents with at least one live birth since January 1990 and their children born since 1st January 1990 had their height and weight taken.

The men's questionnaire was administered to men in sample households in a third of selected EAs. An eligible man was 15-59 years old who is either a usual household member or a visitor who spent the night preceding the day of interview with the household.

Topics enquired about in the men's questionnaire included the following: - Background Characteristics - Reproductive History - Contraceptive Knowledge and Use - Marriage - Fertility Preferences - Knowledge of AIDS and Other STDs.

Cleaning operations

Questionnaires from the field were sent to the secretariat at the Head Office for checking and office editing. The office editing, which was undertaken by two officers, involved correcting inconsistencies in the questionnaire responses and coding open-ended questions. The questionnaires were then forwarded to the data processing unit for data entry. Data capture and verification were undertaken by four data entry operators. Nearly 20 percent of the questionnaires were verified. This phase of the survey covered four and a half months - that is, from mid-October, 1993 to the end of February, 1994.

After the data entry, three professional staff members performed the secondary editing of questionnaires that were flagged either because entries were inconsistent or values of specific variables were out of range or missing. The secondary editing was completed on 17th March, 1994 and the tables for the preliminary report were generated on 18th March, 1994. The software package used for the data processing was the Integrated System for Survey Analysis (ISSA).

Response rate

A sample of 6,161 households was selected, from which 5,919 households were contacted for interview. Interviews were successfully completed in 5,822 households, indicating a household response rate of 98 percent. About 3 percent of selected households were absent during the interviewing period, and are excluded from the calculations of the response rate.

Even though the sample was designed to yield interviews with nearly 5,400 women age 15-49 only 4,700 women were identified as eligible for the individual interview. Individual interviews were successfully completed for 4,562 eligible women, giving a response rate of 97 percent. Similarly, instead of the expected 1,700 eligible men being identified in the households only 1,354 eligible men were found and 1,302 of these were successfully interviewed, with a response rate of 96 percent.

The principal reason for non-response among eligible women and men was not finding them at home despite repeated visits to the households. However, refusal rates for both eligible women and men were low, 0.3 percent and 0.2 percent, respectively.

Note: See summarized response rates in Table 1.1 of the survey report.

Sampling error estimates

The results from sample surveys are affected by two types of errors, non-sampling error and sampling error. Non-sampling error is due to mistakes made in carrying out field activities, such as failure to locate and interview the correct household, errors in the way the questions are asked, misunderstanding on the part of either the interviewer or the respondent, data entry errors, etc. Although efforts were made during the design and implementation of the 1993 GDHS to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be measured statistically. The sample of eligible women selected in the 1993 GDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each one would have yielded results that differed somewhat from the actual sample selected. The sampling error is a measure of the variability between all possible samples; although it is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of standard error of a particular statistic (mean, percentage, etc.), which is the square root of the variance of the statistic. The standard error can be used to calculate confidence intervals within which, apart from non-sampling errors, 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 same statistic as measured in 95 percent of all possible samples with the same design (and expected size) will fall within a range

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

Objectives: To obtain reliable, valid and comparable health, health-related and well-being data over a range of key domains for adult and older adult populations in nationally representative samples To examine patterns and dynamics of age-related changes in health and well-being using longitudinal follow-up of a cohort as they age, and to investigate socio-economic consequences of these health changes To supplement and cross-validate self-reported measures of health and the anchoring vignette approach to improving comparability of self-reported measures, through measured performance tests for selected health domains To collect health examination and biomarker data that improves reliability of morbidity and risk factor data and to objectively monitor the effect of interventions

Additional Objectives: To generate large cohorts of older adult populations and comparison cohorts of younger populations for following-up intermediate outcomes, monitoring trends, examining transitions and life events, and addressing relationships between determinants and health, well-being and health-related outcomes To develop a mechanism to link survey data to demographic surveillance site data To build linkages with other national and multi-country ageing studies To improve the methodologies to enhance the reliability and validity of health outcomes and determinants data To provide a public-access information base to engage all stakeholders, including national policy makers and health systems planners, in planning and decision-making processes about the health and well-being of older adults

Methods: SAGE's first full round of data collection included both follow-up and new respondents in most participating countries. The goal of the sampling design was to obtain a nationally representative cohort of persons aged 50 years and older, with a smaller cohort of persons aged 18 to 49 for comparison purposes. In the older households, all persons aged 50+ years (for example, spouses and siblings) were invited to participate. Proxy respondents were identified for respondents who were unable to respond for themselves. Standardized SAGE survey instruments were used in all countries consisting of five main parts: 1) household questionnaire; 2) individual questionnaire; 3) proxy questionnaire; 4) verbal autopsy questionnaire; and, 5) appendices including showcards. A VAQ was completed for deaths in the household over the last 24 months. The procedures for including country-specific adaptations to the standardized questionnaire and translations into local languages from English follow those developed by and used for the World Health Survey.

Content

Household questionnaire 0000 Coversheet 0100 Sampling Information 0200 Geocoding and GPS Information 0300 Recontact Information 0350 Contact Record 0400 Household Roster 0450 Kish Tables and Household Consent 0500 Housing 0600 Household and Family Support Networks and Transfers 0700 Assets and Household Income 0800 Household Expenditures 0900 Interviewer Observations

Individual questionnaire 1000 Socio-Demographic Characteristics 1500 Work History and Benefits 2000 Health State Descriptions and Vignettes 2500 Anthropometrics, Performance Tests and Biomarkers 3000 Risk Factors and Preventive Health Behaviours 4000 Chronic Conditions and Health Services Coverage 5000 Health Care Utilization 6000 Social Cohesion 7000 Subjective Well-Being and Quality of Life (WHOQoL-8 and Day Reconstruction Method) 8000 Impact of Caregiving 9000 Interviewer Assessment

Geographic coverage

National coverage

Analysis unit

households and individuals

Universe

The household section of the survey covered all households in all ten administrative regions in Ghana. Institutionalised populations are excluded. The individual section covered all persons aged 18 years and older residing within individual households. As the focus of SAGE is older adults, a much larger sample of respondents aged 50 years and older were selected with a smaller comparative sample of respondents aged 18-49 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Ghana used a stratified, multistage cluster design. The sample was stratified by administrative region (Ashanti, Brong Ahafo, Central, Eastern, Greater Accra, Northern, Upper East, Upper West, Volta and Western) and type of locality (urban/rural) resulting in 20 strata and is nationally representative. The Census Enumerated Areas (CEA) of the 2000 Population and Housing Census was used as the sampling frame. A sample of 251 EAs was selected as the primary sampling units (PSU). One of the selected PSUs was not used. This was because the EA which was expected to be located at Korle Bu Teaching hospital cccould not be traced. The number of EAs to be selected from each strata was based on proportional allocation (determined by the number of EAs in each strata specified on the census frame). EAs were then selected from each stratum with probability proportional to size; the measure of size being the number of individuals aged 50 years or more in the EA. In each selected EA, a listing of the households was conducted to classify each household into the following mutually exclusive categories: (1) WHS/SAGE Wave 0 follow-up households with one or more members aged 50 years or more; (2) New households with one or more members aged 50 years or more; (3) WHS/SAGE Wave 0 follow-up households which did not include any members aged 50 years or more, but included residents aged 18-49; and, (4) New households which did not include any members aged 50 years or more, but included residents aged 18-49.

Twenty-four households were randomly selected from each selected EA. All WHS/SAGE Wave 0 follow-up 50-plus households were eligible for the household interview (one household respondent was selected). Twenty such households were selected. If this target number was not reached, then the balance was selected using systematic sampling from the new 50-plus households. All 50+ members of the household were eligible for the individual interview (multiple individual interviews possible in these households).

Stages of selection Strata: Region, Locality=20 PSU: EAs=235 surveyed SSU: Households=5269 surveyed TSU: Individual=5573 surveyed

Sampling deviation

One of the 251 selected PSUs was not used. This was because the EA which was expected to be located at Korle Bu Teaching hospital cccould not be traced.

Mode of data collection

Face-to-face [f2f] PAPI

Research instrument

The questionnaires were based on the WHS Model Questionnaire with some modification and many new additions. A household questionnaire was administered to all households eligible for the study. A Verbal Autopsy questionnaire was administered to households that had a death in the last 24 months. An Individual questionniare was administered to eligible respondents identified from the household roster. A Proxy questionnaire was administered to individual respondents who had cognitive limitations. The questionnaires were developed in English and were piloted as part of the SAGE pretest in 2005. All documents were translated into three local languanges: Akan, Ga and Twi. All SAGE generic questionnaires are available as external resources.

Cleaning operations

Data editing took place at a number of stages including: (1) office editing and coding (2) during data entry (3) structural checking of the CSPro files (4) range and consistency secondary edits in Stata

Response rate

Household Response rate=86% Cooperation rate=98%

Individual: Response rate=80% Cooperation rate=92%

The current healthcare spending per capita in Ghana was forecast to continuously increase between 2024 and 2029 by in total 20.5 U.S. dollars (+22.15 percent). After the fourth consecutive increasing year, the spending is estimated to reach 113.05 U.S. dollars and therefore a new peak in 2029. Depicted here is the average per capita spending, in a given country or region, with regards to healthcare. The spending refers to the average current spending of both governments and consumers per inhabitant.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current healthcare spending per capita in countries like Ivory Coast and Nigeria.

Abstract

In 2001, the World Health Organization (WHO), in collaboration with UNAIDS, UNESCO, and UNICEF, with technical assistance from the US Centers for Disease Control and Prevention (CDC), initiated development of the Global School-based Student Health Survey (GSHS). The GSHS is a part of the WHO STEPwise approach to Surveillance (STEPS). STEPS is a simple, standardized method for collecting, analyzing and disseminating data in WHO member countries (1). The GSHS is a survey conducted in different countries primarily among students aged 13-15 years.

The 2007 Ghana GSHS which was administered to junior high school students was adapted for use with senior high school students. The adapted instrument was called the 2008 Ghana GSHS. The purpose of the 2008 Ghana GSHS is to: 1) help Ghana develop priorities, establish programs, and advocate for resources for school health and youth health programs and policies, 2) to monitor trends in the prevalence of health risk behaviors and factors that influence those behaviors among senior high school students and 3) to allow other WHO member countries, international agencies, and others to make comparisons (same age group) across countries regarding the prevalence of health behaviors and protective factors.

Geographic coverage

National coverage

Analysis unit

Students aged 13-17 years

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2008 Ghana GSHS employed a two-stage cluster sample design to produce a representative sample of students in senior high school (SHS) levels one, two and three. The first-stage sampling frame consisted of all schools containing any SHS class level. Schools were selected with probability proportional to school enrolment size. For sampling, Ghana was divided into 3 zones representing all 10 geographic regions. The geographic regions within each zone are:

South Zone: Greater Accra, Central, Volta, Eastern Central Zone: Brong Ahafo, Ashanti, Western North Zone: Northern, Upper East And Upper West

Twenty five schools were selected from each zone. Therefore a total of 75 schools were selected for the Ghana survey. The second stage of sampling consisted of randomly selecting intact classrooms (using a random start) from each school to participate. All classrooms in each selected school were included in the sampling frame. All students in the sampled classrooms were eligible to participate in the GSHS.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2008 Ghana GSHS is a modification of the generic GSHS. It was developed by school health personnel from School Health Education Programme (SHEP) at GES. It contained 84 questions representing 9 of 10 GSHS core modules. The WHO requires participating member countries to use at least 6 of the 10 core modules. The 9 core areas included in the 2008 Ghana GSHS were: 1) respondent demographics, 2) sexual behaviors that contribute to HIV infection, other STIs and unintended pregnancy, hygiene, 3) dietary behaviors, 4) alcohol and other drug use, 5) physical activity, 6) tobacco, 7) protective factors, 8) violence and unintentional injury and, 9) mental health. Twenty-three of the 84 questions were country specific questions on topics of interest for Ghanaian school health authorities. These questions fell under areas of family dynamics, general health, non-sport physical activity, protective factors and malaria.

Cleaning operations

The data set was cleaned and edited for inconsistencies. Missing data were not statistically imputed. Software that takes into consideration the complex sample design was used to compute prevalence estimates and 95% confidence intervals. GSHS data for Ghana are representative of all students attending SHS level 1, 2 and 3. Students completed the self-administered questionnaire during one classroom period and recorded their responses directly on a computer-scannable answer sheet.

Response rate

The school response rate was 97%, and student response rate was 84%. Overall response rate 81%. A total of, 7137 students completed the survey. Of the latter number, 56.2% were male and 43.8% were female. Students between ages 16 - 18 (65.5%) made up the largest portion of the sample, followed by students 19 years old or older (22.7%) and 15 years or younger (11.8%).

Abstract

The primary objective of the 2014 GDHS was to generate recent reliable information on fertility, family planning, infant and child mortality, maternal and child health, and nutrition. In addition, the survey collected specialised data on malaria treatment, prevention, and prevalence among children age 6-59 months; blood pressure among adults; anaemia among women and children; and HIV prevalence among adults. This information is essential for making informed policy decisions and for planning, monitoring, and evaluating programmes related to health in general, and reproductive health in particular, at both the national and regional levels. Analysis of data collected in the 2014 GDHS provides updated estimates of basic demographic and health indicators covered in the earlier rounds of the 1988, 1993, 1998, 2003, and 2008 surveys.

The GDHS will assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of Ghana’s population. The 2014 GDHS also provides comparable data for long-term trend analysis in Ghana, since the surveys were implemented by the same organisation, using similar data collection procedures. Furthermore, the survey adds to the international database on demographic and health–related information for research purposes.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Children age 0-5
• Children age 4-15
• Woman age 15-49
• Man age 15-59

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2014 GDHS is an updated frame from the 2010 Ghana Population and Housing Census provided by the Ghana Statistical Service (GSS 2013b). The sampling frame excluded nomadic and institutional populations such as persons in hotels, barracks, and prisons.

The 2014 GDHS followed a two-stage sample design and was intended to allow estimates of key indicators at the national level as well as for urban and rural areas and each of Ghana's 10 administrative regions. The first stage involved selecting sample points (clusters) consisting of enumeration areas (EAs) delineated for the 2010 PHC. A total of 427 clusters were selected, 216 in urban areas and 211 in rural areas.

The second stage involved the systematic sampling of households. A household listing operation was undertaken in all the selected EAs in January-March 2014, and households to be included in the survey were randomly selected from the list. About 30 households were selected from each cluster to constitute the total sample size of 12,831 households. Because of the approximately equal sample sizes in each region, the sample is not self-weighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level.

All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed and have their blood pressure measured.

In half of the households, all men age 15-59 who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. In addition, in the subsample of households selected for the male survey: • blood pressure measurements were performed among eligible men who consented to being tested; • children age 6-59 months were tested for anaemia and malaria with the parent's or guardian's consent; • eligible women who consented were tested for anaemia; • blood samples were collected for laboratory testing of HIV from eligible women and men who consented; and • height and weight information was collected from eligible women, men, and children age 0- 59 months.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used for the 2014 GDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires, which were based on standard Demographic and Health Survey (DHS) questionnaires, were adapted to reflect the population and health issues relevant to Ghana. Comments on the questionnaires were solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. The definitive questionnaires were first prepared in English; they were then translated into the major local languages, namely Akan, Ga, and Ewe.

The Household Questionnaire was used to list all the members of and visitors to the selected households. Basic demographic information was collected on the characteristics of each person listed, including his or her age, sex, marital status, education, and relationship to the head of the household. For children under age 18, parents’ survival status was determined. The data on age and sex of household members obtained in the Household Questionnaire were used to identify women and men who were eligible for individual interviews. The Household Questionnaire also included questions on child education as well as the characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, materials used for the floor of the dwelling unit, and ownership of various durable goods.

The Woman’s Questionnaire was used to collect information from all eligible women age 15-49.

In half of the selected households, the Man’s Questionnaire was administered to all men age 15-59. The Man’s Questionnaire collected much of the same information found in the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health.

Cleaning operations

The data processing operation included 100 percent verification (also called second data entry) and secondary editing, which involved resolution of computer-identified inconsistencies. The data processing activities at the central office were led by one key GSS officer who took part in the main fieldwork training. Data processing was accomplished using CSPro software. Data entry and editing were initiated in September 2014 and completed in February 2015.

Response rate

A total of 12,831 households were selected for the sample, of which 12,010 were occupied. Of the occupied households, 11,835 were successfully interviewed, yielding a response rate of 99 percent, the same as the 2008 GDHS household response rate (GSS, GHS, and ICF Macro 2009).

In the interviewed households, 9,656 eligible women were identified for individual interviews; interviews were completed with 9,396 women, yielding a response rate of 97 percent. In the subsample of households selected for the male survey, 4,609 eligible men were identified and 4,388 were successfully interviewed, yielding a response rate of 95 percent. The lower response rate for men was likely due to their more frequent and longer absences from the household.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling 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 2014 Ghana DHS (GDHS) to minimize this type of error, non-sampling 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 2014 GDHS 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 between 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 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 2014 GDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. Sampling errors are computed in either ISSA or SAS, using programs developed by ICF International. These programs use the Taylor linearization method of variance estimation 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.

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

IntroductionIn Sub-Saharan Africa (SSA), HIV remains the leading cause of adult premature death. The rising prevalence of Female Genital Schistosomiasis (FGS) in SSA, including Ghana, has led to a growing dual burden of HIV-FGS cases. This trend has prompted the WHO to advocate for integrated HIV and FGS services. This study examined stakeholder perspectives on integrating FGS prevention and control with HIV care in endemic areas of Ghana.MethodsThe study took place in Ga South Municipality, Greater Accra Region, Ghana. A qualitative approach combining narrative and phenomenological designs was used. Data collection included Focus Group Discussions with Community Health Officers (CHOs) (n = 9), and Key Informant Interviews with healthcare providers at regional, district, and community levels (n = 13). In-depth interviews were also conducted with individuals affected by FGS and HIV (n = 13), female household members (n = 10), Community Health Management Committee members, and community leaders (n = 7). Participants were purposively selected. Audio-recorded interviews were transcribed, coded, and thematically analyzed using NVivo version 13.ResultsThere was a notable knowledge gap on FGS among CHOs and community members. Many health workers mistook FGS for sexually transmitted infections, while community members primarily recognized it through gynecological symptoms. Healthcare was sought from a mix of formal health facilities, herbalists, and spiritual centers, often delaying accurate diagnosis and management. Barriers to integrating HIV and FGS services included limited awareness, stigma, cultural beliefs, provider attitudes, and resource shortages.ConclusionsBoth CHOs and community members lacked sufficient knowledge about FGS, hindering regular screening and timely diagnosis. While integrating FGS and HIV care could support Ghana’s HIV eradication goals, success depends on addressing stigma, improving awareness, ensuring drug availability, and equipping health facilities. Collaboration among healthcare professionals and developing standardized clinical protocols are essential. Training community health workers on these protocols is urgently needed to support effective integration.

Ghana GH: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data was reported at 1.800 % in 2024. This stayed constant from the previous number of 1.800 % for 2023. Ghana GH: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data is updated yearly, averaging 2.600 % from Dec 2000 (Median) to 2024, with 25 observations. The data reached an all-time high of 3.400 % in 2003 and a record low of 1.800 % in 2024. Ghana GH: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ghana – Table GH.World Bank.WDI: Social: Health Statistics. Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.;UNICEF, WHO, World Bank: Joint child Malnutrition Estimates (JME).;Weighted average;Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues. Estimates are modeled estimates produced by the JME. Primary data sources of the anthropometric measurements are national surveys. These surveys are administered sporadically, resulting in sparse data for many countries. Furthermore, the trend of the indicators over time is usually not a straight line and varies by country. Tracking the current level and progress of indicators helps determine if countries are on track to meet certain thresholds, such as those indicated in the SDGs. Thus the JME developed statistical models and produced the modeled estimates.

Abstract (en): The Research on Early Life and Aging Trends and Effects (RELATE) study compiles cross-national data that contain information that can be used to examine the effects of early life conditions on older adult health conditions, including heart disease, diabetes, obesity, functionality, mortality, and self-reported health. The complete cross sectional/longitudinal dataset (n=147,278) was compiled from major studies of older adults or households across the world that in most instances are representative of the older adult population either nationally, in major urban centers, or in provinces. It includes over 180 variables with information on demographic and geographic variables along with information about early life conditions and life course events for older adults in low, middle and high income countries. Selected variables were harmonized to facilitate cross national comparisons. In this first public release of the RELATE data, a subset of the data (n=88,273) is being released. The subset includes harmonized data of older adults from the following regions of the world: Africa (Ghana and South Africa), Asia (China, India), Latin America (Costa Rica, major cities in Latin America), and the United States (Puerto Rico, Wisconsin). This first release of the data collection is composed of 19 downloadable parts: Part 1 includes the harmonized cross-national RELATE dataset, which harmonizes data from parts 2 through 19. Specifically, parts 2 through 19 include data from Costa Rica (Part 2), Puerto Rico (Part 3), the United States (Wisconsin) (Part 4), Argentina (Part 5), Barbados (Part 6), Brazil (Part 7), Chile (Part 8), Cuba (Part 9), Mexico (Parts 10 and 15), Uruguay (Part 11), China (Parts 12, 18, and 19), Ghana (Part 13), India (Part 14), Russia (Part 16), and South Africa (Part 17). The Health and Retirement Study (HRS) was also used in the compilation of the larger RELATE data set (HRS) (N=12,527), and these data are now available for public release on the HRS data products page. To access the HRS data that are part of the RELATE data set, please see the collection notes below. The purpose of this study was to compile and harmonize cross-national data from both the developing and developed world to allow for the examination of how early life conditions are related to older adult health and well being. The selection of countries for this study was based on their diversity but also on the availability of comprehensive cross sectional/panel survey data for older adults born in the early to mid 20th century in low, middle and high income countries. These data were then utilized to create the harmonized cross-national RELATE data (Part 1). Specifically, data that are being released in this version of the RELATE study come from the following studies: CHNS (China Health and Nutrition Study) CLHLS (Chinese Longitudinal Healthy Longevity Survey) CRELES (Costa Rican Study of Longevity and Healthy Aging) PREHCO (Puerto Rican Elderly: Health Conditions) SABE (Study of Aging Survey on Health and Well Being of Elders) SAGE (WHO Study on Global Ageing and Adult Health) WLS (Wisconsin Longitudinal Study) Note that the countries selected represent a diverse range in national income levels: Barbados and the United States (including Puerto Rico) represent high income countries; Argentina, Cuba, Uruguay, Chile, Costa Rica, Brazil, Mexico, and Russia represent upper middle income countries; China and India represent lower middle income countries; and Ghana represents a low income country. Users should refer to the technical report that accompanies the RELATE data for more detailed information regarding the study design of the surveys used in the construction of the cross-national data. The Research on Early Life and Aging Trends and Effects (RELATE) data includes an array of variables, including basic demographic variables (age, gender, education), variables relating to early life conditions (height, knee height, rural/urban birthplace, childhood health, childhood socioeconomic status), adult socioeconomic status (income, wealth), adult lifestyle (smoking, drinking, exercising, diet), and health outcomes (self-reported health, chronic conditions, difficulty with functionality, obesity, mortality). Not all countries have the same variables. Please refer to the technical report that is part of the documentation for more detail regarding the variables available across countries. Sample weights are applicable to all countries exc...

The current health expenditure as a share of the GDP in Ghana was forecast to continuously increase between 2024 and 2029 by in total 0.1 percentage points. The share is estimated to amount to 4.29 percent in 2029. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. It is depicted here in relation to the total gross domestic product (GDP) of the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current health expenditure as a share of the GDP in countries like Senegal and Nigeria.