At the lower-middle-income level, the poverty rate in Ghana was forecast at 26.8 percent in 2021, meaning this share of the population lived up on 3.20 U.S. dollars per day. Considering the upper-middle-income level, at 5.50 U.S. dollars per day, the poverty rate was forecast at 51.7 percent. The values changed slightly compared to the previous years in analysis. This means that the rate of poverty in Ghana was not expected to experience drastic changes in the years following 2019. The coronavirus (COVID-19) pandemic and its impact on economic activities could be attributed to the unimproved poverty levels registered in the country.

Ghana GH: Income Share Held by Lowest 20% data was reported at 5.400 % in 2012. This records an increase from the previous number of 5.200 % for 2005. Ghana GH: Income Share Held by Lowest 20% data is updated yearly, averaging 6.200 % from Dec 1987 (Median) to 2012, with 6 observations. The data reached an all-time high of 7.000 % in 1988 and a record low of 5.200 % in 2005. Ghana GH: Income Share Held by Lowest 20% 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: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Ghana GH: Income Share Held by Highest 10% data was reported at 31.700 % in 2012. This records a decrease from the previous number of 32.700 % for 2005. Ghana GH: Income Share Held by Highest 10% data is updated yearly, averaging 29.850 % from Dec 1987 (Median) to 2012, with 6 observations. The data reached an all-time high of 32.700 % in 2005 and a record low of 27.300 % in 1987. Ghana GH: Income Share Held by Highest 10% 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: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

This dataset contains key characteristics about the data described in the Data Descriptor Physical activity, time use, and food intakes of rural households in Ghana, India, and Nepal. Contents:

    1. human readable metadata summary table in CSV format


    2. machine readable metadata file in JSON format 
     Versioning Note:Version 2 was generated when the metadata format was updated from JSON to JSON-LD. This was an automatic process that changed only the format, not the contents, of the metadata.

Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Middle East & North Africa data was reported at 0.550 % in 2016. This records an increase from the previous number of 0.175 % for 2015. Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Middle East & North Africa data is updated yearly, averaging 0.364 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 1.115 % in 1989 and a record low of 0.031 % in 1961. Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Middle East & North Africa 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: Exports. Merchandise exports to low- and middle-income economies in Middle East and North Africa are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Middle East and North Africa region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

Objectives: Multimorbidity is a growing public health concern due to the increasing burden of non-communicable diseases, yet information about multimorbidity in low- and middle-income countries and migrant populations is scarce. We aimed to investigate the distribution and patterns of multimorbidity in rural and urban areas in Ghana and Ghanaian migrants in Europe.Methods: The RODAM cross-sectional study included 4,833 participants. Multimorbidity was defined as presence of multiple non-communicable chronic conditions. Patterns were determined from frequent combination of conditions. Prevalence ratios were estimated by logistic regression.Results: Prevalence of multimorbidity was higher in women and in urban Ghana and Europe. We observed a cardiometabolic pattern in all sites as well as circulatory-musculoskeletal and metabolic-musculoskeletal combinations in Ghana. Multimorbidity prevalence ratios were higher in Europe (men 1.47, 95% CI 1.34–1.59, women 1.18, 1.10–1.26) and urban Ghana (men 1.46, 1.31–1.59, women 1.27, 1.19–1.34).Conclusion: Distribution and patterns of multimorbidity differed by sex and site. With a higher burden of multimorbidity in urban areas, prevention strategies should focus on forestalling its increase in rapidly growing rural areas.

Ghana GH: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Middle East & North Africa data was reported at 1.892 % in 2016. This records an increase from the previous number of 1.519 % for 2015. Ghana GH: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Middle East & North Africa data is updated yearly, averaging 1.317 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 11.528 % in 1982 and a record low of 0.022 % in 1986. Ghana GH: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Middle East & North Africa 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: Imports. Merchandise imports from low- and middle-income economies in Middle East and North Africa are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Middle East and North Africa region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

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%.

This report consists of four chapters. Chapter one profiles the trends in household consumption and poverty rates, and in the characteristics of the poor observed between 1991 and 2012. Descriptive statistics of consumption and selected poverty indexes are presented and a profile of the characteristics of the poor is given. The chapter concludes with an analysis of vulnerability. Chapter two uses descriptive and econometric techniques to identify the drivers of Ghana’s success over the last two decades. Chapter three examines the main challenges Ghana continues to face: widening inequalities, a persistent spatial divide, and the deteriorating macroeconomic environment. Chapter four provides a roadmap for policy action to effectively address these challenges and consolidate Ghana’s success as a middle-income economy.

Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: East Asia & Pacific data was reported at 16.125 % in 2016. This records an increase from the previous number of 8.270 % for 2015. Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: East Asia & Pacific data is updated yearly, averaging 2.196 % from Dec 1960 (Median) to 2016, with 56 observations. The data reached an all-time high of 16.125 % in 2016 and a record low of 0.050 % in 1992. Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: East Asia & Pacific 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: Exports. Merchandise exports to low- and middle-income economies in East Asia and Pacific are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the East Asia and Pacific region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, and Round 6 (2014-2015) 36 countries. The survey covered 34 countries in Round 7 (2016-2018). Round 8 surveys are planned in at least 35 countries in 2019-2020.

Geographic coverage

National coverage

Analysis unit

Individual

Universe

Citizens of Ghana who are 18 years and older.

Kind of data

Sample survey data [ssd]

Sampling procedure

• Sample size: 2,400
• Sampling frame: 2019 adult population projections based on the 2010 Ghana Population and Housing Census frame.
• Sample design: Nationally representative, random, clustered, stratified, multi-stage area probability sample
• Stratification: Region and urban-rural location
• Stages: PSUs (from strata), start points, households, respondents
• PSU selection: Probability proportionate to population size (PPPS)
• Cluster size: 8 households per PSU
• Household selection: Randomly selected start points, followed by walk pattern using 5/10 interval
• Respondent selection: Gender quota filled by alternating interviews between men and women; respondents of appropriate gender listed, after which computer randomly selects individual.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Round 8 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data. As in previous Rounds, about two-thirds of the items from the Round 6 questionnaire remain the same, and about one-third are new items. In identifying new survey topics, the Questionnaire Committee sought to align the instrument with the global development agenda by incorporating topics that speak to the Sustainable Development Goals (SDGs) that were adopted by the United Nations General Assembly in 2015. Some of the new survey topics in the R8 questionnaire include: Safety and Security; State capacity; Migration; Closing spaces; Inclusion; Climate change and, the Middle class.

The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent. This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent. 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker.

Response rate

Contact rate: 97% Cooperation rate: 92% Refusal rate: 5% Response rate: 89%

Ghana GH: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Within Region data was reported at 6.642 % in 2016. This records a decrease from the previous number of 6.773 % for 2015. Ghana GH: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Within Region data is updated yearly, averaging 12.328 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 39.864 % in 1984 and a record low of 2.385 % in 1967. Ghana GH: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Within Region 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: Imports. Merchandise imports from low- and middle-income economies within region are the sum of merchandise imports by the reporting economy from other low- and middle-income economies in the same World Bank region according to the World Bank classification of economies. Data are as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data. No figures are shown for high-income economies, because they are a separate category in the World Bank classification of economies.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

BackgroundReducing neonatal and child mortality is a key component of the health-related sustainable development goal (SDG), but most low and middle income countries lack data to monitor child mortality on an annual basis. We tested a mortality monitoring system based on the continuous recording of pregnancies, births and deaths by trained community-based volunteers (CBV).Methods and findingsThis project was implemented in 96 clusters located in three districts of the Northern Region of Ghana. Community-based volunteers (CBVs) were selected from these clusters and were trained in recording all pregnancies, births, and deaths among children under 5 in their catchment areas. Data collection lasted from January 2012 through September 2013. All CBVs transmitted tallies of recorded births and deaths to the Ghana Birth and deaths registry each month, except in one of the study districts (approximately 80% reporting). Some events were reported only several months after they had occurred. We assessed the completeness and accuracy of CBV data by comparing them to retrospective full pregnancy histories (FPH) collected during a census of the same clusters conducted in October-December 2013. We conducted all analyses separately by district, as well as for the combined sample of all districts. During the 21-month implementation period, the CBVs reported a total of 2,819 births and 137 under-five deaths. Among the latter, there were 84 infant deaths (55 neonatal deaths and 29 post-neonatal deaths). Comparison of the CBV data with FPH data suggested that CBVs significantly under-estimated child mortality: the estimated under-5 mortality rate according to CBV data was only 2/3 of the rate estimated from FPH data (95% Confidence Interval for the ratio of the two rates = 51.7 to 81.4). The discrepancies between the CBV and FPH estimates of infant and neonatal mortality were more limited, but varied significantly across districts.ConclusionsIn northern Ghana, a community-based data collection systems relying on volunteers did not yield accurate estimates of child mortality rates. Additional implementation research is needed to improve the timeliness, completeness and accuracy of such systems. Enhancing pregnancy monitoring, in particular, may be an essential step to improve the measurement of neonatal mortality.

As of 2023 people in Ghana employed in the field of executive management and change received the highest average salary of ****** U.S. dollars per year. Engineering and financial service professionals followed, with ****** and ****** U.S. dollars of annual earnings, respectively. According to the source, the lowest salary was received by individuals working in the area of logistics, operations and purchasing, as this amounted to ***** U.S. dollars per year.

The definition of urban and rural areas differs across countries, which is evident in household surveys conducted in low- and middle-income countries. This lack of consistency and variation poses challenges for comparative analyses of the relationship between urbanization and health outcomes. Additionally, the binary urban-rural dichotomy fails to acknowledge the existence of an urban-rural continuum, encompassing remote rural areas, semi-urban suburbs, and core urban areas. By utilizing satellite-based datasets, it is possible to employ objective and continuous measures that quantify the level of urbanization with high spatial resolution. We utilize geospatial techniques to derive alternative classifications of the urban continuum from satellite data across nine household surveys conducted from 2005 to 2019 in six African countries and provide the database here

Adolescents need to make informed SRH decisions which may lead to healthy sexual behaviours. Although adolescents have a great need for information regarding sexual and reproductive health, several factors may constrain their parents from openly communicating with them on the topic. This is particularly challenging in the Ghanaian setting, due to its unique socio-cultural and religious context. Considering the adolescent sexual and reproductive health challenges in Ghana, an intervention such as a sexual and reproductive health information communication intervention become an important means of optimizing positive sexual and reproductive health outcomes among adolescents. There is documented evidence of the value of parent-adolescent sexual and reproductive health information communication interventions in improving communication between parents and adolescents. However, it appears there has been insufficient focus on this.The aim of this study was to explore SRH information communication interventions to inform the adaptation of a culturally sensitive SRH information communication intervention to enhance parent-adolescent communication skills, leading to healthy and safe SRH behaviour among adolescents in Ghana.This was an explanatory sequential mixed method study. It began with quantitative data collection, through a systematic review of sexual and reproductive health information communication interventions in lower- and middle-income countries. Key findings were used to develop an interview guide for qualitative data collection in phase 2. Results from the systematic review and the qualitative study were integrated to understand how a culturally sensitive SRH information communication intervention can be adapted in the Ghanaian context. The final phase was the adaptation of a culturally sensitive parent-adolescent sexual and reproductive health information communication intervention.Findings from the systematic review, qualitative and mixed method phases formed the basis of adaptation of a culturally sensitive sexual and reproductive health information communication intervention. The adapted intervention (ɛtwene), which is yet to be implemented, takes into account the following components: (1) experts to deliver the intervention (2) method of delivery of the intervention (3) venue or place of intervention delivery (4) lessons on SRH information (5) lessons on motivation to communicate SRH information (6) lessons on skills to communicate SRH information. The name of the intervention is ‘3twene’, which means bridge.

Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Latin America & The Caribbean data was reported at 1.897 % in 2016. This records an increase from the previous number of 0.201 % for 2015. Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Latin America & The Caribbean data is updated yearly, averaging 0.402 % from Dec 1966 (Median) to 2016, with 49 observations. The data reached an all-time high of 1.897 % in 2016 and a record low of 0.000 % in 1983. Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Latin America & The Caribbean 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: Exports. Merchandise exports to low- and middle-income economies in Latin America and the Caribbean are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Latin America and the Caribbean region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

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 double burden of malnutrition has assumed severer forms in Low and Middle Income Countries (LMICs) arising from sharper increases in prevalence rates of overweight and obesity in these countries compared to higher income countries. Considering that LMICs already have fragile health systems, the rising obesity levels may just be a ticking time bomb requiring expeditious implementation of priority actions by all global and national actors to prevent an explosion of cardiovascular disease related deaths. The aim of this systematic review and meta-analysis was to provide a current estimate of obesity and overweight prevalence among Ghanaian adults and assess socio-demographic disparities following the PRISMA guidelines. We searched Pubmed with Medline, Embase, Science direct and African Journals Online (AJOL) for studies on overweight and obesity published between 2013 and January 2023. Applying a quality effects model, pooled mean Body Mass Index (BMI) and prevalence of overweight and obesity were obtained from 42 studies conducted across all three geographical locations of Ghana with a combined sample size of 29137. From the analysis, the mean BMI of adults in Ghana was 24.7 kgm-2 while overweight and obesity prevalence was estimated as 23.1% and 13.3% respectively. Temporal analysis showed sharper increases in overweight and obesity prevalence from 2017/2018. Mean BMI (Females: 25.3kgm-2 vrs Males: 23.1 kgm-2), overweight (Females: 25.9% vrs Males: 16.5%) and obesity (Females: 17.4% vrs Males: 5.5%) prevalence were higher among females than males. Gender differences in mean BMI and obesity prevalence were both significant at p

Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Within Region data was reported at 16.179 % in 2016. This records an increase from the previous number of 7.758 % for 2015. Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Within Region data is updated yearly, averaging 4.066 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 62.931 % in 2010 and a record low of 0.367 % in 1980. Ghana GH: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Within Region 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: Exports. Merchandise exports to low- and middle-income economies within region are the sum of merchandise exports from the reporting economy to other low- and middle-income economies in the same World Bank region as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data. No figures are shown for high-income economies, because they are a separate category in the World Bank classification of economies.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;