Health Nutrition and Population Statistics database provides key health, nutrition and population statistics gathered from a variety of international and national sources. Themes include global surgery, health financing, HIV/AIDS, immunization, infectious diseases, medical resources and usage, noncommunicable diseases, nutrition, population dynamics, reproductive health, universal health coverage, and water and sanitation.

Abstract copyright UK Data Service and data collection copyright owner.

The Subnational Population Database presents estimated population at the first administrative level below the national level. Many of the data come from the country’s national statistical offices. Other data come from the NASA Socioeconomic Data and Applications Center (SEDAC) managed by the Center for International Earth Science Information Network (CIESIN), Earth Institute, Columbia University. It is the World Bank Group’s first subnational population database at a global level and there are data limitations. Series metadata includes methodology and the assumptions made.

These data were first provided by the UK Data Service in April 2016.

Main Topics:

The following topics are covered:

• Population, total
• Population (% of total)

Context

The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank

Content

This dataset combines key health statistics from a variety of sources to provide a look at global health and population trends. It includes information on nutrition, reproductive health, education, immunization, and diseases from over 200 countries.

Update Frequency: Biannual

For more information, see the World Bank website.

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Acknowledgements

https://datacatalog.worldbank.org/dataset/health-nutrition-and-population-statistics

https://cloud.google.com/bigquery/public-data/world-bank-hnp

Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Citation: The World Bank: Health Nutrition and Population Statistics

Banner Photo by @till_indeman from Unplash.

Inspiration

What’s the average age of first marriages for females around the world?

Explore World Bank Health, Nutrition and Population Statistics dataset featuring a wide range of indicators such as School enrollment, UHC service coverage index, Fertility rate, and more from countries like Bahrain, China, India, Kuwait, Oman, Qatar, and Saudi Arabia.

School enrollment, tertiary, UHC service coverage index, Wanted fertility rate, People with basic handwashing facilities, urban population, Rural population, AIDS estimated deaths, Domestic private health expenditure, Fertility rate, Domestic general government health expenditure, Age dependency ratio, Postnatal care coverage, People using safely managed drinking water services, Unemployment, Lifetime risk of maternal death, External health expenditure, Population growth, Completeness of birth registration, Urban poverty headcount ratio, Prevalence of undernourishment, People using at least basic sanitation services, Prevalence of current tobacco use, Urban poverty headcount ratio, Tuberculosis treatment success rate, Low-birthweight babies, Female headed households, Completeness of birth registration, Urban population growth, Antiretroviral therapy coverage, Labor force, and more.

Bahrain, China, India, Kuwait, Oman, Qatar, Saudi Arabia

Follow data.kapsarc.org for timely data to advance energy economics research.

This database presents population and other demographic estimates and projections from 1960 to 2050, covering more than 200 economies. It includes population data by various age groups, sex, urban/rural; fertility data; mortality data; and migration data.

Subnational Population Database presents estimated population at the first administrative level below the national level. Many of the data come from the country’s national statistical offices. Other data come from the NASA Socioeconomic Data and Applications Center (SEDAC) managed by the Center for International Earth Science Information Network (CIESIN), Earth Institute, Columbia University. It is the World Bank Group’s first subnational population database at a global level and there are data limitations. Series metadata includes methodology and the assumptions made.

This dataset contains Saudi Arabia Population Health Indicators. Data from The World Bank. Follow https://datasource.kapsarc.org/ for timely data to advance energy economics research.

© 2016 The World Bank Group, All Rights Reserved.

Saudi Arabia population health related dataset from the world bank. There are over 1300 series in the dataset, we have selected those relevant to health category. Checkout other related dataset Population, Employment and Education in demographic category of our portal.

The dataset shows the 2019 Somalia population cluster developed by KTH.

This map service, derived from World Bank data, shows various characteristics of the Health topic. The World Bank Group provides financing, state-of-the-art analysis, and policy advice to help countries expand access to quality, affordable health care; protects people from falling into poverty or worsening poverty due to illness; and promotes investments in all sectors that form the foundation of healthy societies.Age Dependency Ratio: Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Age Dependency Ratio Old: Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Birth/Death Rate: Crude birth/death rate indicates the number of births/deaths occurring during the year, per
1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration. Data spans from 1960 – 2008.Total Fertility: Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with current age-specific fertility rates. Data shown is for 1960 - 2008.Population Growth: Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage.
Population is based on the de facto definition of population, which
counts all residents regardless of legal status or citizenship--except
for refugees not permanently settled in the country of asylum, who are
generally considered part of the population of the country of origin. Data spans from 1960 – 2009.Life Expectancy: Life expectancy at birth indicates the number of years a newborn infant
would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life. Data spans from 1960 – 2008.Population Female: Female population is the percentage of the population that is female. Population is based on the de facto definition of population. Data from 1960 – 2009.For more information, please visit: World Bank Open Data. _Other International User Community content that may interest you World Bank World Bank Age World Bank Health

This dataset provides population and other demographic estimates and projections from 1960 to 2050. They are disaggregated by age-group and gender and cover approximately 200 economies.

Follow datasource.kapsarc.org for timely data to advance energy economics research.

© 2016 The World Bank Group, All Rights Reserved.

Saudi Arabia education indicator related dataset from the world bank. There are over 1300 series in the dataset, we have selected those relevant to education category. Checkout other related dataset Population, Health and Employment in demographic category of our portal.

| * Citation: "World Development Indicators| World Databank". Databank.worldbank.org. N.p., 2016. Web. 10 Mar. 2016. | | | | | | |

Abstract

The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

All formal (i.e., registered) private sector businesses (with at least 1% private ownership) and with at least five employees. In terms of sectoral criteria, all manufacturing businesses (ISIC Rev 4. codes 10-33) are eligible; for services businesses, those corresponding to the ISIC Rev 4 codes 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95 are included in the Enterprise Surveys. Cooperatives and collectives are excluded from the Enterprise Surveys. All eligible establishments must be registered with the registration agency. In the case of Ireland, a firm was classified as registered if recorded in the Companies Registration Office.

Kind of data

Sample survey data [ssd]

Sampling procedure

The WBES use stratified random sampling, where the population of establishments is first separated into non-overlapping groups, called strata, and then respondents are selected through simple random sampling from each stratum. The detailed methodology is provided in the Sampling Note (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note-Consolidated-2-16-22.pdf). Stratified random sampling has several advantages over simple random sampling. In particular, it:

• produces unbiased estimates of the whole population or universe of inference, as well as at the levels of stratification
• ensures representativeness by including observations in all of those categories
• produces more precise estimates for a given sample size or budget allocation, and
• may reduce implementation costs by splitting the population into convenient subdivisions.

The WBES typically use three levels of stratification: industry classification, establishment size, and subnational region (used in combination). Starting in 2022, the WBES bases the industry classification on ISIC Rev. 4 (with earlier surveys using ISIC Rev. 3.1). For regional coverage within a country, the WBES has national coverage.

Note: Refer to Sampling Structure section in "The Ireland 2024 World Bank Enterprise Survey Implementation Report" for detailed methodology on sampling.

Mode of data collection

Face-to-face [f2f]

Research instrument

The standard WBES questionnaire covers several topics regarding the business environment and business performance. These topics include general firm characteristics, infrastructure, sales and supplies, trade, management practices, competition, innovation, capacity, land and permits, finance, business-government relations, exposure to bribery, labor, and performance. Information about the general structure of the questionnaire is available in the Enterprise Surveys Manual and Guide (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Enterprise-Surveys-Manual-and-Guide.pdf).

Response rate

Overall survey response rate was 9.9%.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Improving health is central to the Millennium Development Goals, and the public sector is the main provider of health care in developing countries. To reduce inequities, many countries have emphasized primary health care, including immunization, sanitation, access to safe drinking water, and safe motherhood initiatives. Data here cover health systems, disease prevention, reproductive health, nutrition, and population dynamics. Data are from the United Nations Population Division, World Health Organization, United Nations Children's Fund, the Joint United Nations Programme on HIV/AIDS, and various other sources.

Colombia CO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at -2.590 % in 2021. Colombia CO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging -2.590 % from Dec 2021 (Median) to 2021, with 1 observations. The data reached an all-time high of -2.590 % in 2021 and a record low of -2.590 % in 2021. Colombia CO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Poverty and Inequality. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The coverage and quality of the 2017 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2017 exercise of the International Comparison Program. See the Poverty and Inequality Platform for detailed explanations.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

Jamaica Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 0.700 % in 2021. This records an increase from the previous number of 0.300 % for 2018. Jamaica Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 0.500 % from Dec 2018 (Median) to 2021, with 2 observations. The data reached an all-time high of 0.700 % in 2021 and a record low of 0.300 % in 2018. Jamaica Multidimensional Poverty Headcount Ratio: World Bank: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jamaica – Table JM.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Improving health is central to the Millennium Development Goals, and the public sector is the main provider of health care in developing countries. To reduce inequities, many countries have emphasized primary health care, including immunization, sanitation, access to safe drinking water, and safe motherhood initiatives. Data here cover health systems, disease prevention, reproductive health, nutrition, and population dynamics. Data are from the United Nations Population Division, World Health Organization, United Nations Children's Fund, the Joint United Nations Programme on HIV/AIDS, and various other sources.

Overview of population by regions with percentage distribution for the year 2023 andoverview of gross domestic product (GDP) by regions with percentage distribution for the year 2023 with percentage distribution average and range.

Abstract

The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.

Geographic coverage

National coverage

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The universe of inference includes all formal (i.e., registered) private sector businesses (with at least 1% private ownership) and with at least five employees. In terms of sectoral criteria, all manufacturing businesses (ISIC Rev 4. codes 10-33) are eligible; for services businesses, those corresponding to the ISIC Rev 4 codes 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95 are included in the Enterprise Surveys. Cooperatives and collectives are excluded from the Enterprise Surveys. All eligible establishments must be registered with the registration agency. In the case of Rwanda, registration was from the Rwanda Revenue Authority (RRA).

Kind of data

Sample survey data [ssd]

Sampling procedure

The WBES use stratified random sampling, where the population of establishments is first separated into non-overlapping groups, called strata, and then respondents are selected through simple random sampling from each stratum. The detailed methodology is provided in the Sampling Note (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note-Consolidated-2-16-22.pdf). Stratified random sampling has several advantages over simple random sampling. In particular, it:

• produces unbiased estimates of the whole population or universe of inference, as well as at the levels of stratification
• ensures representativeness by including observations in all of those categories
• produces more precise estimates for a given sample size or budget allocation, and
• may reduce implementation costs by splitting the population into convenient subdivisions.

The WBES typically use three levels of stratification: industry classification, establishment size, and subnational region (used in combination). Starting in 2022, the WBES bases the industry classification on ISIC Rev. 4 (with earlier surveys using ISIC Rev. 3.1). For regional coverage within a country, the WBES has national coverage.

Note: Refer to Sampling Structure section in "The Rwanda 2023 World Bank Enterprise Survey Implementation Report" for detailed methodology on sampling.

Mode of data collection

Face-to-face [f2f]

Research instrument

The standard WBES questionnaire covers several topics regarding the business environment and business performance. These topics include general firm characteristics, infrastructure, sales and supplies, management practices, competition, innovation, capacity, land and permits, finance, business-government relations, exposure to bribery, labor, and performance. Information about the general structure of the questionnaire is available in the Enterprise Surveys Manual and Guide (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Enterprise-Surveys-Manual-and-Guide.pdf).

The questionnaire implemented in the Rwanda 2023 WBES included additional questions tailored for the Business Ready Report covering infrastructure, trade, government regulations, finance, labor, and other topics.

Response rate

Overall survey response rate was 51.7%.

Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 1.500 % in 2022. This records an increase from the previous number of 0.600 % for 2021. Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 1.300 % from Dec 2010 (Median) to 2022, with 13 observations. The data reached an all-time high of 1.500 % in 2022 and a record low of 0.500 % in 2020. Multidimensional Poverty Headcount Ratio: World Bank: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Germany Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 0.300 % in 2020. This stayed constant from the previous number of 0.300 % for 2019. Germany Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 0.200 % from Dec 2010 (Median) to 2020, with 10 observations. The data reached an all-time high of 0.300 % in 2020 and a record low of 0.100 % in 2015. Germany Multidimensional Poverty Headcount Ratio: World Bank: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).