******* had the highest level of the Human Development Index (HDI) worldwide in 2023 with a value of *****. With a score of ****, ****** followed closely behind *********** and had the second-highest level of human development in that year. The rise of the Asian tigers In the decades after the Cold War, the four so-called Asian tigers, South Korea, Singapore, Taiwan, and Hong Kong (now a Special Administrative Region of China) experienced rapid economic growth and increasing human development. At number eight and number 13 of the HDI, respectively, *********************** are the only Asian locations within the top-15 highest HDI scores. Both locations have experienced tremendous economic growth since the 1980’s and 1990’s. In 1980, the per capita GDP of Hong Kong was ***** U.S. dollars, increasing throughout the decades until reaching ****** in 2023, which is expected to continue to increase in the future. Meanwhile, in 1989, Singapore had a GDP of nearly ** billion U.S. dollars, which has risen to nearly *** billion U.S. dollars today and is also expected to keep increasing. Growth of the UAE The United Arab Emirates (UAE) is the only Middle Eastern country besides Israel within the highest ranking HDI scores globally. Within the Middle East and North Africa (MENA) region, the UAE has the third-largest GDP behind Saudi Arabia and Israel, reaching nearly *** billion U.S. dollars by 2022. Per capita, the UAE GDP was around ****** U.S. dollars in 1989, and has nearly doubled to ****** U.S. dollars by 2021. Moreover, this is expected to reach over ****** U.S. dollars by 2029. On top of being a major oil producer, the UAE has become a hub for finance and business and attracts millions of tourists annually.

The average for 2023 based on 184 countries was 0.744 points. The highest value was in Iceland: 0.972 points and the lowest value was in South Africa: 0.388 points. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.

Compared to other African countries, Seychelles scored the highest in the Human Development Index (HDI) in 2022. The country also ranked 67th globally, as one of the countries with a very high human development. This was followed by Mauritius, Libya, Egypt, and Tunisia, with scores ranging from 0.80 to 0.73 points. On the other hand, Central African Republic, South Sudan, and Somalia were among the countries in the region with the lowest index scores, indicating a low level of human development.

In 2025, Hong Kong had the highest Human Development Index (HDI) in the Asia-Pacific region, with a score of ****. In contrast, Pakistan's HDI score was roughly **** in the same year. HDI provides a human-centered overview of development based on an individual's longevity and wellness, knowledge, and decent living standards.

The average for 2023 based on 20 countries was 0.77 points. The highest value was in Canada: 0.939 points and the lowest value was in Haiti: 0.554 points. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.

Iceland had the highest level of the Human Development Index (HDI) worldwide in 2023 after adjusting for inequality, with a value of ****. Its Nordic neighbors Norway and Denmark followed behind. Meanwhile, Iceland also topped the HDI not adjusted for inequality.

The average for 2023 based on 27 countries was 0.915 points. The highest value was in Denmark: 0.962 points and the lowest value was in Bulgaria: 0.845 points. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.

South Sudan and Somalia had the ****** levels of human development based on the Human Development Index (HDI). Many of the countries at the bottom of the list are located in Sub-Saharan Africa, underlining the prevalence of poverty and low levels of education in the region. Meanwhile, Switzerland had the ******* HDI worldwide.

Human Development Index by country for 2013. This is a filtered layer based on the "Human Development Index by country, 1980-2010 time-series" layer.The Human Development Index measures achievement in 3 areas of human development: long life, good education and income. Specifically, the index is computed using life expectancy at birth, Mean years of schooling, expected years of schooling, and gross national income (GNI) per capita (PPP $).The United Nations categorizes the HDI values into 4 groups. In 2013 these groups were defined by the following HDI values:

Very High Human Development: 0.736 and higher High Human Development: 0.615 to 0.735 Medium Human Development: 0.494 to 0.614 Low Human Development: 0.493 and lower

Country shapes from Natural Earth 50M scale data. Human Development Index attributes are from The World Bank: HDRO calculations based on data from UNDESA (2013a), Barro and Lee (2013), UNESCO Institute for Statistics (2013), UN Statistics Division (2014), World Bank (2014) and IMF (2014).

The average for 2023 based on 12 countries was 0.787 points. The highest value was in Chile: 0.878 points and the lowest value was in Venezuela: 0.709 points. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.

Context

The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions. The health dimension is assessed by life expectancy at birth, the education dimension is measured by mean of years of schooling for adults aged 25 years and more and expected years of schooling for children of school entering age. The standard of living dimension is measured by gross national income per capita. The HDI uses the logarithm of income, to reflect the diminishing importance of income with increasing GNI. The scores for the three HDI dimension indices are then aggregated into a composite index using geometric mean. Refer to Technical notes for more details. The HDI can be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The HDI simplifies and captures only part of what human development entails. It does not reflect on inequalities, poverty, human security, empowerment, etc. The HDRO provides other composite indices as a broader proxy on some of the key issues of human development, inequality, gender disparity, and poverty. A fuller picture of a country's level of human development requires analysis of other indicators and information presented in the HDR statistical annex.

Content

In this Dataset, we have Global, regional, and country/territory-level data on key dimensions of human development with various composite indices. The human development composite indices have been developed to capture broader dimensions of human development, identify groups falling behind in human progress and monitor the distribution of human development. In addition to the HDI, the indices include Multidimensional Poverty Index (MPI), Inequality-adjusted Human Development Index (IHDI), Gender Inequality Index (GII), Gender Development Index (GDI), Planetary pressures-adjusted HDI (PHDI) and Gender Social Norms Index (GSNI).

Dataset Glossary (Alphabetical Order)

• Adolescent Birth Rate - Births per 1000 Women Ages 15 to 19
• Carbon Dioxide Emissions per Capita Production in Tonnes
• Coefficient of Human Inequality
• Expected Years of Schooling - Female
• Expected Years of Schooling - Male
• Expected Years of Schooling
• Gender Development Index
• Gender Inequality Index
• Gross National Income Per Capita - Female
• Gross National Income Per Capita - Male
• Gross National Income Per Capita
• HDI Female
• HDI Male
• Human Development Index
• Inequality Adjusted Human Development Index
• Inequality in Education
• Inequality in Income
• Inequality in Life Expectancy
• Labour Force Participation Rate - Female Percentage Ages 15 and Older
• Labour Force Participation Rate - Male Percentage Ages 15 and Older
• Life Expectancy at Birth - Female
• Life Expectancy at Birth - Male
• Life Expectancy at Birth
• Material Footprint per Capita in Tonnes
• Maternal Mortality Ratio - Deaths per 100000 Live Births
• Mean Years of Schooling - Female
• Mean Years of Schooling - Male
• Mean Years of Schooling
• Planetary Pressures Adjusted Human Development Index

Cover Photo by: pch.vector on Freepik

The Human development index (HDI) for European countries in 2023 shows that although all the countries in this statistic have scores which imply high levels of development, Iceland score of ***** was the highest in this year. The HDI is a statistic that combines life-expectancy, education levels and GDP per capita. Countries with scores over ***** are considered to have very high levels of development, compared with countries that score lower.

The average for 2023 based on 52 countries was 0.585 points. The highest value was in the Seychelles: 0.848 points and the lowest value was in South Africa: 0.388 points. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.

The Human Development Index (HDI) of Germany has increased from ***** in 1990 to ***** by 2021, indicating that Germany has reached very high levels of human development. The HDI itself is a statistic that combines life-expectancy, education levels and GDP per capita. Countries with scores over ***** are considered to have very high levels of development, compared with countries that score lower. Germany's HDI score has increased from ***** in 1990 to ***** by 2019, implying that Germany has consistently had a very high level of human development.

This dataset provides a country–year panel for OECD countries covering the period 2010–2024. It combines annual data on public, private and total social expenditure as a share of GDP with the World Happiness Index (WHI) and the Human Development Index (HDI).The data are constructed to analyze the relationships between social spending, subjective well-being and human development in OECD countries. The panel structure (one observation per country per year) makes the dataset suitable for descriptive analysis as well as regression-based empirical research.ContentsThe main Excel file contains a single data sheet:Sheet: data_setEach row corresponds to a specific country–year observation for an OECD member state.Variables:Country: Country name (OECD member; e.g., “Australia”, “Türkiye”, “United States”).iso3: ISO 3166-1 alpha-3 country code (e.g., “AUS”, “TUR”, “USA”).year: Calendar year (2010–2024).pub_socexp_gdp: Public social expenditure as a percentage of GDP (%).priv_socexp_gdp: Private (mandatory and voluntary) social expenditure as a percentage of GDP (%).tot_socexp_gdp: Total social expenditure (public + private) as a percentage of GDP (%).WHI: World Happiness Index; average national happiness score on a 0–10 scale based on the Cantril ladder question.HDI: Human Development Index; composite index of three basic dimensions of human development (health, education, and standard of living).income_group: Binary country income group indicator used in the analysis. High‑income OECD countries are coded as 1 (“High”), and all other OECD members (upper‑middle, lower‑middle and low income) are coded as 0 (“NonHigh”). Income groups were constructed using data from the OECD Data Explorer (2024) and the World Bank country income classification for 2024, based on PPP (purchasing power parity) income thresholds.Empty cells indicate that data for the corresponding country–year observation are not available in the original sources or were not included in the analytical sample due to missingness.Data sourcesSocial expenditure (pub_socexp_gdp, priv_socexp_gdp, tot_socexp_gdp)Data are taken from the OECD Social Expenditure Database (SOCX). SOCX provides reliable and internationally comparable statistics on public and mandatory and voluntary private social expenditure at the program level for 38 OECD countries (and some accession countries), with coverage from 1980 and estimates for more recent years.Reference: OECD Social Expenditure Database (SOCX), https://www.oecd.org/en/data/datasets/social-expenditure-database-socx.html.World Happiness Index (WHI)Happiness data are drawn from the World Happiness Report, accessed via HumanProgress.org (World Happiness Report section). The index is based on average national values for answers to the Cantril ladder question, which asks respondents to evaluate their current life on a 0–10 scale, with the worst possible life as 0 and the best possible life as 10.Reference: World Happiness Report; HumanProgress.org, https://humanprogress.org.Human Development Index (HDI)HDI data are drawn from the Human Development Index series compiled by the United Nations Development Programme (UNDP), accessed via HumanProgress.org (Human Development Index section). The HDI measures three basic dimensions of human development: life expectancy at birth; an education component (adult literacy rate and school enrollment); and GDP per capita (purchasing power parity, PPP, in U.S. dollars), combined into a composite index.Reference: United Nations Development Programme (UNDP), Human Development Reports; HumanProgress.org, https://humanprogress.org.Data construction and coverageThe dataset is restricted to OECD member countries and the years 2010–2024.WHI and HDI series are matched to OECD social expenditure data using ISO3 country codes and calendar years.In addition, a binary income group variable (income_group) was created to distinguish high‑income OECD countries from other OECD members, using the World Bank’s 2024 income thresholds (PPP‑based) and country information from the OECD Data Explorer (2024).Some country–year combinations, particularly in later years (e.g., 2022–2024), contain missing values where the original sources do not provide data or only provide partial estimates. These are retained as empty cells.The empirical analyses in the associated study are conducted on subsets of the data restricted to complete cases for the relevant variables.Researchers can use this dataset to replicate the results of the associated study or to conduct additional analyses on the links between social expenditure, happiness and human development within the OECD context.If you use this dataset, please cite both this data file and the original data providers (OECD, World Happiness Report, UNDP, and HumanProgress.org).

This dataset combines economic and development indicators from two key sources:

1. World Bank Economic Indicators (1960–2018) Covers various economic performance metrics for countries worldwide, including:

   • Electricity consumption
   • GDP per capita
   • Population statistics
   • Life expectancy
   • And many other key development indicators

2. United Nations Human Development Index (HDI) Data (1990–2021) Supplementary data tracking human development, environmental impact, and inequality through composite metrics such as:

   • HDI score (combining life expectancy, GDP per capita, education)
   • Inequality indices
   • Environmental measures

Potential Analyses

• Identify countries with the highest growth in population and GDP and analyze overlaps.
• Explore which regions have experienced the most significant HDI improvements in the 21st century.
• Analyze factors most strongly correlated with life expectancy.
• Differentiate economic and social indicators between “High Income” and “Low Income” countries.

Source

Data sourced from The World Bank and United Nations (UN). Licensed under Public Domain.

Global Socio-Economic & Environmental Indicators (1990-2021)

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Description: This comprehensive dataset provides a rich collection of socio-economic and environmental indicators for countries across the world. Spanning the years from 1990 to 2021, the dataset includes valuable information on Human Development Index (HDI), Life Expectancy, Gross National Income per Capita (GNI), and CO2 Production.

Key Columns: - ISO3: Three-letter country code (ISO 3166-1 alpha-3) - Country: Country name - hdicode: Identifier related to the Human Development Index (HDI) - region: Geographical region or grouping - hdi_rank_2021: HDI rank for the year 2021

Temporal Coverage: 1990 to 2021

Use Cases: - Analyze trends in HDI, life expectancy, GNI, and CO2 emissions over time. - Investigate the relationship between socio-economic development and environmental impact. - Conduct comparative studies between countries and regions. - Explore correlations and patterns in socio-economic indicators and HDI rankings.

This dataset offers a valuable resource for researchers, analysts, and policymakers interested in studying the dynamic interplay between socio-economic development and environmental factors on a global scale.

Time series data for the statistic Human development index (HDI) and country Sierra Leone. Indicator Definition:The Human Development Index (HDI) is a summary measure of human development. It measures the average achievements in a country in three basic dimensions of human development: a long and healthy life, access to knowledge and a decent standard of living. The HDI is the geometric mean of normalized indices measuring achievements in each dimension. The HDI is the geometric mean of the three dimension indices and embodies imperfect substitutability across all HDI dimensions. It thus addresses one of the most serious criticisms of the linear aggregation formula, which allowed for perfect substitution across dimensions. Some substitutability is inherent in the definition of any index that increases with the values of its components. Data sources: Life expectancy at birth: UNDESA; Mean years of schooling: Barro and Lee; Expected years of schooling: UNESCO Institute for Statistics; Gross national income (GNI) per capita: World Bank.The indicator "Human development index (HDI)" stands at 0.348 as of 12/31/2011, the highest value at least since 12/31/1990, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes an increase of 0.578 percent compared to the value the year prior.The 1 year change in percent is 0.578.The 3 year change in percent is 3.57.The 5 year change in percent is 7.74.The Serie's long term average value is 0.309. It's latest available value, on 12/31/2011, is 12.73 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2000, to it's latest available value, on 12/31/2011, is +42.62%.The Serie's change in percent from it's maximum value, on 12/31/2011, to it's latest available value, on 12/31/2011, is 0.0%.

Background and Aims: Despite known Indigenous health and socioeconomic disadvantage in countries with a Very High Human Development Index, data on the incidence of stroke in these populations are sparse. With oversight from an Indigenous Advisory Board, we will undertake a systematic review of the incidence of stroke in Indigenous populations of developed countries or regions, with comparisons between Indigenous and non-Indigenous populations of the same region, though not between different Indigenous populations.Methods: Using PubMed, OVID-EMBASE, and Global Health databases, we will examine population-based incidence studies of stroke in Indigenous adult populations of developed countries published 1990-current, without language restriction. Non-peer-reviewed sources, studies including <10 Indigenous People, or with insufficient data to determine incidence, will be excluded. Two reviewers will independently validate the search strategies, screen titles and abstracts, and record reasons for rejection. Relevant articles will undergo full-text screening, with standard data extracted for all studies included. Quality assessment will include Sudlow and Warlow's criteria for population-based stroke incidence studies, the Newcastle-Ottawa Scale for risk of bias, and the CONSIDER checklist for Indigenous research.Results: Primary outcomes include crude, age-specific and/or age-standardized incidence of stroke. Secondary outcomes include overall stroke rates, incidence rate ratio and case-fatality. Results will be synthesized in figures and tables, describing data sources, populations, methodology, and findings. Within-population meta-analysis will be performed if, and where, methodologically sound and comparable studies allow this.Conclusion: We will undertake the first systematic review assessing disparities in stroke incidence in Indigenous populations of developed countries. Data outputs will be disseminated to relevant Indigenous stakeholders to inform public health and policy research.

Breast cancer is a worldwide threat to female health with patient outcomes varying widely. The exact correlation between global outcomes of breast cancer and the national socioeconomic status is still undetermined. Mortality-to-incidence ratio (MIR) of breast cancer was calculated with the contemporary age standardized incidence and mortality rates for countries with data available at GLOBOCAN 2012 database. The MIR matched national human development indexes (HDIs) and health system attainments were respectively obtained from Human Development Report and World Health Report. Correlation analysis, regression analysis, and Tukey-Kramer post hoc test were used to explore the effects of HDI and health system attainment on breast cancer MIR. Our results demonstrated that breast cancer MIR was inversely correlated with national HDI (r = -.950; P < .001) and health system attainment (r = -.898; P < .001). Countries with very high HDI had significantly lower MIRs than those with high, medium and low HDI (P < .001). Liner regression model by ordinary least squares also indicated negative effects of both HDI (adjusted R2 = .903, standardize β = -.699, P < .001) and health system attainment (adjusted R2 =. 805, standardized β = -.009; P < .001), with greater effects in developing countries identified by quantile regression analysis. It is noteworthy that significant health care disparities exist among countries in accordance with the discrepancy of HDI. Policies should be made in less developed countries, which are more likely to obtain worse outcomes in female breast cancer, that in order to improve their comprehensive economic strength and optimize their health system performance.