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.

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.

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.

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 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).

Aims: Socioeconomic and environmental factors influence childhood asthma prevalence across the world. In-depth epidemiological research is necessary to determine the association between asthma prevalence and socio-environmental conditions, and to develop public health strategies to protect the asthmatic children against the environmental precipitators. Our research was based on aggregative data and sought to compare the asthma prevalence between children of two different age-groups across the world and to identify the association among the key socio-environmental conditions with increased childhood asthma prevalence.Method: We included forty countries with available data on various socio-environmental conditions (2014–2015). Childhood asthma prevalence of two different age groups (6–7 and 13–14 years) were obtained from global asthma report 2014. Because of significant diversities, the selected countries were divided into two groups based on human developmental index (HDI), a well-recognized parameter to estimate the overall socioeconomic status of a country. Robust linear regression was conducted using childhood asthma prevalence as the dependent variable and female smoking prevalence, tertiary school enrollment (TSE), PM10 (particulate matter ≤10 μm in diameter) and gross domestic product (GDP) as predictors.Results: Asthma prevalence was not different between two age groups. Among all predictors, only female smoking prevalence (reflecting maternal smoking) was associated with asthma prevalence in the countries with lower socio-economic conditions (HDI), but not in the higher HDI group. The results were unchanged even after randomization.Conclusions: Childhood asthma prevalence did not change significantly with age. Female smoking may have a positive correlation with childhood asthma prevalence in lower HDI countries.

High Density Interconnect (HDI) PCB Market Outlook

The global High Density Interconnect (HDI) PCB market size was valued at approximately USD 12.5 billion in 2023, and it is projected to reach around USD 24.7 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 7.8% during the forecast period. The increasing demand for miniaturized and high-performance electronic devices is a significant growth factor driving this market. As technology advances, the need for compact and efficient electronic components propels the adoption of HDI PCBs across various industries.

The growth factors for the HDI PCB market are multifaceted. One of the primary drivers is the expanding consumer electronics industry. The ever-growing consumer appetite for smaller, more powerful, and multifunctional electronic devices like smartphones, tablets, and wearable technology has significantly bolstered the demand for HDI PCBs. These PCBs are essential for integrating more functionalities into smaller form factors, thus making them indispensable for modern consumer electronics. Additionally, the rise of 5G technology is fueling demand for advanced telecommunications infrastructure, further accelerating the market.

Another substantial growth factor is the automotive industry's transition towards electric vehicles (EVs) and autonomous driving technologies. HDI PCBs are crucial for the advanced electronic systems used in modern vehicles, including infotainment systems, navigation devices, and essential safety components. As the automotive industry continues to evolve, the demand for reliable, high-performance HDI PCBs will likely see significant growth. Furthermore, stringent governmental regulations on vehicle safety and environmental standards are driving automakers to adopt advanced electronic systems, further boosting the HDI PCB market.

The industrial electronics sector also presents a robust growth avenue for the HDI PCB market. With the ongoing trend of Industry 4.0 and increasing automation across various manufacturing processes, the need for sophisticated electronics has never been higher. HDI PCBs enable the development of compact, reliable, and high-performance industrial equipment. This is particularly vital in applications requiring precise control and high data throughput, such as robotics, automated assembly lines, and sensor networks.

Looking at the regional outlook, Asia Pacific stands out as the dominant region in the HDI PCB market. Countries like China, Japan, South Korea, and Taiwan are major hubs for electronics manufacturing, and the presence of key players in these countries significantly contributes to the market's growth. North America and Europe are also substantial markets due to the high demand for advanced electronic devices and automotive technologies. These regions are expected to witness steady growth, driven by technological advancements and high consumer spending power. Lastly, the Middle East & Africa and Latin America are emerging markets with increasing investments in electronics manufacturing and telecommunications infrastructure, promising future growth.

Product Type Analysis

The HDI PCB market is segmented by product type into 4-6 Layers HDI, 8-10 Layers HDI, and 10+ Layers HDI. The 4-6 Layers HDI segment is one of the most popular due to its balance of performance and cost-effectiveness. These PCBs are commonly used in consumer electronics, where cost efficiency is a critical factor. The ability to incorporate multiple functionalities while maintaining a lower production cost makes this segment highly attractive for manufacturers aiming to produce budget-conscious electronic devices.

Moving up the complexity ladder, the 8-10 Layers HDI segment is tailored for applications requiring higher performance and reliability. This segment is particularly significant in industrial electronics and the automotive sector. The additional layers allow for more intricate circuit designs, which are essential for high-performance applications. As industries increasingly adopt automation and smart technologies, the demand for 8-10 Layers HDI PCBs is expected to rise, driven by their capability to handle complex processes and data-intensive operations.

The 10+ Layers HDI segment represents the pinnacle of advanced PCB technology. These PCBs are used in highly sophisticated applications such as advanced telecommunications equipment, aerospace, and defense systems. The need for high-speed data processing, superior reliability, and robust performance in harsh environments makes 10+ Layers HDI PCBs indispensable

🌍 Global Happiness, Wellbeing & Development Indicators (2002–2024)

Integrated OWID datasets on happiness, GDP, governance, corruption, freedom, HDI, and life expectancy.

⭐ Overview

This dataset is a curated integration of multiple global indicators related to happiness, wellbeing, governance, corruption, freedom, gender rights, economic prosperity, and demographic development. All files are sourced from Our World in Data (OWID) and represent harmonized, research-grade metrics used by economists, policy analysts, academics, and data professionals around the world.

The goal of this dataset is to provide a single, easy-to-use resource for exploring the key factors that influence national wellbeing and quality of life across more than 170 countries from 2002 to 2024.

⭐ What’s Included

This dataset brings together multiple dimensions of global wellbeing:

- Happiness & Life Satisfaction - Cantril Ladder (0–10 life evaluation) - Share of people reporting happiness - Time-series emotional wellbeing indicators

- Economic Indicators - GDP per capita (PPP, constant 2021$) - Historical population estimates

- Governance & Institutional Quality - Corruption Perception Index (CPI) - Freedom House civil & political liberties - Women’s civil rights index

- Human Development & Health - Augmented Human Development Index (AHDI) - Life expectancy at birth

Each file has been kept exactly as published by OWID, with no modification of values, ensuring full transparency and reproducibility.

⭐ Why This Dataset Matters

Understanding what drives national wellbeing is a central question in modern economics, social science, and development policy. This dataset enables powerful analysis such as:

• Which countries achieve high happiness at lower income levels?
• Does economic growth lead to improvements in wellbeing?
• How do corruption, freedom, and gender rights influence happiness?
• Which regions show consistent improvement in human development?
• How do life expectancy and governance interact with wellbeing trends?

This collection is ideal for:

• Exploratory Data Analysis (EDA)
• Cross-country comparisons
• Regression modelling & causal inference
• Time-series and panel-data analytics
• Dashboard development
• Machine learning experiments
• Academic and applied research

⭐ Data Source

All datasets are published by Our World in Data (OWID), using original data from:

• Gallup World Poll
• World Bank
• Transparency International
• UN Population Division
• V-Dem Institute
• Freedom House
• International survey archives

Licensed under Creative Commons BY 4.0.

⭐ Temporal & Geospatial Coverage

• Years: 2002–2024
• Countries: 170+
• Regions: All OWID regions (Africa, Asia, Americas, Europe, Oceania)

⭐ Intended Audience

• Data Analysts
• Data Scientists
• Policy Researchers
• Social Scientists
• Students & educators
• Kaggle learners
• Anyone interested in global wellbeing

⭐ Summary

This dataset provides a comprehensive, ready-to-use foundation for studying global happiness, development, and governance. Whether you’re building visualizations, statistical models, dashboards, or research papers, this single dataset gives you everything you need to explore what shapes human wellbeing around the world.

The data collected aim to test whether English proficiency levels in a country are positively associated with higher democratic values in that country. English proficiency is sourced from statistics by Education First’s "EF English Proficiency Index" which covers countries' scores for the calendar year 2022 and 2021. The EF English Proficiency Index ranks 111 countries in five different categories based on their English proficiency scores that were calculated from the test results of 2.1 million adults. While democratic values are operationalized through the liberal democracy index from the V-Dem Institute annual report for 2022 and 2021. Additionally, the data is utilized to test whether English language media consumption acts as a mediating variable between English proficiency and democracy levels in a country, while also looking at other possible regression variables. In order to conduct the linear regression analyses for the dats, the software that was utilized for this research was Microsoft Excel.The raw data set consists of 90 nation states in two years from 2022 and 2021. The raw data is utilized for two separate data sets the first of which is democracy indicators which has the regression variables of EPI, HDI, and GDP. For this table set there is a total of 360 data entries. HDI scores are a statistical summary measure that is developed by the United Nations Development Programme (UNDP) which measures the levels of human development in 190 countries. The data for nominal gross domestic product scores (GDP) are sourced from the World Bank. Having strong regression variables that have been proven to have a positive link with democracy in the data analysis such as GDP and HDI, would allow the regression analysis to identify whether there is a true relationship between English proficiency and democracy levels in a country. While the second data set has a total of 720 data entries and aims to identify English proficiency indicators the data set has 7 various regression variables which include, LDI scores, Years of Mandatory English Education, Heads of States Publicly speaking English, GDP PPP (2021USD), Common Wealth, BBC web traffic and CNN web traffic. The data for years of mandatory English education is sourced from research at the University of Winnipeg and is coded in the data set based on the number of years a country has English as a mandatory subject. The range of this data is from 0 to 13 years of English being mandatory. It is important to note that this data only concerns public schools and does not extend to the private school systems in each country. The data for heads of state publicly speaking English was done through a video data analysis of all heads of state. The data was only used for heads of state who had been in their position for at least a year to ensure the accuracy of the data collected; with a year in power, for heads of state that had not been in their position for a year, data was taken from the previous head of state. This data only takes into account speeches and interviews that were conducted during their incumbency. The data for each country’s GDP PPP scores are sourced from the World Bank, which was last updated for a majority of the countries in 2021 and is tied to the US dollar. Data for the commonwealth will only include members of the commonwealth that have been historically colonized by the United Kingdom. Any country that falls under that category will be coded as 1 and any country that does not will be coded as 0. For BBC and CNN web traffic that data is sourced by using tools in Semrush which provide a rough estimate of how much web traffic each news site generates in each country. Which will be utilized to identify the average number of web traffic for BBC News and CNN World News for both the 2021 and 2022 calendar. The traffic for each country will also be measured per capita, per 10 thousand people to ensure that the population density of a country does not influence the results. The population of each country for both 2021 and 2022 is sourced from the United Nations revision of World Population Prospects of both 2021 and 2022 respectively.

In 2023, Ukraine and Qatar topped the Gender Development Index (GDI) with index scores over ****. On the other hand, Yemen reported the lowest index, with only ****. The higher the value, the smaller the gap between women and men. The Gender Development Index (GDI) is basically a ratio of Human Development Index calculated separately for women and men.

In 2024, Sudan was ranked as the most miserable country in the world, with a misery index score of 374.8. Argentina ranked second with an index score of 195.9. Quality of life around the worldThe misery index was created by the economist Arthur Okun in the 1960s. The index is calculated by adding the unemployment rate, the lending rate and the inflation rate minus percent change of GDP per capita. Another famous tool used for the comparison of development of countries around the world is the Human Development Index, which takes into account such factors as life expectancy at birth, literacy rate, education level and gross national income (GNI) per capita. Better economic conditions correlate with higher quality of life Economic conditions affect the life expectancy, which is much higher in the wealthiest regions. With a life expectancy of 85 years, Liechtenstein led the ranking of countries with the highest life expectancy in 2023. On the other hand, Nigeria was the country with the lowest life expectancy, where men were expected to live 55 years as of 2024. The Global Liveability Index ranks the quality of life in cities around the world, basing on political, social, economic and environmental aspects, such as personal safety and health, education and transport services and other public services. In 2024, Vienna was ranked as the city with the highest quality of life worldwide.

In 2025, Luxembourg was the country with the highest gross domestic product per capita in the world. Of the 20 listed countries, 13 are in Europe and five are in Asia, alongside the U.S. and Australia. There are no African or Latin American countries among the top 20. Correlation with high living standards While GDP is a useful indicator for measuring the size or strength of an economy, GDP per capita is much more reflective of living standards. For example, when compared to life expectancy or indices such as the Human Development Index or the World Happiness Report, there is a strong overlap - 14 of the 20 countries on this list are also ranked among the 20 happiest countries in 2024, and all 20 have "very high" HDIs. Misleading metrics? GDP per capita figures, however, can be misleading, and to paint a fuller picture of a country's living standards then one must look at multiple metrics. GDP per capita figures can be skewed by inequalities in wealth distribution, and in countries such as those in the Middle East, a relatively large share of the population lives in poverty while a smaller number live affluent lifestyles.

The statistic depicts the literacy rate in Mexico from 2008 to 2020. The literacy rate measures the percentage of people ages 15 and above who can read and write. In 2020, Mexico's literacy rate was around 95.25 percent. The source does not provide data for 2019.Education in MexicoThe literacy rate is commonly defined as the share of people in a country who are older than 15 years and are able to read and write. In Mexico, a state with more than 115 million inhabitants, the literacy rate is above 90 percent, making it significantly higher than the global average. More than 70 percent of Mexico’s population is older than 15 years, a figure than has been quite consistent over the last ten years. Mexico’s compulsory education comprises grades 1 to 9, with an optional secondary education up to grade 12. Literacy is considered basic education. The lowest literacy rates can be found in African countries, the highest in Europe. Additionally, the literacy rate is one of the factors that determines a country’s ranking on the Human Development Index of the United Nations, which ranks the overall well-being of a country’s population. Apart from literacy, it also includes factors such as per-capita income, health and life expectancy and others. Mexico is currently not among the countries with the highest Human Development Index value.