Correlation between rural comprehensive development level and income type, per capita GDP, HDI, and urbanization rate.

UNDP first published the Human Development Report in 1990 in collaboration with economist Mehboob Haque, who is credited as the promoter of the HDI Index. The most important aspects of the HDI Index are longevity, healthy living, educational attainment, and quality of life as well as other important factors such as political independence, human rights, and self-respect. UNDP's Human Development Report is a combination of three principles. That is.
1) Life expectancy at birth.
2) Level of education. (Rate of adult education, rate of primary, secondary, higher education)
3) The standard of living. (GDP per capita based on USD)
The HDI index is averaged based on the maximum and minimum values of these three elements. According to the report, India was ranked 126th in the HDI Index in 2006. In 2008, Maxine Olson, UNDP Representative in India, and Motek Singh Ahluwalia, Deputy Chairman of the Planning Commission, published the Human Development Report in Delhi, in which India was ranked 128th (Value 0.619). Compared to 2006, India has slipped two places.

This dataset enables studying the relationship between a country's economic and social factors — such as GDP per capita, government health expenditure, Human Development Index (HDI), World Happiness Index, and density of doctors per population — with several key health indicators, like alcohol consumption, life expectancy, child mortality, non-communicable disease mortality, obesity prevalence, and undernourishment rates. It covers 50 countries from 2002 to 2021.A dashboard is also provided to facilitate the study, including plots for comparison of any selected variables for any of the available years, countries and geographic regions.

This dataset and dashboard has been created as part of a data management project for university IQS, Ramon Llull.

This project aims to explore the relationship between the social conditions of different countries and the prevalence of mental disorders. By integrating multiple datasets, including mental health statistics, economic indicators, and demographic variables, we analyzed patterns and potential correlations to gain valuable insights.

To facilitate this analysis, we developed an interactive dashboard featuring various visualizations that compare different variables. The final dataset includes:

• Demographic & Geographic Data: Country ISO code, country name, age range, sex, rural population percentage.
• Health Indicators: AVD for mental disorders, suicide mortality rate (2019), life expectancy at birth.
• Economic & Social Indicators: HDI value, rank and classification, GDP, GDP per capita (PPP, constant 2021 dollars) and GDP classification, Gini Index (classified as high/not high), unemployment rate (ILO estimate, 2021).

By combining these diverse data sources, the project provides a comprehensive understanding of how social and economic conditions influence mental health outcomes globally.

This work was developed as part of a course in our degree program.