50+ Variable Correlation Engine
Plot any two variables against each other across 204 countries. Explore relationships between health, wealth, lifestyle, diet, environment, and happiness with regression statistics, colour-coded regions, and pre-computed strongest correlations.
Ecological fallacy warning: These estimates are based on cross-country correlations and assume a causal relationship. Individual-level effects may differ significantly. This is for exploration only -- not medical or policy advice.
⚠️ Ecological analysis: These are cross-country (ecological) regressions, not individual-level. Results should NOT be interpreted as causal relationships. R² shows the variance explained by the model.
Mortality and Socioeconomic Correlations
What drives death rates? Explore the statistical relationships
The Correlation Explorer enables you to investigate statistical relationships between mortality rates and key socioeconomic indicators. By plotting cause-specific death rates against GDP per capita, Gini inequality, and income classification, you can explore the macro-level factors associated with national mortality patterns.
Each scatter plot positions 204 countries as data points, colour-coded by World Bank income group or world region. Hover over any country to see its exact values. This tool is useful for researchers, students, and analysts seeking to understand the broader determinants of health at the population level.
What correlations can I explore?
The Correlation Explorer lets you plot mortality rates against socioeconomic variables including GDP per capita, Gini inequality index, and World Bank income classification. You can examine relationships for total mortality or specific causes of death across 204 countries.
Does correlation mean causation in mortality data?
No. The correlations shown are observational associations, not causal relationships. For example, higher GDP is associated with lower death rates, but many confounding factors (healthcare investment, education, sanitation) drive this relationship. The tool is designed for exploratory analysis, not causal inference.
What is the Gini index and how does it relate to mortality?
The Gini index measures income inequality on a scale from 0 (perfect equality) to 1 (maximum inequality). Research suggests that higher inequality is associated with worse health outcomes, including higher mortality rates, though the relationship is complex and debated among economists and epidemiologists.