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Economic Health

Economic Health of Nations

How do health expenditure, income classification, inequality, and infrastructure shape life expectancy and mortality? Explore the Preston curve, income group comparisons, radar profiles, and sortable economic indicators for 200+ countries.

The Preston Curve: Health Expenditure vs Life Expectancy
Each dot is a country, coloured by World Bank income group. Dashed line = log-linear best fit.
Life Expectancy & Death Rate by Income Group
Average life expectancy (bars) and crude death rate proxy (line) by World Bank income classification
Inequality & Longevity: Gini Index vs Life Expectancy
Countries with available Gini data, coloured by region.
Infrastructure Radar Comparison
Compare two countries on water, sanitation, electricity, and internet access (% coverage)
Economic Indicators Table
Sortable table of key economic and health metrics. Click column headers to sort.
Country Income Group GNI/Capita Health Exp. Inflation % Poverty % Unemp. % Life Exp.

Economic Determinants of Health

How national wealth, spending, and infrastructure shape mortality

The relationship between economic development and health outcomes is one of the most studied topics in global health. The Preston Curve demonstrates that life expectancy rises steeply with national income at lower levels of development but flattens at higher income levels. This page extends that analysis to health expenditure per capita, income inequality, and infrastructure indicators to reveal the multiple economic pathways that shape mortality patterns worldwide.

Health Spending: How Much Is Enough?

The diminishing returns of healthcare investment at scale

Health expenditure per capita follows a similar curve to GDP: the first few hundred dollars spent on health systems produce dramatic mortality reductions through basic interventions like vaccination, safe childbirth, and antibiotic access. The United States spends over $12,000 per person annually on healthcare — roughly double the OECD average — yet achieves worse life expectancy than countries spending half as much. This paradox illustrates that spending efficiency, equitable access, and public health priorities matter at least as much as total expenditure. Countries like Thailand and Costa Rica demonstrate that well-designed universal health systems can deliver excellent outcomes at modest cost.

Income inequality, measured by the Gini index, adds another dimension. The Wilkinson Hypothesis proposes that societies with greater inequality experience worse health outcomes across all income strata — not just among the poorest — through chronic psychosocial stress, weaker social safety nets, and underinvestment in public goods. Infrastructure indicators like clean water access, sanitation coverage, electricity, and internet penetration represent the foundational determinants that underlie all other health gains. The radar chart on this page enables direct comparison between any two countries across these dimensions.

Frequently Asked Questions
What is the Preston curve?

The Preston curve describes the empirical relationship between national income (or health expenditure) and life expectancy. It shows steep gains in life expectancy at lower income levels that flatten at higher incomes, suggesting diminishing health returns to wealth beyond a certain threshold.

How does income inequality affect life expectancy?

Countries with higher Gini coefficients (greater inequality) tend to have lower life expectancies, even after controlling for average income. The Wilkinson hypothesis suggests that inequality creates psychosocial stress and undermines social cohesion, though the causal mechanisms remain debated among researchers.

Why do some low-income countries have high life expectancy?

Countries like Costa Rica, Cuba, and Sri Lanka outperform their income peers on life expectancy through strong primary healthcare systems, high vaccination coverage, and effective public health programmes. This demonstrates that targeted health investment can partially compensate for lower national income.

What infrastructure metrics relate to health outcomes?

Access to clean water, sanitation, electricity, and internet connectivity are strongly associated with better health outcomes. These infrastructure indicators enable disease prevention, health education, cold-chain vaccine storage, and access to telemedicine — all of which reduce mortality.

Why does the US spend more on healthcare but have lower life expectancy than peers?

The US healthcare system is characterised by high administrative costs, fragmented coverage, and a fee-for-service model that incentivises treatment over prevention. Additionally, high income inequality, elevated rates of gun violence, drug overdose, and obesity contribute to worse outcomes. Countries with universal health systems achieve better population-level results at lower per-capita cost.

How does poverty directly cause higher mortality?

Poverty affects mortality through multiple pathways: reduced access to healthcare and medicines, inadequate nutrition, exposure to environmental hazards (unsafe water, indoor air pollution), dangerous working conditions, and chronic psychosocial stress. In low-income countries, extreme poverty is the single strongest predictor of child mortality, primarily through infectious disease and malnutrition.

What does the radar chart compare between countries?

The radar chart compares two countries across key infrastructure dimensions: clean water access, basic sanitation, electricity coverage, internet penetration, and health expenditure. Each axis is normalised to show the percentage of maximum, making it easy to identify which dimensions drive the gap between countries. Large differences in water and sanitation access often explain much of the mortality disparity between high- and low-income nations.