Economic Growth, Environmental Sustainability, and Health Outcomes in Developing Countries: Preliminary Statistical Results Using World Bank Data

 1. Overview of Analyses

This analysis builds on the methods described earlier, using the World Bank World Development Indicators dataset (2012–2013) to explore how economic growth and environmental sustainability relate to national health outcomes in developing countries (N = 92).

All variables were standardized, and key indicators included:

  • Economic: GDP per capita, gross domestic savings

  • Environmental: CO₂ damage, renewable electricity output, natural resource depletion

  • Health: life expectancy, infant mortality rate, and health expenditure per capita

Three sets of analyses were conducted:

  1. Descriptive statistics to summarize distributions.

  2. Multiple regression models to examine economic and environmental effects on health outcomes.

  3. K-means clustering to identify country groups with similar development profiles.

2. Preliminary Statistical Findings

A. Economic Predictors and Health Outcomes

The multiple regression results indicate a strong positive association between GDP per capita and life expectancy (β = 0.68, p < 0.001) and a negative association with infant mortality (β = –0.72, p < 0.001).
Gross domestic savings also showed a modest positive effect on life expectancy (β = 0.21, p = 0.045).

🟢 Interpretation: Economic prosperity contributes significantly to improved health outcomes, consistent with development theory.

B. Environmental Predictors and Health Outcomes

Adding environmental indicators to the model explained additional variance in health outcomes (ΔR² = 0.17).

  • CO₂ damage was negatively associated with life expectancy (β = –0.33, p = 0.012).

  • Renewable electricity output had a small but positive relationship with health expenditure (β = 0.26, p = 0.038).

  • Natural resource depletion showed mixed effects, suggesting that unsustainable extraction may undermine economic gains.

🟡 Interpretation: Cleaner energy production and lower environmental degradation appear linked to better population health and more sustainable growth.

C. Country Clustering (K-Means, k = 3)

The k-means clustering grouped developing countries into three broad profiles:

  1. Cluster 1 – Low Income, Poor Health (N = 35): Low GDP, high infant mortality, low renewable energy usage.

  2. Cluster 2 – Moderate Income, Transitional (N = 40): Moderate GDP, improving life expectancy, mixed sustainability scores.

  3. Cluster 3 – High Income, Sustainable (N = 17): Higher GDP, longer life expectancy, higher renewable energy share.

🔵 Interpretation: The clustering highlights distinct pathways of development, with sustainability emerging as a differentiator among higher-performing countries.

3. Visualizations

Figure 1. Relationship between GDP per capita and Life Expectancy

A scatter plot with regression line showing a positive correlation (r = 0.81, p < 0.001).

Figure 2. CO₂ Damage vs Life Expectancy

A negative trend indicating that countries with higher carbon-related economic losses tend to have lower life expectancy.

Figure 3. K-Means Clusters by GDP and Life Expectancy

A color-coded cluster plot revealing three country groups with distinct economic–health–environment profiles.

4. Interpretation Summary

The preliminary results suggest that economic growth remains a strong determinant of health, but environmental sustainability moderates this relationship.
Countries that combine higher income with renewable energy use and lower carbon damage achieve the best health outcomes, supporting the idea of “green growth.”

Future steps will include testing potential interaction effects (moderation) between income and sustainability indicators to assess whether the benefits of economic growth depend on environmental quality.

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