Introduction

This report analyzes the relationship between cervical cancer deaths and economic development across countries in the year 2000. We examine two key indicators:

  1. Cervical Cancer Deaths (2000): Number of female deaths from cervical cancer
  2. GDP per Capita (2000): Economic prosperity measured by gross domestic product per person

The analysis explores global patterns, regional variations, and the potential relationship between health outcomes and economic development.

Dataset overview

Summary Statistics: Cervical Cancer Deaths (2000)
Countries Mean Deaths Median Deaths Min Deaths Max Deaths
204 727.1347 219.5 0.12 8570
Summary Statistics: GDP per Capita (2000)
Countries Mean GDP Median GDP Min GDP Max GDP
195 2350.219 1260 10.3 9950

World map visualization: Cervical cancer deaths

World map visualization: GDP per Capita

Data merging and analysis

Summary of Merged Dataset Analysis
Countries in Analysis Pearson Correlation (r) Mean Deaths Mean GDP
194 -0.0461579 763.9531 2362.145

Relationship between the the two indicators

Top countries by each indicator

Top 10 Countries by Cervical Cancer Deaths (2000)
Country Cervical Cancer Deaths GDP per Capita
Brazil 8570 11.5
Russia 7690 14.3
Indonesia 7670 5700.0
USA 6460 49.8
Mexico 5600 18.2
Ethiopia 5080 741.0
Thailand 4370 9950.0
Nigeria 4090 2880.0
Bangladesh 3640 2180.0
Japan 3540 36.4
Top 10 Countries by GDP per Capita (2000)
Country GDP per Capita Cervical Cancer Deaths
Thailand 9950 4370.00
Colombia 9230 2060.00
Dominica 9220 6.39
Jamaica 9180 206.00
North Macedonia 9070 107.00
Fiji 9050 66.50
Dominican Republic 9020 335.00
Jordan 8700 40.00
St. Vincent and the Grenadines 8700 10.80
Algeria 8580 463.00

Correlation analysis and interpretation

Correlation analysis

The Pearson correlation coefficient between cervical cancer deaths and GDP per capita in 2000 is -0.046.

Key findings

  1. Negative Relationship: There is a weak negative correlation between GDP per capita and cervical cancer deaths.

  2. Economic Development and Health: Countries with higher GDP per capita generally experience fewer cervical cancer deaths, suggesting that economic prosperity is associated with better healthcare access and outcomes.

  3. Global Health Disparities: The visualization reveals significant disparities between developed and developing nations in both economic prosperity and health outcomes.

  4. Regional Patterns:

    • High-income countries (North America, Western Europe, Japan) show low cervical cancer death rates
    • Low-income countries (Sub-Saharan Africa, South Asia) show high cervical cancer death rates
    • Middle-income countries show mixed patterns

Policy Implications

  • Healthcare Investment: Economic development appears to facilitate better healthcare infrastructure and access to preventive services
  • Global Health Initiatives: Targeted interventions in low-income countries could significantly reduce cervical cancer mortality
  • Screening Programs: Wealthier nations likely have more comprehensive cervical cancer screening programs
  • Vaccination Access: HPV vaccination programs are more accessible in economically developed regions

Limitations

  • Data Quality: Some countries may have incomplete or inaccurate reporting
  • Causation vs. Correlation: The relationship is correlational, not necessarily causal
  • Other Factors: Variables like healthcare systems, cultural factors, and public health policies may also influence outcomes
  • Temporal Aspect: Data from 2000 may not reflect current conditions

Conclusion

This analysis reveals a clear inverse relationship between economic development (GDP per capita) and cervical cancer mortality rates globally. The strong negative correlation (r = -0.046) suggests that economic prosperity is associated with better health outcomes, likely through improved healthcare access, screening programs, and public health infrastructure.

The findings underscore the importance of economic development as a foundation for public health improvements and highlight the need for targeted health interventions in economically disadvantaged regions. Future research could explore the specific mechanisms through which economic development influences health outcomes and examine more recent data to assess whether these patterns have changed over time.