Unveiling the Correlation: Does Having Many Healthcare Providers Really Extend Life Expectancy?

The complete analysis and all related work are documented in the following files:

• Analysis of Correlation between Life Expectancy vs Medical Professional Density.ipynb
• Presentation - Life Expectancy vs Medical Professional Density.pptx

1. Introduction

Background

Healthcare accessibility and quality are crucial in enhancing the well-being and longevity of populations. Existing research underscores the pivotal role of healthcare providers—such as medical doctors and pharmacists—in delivering timely and effective care. However, the direct correlation between the density of these providers and life expectancy is an area still ripe for exploration.

This project leverages data from the World Health Statistics 2020, covering healthcare provider distribution and life expectancy metrics from 1990 to 2019. The dataset includes information on the number of pharmacists and medical doctors per 10,000 population, along with healthy life expectancy at birth. Our analysis aims to uncover patterns and insights into how the density of healthcare providers influences life expectancy.

The outcomes of this study could inform policymakers and healthcare planners about the importance of investing in healthcare infrastructure and personnel, ultimately contributing to the optimization of healthcare resources to improve global life quality and longevity.

Objective & Research Questions

The primary aim of this project is to explore the correlation between the density of healthcare providers (pharmacists and medical doctors) and life expectancy. We seek to determine if a higher number of healthcare providers per capita correlates with increased life expectancy.

To address this, the project is structured around two main objectives and their respective questions:

Objective 1: Provide an overview of Life Expectancy by Gender and Continent for the years 2000, 2010, and 2015.

• Do females or males tend to have higher life expectancy?
• Which continent or country within each continent has the highest and lowest life expectancy?

Objective 2: Investigate the potential relationship between Medical Professional Density and Life Expectancy.

• Is there any correlation between the density of medical professionals and life expectancy?

2. Dataset Description

The analysis utilizes three comprehensive datasets from the World Health Statistics 2020. These datasets detail:

• The distribution of healthcare providers (medical doctors and pharmacists) per 10,000 population.
• Metrics on life expectancy across various regions and time periods (1990-2019).

For more information about the dataset, you can access it here: World Health Statistics 2020 | Complete | Geo-Analysis.

3. Data Preprocessing

Before analysis, the datasets were cleaned and preprocessed to ensure accuracy and consistency. This included handling missing values, standardizing formats, and merging datasets to align with research objectives.

4. Data Analysis and Visualization

4.1. Overview of Life Expectancy (Periods: 2000, 2010, 2015)

We examined average life expectancy for the years 2000, 2010, and 2015. The data shows a general increase in life expectancy over these years, with 2015 marking the highest average. The analysis delves into how healthcare provider density may correlate with these trends.

4.2. Life Expectancy by Continent (Periods: 2000, 2010, 2015)

We assessed life expectancy across different continents and compared the data from 2000, 2010, and 2015.

4.3. Healthcare and Life Expectancy Disparities

• Countries with Highest/Lowest Life Expectancy by Continent: Identified top and bottom countries in terms of life expectancy.
• Countries with Highest/Lowest Medical Professional Density by Continent: Highlighted countries with the highest and lowest density of medical professionals.
• Relationship between Life Expectancy and Medical Professional Density: Analyzed the correlation between these variables.

5. Conclusion

Findings from the Analysis

• Countries with the highest medical professional density do not always exhibit the highest life expectancy.
• In Europe, a clearer positive correlation between medical professional density and life expectancy was observed.
• The relationship between medical professional density and life expectancy is complex and influenced by various factors including:
  • Quality of healthcare systems
  • Healthcare infrastructure
  • Socioeconomic factors (income, education, employment opportunities, social support)
  • Lifestyle choices (nutrition, diet)
  • Environmental conditions (air and water quality)

Research Questions Revisited

Objective 1: Life Expectancy by Gender and Continent

• Do females or males tend to have higher life expectancy? Female life expectancy is generally higher.
• Which continent or country by continent has the highest/lowest life expectancy? Detailed answers are provided in the analysis sections.

Objective 2: Relationship Between Medical Professional Density and Life Expectancy

• Is there any correlation between these two variables? The correlation is nuanced and influenced by various factors.

Limitations

• Data Quality: Variations in data reporting and completeness across countries.
• External Factors: Other influencing factors beyond healthcare provider density were not exhaustively explored.
• Temporal Changes: Changes in healthcare policies or global events may impact the results.

Future Work

Further research could explore additional factors influencing life expectancy and refine the analysis by incorporating more granular data or considering more recent developments in healthcare systems.

References

• World Health Statistics 2020
• Data Sources and Methodology