U.S. State-Level COPD Choropleth Map

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Author

nikcompsci

https://github.com/nikcompsci/

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Project Purpose:

Visualize state-level COPD prevalence in the U.S. using R and CDC BRFSS data (adults 18+).

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Data Source

Centers for Disease Control and Prevention (CDC)

Behavioral Risk Factor Surveillance System (BRFSS): Prevalence & Trends Data, , Chronic Health Indicators: COPD, Adults 18+ Prevalence & Trends Data, Adults 18+ https://www.cdc.gov/brfss/brfssprevalence/index.html

The dataset contains state-level prevalence percentages for adults reporting a diagnosis of Chronic Obstructive Pulmonary Disease (COPD).

Note: The source table was manually reviewed and cleaned prior to analysis. A spelling inconsistency in the prevalence column name was corrected to ensure accurate merging and visualization.

📁 Project Structure

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Visualization

• Choropleth map created using ggplot2 and geom_sf().
• Color gradients reflect increasing COPD prevalence.

Key R Packages Used:

• tidyverse – data manipulation and cleaning

• sf – spatial data handling

• ggplot2 – data visualization

• maps – U.S. state boundary data

• here – reproducible file paths

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Output

Figure: figures/copd_map.png

• Choropleth map illustrating state-level COPD prevalence across the U.S.

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Reproducibility

To reproduce this analysis:

1. Open the R project file (.Rproj)
2. Ensure required packages are installed
3. Run the script: COPD_Prevalence.R

All file paths are handled using here() for cross-system compatibility.

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Disclaimer

This project is for educational and portfolio purposes only. The analysis does not represent official CDC interpretations or conclusions.

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References

1. Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division of Population Health. BRFSS Prevalence & Trends Data [online]. 2025. [accessed Thu, 18 Dec 2025 05:16:46 GMT]. URL: https://www.cdc.gov/brfss/brfssprevalence/.

2. Becker, R. A., Wilks, A. R., Brownrigg, R., Minka, T. P., & Deckmyn, A. (2018).
   maps: Draw Geographical Maps. R package.
   https://cran.r-project.org/web/packages/maps/index.html

3. Pebesma, E. (2018).
   sf: Simple Features for R. R package.
   https://cran.r-project.org/package=sf

4. Wickham, H. et al. (2019).
   Welcome to the tidyverse. Journal of Open Source Software.
   https://www.tidyverse.org/