# Data from: Broadband Access and Health Outcomes in FCC Priority Counties: A Longitudinal Analysis

The tables and figures from the article “Broadband Access and Health Outcomes in FCC Priority Counties: A Longitudinal Analysis,” published in ConductScience Journal on February 24, 2025, as separate files: each table as a CSV file and each figure as the image in the accepted manuscript.

- Data record: https://conductscience.org/data/records/broadband-health-outcomes
- Article: https://doi.org/10.55157/csj.v1i1.04
- Version: 1.0.0, released September 26, 2026

## Files

| File | Contents |
|---|---|
| `table-1.csv` | Table 1. Demographics characteristics of FCC 2017 priority counties (N=171). |
| `table-2.csv` | Table 2. Trends in preventable hospitalizations, obesity, diabetes, and broadband access in FCC priority counties from 2013- 2020. |
| `figure-1.png` | Figure 1. Figure Caption: The Pearson’s correlation matrix explores linear relationships between continuous variables, using averages across all 171 FCC priority counties and over time periods (2013-2020). |
| `table-3.csv` | Table 3. Regression analyses of relationships between broadband and health outcomes over time (2013-2020) in FCC priority counties (N=171), controlling for county-level characteristics. |
| `figure-s1a.png` | Figure S1A. Figure Caption: Pearson’s correlation matrix of relationships between continuous variables including averages across all 187 FCC priority counties (including the 16 counties identified as potential outlier) and over time periods (2013-2020). |
| `figure-s1b.png` | Figure S1B. Figure Caption: Spearman’s correlation matrix of relationships between continuous variables including averages across all 187 FCC priority counties (including the 16 counties identified as potential outlier) and over time periods (2013-2020). |
| `figure-s1c.png` | Figure S1C. Figure Caption: Pearson’s correlation matrix of relationships between continuous variables including averages across 171 FCC priority counties (excluding the 16 counties identified as potential outlier) and over time periods (2013-2020). |
| `figure-s1d.png` | Figure S1D. Figure Caption: Spearman’s correlation matrix of relationships between continuous variables including averages across all 187 FCC priority counties (including the 16 counties identified as potential outlier) and over time periods (2013-2020). |
| `figure-s2a.png` | Figure S2A. Figure Caption: Boxplots explore the mean and variance of percent of diabetes prevalence in a county, grouping by county characteristics and averaging across FCC priority counties (N=171) and over time (2013-2020). PCPS: Primary Care Physician Shortage; PP: Persistent Poverty; Vet: Veteran. |
| `figure-s2b.png` | Figure S2B. Figure Caption: Boxplots explore the mean and variance of obesity prevalence in a county, grouping by county characteristics and averaging across FCC priority counties (N=171) and over time (2013-2020). PCPS: Primary Care Physician Shortage; PP: Persistent Poverty; Vet: Veteran. |
| `figure-s2c.png` | Figure S2C. Figure Caption: Boxplots explore the mean and variance of the number of preventable hospitalizations in a county, grouping by county characteristics and averaging across FCC priority counties (N=171) and over time (2013-2020). PCPS: Primary Care Physician Shortage; PP: Persistent Poverty; Vet: Veteran. |
| `figure-s2d.png` | Figure S2D. Figure Caption: Boxplots explore the mean and variance of broadband speed (Mbps) in a county, grouping by county characteristics and averaging across FCC priority counties (N=171) and over time (2013-2020). PCPS: Primary Care Physician Shortage; PP: Persistent Poverty; Vet: Veteran. |
| `figure-s2e.png` | Figure S2E. Figure Caption: Boxplots explore the mean and variance of percent of households in a county with broadband subscriptions, grouping by county characteristics and averaging across FCC priority counties (N=171) and over time (2013-2020). PCPS: Primary Care Physician Shortage; PP: Persistent Poverty; Vet: Veteran. |
| `figure-s2f.png` | Figure S2F. Figure Caption: Boxplots explore the mean and variance of percent of households in a county with advanced broadband speeds (> 25 Mbps), grouping by county characteristics and averaging across FCC priority counties (N=171) and over time (2013-2020). PCPS: Primary Care Physician Shortage; PP: Persistent Poverty; Vet: Veteran. |
| `table-s1.csv` | Table S1. Sensitivity analyses of relationships between broadband and health outcomes over time (2013-2020) in FCC priority counties including potential outliers (N=187), controlling for county-level characteristics. |

`METHODS.md` explains how the files were made, `data_dictionary.csv` describes each data file, `CITATION.cff` gives the citation and `MANIFEST.json` lists every file's size and SHA-256.

## Reading the tables

Each CSV keeps the table's rows and cells as printed, including header rows, section rows and footnote markers. Values were not retyped, recalculated or reformatted.

`table-3.csv`, `table-s1.csv` have merged cells or section rows, so some rows have fewer cells than the header. Read them alongside the article.

## License

CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/), the same license as the article. Credit the authors and cite this dataset and the article when you reuse the files. `LICENSE` has the full legal code.

## Citation

Green, R., von Franque, M., Martinez, M., & Martin, A. (2026). Data from: Broadband Access and Health Outcomes in FCC Priority Counties: A Longitudinal Analysis (Version 1.0.0) [Data set]. ConductScience Data. https://conductscience.org/data/records/broadband-health-outcomes

Article:

Green, R., von Franque, M., Martinez, M., & Martin, A. (2025). Broadband Access and Health Outcomes in FCC Priority Counties: A Longitudinal Analysis. ConductScience Journal, 1(1). https://doi.org/10.55157/csj.v1i1.04