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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2412.19774 |
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| _version_ | 1866915081591193600 |
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| author | Rich, Richard Diaz, Ernesto |
| author_facet | Rich, Richard Diaz, Ernesto |
| contents | Understanding factors contributing to premature mortality is critical for public health planning. This study examines the relationships between premature death rates and multiple risk factors across several Texas counties, utilizing EPA air quality data, Census information, and county health records from recent years. We analyze the impact of air quality (PM2.5 levels), socioeconomic factors (median household income), and health conditions (COPD prevalence) through statistical analysis and modeling techniques. Results reveal COPD prevalence as a strong predictor of premature death rates, with higher prevalence associated with a substantial increase in years of potential life lost. While socioeconomic factors show a significant negative correlation, air quality demonstrates more complex indirect relationships. These findings emphasize the need for integrated public health interventions that prioritize key health conditions while addressing underlying socioeconomic disparities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_19774 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Analysis of Premature Death Rates in Texas Counties: The Impact of Air Quality, Socioeconomic Factors, and COPD Prevalence Rich, Richard Diaz, Ernesto Machine Learning Understanding factors contributing to premature mortality is critical for public health planning. This study examines the relationships between premature death rates and multiple risk factors across several Texas counties, utilizing EPA air quality data, Census information, and county health records from recent years. We analyze the impact of air quality (PM2.5 levels), socioeconomic factors (median household income), and health conditions (COPD prevalence) through statistical analysis and modeling techniques. Results reveal COPD prevalence as a strong predictor of premature death rates, with higher prevalence associated with a substantial increase in years of potential life lost. While socioeconomic factors show a significant negative correlation, air quality demonstrates more complex indirect relationships. These findings emphasize the need for integrated public health interventions that prioritize key health conditions while addressing underlying socioeconomic disparities. |
| title | Analysis of Premature Death Rates in Texas Counties: The Impact of Air Quality, Socioeconomic Factors, and COPD Prevalence |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2412.19774 |