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Analysis of Premature Death Rates in Texas Counties: The Impact of Air Quality, Socioeconomic Factors, and COPD Prevalence

Richard Rich, Ernesto Diaz

TL;DR

This study addresses premature mortality in Texas counties by modeling years of potential life lost ($YPLL$) as a function of ambient air quality ($PM_{2.5}$), median household income, and COPD prevalence. Data are drawn from the EPA Air Quality System (2022), American Community Survey 5-Year Estimates (2019), and CDC County Health Rankings, merged for 29 counties, and analyzed with a linear regression model. Key results show COPD prevalence as the strongest predictor of $YPLL$, a negative association with income, and a weaker direct link to $PM_{2.5}$, suggesting that air pollution may influence mortality primarily through indirect pathways. These findings support targeted public health strategies addressing respiratory disease and socioeconomic disparities and motivate longitudinal studies to better establish causal relationships.

Abstract

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.

Analysis of Premature Death Rates in Texas Counties: The Impact of Air Quality, Socioeconomic Factors, and COPD Prevalence

TL;DR

This study addresses premature mortality in Texas counties by modeling years of potential life lost () as a function of ambient air quality (), median household income, and COPD prevalence. Data are drawn from the EPA Air Quality System (2022), American Community Survey 5-Year Estimates (2019), and CDC County Health Rankings, merged for 29 counties, and analyzed with a linear regression model. Key results show COPD prevalence as the strongest predictor of , a negative association with income, and a weaker direct link to , suggesting that air pollution may influence mortality primarily through indirect pathways. These findings support targeted public health strategies addressing respiratory disease and socioeconomic disparities and motivate longitudinal studies to better establish causal relationships.

Abstract

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.
Paper Structure (21 sections, 1 equation, 5 figures, 2 tables)

This paper contains 21 sections, 1 equation, 5 figures, 2 tables.

Figures (5)

  • Figure 1: Correlation Matrix of Key Variables.
  • Figure 2: COPD Prevalence vs. Premature Death Rate.
  • Figure 3: PM2.5 vs. Premature Death Rate in Texas Counties.
  • Figure 4: Average PM2.5 vs. COPD Prevalence in Texas Counties.
  • Figure 5: Actual vs. Predicted Premature Death Rates.