Climate change is increasingly recognized as a critical determinant of human health, yet its integration into health policy remains limited. Understanding the link between climate variables and human life expectancy is essential for developing targeted interventions that mitigate health risks. This study examines the relationship between key climate features and life expectancy, providing evidence to inform integrated climate and health policies.

We applied a multi-method modeling framework, including Random Forest, Geographically Weighted Regression, and Generalized Additive Models, to analyze the impact of climate variables on human life expectancy in the United States. Key environmental factors, such as vapor pressure, temperature, actual evapotranspiration, and solar radiation, were assessed for their influence on life expectancy across diverse geographic regions. Model performance and variable importance were evaluated to ensure robustness and consistency.

Our findings indicate that higher vapor pressure, actual evapotranspiration, and temperature are associated with reduced life expectancy, whereas increased solar radiation demonstrates a protective effect. These associations remained consistent across all models, highlighting the reliability of our approach. The Random Forest model exhibited strong predictive performance, reinforcing the validity of our findings.

This study underscores the significant impact of climate on human life expectancy and highlights the need for integrated climate and health policies. Addressing harmful climate variables through targeted interventions—such as urban planning and emergency management—can enhance public health resilience. Our findings provide a scientific foundation for policymakers to develop sustainable strategies that safeguard human well-being in the face of climate change.