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Land surface temperature predicts mortality due to chronic obstructive pulmonary disease: a study based on climate
Alireza Mohammadi1, Bardia Mashhoodi2, Ali Shamsoddini3
1Department of Geography and Urban Planning, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil.
Geospatial Health
|March 27, 2025
Summary
Chronic Obstructive Pulmonary Disease (COPD) mortality is spatially clustered and increases with rising night-time land surface temperatures (LSTnt). These findings highlight the impact of global warming on respiratory health in the United States.
Area of Science:
- Environmental Health
- Epidemiology
- Spatial Analysis
Background:
- Global warming and climate change pose significant public health challenges.
- Chronic Obstructive Pulmonary Disease (COPD) mortality is a growing concern linked to environmental factors.
Purpose of the Study:
- To investigate the spatial patterns of COPD mortality in the United States from 2001 to 2020.
- To examine the relationship between COPD mortality and night-time land surface temperatures (LSTnt) as an indicator of warming.
Main Methods:
- Utilized county-level, age-adjusted COPD mortality data (adults >25 years).
- Employed Global Moran's I for spatial autocorrelation analysis.
- Applied the forest-based classification and regression (FCR) model to predict mortality rates using LSTnt data from the Terra satellite.
Main Results:
- COPD mortality exhibited significant spatial clustering across US counties over the 20-year study period.
- A positive correlation was observed between COPD mortality rates and LSTnt (Moran's I = 0.18).
- The strongest spatial association between COPD mortality and LSTnt was identified in eastern and southeastern counties, with the FCR model achieving an R² of 0.68.
Conclusions:
- Findings indicate a spatial link between global warming indicators and COPD mortality in the US.
- Results can inform the development of targeted spatial and public health strategies to mitigate the impact of warming on respiratory health.
- Policymakers can use this data to reduce the vulnerability of patients with respiratory conditions to climate change.
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