High-Throughput Geocoding to Assess Short-Term Air Pollution in Correlation With Mortality in a French Cancer Patient...

Area of Science:

• Environmental Health
• Epidemiology
• Geomatics

Background:

• Air pollution is a significant risk factor for human mortality, including cancer deaths.
• Existing studies often lack spatial precision, necessitating advanced methods for vulnerable populations.
• Geomatic tools can enhance the understanding of environmental impacts on cancer patient mortality.

Purpose of the Study:

• To assess the association between short-term air pollution exposure and mortality in cancer patients in France.
• To utilize a geomatic framework for fine-spatial-granularity analysis.
• To identify key air quality predictors of mortality in this cohort.

Main Methods:

• Retrospective cohort study of 44,268 cancer patients (2017-2020).
• Geomatic analysis linking air quality data (PM2.5, PM10, NO2, O3, temperature) to patients.
• Principal Component Analysis (PCA) for exposure grouping and Random Forest for mortality prediction.

Main Results:

• Four distinct air quality exposure clusters were identified among patients.
• Higher levels of particulate matter (PM2.5, PM10, NO2) were linked to increased mortality (12%-13%).
• Key predictors of death included elevated PM2.5 within 31 days, higher temperature, older age, male sex, and thoracic cancer.

Conclusions:

• Short-term exposure to poor air quality, even at a fine spatial scale, is associated with excess mortality in cancer patients.
• A 31-day lag window for PM2.5 exposure is identified, suggesting a critical period for intervention.
• Findings support targeted public health strategies for cancer patients in polluted areas.