Development of Life Course Exposure Estimates Using Geospatial Data and Residence History

Area of Science:

• Environmental Epidemiology
• Geospatial Health
• Exposure Science

Background:

• Accurate life course exposure assessment is crucial for understanding environmental health impacts.
• Existing geospatial methods face challenges with individual mobility, data gaps, and scaling issues.

Purpose of the Study:

• To develop and validate methods for creating individual exposure histories.
• To address challenges in geospatial exposure estimation for a cohort with amyotrophic lateral sclerosis (ALS) and controls.

Main Methods:

• Enhanced residence history surveys incorporating date and age, accounting for preceding/following residences.
• Novel spatial multiple imputation for handling missing or incomplete address data.
• Utilized PM2.5, black carbon, NO2, and traffic intensity geospatial datasets.

Main Results:

• Residence history completeness improved significantly, capturing a 20-year window for 95% of the cohort.
• Spatial imputation boosted time history completion to 99% and geocoding success to 92%.
• PM2.5 and NO2 showed moderate agreement with observed data, but 1km resolution limited fine-scale heterogeneity capture.

Conclusions:

• The proposed methods substantially improve the completeness, reliability, and accuracy of life course exposure estimates.
• This study pioneers examination of older cohort mobility for long exposure windows and spatial imputation techniques.
• The recommended methods offer broad applicability for environmental exposure research.