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- W4316924744 abstract "Background and Aim Health effects of spatially ubiquitous environmental factors are optimally assessed through cohort epidemiological analyses. However, their application requires the reconstruction of highly granular exposures summaries, which can show high variability within and between individuals. Availability of improved maps with finely resolved spatio-temporal measurements can address those limitations, but the linkage procedure poses methodological and practical problems. This study aims to describe a linkage framework to couple precise environmental measurements to subject-specific cohort data, maximizing the exposure information and accounting for privacy constraints and residential mobility. Methods Accomplishment of this goal is conditional to the availability of subjects’ residential mobility histories and geographical locations. The linkage process is carried out in three steps: (1) Spatial alignment of GIS exposure maps and the residential addresses, based on interpolation methods to avoid locations back-tracing; (2) Reconstruction of exposure histories accounting for residential changes in addresses during the follow-up; (3) Flexible definition of exposure summaries consistent with alternative research questions and epidemiological designs. Results This procedure is illustrated with the linkage and processing of daily predictions of exposure of temperature and particulate matter to 502,408 participants of the UK Biobank cohort from gridded spatio-temporal maps across Great Britain. The outcome of the process is concretized with the extraction of exposure summaries defined at daily level, suitable for the investigation of complex temporal dependencies. Particularly, they can be applied to compute averages of the two stressors, subsequently included in traditional analyses of short- and long-term associations. Conclusions Embedding highly informative contextual data in cohorts characterized by extensive individual phenotypes and genetic information allows the quantification of independent and synergistic health risks associated with environmental exposures. Further frameworks development with public cohort data should be encouraged to ensure reproducibility and extension of epidemiological analyses. Keywords Environmental exposures. Spatio-temporal models. data linkage. cohort analysis." @default.
- W4316924744 created "2023-01-18" @default.
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- W4316924744 date "2022-09-18" @default.
- W4316924744 modified "2023-10-16" @default.
- W4316924744 title "Linking subject-specific environmental exposures to individual cohort data: an example with the UK Biobank" @default.
- W4316924744 doi "https://doi.org/10.1289/isee.2022.p-0865" @default.
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