Time-stratified case-crossover studies for aggregated data in environmental epidemiology: a tutorial
The case-crossover design is widely used in environmental epidemiology as an effective alternative to the conventional time-series regression design to estimate short-term associations of environmental exposures with a range of acute events. This tutorial illustrates the implementation of the time-stratified case-crossover design to study aggregated health outcomes and environmental exposures, such as particulate matter air pollution, focusing on adjusting covariates and investigating effect modification using conditional Poisson regression. Time-varying confounders can be adjusted directly in the conditional regression model accounting for the adequate lagged exposure-response function. Time-invariant covariates at the subpopulation level require reshaping the typical time-series data set into a long format and conditioning out the covariate in the expanded stratum set. When environmental exposure data are available at geographical units, the stratum set should combine time and spatial dimensions. Moreover, it is possible to examine effect modification using interaction models. The time-stratified case-crossover design offers a flexible framework to properly account for a wide range of covariates in environmental epidemiology studies.
| Main Authors: | , , |
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| Other Authors: | |
| Format: | artículo biblioteca |
| Language: | English |
| Published: |
Oxford University Press
2024-02-14
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| Subjects: | Environmental epidemiology, Time-stratified case-crossover, Air pollution, Conditional Poisson regression, Ensure healthy lives and promote well-being for all at all ages, Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation, Make cities and human settlements inclusive, safe, resilient and sustainable, Take urgent action to combat climate change and its impacts, |
| Online Access: | http://hdl.handle.net/10261/349705 https://api.elsevier.com/content/abstract/scopus_id/85185708249 |
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