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Title: Control for seasonal variation and time trend in case-crossover studies of acute effects of environmental exposures.

Authors: Bateson, T F; Schwartz, J

Published In Epidemiology, (1999 Sep)

Abstract: The case-crossover study design is used to study the triggers of acute outcomes in populations. It controls for all measured and unmeasured time-invariant confounders by design. Studies of environmental triggers of morbidity are potentially confounded by temporal trends in the outcome owing to omitted covariates. We conducted a simulation study of the case-crossover design's ability to control for temporal confounding patterns by design rather than through modeling. We compared five case-crossover control sampling strategies including the matched pair, a symmetric bi-directional, a total history approach, and two approaches proposed by Navidi (Biometrics 1998;54:596-605). We simulated true relative risks (RR) of 1.10 and 2.00 and induced confounding by seasonal patterns as well as linear and nonlinear long-term trends to yield estimated RR values as high as 3.18. The symmetric bi-directional approach was compared across four lag times and controlled for temporal confounding best when the lag was shortest. With a 1-week lag, it estimated the RR values as 1.10 and 2.01. The four other approaches failed to control for the temporal trends. Our simulations show that the symmetric bi-directional case-crossover design can substantially control for temporal confounding by design although it is not as efficient (66%) as Poisson regression analysis.

PubMed ID: 10468428 Exiting the NIEHS site

MeSH Terms: Computer Simulation; Confounding Factors (Epidemiology); Cross-Over Studies*; Environmental Exposure/statistics & numerical data*; Longitudinal Studies*; Research Design*; Research Support, U.S. Gov't, P.H.S.; Risk Assessment/methods; Seasons*; Statistics/methods; Time Factors

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