Simulation study of the effects of excluding early deaths on risk factor-mortality analyses in the presence of confounding due to occult disease: Theexample of body mass index
Db. Allison et al., Simulation study of the effects of excluding early deaths on risk factor-mortality analyses in the presence of confounding due to occult disease: Theexample of body mass index, ANN EPIDEMI, 9(2), 1999, pp. 132-142
PURPOSE: Estimating the effects of continuous chronic disease risk factors
on mortality is an area that generates confusion and controversy. The frequ
ently observed U-shaped or J-shaped relationships between the risk factors
and mortality are often in contrast with presumed monotone relationships. T
herefore, some investigators suggest that subjects dying during the first k
years of follow-up (where k Is some positive number less than the total le
ngth of follow-up) be excluded from statistical analyses. The rationale for
this approach is that subjects dying during the first k years of follow-up
are likely to have some pre-existing occult disease that confounds the rel
ationship between the risk factors and mortality. Excluding such subjects p
urportedly reduces bias due to this confounding. The purpose of this study
was to test the effects of excluding subjects who die during the first k ye
ars of follow-up on the reduction of bias under a variety of situations,
METHODS: Using body mass index (BMI; kg/m(2)) as an example, we conducted M
onte Carlo simulations to investigate such effects.
RESULTS: Results suggest that under the conditions investigated, the method
of excluding early deaths does not reliably or substantially reduce bias d
ue to confounding introduced by occult disease.
CONCLUSION: Excluding subjects dying during the first Ic years of follow-up
may nor be a judicious strategy for handling confounding due to occult dis
ease. investigators are encouraged to develop alternative methods. (C) 1999
Elsevier Science Inc. All rights reserved.