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

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.