Atlas home || Conferences | Abstracts | about Atlas

New Zealand Statistics Conference
September 1, 2000
University of Canterbury
Christchurch, New Zealand

Organizers
Dr Marco Reale, Prof Malcolm Faddy, Dr Irene Hudson, Doris Barnard, Julian Visch

View Abstracts
Conference Homepage

Blood Pressure attenuation factors using Peto's Method
by
Michelle Wood
Clinical Trials Research Unit, Statistics Department University of Auckland
Coauthors: Thomas Yee, Statistics Department, University of Auckland

Blood pressure is an established risk factor of stroke. However an individual's blood pressure varies over time, even during the course of a day. Despite this, researchers often use ``one off'' readings of blood pressure to estimate a person's usual blood pressure and hence their risk of stroke. The level of attenuation can be ascertained by obtaining repeated measurements of blood pressure.

Peto's method (1990), gives a common approach to calculate an attenuation factor to adjust the risk of stroke for the variation in a person's blood pressure. This method involves splitting the data into groups according to the baseline blood pressure measurement. In practice, the splitting of the data has been done by both quintiles and even arbitrary cut points. The use of qunitiles is questioned in Frost Thompson (2000). They ask why not the use of tertiles, quartiles of deciles?

This paper presents the results of a simulation study optimizing the attenuation factor by the selection the splitting points for the groups. This research was motivated by Asia Pacific Studies Collaboration (APCSC), a large collection of prospective cohorts from several different countries. Group selection becomes an issue for this data as there is a large degree of rounding in the blood pressure measurements usually to the nearest 10 mmHg but also to the nearest 5 mmHg.

MacMahon, Stephan and Peto, Richard and Culter, Jeffery and Collins, Rory, Blood pressure, stroke, and coronary heart disease, Part 1, prongled differences in blood pressure: prospective observational studies corrected for the regression dilution bias The Lancet, 1990, 335, 765-774.

Frost, Chris and Thompson, Simon. G., Correcting for regression dilution bias: comparsion of methods for a single predictor variable, Journal of Royal Statistical Society, 2000, 163, 173-189

Date received: June 25, 2000


Copyright © 2000 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # cadt-07.