How to estimate the association between change in a risk factor and a health outcome?

12/21/2020
by   Michail Katsoulis, et al.
0

Estimating the effect of a change in a particular risk factor and a chronic disease requires information on the risk factor from two time points; the enrolment and the first follow-up. When using observational data to study the effect of such an exposure (change in risk factor) extra complications arise, namely (i) when is time zero? and (ii) which information on confounders should we account for in this type of analysis? From enrolment or the 1st follow-up? Or from both?. The combination of these questions has proven to be very challenging. Researchers have applied different methodologies with mixed success, because the different choices made when answering these questions induce systematic bias. Here we review these methodologies and highlight the sources of bias in each type of analysis. We discuss the advantages and the limitations of each method ending by making our recommendations on the analysis plan.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 23

04/16/2018

Mendelian randomization with a binary exposure variable: interpretation and presentation of causal estimates

Mendelian randomization uses genetic variants to make causal inferences ...
03/11/2018

Contextualizing selection bias in Mendelian randomization: how bad is it likely to be?

Selection bias affects Mendelian randomization investigations when selec...
07/23/2019

The effect of short-term exposure to the natural environment on depressive mood: A systematic review and meta-analysis

Research suggests that exposure to the natural environment can improve m...
04/29/2022

Bayesian Benefit Risk Analysis

The process of approving and assessing new drugs is often quite complica...
10/28/2019

Effects of Social Cues on Biosecurity Compliance in Livestock Facilities: Evidence from Experimental Simulations

Disease outbreaks in U.S. animal livestock industries have economic impa...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.