Potential Errors In Epidemiology

Potential Errors In Epidemiology

Potential Errors In Epidemiologic Studies IV. Confounding Dr. Sherine Shawky Learning Objectives Understand the concept of

confounding Recognize the methods to prevent confounding Know the methods to evaluate the impact of confounding Performance Objectives Prevent confounding

Evaluate confounding Confounding A situation in which effects of two risk factors are mixed in the occurrence of the health problem under study

Confounding may lead to overestimation or underestimation of the true association between exposure and outcome and can even

change the direction of the observed effect Criteria for Confounding Exposure Outcome

Confounding Control of Confounding Prevent Prevent Study Study Evaluate

Evaluate Prevention of Confounding Restriction Matching

Randomization Restriction Putting admissibility criteria for subjects and limiting enrollment into the study to individuals who fall within a specified

category or categories of the confounder. Restriction Strength Straightforward Convenient if criteria are

narrow Inexpensive Restriction Limitation Reduces the number of subjects eligible to participate

Difficult if criteria are not narrow Does not permit evaluation of association between exposure and outcome for varying levels of factor Randomization Every individual has the same chance of being classified in either of the two groups. The two

methods commonly used for randomization are the use of a table of random numbers or the use of a computer-generated randomization Randomization Strength

Controls confounders even those unsuspected Study groups are comparable Permits evaluation of association between exposure and outcome for varying levels of the factor Randomization Limitation

Not easy to perform Ethical problems Expensive Matching Selecting study group and comparison group so that they are comparable with respect to various defined factors. In

addition to the use of specific statistical tests for analyses of paired data Matching Strength Appropriate when sample size is small and matching

variables are limited Study groups are comparable Matching Limitation Difficult, expensive and time consuming to find comparison subjects

Matching on a particular variable prohibits studying its association with the outcome Evaluation of Confounding Stratified analysis Multivariate analysis

Stratified Analysis Stratification is a technique used to control confounding in the analysis stage that involves the evaluation of the association within homogeneous categories or strata of the confounding factor

Stratification Strength Easy for limited variables with limited number of categories Permits evaluation of confounding and interaction Permits evaluation of association between exposure and outcome for

varying levels of the factor Stratification Limitation Difficult if many variables with varying number of categories are required Multivariate Analysis

Analysis of data through construction of mathematical model that takes into account number of variables at the same time Multivariate Analysis Strength Describes

efficiently the association between exposure and outcome taking in consideration the impact of other variables.

Multivariate Analysis Limitation The choice of the appropriate model is complex and requires training and experience Conclusion There are number of methods for

control of confounding. Each has its strength and limitation. In most situations, a combination of strategies provides better insights of data and more efficient control of confounding.

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