Instructor Resource

Chapter 2

Copyright © Scott B. Patten, 2015.

Permission granted for classroom use with Epidemiology for Canadian Students: Principles, Methods & Critical Appraisal (Edmonton: Brush Education Inc. www.brusheducation.ca).

Chapter 2. Epidemiological

reasoning

Objectives

• State the “fundamental assumption” of epidemiological research.• Explain the key concepts of association, proportion,

prevalence, and point prevalence.• Identify the 2 main sources of error in

epidemiologic research: • random error (sampling variability)• systematic error (bias)

• Define critical appraisal.

The “fundamental assumption”• Diseases do not distribute randomly in populations,

but rather distribute in relation to their determinants.• Therefore, determinants can be identified by

studying distributions.

A classic example

• “Smoking and Carcinoma of the Lung: Preliminary Report,” Doll & Hill, 1950• compared lung cancer cases (disease) to controls • exposure in question: smoking

http://en.wikipedia.org/wiki/Austin_Bradford_Hill

Basic epidemiological parameters• A parameter, in epidemiology, represents a

characteristic of a population.

A basic parameter: prevalence• Prevalence is the proportion of a population with a

disease. • Types of prevalence include:• point prevalence• period prevalence• lifetime prevalence

• Usually, prevalence needs to be estimated from a sample.

Random error

• The law of large numbers ensures that prevalence estimated on data collected from random samples provides information about population prevalence.• Even with perfect sampling procedures and

measurement, estimates from small samples may be wrong by chance.• Large samples are less likely to be seriously wrong due

to sampling variability than small samples.• If there are defects in study design (e.g., sampling or

measurement), the estimates can be systematically wrong. This is called bias.

Critical Appraisal

• Critical appraisal comes into play when you read a study (and when you design and conduct a study).• You read with a critical eye (seek to criticize). • This involves searching for sources of error:• random error due to sampling variability• systematic sources of error due to study design defects

1 x 2 Contingency table (population) Has disease No disease Row totals

A B N

P REVALENCE=AA+B

=AN

1 x 2 Contingency table (sample) Has disease No disease Row totals

a b n

Prevalence

Standard error of an estimated proportion

In this formula, p is the estimated prevalence

What will happen as n gets bigger?

S

End