10.2: Observational Studies ✅

Question 1

Cross-sectional studies: characteristics

Answer 1

1) Descriptive

2) Analytic

-Random sample taken from the source population
-All assessments happen at a specific time point
-Exposure and outcome are assessed simultaneously
-Mostly deal with the present
-Many countries have annual cross-sectional studies to assess health of the population (called surveys)

Question 2

Descriptive

Answer 2

Assessment of only 1 variable at a time

Question 3

Analytic

Answer 3

Assessment of association between 2 variables

Question 4

Descriptive measures for Cross-sectional studies

Answer 4

Proportions (categorical)

Prevalence (binary categorical)

Mean/median (numeric)

Question 5

Measures of association for Cross-sectional

Answer 5

Odds ratio (binary categorical)

Mean difference (categorical exposure vs numeric outcome)

Regression/correlation coefficient (numeric exposure vs numeric outcome)

Question 6

Pros of Cross-sectional studies

Answer 6

Easy

Cheap

Gives the opportunity to readily assess the prevalence of disease in a population

Question 7

Cons of cross-sectional studies

Answer 7

Observational design often leads to information bias
-as mostly self reporting

Prone to confounding
-as can’t assess all potential confounders

Impossible to assess risk of a disease (incidence)

Impossible to establish temporality in an association
-as exposure and outcome are assessed simultaneously

Not appropriate for inferring causality between an exposure and an outcome (high likelihood of reverse causation)

Question 8

Case group

Answer 8

A group of patients with a specific disease

Question 9

Control group

Answer 9

Random sample of individuals not suffering from the specific disease

-has to be recruited from the source population

Question 10

Case-control studies: characteristics

Answer 10

Case group usually matched for key characteristics to eliminate confounding

Overmatching should be avoided and restricted to 2-3 factors
-rest should be adjusted at the analysis stage.

Final step involves assessment of a series of exposures in cases and controls which occurred in the past

Retrospective

Question 11

Retrospective

Answer 11

Start with the disease and then look back in time for identification of exposures

Question 12

Measure of association for Case-control

Answer 12

Odds ratio (categorical)

Mean difference (numeric)

*note: outcome is ALWAYS binary

Question 13

Descriptive measures for Case-control

Answer 13

Never calculated

->only analytical

Question 14

Pros of Case-control

Answer 14

Can investigate determinants of rare diseases

Easy to perform

Cheap

Possible to assess several exposures and potential confounders for a single outcome

Possible to investigate exposures that happened in the long past

Question 15

Cons of case-control

Answer 15

Observational design, prone to information bias (measurements are based on self-reports)

Prone to recall bias
(assessments of exposures are based on self reports of events that happened many years back)

Very prone to confounding

If the control group is not a representative sample, can lead to selection bias

Impossible to assess the risk of disease

Difficult to prove the causality due to confounding and bias

Question 16

Cohort studies characteristics

Answer 16

Random sample is selected from the source population

Before study, all participants suffering from the disease of interest are excluded

At the study baseline, all exposures of interest and potential confounders are assessed

Following this, participants continue to live normally and researchers record new cases of disease during follow-up

Ascertainment of disease cases occur from clinical examination, hospital or national registries or self reports in specific time intervals

In a follow up, reassessment of exposures to see if they have changed

Main aim is to investigate whether the risk of different diseases differs based on different exposures

Prospective due to time-lapse between exposure and outcome

Question 17

Descriptive measures of Cohort studies

Answer 17

Incidence (binary)

Mean/median (numeric)

*note: descriptive measures are rarely calculated in cohort studies

Question 18

Measures of association for Cohort studies

Answer 18

Risk ratio (binary categorical)

Rate ratio (binary categorical when person-years can be calculated)

Mean difference (categorical vs numeric exposure)

*note: Odds ratio could be calculated when the binary outcome is very rare

Question 19

Pros of Cohort studies

Answer 19

Can assess risk of disease
–> calculate relative risk

Can assess temporal associations

Can assess several exposures and outcomes so results are more valid

Can investigate risk factors for chronic diseases

Study samples are usually large, increases internal validity

Question 20

Cons of cohort studies

Answer 20

Observational design, so is prone to informational bias
(as measurements based on self reports)

Selection drop out can lead to risk of selection bias

Observational design = prone to confounding

Hard to assess risk of rare disease outcomes
(as a large sample would be required)

Difficult to prove causality due to possible bias and confounding, but easier than compared to other observational study designs