Strengths
Relatively quick, cheap and easy to conduct (no long periods of follow-up).
Data on all variables is only collected once.
Able to measure prevalence for all factors under investigation.
Multiple outcomes and exposures can be studied.
The prevalence of disease or other health-related characteristics are important
in public health for assessing the burden of disease in a specified population
and in planning and allocating health resources.
Good for descriptive analyses and for generating hypotheses.
Weaknesses
Difficult to determine whether the exposure or outcome came first (“Association and
Causation”)
Not suitable for studying rare diseases or diseases with a short duration.
As cross-sectional studies measure prevalent rather than incident
Associations identified may be difficult to interpret.
Susceptible to biases
Strengths
Cost-effective relative to other analytical studies such as cohort studies.
Case-control studies are retrospective, cases are identified at the beginning of the study
therefore there is no long follow-up period (compared to cohort studies).
Efficient for the study of diseases with long latency periods.
Efficient for the study of rare diseases.
Good for examining multiple exposures simultaneously
Weaknesses
Particularly prone to bias; especially selection, recall and observer bias.
Unable to estimate incidence rates of disease
Poor choice for the study of rare exposures.(diagnostic)
.
Strengths
Multiple outcomes can be measured for any one exposure.
Can look at multiple exposures.
Exposure is measured before the onset of disease (in prospective cohort studies) i.e. the
temporal relationship is certain.
Demonstrates direction of causality.
Good for measuring rare exposures, for example among different occupations.
Good for outcomes which occur long after exposure
Can measure incidence and prevalence.
Weaknesses
Costly and time consuming.
Prone to bias due to loss to follow-up.
Being in the study may alter participant behavior.
Inefficient for the study of a rare disease outcome.