Download Analyzing Results of a Cohort Study

Analyzing Results of a Cohort Study
The goal of a cohort study is to identify the risk factor(s) for the development of some. disease
(or health problem). This is done by calculating attack rates and relative risks.
The attack rate is the incidence of disease in a selected group of people. It is the number of
people in that group who developed disease, divided by the total number of people in the
group. In a cohort study, you will compare the attack rate among people exposed to a certain
risk factor and the attack rate among those not exposed.
In a cohort study, you will also compute the ratio of these attack rates, known as the relative
risk. The relative risk is the measure of association for a cohort study.
The relative risk quantifies the relationship between an exposure and a disease and tells us how
many times more likely it is that people who were exposed to a risk factor became ill compared
to people not exposed to that risk factor. A relative risk of:
• l.0 (or close to 1.0) means the risk of disease is similar in the exposed and unexposed group,
and the exposure is not associated with disease.
• greater than l.0 means the risk of disease is greater in the exposed than the unexposed.
group, and the exposure could be a risk factor.
• less than l.0 means the risk of disease is less in the exposed group than the unexposed group,
and the exposure could be "protective". If a risk factor is associated with disease, you should
see the following outcomes:
• The attack rate is high among those exposed to the factor.
• The attack rate is low among those not exposed, so the relative risk (or ratio between. the
attack rates) is high.
• Most of the cases were exposed to the factor, so exposure could explain" most, if not all, of
the cases.
It is important to note, however, that these outcomes do not automatically mean that the
exposure is a risk factor for the disease. Tests of statistical significance (such as the. chi-square
or Fisher exact test) must be used to determine the probability that an observed outcome could
have occurred due to chance alone. This probability is called the p-value.
A very small p-value (i.e., a low probability) means that you would be unlikely to observe an.
outcome due to chance alone, if there was no association between exposure and disease. If
the p-value is smaller than some predetermined cut-off (usually 0.05 or a 5 in 100 chance), the
association is then said to be "statistically significant".