# Explanation of Disease Rate Statistics

When comparing incidence or mortality rates of two or more groups, one group is assigned the rate of 1.00 and the other groups are compared to it. These are called disease rate ratios or odds rate ratios.

Examples:

Group A 1.00
Group B 1.35

Group B has a 35% higher rate of the disease than Group A.

Group A 1.00
Group B .85

Group B has a 15% lower rate of the disease than Group A.

In addition to the rates, there has to be a test to determine if the rates are different enough not to be due merely to random chance (also known as statistical significance). Statistical significance for a disease rate is usually expressed by way of a 95% confidence interval (CI). This is done by giving a lower and upper limit for the interval. If 1.00 does not fall between the two numbers (i.e., within the interval), then the finding is significant and not due to random chance.

Example 1:

.85 (.75, .95)

The finding is statistically significant because 1.00 falls outside the 95% CI.

Example 2:

.85 (.65, 1.05)

The finding is not statistically significant because 1.00 falls inside the 95% CI.

Sometimes, p-values are given rather than confidence intervals. In these cases, a p-value of less than .05 means the finding is statistically significant.