The term ‘morbidity rate’ might bring up images that are, well, morbid. And the term indeed deals with dark topics — it’s the rate at which an event, usually an illness, occurs in a population.

Learn more in this lesson about its calculation and its usefulness for predicting certain illnesses.

## Understanding Morbidity Rate

If seven out of ten of your family members lost their teeth in 2009, the morbidity rate for tooth loss in your family in 2009 would be 70%. **Morbidity rate** is an assessment of the frequency of an event making itself known or occurring in a defined population.

Morbidity rate is a broad statistic that relates to the likelihood of developing or contracting a certain illness or event. The topic can be better understood by looking at various subsets of the overall morbidity rate.To increase the usefulness of information from calculation of morbidity rate, it is preferable to look at two subsets: **incidence** and **prevalence**. It’s also useful to remember that ‘morbidity’ refers to illness or being affected by an illness, while mortality refers to death due to an event. Therefore, morbidity rate tell us nothing about mortality rate.

## Incidence

**Incidence** is the rate at which a disease or event occurs or develops within a given population in a defined time period. It does not address specific causation or predict the course of a disease for an individual. It is a statistic that looks at overall occurrence within a population and can be used to predict the rate at which occurrence of a disease is increasing or decreasing.For calculation of incidence, the numerator is the number of new cases identified within a defined time period. This is divided by the denominator, which is the number of people at risk in the same time period.

You then multiply the whole thing by 100 to get the incidence rate. For example, if the event being studied is the incidence of ovarian cancer in Florida in 2004, the numerator would be the number of newly diagnosed ovarian cancer cases in Florida in 2004. The denominator would be the number of women in Florida in 2004.

Men would not be included in the denominator as they are not at risk for developing ovarian cancer.

## Prevalence

**Prevalence** is the number of cases (both newly diagnosed and previously diagnosed in current survivors) within a given population in a defined time period. It reflects the penetration of a particular disease or event within a population and can be used to evaluate the impact that treatments are having on a particular disease.To determine the prevalence of ovarian cancer in Florida in 2004, the numerator would be the number of ovarian cancer cases diagnosed in Florida in 2004 and the number of woman previously diagnosed with ovarian cancer in Florida who are still alive.

The denominator would be represented by the number of woman in Florida in 2004. Again, men would not be included in the denominator.

## Examples of Calculations

Now that we know how to calculate incidence rate and prevalence rate – the two components of morbidity rate – let’s look at some examples using actual numbers.

Please keep in mind that all these numbers are hypothetical and for illustration only.

Number of ovarian cancer cases diagnosed in Florida in 2004 | 50,000 |

Number of ovarian cancer cases diagnosed before 2004 and still alive in 2004 | 77,000 |

Florida population in 2004 | 3,000,000 |

Number of females in the Florida population in 2004 | 1,999,000 |

To get the incidence rate, remember that we need to divide the number of cases during the time we’re looking at – which in this case is 50,000 – and divide that by the population at risk – which would be the 1,999,000 females living in Florida at that time. We then multiply by 100 to get our incidence rate, which is 2.

5%.*Incidence rate = (50,000 / 1,999,000) x 100 = 2.5%*If the incidence rate of a specific disease was found to be increasing or decreasing over several years, it is suggestive that the incidence of the disease is changing.

However, the researcher must be careful to investigate other possibilities such as changes in reporting mechanisms for newly diagnosed diseases or changes in the total population in the area as the cause of the change.To get the prevalence rate, we do most of what we did to find the incidence rate, only this time our numerator consists of the 50,000 newly diagnosed and add the 77,000 women who were diagnosed prior to 2004 and who are still living. Then we divide by the number of women living in Florida at the time – which we know was 1,999,000 – and multiply all that by 100.

We get a prevalence rate of 6.35%.*Prevalence rate = ((50,000 + 77,000) / 1,999,000) x 100 = 6.35%*If the prevalence rate of a specific disease was found to be increasing or decreasing, it suggests that the prevalence or penetration of the disease in the population is changing. This may be due to improved treatments and people living longer with the disease, but changes in reporting mechanisms or population changes must also be considered before determining the cause of the change.

## Lesson Summary

**Morbidity rate** allows us to track the occurrence and distribution of a disease or event in the population over a defined period of time. The two components of this are **incidence** and **prevalence**.

The incidence tells us the number of times the event was diagnosed in a defined time period. The prevalence tells us the number of current events, both newly diagnosed and previously diagnosed but still alive.27 children in a school are diagnosed with measles in February, an example of incidence. However, during that same month of February, 34 children had measles but 7 of them had been diagnosed in January and were still dealing with the symptoms in February, an example of prevalence.

In the following months the incidence may increase or decrease, but we cannot tell from these numbers if the disease incidence is really changing or parents are hiding cases from the school or calling every itchy red spot measles. Prevalence can be affected the same way or may indicate shorter or longer periods of symptoms.