HLTH 5013 Module 1 Prevalence and Incidence Analysis Example

Nine in a Hundred, Nine in a Thousand: Calculating and Interpreting the Prevalence and Incidence of Diagnosed Type 2 Diabetes in a County

Student Name

American College of Education

HLTH5013: Epidemiology and Statistics

Module 1 Assignment

Instructor Name

October 5, 2026

The Question and the Data

A composite county health department in the Midwest wants to know how much type 2 diabetes it has and how fast new cases are appearing, because it is deciding whether to fund a diabetes prevention program or expand services for people already diagnosed. The two questions call for two different measures. Prevalence is a snapshot of how many people are living with a condition, taken on a date or across a span of time. Incidence describes how many new cases arise among people who did not have it, over a defined time.

The data come from a regional health information exchange that covers nearly all adults in the county who receive care, supplemented by census estimates. On January 1, 2025, the county had about 180,000 adults, of whom 16,740 had a recorded diagnosis of type 2 diabetes. During 2025, 1,410 adults without a previous diagnosis received one. The figures describe diagnosed diabetes only; people with undiagnosed diabetes are not counted, a limitation that affects both measures.

Point Prevalence

To get point prevalence, count everyone who has the condition on a chosen date and divide by everyone in the population on that date. Noordzij et al. (2010) describe prevalence as the proportion of a population that has the condition at a specific point or period, a measure that reflects the burden of disease and is useful for planning services. For the county:

Point prevalence = 16,740 / 180,000 = 0.093, or 9.3%.

About 9 in every 100 adults in the county were living with diagnosed type 2 diabetes at the start of 2025. That is the figure to use when planning services for people already affected, such as diabetes education, podiatry and eye examinations. It says nothing, by itself, about whether the problem is growing.

Incidence

Incidence counts only new cases among people at risk, meaning those who did not already have the condition. At the start of 2025, the population at risk was 180,000 minus 16,740, or 163,260 adults. Cumulative incidence, also called incidence proportion or risk, takes the new cases and divides them by the number who were free of the condition when the year began:

Cumulative incidence = 1,410 / 163,260 = 0.0086, or about 8.6 per 1,000 adults over one year.

An incidence rate uses person-time instead, because people leave the at-risk population during the year when they are diagnosed, move or die. Using the average population at risk, about 162,555, as an approximation of person-years gives an incidence rate of about 8.7 per 1,000 person-years. The two figures are close here because only a small share of the population developed diabetes during the year; with a common outcome or a long period, the difference would matter more. Prevalence tells the department how many people need care today; incidence tells it how quickly that number is being replenished.

How Prevalence and Incidence Are Related

When incidence and duration hold fairly steady, the size of the prevalent pool is set by two things together: the pace at which people enter it and the length of time they stay in it. For a condition that is not rare, the relationship is expressed as prevalence divided by one minus prevalence being approximately equal to incidence rate multiplied by average duration. Applied to the county, 0.093 divided by 0.907 is about 0.103, and dividing that by an incidence rate of 0.0086 per year gives an average duration of roughly 12 years.

The estimate is rough, since it assumes steady conditions that do not fully hold, but it is useful. Type 2 diabetes is a long-lasting condition, and improvements in treatment that help people live longer with it will raise prevalence even if incidence falls. A rising prevalence is therefore not, by itself, evidence that prevention is failing, a point the department should make when presenting the figures to its board.

Counting Only Diagnosed Cases

Both measures count only diagnosed diabetes, and the gap between diagnosed and total diabetes is large. The national diabetes statistics report estimates that 27.6% of U.S. adults with diabetes are undiagnosed (Centers for Disease Control and Prevention, 2026). If the county resembled the nation, its diagnosed prevalence of 9.3% would correspond to a total prevalence of about 9.3 divided by 0.724, or roughly 12.8%, meaning some 6,400 additional adults with diabetes who do not know it. That figure is an assumption rather than a measurement, since the undiagnosed share varies with access to care and screening, but it changes the planning picture.

The same issue distorts incidence. A diagnosis date is not the date the disease began; it is the date someone was tested. If the department or local clinics expand screening, recorded incidence will rise for a year or two as hidden cases are found, even if the true rate of new disease is unchanged. The department should therefore note any screening campaign alongside the incidence trend, and interpret a sudden increase with caution rather than as a sign that prevention is failing.

Crude Versus Age-Adjusted Comparison

The board also asked why a neighboring county reports a higher prevalence, 10.8%, than this county's 9.3%. Diabetes is strongly related to age, so differences in age structure can drive crude differences. The county's age-specific prevalence was 2.1% among adults aged 18 to 44, 12.1% among those aged 45 to 64, and 19.5% among those 65 and older. The neighboring county's figures were 2.3%, 12.9% and 21.0%, and a larger share of its adults were 65 or older.

Direct age adjustment asks what each county's overall prevalence would be if both had the same age mix, using a shared standard population, here the combined adult population of the two counties, of whom about 42% are 18 to 44, 33% are 45 to 64 and 24% are 65 or older. The age-adjusted prevalence is about 9.6% for this county and 10.4% for the neighbor. The gap shrinks from 1.5 percentage points to about 0.7, so roughly half of the crude difference reflects the neighbor's older population. The neighbor's rate is still higher in every age group, however, so age does not explain the whole difference.

What the Figures Mean for the Department

The two measures support different decisions. With about 9% of adults already diagnosed, services for people living with diabetes are a large and continuing need. With about 1,400 new diagnoses a year, a prevention program for adults at high risk could, if it reduced incidence even modestly, prevent a meaningful number of cases over a decade. Grimes and Schulz (2002) note that descriptive studies such as this one are the first step in epidemiology: they describe who, where and when, and generate hypotheses, but they cannot establish why. The next analyses should therefore look at incidence by age, neighborhood and insurance to target prevention, and should be repeated each year so the department can see whether incidence is changing.

References

Centers for Disease Control and Prevention. (2026, September 16). National diabetes statistics report. https://www.cdc.gov/diabetes/php/data-research/index.html

Grimes, D. A., & Schulz, K. F. (2002). Descriptive studies: What they can and cannot do. The Lancet, 359(9301), 145-149. https://doi.org/10.1016/S0140-6736(02)07373-7

Noordzij, M., Dekker, F. W., Zoccali, C., & Jager, K. J. (2010). Measures of disease frequency: Prevalence and incidence. Nephron Clinical Practice, 115(1), c17-c20. https://doi.org/10.1159/000286345