HLTH 4200 Week 3 Rate Calculation Example

Type 2 Diabetes in the Hartwell County Employee Health Plan: Prevalence on January 1, Incidence Across 2025, and Why the Second Figure Divides by a Smaller Group

Student Name

Walden University

HLTH 4200: Principles of Epidemiology

Instructor Name

Month Day, Year

Type 2 Diabetes in the Hartwell County Employee Health Plan: Prevalence on January 1, Incidence Across 2025, and Why the Second Figure Divides by a Smaller Group

The Population and the Data

The Hartwell County employee health plan, a composite used for this exercise, covers county employees, retirees and their adult dependents. Its claims and enrollment records show who was enrolled on each day and whether each member's claims carried a type 2 diabetes code. This calculation uses members aged 18 and older. A member is counted as having diagnosed type 2 diabetes if they had at least two outpatient claims or one inpatient claim with a type 2 diabetes diagnosis code, a common rule for identifying the condition in claims. Every figure below carries the population it was divided by.

Prevalence on January 1, 2025

Prevalence describes what share of a population is living with a condition at one chosen moment (Centers for Disease Control and Prevention, 2012). On January 1, 2025, 12,000 adults were enrolled, and 1,020 of them had diagnosed type 2 diabetes.

The plan's prevalence of 8.5% is similar to the national figure: in the 2016 and 2017 National Health Interview Survey, the weighted prevalence of diagnosed type 2 diabetes among U.S. adults was 8.5% (Xu et al., 2018). The resemblance should not be overread; the plan's members are working-age employees and retirees, not a national sample, and the national estimate was based on self-report rather than claims.

Table 1

Point Prevalence, January 1, 2025

Point prevalence counts everyone with the condition on that date, however long they have had it.

Incidence Across 2025

Incidence measures new cases. It asks how many people who did not have the condition developed it during a period (Centers for Disease Control and Prevention, 2012). That changes the denominator in two ways.

First, people who already had the condition cannot become new cases. The 1,020 members with diabetes on January 1 are removed, leaving 10,980 adults at risk.

Second, not everyone at risk was observed for the whole year. In 2025, 1,100 of the 10,980 at-risk members left the plan, on average halfway through the year. Their diagnoses after leaving are unknown.

During 2025, 92 at-risk members received a new diagnosis of type 2 diabetes: 84 among the 9,880 members enrolled for the whole year, and 8 among the 1,100 who left.

Cumulative Incidence Among Members Followed All Year

The simplest incidence measure uses only people observed for the full period.

Table 2

Cumulative Incidence, 2025

This measure ignores the 8 new diagnoses and the observation time contributed by members who left.

Incidence Rate Using Person-Time

A second measure keeps everyone, counting how long each person was observed while at risk.

Members stop contributing time at risk when they are diagnosed, because after that they are no longer at risk, or when they leave the plan, because after that they are no longer observed. The half-year assumptions are simplifications; with exact dates from the records, each member's time would be counted to the day.

Table 3

Person-Time and Incidence Rate, 2025

Incidence rate = 92 new diagnoses ÷ 10,388 person-years = 8.9 per 1,000 person-years.

Why the Incidence Denominator Is Smaller

The prevalence denominator was 12,000. The incidence denominators were 9,880 for cumulative incidence and 10,388 person-years for the rate. The incidence denominators are smaller for two reasons: people who already had diabetes were removed, because they could not become new cases, and time when members were not observed was removed, because diagnoses during that time could not be counted. Using 12,000 as the denominator for 92 new cases would understate incidence, at 7.7 per 1,000, by mixing people who could not have been new cases into the count.

How the Two Figures Relate

Prevalence and incidence answer different questions. Prevalence, 8.5%, describes the burden on January 1: how many members needed diabetes care. Incidence, about 8.5 to 8.9 per 1,000 per year, describes risk: how quickly new cases arose among those without diabetes. When conditions are stable, prevalence reflects both incidence and the length of time a condition lasts (Freeman & Hutchison, 1980). Because type 2 diabetes usually lasts for life, prevalence is many times larger than annual incidence: most of the 1,020 members with diabetes on January 1 were diagnosed in earlier years.

Choosing Between the Two Incidence Measures

The two incidence figures, 8.5 per 1,000 and 8.9 per 1,000 person-years, differ because they treat members who left the plan differently. Cumulative incidence is easier to explain, a proportion of people followed for a year, but it discards information from members who left and assumes their risk was the same as everyone else's. The person-time rate keeps all observed time and is preferred when follow-up is uneven, as it usually is in an insurance plan where people join and leave with their jobs. Reporting both, with their denominators, lets a reader see how much the choice matters.

Limits

Both figures count diagnosed diabetes only. Members with undiagnosed diabetes are counted as at risk and, if diagnosed during 2025, as new cases, even though their disease began earlier. Members who use little care may be diagnosed later than others, which affects both measures. Finally, the plan's population changes as people join and leave, so its prevalence on another date could differ even if no one's health changed.

Conclusion

On January 1, 2025, 8.5% of the plan's 12,000 adult members had diagnosed type 2 diabetes. Across 2025, new diagnoses arose at 8.5 per 1,000 among members followed all year, or 8.9 per 1,000 person-years when all at-risk time was counted. The incidence figures divide by a smaller group because they exclude people who already had the condition and time when members were not observed.

References

Centers for Disease Control and Prevention. (2012). Principles of epidemiology in public health practice: An introduction to applied epidemiology and biostatistics (3rd ed.). U.S. Department of Health and Human Services. https://archive.cdc.gov/www_cdc_gov/csels/dsepd/ss1978/index.html

Freeman, J., & Hutchison, G. B. (1980). Prevalence, incidence and duration. American Journal of Epidemiology, 112(5), 707-723. https://doi.org/10.1093/oxfordjournals.aje.a113043

Xu, G., Liu, B., Sun, Y., Du, Y., Snetselaar, L. G., Hu, F. B., & Bao, W. (2018). Prevalence of diagnosed type 1 and type 2 diabetes among US adults in 2016 and 2017: Population based study. BMJ, 361, Article k1497. https://doi.org/10.1136/bmj.k1497