| Course | HLTH 4200 Principles of Epidemiology |
|---|---|
| Week | Week 4 |
| Paper type | Denominator audit |
| Length | About 1,020 words, 6 pages |
| Format | APA 7 student paper |
| School | Walden University |
| Program | BS in Public Health |
| Updated | October 2026 |
Free sample paper for HLTH 4200 Week 4
Did Elevated Blood Lead Fall From 13.0% to 5.5%? A Denominator Audit of Two Years in the Milford County Health Report, Rebuilt on a Common Base
Student Name
Walden University
HLTH 4200: Principles of Epidemiology
Instructor Name
Month Day, Year
Did Elevated Blood Lead Fall From 13.0% to 5.5%? A Denominator Audit of Two Years in the Milford County Health Report, Rebuilt on a Common Base
The Claim Under Audit
The Milford County Health Department's annual report, a composite for this exercise, states that the share of young children with elevated blood lead levels "fell from 13.0% in 2023 to 5.5% in 2024." Both percentages use one cutoff, 3.5 micrograms per deciliter, which became CDC's blood lead reference value in 2021 (Ruckart et al., 2021). The numerators are counted the same way. The denominators are not. This audit shows why the two percentages cannot be compared as published and rebuilds them on a common base.
The Two Denominators
In 2023, the county tested children aged 1 to 5 at four clinics serving neighborhoods with older housing, where lead paint exposure is most likely. In 2024, after a policy change, every pediatric practice in the county began offering a blood lead test at the 12-month and 24-month well-child visits, and testing continued at the four clinics.
The 2024 denominator is five times larger and contains a different mix of children. Most of the added children were tested because of their age, not because they lived in neighborhoods with older housing. A lower percentage among them is expected even if nothing changed for any child.
This problem is not unique to Milford County. National surveillance summaries of childhood blood lead levels draw on tests that states and localities choose to perform, and testing is often directed toward children considered at higher risk, so the share of tested children with elevated levels depends on who was tested and cannot be read as the share among all children (Raymond & Brown, 2017).
Table 1
The Two Published Percentages
| Year | Children tested | Results at or above 3.5 µg/dL | Percentage | Who was tested | |
|---|---|---|---|---|
| 2023 | 1,200 | 156 | 13.0% | Children at four targeted clinics | |
| 2024 | 6,000 | 330 | 5.5% | Children at the four clinics plus all well-child visits countywide | |
Figures are composite values for the exercise. Both years use the same threshold and the same laboratory.
Rebuilding on a Common Base
A fair comparison needs the same kind of children in both years. The 2024 records identify the testing site, which allows the 2024 results to be divided into two groups: children tested at the four targeted clinics, as in 2023, and children tested only through the new countywide well-child testing.
Comparing like with like, the four targeted clinics, the elevated share went from 13.0% in 2023 to 12.0% in 2024, a fall of 1.0 percentage point rather than 7.5. Whether even that difference is meaningful depends on chance variation; with about 1,200 children tested each year, a one-point difference is within what could be expected from year-to-year variation alone.
Table 2
2024 Results Divided by Testing Site
| 2024 group | Children tested | Results at or above 3.5 µg/dL | Percentage | |
|---|---|---|---|
| Four targeted clinics | 1,250 | 150 | 12.0% | |
| Countywide well-child testing only | 4,750 | 180 | 3.8% | |
| All 2024 testing | 6,000 | 330 | 5.5% | |
The two groups add to the published 2024 totals.
What the Audit Shows
The published fall from 13.0% to 5.5% is mostly a change in who was tested. Most of the apparent improvement comes from adding 4,750 children from lower-risk settings to the denominator. The audit does not show that lead exposure stayed the same; it shows that the published figures cannot tell. The comparable figure, from the targeted clinics, changed little.
The audit also reveals something the published trend hid. In 2024, the countywide testing found 180 children with elevated levels outside the targeted clinics. In 2023 those children were not tested, and some of them would have had elevated levels too. Expanding testing did not reduce the number of children with elevated lead; it found more of them. That is a success for the program, but it is a success of case finding, not of prevention.
Other Checks on Comparability
Three further questions should be asked before any trend is claimed. First, were the same specimen types used? Capillary tests from a finger stick can be contaminated by lead on the skin and give falsely high results; if the share of capillary tests changed between years, so would the percentage elevated. Second, were repeat tests on the same child counted once? Children with elevated results are retested, and counting tests rather than children inflates the numerator. Third, did the threshold stay the same? Before 2021, the reference value was 5 micrograms per deciliter (Ruckart et al., 2021); a series that crosses that change must be recalculated at a single threshold. The Milford figures use 3.5 throughout, but a longer trend would not.
What Would Make a Trend Possible
A trend in childhood lead exposure needs a denominator that stays the same kind of population from year to year. With universal testing at well-child visits now in place, the county can build one: children tested at their 12-month and 24-month visits, by year, using the same specimen rules and threshold. After two or three years of such testing, changes in the elevated share among those children could be read as changes in exposure, provided testing coverage at those visits stays high. Until then, the targeted clinic line is the only comparable series.
Recommendation for the Report
The report should present the 2024 figures in two lines, targeted clinics and countywide testing, and compare only the targeted clinic line with 2023. It should state the denominator for every percentage, describe the change in testing policy and avoid the word "fell" for any figure whose denominator changed. Defining populations, numerators and denominators before comparing rates is basic epidemiologic practice (Centers for Disease Control and Prevention, 2012), and the report's readers, including county officials deciding on lead abatement funding, need the comparable figure.
Conclusion
The report's two percentages look alike and are not. Rebuilt on a common base, the targeted clinics' elevated share went from 13.0% to 12.0%, not 13.0% to 5.5%. The larger apparent fall came from adding lower-risk children to the denominator, and the expanded testing found 180 additional children who needed follow-up.
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
Raymond, J., & Brown, M. J. (2017). Childhood blood lead levels in children aged <5 years: United States, 2009-2014. MMWR Surveillance Summaries, 66(3), 1-10. https://doi.org/10.15585/mmwr.ss6603a1
Ruckart, P. Z., Jones, R. L., Courtney, J. G., LeBlanc, T. T., Jackson, W., Karwowski, M. P., Cheng, P.-Y., Allwood, P., Svendsen, E. R., & Breysse, P. N. (2021). Update of the blood lead reference value: United States, 2021. Morbidity and Mortality Weekly Report, 70(43), 1509-1512. https://doi.org/10.15585/mmwr.mm7043a4
What the HLTH 4200 Week 4 instructions ask for
A denominator audit asks you to test whether two published percentages can be compared. Start by stating the claim and the threshold or definition both figures share. Then examine each denominator: who was counted, how they were selected and whether the group changed between periods. Present the published figures in a table with their denominators. If the data allow, divide the later figure into groups that match the earlier one, and rebuild the comparison on a common base. Explain what the audit shows about the original claim and what it reveals that the claim hid. List other checks on comparability, such as specimen types or definitions. End with a specific recommendation for how the figures should be reported, and avoid words like "fell" or "rose" for any comparison whose denominator changed.
Inside the HLTH 4200 Week 4 example
The audit opens with the report's claim and the shared threshold from Ruckart and colleagues. A section describes the two testing approaches and Table 1 sets out the published figures. Raymond and Brown's caution about targeted testing in national data follows. Table 2 divides the second year's results by testing site and rebuilds the comparison on the targeted clinics, showing a one-point change. A section explains that most of the apparent fall came from adding lower-risk children and that expanded testing found 180 more children needing follow-up. Sections cover other comparability checks and how to build a true trend, followed by a recommendation and conclusion.
HLTH 4200 Week 4 rubric: what earns full marks
Faculty grade a denominator audit on whether it identifies exactly how the denominators differ and rebuilds a fair comparison. Stating the shared definition first shows the student knows what must be held constant. Tables with numerators and denominators earn credit. Rebuilding on a common base is usually the most heavily weighted step. Faculty value audits that explain what the original figures did show, such as more children found, rather than only what they did not. Discussion of other comparability issues shows thoroughness. A concrete reporting recommendation adds credit. Audits that state the figures are not comparable without rebuilding them, or that ignore threshold changes, earn less.
Common HLTH 4200 Week 4 mistakes, and how to avoid them
Find the methods notes for each year's figure and write down exactly who was tested or counted. If the group changed, ask whether the later data can be split to match the earlier group; testing site, age or referral reason often allow this. Rebuild the comparison only on matching groups. Check whether the threshold, specimen type and counting rules stayed the same. Then write what the original claim got right as well as what it got wrong. A sample audit of figures from your own reading is something our team can draft. Before finishing, reread every percentage in your paper and confirm that its denominator is stated in the same sentence or table.
Get a HLTH 4200 Week 4 example written to your instructions
Paste the Week 4 prompt and rubric, and include the two figures or reports your section is comparing. The audit sets their numerators and denominators side by side, explains any mismatch as a mechanism and rebuilds the comparison on one base. Your first audit is free, delivered within 24-48 hours.
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HLTH 4200 Week 4 questions, answered
Where can I find a free HLTH 4200 Week 4 sample paper?
The denominator audit of a county's blood lead figures, with its rebuilt comparison tables and references, is free to read here.
What claim does the HLTH 4200 Week 4 example audit?
That elevated childhood blood lead fell from 13.0% to 5.5% between two years.
Why are the published percentages not comparable?
The first year tested only children at targeted clinics, while the second added children tested at every well-child visit countywide.
What does the rebuilt comparison show?
At the targeted clinics, the elevated share moved only from 13.0% to 12.0%.
What did expanded testing actually achieve?
It found 180 additional children with elevated levels who needed follow-up, a success of case finding rather than prevention.