HLTH 8574 Week 6 Cancer Disparities Memo Example

Course	HLTH 8574 Women's Health Issues
Week	Week 6
Paper type	Disparities memo
Length	About 630 words, 5 pages
Format	APA 7 student paper
School	Walden University
Program	PhD in Public Health
Updated	October 2026

Free sample paper for HLTH 8574 Week 6

Disparities Memo: Uterine Cancer Deaths Among Black and White Women Compared on One Axis, With Stage, Subtype, Income and Insurance Tested Inside That Comparison and the Surveillance Systems Behind Each Number Explained

Student Name

Walden University

HLTH 8574: Women's Health Issues

Instructor Name

Month Day, Year

What this page is doingThe title commits to one axis and names what will be tested inside it, which keeps the memo from becoming a list of every difference at once.

Purpose and Axis

This memo compares uterine cancer deaths among Black and White women in the United States on one axis, race. It does not try to cover every axis of difference at once. Instead, stage, tumor subtype, income and insurance are treated as conditions to test inside the race comparison: does the gap shrink, hold or grow when women are compared within the same stage, subtype or coverage? The memo also explains which surveillance systems produce the numbers and why their figures differ.

What this page is doingChoosing one axis and testing others within it keeps the comparison interpretable.

The Size of the Gap

National cancer statistics report that mortality from uterine corpus cancer is about twice as high among Black women as among White women (Siegel et al., 2024). Among common cancers, uterine cancer stands out because its death rate has been climbing rather than declining, and the rise is concentrated in the more aggressive nonendometrioid subtypes.

Why the Numbers Differ Across Systems

Three systems count these deaths, and each answers a different question.

The third row matters most for this comparison. Women who have had a hysterectomy cannot develop uterine cancer, and hysterectomy is more common among Black women. Rates that keep these women in the denominator understate risk for the group in which hysterectomy is most frequent. Clarke et al. (2019), correcting for hysterectomy using national survey data, found that corrected incidence rates were similar for Black and White women and that Black women had the lowest survival regardless of stage or subtype, while nonendometrioid cancers rose in every group.

Table 1

Surveillance Systems That Produce Uterine Cancer Mortality Figures

System	What it counts	Strength	What it cannot show \|
National vital statistics (death certificates)	All deaths in the country by cause	Complete national coverage	Stage, subtype or treatment at diagnosis \|
SEER incidence-based mortality	Deaths among women diagnosed in SEER registry areas	Links each death to stage and histology	Covers only part of the population \|
Hysterectomy-corrected rates	Same deaths, with women who have had a hysterectomy removed from the denominator	Counts only women who still have a uterus and are therefore at risk	Depends on survey estimates of hysterectomy \|

SEER registries covered about 26% of the U.S. population in the analysis by Clarke et al. (2022).

What this page is doingExplaining the denominator correction shows why the same deaths can yield different disparities.

Testing the Gap Inside Stage and Subtype

If Black women were simply diagnosed later or with more aggressive subtypes, the gap would shrink when women at the same stage and with the same subtype are compared. Using SEER incidence-based mortality with hysterectomy correction for deaths from 2010 to 2017, Clarke et al. (2022) found that corrected mortality rates were highest among Black women overall, within each histologic subtype and at each stage at diagnosis. They concluded that subtype distribution and stage do not fully explain the disparity.

What this page is doingReporting that the gap holds within stage and subtype is the central finding the one-axis design was built to test.

Testing Income and Insurance

Income and insurance are the next conditions to test, and the memo recommends doing so within the same framework rather than adding them as separate axes. SEER files carry area-level measures of income and, for recent years, insurance at diagnosis. The analysis would compare Black and White women with the same insurance type and similar area income, at the same stage and subtype. If the gap persists among insured women in higher-income areas, the explanation lies elsewhere, possibly in delays between first symptoms and diagnosis or in differences in treatment received.

Recommendation

A health department or cancer coalition reporting on uterine cancer should use hysterectomy-corrected rates when comparing groups, report mortality by subtype and stage, and test income and insurance within the race comparison. Reporting uncorrected national rates alone would understate the risk Black women face and hide the subtype trends driving the rise.

References

Clarke, M. A., Devesa, S. S., Hammer, A., & Wentzensen, N. (2022). Racial and ethnic differences in hysterectomy-corrected uterine corpus cancer mortality by stage and histologic subtype. JAMA Oncology, 8(6), 895-903. https://doi.org/10.1001/jamaoncol.2022.0009

Clarke, M. A., Devesa, S. S., Harvey, S. V., & Wentzensen, N. (2019). Hysterectomy-corrected uterine corpus cancer incidence trends and differences in relative survival reveal racial disparities and rising rates of nonendometrioid cancers. Journal of Clinical Oncology, 37(22), 1895-1908. https://doi.org/10.1200/JCO.19.00151

Siegel, R. L., Giaquinto, A. N., & Jemal, A. (2024). Cancer statistics, 2024. CA: A Cancer Journal for Clinicians, 74(1), 12-49. https://doi.org/10.3322/caac.21820

What the HLTH 8574 Week 6 instructions ask for

Students write a memo comparing a health outcome between two groups of women. Faculty expect a focused comparison on one axis, with other factors tested within it rather than added as separate comparisons. The memo should explain which data systems produce the figures and why their numbers may differ, since a disparity can look larger or smaller depending on the source. The strongest memos show whether the gap persists when groups are compared within the same stage, subtype or other condition, which helps rule explanations in or out. Recommendations for how the gap should be measured and reported are commonly expected. Evidence should come from national statistics and peer-reviewed analyses, and its audience is someone with authority to change how the gap is measured.

How this HLTH 8574 Week 6 example is built

The memo opens by stating its single axis and the conditions it will test inside it. A short section reports the twofold mortality gap from Siegel and colleagues and notes the rise in nonendometrioid subtypes. Table 1 compares three surveillance systems by what they count, their strengths and what they cannot show. A paragraph explains hysterectomy correction and reports Clarke and colleagues' 2019 findings on corrected incidence and survival. The next section reports their 2022 findings that corrected mortality was highest among Black women within every stage and subtype. A section proposes testing insurance and area income within the race comparison using SEER variables. The memo closes with a recommendation to use corrected rates and to report by subtype and stage.

Reading the HLTH 8574 Week 6 rubric

Faculty grade the memo on focus and on the handling of data sources. A memo that lists many disparities earns less than one that examines one comparison carefully. Credit rises when the memo explains how different systems produce different figures and why, especially when a correction changes the size of a gap. The central analytic credit goes to testing the gap within other conditions, here stage and subtype, and reporting what the test shows. Accurate reporting of published findings is checked. Faculty value a memo that sets up the next test, such as insurance and income, rather than claiming to have settled the cause. Recommendations should concern measurement and reporting as well as action. Clear writing for a decision-maker completes a strong memo.

HLTH 8574 Week 6 help: mistakes that cost marks

Disparities memos often report a gap and then list possible causes without testing any of them. To write a stronger memo, choose one axis of comparison and decide which other factors you will test inside it. Explain where your numbers come from and how different data systems might change the size of the gap. Look for an analysis that compares groups within the same stage, subtype or coverage, and report whether the gap holds. If the gap persists, say which explanations that rules out. Propose the next comparison that would narrow the cause further. Recommend how the gap should be measured and reported. A disparities memo on the comparison your section assigns can be prepared from these steps.

Get a HLTH 8574 Week 6 example written to your instructions

Attach your Week 6 prompt and rubric and name the comparison it asks for, whether race, insurance, rurality or age; the memo holds that single axis and sorts the measurement systems before any finding. A first custom sample is free and is delivered within 24-48 hours with every figure left to its source table.

More HLTH 8574 papers and PhD in Public Health samples

HLTH 8574 Week 6 questions, answered

Where can I find a free HLTH 8574 Week 6 sample paper?

The complete Week 6 disparities memo is published here, comparing uterine cancer deaths among Black and White women on one axis, explaining three surveillance systems and testing the gap within stage and subtype, with three references.

What is hysterectomy correction?

It removes women who have had a hysterectomy from the population at risk, since they cannot develop uterine cancer. Because hysterectomy is more common among Black women, uncorrected rates understate their risk.

Does the disparity disappear when stage and subtype are taken into account?

No. Clarke and colleagues found hysterectomy-corrected mortality highest among Black women overall, within each histologic subtype and at each stage at diagnosis, and concluded that subtype and stage do not fully explain the gap.

Why test income and insurance inside the race comparison?

Testing them within the comparison shows whether the gap persists among women with the same coverage and similar income. If it does, the explanation lies elsewhere, such as delays before diagnosis or differences in treatment.

Which data system should a health department use?

For comparing groups, hysterectomy-corrected rates give the clearest picture of risk among women who can develop the disease. National death certificate data remain useful for overall counts but cannot show stage or subtype.