HLTH 2110 Week 3 Disparity Analysis Example

Behavioral and Cultural Issues in Healthcare Walden University Free custom sample in 24 to 48h

This HLTH 2110 Week 3 disparity analysis example starts from one published number and stays with it: a pregnancy-related mortality ratio of 40.8 deaths per 100,000 live births for Black women against 12.7 for white women, 2007 to 2016, from Petersen and colleagues' CDC report. Walden HLTH 2110 asks BS in Public Health students to report a disparity exactly as its source states it, and the paper explains how deaths were identified, what the denominator was and how race was recorded. The report's own data then rule out education as a complete explanation, since the gap was larger among college graduates. Four explanations are weighed in turn: socioeconomic position, chronic conditions and causes of death, site of care drawing on Howell and colleagues and racism in care and conditions drawing on Jones and Hall and colleagues. None is allowed to become the default.

CourseHLTH 2110 Behavioral and Cultural Issues in Healthcare
WeekWeek 3
Paper typeDisparity analysis
LengthAbout 1,150 words, 7 pages
FormatAPA 7 student paper
SchoolWalden University
ProgramBS in Public Health
UpdatedOctober 2026

Free sample paper for HLTH 2110 Week 3

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Black Women's Pregnancy-Related Mortality Ratio of 40.8 Against 12.7 for White Women, 2007-2016: The Number as Published and Four Explanations, None Allowed to Become the Default

Student Name

Walden University

HLTH 2110: Behavioral and Cultural Issues in Healthcare

Instructor Name

Month Day, Year

What this page is doingThe title puts the published figures first and announces that explanations will be weighed rather than assumed, which is the discipline this analysis is graded on.
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Black Women's Pregnancy-Related Mortality Ratio of 40.8 Against 12.7 for White Women, 2007-2016: The Number as Published and Four Explanations, None Allowed to Become the Default

The Measured Difference

Between 2007 and 2016, the pregnancy-related mortality ratio (PRMR) in the United States was 40.8 deaths per 100,000 live births among non-Hispanic Black women and 12.7 among non-Hispanic white women, a ratio of 3.2 to 1 (Petersen et al., 2019). The PRMR for non-Hispanic American Indian and Alaska Native women was 29.7, 2.3 times the white rate. These figures come from CDC's Pregnancy Mortality Surveillance System, which collected 6,765 pregnancy-related deaths over the decade. The overall PRMR was 16.7.

How the populations were counted matters for what the number means. A pregnancy-related death is a death during pregnancy or within one year of its end, from a cause related to the pregnancy or aggravated by it; deaths from unrelated causes, such as an accident, are excluded. States send CDC death certificates for women who died during or within a year of pregnancy, with linked birth or fetal death certificates, and medically trained epidemiologists review each case to decide whether it was pregnancy-related. Rates are expressed per live birth rather than per pregnancy, and race and Hispanic origin come from vital records. Categories are mutually exclusive: Black and white refer to non-Hispanic women, and Hispanic women of any race form a separate group. This analysis concerns the Black-white difference only.

What the Report Itself Rules In and Out

The report's own data limit some explanations before any outside evidence is considered. The disparity did not change significantly over the decade. It appeared in every age group, and among women aged 30 and older the Black rate was roughly four to five times the white rate. It appeared at every level of education. Black women who had finished college died of pregnancy-related causes at 1.6 times the rate of white women without a high school diploma, and among college-educated women the Black rate was 5.2 times the white rate. The disparity also appeared in states with low, middle and high overall rates.

Citing review committees in 13 states, the report adds that roughly three in five of these deaths could have been prevented, and that the share did not differ significantly between racial and ethnic groups (Petersen et al., 2019).

Explanation 1: Socioeconomic Position

A common explanation is that Black women have, on average, lower incomes and less education, and that these, not race, drive the difference. The report's education data weigh heavily against this explanation as a complete account. If education explained the gap, college-educated Black women would have rates close to college-educated white women. Instead, the ratio was larger among college graduates than overall. Socioeconomic position may contribute to the overall rates, but it cannot explain why the gap persists, and widens, at the top of the education scale.

Explanation 2: Differences in Chronic Conditions and Causes of Death

A second explanation is that Black women enter pregnancy with more chronic conditions, such as hypertension, and die of different causes. The report found significant differences in the share of deaths from particular causes: cardiomyopathy, thrombotic pulmonary embolism and hypertensive disorders of pregnancy accounted for significantly larger proportions of deaths among Black women than among white women (Petersen et al., 2019). This explanation has support. But it moves the question rather than answering it: if chronic conditions are more common before pregnancy, the next question is why, and the answer leads back to conditions and care across a lifetime. It also does not explain the equal share of preventable deaths, which suggests that care during and after pregnancy matters regardless of prior conditions.

Explanation 3: Where Women Receive Care

A third explanation concerns the hospitals where women deliver. Howell et al. (2016) studied severe maternal morbidity, life-threatening complications at delivery, in a national sample of hospital discharges for 2010 and 2011. They found that 74% of deliveries to Black women occurred in a relatively small group of hospitals where Black patients made up a large share of deliveries, and that these hospitals had higher rates of severe maternal morbidity for both Black and white women after adjusting for patient characteristics. This points to quality differences between hospitals as part of the explanation. The study concerned morbidity rather than death, so it supports this explanation for deaths only indirectly.

Explanation 4: Racism in Care and in Conditions

A fourth explanation holds that racism, both in the conditions women live in and in how they are treated by health care systems, contributes to the gap. Jones (2000) describes racism operating at institutional, interpersonal and internalized levels; institutional racism could shape where hospitals are and how they are funded, while interpersonal bias could shape whether symptoms are taken seriously. A systematic review found that most studies measuring implicit bias among health care professionals found evidence of pro-white or anti-Black bias, and some linked it to differences in care and communication (Hall et al., 2015). This explanation is consistent with the education finding and with the hospital finding. It is also harder to measure directly than the others, and the report does not test it.

Weighing the Explanations

The evidence rules out socioeconomic position as a complete explanation and supports partial roles for chronic conditions and site of care. The racism explanation fits the pattern of the evidence but rests on studies other than the one that produced the number. None of the four should become the default, because each points to different action: the first to income support, the second to care before pregnancy, the third to hospital quality and the fourth to how institutions and clinicians treat Black women.

Table 1

Four Explanations Against the Report's Evidence

ExplanationConsistent with the evidenceNot consistent with the evidenceStatus |
Socioeconomic positionOverall rates differ by educationGap persists and widens among college graduatesInsufficient alone |
Chronic conditions and causesLarger share of deaths from cardiomyopathy, embolism and hypertensive disordersEqual preventability across groupsPartial; shifts the question to why conditions differ |
Site of careConcentration of Black deliveries in hospitals with higher morbidityStudy measures morbidity, not deathPartial; indirect for deaths |
Racism in care and conditionsGap at all education levels; hospital concentration; evidence of bias among cliniciansNot directly measured in the reportPlausible; not tested here |

No single row accounts for the whole difference, and the strongest evidence rules out only the first explanation as complete.

Conclusion

The published figure, a pregnancy-related mortality ratio of 40.8 for Black women against 12.7 for white women, is a measured difference with a clear definition and a known counting method. The report's own data show that the gap survives education, age and state. What produced it is not settled by the number, and an analysis that settles it by assumption would mistake the strongest explanation for the proven one.

References

Hall, W. J., Chapman, M. V., Lee, K. M., Merino, Y. M., Thomas, T. W., Payne, B. K., Eng, E., Day, S. H., & Coyne-Beasley, T. (2015). Implicit racial/ethnic bias among health care professionals and its influence on health care outcomes: A systematic review. American Journal of Public Health, 105(12), e60-e76. https://doi.org/10.2105/AJPH.2015.302903

Howell, E. A., Egorova, N., Balbierz, A., Zeitlin, J., & Hebert, P. L. (2016). Black-white differences in severe maternal morbidity and site of care. American Journal of Obstetrics and Gynecology, 214(1), 122.e1-122.e7. https://doi.org/10.1016/j.ajog.2015.08.019

Jones, C. P. (2000). Levels of racism: A theoretic framework and a gardener's tale. American Journal of Public Health, 90(8), 1212-1215. https://doi.org/10.2105/AJPH.90.8.1212

Petersen, E. E., Davis, N. L., Goodman, D., Cox, S., Syverson, C., Seed, K., Shapiro-Mendoza, C., Callaghan, W. M., & Barfield, W. (2019). Racial/ethnic disparities in pregnancy-related deaths: United States, 2007-2016. Morbidity and Mortality Weekly Report, 68(35), 762-765. https://doi.org/10.15585/mmwr.mm6835a3

The Walden HLTH 2110 Week 3 instructions

A disparity analysis asks you to start from a published difference and reason carefully about its causes. Report the number exactly as your source gives it, including the measure, the period and the groups compared. Explain how the populations were defined and counted, since that shapes what the number means. Note what the source's own data rule in or out. Then present competing explanations one at a time, with evidence for and against each. Avoid letting any single explanation become the assumed answer. A table summarizing the evidence can help. Conclude by stating what the number establishes and what remains unsettled. Use the source's own subgroup tables before turning to outside studies, since they often rule explanations in or out more directly than any later paper.

How this HLTH 2110 Week 3 example is built

The paper opens with the published mortality ratios and explains the surveillance system, the one-year definition, the live-birth denominator and the race categories. A section reports what the source itself shows: a gap that persisted over time, across ages, states and education levels. Four sections weigh explanations: socioeconomic position, which the education data weaken; chronic conditions and causes of death; site of care, from Howell and colleagues; and racism, from Jones and Hall and colleagues. Table 1 sets each explanation against the evidence. The conclusion separates the measured difference from its unsettled causes.

HLTH 2110 Week 3 rubric: what earns full marks

Faculty assess a disparity analysis on accuracy and restraint. The number must be reported exactly, with its source, period and definitions. Explaining how the populations were counted earns credit, since how people were counted limits what any number can say. Using the source's own data to test explanations is valued. Each explanation should receive fair treatment, with evidence for and against. Faculty often reward analyses that refuse to settle on one cause without support. Accurate citation is checked closely, since disparity figures are often misquoted. Papers that state a cause as fact, or that report a number without its definitions, earn less.

HLTH 2110 Week 3 help from the desk

Choose a disparity from a published report you can read in full, not from a news story. Copy the number exactly and write down how it was measured. Before reading explanations, look at what the report itself shows by age, education or place. Then list the explanations you have heard and look for evidence on each. Be willing to say that an explanation is partial or untested. Resist the urge to name one cause in your conclusion. We can help you build an analysis around a disparity you choose. Check your numbers against the source one final time before you submit. If the source defines terms differently from other reports, use the source's definitions throughout so your comparisons stay fair.

Get a HLTH 2110 Week 3 example written to your instructions

Attach the prompt, the rubric and the data source the section assigned; a finished analysis returns in 24-48 hours, the first without charge. Every figure is reported as its publisher states it, with year and units intact, and no explanation appears in the paper unless a citation stands behind it.

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HLTH 2110 Week 3 questions, answered

Where can I find a free HLTH 2110 Week 3 sample paper?

The analysis of the Black-white gap in pregnancy-related deaths, with its evidence table and references, is free to read on this page.

What number does the HLTH 2110 Week 3 example analyze?

Pregnancy-related mortality ratios of 40.8 for Black women and 12.7 for white women per 100,000 live births, 2007 to 2016.

How does the report rule out education as a full explanation?

The gap was larger among college-educated women than overall.

What explanations are weighed?

Socioeconomic position, chronic conditions and causes of death, site of care and racism in care and conditions.

Which explanation does the paper adopt?

None as the default; it finds partial support for several and treats racism as plausible but not tested by the report.