| Course | NU 780 Population Health |
|---|---|
| Unit | Unit 4 |
| Paper type | Social determinants and disparities analysis |
| Length | About 1,000 words, 6 pages |
| Format | APA 7 student paper |
| School | Herzing University |
| Program | MSN |
| Updated | October 2026 |
Free sample paper for NU 780 Unit 4
Why Hypertension Control Lags Among Black Adults in One Southern County: Proximate Causes and the Structures Behind Them
Student Name
Department of Nursing, Herzing University
NU 780: Population Health
Instructor Name
February 13, 2026
Why Hypertension Control Lags Among Black Adults in One Southern County: Proximate Causes and the Structures Behind Them
The Disparity
In a composite county in the Southeast, the health department's analysis of the regional health information exchange found a clear gap among adults with diagnosed hypertension seen in primary care during 2024: the last recorded reading was under 140/90 for 52% of White adults but for only 38% of Black adults. The county's pattern mirrors national data: in national survey data from 2013 to 2018, Black adults had higher hypertension prevalence and, among those treated, lower rates of control than White adults (Aggarwal et al., 2021). What this analysis asks is why the gap exists here, in terms specific enough to act on.
Social determinants of health are often described as a list of factors. That approach tends to end with poverty or education as general explanations. The alternative, argued by Braveman and Gottlieb (2014), is to follow the chain from the outcome back to the conditions that produce the proximate causes, the causes of the causes, and to name those conditions precisely.
Proximate Causes
Three proximate causes, closest to the outcome, were identified from a review of 60 charts of Black adults with uncontrolled hypertension at the county's two largest primary care sites and from interviews with eight patients. First, medication gaps: pharmacy refill records showed that 27 of 60 had a gap of more than 30 days in at least one antihypertensive prescription in the past year. Second, treatment inertia: in 22 of 60, blood pressure was elevated at two or more consecutive visits without a documented medication change. Third, diet: most interviewed patients described frequent use of convenience foods high in sodium. None of these is surprising. The analysis is useful only if it explains why these behaviors and clinical patterns occur more often among Black patients in this county.
Structural Conditions Behind the Medication Gaps
Two structural conditions explain most of the medication gaps. The first is the copayment structure. Many patients were enrolled in marketplace plans with high deductibles; until the deductible was met, a month's supply of two generic medicines cost $25 to $40, and patients reported rationing or skipping refills in months with unexpected bills. The second is pharmacy location. The two ZIP codes where most of the county's Black residents live lost two of their three pharmacies between 2019 and 2023. Patients without cars now travel to a pharmacy across the county, a trip of more than an hour each way by bus. Pharmacy closures are concentrated in segregated neighborhoods of color in other cities too (Qato et al., 2014). Neither cost nor distance is described here as poverty in general; each is a specific barrier with a specific remedy, such as a mail-order option, 90-day supplies, or a medication access program.
Structural Conditions Behind Treatment Inertia
Treatment inertia has structural roots too. Most Black patients in the chart sample were seen at the site with the shortest visit times, 15 minutes, and the highest share of patients with multiple chronic conditions. Clinicians interviewed said that when a patient arrives with several problems, blood pressure is often deferred. The practice had no protocol allowing nurses or pharmacists to adjust antihypertensives between visits. Clinician bias may also contribute: several patients described feeling that their reports of side effects were dismissed. The literature on structural racism describes how differences in resources, institutional practices, and interpersonal treatment combine to produce unequal outcomes even within the same health system (Bailey et al., 2017). The chart review cannot measure bias directly, but the unequal distribution of visit time and team resources between sites is measurable and was confirmed.
Structural Conditions Behind Diet
The sodium-heavy diet described by patients reflects the food environment and working conditions. The same two ZIP codes have no full-service grocery store; the nearest is four miles away. Several patients work shifts at two poultry processing plants, with long hours and no paid sick leave, which leaves little time for shopping or cooking and makes attending daytime clinic visits costly. These are not individual choices in any simple sense; they are conditions set by land use, employer practices, and labor policy.
Alternative Explanations and How to Test the Mechanism
Two alternative explanations were considered. The first attributes the gap to biological differences, such as salt sensitivity. Biological variation exists, but it cannot explain a difference in control among treated patients whose medication access and follow-up differ so sharply, and treating race as a biological cause risks obscuring the modifiable conditions described above. The second attributes the gap to health literacy or mistrust. Mistrust was mentioned by several patients and is itself a product of past and present experiences with health care, so it belongs in the structural account rather than outside it.
The mechanism proposed here makes predictions that can be tested with data the county already holds. If cost drives the medication gaps, gaps should be concentrated among patients in high-deductible plans and in the early months of the plan year. If pharmacy closures matter, gaps among residents of the two ZIP codes should have risen after the closures. If visit time and team resources matter, control should differ between sites even after accounting for patients' characteristics. Checking these predictions before designing the program would show which cause is largest.
What Is Modifiable, and by Whom
Separating proximate from structural causes shows which levels a nursing-led population program can change. Within reach of the health system: team-based blood pressure management with pharmacist or nurse titration between visits, 90-day and mail-order prescriptions, a medication cost review at every visit, and evening clinic hours. Within reach of partnership: mobile pharmacy services, and a produce voucher program with the local food bank. Beyond the program's direct reach, but relevant for advocacy: paid sick leave, the location of pharmacies and grocers, and insurance design. A prevention program that targets only individual behavior, such as sodium education, would address the proximate cause while leaving the conditions that produce it intact.
References
Aggarwal, R., Chiu, N., Wadhera, R. K., Moran, A. E., Raber, I., Shen, C., Yeh, R. W., & Kazi, D. S. (2021). Racial/ethnic disparities in hypertension prevalence, awareness, treatment, and control in the United States, 2013 to 2018. Hypertension, 78(6), 1719-1726. https://doi.org/10.1161/HYPERTENSIONAHA.121.17570
Bailey, Z. D., Krieger, N., Agenor, M., Graves, J., Linos, N., & Bassett, M. T. (2017). Structural racism and health inequities in the USA: Evidence and interventions. The Lancet, 389(10077), 1453-1463. https://doi.org/10.1016/S0140-6736(17)30569-X
Braveman, P., & Gottlieb, L. (2014). The social determinants of health: It's time to consider the causes of the causes. Public Health Reports, 129(Suppl. 2), 19-31. https://doi.org/10.1177/00333549141291S206
Qato, D. M., Daviglus, M. L., Wilder, J., Lee, T., Qato, D., & Lambert, B. (2014). "Pharmacy deserts" are prevalent in Chicago's predominantly minority communities, raising medication access concerns. Health Affairs, 33(11), 1958-1965. https://doi.org/10.1377/hlthaff.2013.1397
Reading the NU 780 Unit 4 instructions
Unit 4 asks you to analyze a health disparity in a population, identifying the social and structural determinants that produce it. Expect to describe the disparity with data, explain the causes at multiple levels from individual to structural, consider alternative explanations, and identify points of intervention. Many versions ask you to use a determinants framework, such as Healthy People 2030 domains or the WHO conceptual framework. Check whether your section expects a particular population or lets you choose. Handle race and ethnicity carefully, treating them as social categories that track exposure to structural conditions rather than as biological causes. Data from your county or health system make the analysis concrete. The paper should connect each structural condition to a specific proximate cause instead of listing determinants in general.
Inside the NU 780 Unit 4 example
The paper begins with the disparity in numbers, so the gap is clear before any explanation. Proximate causes come from a defined chart review, with the method stated briefly. Three sections then take each proximate cause and trace it to structural conditions, which is the move the assignment is built around. The medication section links gaps to copayment design and pharmacy access; the inertia section links it to visit length and site staffing; the diet section links it to food environment and work schedules. A section on alternative explanations considers biology and patient choice and says what evidence would distinguish them. The final section sorts causes by who can change them, which turns the analysis toward later program design.
Reading the NU 780 Unit 4 rubric
The rubric Herzing uses for a disparities analysis generally scores the description of the disparity, the analysis of determinants, the use of a framework, consideration of alternative explanations, implications for intervention, and writing. Disparity points require cited data comparing groups. Determinants are the core row; the highest marks need individual, community and structural factors tied to one another and to the outcome. Framework points reward accurate application of a named model, such as Braveman and Gottlieb's account of social determinants. Alternative explanations are often a separate row. Intervention implications earn credit when they match the level of each cause. Writing points include careful language about race and APA 7 citations, including Aggarwal and colleagues on national control trends.
NU 780 Unit 4 help: mistakes that cost points
The weakness in many Unit 4 papers is listing social determinants, poverty, education, housing, without connecting any of them to the specific outcome. Another is describing the disparity as a matter of patient choices or culture, which graders see as missing the structural level. Students sometimes treat race as a biological cause without evidence. Data showing the disparity are often national when local figures are available. Alternative explanations are frequently skipped. Recommendations that only address individual education do not match structural causes. Finally, be precise about mechanisms, such as how a copayment structure produces missed refills, because a vague link between a determinant and an outcome earns less credit than a traced pathway.
Get a NU 780 Unit 4 example written to your instructions
Send the Unit 4 instructions and the rubric from your NU 780 classroom, plus your community profile and the burden you are explaining. We write a custom example that separates proximate from structural causes and names what is modifiable, returned in 24 to 48 hours. The first custom sample is free.
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NU 780 Unit 4 questions, answered
How do I write about structural determinants specifically?
Say what the structure does. Not limited access to care but the nearest clinic accepting this insurance is eleven miles away and the bus does not run there after six. Not poverty but a thirty dollar copay against a weekly grocery budget. The concrete version can be addressed by a program; the abstract one cannot, and the rubric is looking for the first.
How should I handle race and ethnicity in the analysis?
As markers for conditions rather than as causes. A disparity by race reflects structures, historic and current, that distribute exposure, resources and treatment unevenly, and naming those is the analysis. Treating the category itself as explanatory stops the reasoning at the point where it should start, and faculty read it as a substantive weakness rather than a wording problem.
What does it mean for determinants to compound?
They multiply rather than add. Someone without transport and without paid sick leave and without a nearby clinic does not face three separate obstacles; they face a situation where any one of the three would be manageable and all three together make care effectively unavailable. Showing that interaction is a stronger analysis than treating each factor independently.
Where can I find a free NU 780 Unit 4 sample paper?
The full NU 780 Unit 4 hypertension disparity analysis is posted here without charge, from proximate causes to the structural conditions behind them. A custom analysis can address another disparity or population your section assigns.
What is the difference between proximate and structural causes of a health disparity?
Proximate causes act closest to the outcome, such as missed medications. Structural causes produce those conditions, such as copayment design or pharmacy closures. This sample traces each proximate cause of uncontrolled hypertension back to the structures behind it.