What the Average Hides: Subgroup Rates of Blood Pressure Control and Three Measurable Disparities in a Composite County
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Doctor of Nursing Practice Program, Aspen University
DNP875: Population Health and Person-Centered Care
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Month Day, Year
What the Average Hides: Subgroup Rates of Blood Pressure Control and Three Measurable Disparities in a Composite County
An overall rate can mask large differences within a population. In the composite Delmont County hypertension population, 58.4 percent of adults had controlled blood pressure in 2025, but that average says nothing about who is being left behind. This paper compares control rates across subgroups defined by race and ethnicity, insurance, and preferred language, reports each comparison with counts, differences, ratios, and confidence intervals, and interprets which gaps represent disparities that the project should address.
Disparity as a Concept
Braveman (2006) uses the term disparity for a gap in health, or in what shapes health, that tracks social advantage and disadvantage, such as those linked to race or ethnicity, income, or other markers of social position, and that put already disadvantaged groups at further disadvantage. By this definition, not every difference is a disparity; a difference becomes a disparity when it follows the lines of social advantage. Measuring disparities requires comparing a group with a reference group, typically the most advantaged, using both absolute differences and relative measures.
Methods
Control was defined as the most recent 2025 blood pressure below 140/90 mm Hg across all 24,610 members of the defined hypertension population. For each subgroup, the control rate was calculated with its count. The rate difference, in percentage points, and the rate ratio were calculated against a reference group: non-Hispanic White adults for race and ethnicity, Medicare beneficiaries for insurance, and English speakers for language. Ninety-five percent confidence intervals for rate differences were calculated using the normal approximation. Race, ethnicity, and language were taken from patient self-report at registration; 4 percent of records lacked race or ethnicity and were grouped as other or unknown (Celentano & Szklo, 2019).
Results by Race and Ethnicity
Among non-Hispanic White adults, 10,470 of 17,230 had controlled blood pressure, 60.8 percent. Among non-Hispanic Black adults, 1,970 of 3,940, or 50.0 percent, were controlled, a difference of 10.8 percentage points (95% CI, 9.0 to 12.5) and a rate ratio of 0.82. Among Hispanic adults, 1,380 of 2,460, or 56.1 percent, were controlled, a difference of 4.7 points (95% CI, 2.6 to 6.8) and a ratio of 0.92. Among adults of other or unknown race and ethnicity, 540 of 980, or 55.1 percent, were controlled. The gap for Black adults is consistent with national survey data showing lower control among Black adults than White adults (Muntner et al., 2020).
Results by Insurance and Language
By insurance, control was 62.0 percent among Medicare beneficiaries (7,020 of 11,320), 59.9 percent among commercially insured adults (4,430 of 7,390), 53.4 percent among Medicaid enrollees (2,300 of 4,310), and 38.4 percent among uninsured adults (610 of 1,590). The difference between uninsured adults and Medicare beneficiaries was 23.6 percentage points (95% CI, 21.1 to 26.2), with a rate ratio of 0.62. By language, control was 48.2 percent among adults whose preferred language was Spanish (540 of 1,120) and 58.8 percent among English speakers (13,820 of 23,490), a difference of 10.6 points (95% CI, 7.6 to 13.6). The largest gap in the county runs along insurance lines: an uninsured adult with hypertension is about 40 percent less likely to be controlled than a Medicare beneficiary.
Interpreting the Disparities
All three gaps meet Braveman's definition: they are systematic, their confidence intervals exclude zero, and they follow lines of social disadvantage. They also overlap. Uninsured adults are disproportionately Hispanic and Spanish-speaking in the county, and Black adults are overrepresented among Medicaid enrollees, so the dimensions are not independent. A stratified check found that the Black-White gap narrowed to 7.9 points within the commercially insured group, which suggests that insurance explains part, but not all, of the racial gap. The remainder is consistent with the determinants identified in the previous module, including neighborhood conditions, experiences of discrimination, and trust in care (Havranek et al., 2015).
Absolute and relative measures tell complementary stories. The relative gap for Black adults, a ratio of 0.82, is the same as for Spanish speakers, but the absolute gap affects more people: about 3,940 Black adults versus 1,120 Spanish speakers. Closing the Black-White gap entirely would bring roughly 430 more Black adults to control, while closing the language gap would bring about 120 more Spanish speakers to control, and closing the insurance gap for uninsured adults would bring about 380 more.
Cautions in Interpretation
Several cautions apply. Clinic readings vary with technique, and if measurement practices differ by site, and sites differ by patient population, part of a gap could reflect measurement rather than true control; the project will check whether sites follow the same measurement protocol. Patients with fewer visits have fewer chances for a controlled reading to be recorded, so groups with less access may appear less controlled partly because they are seen less often. And rates for smaller groups, such as adults of other or unknown race and ethnicity, are less precise. None of these cautions erases the disparities, whose confidence intervals are well away from zero, but they shape how the project will investigate their causes.
Implications for Priorities
The analysis suggests three priorities. Uninsured adults have the lowest control and would benefit from enrollment assistance, low-cost medication programs, and care at the federally qualified health center regardless of ability to pay. Black adults represent the largest number of people affected by a racial gap and call for interventions built with trusted community partners and attention to continuity and communication in care. Spanish-speaking adults need interpreter access and translated materials at every visit. Each priority will be monitored with the same subgroup rates, so that the project can show whether gaps narrow as well as whether the average improves.
Conclusion
Delmont County's 58.4 percent control rate hides three measurable disparities: 10.8 percentage points between Black and White adults, 23.6 points between uninsured adults and Medicare beneficiaries, and 10.6 points between Spanish and English speakers, all with confidence intervals excluding zero. Reporting subgroup rates with counts, differences, ratios, and intervals turns an average into a map of where the population health project should focus.
References
Braveman, P. (2006). Health disparities and health equity: Concepts and measurement. Annual Review of Public Health, 27, 167-194. https://doi.org/10.1146/annurev.publhealth.27.021405.102103
Celentano, D. D., & Szklo, M. (2019). Gordis epidemiology (6th ed.). Elsevier.
Havranek, E. P., Mujahid, M. S., Barr, D. A., Blair, I. V., Cohen, M. S., Cruz-Flores, S., Davey-Smith, G., Dennison-Himmelfarb, C. R., Lauer, M. S., Lockwood, D. W., Rosal, M., & Yancy, C. W. (2015). Social determinants of risk and outcomes for cardiovascular disease: A scientific statement from the American Heart Association. Circulation, 132(9), 873-898. https://doi.org/10.1161/CIR.0000000000000228
Muntner, P., Hardy, S. T., Fine, L. J., Jaeger, B. C., Wozniak, G., Levitan, E. B., & Colantonio, L. D. (2020). Trends in blood pressure control among US adults with hypertension, 1999-2000 to 2017-2018. JAMA, 324(12), 1190-1200. https://doi.org/10.1001/jama.2020.14545
How this DNP 875 Module 4 example is structured
DNP875 Module 4 assignments frequently compare subgroup rates to expose a measurable disparity. Aspen does not publish module deliverables, so check your classroom for the exact prompt. This example defines disparity, states methods and reference groups, reports each comparison with full statistics, interprets overlap and magnitude and sets priorities with a monitoring plan.
DNP875 Module 4 questions, answered
What does DNP875 Module 4 usually ask for?
The module frequently asks you to compare rates of an outcome across subgroups of your population to identify and measure disparities. Aspen does not publish module deliverables, so your classroom's instructions govern.
What is the difference between a health difference and a health disparity?
A disparity is a difference in health or its determinants that is systematically associated with social advantage or disadvantage, such as race, income or insurance, and that further disadvantages groups already disadvantaged.
Why report both absolute and relative measures?
Relative measures such as rate ratios show how much worse one group fares proportionally, while absolute measures such as rate differences and counts show how many people are affected, which guides where effort can do the most good.
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