NU450 Unit 5 Sample Paper

Community Assessment of Type 2 Diabetes Among Adults Aged 45 to 74 in Marion Ridge County: Findings, Determinants and a Population-Level Nursing Diagnosis

[Author Name]

School of Nursing, Purdue University Global

NU450 Public Health Nursing: Population-Centered Health Care in the Community

Unit 5 Assignment

[Instructor Name]

August 11, 2026

Marion Ridge County is a composite population written as a model document. No real county, agency, employer or resident is described.

What this page is doingThe title names the population, the age band, the county and the product of the paper, so a reader knows the scenario before the first paragraph. The course line carries Purdue Global's own vocabulary, Unit 5 Assignment, instead of a fabricated deliverable name, which keeps the page honest where the unit's exact requirement is not published. The closing line states plainly that the county is a composite. Graders reward a title that could belong to only one paper; a generic label such as Community Assessment Paper gives that credit away for nothing.

Community Description and Data Sources

Marion Ridge County is a composite rural county with an estimated 96,400 residents in 2024. One city of 31,200 holds roughly a third of them; the remaining 65,200 live across eleven townships, four of which sit more than twenty-five road miles from the county seat. Adults aged 65 and older make up 21.3 percent of residents. Median household income is 54,800 dollars, and 11.4 percent of adults aged 18 to 64 reported no health coverage in the 2024 county survey. Services consist of one 74-bed critical access hospital, three primary care clinics, one federally qualified health center, four retail pharmacies and an endocrinologist who visits two days each month.

Four sources support this assessment, each reported with the window it covers. County vital records supplied resident deaths for the five calendar years 2019 through 2023. The hospital system supplied a de-identified registry count of patients carrying a type 2 diabetes diagnosis as of December 31, 2023, with each patient's most recent glycated hemoglobin value from that calendar year. A telephone and mail survey modeled on the Behavioral Risk Factor Surveillance System (Centers for Disease Control and Prevention, 2024a) reached 1,842 adults between March 4 and June 28, 2024, a response rate of 31.6 percent of the 5,830 households contacted. Small-area estimates from PLACES (Centers for Disease Control and Prevention, 2024c) checked the survey against a second method and never replaced it.

A windshield survey covering the county seat and seven township centers was completed over four days in April 2024 along a fixed route of 212 miles, recording food retail, sidewalks, recreation space, transit stops and clinic signage. Nine key informants were interviewed for thirty to fifty minutes each: two public health nurses, the health center medical director, two pharmacists, an extension educator, the transit coordinator, a food pantry manager and the safety officer of the county's largest employer. Their accounts were read against the counted record rather than as evidence standing alone.

What this page is doingSources are named before findings, and each source is given the window it covers. That one move protects everything downstream: a reader who meets a prevalence figure on the next sheet already knows it came from a registry extract dated December 31, 2023 rather than from an estimate. The response rate is reported with the number of households contacted, so the survey can be weighed instead of trusted. Model-based small-area estimates appear as a cross-check rather than as data, which is the honest use of them.

Findings: Burden and Distribution

Diagnosed type 2 diabetes concentrates in middle and later adulthood. Of the 41,900 residents aged 45 to 74 in the 2024 population estimate, 6,150 appeared in the registry with a type 2 diabetes diagnosis on December 31, 2023, a diagnosed prevalence of 14.7 percent in that band on that date. The same registry counted 1,940 of the 29,600 residents aged 20 to 44, or 6.6 percent. Burden is not evenly spread. The four townships furthest from the county seat held 9,300 residents aged 45 to 74 and 1,720 registry patients, 18.5 percent, against 1,690 of the county seat's 14,100 residents in that band, or 12.0 percent.

Control, not prevalence alone, defines the problem here. Among the 4,880 registry patients aged 45 to 74 with at least one glycated hemoglobin result between January 1 and December 31, 2023, the most recent value stood above 9.0 percent for 1,586 patients, or 32.5 percent, and below 7.0 percent for 1,708, or 35.0 percent. The remaining 1,270 registry patients in that band had no value recorded in those twelve months and are counted here as unmeasured rather than controlled, because a missing result is not a normal one. Among respondents reporting diabetes (n = 214), 41.1 percent had ever attended a self-management session and 28.5 percent had stretched doses over cost in the past twelve months.

Downstream events follow the control pattern. The critical access hospital recorded 388 emergency department visits by residents aged 45 to 74 with a primary diagnosis of hyperglycemia or diabetic ketoacidosis between July 1, 2023 and June 30, 2024, or 9.3 visits per 1,000 residents in that band across that twelve-month window. Lower-extremity amputations among the same residents numbered 31 across the three fiscal years ending June 2024, an average of 10.3 per year, or 24.6 per 100,000 residents in that band per year. Diabetes was the underlying cause on 71 of the 4,320 resident deaths recorded from 2019 through 2023, a rate of 14.7 per 100,000 residents per year countywide, with 244 further deaths listing it as contributing.

What this page is doingEvery rate here carries its denominator and its window, and the denominators are deliberately not interchangeable. Prevalence is written against residents in the age band, control against measured patients only, and the mortality rate against the whole county because deaths were counted that way. Patients with no result recorded are held out as unmeasured instead of folded into the controlled group, which is where many assessments quietly improve their own numbers. Township figures show distribution, so the later etiology has somewhere to point.

Determinants, Capacity and Assets

Distance and retail structure shape what the county eats. The windshield survey found full-line grocery stores in three of the eleven townships; residents of the four highest-burden townships travel a median of 21 road miles to fresh produce, and the two convenience stores serving them stocked no fresh vegetables on either survey day. County transit runs a fixed route into the county seat on Tuesdays and Thursdays only, with the last return departure at 3:15 p.m., which places a midday clinic appointment and a grocery trip on the same round trip or on neither. In the 2024 survey, 22.8 percent of households (n = 1,842) had run out of food before they had money to buy more in the past twelve months.

Clinical capacity is thinnest where control is decided. The county holds one primary care clinician for every 2,140 residents against a statewide figure of one for every 1,340, and the endocrinologist's two clinic days each month produced a next-available appointment 96 days out. The health center employs two certified diabetes care and education specialists who together delivered 46 group sessions in the twelve months ending June 30, 2024, reaching 312 unique patients, or 5.1 percent of the 6,150 adults in the registry. Three of the four retail pharmacies close by 6:00 p.m. and none opens on Sunday, so a refill missed on Friday waits until Monday.

The county is not without means. The extension office runs a produce voucher program that enrolled 640 households at the 2024 summer market and already collects redemption data. A congregational network of eleven churches has trained twenty-two lay volunteers who take blood pressures at monthly gatherings. The largest employer, a food processing plant running 1,100 workers across three shifts, funds an on-site clinic its safety officer called underused. Two of the three primary care clinics already maintain the registry that produced the figures above, so a recall list needs no new software. These assets are counted because the diagnosis that follows must be answerable with what the county can reach.

What this page is doingDeterminants appear as observable facts with sources rather than as adjectives. A transit timetable and a next-available appointment date do work that a phrase like limited access cannot, because each can be checked and each names something that could change. Assets are counted with the same discipline: households already enrolled in a voucher program, volunteers already trained, a registry already running. Every clause of the etiology on the final sheet is drawn from this one, so nothing in the diagnosis arrives unprepared.

Priority Setting and Population-Level Nursing Diagnosis

Three candidate problems entered priority setting: uncontrolled type 2 diabetes among adults aged 45 to 74, adult tobacco use, and unmet behavioral health need. Each was weighed against population size, seriousness of consequences, the feasibility of a response the county could mount, and community concern. Adult smoking stood at 19.7 percent of respondents (n = 1,842) against roughly 11.6 percent nationally (Centers for Disease Control and Prevention, 2024a), a wider relative gap, but the county has no cessation staffing and the nearest tobacco treatment specialist practices 68 miles away. Behavioral health drew the loudest informant comment, yet the survey carried no validated screening item, so its magnitude cannot be stated with a denominator. Both are held for the next cycle.

Uncontrolled diabetes ranked first on all four considerations, and the population diagnosis for this cycle reads: risk for sustained hyperglycemia and its complications among adults aged 45 to 74 in Marion Ridge County, related to limited local access to diabetes self-management education, distance from fresh food retail, a transit schedule that forces a choice between a clinic visit and a grocery trip, and out-of-pocket medication cost; as evidenced by a most recent glycated hemoglobin value above 9.0 percent in 1,586 of 4,880 measured registry patients in that band during 2023, a further 1,270 patients with no value recorded that year, 9.3 hyperglycemia emergency visits per 1,000 residents in that band in the twelve months ending June 30, 2024, and 24.6 amputations per 100,000 in that band per year across the three fiscal years ending June 2024.

Written this way, the diagnosis can be judged rather than admired. The paired objective is to reduce the share of measured registry patients aged 45 to 74 whose most recent value exceeds 9.0 percent from 32.5 percent to 26.0 percent, and to cut the count with no value recorded in a calendar year from 1,270 to fewer than 800, both by December 31, 2025, drawn from the same registry extract that produced this baseline so that neither numerator nor denominator shifts under the intervention (Stanhope & Lancaster, 2020). Every clause of the etiology names something a county nurse can act on with the assets above, and every clause of the evidence names a number that can be pulled again in twelve months.

What this page is doingThe diagnosis follows the population format community health nursing uses: the risk, the population and place, the related-to etiology, and the as-evidenced-by data. No clause of the etiology is a personal failing, and each one is something the county can act on. The evidence clauses repeat the exact figures, denominators and windows from the findings sheet, so a reader can re-derive the diagnosis from the paper itself. The objective then restates it as a measurement, which is what makes evaluation possible at all.

References

Centers for Disease Control and Prevention. (2024a). Behavioral Risk Factor Surveillance System: Survey data and documentation. U.S. Department of Health and Human Services. https://www.cdc.gov/brfss/

Centers for Disease Control and Prevention. (2024b). National diabetes statistics report. U.S. Department of Health and Human Services. https://www.cdc.gov/diabetes/php/data-research/

Centers for Disease Control and Prevention. (2024c). PLACES: Local data for better health. U.S. Department of Health and Human Services. https://www.cdc.gov/places/

Office of Disease Prevention and Health Promotion. (2024). Healthy People 2030: Diabetes objectives. U.S. Department of Health and Human Services. https://health.gov/healthypeople

Stanhope, M., & Lancaster, J. (2020). Public health nursing: Population-centered health care in the community (10th ed.). Elsevier.

University of Wisconsin Population Health Institute. (2024). County health rankings and roadmaps: National findings report. https://www.countyhealthrankings.org

How this NU 450 Unit 5 example is structured

In many sections this unit asks for a community or population assessment that ends in a diagnosis; your classroom's instructions decide the exact form, so read the unit assignment page and the rubric before you use this NU450 Unit 5 example as a shape. The paper is ordered the way a public health nurse builds an argument. The community description comes first, with every source and collection window named, so a reader knows what the later numbers are made of. Findings follow, each rate written against the population it was drawn from and the period it covers. Determinants and assets come third, because a diagnosis needs an etiology and a county deserves credit for what it already holds. The diagnosis lands last, in population form, with the objective that would test it. Public Health Nursing: Population-Centered Health Care in the Community supplies the frame; the county itself is a composite.

NU450 Unit 5 questions, answered

What does NU450 Unit 5 usually ask for?

In many sections this unit asks for a community or population assessment: a defined population, data with named sources and windows, an analysis of determinants and assets, and a population-level nursing diagnosis at the end. Your classroom's instructions decide the exact form, so read the unit assignment page and the rubric before you use this example as a shape.

How is a population-level nursing diagnosis different from a patient one?

The subject is a group in a place, not a person. It names the population and the geography, states an etiology built from community conditions rather than individual behavior, and supplies evidence as rates with denominators and time windows. Written that way it can be evaluated later by pulling the same numbers again, which a patient-level diagnosis never has to support.

Can I submit this community assessment as my own work?

No. This is an original model document written by our desk to show what a finished community assessment looks like; it is not a student submission and carries no grade. Marion Ridge County is a composite and its figures are illustrative. Take the shape and the discipline about denominators, then write your own from data for your own community.

Write yours, or have the desk draft it

This paper is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.

NU450 Unit 5: sample paper, in real form