NURS 8310 Week 3 Rate Standardization Problem Set Example

Epidemiology and Population Health Walden University Free custom sample in 24 to 48h

This NURS 8310 Week 3 problem set example answers, with illustrative figures, whether people experiencing homelessness in a composite county die at higher rates than other adults. Walden NURS 8310 asks DNP students to calculate and standardize rates, and five linked problems move from crude rates, which misleadingly show a lower homeless rate of 788 against 1,061 per 100,000 person-years, to age-specific rate ratios of 2.5, 1.6 and 1.1. Direct standardization with the county's adults as standard gives a ratio of about 1.29; indirect standardization gives a standardized mortality ratio of about 1.54 from 41 observed and 26.6 expected deaths. Each answer shows its denominator and period. The final problem flags the unstable oldest age group, cites Klein and Schoenborn on the 2000 standard and Hwang and Baggett and colleagues, and recommends what the county should report.

CourseNURS 8310 Epidemiology and Population Health
WeekWeek 3
Paper typeRate standardization problem set
LengthAbout 1,020 words, 6 pages
FormatAPA 7 student paper
SchoolWalden University
ProgramDoctor of Nursing Practice (DNP)
UpdatedSeptember 2026

Free sample paper for NURS 8310 Week 3

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Crude, Age-Specific and Standardized: Five Linked Problems on Whether People Experiencing Homelessness in One County Die at Higher Rates Than Other Adults

Student Name

College of Nursing, Walden University

NURS 8310: Epidemiology and Population Health

Instructor Name

Month Day, Year

What this page is doingThe title lists the three kinds of rate the problem set moves through and states the single question every problem serves.
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Crude, Age-Specific and Standardized: Five Linked Problems on Whether People Experiencing Homelessness in One County Die at Higher Rates Than Other Adults

The Question and the Data

The opening week's discussion showed that a median age at death cannot say whether people experiencing homelessness die at higher rates than other adults. This problem set answers that question with rates. It uses a composite county, and all figures are illustrative, constructed so that the arithmetic can be followed and checked. Every rate is written with its numerator, denominator, period and, where relevant, the standard applied.

Table 1 gives the data. For people experiencing homelessness, person-years at risk were estimated from shelter and outreach records linked across the year, and deaths were identified by linking those records to the state's death records, the approach cohort studies such as Hwang (2000) used. For the general adult population, person-years are mid-year population estimates and deaths come from vital statistics.

Table 1

Illustrative Person-Years and Deaths by Age Group, One Year

Age groupHomeless person-yearsHomeless deathsGeneral population person-yearsGeneral population deaths
18 to 443,0009350,000420
45 to 642,00022230,0001,610
65 and older20010120,0005,400
Total5,20041700,0007,430

Problem 1: Crude Death Rates

Question. Calculate the crude death rate for each group per 100,000 person-years.

Answer. Homeless: 41 deaths divided by 5,200 person-years, multiplied by 100,000, equals 788 per 100,000 person-years for the year. General population: 7,430 divided by 700,000, multiplied by 100,000, equals 1,061 per 100,000 person-years.

Interpretation. Taken at face value, the crude rates suggest that people experiencing homelessness die at a lower rate than other adults. That conclusion is wrong, and the next problems show why. The crude rate mixes the risk at each age with the age structure of the group, and the two groups have very different age structures: only 4% of homeless person-years are at age 65 and older, compared with 17% in the general population.

What this page is doingStating the misleading crude result first, and saying why it misleads, is what makes the later standardization meaningful.
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Problem 2: Age-Specific Rates and Rate Ratios

Question. Calculate age-specific death rates for each group and the rate ratio at each age.

Answer. Ages 18 to 44: homeless 9 divided by 3,000 equals 300 per 100,000 person-years; general 420 divided by 350,000 equals 120; rate ratio 2.5. Ages 45 to 64: homeless 1,100; general 700; rate ratio 1.6. Ages 65 and older: homeless 5,000; general 4,500; rate ratio 1.1.

Interpretation. At every age, people experiencing homelessness die at a higher rate. The excess is largest among younger adults, which matches the pattern Hwang (2000) reported among men using shelters. The crude rate hid this because most homeless person-years fall in the younger groups, where death rates for everyone are low. Age is acting as a confounder of the crude comparison (Rothman, 2012).

Problem 3: Direct Standardization

Question. Using the general adult population as the standard, calculate the age-standardized death rate for people experiencing homelessness and the standardized rate ratio.

Answer. The standard weights are each age group's share of general population person-years: 0.500, 0.329 and 0.171. The standardized rate is 300 times 0.500, plus 1,100 times 0.329, plus 5,000 times 0.171, which equals about 1,369 per 100,000 person-years. Because the general population is the standard, its standardized rate equals its crude rate, 1,061. The standardized rate ratio is 1,369 divided by 1,061, or about 1.29.

Interpretation. If people experiencing homelessness had the same age structure as the county's adults, their death rate would be about 29% higher. Direct standardization answers a hypothetical question, and the answer depends on the standard chosen. National reports in the United States commonly use the 2000 projected population as the standard (Klein & Schoenborn, 2001); using it here would give a different standardized rate, though the direction would be the same. Whatever standard is used, it should be named in every table, and the same standard should be used across years, or changes in the standardized rate may reflect a change in weights rather than a change in risk.

Problem 4: Indirect Standardization

Question. Using the general population's age-specific rates, calculate the expected number of deaths among people experiencing homelessness and the standardized mortality ratio.

Answer. Expected deaths equal the sum of homeless person-years at each age multiplied by the general population's rate at that age: 3,000 times 0.0012, plus 2,000 times 0.0070, plus 200 times 0.0450, which equals 3.6 plus 14.0 plus 9.0, or 26.6 expected deaths. Observed deaths are 41. The standardized mortality ratio is 41 divided by 26.6, or about 1.54.

Interpretation. People experiencing homelessness had about 54% more deaths than would be expected if they died at the general population's age-specific rates. The ratio differs from the directly standardized ratio of 1.29 because the two methods weight the age groups differently. The standardized mortality ratio uses the homeless group's own age structure, which is weighted toward younger adults, where the excess is largest. Indirect standardization is often preferred when the study group is small, because it does not rely on unstable age-specific rates from that group.

Problem 5: Stability and What the Rates Can Support

Question. Which result is least stable, and what should the county report?

Answer. The rate for people experiencing homelessness aged 65 and older rests on 10 deaths in 200 person-years. One or two more or fewer deaths would change that rate substantially, so the rate ratio of 1.1 at that age is too uncertain to interpret alone. The standardized mortality ratio, based on 41 observed deaths, is more stable, though still subject to random variation from year to year and to error in the person-years estimate.

Recommendation. The county should report age-specific rates with their counts, a standardized mortality ratio with its expected deaths and a note on how person-years were estimated. It should stop reporting the crude rate alone, which in this example points the wrong way, and should combine several years of data before drawing conclusions about the oldest group. With those changes, the county could state what Baggett et al. (2013) found in Boston: that mortality among people experiencing homelessness exceeds that of the general population once age is taken into account.

References

Baggett, T. P., Hwang, S. W., O'Connell, J. J., Porneala, B. C., Stringfellow, E. J., Orav, E. J., Singer, D. E., & Rigotti, N. A. (2013). Mortality among homeless adults in Boston: Shifts in causes of death over a 15-year period. JAMA Internal Medicine, 173(3), 189-195. https://doi.org/10.1001/jamainternmed.2013.1604

Hwang, S. W. (2000). Mortality among men using homeless shelters in Toronto, Ontario. JAMA, 283(16), 2152-2157. https://doi.org/10.1001/jama.283.16.2152

Klein, R. J., & Schoenborn, C. A. (2001). Age adjustment using the 2000 projected U.S. population (Healthy People 2010 Statistical Notes No. 20). National Center for Health Statistics.

Rothman, K. J. (2012). Epidemiology: An introduction (2nd ed.). Oxford University Press.

The Walden NURS 8310 Week 3 instructions

Problem sets on rates in this course usually ask you to calculate crude, age-specific and standardized rates from supplied or illustrative data and to interpret each result. Expect several pages with tables. Show every calculation with its numerator, denominator, period and units. Interpret each result in words before moving on, including results that mislead. Name the standard population used for direct standardization and explain why indirect standardization can give a different answer. Comment on which rates rest on few events and are unstable. Close with a recommendation about what should be reported and what should not, tied to the question the problem set was built to answer.

Inside the NURS 8310 Week 3 example

An opening section explains the question and gives Table 1 with person-years and deaths by age for both groups. Problem 1 calculates crude rates and explains why the lower homeless rate is misleading. Problem 2 gives age-specific rates and rate ratios and names age as a confounder, citing Rothman and Hwang. Problem 3 applies direct standardization with the county's adults as the standard and notes the 2000 US standard from Klein and Schoenborn. Problem 4 calculates expected deaths and the standardized mortality ratio and explains why it differs. Problem 5 identifies the unstable oldest group and recommends reporting, citing Baggett and colleagues. Every answer states its units, so a reader can check any figure against the table.

NURS 8310 Week 3 rubric: what earns full marks

Rate problem sets are usually graded on correct calculation, clear presentation, accurate interpretation and sound judgment about stability and reporting. Calculation credit depends on correct arithmetic with numerators and denominators shown. Presentation rewards labeled units, periods and standards. Interpretation is often weighted heavily and favors explaining why crude and standardized results differ. Judgment credit goes to identifying unstable rates and recommending appropriate reporting. Tables and citations make up the remainder. Instructors tend to reward problem sets that explain a misleading result rather than skipping past it. Some instructors also give credit for a sentence on why person-time suits a population whose membership changes during the year. Faculty also notice whether each answer is interpreted before the next problem begins.

Common NURS 8310 Week 3 mistakes, and how to avoid them

Problem sets lose marks when rates appear without denominators, periods or units. Another common loss is standardizing without naming the standard population. Some submissions compute a standardized mortality ratio without explaining why it differs from a directly standardized ratio. Others report rates from a handful of deaths as if they were precise. Show every step, interpret each result, name the standard, compare methods and flag unstable rates. The desk can draft a problem set using data your section supplies. Check each rate by estimating it roughly in your head before calculating, since an answer an order of magnitude off usually reveals a unit error.

Get a NURS 8310 Week 3 example written to your instructions

Forward the Week 3 problems exactly as your section posted them, plus the rubric and any data tables. Each answer is worked and then written as a full sentence that keeps its unit, denominator, period and standard. Free the first time, and it arrives in 24-48 hours.

More NURS 8310 papers and DNP samples

NURS 8310 Week 3 questions, answered

Why use person-time for this population?

Because membership changes constantly. People enter homelessness, leave it and sometimes return within one year, so counting them once overstates some exposure and misses the rest. Person-time adds up the days each person actually spent in the population. The example derives it from shelter enrollment dates, labeled illustrative. If your problems provide a midyear population instead, the custom answers use it and note the trade-off.

When is indirect standardization the better choice?

When the study group is small and its age-specific rates rest on few events, so they swing widely. Indirect standardization applies a reference population's stable rates to the group's age structure and compares expected deaths with observed deaths. The example shows both methods so the contrast is clear. Your prompt may require one; the custom set uses that method and explains why it fits.

Where can I find a free NURS 8310 Week 3 sample paper?

The complete five-problem set with worked answers and interpretations can be read here without charge. A problem set using your own section's data can be requested.

Why does the crude rate mislead in the NURS 8310 Week 3 problem set?

Only about 4% of homeless person-years fall at ages 65 and older, compared with 17% in the general population, so the crude rate hides higher death rates at every age.

Why do the direct and indirect results differ?

The directly standardized ratio weights age groups by the county's adults, while the standardized mortality ratio uses the homeless group's younger age structure, where the excess is largest.