CHL 610 Week 2 Secondary Data on Health Outcomes Example

Twelve Percent Here, Six Percent There: What Existing Data Reveal About Health in a Central Washington Neighborhood

[Student Name]

University of Phoenix

CHL/610: Community Health Assessment

Week 2 Assignment

[Instructor Name]

[Date]

The east side boundaries, partners, hospital and vital records summaries are composites written for a model paper modeled on Yakima, Washington; county, city and census tract estimates come from CDC PLACES, and research findings come from the sources cited.

At the steering committee's second meeting, the health district's epidemiologist presented the first look at existing data. Residents on the committee asked the questions that shaped her presentation: are we sicker than other places, is it worse on our side of town and why? This paper presents the secondary data review that answered those questions and the gaps it revealed.

Data Sources

The review used six sources: CDC's PLACES small-area estimates for the county, the city and census tracts; state vital records on births and deaths; hospital discharge data for preventable admissions; school district data on attendance; the County Health Rankings; and the hospital's own emergency department data by zip code.

How the CDC Estimates Are Made

PLACES estimates are modeled from national survey responses combined with census population data, not measured directly in each tract. They are useful for comparing places and spotting patterns but carry uncertainty, especially for small areas.

The County Picture

For Yakima County as a whole, CDC's 2023 estimates put diagnosed diabetes at 12.9% of adults and obesity at 39.7%, with 18.8% of working-age adults lacking health insurance, 27.9% reporting no leisure-time physical activity and 26.4% rating their health as fair or poor (Centers for Disease Control and Prevention [CDC], 2025a).

The City Compared

The city's estimates closely match the county's, with diabetes at 12.9%, obesity at 39.7%, uninsurance at 19.7% and inactivity at 28.1% (CDC, 2025b). Comparisons with other Washington cities are striking: Seattle's estimates are 6.1% for diabetes, 22.2% for obesity, 6.1% for uninsurance and 12.2% for inactivity. Spokane falls between, at 10.3% for diabetes and 8.2% for uninsurance. Pasco, another agricultural city with a large Hispanic population, resembles the city, with uninsurance at 21.7%.

Choosing Benchmarks

Benchmarks shape conclusions. Comparing the city only with the county hides its disadvantage, since the city drives the county's figures. Comparing it with Seattle shows the gap with the state's wealthiest city but may exaggerate what is achievable. The epidemiologist therefore used three comparisons: Seattle as an aspirational benchmark, Spokane as a mid-sized eastern Washington city and Pasco and Wenatchee as agricultural cities with similar economies.

Blood Pressure and Smoking

High blood pressure affects 33.2% of city adults, compared with 23.6% in Seattle, and 13.1% smoke, about double Seattle's 6.5%. Heart disease and stroke estimates follow the same pattern, reinforcing that the gap is not limited to diabetes.

Oral Health and Prevention

Only 56.1% of city adults visited a dentist in the past year, compared with 71.3% in Seattle, and 15.9% of adults 65 and older have lost all their teeth. Only 58.7% of city adults in the recommended age range had been screened for colorectal cancer on schedule, against 66.9% in Seattle.

Mental Health

Mental health estimates tell a less expected story. Diagnosed depression in the city, 23.1%, is slightly lower than Seattle's 25.1%, while frequent mental distress is higher, 18.1% versus 15.3%. A lower rate of diagnosis alongside higher distress may reflect less access to mental health care and stigma rather than better mental health, a question for focus groups.

Within the County

Averages conceal large differences. Across the county's 57 census tracts, uninsurance ranges from 7.4% to 38.9%, with 21 tracts at 25% or higher; inactivity ranges from 17.2% to 43.1%; fair or poor self-rated health from 15.7% to 42.5%; and diabetes from 8.9% to 18.8% (CDC, 2025c). In one tract, nearly four in ten working-age adults have no health insurance. The next phase will map exactly where the east side's own tracts fall within these ranges.

Vital Records and Hospital Data

State vital records show that east side zip codes have higher rates of teen births and of births with late or no prenatal care than the city overall. Hospital discharge data show higher rates of admissions for uncontrolled diabetes and asthma, conditions often manageable with timely primary care.

Why the Differences

The County Health Rankings offer a model for interpreting differences. Its conceptual model ranks counties on health outcomes and on health factors, grouped as behaviors, clinical care, the physical environment and social and economic conditions, drawing on more than 30 measures from national sources; the rankings reveal more than twofold differences within states on measures such as premature death and child poverty and are meant to stimulate community improvement (Remington et al., 2015).

Income and Health

Research on income points the same way. An analysis of 1.4 billion tax records linked with death records found that higher income was associated with greater longevity throughout the income distribution, with a gap of 14.6 years in life expectancy for men and 10.1 years for women between the richest and poorest 1% (Chetty et al., 2016). East side households earn well below the city median, and many work seasonal jobs without benefits.

A Summary Table

The epidemiologist's table lists each measure in rows, with columns for the city, the county, Seattle, Spokane and Pasco, the tract range and the data source and year. A final column flags measures where the east side likely differs most from the city average, pending primary data. One page lets committee members see every comparison at once.

Children and Families

School district data add a view of children. Chronic absence, missing ten percent or more of school days, is higher in the east side elementary schools than in the district overall, and school nurses report asthma and dental pain as common reasons. Child health data are thin in national surveys, so school and clinic records matter more for young residents.

Data Quality

Each source has limits. Model-based estimates may miss local conditions. Vital records are reliable but lag by a year or two. Hospital data reflect who seeks care, not who needs it. Survey data underrepresent people without phones and people who fear sharing information, a concern in immigrant communities.

What the Data Cannot Tell Us

Secondary data describe problems but not residents' priorities, experiences or explanations. They say little about mental health, housing conditions, workplace hazards for farmworkers or community strengths.

Questions for Primary Data

The review produced questions for the next phase: How do residents experience access to care? What do farmworkers face at work? How serious are housing and food problems? What do residents see as their community's strengths? Which problems do they want addressed first?

Presenting the Data

The epidemiologist presented findings in a short slide set with charts comparing the city with Seattle and Spokane and a tract map, avoiding jargon. Residents on the committee asked that future presentations include Spanish versions and explanations of what each measure means.

Conclusion

Secondary data show that the city, and especially its east side, carries a heavier burden of diabetes, obesity, inactivity and uninsurance than Washington's larger cities, with wide differences among tracts. The County Health Rankings model and income research point to social and economic conditions behind these gaps. Data limits and unanswered questions set the agenda for collecting residents' perspectives.

References

Centers for Disease Control and Prevention. (2025a). PLACES: Local data for better health, county data, 2025 release [Data set]. data.cdc.gov. https://data.cdc.gov/d/swc5-untb

Centers for Disease Control and Prevention. (2025b). PLACES: Place data (GIS friendly format), 2025 release [Data set]. data.cdc.gov. https://data.cdc.gov/d/vgc8-iyc4

Centers for Disease Control and Prevention. (2025c). PLACES: Local data for better health, census tract data, 2025 release [Data set]. data.cdc.gov. https://data.cdc.gov/d/cwsq-ngmh

Chetty, R., Stepner, M., Abraham, S., Lin, S., Scuderi, B., Turner, N., Bergeron, A., & Cutler, D. (2016). The association between income and life expectancy in the United States, 2001-2014. JAMA, 315(16), 1750-1766. https://doi.org/10.1001/jama.2016.4226

Remington, P. L., Catlin, B. B., & Gennuso, K. P. (2015). The County Health Rankings: Rationale and methods. Population Health Metrics, 13, Article 11. https://doi.org/10.1186/s12963-015-0044-2