| Course | HLTH 6205 Assessing Health and Wellness Needs for Communities |
|---|---|
| Week | Week 6 |
| Paper type | Peer reply |
| Length | About 360 words, 3 pages |
| Format | Discussion reply, APA 7 citations |
| School | Walden University |
| Program | MS in Health Education and Promotion |
| Updated | October 2026 |
Free sample paper for HLTH 6205 Week 6
Week 6 Discussion: Testing a Comparison
Reply to Jordan: Eau Claire County Against Wisconsin Sets a County Where One Adult in Five Is 18 to 24 Beside a State Where One in Eight Is, and an Age-Adjusted Neighbor Would Make a Fairer Referent
Jordan, you set Eau Claire County's 2023 binge drinking estimate of 20.0% (Centers for Disease Control and Prevention [CDC], 2025) beside Wisconsin's 18.4% (CDC, 2026) and read the 1.6-point gap as a sign that the county's adults binge drink more than adults statewide. I want to test whether those two groups are alike enough for the gap to mean anything.
They differ sharply on age. In the 2020 to 2024 American Community Survey, adults aged 18 to 24 make up 19.8% of Eau Claire County's adult population, compared with 11.8% of Wisconsin's (U.S. Census Bureau, 2025). Binge drinking in Wisconsin varies strongly by age, from 24.2% among 18- to 24-year-olds and 28.3% among 25- to 34-year-olds down to 6.5% among adults 65 and older (CDC, 2026). A county with a younger adult population will report a higher crude prevalence even if every age group drinks exactly as its statewide peers do. Some or all of your 1.6 points could be the age mix, not the county.
A fairer referent is available in the same CDC file. PLACES publishes an age-adjusted estimate for every county from the same model and year, so county can be compared with county without mixing a modeled figure and a direct survey figure. Eau Claire's age-adjusted estimate is 20.7% (95% CI 17.5% to 23.9%). Its neighbor Chippewa County, where only 8.8% of adults are 18 to 24, has an age-adjusted estimate of 22.3% (19.0% to 26.1%) (CDC, 2025).
Here is what I think would change if you made the substitution. On an age-adjusted basis, Eau Claire no longer stands out; it sits slightly below a neighbor with far fewer young adults, and the intervals overlap. The comparison would then say that Eau Claire's adults binge drink at roughly the rate of other west-central Wisconsin counties once age is held constant. Would you be willing to rerun your table with age-adjusted county figures and see whether your gap holds?
References
Centers for Disease Control and Prevention. (2025). PLACES: Local data for better health, county data, 2025 release [Data set]. https://data.cdc.gov/d/swc5-untb
Centers for Disease Control and Prevention. (2026). Behavioral Risk Factor Surveillance System (BRFSS) prevalence data (2011 to present) [Data set]. https://data.cdc.gov/d/dttw-5yxu
U.S. Census Bureau. (2025). American Community Survey 5-year estimates, 2020-2024 [Data set]. https://data.census.gov/
HLTH 6205 Week 6 instructions, in plain terms
Replies in the sixth week test a classmate's comparison between a local figure and a state or national one. The reply restates the comparison exactly, including which figure was set against which, so the challenge is specific. It then names one dimension on which the two groups differ, such as age structure, urban or rural setting, insurance coverage or an institutional population, and explains how that difference alone could produce the gap on the measure in question. A substitute referent follows, named concretely and obtainable by the classmate. The reply closes by predicting what would change if the substitution were made. Replies stay on the data rather than on the classmate's conclusions or interpretation. They are short and carry at least one APA reference. Most sections require two replies on different classmates' posts.
How the HLTH 6205 Week 6 example is put together
The sample opens by quoting the classmate's two figures and the conclusion drawn from them. Its second paragraph names age as the dimension, citing ACS data that put 18- to 24-year-olds at 19.8% of Eau Claire's adults and 11.8% of Wisconsin's. It connects that difference to binge drinking with state figures by age, from 24.2% and 28.3% in the younger groups to 6.5% at 65 and older, and explains that a younger county would report a higher crude rate even if every age group matched its state peers. The third paragraph proposes PLACES age-adjusted estimates and offers Eau Claire's 20.7% beside Chippewa County's 22.3%. The final paragraph predicts that Eau Claire would no longer stand out and asks the classmate to rerun the comparison.
Where the marks sit in the HLTH 6205 Week 6 rubric
These replies are graded on whether the challenge can actually be answered. Saying a comparison "may not be fair" without naming a dimension earns little, because the classmate has nothing to respond to. The strongest credit goes to the mechanism: the reply must link the difference between groups to the specific measure, not list contrasts. A proposed alternative referent earns the next block, scored partly on whether the classmate can obtain it. Predicting the consequence of the substitution adds further marks. Accuracy of every figure cited matters, since a reply built on a wrong number undermines its own point. Tone counts too; the reply should stay on the data and leave the classmate room to respond. APA citations for each source used complete the expectations.
HLTH 6205 Week 6 help from the desk
Week 6 replies often fall short by objecting in general terms, saying comparisons are tricky without naming why. Another frequent mistake is listing several differences between groups without explaining how any of them would affect the measure being compared. Some replies propose a better referent that the classmate cannot access, which helps no one. To write a stronger reply, restate the comparison in one sentence with both figures. Pick the single dimension most likely to drive the gap and find data showing the groups differ on it. Show how that dimension relates to the measure. Name a substitute referent and where to get it. Predict what would change. If your section needs replies on different classmates' comparisons, our writers can prepare drafts that address each post's specific figures.
Get a HLTH 6205 Week 6 example written to your instructions
Share the post being answered along with the prompt and rubric, and a sample reply comes back within 24-48h, free the first time. Where sharing a classmate's writing sits uncomfortably, a stand-in comparison is constructed to answer instead, and the shape of the challenge comes out identical. Nothing another person wrote is reproduced on any page here.
More HLTH 6205 papers and MS in Health Education and Promotion samples
- HLTH 6205 Week 1: Population Boundary Discussion Post
- HLTH 6205 Week 2: Calumet County Community Profile
- HLTH 6205 Week 3: Binge Drinking Data Source Review
- HLTH 6205 Week 4: County Binge Drinking Comparison
- HLTH 6205 Week 5: Drinking Patterns Survey Instrument
- HLTH 6205 Week 7: Key Informant Interview Plan
- HLTH 6205 Week 8: Adult Needs Prioritization Brief
- HLTH 6205 Week 9: Binge Drinking Needs Assessment
- HLTH 6205 Week 10: Binge Drinking Findings Report
- HLTH 6205 Week 11: Needs Assessment Summary Paragraph
- HLTH 6112 Week 6: Missing Federal Level Peer Reply
- HLTH 6110 Week 6: Artifact Claim Peer Reply
- HLTH 6051 Week 6: Standard Reach Peer Reply
- HLTH 6038 Week 6: Theory Comparison Paper
HLTH 6205 Week 6 questions, answered
Where can I find a free HLTH 6205 Week 6 sample paper?
A complete Week 6 peer reply challenging a comparison of Eau Claire County's binge drinking with Wisconsin's, with three references, is posted on this page.
What dimension does the HLTH 6205 Week 6 reply name?
Age structure: adults aged 18 to 24 are 19.8% of Eau Claire County's adults but 11.8% of Wisconsin's, and binge drinking differs sharply by age.
What substitute referent does the reply propose?
PLACES age-adjusted county estimates from the same model and year, such as Eau Claire's 20.7% beside neighboring Chippewa County's 22.3%.
Is age adjustment enough to fix a bad comparison?
It removes differences in age mix only; the reply still compares county with county from one model, because setting an adjusted figure against a crude state figure would mix methods.
Does the reply challenge the classmate's conclusion?
It stays on the data, predicting that Eau Claire would no longer stand out once age is held constant and inviting the classmate to rerun the table.