| Course | HLTH 8035 Epidemiology: Decoding the Science of Public Health |
|---|---|
| Week | Week 3 |
| Paper type | Measure interpretation |
| Length | About 600 words, 5 pages |
| Format | APA 7 student paper |
| School | Walden University |
| Program | PhD in Public Health |
| Updated | October 2026 |
Free sample paper for HLTH 8035 Week 3
Three Numbers in Plain Words: What the Risk Ratio, Risk Difference and Odds Ratio From a Composite Football Cohort Say About Midlife Memory Complaints, and What They Cannot Mean
Student Name
Walden University
HLTH 8035: Epidemiology: Decoding the Science of Public Health
Instructor Name
Month Day, Year
Three Numbers in Plain Words: What the Risk Ratio, Risk Difference and Odds Ratio From a Composite Football Cohort Say About Midlife Memory Complaints, and What They Cannot Mean
The Study
The composite study identified adults who played tackle football in adolescence and adults who played only non-contact sports, using school athletic rosters, and surveyed both groups decades later about memory complaints at midlife. The figures below are invented and labeled illustrative; they are chosen so that each measure can be read cleanly.
Table 1
Illustrative Results: Memory Complaints at Midlife
| Group | Reported complaints | Did not | Risk | |
|---|---|---|---|
| Former tackle players | 30 | 70 | 30 per 100 | |
| Former non-contact players | 20 | 80 | 20 per 100 | |
Risk ratio 1.5; risk difference 10 per 100; odds ratio about 1.7.
The Risk Ratio
The number. 30 per 100 divided by 20 per 100 gives a risk ratio of 1.5.
In plain words. Among former tackle players, memory complaints were half again as common as among former non-contact players.
What it cannot mean. It does not say that tackle football raises anyone's risk by half, because the groups were not randomized and may differ in other ways, such as later occupations or alcohol use. Nor does it reveal how many people the difference touches; a risk ratio of 1.5 can describe a rare outcome or a common one.
The Risk Difference
The number. 30 per 100 minus 20 per 100 gives a risk difference of 10 per 100.
In plain words. For every hundred former tackle players, ten more reported memory complaints than we would expect from a hundred non-contact players.
What it cannot mean. The ten are not identifiable people whose complaints football caused. It is a difference between groups, and like the ratio it carries any confounding the comparison contains. It does, however, give readers a sense of scale that the ratio hides.
The Odds Ratio in the Abstract
The number. The odds of complaints were 30 to 70 among tackle players and 20 to 80 among non-contact players, giving an odds ratio of about 1.7.
In plain words. The abstract's figure describes odds, not risks, and it is larger than the risk ratio.
What it cannot mean. It cannot be read as "1.7 times as likely." When an outcome is common, as here, the odds ratio moves further from 1 than the risk ratio does and so overstates the relative risk if read as one (Davies et al., 1998). A simple conversion using the risk in the unexposed group recovers the risk ratio from an odds ratio in cohort data with a common outcome (Zhang & Yu, 1998); with these figures it returns 1.5.
The Attributable Proportion Among the Exposed
If, and only if, the association were causal and unconfounded, the proportion of complaints among former tackle players attributable to tackle football would be (1.5 minus 1) divided by 1.5, or one third. That conditional matters. The figure describes what share of the exposed group's complaints the exposure would account for under causation; it is not evidence of causation, and it inherits every weakness of the comparison (Porta, 2014).
Which Measure for Which Audience
For a public reader or a parent, the risk difference comes first, since ten more per hundred is concrete and does not exaggerate. For a researcher comparing studies, the risk ratio is the natural summary. The odds ratio belongs in technical tables for designs that require it, such as case-control studies, and should be converted or explained when an outcome is common. The attributable proportion should appear only with its condition attached, never as a headline figure.
References
Davies, H. T. O., Crombie, I. K., & Tavakoli, M. (1998). When can odds ratios mislead? BMJ, 316(7136), 989-991. https://doi.org/10.1136/bmj.316.7136.989
Porta, M. (Ed.). (2014). A dictionary of epidemiology (6th ed.). Oxford University Press.
Zhang, J., & Yu, K. F. (1998). What's the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA, 280(19), 1690-1691. https://doi.org/10.1001/jama.280.19.1690
HLTH 8035 Week 3 instructions, in plain terms
The third week asks students to interpret epidemiologic measures from a study for readers who are not epidemiologists. A useful structure gives each measure three parts: the number and how it was calculated, a plain-language sentence and what the number cannot be taken to mean. The relative and absolute measures should both appear, since each hides what the other shows. Where a study reports an odds ratio for a common outcome, the interpretation should explain why it overstates the risk ratio and how to convert it. Any attributable measure should carry its causal condition. A closing section can rank the measures for different audiences. Sources on measure interpretation are cited in APA style.
How this HLTH 8035 Week 3 example is built
The sample describes the composite cohort and shows illustrative counts in a small table. It calculates a risk ratio of 1.5, translates it as half again as common and warns that it neither proves causation nor shows scale. It calculates a risk difference of 10 per 100, translated as ten more people per hundred. It shows how an odds ratio of about 1.7 arises from the same data and overstates the risk ratio for a common outcome, citing a conversion method that recovers 1.5. A short section gives an attributable proportion of one third, explicitly conditional on causation, and a final section recommends the risk difference for public readers and the risk ratio for researchers.
Where the marks sit in the HLTH 8035 Week 3 rubric
Measure interpretations are graded on accuracy and plain language. Faculty check calculations and reward sentences a non-specialist could follow without being misled. Including both relative and absolute measures earns credit, as does stating what each cannot mean. Explaining why an odds ratio overstates risk when an outcome is common, and showing a conversion, demonstrates understanding beyond formulas. Attributable measures must carry their causal condition. A ranking of measures by audience shows judgment about communication. Showing the arithmetic lets graders confirm each figure quickly. Interpretations that read an odds ratio as "times as likely" or present an attributable fraction as proven lose marks. Accurate citations complete the work.
HLTH 8035 Week 3 help: mistakes that cost marks
Measure interpretations often fall short by reporting numbers without translating them, or by reading the odds ratio as though it described risk. Another common problem is giving only a relative measure, which can make a small difference sound large. Some students also present attributable fractions as facts rather than conditional estimates. To write a stronger interpretation, lay out the counts first. For each measure, give the number, one plain sentence and one sentence on what it cannot mean. Show how the odds ratio relates to the risk ratio when outcomes are common. State causal conditions plainly. Recommend which measure suits which reader. If you need help interpreting study measures, our writers can help.
Get a HLTH 8035 Week 3 example written to your instructions
Attach the Week 3 prompt and rubric, and the article or table containing the measure your section must interpret. Each reported number is restated in plain words, paired with what it cannot be taken to mean, and checked against the design that produced it. The first sample is free, returned inside 24-48 hours.
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HLTH 8035 Week 3 questions, answered
Where can I find a free HLTH 8035 Week 3 sample paper?
A complete Week 3 interpretation of a risk ratio, risk difference and odds ratio from a composite football cohort, with three references, is set out beneath the facts table.
What does the risk ratio of 1.5 mean in the HLTH 8035 Week 3 example?
Memory complaints were half again as common among former tackle players as among former non-contact players, without showing that football caused them.
Why does the odds ratio overstate the risk?
Because complaints were common, the odds ratio of about 1.7 sits further from 1 than the risk ratio; a conversion using the unexposed risk returns 1.5.
What is the attributable proportion among the exposed?
One third, but only if the association is causal and unconfounded; it is not evidence of causation.
Which measure suits a public reader?
The risk difference, ten more people per hundred, because it is concrete and does not exaggerate the size of the difference.