| Course | HEP 444 Epidemiology |
|---|---|
| Module | Module 5 |
| Paper type | Epidemiology data analysis report |
| Length | About 705 words, 5 pages |
| Format | APA 7 student paper |
| School | Arizona State University |
| Program | BS in Health Education and Health Promotion |
| Updated | October 2026 |
Free sample paper for HEP 444 Module 5
Six Exposures and Hypertension: An Analysis of the 2023 National Health Interview Survey
Student Name
BS in Health Education and Health Promotion, Arizona State University
HEP 444: Epidemiology
Instructor Name
Month Day, Year
Six Exposures and Hypertension: An Analysis of the 2023 National Health Interview Survey
Purpose
This report examines six exposures associated with diagnosed hypertension among U.S. adults, estimates the strength of each association and judges which are most likely causal.
Data and Methods
Data came from the 2023 National Health Interview Survey adult public-use file, a nationally representative household survey (National Center for Health Statistics [NCHS], 2024). Of 29,522 sample adults, 29,471 answered whether a health professional had ever told them they had hypertension. Exposures were obesity (body mass index 30 or higher, from self-reported height and weight), diagnosed diabetes, ever being told of high cholesterol, current cigarette smoking, family income below the federal poverty level and age 65 or older. Adults with missing answers were excluded exposure by exposure.
For each exposure, I built a 2 × 2 table and calculated the prevalence of hypertension in exposed and unexposed adults, the prevalence ratio and the odds ratio, each with a 95% confidence interval using the log method. Because the survey is cross-sectional, prevalence ratios and odds ratios describe associations, not incidence. Estimates are unweighted; the survey-weighted prevalence of hypertension was 32.3%.
Results
Overall, 11,094 of 29,471 adults, 37.6% unweighted, reported diagnosed hypertension.
As an example, the obesity table had 4,776 obese adults with hypertension, 4,839 obese adults without, 6,085 non-obese adults with hypertension and 13,155 without. The odds ratio is (4,776 × 13,155) ÷ (4,839 × 6,085) = 2.13.
| Exposure | Prevalence exposed | Prevalence unexposed | Prevalence ratio (95% CI) | Odds ratio (95% CI) |
|---|---|---|---|---|
| Obesity | 49.7% | 31.6% | 1.57 (1.53 to 1.62) | 2.13 (2.03 to 2.24) |
| Diagnosed diabetes | 75.5% | 32.9% | 2.30 (2.24 to 2.36) | 6.30 (5.79 to 6.85) |
| High cholesterol | 63.5% | 25.0% | 2.54 (2.47 to 2.61) | 5.22 (4.95 to 5.50) |
| Current smoking | 40.7% | 37.4% | 1.09 (1.04 to 1.14) | 1.15 (1.06 to 1.24) |
| Income below poverty | 41.8% | 37.2% | 1.13 (1.08 to 1.18) | 1.22 (1.13 to 1.31) |
| Age 65 or older | 61.7% | 25.9% | 2.38 (2.32 to 2.45) | 4.61 (4.38 to 4.86) |
Interpretation
All six associations were statistically significant, because the sample is large, but they differed greatly in size. Diabetes, high cholesterol and older age were strongly associated with hypertension: adults with diabetes were 2.3 times as likely to report hypertension as those without. Obesity showed a moderate association. Smoking and poverty showed weak associations, with prevalence ratios near 1.1.
Odds ratios were larger than prevalence ratios for every exposure. When an outcome is common, as hypertension is here, the odds ratio overstates the prevalence ratio, so the prevalence ratio is the better summary for a cross-sectional survey.
These are crude estimates. Age is related to hypertension and to diabetes, high cholesterol and obesity, so part of each association may reflect age. The weak smoking association may also be distorted: smokers are younger on average, and some people quit after a diagnosis of heart or blood pressure problems, which would hide an effect. Stratifying by age or fitting a regression model would be the next step.
Hill's Criteria
A cross-sectional survey cannot establish temporality, which Hill (1965) treated as essential, so causal judgments rest on cohort and trial evidence beyond these data.
| Exposure | Strength | Temporality | Gradient and plausibility | Judgment |
|---|---|---|---|---|
| Obesity | Moderate | Unclear in this survey; established in cohort studies | Plausible through blood volume and vascular changes | Likely causal |
| Diabetes | Strong | Unclear; the two conditions share causes | Plausible through vascular and kidney damage | Strong association, shared causes likely |
| High cholesterol | Strong | Unclear | Shared lifestyle and age pathways | Association likely confounded |
| Smoking | Weak | Unclear | Acute blood pressure rise is plausible | Inconclusive here |
| Poverty | Weak | Unclear | Plausible through diet, stress and access | Inconclusive here |
| Age 65+ | Strong | Age precedes diagnosis | Arterial stiffening with age | A fixed risk marker |
Prevention Strategies
Weight loss, the DASH eating pattern, lower sodium intake, regular physical activity and limiting alcohol are recommended to prevent and treat high blood pressure (Carey & Whelton, 2018). In the DASH feeding trial, the combination eating pattern cut systolic pressure 5.5 points below the control diet's result within eight weeks (Appel et al., 1997). Community programs that support weight management and screening for adults with diabetes would target the strongest modifiable associations found here.
Limitations
All measures are self-reported, estimates are unweighted and crude, and the cross-sectional design cannot show which came first.
References
Appel, L. J., Moore, T. J., Obarzanek, E., Vollmer, W. M., Svetkey, L. P., Sacks, F. M., Bray, G. A., Vogt, T. M., Cutler, J. A., Windhauser, M. M., Lin, P.-H., Karanja, N., Simons-Morton, D., McCullough, M., Swain, J., Steele, P., Evans, M. A., Miller, E. R., & Harsha, D. W. (1997). A clinical trial of the effects of dietary patterns on blood pressure. New England Journal of Medicine, 336(16), 1117-1124. https://doi.org/10.1056/NEJM199704173361601
Carey, R. M., & Whelton, P. K. (2018). Prevention, detection, evaluation, and management of high blood pressure in adults: Synopsis of the 2017 American College of Cardiology/American Heart Association hypertension guideline. Annals of Internal Medicine, 168(5), 351-358. https://doi.org/10.7326/M17-3203
Hill, A. B. (1965). The environment and disease: Association or causation? Proceedings of the Royal Society of Medicine, 58(5), 295-300. https://doi.org/10.1177/003591576505800503
National Center for Health Statistics. (2024). National Health Interview Survey, 2023: Adult public-use data file [Data set]. Centers for Disease Control and Prevention. https://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/NHIS/2023/
What the HEP 444 Module 5 instructions ask for
The Epidemiology Data Analysis and Evaluation Short Report is the largest written assignment in HEP 444, worth 60 points, and the syllabus states it cannot be submitted late. For the topic and data your instructor provides, you analyze six exposures for one health outcome, compute the appropriate risk estimates, interpret them, apply Hill's criteria for causality and identify prevention strategies supported by research. Choose the measure that fits the design: risk or rate ratios for cohort data, odds ratios for case-control data and prevalence ratios or odds ratios for cross-sectional data. Show your 2 × 2 tables or calculations as the instructions require. Plan your time: the analysis takes longer than the writing, and the deadline is firm.
Inside the HEP 444 Module 5 example
The sample states its purpose, then describes the data source, sample, exposure definitions and calculations. A results table gives prevalence, prevalence ratios and odds ratios with confidence intervals for all six exposures, and one calculation is worked in full. The interpretation ranks associations by size, explains why odds ratios exceed prevalence ratios for a common outcome and discusses confounding by age. A Hill's criteria table judges each exposure, and the report ends with prevention strategies from a guideline and a trial and a short list of limitations. The data and methods section is specific enough that another student could repeat the analysis with the same public file. Confidence intervals appear beside every estimate rather than in a separate table.
HEP 444 Module 5 rubric: what earns full marks
The report is worth 60 points. Readers check that each risk estimate is calculated correctly from the 2 × 2 table, that confidence intervals are interpreted, that the measure fits the study design and that interpretation goes beyond statistical significance to strength and possible bias. Hill's criteria should be applied exposure by exposure, and prevention strategies should be supported by research. Marks drop for arithmetic errors, for treating statistical significance as proof of causation, for ignoring confounding and for prevention ideas without sources. Reports that discuss which estimate best fits the design and that propose the next analytic step, such as stratifying by age, show a level of understanding the rubric rewards.
HEP 444 Module 5 help from the desk
Lay out every 2 × 2 table the same way, exposure down the side and outcome across the top, with cells named a to d. Check one calculation by hand. Report every estimate with its confidence interval. Ask which exposures could be confounded by age or another factor. Say plainly what the design cannot show. Find one guideline and one trial for prevention. Submit early; late reports are not accepted. If your numbers look wrong, the desk can check your tables. Keep a spreadsheet of each table so you can recheck figures quickly. Round consistently to two decimals for ratios.
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 Arizona State University 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.
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HEP 444 Module 5 questions, answered
Where can I find a free HEP 444 Module 5 sample paper?
The full report analyzing six exposures for hypertension in the 2023 National Health Interview Survey is on this page.
How do I calculate an odds ratio from a 2 × 2 table?
Multiply a by d, then divide by b times c.
Why are odds ratios larger than prevalence ratios for common outcomes?
When an outcome is common, odds grow faster than proportions, so the odds ratio overstates the prevalence ratio.
Can a cross-sectional survey show causation?
No; it cannot establish that exposure came before the outcome.
Can the HEP 444 data report be submitted late?
No; the syllabus states this assignment cannot be submitted late.