| Course | MPH 530 Epidemiology Concepts and Public Health Diseases (MPH/530) |
|---|---|
| Week | 3 |
| Paper type | Study design comparison paper |
| Length | about 1,152 words, 4 double-spaced pages plus title page and references |
| Format | APA 7 student paper |
| School | University of Phoenix |
| Program | MPH |
| Updated | September 2026 |
Free sample paper for MPH 530 Week 3
Four Designs, Four Questions: Choosing Between Case-Control, Cohort, Cross-Sectional and Randomized Studies to Test the County's Overdose Hypotheses
[Student Name]
University of Phoenix
MPH/530: Epidemiology Concepts and Public Health Diseases
Week 3 Assignment
[Instructor Name]
[Date]
The county health department, its hypotheses and proposed studies are composites written for a model paper; study findings come from the sources cited.
After the county's descriptive analysis of overdose deaths, the review team had three hypotheses: that fentanyl in the local supply drove most of the increase, that people using stimulants were exposed to fentanyl unknowingly and that people who received treatment after a nonfatal overdose were less likely to die later. A team member asked which of these could actually be tested, and how. The epidemiologist answered by explaining the main study designs and matching each to a question. This paper presents that explanation.
Designs and Questions
Each epidemiologic design answers a particular kind of question. Cross-sectional studies measure how common something is at one time. Case-control studies compare past exposures of people with and without an outcome. Cohort studies follow people with and without an exposure to see who develops an outcome. Randomized trials assign an intervention to test whether it causes a change.
Cross-Sectional Studies
A cross-sectional study measures exposure and outcome at the same time in a sample. It is fast and inexpensive and estimates prevalence, but it cannot establish which came first. For the county, a cross-sectional survey of people who use drugs could measure how many had unknowingly used fentanyl, using urine tests and interviews, answering the second hypothesis in part.
Case-Control Studies
A case-control study begins with cases, people with the outcome, and controls without it, and compares their past exposures. It is efficient for rare outcomes and produces odds ratios. The classic example is a British study of hospital patients: among 649 men with lung cancer, only 2 were nonsmokers, a far smaller proportion than among control patients, and the risk rose with the amount smoked (Doll & Hill, 1950). Two nonsmokers among 649 men with lung cancer made the case against tobacco before any trial was possible.
Strengths and Weaknesses of Case-Control Studies
Case-control studies are quick and suited to rare outcomes, but they are vulnerable to recall bias, since cases may remember exposures differently, and to selection bias in choosing controls. They cannot estimate incidence directly.
Cohort Studies
A cohort study identifies people by exposure and follows them over time. It establishes that exposure preceded the outcome, can study several outcomes and estimates incidence, risk ratios and hazard ratios. It is slower and costlier, especially for rare outcomes.
A Cohort Example From Overdose Research
A statewide cohort of 17,568 adults who survived an opioid overdose in Massachusetts linked records to see who received medication for opioid use disorder and who died over the following year. Compared with no medication, methadone was associated with lower all-cause mortality, with an adjusted hazard ratio of 0.47, and buprenorphine with an adjusted hazard ratio of 0.63; no association was found for naltrexone (Larochelle et al., 2018).
Ecologic Studies
Ecologic studies compare groups rather than individuals, such as overdose rates across states with different policies. They are inexpensive and useful for generating hypotheses, but they risk the ecologic fallacy: an association between group averages may not hold for individuals within the groups.
Hybrid Designs
Some studies combine features. A nested case-control study selects cases and controls from within a cohort, gaining efficiency while keeping the cohort's timing. A case-crossover design compares each person's exposure just before an event with their own exposure at other times, useful for transient triggers such as a new drug batch.
Randomized Trials
A randomized trial assigns participants by chance to an intervention or comparison, balancing known and unknown factors and providing the strongest evidence that an intervention causes an effect. The trial of diabetes prevention described earlier in the program randomly assigned adults with elevated glucose to lifestyle intervention, metformin or placebo; the lifestyle group developed diabetes at a 58% lower rate than the placebo group (Diabetes Prevention Program Research Group, 2002).
Why Not Always a Trial
Trials are expensive, slow and sometimes unethical or impossible. No one could randomly assign people to use fentanyl. For many public health questions, well-designed observational studies are the best available evidence.
Hypothesis One: Fentanyl and the Increase
Whether fentanyl drove the increase is best examined with the existing descriptive and toxicology data over time, an ecologic time-series approach, supplemented by review of death certificates. A new study design is not needed; the data already show fentanyl's growing role.
Hypothesis Two: Unknowing Exposure
A cross-sectional survey with drug testing among people who use stimulants, recruited through syringe services and treatment programs, would estimate how many had fentanyl in their system without knowing it. The design is feasible within months.
Hypothesis Three: Treatment After Overdose
A cohort study linking emergency department records of nonfatal overdoses with treatment records and death certificates would compare mortality among those who did and did not start medication treatment, following the Massachusetts approach. Data sharing agreements would be needed.
Measures of Association
The cross-sectional survey would produce prevalence and prevalence ratios; a case-control study, if used, odds ratios; the cohort, incidence rates and hazard ratios.
Bias and Confounding
In the cohort, people who start treatment may differ from those who do not in motivation, housing or insurance, which could confound the association with mortality. Adjusting for measured factors helps, but unmeasured differences may remain.
Loss to Follow-Up
Cohorts of people who use drugs are hard to follow; many move, lose phones or become homeless. Linked administrative records reduce this problem, since deaths and treatment are recorded wherever people go within the state. A cohort that relied on interviews would lose many participants and could be biased if those lost differed from those who stayed.
Choosing Among Imperfect Options
No design is perfect. The team accepted that the cohort would not prove causation, but judged that combining it with the existing trial evidence on medication treatment would give a strong enough basis for action, especially since the stakes, preventable deaths, are high.
Ethics
All studies require protection of sensitive information about drug use. The survey would use anonymous identifiers, and record linkage would occur under data use agreements with strict confidentiality.
Temporality
Establishing that exposure came before outcome is central to causal inference. Cross-sectional data cannot do this; case-control studies rely on recall or records; cohorts establish order by design. For the treatment question, the cohort's ability to show that treatment preceded survival is its main advantage.
Resources
The survey requires staff time and test kits; the cohort requires data agreements and analyst time. Both fit the department's capacity with a university partner.
Conclusion
Each of the county's hypotheses called for a different design: existing time-series data for fentanyl's role, a cross-sectional survey for unknowing exposure and a cohort for treatment and survival. Landmark and recent studies show what each design can do, from the case-control study that linked smoking to lung cancer to the cohort that tied medication treatment to survival and the trial that proved diabetes prevention. Matching design to question is the core skill.
References
Diabetes Prevention Program Research Group. (2002). Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. New England Journal of Medicine, 346(6), 393-403. https://doi.org/10.1056/NEJMoa012512
Doll, R., & Hill, A. B. (1950). Smoking and carcinoma of the lung: Preliminary report. BMJ, 2(4682), 739-748. https://doi.org/10.1136/bmj.2.4682.739
Larochelle, M. R., Bernson, D., Land, T., Stopka, T. J., Wang, N., Xuan, Z., Bagley, S. M., Liebschutz, J. M., & Walley, A. Y. (2018). Medication for opioid use disorder after nonfatal opioid overdose and association with mortality: A cohort study. Annals of Internal Medicine, 169(3), 137-145. https://doi.org/10.7326/M17-3107
What the MPH 530 Week 3 instructions ask
MPH 530 Week 3 usually asks students to describe and compare epidemiologic study designs. Prompts may ask students to explain cross-sectional, case-control, cohort and randomized designs, compare their strengths, weaknesses, costs and measures of association, give examples and choose an appropriate design for a public health question. Some versions ask students to critique a published study or to design one of their own for a local question. Follow the prompt your instructor posted. Strong papers match each design to the question it answers best, explain which measure of association each produces, discuss timing and temporality, recognize practical and ethical limits and illustrate each design with a real study.
How this MPH 530 Week 3 example is built
A review team member's question about which hypotheses could be tested, and how, opens the paper and frames the comparison of designs. The four main designs are defined in order of evidence strength for causal questions. A cross-sectional survey of people who use drugs shows prevalence of fentanyl exposure. A classic case-control study of smoking and lung cancer shows how cases and controls compare exposures. A cohort study of overdose survivors shows how treatment exposure relates to later deaths. A randomized trial of diabetes prevention shows experimental design. Each hypothesis is matched to a design, with feasibility, ethics, bias, measures of association and resources considered.
MPH 530 Week 3 grading rubric: where the points go
The study design week is typically graded on accurate definitions, sound comparison and good judgment in choosing a design. Graders look for clear descriptions of each design, the measure of association each produces, strengths and weaknesses including cost, time and bias, real examples, attention to ethics and a justified choice of design for a specific question. Landmark and recent peer-reviewed studies strengthen the paper considerably, especially when their numbers are reported accurately. Explaining why randomization is not always possible or ethical, and what replaces it, earns credit. A final portion of credit rewards clean organization and references. Papers that rank designs without considering the question, or confuse case-control with cohort studies, commonly lose points.
MPH 530 Week 3 help: mistakes to avoid
MPH 530 Week 3 papers often rank designs from weakest to strongest and stop. Start instead with the question: how common is something now, what exposures do cases share, what happens over time to people with and without an exposure, or does an intervention cause a change? Match each question to the design built for it. Name the measure each design produces, such as prevalence, odds ratio, risk ratio or hazard ratio, and what each can and cannot tell you. Weigh cost, time, bias and ethics. Illustrate each design with a real study you have read. Finally, explain the limits of the chosen design and how you would reduce bias, confounding and loss to follow-up.
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Other MPH 530 week samples
- MPH 530 Week 1: Measures of Disease Frequency
- MPH 530 Week 2: Descriptive Epidemiology
- MPH 530 Week 4: Bias, Confounding and Causation
- MPH 530 Week 5: Outbreak Investigation
- MPH 530 Week 6: Applied Epidemiologic Case Study
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MPH 530 Week 3 questions, answered
What does MPH/530 Week 3 usually ask for?
The third epidemiology paper typically asks students to describe and compare study designs, give examples and choose an appropriate design for a public health question.
Where can I find a free MPH 530 Week 3 sample paper?
The overdose study design paper above can be read without paying; each design carries a note. Tell us the question you need to study, and we draft the opening paper free.
What is the difference between a case-control and a cohort study?
A case-control study starts with people who have the outcome and compares their past exposures with those of people who do not; a cohort study starts with exposure groups and follows them to see who develops the outcome.
What measure of association does a case-control study produce?
Usually the odds ratio, because the study samples on outcome, so it cannot directly estimate incidence or risk in the population.
Why are some questions not studied with randomized trials?
Randomizing people to a harmful exposure would be unethical, and some exposures cannot be assigned, so observational designs are used instead.
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