Epidemiologic Study DesignsThe Population Health Topic

The selected topic is the “correlation between cardiovascular disease and physical
exercise in elderly patients aged 65 and older.” Cardiovascular diseases (CDVs) typically refer to
diseases affecting blood vessels and the heart. CDVs include coronary heart disease (CHD),
cerebrovascular disease, peripheral arterial disease, rheumatic heart disease, congenital heart
disease, and deep vein thrombosis (Tran et al., 2021). Stroke and heart attacks are acute events
caused primarily by a blockage/obstruction preventing blood from flowing to the brain or heart.
Cardiovascular diseases are the number one cause of mortality worldwide. Approximately 17.9
million deaths were linked to cardiovascular diseases in 2019, accounting for roughly 32 percent
of all deaths globally. Of these, about 85 percent were due to stroke and heart attack (World
Health Organization, 2021). The most integral behavioral risk factors associated with CDVs,
mainly stroke and heart disease, are tobacco use, physical inactivity, unhealthy diets, and
uncontrolled alcohol intake. The impacts of these behavioral risk factors in CDVs may be
indicated by elevated blood pressure, blood glucose, blood lipids, and body mass indices (BMIs).
My project aims to measure whether a correlation exists between cardiovascular diseases
(CVDs) and physical activity, particularly among older adults aged 65 and above.
Research Question:
In people aged 65+ years (P), does physical activity (I), compared to lack of physical activity
(C), increase the risk of high blood pressure/hypertension (O) in four weeks?

Epidemiologic Study Design

A quasi-experimental study design is the most effective epidemiologic study design to
assess the correlation between physical activity and cardiovascular disease and potentially

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address the risk of CDVs. A quasi-experimental study design is a process of objectively
investigating variables (independent vs. dependent) in a controlled environment so that the
researcher optimizes precision and particular conclusions concerning a hypothesis statement
(Miller, Smith, & Pugatch, 2020). Like experimental designs, quasi-experimental designs are
classified as cause-and-effect approaches because they define the impact that an independent
variable (factor) can have on a dependent variable. The only difference is that quasi-experimental
study designs do not use random sampling. In this case, the independent variable is the “physical
exercise,” and the dependent variable is the “cardiovascular disease.” Therefore, the quasi-
experiment will measure the impact of “physical exercise” on the occurrence or severity of
“cardiovascular diseases.” Other parameters like BMI, cholesterol levels, and blood pressure will
be tracked to examine the increase, decline, severity, or risk of cardiovascular diseases.

Data Collection Activities

Questionnaire surveys, interviews, and direct observation are the most effective
techniques for collecting data. Since a quasi-experimental study design will be used, surveys and
direct observations are the most appropriate methods because subjects will be studied in their
natural environment. Patients (65+ years) diagnosed with cardiovascular disease will be
subjected to a uniquely-designed physical exercise program for four weeks. Pre-and-post
experimentation data will be kept on parameters like BMI, blood pressure, and cholesterol levels
– CVD indicators.

Methodologic Strategies

Purposeful/purposive/selective/judgmental sampling rather than random sampling is the
most appropriate strategy for the quasi-experiment to avoid ethical issues often associated with
using human subjects for experimentation (Lavrakas, 2019). Purposive sampling means the

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research team will subjectively choose study participants based on specific attributes. This will
ensure that only willing individuals with a known cardiovascular disease (those diagnosed) are
recruited. Participants must also be ready (through written consent) to participate in the study
and commit to the physical exercise program.

Strengths and Limitations of the Sampling Method Selected
Purposive sampling is a non-probability approach that focuses on selecting
subjects/participants based on the judgment and desires of the researcher (Lavrakas, 2019). The
one advantage of purposive sampling is that researchers can identify and focus on the specific
characteristics that will enable them to answer the proposed research question quickly, cost-
effectively, and satisfactorily. Since the researcher has the freedom to choose the particular
features they desire, purposive sampling is considered by many as more cost-effective and time-
effective than random sampling. The technique can also assist researchers in avoiding ethical
issues associated with human test subjects. However, purposive sampling is vulnerable to errors
in judgment by the researcher, has low reliability levels due to high bias levels, and does not
allow for the generalizability of research findings.

Ethical Considerations

Like other experimental or scientific studies involving human subjects, this research must
consider aspects to do with informed consent, respect for human dignity and life, and the
autonomy of the participants to withdraw from the experiment without retribution or
repercussions. Informed consent means that the researcher must explain the investigation’s
benefits, risks, and procedures and request the participants’ permission upon recruitment. The
methodology applied or assigned to the subject must also respect human life and not put them at
any potential risk.

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References

Lavrakas, P. J., et al. (2019). Experimental methods in survey research: Techniques that combine
random sampling with random assignment. John Wiley & Sons.
Miller, C. J., Smith, S. N., & Pugatch, M. (2020). Experimental and quasi-experimental designs
in implementation research. Psychiatry Research, 283.
https://doi.org/10.1016/j.psychres.2019.06.027
Reeves, B. C., Wells, G. A., & Waddington, H. (2017). Quasi-experimental study designs series-
paper 5: a checklist for classifying studies evaluating the effects on health interventions-a
taxonomy without labels. Journal of Clinical Epidemiology, 89, 30-42. doi:
10.1016/j.jclinepi.2017.02.016
Tran, D. T., Lekhak, N., Gutierrez, K., & Moonie, S. (2021). Risk factors associated with
cardiovascular disease among adult Nevadans. PLoS One, 16(2). doi:
10.1371/journal.pone.0247105
World Health Organization. (2021). Cardiovascular diseases (CVDs).
https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds)