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Obesity is a complex disease that involves excessive body fat deposition (Bray et al., 2017). High-energy foods such as fatty foods and sweetened drinks combined with modern sedentary lifestyles contribute to the development of obesity. Obesity causes psychological suffering due to its cosmetic concerns (Upadhyay et al., 2018). Other than the cosmetic concern, obesity detrimentally affects the liver, pancreas, heart, and other organs’ normal functions. The development of obesity is linked to the pathophysiology of fatal diseases, including diabetes mellitus, insulin resistance, dyslipidemia, hypertension, and atherosclerosis (Redinger, 2007). Due to the detrimental effects of obesity, it fits in the epidemiological model of a disease process despite having no pathogenic cause.

The rationale for selecting the topic of obesity is that obesity is becoming an ignored global pandemic. Further, the primary agent in disease development is food and lifestyle. The sedentary lifestyles and an appetite for fast, fatty foods and sweetened drinks have resulted in increased obesity cases globally. The condition can be diagnosed across populations regardless of age, gender, and region. Currently, there is a developing woke culture pushing for the appreciation of all body types and weights, making it hard to tackle the disease. Therefore, my selection of this topic is to develop data and critical information to help raise awareness of obesity, risk factors, and obesity care issues and tackle regional and global obesity to prevent the development of related illnesses eventually.

The project data on obesity will be collected through a mixed methods approach, applying both quantitative and qualitative research methods of data collection. Quantitative data collection methods within the positivistic research paradigm allow for collecting objective data from a sizeable blind sample. Quantitative data allows mathematical computation to explain causal relationships and highlight statistical differences in the research’s issues and factors of focus (Howlett, 2013). In this project, the causal relationships and statistical differences highlighted will help explain the relationship between risk factors for obesity and the identified obesity cases within the region. It will also help to measure the impacts of care interventions for obesity and other related issues. A naturalistic qualitative approach to data collection would have also benefited the research because it uses a small and uncontrolled sample (Howlett, 2013). The data collected focuses on the participants’ lived experiences regarding obesity. Further, data can be drawn not only from the participants but also from past research. Therefore, a mixed methods data collection strategy will utilize the advantages of naturalistic and positivist research paradigms while overcoming the limitations of the independent research methods.


Bray, G. A., Kim, K. K., & Wilding, J. P. H. (2017). Obesity: a chronic relapsing progressive disease process. A position statement of the World Obesity Federation. Obesity Reviews, 18(7), 715–723.

Howlett, B. (2013). Healthcare Research Methods. Evidenced-Based Practice for Health Professionals, 25–55.

Redinger, R. N. (2007). The Pathophysiology of Obesity and Its Clinical Manifestations. Gastroenterology & Hepatology, 3(11), 856. /PMC/articles/PMC3104148/

Upadhyay, J., Farr, O., Perakakis, N., Ghaly, W., & Mantzoros, C. (2018). Obesity as a Disease. Medical Clinics of North America, 102(1), 13–33.


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In Week 1, you will begin working on your course project, which will be completed in Week 5. This week, you will select a topic for your project (Topic 1: Disease Process or Topic 2: Healthcare Profession). You will use this and only this topic for the remainder of the 5 Weeks course Assignments.



In Weeks 2–4, you will complete weekly tasks for the selected topic, and in Week 5, you will present the course project in one formatted document.

Week 1 Tasks
Select one of the two topics below for your project and:

Provide a short definition or description of the topic.
Provide the rationale for choosing this topic.
Conclude with a high-level description of how you plan to collect the data for this project.
Complete a 300- to 350-word essay in a Microsoft Word document with appropriate references noted.

Topic 1: Disease Process Examples
Select a disease process from among the following:

Coronary artery disease
Alzheimer’s disease
Cancer (lung, colon, breast)
Next week, you will trace the continuum of care for this disease process in your geographic region. Select a specific payer type before beginning. Be sure to collect information on the following:

Socioeconomic issues
Primary care
Specialist referrals
Outpatient services
Hospital care
Tertiary care, if appropriate
Rehabilitation care, if appropriate
Managed care issues
Quality-of-care issues
Total cost of care
Support your answers with relevant examples.
Cite any sources in APA format.
Post your response to the Submissions Area by the due date assigned.

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