Week 5 Discussion: Measures used in Epidemiology

Week 5 Discussion: Measures used in Epidemiology

Week 5 Discussion: Measures used in Epidemiology

One important application of epidemiology is to identify factors that could increase the likelihood of a certain health problem occurring within a specific population. Epidemiologists use measures of effect to examine the association or linkage in the relationship between risk factors and emergence of disease or ill health. For instance, they may use measures of effect to better understand the relationships between poverty and lead poisoning in children, smoking and heart disease, or low birth weight and future motor skills. The following are some common measures used in epidemiology:

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  • Odds ratio: The odds ratio quantifies the association between an independent variable (exposure) and a dependent variable (outcome). It is calculated as the odds that an effect will occur given the presence or exposure to a studied variable, compared to the odds when there is no exposure (e.g., lung cancer and smoking)
  • Risk ratio (also called relative risk): Also quantifies the association between an independent variable and a dependent variable. The risk of an effect occurring in one population versus another population (e.g., preeclampsia in women <35 versus >35). Risks greater than one suggest that exposure to a given variable is associated with an increase in the risk of the outcome, and a risk ratio of less than one indicates that the exposure is associated with a decrease in the risk of the outcome.
  • Mortality: Measure of deaths in a particular population during a specified time interval. If this is attributed to a specific cause, it is referred to as cause-specific mortality.
  • Morbidity: Measure of instances of illness or disability in a population from a given cause (e.g., heart disease) during a specified time interval
  • Incidence: The occurrence of new cases of an effect or disease in a population over a defined time period relative to the size of the population at risk (e.g., new cases of COVID-19 in a population over a 7-day period/1000 people)
  • Prevalence: The number of all cases of an effect or disease, not just new ones, in a population at a given time relative to the size of the population (e.g., number of people with autism/1000)

What is the significance of these measures of effect for nursing practice? In this Discussion, you will consider this pivotal question.

Provided Resources to help with Assignment:

  • Curley, A. L. C. (Ed.). (2020). Population-based nursing: Concepts and competencies for advanced practice(3rd ed.). Springer.
    • Chapter 3, “Epidemiological Methods and Measurements in Population-Based Nursing Practice: Part I”
  • Friis, R. H., & Sellers, T. A. (2021). Epidemiology for public health practice(6th ed.). Jones & Bartlett.
    • Chapter 3, “Measures of Morbidity and Mortality Used in Epidemiology”
    • Chapter 9, “Measures of Effect”


  • Choose two of the following measures of effect to use for this Discussion. Consider the definitions, differences, and utility of each.
    • Odds ratio and risk ratio
    • Mortality and morbidity
    • Incidence and prevalence
  • Consider how these epidemiologic measures strengthen and support nursing practice.
  • Assess practice limitations of not using these measures in nursing practice.
  • Conduct additional research in the Walden Library and other credible resources, and then locate two examples in the scholarly literature that support your insights.

Post a cohesive scholarly response that addresses the following:

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  • Explain how your selected measures of effect strengthen and support nursing practice. Provide at least two specific examples from the literature to substantiate your insights.
  • Assess limitations of not using measures of effect in nursing practice.

A Sample Of This Assignment Written By One Of Our Top-rated Writers

Measures used in Epidemiology

Epidemiology is a public health science that explores factors that determine and influence diseases’ frequency, distribution, consequences, and health-related events. According to Curley (2020), understanding epidemiologic information regarding health conditions profoundly promotes population-centered care interventions and enhances people’s well-being. Also, epidemiology enables healthcare professionals and health policymakers to identify and address social health determinants (SDOH) contributing to health inequalities and disparities. For example, epidemiological data allow healthcare professionals to identify at-risk people and implement targeted strategies and policies to alleviate people’s exposure to diseases and prevent adverse events. The quality of epidemiologic data relies massively upon the applied measures. In this sense, incomplete information and misinformation can complicate the interpretation and application of epidemiological research (Hernandez & Kim, 2023). Consequently, this paper describes incidence and prevalence as ideal epidemiological measures, how they strengthen and support nursing practice, and practice limitations of not using these measures in nursing practice.

Incidence and Prevalence

Incidence and prevalence are interrelated epidemiologic measures that express the populations’ health status. However, they vary in definition and utility. Spronk et al. (2019) define the incidence rate as an epidemiologic measure that “represents the frequency of new occurrences of medical disorders in the studied population at risk of the medical disorder arising in a given time” (p. 1). It is possible to compute the disease’s incidence rate by dividing the total number of newly diagnosed cases by the population of the target community and multiplying it by a constant multiplier, including 1000 or 100000. Therefore, the incidence rate = (new cases)/(population) × n (Curley, 2020). The incidence rate is essential in providing information about the measure of risk and how often new cases occur.

Conversely, the disease prevalence rate describes the number of all cases within a population during a specific time. The formula for computing the disease prevalence rate is: (Total number of people with a condition or disease)/ (population in that community at a given time) × a constant multiplier (Curley, 2020, p. 63). Unlike incidence rates which provide the basis for measuring the community’s susceptibility to a disease, prevalence rates are a profound measure of the disease burden. Also, disease prevalence forms the basis of comparing population rates and increasing the attention toward addressing the disease’s burden.

How do these epidemiologic measures strengthen and support nursing practice?

Incidence and prevalence rates are requisites for evidence-based practices that target the alleviation of diseases’ burdens and risks. According to Friis & Sellers (2021), incidence rates can reveal the at-risk population and enable healthcare professionals to identify factors contributing to the population’s vulnerability to health conditions. For example, understanding the incidence rates of stroke among older adults in the United States at a given can allow healthcare professionals to study the population’s association with the disease. For instance, that can explore the role of aging in increasing the risk of stroke and study environmental and psychosocial risk factors for the disease. As a result, they can implement health promotion programs targeting to reduce people’s susceptibility to the studied disease.

Similarly, prevalence rates strengthen and support the evidence-based nursing practice by providing an ideal measure of the disease’s burden. Although disease prevalence does not provide information regarding the actual and perceived risk estimates, it can inform interventions focusing on primary and secondary prevention (Curley, 2020, p. 64). For example, understanding the prevalence rate of adult obesity in a community can prompt healthcare professionals and policymakers to implement interventions for alleviating the condition’s burden, including timely screening and detection, community-based education programs, and increased opportunities for physical exercise.

Practice limitations of not using these measures in nursing practice

The failure to incorporate information regarding diseases’ incidence and prevalence rates results in various practice limitations. Firstly, healthcare professionals cannot measure the actual and perceived risks of conditions in the studied population. Secondly, they cannot effectively estimate disease burdens without relying upon prevalence rates. Thirdly, the subsequent failure to define disease risks and burdens can compromise population-centered care (PCC). According to Curley (2020), population-based care emphasizes at-risk populations, recognizing health disparities, evaluating demographic factors, and analyzing aggregate data. Therefore, limited understanding and utilization of information regarding disease incidence and prevalence rates obscure the tenets of individualized and population-centered care, leading to fragmented care and a lack of prioritization in factors affecting the at-risk population.


Epidemiological measures provide information regarding diseases’ frequency, distribution, consequences, and health-related events. Incidence and prevalence rates are profound epidemiological measures that give information on newly diagnosed cases and the total number of cases at a given time. While incidence rates are effective measures of risks, prevalence rates provide information about the burden inflicted by the studied health condition. Therefore, the two epidemiological measures profoundly support nursing practices by justifying and informing population-centered interventions for addressing risks and alleviating burdens. Consequently, the failure to use incidence and prevalence rates can result in multiple limitations on nursing practices.


Curley, A. L. C. (Ed.). (2020). Population-based nursing: Concepts and competencies for advanced practice (3rd ed.). Springer.

Friis, R. H., & Sellers, T. A. (2021). Epidemiology for public health practice (6th ed.). Jones & Bartlett.

Hernandez, J. B. R., & Kim, P. Y. (2023). Epidemiology morbidity and mortality. StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK547668/#

Spronk, I., Korevaar, J. C., Poos, R., Davids, R., Hilderink, H., Schellevis, F. G., Verheij, R. A., & Nielen, M. M. J. (2019). Calculating incidence rates and prevalence proportions: Not as simple as it seems. BMC Public Health, 19(1), 1–9. https://doi.org/10.1186/s12889-019-6820-3

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