*PUB 540 Explain the difference between relative risk, attributable risk, and population attributable risk*

PUB 540 Explain the difference between relative risk, attributable risk, and population attributable risk

Measures of effect between disease and the population are needed to track the association between exposure and outcomes. In Epidemiology according to Friis & Sellers (2020) there are three measures that track the by how many cases are associated with a certain factor, how much risk is added for disease exposure, and lastly how much dose that factor multiply the risk of that disease.

In relative risk association measures as discussed by the Centers for Disease Control and Prevention (2022) is also known as the risk ratio that compares the disease state in one group to another group.

Risk of disease=incidence proportion/attack rate (Group A) divided by Risk of disease=incidence proportion/attack rate (Group B). This is the relative risk value. What are the odds of a healthy individual contracting COVID and dying and an individual with COPD and Diabetes?

Another measure is figuring out the difference measure of association, also known as the attributable risk. How many people died from COVID or were hospitalized with co-morbid conditions compared to those that did not have co-morbid conditions? This also is known as the risk difference measure as discussed in the text by Friis & Sellers (2020). It is the incidence rate of in exposed individuals compared to the group of individuals that were not exposed. And, lastly this will lead us to the question of how many people in a population can attribute their illness to one exposure such as the spread of COVID-19 in the United States.

We can advocate in such was from our lessons on COVID-19, and what patients are at risk for serious disease that may lead to death. As discussed by Vela et al. (2022), risk stratification models have examined the data on the baseline health status of certain segments in the population. And, by determining which groups have the higher risk factors for exposure and death, we as health care professionals can make sure that resources such as the COVID-19 vaccines are targeted first to receive these resources.

### References

Friis, R. H., & Sellers, T. (2020). *Epidemiology for public health practice* (6th ed.). Jones & Bartlett Learning.

Centers for Disease Control and Prevention. (2022, May 17). *Principles of Epidemiology in Public Health Practice: An Introduction to Applied Epidemiology and Biostatistics* (2012). https://www.cdc.gov/csels/dsepd/ss1978/lesson3/section5.html

Vela, E., Carot-Sans, G., Clèries, M., Monterde, D., Acebes, X., Comella, A., García Eroles, L., Coca, M., Valero-Bover, D., Pérez Sust, P., & Piera-Jiménez, J. (2022). Development and validation of a population-based risk stratification model for severe COVID-19 in the general population. *Scientific Reports*, *12*(1), 1–10. https://doi-org.lopes.idm.oclc.org/10.1038/s41598-022-07138-y

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**Relative risk** can be viewed in an equational format. Simply it’s the incidence risk among exposed groups over the incidence risk among a non- exposed group. When there is a relative risk that is greater than one is indication that risks have increased due to factor exposure. In laments terms it’s how many times factor exposure would increase the incidence of an individual. In epidemiology relative risk is used for three possible calculations: risk ratio, rate ratio, and odds ratio. However, in order to use or determine relative risk one must have knowledge of those exposure and unexposed. For example, “If we hypothetically find that 17% of smokers develop lung cancer and 1% of non-smokers develop lung cancer, then we can calculate the relative risk of lung cancer in smokers versus non-smokers as: Relative Risk = 17% / 1% = 17” ( Tenny, 2021). This is simply saying that smokers are seventeen more times likely to develop lung cancer.

**Attributable risk **is how many times factor exposure would increase the incidence rate of a group. Looking at this

numerical attributable risk is equal to the incidence risk among an exposed group minus the incidence risk among a non-exposed group. Simply, it is the percent of the incidence of a disease in the exposed that would be eliminated if exposure was eliminated. An example would be if people wasn’t exposed to crystalline silica then there would not be the development of silicosis which is an interstitial lung disease. In epidemiology attributable risk are used to measure the vaccine efficacy and effectiveness (Principles of Epidemiology, 2012).

**Population Attributable Risk**: this is defined as the difference in incidence rates between people exposed to some risk factor verses the people not exposed. Simply, it depicts the additional risk with respect to entire population. In epidemiology that provides an overview of the number of people exposed verses who developed a disease or issue due to the exposure. For example, many people was exposed to COVID-19 however majority was asymptomatic but majority tested positive. Therefore, I suggest using this method of epidemiology in covid-19 prevention. While there is data to suggest the rate of infection, and we have an approximate exposure rate. Estimating the number of encounters we can calculate an approximate population attributable risk which can aid in covid-19 control measures.

__References:__

__References:__

Askari, M., & Namayandeh, S. M. (2020). The Difference between the Population Attributable Risk (PAR) and the Potentioal Impact Fraction (PIF). Iranian journal of public health, 49(10), 2018–2019. https://doi.org/10.18502/ijph.v49i10.4713

Centers for Disease Control and Prevention. (2012, May 18). Principles of Epidemiology. Centers for Disease Control and Prevention. Retrieved May 16, 2022, from https://www.cdc.gov/csels/dsepd/ss1978/lesson3/section6.html

Tenny S, Hoffman MR. Relative Risk. [Updated 2021 Mar 30]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK430824

**Relative risk** can be viewed in an equational format. Simply it’s the incidence risk among exposed groups over the incidence risk among a non- exposed group. When there is a relative risk that is greater than one is indication that risks have increased due to factor exposure. In laments terms it’s how many times factor exposure would increase the incidence of an individual. In epidemiology relative risk is used for three possible calculations: risk ratio, rate ratio, and odds ratio. However, in order to use or determine relative risk one must have knowledge of those exposure and unexposed. For example, “If we hypothetically find that 17% of smokers develop lung cancer and 1% of non-smokers develop lung cancer, then we can calculate the relative risk of lung cancer in smokers versus non-smokers as: Relative Risk = 17% / 1% = 17” ( Tenny, 2021). This is simply saying that smokers are seventeen more times likely to develop lung cancer.

**Attributable risk **is how many times factor exposure would increase the incidence rate of a group. Looking at this numerical attributable risk is equal to the incidence risk among an exposed group minus the incidence risk among a non-exposed group. Simply, it is the percent of the incidence of a disease in the exposed that would be eliminated if exposure was eliminated. An example would be if people wasn’t exposed to crystalline silica then there would not be the development of silicosis which is an interstitial lung disease. In epidemiology attributable risk are used to measure the vaccine efficacy and effectiveness (Principles of Epidemiology, 2012).

**Population Attributable Risk**: this is defined as the difference in incidence rates between people exposed to some risk factor verses the people not exposed. Simply, it depicts the additional risk with respect to entire population. In epidemiology that provides an overview of the number of people exposed verses who developed a disease or issue due to the exposure. For example, many people was exposed to COVID-19 however majority was asymptomatic but majority tested positive. Therefore, I suggest using this method of epidemiology in covid-19 prevention. While there is data to suggest the rate of infection, and we have an approximate exposure rate. Estimating the number of encounters we can calculate an approximate population attributable risk which can aid in covid-19 control measures.

__References:__

__References:__

Askari, M., & Namayandeh, S. M. (2020). The Difference between the Population Attributable Risk (PAR) and the Potentioal Impact Fraction (PIF). Iranian journal of public health, 49(10), 2018–2019. https://doi.org/10.18502/ijph.v49i10.4713

Centers for Disease Control and Prevention. (2012, May 18). Principles of Epidemiology. Centers for Disease Control and Prevention. Retrieved May 16, 2022, from https://www.cdc.gov/csels/dsepd/ss1978/lesson3/section6.html

Tenny S, Hoffman MR. Relative Risk. [Updated 2021 Mar 30]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK430824