# 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

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

Relative risk is also known as measure of effects which provides a ratio of the risk of events such as diseases for the exposed group to risk of unexposed group (Friss & Sellers, 2021). It identifies the ratio of probability of event from exposed group to probability of even from not exposed group. An example is finding the relative risk for group of people who ate seafood and suffered diarrhea to people who did not eat seafood but suffered diarrhea. There are 25 people suffered diarrhea out of 37 people who ate seafood, resulting to .68 probability for exposed group. The unexposed group has 5 individuals who suffered diarrhea out of 33 people who did not eat seafood resulting to .15 probability for unexposed group. Therefore, the relative risk is 4.53.

The attributable risk is also known as risk difference which refers to the difference between the incidence rate of event or disease with the exposed group and the incidence rate of event or disease from unexposed group (Friis & Sellers, 2021). Utilizing the scenario above as example the risk difference is .52.

The population attributional risk or also know as population risk difference is defined as the proportion of disease in the area of population which reflect to the exposure (Friis & Sellers, 2021). Utilizing the scenario above the population attributional risk is 65.2 %. Population attributional risk is presented in percentage with confidence interval of when the relative risk is greater than or equal to one ( Sahai and Kurshid, 1996 as cited in Stats Direct, n.d.)

Statistics are used in research to prove a hypothesis. Population Attributional risk can be utilize in health promotion through proven research.

### Reference

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

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?

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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 Reports12(1), 1–10. https://doi-org.lopes.idm.oclc.org/10.1038/s41598-022-07138-y

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:

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

In relative risk also known as (RR) measure the strength of the association or causal link between a risk factor and the outcome. An example includes: Two groups of Women and one group has a mother, sister or daughter who had ovarian cancer. Attribute risk (AR) assist in measuring the excess risk associated with the risk factor. An example includes lung cancer has mass causes, including smoking cigarettes and exposure to indoor radon (EPA Unites States Environmental Protection Agency, 2021). According to Askari & Namayandeh, (2020) “ Populated Attributable Risk (PAR) focuses on the portion of the incidence of a disease within the population including exposed and non-exposed) which is due to exposure, including the difference between the risk in the total population that were unexposed. For example, a population attributable risk can be identified if we know the lung cancer death rate in general population and in those in non-smokers. This rate can help epidemiologist understand how much of lung cancer deaths could be eliminated if smoking was eliminated. Population attributable risks is calculated by the incidence in the general population minus the incidence in the unexposed population and helps guide public health interventions and decision making. Utilizing population attributable risk can be used to advocate health policy because it can objectively provide risk reduction percentages for stakeholders, so they understand the benefits of certain public health interventions and its effect on reducing certain diseases. Utilizing objective data provides a more science based and analytical approach in prioritizing and developing programs to improve health and wellness in populations.

### References

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

EPA Unites States Environmental Protection Agency (2021). Relative Extent, relative Risk and Attributable Risk. Retrieved from https://www.epa.gov/national-aquatic-resource-surveys/relative-extent-relative-risk-and-attributable-risk

Risk is the probability of an event occurring, that marks the end of a good state of health and the beginning of the disease. Relative risk compares the exposure group and non-exposure group. In essence, relative risk is a ratio of the probability of an event occurring in a group exposed to a hazard or health risk versus the probability of the event occurring in the non-exposed group (Tenny et al., 2021). Relative risk is mostly greater than 1, that is there is a likelihood of an event occurring after exposure. However, relative risk below 1 indicates that exposure lowers the probability of an event occurring. A relative risk of 1 indicates that exposure and non-exposure do not affect the probability of an event occurring (Tenny et al., 2021). Epidemiologists can apply relative risk among populations with different disease prevalence. For instance, epidemiologists study the prevalence of lung cancer among smokers and non-smokers or HIV prevalence among sexually active youths and sexually inactive youths.

Attributable risk refers to the number of reported cases following an exposure. Attributable risk depicts the excess effects that are related to a particular exposure (Askari et al., 2020). This risk is based on absolute differences and is applicable in measuring how great the frequency of an outcome is among the exposed group compared to the non-exposed group. Therefore, subtracting 1 from the relative risk indicates the excess risk (attributable risk) (Faustini et al., 2020). On the other hand, population attributable risk refers to the incidences of an event in a population that is caused by exposure. In essence population, attributable risk (PAF) is avoidable by elimination of exposure. Epidemiologists apply PAF to determine the risk difference between the total population (both exposed and non-exposed) and the unexposed population (Askari et al., 2020). I would propose the application of population attributable risk to advocate the tobacco ban policy to promote population health by eliminating the dominant risk for respiratory diseases such as cancer.

### References

Askari, M., & Namayandeh, S. M. (2020). The Difference between the Population Attributable   Risk (PAR) and the Potential Impact Fraction (PIF). Iranian journal of public  health49(10), 2018–2019. https://doi.org/10.18502/ijph.v49i10.4713

Faustini, Annunziata, and Marina Davoli. (2020 June 23). “Attributable Risk to Assess the Health Impact of Air Pollution: Advances, Controversies, State of the Art and Future     Needs.” International journal of environmental research and public health vol. 17,12      4512 doi:10.3390/ijerph17124512

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/