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Presentation/PPT
27/08/2022
POST EACH RESPONSE SEPARATELY
REPLY TO MY CLASSMATE DISCUSSION BELOW AND EXPLAIN WHY YOU AGREE (Lorraine)
MINIMUM OF 200 WORDS)
The measure of association I will be using as an example is relative risk. Relative risk is a
primary measure used to assess the strength of the relation between an exposure and an
outcome. An example is the relation of a risk factor or intervention to an outcome, typically a
disease or health condition. Relative risk is advantageous in case-control studies because these
studies are when researchers follow individuals over time to watch the development of an
outcome. Then, they compare based on exposure status.
These measures give tremendous value to public health decision-makers in many ways, such as
quantifying the impact of risk factors, identifying the cause, setting public health priorities, and
evaluating intervention effectiveness. These measures allow for assessing a specific risk factor
or exposure linked with a particular health outcome. Identifying causes can not be done
explicitly by measures of association; however, measures of association can provide evidence
of a relationship when put together with additional epidemiological criteria. Prioritization of
public health efforts is more efficient by decision-makers when measures of association are
utilized. When measures identify high relative risks associated with particular exposures, it will
highlight the need for rapid intervention. Lastly, measuring public health interventions can be
assessed by measurements of association. Comparing measures before and after an
intervention allows for a data-driven assessment of whether the intervention was effective.
REPLY TO MY CLASSMATE DISCUSSION BELOW AND EXPLAIN WHY YOU AGREE (Tiny)
MINIMUM OF 200 WORDS)
With any treatment there are risks. Absolute risk reduction enumerates those risks versus no
treatment at all. According to Barratt et al. (2004), these numbers are the most useful way of
presenting the risks in a quantifiable way (Barratt et al., 2004), Health decision makers use this
information regularly. It is a good process to implement if a facility wishes to avoid mal-practice
or a researcher desires publication. Studies on the effectiveness of public health interventions
present results in different ways. Knowing how to interpret those results not only helps the
researcher and the hospital administrator but the population as a whole. When the outcome is
defined as the presence or absence of an event, the outcome is often reported as the absolute
risk. Absolute risk is the percentage of people with the outcome within a group. In studies
evaluating the effectiveness of an intervention, the absolute risk is calculated for both the
intervention and control groups. Then, the two are compared.
Hypothetical Example
A study evaluates the effectiveness of an intervention to reduce brain damage among
premature babies. The researcher compares the number of babies with brain damage in those
exposed to the intervention and those not exposed.
300 premature babies are randomly allocated to intervention group
300 to control group with no intervention
90 babies in the control group experience brain damage.
Their absolute risk for brain damage is calculated by dividing 90/300= 0.30 or 30% of those in
control group. Baseline risk for brain damage for those in control group is 30% as the absolute
risk is equivalent to baseline risk for those not exposed to the intervention. The baseline risk for
brain damage in the intervention group is also around 30% but, after exposure to the
intervention, 54 premature babies acquire brain damage. Calculate absolute risk for brain
damage in the intervention group by dividing 54/300=0.18 or 18%. The intervention group has
an absolute risk for brain damage at 18% following intervention. Because the risk for brain
damage is lower following intervention. It is possible to calculate the absolute risk reduction.
This can be calculated by subtracting the absolute risk of those exposed to the intervention to
those not exposed. 30%-18%= absolute risk reduction of 12%. The intervention lowered the risk
for brain damage by 12%.
More Complete Data
According to Mayne et al. (2006), while the absolute risk reduction gives us an indication of the
impact of an intervention, more data can be uncovered (Mayne et al.,2006). The intervention
lowers the risk for brain damage by 12%. It is necessary to calculate the relative risk to find the
risk for brain damage remaining among those exposed to the intervention. The relative risk
takes into account the baseline risk for the outcome among those in the intervention group
compared to those in the control group. To calculate relative risk, divide absolute risk of
intervention group by absolute risk of control group. 18%/30%=0.60 this tells us that the risk for
brain damage among those in the intervention group is 60 % of the risk in the control group.
Now it is possible to calculate how much the risk for brain damage is reduced among those in
the intervention group. This refers to the relative risk reduction. It is calculated by subtracting
the Relative risk percentage from 100%. 100%-60%= 40%. So, the intervention reduces the
relative risk for brain damage by 40% among those exposed to the intervention. These stats are
important for different reasons.
A Lower Risk
Another study is conducted with the baseline risk for brain damage is 10%. This means the
absolute risk for brain damage in the control group is 10%. If the groups are randomly
allocated. We can assume the baseline risk in the intervention group is also about 10%. The
intervention has the same effect as in the first study. So, the relative risk reduction is 40%.
Therefore, following the intervention, the intervention group’s risk for brain damage will be 40%
of 10% which means absolute risk in intervention group will be 6%. To calculate the absolute
risk reduction, we subtract absolute risk of 6% in the intervention group from the absolute risk
of 10% in the control group which is 4%. In this case, when the baseline risk for brain damage is
10% and the relative risk remains the same at 40% the absolute risk reduction for fracture is
only 4%.
Summary
In the first study the baseline risk for fracture is 30%. The absolute risk reduction is 12% and the
relative risk reduction is 40%. In the second study, even though the relative risk reduction
stayed the same at 40%, when the baseline risk drops to 10%, the absolute risk reduction
decreases to 4%. These two samples illustrate how baseline risk outcome influences absolute
risk reduction, even when the relative risk reduction remains the same. That’s why it’s
important to consider the baseline risk in your population prior to implementing an
intervention. If it’s lower in the population than those in the study, the researcher can
anticipate the absolute risk reduction to be less than published. When baseline risk is higher
the opposite is true.
References
Barratt, A., Wyer, P. C., Hatala, R., McGinn, T., Dans, A. L., Keitz, S., & Moyer, V. (2004). Tips for
learners of evidence-
based medicine: 1. Relative risk reduction, absolute risk reduction and number needed to
treat. Cmaj, 171(4), 353-358.
Mayne, T. J., Whalen, E., & Vu, A. (2006). Annualized was found better than absolute risk
reduction in the
calculation of number needed to treat in chronic conditions. Journal of clinical
epidemiology, 59(3), 217-223.
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