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Evidence Public Health part 2 - Coggle Diagram
Evidence Public Health part 2
The term rate can be used to describe any type of measurement that has a top number or a bottom number.
The numerator involves the case defination where it measures the ocurrance of the disease.
The denominator looks how how many times the event could occur within an entire population. this is known as the at risk population.
from there we can describe the data using 2 definitions. the first being incidence and the second being prevalence.
All of these defniations and ideas can be used to describe and indentify the etiology of a disease.
When looking at the differences or changes in a disease we can look at several related factors.
we can assess the various factos like age adjusment
This factor looks like various age groups what disease they are more likely to fall victim too. . In each age group, there is a age distribution. A number of people within a age group that ultimately contribute to the outcomes of disease in said age populations.
to establish contributing cause we can go beyond case control, cohort, and randomized trials,
we can identify risk factors, actions or behoviors that put somebody at risk for disease or illness. A example of this would be ciegarete smoking and how it puts them at risk for lung disease.
but, to have more of a definitive understanding or draw a logical conclusion, we can use supportive critieria. this is done to establish the association as a cause. It helps to establish a link as a causation.
efficacy can also be used in relation to risks but it is primarily used to state that a intervention works and that it increases the more postive results of a outcome.
efficacy can be applied to the various studies in order to establish or satisfy various requirements that are needed to draw on those positive outcomes.
similar to the other thought bubbles, the Strength of a Relationship can used to establish how strong a risk factor is to being the cause of the disease.
To see how strong a risk factor is, we can measure the relationship between a risk and outcome. The proportion that we generate is known as the relative risk. this establishes a probability.
This risk can then be further evaluated by dose dependency. Where we can look at how much of one thing is needed to increase or initiate the risk. A common example of this is smoking and the number of packs in a given day
we can also factor in causes that go beyond what we do. These would be out genetics and how they put us at risk. This would be things like biological plausability.
contributory cause is establish on the basis of evidence and attempts to answer a variety of questions
these questions often include , what was the disease due to, who caused it, who should be blamed, what is it a result from, what produced it, and how can it be explained.