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Both risk and odds can be applied to a cohort study designs based on population. On the other hand, a case-control study is not based on population but designed by separate sampling procedures in the disease group and no disease group. Therefore, there is no denominator to estimate the risk in the entire population and only odds can be obtained in the case-control design.
Regarding those study designs, we'll talk about definitions, applicability, difference, and interpretation of risk difference RD , risk ratio RR , and odds ratio OR as measures of effects in studies with cohort and case-control design. RD or AR is defined as the difference in risk of a condition such as a disease between an exposed group and an unexposed group Table 1. RR is the ratio between the risk of exposed group and unexposed group.
OR is the ratio between odds of exposed group and unexposed group. A cohort study design pursues the effect of exposure such as treatment, prospectively.
In the cohort study, we extract an adequate size of a random sample from the target population, then randomly assign the subjects into either the expose group or unexposed group. The effect of exposure is observed as the changes in outcome of interest over time. Risk is easily calculated as the number of persons having the disease in exposed and unexposed groups divided by the number of all the persons in both groups.
In the cohort study, we have a clear denominator: the number of persons assigned in the groups. RD and RR are frequently used to assess the association between the exposed and control groups. RD, which is also known as AR or excessive risk, represents the amount of risk, which decreased or increased when the exposure exists compared to that when the exposure is absent. A positive RD value means increased risk and a negative one means decreased risk by the exposure.
RR is calculated as the risk of an exposed group divided by the risk of an unexposed group. A RR value of 1 means no difference in risk between groups, and larger or smaller values mean increased or decreased risk in an exposed group compared to the risk in an unexposed group, which can be interpreted that the occurrence of disease is more or less likely in the exposed group, respectively.
In addition, we can also use OR for the same purpose in cohort studies. OR is the ratio of odds of disease in an exposed group and an unexposed group. The interpretation OR is not as intuitive as RR. An OR value of 1 means no difference in odds between groups, and larger value than 1 means increased odds in exposed group, interpreted as a positive association between having disease and having exposure.
Contrarily an OR value of smaller than 1 means decreased odds in exposed group which is interpreted as the association between having disease and not having exposure. Though the interpretation of OR is similar to that of RR, they have similar values only when risks of both groups are very low, e. Otherwise, they show different values. Therefore, incorrect interpretation of OR value as RR will lead to an overstatement of the effect by either erroneously increasing or decreasing the true risks.
Figure 1 depicts that the differences between OR and RR values get larger as the levels of baseline risk in the control group I 0 increase.
OR has been used as a very popular estimate of effect in epidemiological studies. The interpretation of the value of a rate ratio is similar to that of the risk ratio. That is, a rate ratio of 1. They recorded Calculate the rate ratio. Note: Of 58 viral isolates identified from nasal cultures from passengers, most were influenza A, making this the largest summertime influenza outbreak in North America.
Brit Med J ; —, — Check your answer. An odds ratio OR is another measure of association that quantifies the relationship between an exposure with two categories and health outcome. Referring to the four cells in Table 3. Notice that the odds ratio of 5. That is one of the attractive features of the odds ratio — when the health outcome is uncommon, the odds ratio provides a reasonable approximation of the risk ratio. Another attractive feature is that the odds ratio can be calculated with data from a case-control study, whereas neither a risk ratio nor a rate ratio can be calculated.
In a case-control study, investigators enroll a group of case-patients distributed in cells a and c of the two-by-two table , and a group of non-cases or controls distributed in cells b and d.
The odds ratio is the measure of choice in a case-control study see Lesson 1. The number of persons in the control group is usually decided by the investigator.
Often, the size of the population from which the case-patients came is not known. As a result, risks, rates, risk ratios or rate ratios cannot be calculated from the typical case-control study.
However, you can calculate an odds ratio and interpret it as an approximation of the risk ratio, particularly when the disease is uncommon in the population. Calculate the odds ratio for the tuberculosis data in Table 3. Would you say that your odds ratio is an accurate approximation of the risk ratio? Hint: The more common the disease, the further the odds ratio is from the risk ratio. Section Navigation.
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