Calculating Odds Ratio in Nursing
Data can be qualitative or quantitative. Qualitative data is helpful to generate a hypothesis and gather information if little is known about an expected association. Focus groups, key informant interviews, and case studies are types of qualitative data collection methods used to identify common themes from which to build a hypothesis. Quantitative data collection and analysis is used to test a hypothesis and make comparisons to determine the direction and strength of a potential association. The Behavioral Risk Factor Surveillance System (BRFSS) is crosssectional panel survey used to collect quantitative data on adult behaviors and risk factors. It is one of the largest U.S. health data collection efforts. The data can be used to analyze associations on a state or country level. Follow the steps to obtain a 2×2 contingency table (also known as a “cross tabulation”) crossing binge drinking with depression.
1. Retrieve the “BRFSS WebEnabled Analysis Tool” resource provided in the Topic Materials.
2. Select “Cross Tabulation.”
3. Select “2015” for the year.
4. Select “Arizona” for the state.
5. Select “Alcohol Consumption: Binge drinkers (males having five or more drinks on one occasion, females having four or more drinks on one occasion)” for Step 2 Select Row.
6. Select “Chronic Health Conditions: Ever diagnosed with a depressive disorder, including depression, major depression, dysthymia, or minor depression” for Step 3 Select Column.
7. Skip Steps 4 and 5.
8. Select “Sample Size” for Step 6 Select Statistics and run the report for the cross tabulation.
Part 1
Using the data from the cross tabulation results, calculate the odds ratio for depression among those exposed to binge drinking. Interpret the odds ratio and discuss if the odds ratio is a good estimate of the relative risk in this situation. Why or why not? Show your 2×2 table and all calculations. Present or describe the formula you used to arrive at your answer.
Part 2
Use the Topic Material, “BRFSS WebEnabled Analysis Tool,” located on the CDC website, and run a report for two variables of interest to you. Create a 2×2 table and calculate the odds ratio for this association. Interpret the odds ratio and discuss the public health importance of the association. Show your 2×2 table. Present or describe the formula you used to arrive at your answer.
Refer to the “Creating a 2×2 Contingency Table” resource for guidance in creating 2×2 contingency tables.
General Requirements
APA style is not required, but solid academic writing is expected.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
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You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.
Use the “BRFSS Web Enabled Analysis Tool,” located on the Centers for Disease Control and Prevention (CDC) website, to complete the topic assignment.
URL:
https://nccd.cdc.gov/weat/#/
The odds ratio (OR) is a measure of how strongly an event is associated with exposure. The odds ratio is a ratio of two sets of odds: the odds of the event occurring in an exposed group versus the odds of the event occurring in a nonexposed group. Odds ratios commonly are used to report casecontrol studies. The odds ratio helps identify how likely an exposure is to lead to a specific event. The larger the odds ratio, the higher odds that the event will occur with exposure. Odds ratios smaller than one imply the event has fewer odds of happening with the exposure
Odds Ratio = (odds of the event in the exposed group) / (odds of the event in the nonexposed group)
If the data is set up in a 2 x 2 table as shown in the figure then the odds ratio is (a/b) / (c/d) = ad/bc. The following is an example to demonstrate calculating the odds ratio (OR).
Example 1
If we have a hypothetical group of smokers (exposed) and nonsmokers (not exposed), then we can look for the rate of lung cancer (event). If 17 smokers have lung cancer, 83 smokers do not have lung cancer, one nonsmoker has lung cancer, and 99 nonsmokers do not have lung cancer, the odds ratio is calculated as follows.
First, we calculate the odds in the exposed group.

Odds in exposed group = (smokers with lung cancer) / (smokers without lung cancer) = 17/83 = 0.205
Next we calculate the odds for the nonexposed group.

Odds in not exposed group = (nonsmokers with lung cancer) / (nonsmokers without lung cancer) = 1/99 = 0.01
Finally we can calculate the odds ratio.

Odds ratio = (odds in exposed group) / (odds in not exposed group) = 0.205 / 0.01 = 20.5
Thus using the odds ratio, this hypothetical group of smokers has 20 times the odds of having lung cancer than nonsmokers. The question then arises: is this significant?
The odds ratio is the ratio of the odds of the event happening in an exposed group versus a nonexposed group. The odds ratio is commonly used to report the strength of association between exposure and an event. The larger the odds ratio, the more likely the event is to be found with exposure. The smaller the odds ratio is than 1, the less likely the event is to be found with exposure. It is important to look at the confidence interval for the odds ratio, and if the odds ratio confidence interval includes 1, then the odds ratio did not reach statistical significance
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