• Consider each of the following scenarios and explain whether the variable in question is a confounder:
a. A study of the relationship between exercise and heart attacks that is conducted among women who do not smoke. Explain whether gender is a confounder.
b. A case-control study of the relationship between liver cirrhosis and alcohol use. In this study, smoking is associated with drinking alcohol and is a risk factor for liver cirrhosis among both non-alcoholics and alcoholics. Explain whether smoking is a confounder.
• Interpret the results of the following studies
a. An odds ratio of 1.2 (95% confidence interval: 0.8-1.5) is found for the association of low socioeconomic status and occurrence of obesity.
b. A relative risk of 3.0 is reported for the association between consumption of red meat and the occurrence of colon cancer. The p-value of the association is 0.15.
c. An odds ratio of 7 (95% confidence interval: 3.0 – 11.4) is found for the association of smoking and lung cancer.
• The relationship between cigarette smoking and lung cancer was conducted in a case-control study with 700 cases and 425 controls. Using the results below, calculate the crude odds ratio and explain what the ratio means:
o Heavy Smoking—Cases: 450; Controls: 200
o Not Heavy Smoking—Cases: 250; Controls: 225
• A case-control study looked at the association of alcohol use with the occurrence of coronary heart disease (CHD). There were 300 participants in the study (150 cases and 150 controls). Of the cases, 90 participants drank alcohol; of the controls, 60 participants drank alcohol.
Design the appropriate 2x2 table, calculate and interpret the appropriate measure of association.
You suspect that the association between alcohol use and CHD might be confounded by smoking. You collect the following data:
Smokers Non-Smokers
CHD No CHD CHD No CHD
Alcohol Use 80 40 10 20
No Alcohol Use 20 10 40 80
•
Calculate the appropriate measure of association between alcohol use and CHD in both smokers and non-smokers. Discuss whether smoking was a confounder of the association. What is the relationship of alcohol use to CHD after controlling for confounding?
• A study was conducted in young adults to look at the association between taking a driver’s education class and the risk of being in an automobile accident. 450 participants were included in the study, 150 cases who had been in an accident and 300 controls who had not. Of the 150 cases, 70 reported having taken a driver’s education class. Of the 300 controls, 170 reported having taken a driver’s education class.
Calculate and interpret the appropriate measure of association between driver’s education and accidents.
The question arose as to whether gender might be an effect modifier of this association. When gender was assessed, the data looked like the following:
Women Men
Accident No Accident Accident No Accident
Driver's Ed 10 50 60 120
No Driver's Ed 40 50 40 80
Perform the appropriate calculations to test for effect modification. Interpret your results.
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Design the appropriate 2x2 table, calculate and interpret the appropriate measure of association.
You suspect that the association between alcohol use and CHD might be confounded by smoking. You collect the following data:
Smokers Non-Smokers
CHD No CHD CHD No CHD
Alcohol Use 80 40 10 20
No Alcohol Use 20 10 40 80
How would you calculate te measure of association n this problem?
I do not have an answer
You are right but I'm having some difficulties
a. In the study of the relationship between exercise and heart attacks among women who do not smoke, gender is not a confounder. This is because gender is not associated with either exercise or heart attacks in this specific scenario. The study has already restricted the population to women, so gender is not a factor that could confound the relationship between exercise and heart attacks.
b. In the case-control study of the relationship between liver cirrhosis and alcohol use, smoking is a confounder. This is because smoking is associated with both drinking alcohol and the risk of liver cirrhosis among both non-alcoholics and alcoholics. Therefore, smoking could potentially confound the relationship between liver cirrhosis and alcohol use.
a. An odds ratio of 1.2 (95% confidence interval: 0.8-1.5) for the association of low socioeconomic status and occurrence of obesity suggests that there is no significant association between low socioeconomic status and obesity. The odds ratio of 1.2 indicates that individuals with low socioeconomic status are 1.2 times as likely to be obese compared to individuals with higher socioeconomic status. However, since the confidence interval includes 1.0, there is no statistically significant evidence to support a real association between low socioeconomic status and obesity.
b. A relative risk of 3.0 for the association between consumption of red meat and the occurrence of colon cancer with a p-value of 0.15 suggests that there is no significant association between the two. The relative risk of 3.0 indicates that individuals who consume red meat are 3 times more likely to develop colon cancer compared to those who do not consume red meat. However, since the p-value is greater than the conventional significance level of 0.05, there is not enough evidence to reject the null hypothesis and conclude that there is a real association between red meat consumption and colon cancer.
c. An odds ratio of 7 (95% confidence interval: 3.0 – 11.4) for the association of smoking and lung cancer suggests a significant positive association between the two. The odds ratio of 7 indicates that smokers are 7 times more likely to develop lung cancer compared to non-smokers. The confidence interval and the absence of 1.0 within it suggest that the association is statistically significant.
For the relationship between cigarette smoking and lung cancer in the case-control study:
- Crude odds ratio = (450/200) / (250/225) = 2.25
The crude odds ratio of 2.25 means that individuals who heavily smoke are 2.25 times more likely to develop lung cancer compared to those who do not heavily smoke.
In the case-control study of alcohol use and CHD:
- Cases who drank alcohol: 90
- Controls who drank alcohol: 60
- Cases who did not drink alcohol: 60
- Controls who did not drink alcohol: 90
Based on these values, the appropriate measures of association are odds ratios.
For smokers:
- Odds ratio = (80/10) / (20/40) = 16
For non-smokers:
- Odds ratio = (40/40) / (10/20) = 4
Smoking is a confounder in this association because it is associated with both alcohol use and CHD. The association between alcohol use and CHD is different in smokers and non-smokers. After controlling for confounding (smoking), the true relationship between alcohol use and CHD is:
- In smokers, the odds of having CHD for those who drink alcohol is 16 times higher than those who do not drink alcohol.
- In non-smokers, the odds of having CHD for those who drink alcohol is 4 times higher than those who do not drink alcohol.
In the study on the association between driver's education and accidents:
- Cases who took driver's education: 70
- Controls who took driver's education: 170
- Cases who did not take driver's education: 80
- Controls who did not take driver's education: 130
The appropriate measure of association is the odds ratio.
- Odds ratio = (70/80) / (170/130) ≈ 0.82
The odds ratio of approximately 0.82 indicates that individuals who took driver's education are about 0.82 times as likely to be in an automobile accident compared to those who did not take driver's education. However, the interpretation should be done with caution as the odds ratio is less than 1.0, implying a potentially protective effect but the association is not statistically significant.