Coffee-Heart Study: Bias & Confounding.
ANSWER
Theoretical Investigation of Coffee Consumption and Risk of Heart Disease
Consider a hypothetical study that seeks to determine whether drinking coffee affects one’s chance of acquiring heart disease. Participants are drawn from the nearby neighborhood, and over the course of ten years, the study tracks their heart disease outcomes as well as information on their coffee consumption habits.
Bias Can Be Introduced In These Ways:
Differential Recall Bias: Differential recall bias has the potential to introduce prejudice. The statistics could be inaccurate because participants might not accurately recall or record their coffee consumption. People with heart illness, for example, might be more motivated to remember their coffee consumption in a different way than people without heart disease.
Loss to Follow-Up: Bias may be introduced if a sizable fraction of study participants are lost to follow-up. This could happen if participants who have heart disease are less likely to stay in the study, resulting in a final sample that is disproportionately made up of healthier persons.
Bias Type and Justification:
Differential Recall Bias: This prejudice would be categorized as an information prejudice. The uneven recollection of coffee consumption in this situation is an example of an information bias that results from systematic errors in data collection. The association between coffee drinking and the risk of heart disease may be distorted because certain individuals’ memories of their coffee consumption may be more accurate or different depending on their health state.
Potential confounding factors include:
Smoking Habits: Smoking is linked to coffee drinking and is known to increase the risk of heart disease. People who smoke might drink more coffee. The study could gather information on smoking habits and use it as a covariate in their analysis to adjust for this confounder.
Level of Physical exercise: Physical exercise is a significant risk factor for heart disease. Coffee consumption among those who are physically active may differ from that of sedentary people because they may be less likely to acquire heart disease. The study might measure the individuals’ levels of physical activity and include this as a covariate in the analysis to adjust for this confounder.
Controlling Confounding Variables:
Matching: The study could make use of matching techniques to account for confounding characteristics like smoking behavior and degree of physical activity. To lessen their effects on the coffee-heart disease association, participants with similar smoking and physical activity characteristics could be matched together in the analysis.
Stratification: Based on the participants’ smoking and physical activity habits, the study could divide the data into several groups before examining the association between coffee consumption and heart disease within each group. By taking into account any confounding, this would enable a more precise assessment of the impact of coffee consumption on heart disease risk among particular subgroups.
The hypothetical study on coffee intake and heart disease risk can reduce the danger of invalidating its results and provide more precise insights into the association between these variables by addressing recall bias, loss to follow-up, and correcting for potential confounders.
QUESTION
Description
This week you will review different types of bias, present an example of a study, and discuss whether bias was a factor in the study outcome. You will also discuss how the study design could have been altered to minimize or eliminate the risk of invalidating the results.
To prepare for this Discussion:
Review the types of bias listed below.
Non-differential recall bias
Differential recall bias
- Publication bias
Loss to follow-up
- Refusal to participate
- Interviewer bias
- Confounding
- Select one type of bias from the list above, and consider the ways that bias could impact a study.
- To complete this Discussion, post a real or hypothetical example of one study. You can use one of the studies you designed during Weeks 3 or 4 or search for a different study.
- How could bias be introduced in the study?
- Would the bias be considered a selection bias or an information bias? Why?
Name two or three variables that might be possible confounders in your study.
Describe at least one method of controlling those confounding variables.
Fill in the order form and submit all your files, including instructions, rubrics, and other information given to you by your instructor.
Once you complete filling the forms, complete your payment. We will get the order and assign it to a writer.
When your order is completed, it’s assigned to an editor for approval. The editor approves the order.
Once approved, we will upload the order to your account for you to download. You can rate your writer or give your customer review.
