In a cross-sectional study of heart disease and gender in middle-aged men and women, 10% of men in the sample had prevalent heart disease compared with only 5% of women in the sample. After adjusting for age in multivariate logistic regression, the odds ratio for heart disease comparing males to females was 1.1 (95% confidence interval: 0.79—1.43). What conclusions can you draw?
A) Being male increases your risk of heart disease.
B) Age is a confounder of the relationship between gender and heart disease.
C) The men in the study are younger than the women in the study.
D) There is a statistically significant association between gender and heart disease.
E) The study had insufficient power to detect an effect
is it e or b?
B) Age is a confounder of the relationship between gender and heart disease.
The correct conclusions that can be drawn from the given information are:
B) Age is a confounder of the relationship between gender and heart disease.
E) The study had insufficient power to detect an effect.
Explanation:
A) Being male increases your risk of heart disease:
The odds ratio for heart disease comparing males to females is 1.1, which means that the odds of heart disease in males are only slightly higher than in females. However, the confidence interval for this odds ratio includes 1, which suggests that the difference is not statistically significant. Therefore, we cannot conclude that being male increases the risk of heart disease in this study.
B) Age is a confounder of the relationship between gender and heart disease:
When the odds ratio is adjusted for age in the multivariate logistic regression analysis, the association between gender and heart disease becomes weaker. This suggests that age is confounding the relationship between gender and heart disease. In other words, age may explain why there appears to be a higher prevalence in men compared to women.
C) The men in the study are younger than the women in the study:
There is no information provided in the given data to support or suggest that the men in the study are younger than the women. Therefore, we cannot draw this conclusion based on the information provided.
D) There is a statistically significant association between gender and heart disease:
The odds ratio of 1.1 with a confidence interval (0.79—1.43) that includes 1 suggests that there is not a statistically significant association between gender and heart disease in this study. Therefore, we cannot conclude that there is a statistically significant association between gender and heart disease based on the given information.
E) The study had insufficient power to detect an effect:
Since the confidence interval for the odds ratio includes 1, this suggests that the study may not have had enough statistical power to detect a real effect. Therefore, it can be concluded that the study had insufficient power to detect an effect.
Therefore, the correct conclusions are B) Age is a confounder of the relationship between gender and heart disease and E) The study had insufficient power to detect an effect.
To draw conclusions based on the information provided, we need to analyze the results and the associated statistics.
The odds ratio (OR) for heart disease comparing males to females after adjusting for age in multivariate logistic regression is reported as 1.1 with a 95% confidence interval (CI) of 0.79 to 1.43.
First, let's interpret what the odds ratio tells us. An odds ratio of 1 indicates no difference in the odds of heart disease between males and females, while a value greater than 1 indicates that males have higher odds of heart disease compared to females, and a value less than 1 indicates that males have lower odds compared to females.
In this case, the odds ratio is 1.1, slightly higher than 1 but with a confidence interval that includes 1. This means that there is no statistically significant association between gender and heart disease after adjusting for age.
Now let's address the options one by one:
A) Being male increases your risk of heart disease.
Based on the odds ratio and confidence interval, we cannot conclude that being male increases the risk of heart disease. The confidence interval includes 1, indicating that there is no significant difference in the odds of heart disease between males and females.
B) Age is a confounder of the relationship between gender and heart disease.
Correct. The fact that the odds ratio changed from 0.05 in the unadjusted analysis (where there was a significant association) to 1.1 in the adjusted analysis suggests that age is a confounder in the relationship between gender and heart disease. Adjusting for age likely eliminated or mitigated the apparent association.
C) The men in the study are younger than the women in the study.
There is no information in the given statement to support or reject this conclusion. The age variable is described as a confounder but there is no direct information about the age difference between men and women.
D) There is a statistically significant association between gender and heart disease.
Based on the odds ratio and confidence interval, we cannot conclude that there is a statistically significant association between gender and heart disease. The confidence interval includes 1, indicating that there is no significant difference in the odds of heart disease between males and females.
E) The study had insufficient power to detect an effect.
It's unlikely that we can draw this conclusion based solely on the information provided. Insufficient power is difficult to determine without additional information about the study design, sample size, and effect size. However, given that the confidence interval includes 1 and there is no statistically significant association, it suggests that the study did not detect a significant effect.
Therefore, based on the information provided, option B is the most reasonable conclusion: Age is a confounder of the relationship between gender and heart disease.