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A study in Rotterdam (European Journal of Heart Failure, vol. \(11,2009,\) pp. \(922-928\) ) followed the health of 7983 subjects over 20 years to determine whether intake of fish could be associated with a decreased risk of heart failure in a general population of men and women aged 55 years and older. Results showed that the dietary intake of fish was not significantly related to heart failure incidence. Even for a high daily fish consumption of more than 20 grams a day there appeared no added protection against heart failure. Incidence rates were similar in those who consumed no fish (incidence rate of 11 per 1000 ), moderate fish (median \(9 \mathrm{~g}\) per day, 12.3 per 1000 ) or high fish ( 9.9 per 1000 ). The relative risk of heart failure in the high intake groups (medium and high fish) was 0.96 when compared with no intake with a \(95 \%\) confidence interval of \((0.78,1.18) .\) Explain how to interpret the (a) reported relative risk and (b) confidence interval for the relative risk.

Step by step solution

01

Understand Relative Risk

Relative risk (RR) is a measure used to determine how much more (or less) likely an event is to occur in the treatment group compared to a control group. Here, the treatment group consists of individuals with moderate to high fish intake. An RR of 0.96 indicates that the risk of heart failure for individuals consuming a moderate to high amount of fish is 96% of the risk for those with no fish intake. This value is close to 1, suggesting no strong association between fish intake and the risk of heart failure.

02

Analyze the Confidence Interval

The confidence interval (CI) gives a range of values within which the true relative risk is expected to fall, with a certain level of confidence (here, 95%). The given CI is (0.78, 1.18). Since this interval includes the value 1, it implies there is no statistically significant effect of fish intake on heart failure risk, as the true relative risk could be less than, greater than, or exactly 1.

03

Conclusion from the Analysis

Combining these interpretations, the study suggests that any difference in heart failure risk due to fish intake among the studied groups could be due to random variation, given that the relative risk is close to 1 and the confidence interval includes 1. Thus, there is no statistically significant evidence to claim that fish intake affects heart failure risk.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Relative Risk

Relative risk, or RR, is a statistic used to compare the risk of a specific event happening in one group versus another. In this study, it looked at whether consuming fish could change the likelihood of heart failure. We can see that the RR is 0.96 which suggests that the chance of heart failure for those eating moderate to high amounts of fish is about 96% of that for people who eat no fish.
This number being close to 1 is important. Why? Because it means the fish-eating group and the no-fish group have almost the same risk. This indicates there might not really be any helpful effect of fish consumption on heart failure.
In general, a relative risk of 1 means there's no difference between the two groups in terms of the risk of the event. A relative risk less than 1 means the event is less likely in the treatment group, while greater than 1 means it's more likely. In simple terms, here, eating more fish didn't change the risk of heart failure substantially.

Confidence Interval

A confidence interval (CI) is like a safety net for statistics, offering a range where we believe the true number lies with a certain level of certainty, often 95%. The CI for the relative risk in this research is from 0.78 to 1.18.
Why is this range significant? Because we are saying that we're 95% confident that the true relative risk is somewhere between these numbers. Now, there's a special number in this range: 1.
If a CI includes 1, like this one does, it means the treatment effect might be zero. In simpler words, there's a chance that fish intake has no effect on heart failure, since the actual risk could fall just as easily on either side of 1. Hence, the study wasn't able to rule out the possibility of no association between fish consumption and heart failure risk.

Statistical Significance

Statistical significance is a way to tell if an observed effect seen in a study truly exists in the larger population, or if it's likely due to just random chance. Based on the relative risk (0.96) and its confidence interval (0.78 to 1.18), this study didn't find statistical significance.
If results are statistically significant, it suggests a high confidence that what was observed wasn’t due to random fluke. In our heart failure study, because the confidence interval crosses 1, the results aren't statistically significant, signaling that the observed difference or lack thereof could simply be due to random variation.
This means that while fish consumption levels were varied among the participants, these differences didn't lead to conclusive evidence about heart failure risk. Statistical significance is key in validating scientific findings—without it, findings remain inconclusive.