confidence interval

A confidence interval is a range of values that scientists report alongside a single estimated number (like a risk estimate) to show how precise that estimate is. A 95% confidence interval means that if the study were repeated many times, about 95 out of 100 such intervals would contain the true value. A narrow interval suggests a precise estimate; a wide interval suggests more uncertainty.

Origin

The concept was introduced by Polish statistician Jerzy Neyman in 1937 as part of his framework for statistical inference. It has since become the standard way to express uncertainty in epidemiology, including the asbestos studies that established risk estimates for mesothelioma and lung cancer.

Significance in Asbestos Context

In asbestos cases, expert reports and the epidemiology they rely on almost always present risk estimates (such as relative risk or standardized mortality ratios) with a confidence interval attached. If the interval does not cross 1.0, the study generally shows a statistically significant increased risk from exposure, an important point when proving that a particular trade, product, or fiber type causes disease. Defense experts often attack plaintiff studies by pointing to wide intervals or intervals that touch 1.0, arguing the data are too imprecise to support causation. Understanding that a wide interval reflects limited data, not absence of risk, helps patients and families make sense of conflicting expert testimony.

Example Sentence

The epidemiologist testified that shipyard insulators had a relative risk for mesothelioma of 8.1, with a 95% confidence interval of 5.3 to 12.4, meaning the increased risk was both large and statistically robust.

Related Terms

Relative Risk, Standardized Mortality Ratio, Statistical Significance, Epidemiology, Dose-Response, Meta-Analysis

Notes

• When reviewing expert reports, ask your legal team whether the cited studies' confidence intervals exclude 1.0 (the no-effect value). This is often central to admissibility and weight.
• Be cautious of defense arguments that dismiss a study solely because its confidence interval is wide; wide intervals often reflect small study size, not the absence of a real effect.
• For rare diseases like mesothelioma, even well-designed studies can produce wide intervals; pooled analyses and meta-analyses can narrow them and strengthen causation evidence.
• Ask your attorney whether the epidemiology cited in your case includes occupation- or product-specific risk estimates with their confidence intervals, as these are stronger than general asbestos-risk figures.