Concept: Attributable Risk (Attributable Risk Percent)

Attributable Risk (AR) is the amount of disease incidence that can be directly attributed to a specific exposure — here, cigarette smoking. It is calculated as the difference between the incidence rate of disease in the exposed group and the incidence rate in the unexposed group, expressed as a percentage of the incidence in the exposed group.

Step 1: Incidence in Smokers (Exposed Group)

• Total smokers = 7,000
• Developed lung cancer = 70
• Incidence in smokers (Ie) = 70 / 7,000 = 0.01 = 1% (10 per 1,000)

Step 2: Incidence in Non-Smokers (Unexposed Group)

• Total non-smokers = 3,000
• Developed lung cancer = 3
• Incidence in non-smokers (Iu) = 3 / 3,000 = 0.001 = 0.1% (1 per 1,000)

Step 3: Calculating Attributable Risk Percent

$$\text{AR\%} = \frac{I_e - I_u}{I_e} \times 100$$

$$\text{AR\%} = \frac{0.01 - 0.001}{0.01} \times 100 = \frac{0.009}{0.01} \times 100 = 90\%$$

This means that 90% of the lung cancer risk among smokers is directly attributable to cigarette smoking, while the remaining 10% of the risk would exist even without smoking (background/baseline risk).

Why the Other Options Are Incorrect

• 10% — This is actually the proportion of risk in smokers that is not attributable to smoking (Iu/Ie × 100 = 0.1/1 × 100 = 10%); it is the inverse of the correct answer, not the attributable risk itself.
• 30% — Does not correspond to any standard attributable risk calculation using the given incidence values; there is no valid epidemiological formula applied to these numbers (Ie = 1%, Iu = 0.1%) that yields 30%.
• 60% — Also does not match any recognized attributable risk, relative risk, or population attributable risk formula for this dataset.

Key Takeaway

Given Ie = 1% and Iu = 0.1%, the correctly computed Attributable Risk Percent = 90%, making it the mathematically and epidemiologically correct answer for this classic study design comparing smokers and non-smokers.