Attributable risk
Attributable Risk
Attributable risk, also known as the risk difference, is a measure used in epidemiology to determine the proportion of incidence of a disease in the exposed group that can be attributed to the exposure. It is a crucial concept in public health and clinical research, as it helps to quantify the impact of a risk factor on the occurrence of a disease.
Definition[edit | edit source]
Attributable risk is defined as the difference in the rate of a condition between an exposed population and an unexposed population. Mathematically, it is expressed as:
- AR = I_e - I_u
where:
- AR is the attributable risk.
- I_e is the incidence rate of the disease in the exposed group.
- I_u is the incidence rate of the disease in the unexposed group.
Interpretation[edit | edit source]
Attributable risk provides insight into the public health impact of removing a risk factor. For example, if smoking is a risk factor for lung cancer, the attributable risk would indicate how many cases of lung cancer could be prevented if smoking were eliminated.
Applications[edit | edit source]
Attributable risk is used in various fields, including:
- Public health: To design and evaluate interventions aimed at reducing exposure to risk factors.
- Clinical research: To assess the potential benefits of removing or reducing exposure to a risk factor.
- Health policy: To inform policy decisions and prioritize resource allocation.
Calculation Example[edit | edit source]
Suppose a study finds that the incidence of lung cancer among smokers (I_e) is 200 per 100,000 person-years, while the incidence among non-smokers (I_u) is 20 per 100,000 person-years. The attributable risk would be:
- AR = 200 - 20 = 180 per 100,000 person-years.
This means that 180 cases of lung cancer per 100,000 person-years can be attributed to smoking.
Limitations[edit | edit source]
While attributable risk is a valuable measure, it has limitations:
- It assumes a causal relationship between exposure and disease, which may not always be valid.
- It does not account for confounding factors that may influence the association.
- It is not applicable to case-control studies, where odds ratios are used instead.
Also see[edit | edit source]
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