Attributable fraction for the population explained

In epidemiology, attributable fraction for the population (AFp) is the proportion of incidents in the population that are attributable to the risk factor. The term attributable risk percent for the population is used if the fraction is expressed as a percentage.^[1] It is calculated as

AF _{p} = (I _{p} - I _{u)/I} _{p} , where I _{p} is the incidence in the population, and I _{u} is the incidence in the unexposed group.

Equivalently it can be calculated as

AF _{p} = (P _{e(RR} -1 ))/(1+ P _{e(RR-1)}) , where P _{e} is the exposed proportion of the population and RR is the relative risk not adjusted for confounders.^[2]

It is used when an exposure increases the risk, as opposed to reducing it, in which case its symmetrical notion is preventable fraction for the population.

Synonyms

Multiple synonyms of the attributable fraction for the population are in use: attributable proportion for the population, population attributable proportion, Levin's attributable risk, population attributable risk, and population attributable fraction.^{[3] [4]}

Similarly, population attributable risk percent (PAR) is used as a synonym for the attributable risk percent for the population.^[5]

Interpretation

Attributable fraction for the population combines both the relative risk of an incident with respect to the factor, as well as the prevalence of the factor in the population. Values of AF_p close to 1 indicate that both the relative risk is high, and that the risk factor is prevalent. In such case, removal of the risk factor will greatly reduce the number of the incidents in the population. The values of AF_p close to 0, on the other hand, indicate that either the relative risk is low, or that the factor is not prevalent (or both). Removal of such factor from the population will have little effect. Because of this interpretation, AF_p is considered useful for guiding public health policy.^[6]

For example, in 1953 Levin's paper estimated that lung cancer has a relative risk of 3.6–13.4 in smokers compared to non-smokers, and that the proportion of the population exposed to smoking was 0.5–0.96, resulting in the high AF_p value of 0.56–0.92. Recently, it has been shown that the population attributable fraction for anthropogenic risk factors strongly correlates with the number of oncogenic mutations in multiple cancer types, both sexes, and three countries – US, UK and Australia.^[7]

Generalizations

Attributable fraction for the population can be generalized to the case where the multilevel exposure to the risk factor. In such case

AF _{p} = (\sum _{i} P _{i} RR _{i} - \sum _{i} P _{i'RR} _{i})/(\sum _{i} P _{i} RR _{i}) where P _{i} is the proportion of the population exposed to the level i , P _{i'} is the desired (ideal) proportion of the population exposed to the level i , and RR _{i} is the relative risk at exposure level i .

See also

• Population Impact Measures
• Attributable fraction among the exposed

Notes and References

1. Book: Dictionary of Epidemiology - Oxford Reference. A Dictionary of Epidemiology . 2014. Oxford University Press . en. 10.1093/acref/9780199976720.001.0001. 9780199976720. 2018-05-09. Porta. Miquel.
2. Book: Statistical methods in medical research . Armitage P, Berry G, Matthews JN . 2002 . Blackwell Scientific Publications . 978-0-470-77366-6 . 4th . Oxford . 682 . 646751070 .
3. Rockhill B, Newman B, Weinberg C . Use and misuse of population attributable fractions . American Journal of Public Health . 88 . 1 . 15–9 . January 1998 . 9584027 . 1508384 . 10.2105/ajph.88.1.15.
4. Web site: Metrics: Population Attributable Fraction (PAF). https://web.archive.org/web/20140502012139/http://www.who.int/healthinfo/global_burden_disease/metrics_paf/en/ . dead . May 2, 2014 . World Health Organization . 2018-05-09 .
5. Cole P, MacMahon B . Attributable risk percent in case-control studies . British Journal of Preventive & Social Medicine . 25 . 4 . 242–4 . November 1971 . 5160433 . 478665 . 10.1136/jech.25.4.242.
6. . September 1995 . Public health methods--attributable risk as a link between causality and public health action . . 85 . 9 . 1202–4 . 1615585 . 7661224 . 10.2105/ajph.85.9.1202.
7. Belikov . Aleksey V. . Leonov . Sergey V. . Cancer types with high numbers of driver events are largely preventable . PeerJ . 5 January 2022 . 10 . e12672 . 10.7717/peerj.12672. 35036090 . 8742550 . free .