Communicating risks at the population level: application of population impact numbers

BMJ 2003; 327 doi: http://dx.doi.org/10.1136/bmj.327.7424.1162 (Published 13 November 2003)
Cite this as: BMJ 2003;327:1162

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  1. Richard F Heller (dick.heller@man.ac.uk), professor of public health1,
  2. Iain Buchan, senior lecturer in public health informatics1,
  3. Richard Edwards, senior lecturer in public health1,
  4. Georgios Lyratzopoulos, lecturer in public health1,
  5. Patrick McElduff, lecturer in medical statistics1,
  6. Selwyn St Leger, senior lecturer in public health1
  1. 1Evidence for Population Health Unit, School of Epidemiology and Health Sciences, Medical School, University of Manchester, Manchester M13 9PT
  1. Correspondence to: R F Heller
  • Accepted 19 August 2003

Communicating population risk to policy makers and the public is important, but traditional epidemiological measures of risk are difficult to understand. PIN-ER-t, a measure of the population impact of risk factors, is simpler to understand and hence may be useful

Communicating levels of health related risks to decision makers and the public is increasingly important. Clinical and public health professionals are becoming familiar with best practice in communicating risk to individual patients or members of the public.1 However, communicating risk to those who determine health policy has been less well studied. Although we do not have direct evidence of inappropriate health policy decisions being made, a questionnaire survey found health service managers seem to be inappropriately influenced by presentations of risk and benefit in relative rather than absolute terms.2

For understanding disease causation and to describe the impact of risk factors for disease, the traditional epidemiological measures are absolute and relative risk. However, these do not give a clear indication of the impact of a risk factor at population level, since they do not take into account the prevalence of the risk factor in a population. Epidemiological measures that do take this into account, such as population attributable risk (PAR), are difficult to conceptualise and remember and may be incomprehensible to non-epidemiologists. (In addition, different terms are used for PAR,3 including population attributable fraction (PAF)4 and population attributable risk proportion (PARP),5 which can be confusing for expert and non-expert audiences alike.6)

For a healthcare organisation to allocate resources effectively and develop services according to its health priorities, there may be value in producing and communicating numbers that show the impact of risk factors for disease in the local population in ways that can be easily calculated and understood. We have therefore …

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