Skip to main content
Top
Published in: BMC Medical Informatics and Decision Making 1/2016

Open Access 01-12-2016 | Debate

How old are you, really? Communicating chronic risk through ‘effective age’ of your body and organs

Author: David Spiegelhalter

Published in: BMC Medical Informatics and Decision Making | Issue 1/2016

Login to get access

Abstract

In communicating chronic risks, there is increasing use of a metaphor that can be termed ‘effective-age’: the age of a ‘healthy’ person who has the same risk profile as the individual in question. Popular measures include ‘real-age’, ‘heart-age’, ‘lung-age’ and so on.
Here we formally define this concept, and illustrate its use in a variety of areas. We explore conditions under which the years lost or gained that are associated with exposure to risk factors depends neither on current chronological age, nor the period over which the risk is defined. These conditions generally hold for all-cause adult mortality, which enables a simple and vivid translation from hazard-ratios to years lost or gained off chronological age. Finally we consider the attractiveness and impact of this concept.
Under reasonable assumptions, the risks associated with specific behaviours can be expressed in terms of years gained or lost off your effective age. The idea of effective age appears a useful and attractive metaphor to vividly communicate risks to individuals.
Appendix
Available only for authorised users
Literature
1.
go back to reference Trevena LJ, Zikmund-Fisher BJ, Edwards A, Gaissmaier W, Galesic M, Han PKJ, et al. Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers. BMC Med Inform Decis Mak. 2013;13 Suppl 2:S7.CrossRefPubMedPubMedCentral Trevena LJ, Zikmund-Fisher BJ, Edwards A, Gaissmaier W, Galesic M, Han PKJ, et al. Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers. BMC Med Inform Decis Mak. 2013;13 Suppl 2:S7.CrossRefPubMedPubMedCentral
6.
10.
go back to reference Groenewegen K, den Ruijter H, Pasterkamp G, Polak J, Bots M, Peters SA. Vascular age to determine cardiovascular disease risk: a systematic review of its concepts, definitions, and clinical applications. Eur J Prev Cardiol. 2016;23(3):264–74.CrossRefPubMed Groenewegen K, den Ruijter H, Pasterkamp G, Polak J, Bots M, Peters SA. Vascular age to determine cardiovascular disease risk: a systematic review of its concepts, definitions, and clinical applications. Eur J Prev Cardiol. 2016;23(3):264–74.CrossRefPubMed
15.
go back to reference Morris JF, Temple W. Spirometric “lung age” estimation for motivating smoking cessation. Prev Med. 1985;14(5):655–62.CrossRefPubMed Morris JF, Temple W. Spirometric “lung age” estimation for motivating smoking cessation. Prev Med. 1985;14(5):655–62.CrossRefPubMed
16.
go back to reference Ganna A, Ingelsson E. 5 year mortality predictors in 498 103 UK Biobank participants: a prospective population-based study. Lancet. 2015;386(9993):533–40.CrossRefPubMed Ganna A, Ingelsson E. 5 year mortality predictors in 498 103 UK Biobank participants: a prospective population-based study. Lancet. 2015;386(9993):533–40.CrossRefPubMed
17.
go back to reference Brenner H, Gefeller O, Greenland S. Risk and rate advancement periods as measures of exposure impact on the occurrence of chronic diseases. Epidemiol Camb Mass. 1993;4(3):229–36.CrossRef Brenner H, Gefeller O, Greenland S. Risk and rate advancement periods as measures of exposure impact on the occurrence of chronic diseases. Epidemiol Camb Mass. 1993;4(3):229–36.CrossRef
18.
go back to reference Liese AD. Assessing the impact of classical risk factors on myocardial infarction by rate advancement periods. Am J Epidemiol. 2000;152(9):884–8.CrossRefPubMed Liese AD. Assessing the impact of classical risk factors on myocardial infarction by rate advancement periods. Am J Epidemiol. 2000;152(9):884–8.CrossRefPubMed
20.
go back to reference Gompertz B. On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philos Trans R Soc Lond. 1825;115:513–83.CrossRef Gompertz B. On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philos Trans R Soc Lond. 1825;115:513–83.CrossRef
23.
go back to reference Soureti A, Hurling R, Murray P, van Mechelen W, Cobain M. Evaluation of a cardiovascular disease risk assessment tool for the promotion of healthier lifestyles. Eur J Cardiovasc Prev Rehabil. 2010;17(5):519–23.CrossRefPubMed Soureti A, Hurling R, Murray P, van Mechelen W, Cobain M. Evaluation of a cardiovascular disease risk assessment tool for the promotion of healthier lifestyles. Eur J Cardiovasc Prev Rehabil. 2010;17(5):519–23.CrossRefPubMed
24.
go back to reference Lopez-Gonzalez AA, Aguilo A, Frontera M, Bennasar-Veny M, Campos I, Vicente-Herrero T, et al. Effectiveness of the Heart Age tool for improving modifiable cardiovascular risk factors in a Southern European population: a randomized trial. Eur J Prev Cardiol. 2015;22(3):389–96.CrossRefPubMed Lopez-Gonzalez AA, Aguilo A, Frontera M, Bennasar-Veny M, Campos I, Vicente-Herrero T, et al. Effectiveness of the Heart Age tool for improving modifiable cardiovascular risk factors in a Southern European population: a randomized trial. Eur J Prev Cardiol. 2015;22(3):389–96.CrossRefPubMed
25.
go back to reference Parkes G, Greenhalgh T, Griffin M, Dent R. Effect on smoking quit rate of telling patients their lung age: the Step2quit randomised controlled trial. BMJ. 2008;336(7644):598–600.CrossRefPubMedPubMedCentral Parkes G, Greenhalgh T, Griffin M, Dent R. Effect on smoking quit rate of telling patients their lung age: the Step2quit randomised controlled trial. BMJ. 2008;336(7644):598–600.CrossRefPubMedPubMedCentral
26.
27.
go back to reference Lyna P, McBride C, Samsa G, Pollak KI. Exploring the association between perceived risks of smoking and benefits to quitting: Who does not see the link? Addict Behav. 2002;27(2):293–307.CrossRefPubMed Lyna P, McBride C, Samsa G, Pollak KI. Exploring the association between perceived risks of smoking and benefits to quitting: Who does not see the link? Addict Behav. 2002;27(2):293–307.CrossRefPubMed
28.
go back to reference Kaminsky DA, Marcy T, Dorwaldt A, Pinckney R, DeSarno M, Solomon L, et al. Motivating smokers in the hospital pulmonary function laboratory to quit smoking by use of the lung age concept. Nicotine Tob Res. 2011;13(11):1161–6.CrossRefPubMedPubMedCentral Kaminsky DA, Marcy T, Dorwaldt A, Pinckney R, DeSarno M, Solomon L, et al. Motivating smokers in the hospital pulmonary function laboratory to quit smoking by use of the lung age concept. Nicotine Tob Res. 2011;13(11):1161–6.CrossRefPubMedPubMedCentral
29.
go back to reference Spiegelhalter D. Using speed of ageing and “microlives” to communicate the effects of lifetime habits and environment. BMJ. 2012;345:e8223.CrossRefPubMed Spiegelhalter D. Using speed of ageing and “microlives” to communicate the effects of lifetime habits and environment. BMJ. 2012;345:e8223.CrossRefPubMed
31.
go back to reference Rohrmann S, Overvad K, Bueno-de-Mesquita HB, Jakobsen MU, Egeberg R, Tjønneland A, et al. Meat consumption and mortality - results from the European Prospective Investigation into Cancer and Nutrition. BMC Med. 2013;11(1):63.CrossRefPubMedPubMedCentral Rohrmann S, Overvad K, Bueno-de-Mesquita HB, Jakobsen MU, Egeberg R, Tjønneland A, et al. Meat consumption and mortality - results from the European Prospective Investigation into Cancer and Nutrition. BMC Med. 2013;11(1):63.CrossRefPubMedPubMedCentral
32.
go back to reference Wijndaele K, Brage S, Besson H, Khaw K-T, Sharp SJ, Luben R, et al. Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk Study. Int J Epidemiol. 2011;40(1):150–9.CrossRefPubMed Wijndaele K, Brage S, Besson H, Khaw K-T, Sharp SJ, Luben R, et al. Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk Study. Int J Epidemiol. 2011;40(1):150–9.CrossRefPubMed
33.
go back to reference Prospective Studies Collaboration. Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet. 2009;373:1083–96.CrossRefPubMedCentral Prospective Studies Collaboration. Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet. 2009;373:1083–96.CrossRefPubMedCentral
34.
go back to reference Ekelund U, Ward HA, Norat T, Luan J’a, May AM, Weiderpass E, et al. Physical activity and all-cause mortality across levels of overall and abdominal adiposity in European men and women: the European Prospective Investigation into Cancer and Nutrition Study (EPIC). Am J Clin Nutr. 2015;101(3):613–21.CrossRefPubMedPubMedCentral Ekelund U, Ward HA, Norat T, Luan J’a, May AM, Weiderpass E, et al. Physical activity and all-cause mortality across levels of overall and abdominal adiposity in European men and women: the European Prospective Investigation into Cancer and Nutrition Study (EPIC). Am J Clin Nutr. 2015;101(3):613–21.CrossRefPubMedPubMedCentral
35.
go back to reference Wang X, Ouyang Y, Liu J, Zhu M, Zhao G, Bao W, et al. Fruit and vegetable consumption and mortality from all causes, cardiovascular disease, and cancer: systematic review and dose–response meta-analysis of prospective cohort studies. BMJ. 2014;349:g4490.CrossRefPubMedPubMedCentral Wang X, Ouyang Y, Liu J, Zhu M, Zhao G, Bao W, et al. Fruit and vegetable consumption and mortality from all causes, cardiovascular disease, and cancer: systematic review and dose–response meta-analysis of prospective cohort studies. BMJ. 2014;349:g4490.CrossRefPubMedPubMedCentral
36.
go back to reference Ray KK, Seshasai SRK, Erqou S, Sever P, Jukema JW, Ford I, et al. Statins and all-cause mortality in high-risk primary prevention: a meta-analysis of 11 randomized controlled trials involving 65,229 participants. Arch Intern Med. 2010;170(12):1024–31.CrossRefPubMed Ray KK, Seshasai SRK, Erqou S, Sever P, Jukema JW, Ford I, et al. Statins and all-cause mortality in high-risk primary prevention: a meta-analysis of 11 randomized controlled trials involving 65,229 participants. Arch Intern Med. 2010;170(12):1024–31.CrossRefPubMed
Metadata
Title
How old are you, really? Communicating chronic risk through ‘effective age’ of your body and organs
Author
David Spiegelhalter
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2016
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-016-0342-z

Other articles of this Issue 1/2016

BMC Medical Informatics and Decision Making 1/2016 Go to the issue