Heller et al [1] propose the PIN-ER-t calculation as a contribution
to "communicating levels of health related risks to decision makers and
the public". We respectfully suggest that they must be joking. They say
that "PIN-ER-t is an easy to understand measure of the impact of risk
factors at the population level, although it does require a degree of
numeracy by the user." Let's make that a PhD degree or else pass the
authors an award for understatement of the year.
Try explaining the following to a typical health department
bureaucrat or the man down at the pub: you take your non-manual workers
proportion (0.458), contemplate their predicted three year incidence of
outcome locally (0.016059), then just hop, skip and jump your way to a
genteel mulling of the estimated number affected locally in next three
years (24.56) and you cannot help but be impressed with the (5.10)
population
impact number by eliminating risk factor (PIN-ER-3). Got that?
Surely, the banner headlines will follow.
But seriously, this sort of work is premised on assumptions that if
only policy makers could be handed a simple number of impressive
proportions, robustly derived, all else would follow. We're sorry, but
policy change doesn't work like that. Stratospheric figures on smoking
deaths have been available for years [2]. Stalin understood that one death
was a tragedy, while a million deaths were just a statistic. Potent risk
communication is so much more than a numbers game.
Simon Chapman
Professor of Public Health,
University of Sydney
Stan Shatenstein
Editor, The Lighter Side,
Tobacco Control
1. Heller RF, Buchan I, Edwards R, Lyratzopoulos G, McElduff P, St
Leger S. Communicating risks at the population level: application of
population impact numbers. BMJ 2003;327:1162-1165.
2. Ezzati M, Lopez AD. Measuring the accumulated hazards of smoking:
global and regional estimates for 2000. Tob Control. 2003 Mar;12:79-85.
Rapid Response:
Policy makers .. now pay attention!
Heller et al [1] propose the PIN-ER-t calculation as a contribution
to "communicating levels of health related risks to decision makers and
the public". We respectfully suggest that they must be joking. They say
that "PIN-ER-t is an easy to understand measure of the impact of risk
factors at the population level, although it does require a degree of
numeracy by the user." Let's make that a PhD degree or else pass the
authors an award for understatement of the year.
Try explaining the following to a typical health department
bureaucrat or the man down at the pub: you take your non-manual workers
proportion (0.458), contemplate their predicted three year incidence of
outcome locally (0.016059), then just hop, skip and jump your way to a
genteel mulling of the estimated number affected locally in next three
years (24.56) and you cannot help but be impressed with the (5.10)
population
impact number by eliminating risk factor (PIN-ER-3). Got that?
Surely, the banner headlines will follow.
But seriously, this sort of work is premised on assumptions that if
only policy makers could be handed a simple number of impressive
proportions, robustly derived, all else would follow. We're sorry, but
policy change doesn't work like that. Stratospheric figures on smoking
deaths have been available for years [2]. Stalin understood that one death
was a tragedy, while a million deaths were just a statistic. Potent risk
communication is so much more than a numbers game.
Simon Chapman
Professor of Public Health,
University of Sydney
Stan Shatenstein
Editor, The Lighter Side,
Tobacco Control
1. Heller RF, Buchan I, Edwards R, Lyratzopoulos G, McElduff P, St
Leger S. Communicating risks at the population level: application of
population impact numbers. BMJ 2003;327:1162-1165.
2. Ezzati M, Lopez AD. Measuring the accumulated hazards of smoking:
global and regional estimates for 2000. Tob Control. 2003 Mar;12:79-85.
Competing interests:
None declared
Competing interests: No competing interests