Prevention Paradox

blue and red lines in a graph

Consider the following scenario with regard to coronary heart disease in a given population;

Look at the following bar chart.

I created it using Geoffrey Rose’s data. He had obtained it from the UK Heart Disease Prevention Project.

As we can see in the above bar chart, as many as 32 per cent of all heart attacks have occurred among those having risk factors alone.

On the other hand, only 12 per cent of all heart attacks have occurred among those with the highest risk of a heart attack: Those having both risk factors and chest pain (ischemia).

How can we explain this?

The answer is simple; those with the highest risk of a heart attack are fewer in number than those with a lower risk.

Geoffrey Rose introduced the term: “Prevention paradox” in 1981 1 to describe the above phenomenon.

He said,

“A measure that brings large benefits to the society only offers a little to each participating individual”.

He referred this to population preventive measures. Here the intervention focuses on a group of people, sometimes a whole population, not an individual person. This is termed “population strategy”.

He made the following arguments to pitch his case in 1981.

  1. The mass diphtheria vaccination campaign, which was implemented in Britain in the early 20th century: he wrote, “roughly 600 children had to be immunized” to save one life.
  2. Based on the evidence, about 400 British doctors had to wear a car seat belt daily for 40 years to save one life.

“A preventive measure brings large benefits to the society

but offers a little to each participating individual”

Rose, G. 1981. ‘Strategy of prevention: Lessons from cardiovascular disease’. 
British Medical Journal, 282, 1847-18511.

To convince us about the utility of the prevention paradox, Rose used two evidence-based scenarios2.

However, the debate on the population strategy’s utility in preventing coronary heart disease continues. Much later, Douglas Manuel et al.3 argued that the high-risk strategy could also be as effective as the population strategy in coronary heart disease mortality reduction3. Their arguments were based on the following concepts;

  • The coronary heart disease prevention strategies should be based on the population risk distribution; Using Canadian Heart Health Survey data, they argue that the risk is concentrated in a modest proportion of the population.
  • As a result, population-based strategies should first evaluate a population’s baseline risk distribution.
  • Risk screening methods have now improved because multiple risk factors are used.
  • Treatment guidelines are potentially as effective as population strategies.

However, the above arguments depend on the wide-scale applicability of treatment methods and medication adherence.

Still, Rose’s analogy is valid and irrefutable.

He said,

High-risk approach is analogus to famine relief, which feeds the hungry but does not tackle the causes of famine (p.47).

Geoffery Rose, The strategy of preventive medicine. 1992. Oxford Uni. Press.

It is more so when we acknowledge the modifiable root causes for many non-communicable diseases: Socioeconomic, and political determinants of health.

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Then, Rose uses another well-illustrated example burrowing data from Alberman et al.4

Example 2: More babies with Down syndrome are born to women younger although the risk increases significantly among those aged 34 and above.

Why is that? It is simply because the number of younger women get pregnant more than their older counterparts.

Now, look at this graph, which I created using data published in the same paper2.

As we can see here, of all babies with Downs Syndrome, 71 per cent were born to mothers aged 34 or younger although the individual risk is much lower. In contrast, only 29 per cent of such babies were born to mothers aged 35 and above. In this instance, Rose convincingly demonstrates that the high-risk approach does not work here.

Later, Norman Kreitman demonstrated evidence supporting the prevention paradox regarding alcohol-related problems.

What does this evidence mean?

Rose summarised these findings as follows:

“A large number of people at a small risk may give rise to more cases of disease than the small number who are at a high risk“.

Geoffrey Rose, Sick individuals and sick populations, International Journal of Epidemiology,
Volume 30, Issue 3, June 2001, Pages 427–432,,

Here, it is clear that screening for high-risk is not going to be effective in this instance; it requires a population-based approach.

As mentioned before, the population approach is not without its own problems. I mentioned some of those above in regard to the progress of high-risk screening tools such as the Framingham screening tool for coronary heart diseases.

Another critic says that the population approach can exacerbate social inequalities5.


  1. Rose, G. 1981. ‘Strategy of prevention: lessons from cardiovascular disease’. British Medical Journal, 282, 1847-1851
  2. Geoffrey Rose, Sick individuals and sick populations, International Journal of Epidemiology, Volume 30, Issue 3, June 2001, Pages 427–432,
  3. Manuel DG, Lim J, Tanuseputro P, Anderson GM, Alter DA, Laupacis A, Mustard CA. Revisiting Rose: strategies for reducing coronary heart disease. BMJ. 2006 Mar 18;332(7542):659-62. doi: 10.1136/bmj.332.7542.659. PMID: 16543339; PMCID: PMC1403258.
  4. Alberman E, Berry C. Prenatal diagnosis and the specialist in community medicine. Community Med 1979;1:89–96.
  5. Katherine L. Frohlich, Louise Potvin, “Transcending the Known in Public Health Practice”, American Journal of Public Health 98, no. 2 (February 1, 2008): pp. 216-221.

Author: Prasantha De Silva

A specialist in Community Medicine board-certified in Sri Lanka and a research analyst in Canada

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