What is Prevention Paradox?

Geoffrey Rose, an epidemiologist from the London School of Hygiene and Tropical Medicine coined the term “prevention paradox”.

In 1985 he popularized the concept through his paper under the title of “sick individuals and sick populations” and published in the International Journal of Epidemiology. In 2001, The World Health Organization’s bulletin reproduced this paper under its classic papers series.

This paper created an interesting and sustained debate about prevention strategies in the public health sector. To date, the paper has been cited by 4166 articles in the world according to Google search.

What is the prevention paradox?

To discuss the prevention paradox, I am using two examples that appeared in the Rose’s paper.

Example 1: More heart attacks from those with lower risk

Look at the following graph that I created using data published in Rose’s paper. He had obtained this data from the UK Heart Disease Prevention Project.

“Prevention paradox in heart health”
Created by Prasantha De Silva using data published in the
Rose paper, p.37.

The brown color represents the proportions of those who suffered a heart attack (myocardial infarction) out of all attacks reported during a 5-year period at 3 different increasing risk severity situations: the presence of risk factors, the presence of ischemia, and the presence of both risk factors and ischemia.

The blue color (including its shadow under the brown color) refers to the distribution of increasing risk severity. 7%, 11%, and 22%. For example,7 percent denotes that only 7 percent of those with risk factors suffered an attack. This percentage increases with ischemia to 11 percent. When both factors exist together, the risk reaches its highest: 22 percent.

What do you notice in the graph?

Contrary to our normal expectations, the majority of events occurred not among those with the highest risk, but among those with the lowest risk; This is the paradox.

Rose called it prevention paradox because, although we can certainly prevent attacks by screening the highest risk group and treating them, we can yield maximum benefit only by preventing events among those with the lowest risk.

Example 2: Down syndrome and its risk severity

Now, look at this graph, again, created by myself using data published in the same paper.

“Prevention paradox in Downs syndrome”: created by Prasantha De Silva using data published in the Rose paper, p. 37

As in the case of the previous graph, the brown color represents the proportions of cases of Down syndrome out of all reported and the blue color denotes the risk percentages of having such a baby relevant to maternal age. We all know that the risk rises with maternal age; the risk is lowest among those younger than 34 years and highest among those aged 45 and above. However, more than half the cases originate not among the highest risk but the lowest risk because of the relatively higher number of young women.

In another post, I discussed how another researcher demonstrated the existence of prevention paradox in alcohol-related problems. You can read that through this link: https://www.researchenthusiast.science/prevention-paradox-in-preventing-alcohol-problems/.

Author: Prasantha De Silva

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

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