This week both the Daily Telegraph and the Daily Mail ran stories claiming that switching off street lights could significantly increase the number of road
deaths. The stories were based on a paper published in the Cochrane Library, which considered three studies into the connection between road accidents and street lighting. However, it seems that the headlines are a typical example of misinterpretation of statistics.
As David Spiegelhalter, Professor for the Public Understanding of Risk at the University of Cambridge, writes on his website Understanding Uncertainty, the studies suffer from three major flaws: poor data, publication bias, and what's known as regression to the mean. Spiegelhalter points out that the three studies underlying the
paper were poor and conducted decades ago, with one dating from as far back as 1948 — not a very good basis for drawing conclusions about today's traffic. The term publication bias refers to the fact that studies which show dramatic results are more likely to be published than those that don't. It's quite possible that there were other studies, which found no connection between street
lights and accidents, but that no-one bothered to publish such boring results. Regression to the mean is a commonly observed effect, which results from random fluctuations. If street lights were installed on a certain road, then this is most likely because that road recently experienced a spade of accidents. Such a freak period can be purely down to chance, in which case one would expect the
accident rate to return to normal after a while. Thus the improved accident rate after the installation of lights may be purely down to chance, rather than the improved lighting.
All this doesn't of course mean that street lights are useless. It simply means that the evidence is nowhere near as sound as the newspaper headlines claim. The Daily Mail, to its credit, did consult an expert, namely Spiegelhalter, but it's probably the headline, rather than his warning, that will stick in readers' minds.
If you're interested in matters of uncertainty and risk, then visit the Understanding Uncertainty website, or read Spiegelhalter's column in Plus.
Labels: Health and medicine