Francis Papon, Institut National de Recherche sur les Transports et leur Sécurité

The following are excerpts from Francis Papon's paper (Excerpted by Eran Shchori, 'Israel Bicycle Association')

Abstract

A possible decrease in cycling that would be induced by a bicycle helmet program designed without caution.

Background

Helmets are effective at protecting cyclists at the individual level. At the society level, the effectiveness of helmet actions at reducing cyclists’ injuries is more disputed.

the effectiveness of helmets at protecting cyclists at the individual level cannot be replicated at the society level, because of complex interactions with the environment. To take them into account, ecological studies are needed.

helmet policies could reduce the number of cyclists and then make the remaining cyclists less safe, as a greater number of cyclists leads to a reduced individual risk for each cyclist.

Less cycling would reduce the health benefits of cycling, benefits that generally far offset accident risks. These benefits and risks were estimated in France at 0.57 versus 0.23 euro per kilometre in Papon (2002) at the individual level.  In New Zealand, the proposed health benefit value is 0.92 euro per kilometre (Genter et al., 2008). These benefits ground several governmental reports recommending an increase in bicycling (Toussaint, 2008). From the premise of the ratio of health benefit to accident risks (called “beta”), de Jong (2009) theoretically proved that helmet laws are counterproductive in terms of net health benefits.

The aim of this paper is not to discuss the effectiveness of helmet policies in general, but to make a contribution to the critical point of the effect of helmets on the level of cycling. We state the hypothesis that helmeted cyclists cycle less than not helmeted cyclists.

Description of the data used

The data used are those from the National Travel Survey passed in France in 2007-2008 to a sample of approximately 20,000 households including 45,000 individuals, in face to face interviews during two visits amounting to a total of more than two hours.

Helmet wearing at the individual level

On average, 77% of cyclists never wear a helmet.

The most important variable explaining helmet wearing is age. Children aged 6 to 9 declare the highest proportion of helmet wearing. The proportion sharply decreases for those aged 10 to 14 and then again for those aged 15 to 19: teenagers are known to be reluctant to helmet wearing.

Results of first stage: direct comparison

1. Probability of a bicycle trip

The first evidence is that occasional cyclists do have a significant lower probability of bicycle trip than regular cyclists, whatever the helmet behaviour (always wearing helmet, regularly wearing helmet, occasionally wearing helmet). The ratio of the probability of bicycle trip by regular cyclists never wearing a helmet to that of occasional cyclists never wearing a helmet is 9.6.

Regular cyclists always wearing a helmet do have a significantly lower probability of bicycle trip than regular cyclists occasionally or never wearing a helmet. Besides, regular cyclists never wearing helmet do have a significantly higher probability of bicycle trip than regular cyclists always or regularly wearing a helmet. 

2. Number of bicycle trips

Occasional cyclists perform a significant lower number of bicycle trips than regular cyclists, whatever the helmet behaviour. The ratio of the number of bicycle trips by regular cyclists never wearing a helmet to that of occasional cyclists never wearing a helmet is 11.9. 

Regular cyclists always wearing a helmet do perform a significantly lower number of bicycle trips than regular cyclists occasionally or never wearing a helmet. Besides, regular cyclists never wearing a helmet do perform a significantly higher number of bicycle trips than regular cyclists wearing a helmet with any of the other three frequencies (always wearing helmet, regularly wearing helmet, occasionally wearing helmet).

Results of second stage: modelling

1. Separated helmet effect for all individuals, linear models

Compared with those who never cycles, regular and occasional cyclists do significantly cycle more by the two measures.

Compared with those who never wear a helmet, all other helmet behaviours entail fewer trips and fewer time bicycling.

2. Crossed helmet and cycling behaviour for all individuals, logistic model

Regular cyclists who never wear a helmet have a probability of performing a bicycle trip higher by a factor 2.5 than regular cyclists who always wear a helmet.

In summary, concerning regular cyclists, models confirm that helmet always wearers cycle 2.5 times less often and perform 0.4 fewer cycling trips.

 

Discussion 

Both stages yield convergent results.

 

Direct comparison shows the following: regular cyclists always wearing a helmet have a probability of bicycling on selected weekday divided by 2.4, a bicycle trip rate divided by 3.1, total time bicycling divided by 1.4, as compared with regular cyclists never wearing a helmet, with no significant difference for occasional cyclists.

 

A linear model with separated helmet variable provides the following: cyclists always wearing a helmet have a bicycle trip rate reduced by 0.15 trip per day as compared with cyclists never wearing a helmet.

 

A logistic model with crossed helmet variable derives the following: regular cyclists always wearing a helmet have a probability of bicycling on selected weekday divided by 2.5, as compared with regular cyclists never wearing a helmet, while for respective occasional cyclists categories, the probability is multiplied by 1.7.

 

As regular cyclists perform four weekday trips out of five in France, there is clear evidence that helmet behaviour is correlated with cycling level, and that helmeted cyclists cycle less than their bare head companions. From there, it is interesting to discuss the implication of this behavioural outcome for the effectiveness and design of helmet programs.

 

Source: Francis Papon, Institut National de Recherche sur les Transports et leur Sécurité

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