Bicycle Helmet - Science: Measuring Helmet Effectiveness - Desirable Effects of Helmet Use - Time-trend Analyses

Time-trend Analyses

Time-trend analyses compare changes in helmet use and injury rates in populations over time. This type of study usually shows that as helmet-use increases, head injury rates among cyclists do not fall faster than for road users without helmets such as pedestrians and motorists.

Authors do not agree on how studies should be selected for analysis, nor on what summary statistics are most relevant. Potential weaknesses of this type of study include: simultaneous changes in the road environment (e.g. drink-drive campaigns); inaccuracy of exposure estimates (numbers cycling, distance cycled etc.), changes in the definitions of the data collected, failure to analyse control groups, failure to analyse long-term trends, and the ecological fallacy.

Robinson's reviews of cyclists and control groups in jurisdictions where helmet use increased by 40% or more following compulsion conclude that enforced helmet laws discourage cycling but produce no obvious response in percentage of head injuries. These studies have been the subject of vigorous debate. A review, by Macpherson and Spinks, which included two original papers (neither of which meet the criteria for inclusion in Robinson's review), concluded that "Bicycle helmet legislation appears to be effective in increasing helmet use and decreasing head injury rates in the populations for which it is implemented. However, there are very few high-quality evaluative studies that measure these outcomes, and none that reported data on an (sic) possible declines in bicycle use." Later work by Macpherson's group admitted that this conclusion had been erroneous and that "Although bicycle-related injuries are generally declining, this decline is not consistent, nor is it clearly associated with helmet laws."

One study covering eight million cyclist injuries over 15 years, showed no effect on serious injuries and a small but significant increase in risk of fatality. Although the head injury rate in the US rose in this study by 40 % as helmet use rose from 18 % to 50 %, this is a time-trend analysis with the potential weaknesses mentioned above; the correlation may not be causal. Association with increased risk has been reported in other studies. Different analyses of the same data can produce different results. For example, Scuffham analysed data on the increase of voluntary wearing in New Zealand to 1995; he concluded that, after taking into account long-term trends, helmets had no measurable effect. His subsequent re-analysis without accounting for the long-term trends suggested a small benefit. Scuffham's later cost-benefit analysis of the New Zealand helmet law showed that the cost of helmets outweighed the savings in injuries, even taking the most optimistic estimate of injuries prevented.

Read more about this topic:  Bicycle Helmet, Science: Measuring Helmet Effectiveness, Desirable Effects of Helmet Use

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