CUMULATIVE INCIDENCE OF AND RISK FACTORS FOR WAD
The cumulative incidence is the number of new cases of an event or outcome occurring in a population over a certain time period. Some evidence from the literature indicates that the incidence of WAD differs between countries. There is also some evidence that the incidence of WAD has increased from the beginning of the 1990s to after the year 2000, with the annual incidence for the latter period being about 300 per 100,000 inhabitants in the studies where emergency setting visits are used. In some instances, the increase is between three and tenfold. It is not known if this increase is partly due to a change in care-seeking behavior.
There are also some indications from administrative insurance claims database in different European countries (e.g. Norway, the Netherlands and Sweden) of a reduction in the number of WAD claims, whereas such decreases have not been seen in Denmark or the United Kingdom. Sweden, for instance, has seen a 33% decrease in personal motor vehicle crash (MVC) injury claims between 2002 and 2008. The relative decrease is similar between the incidence of WAD and other types of injuries, with WAD constituting about 50% of all MVC injury claims. This decrease is not due to reduction in the number of MVCs, and nor has the insurance system in Sweden changed. Instead, this decrease is likely to be due to a combination of reasons. For example, some care manufacturers have developed whiplash-protection devices for new car models, which presumably will result in fewer cases of WAS as a result of rear-end collisions. Secondly, during the second half of the 1990s, police personnel in Sweden showed an increased awareness that there is no need to advise car occupants to seek healthcare if no symptoms are present. Thirdly, the mass media focus in Sweden on whiplash has decreased substantially from over 800 articles in the beginning of the 2000s to only about 200 articles in 2008.
Incidence calculation through insurance claims may be prone to other forms of bias. For instance, insurance systems where there are no benefits for the person responsible for a collision may underestimate the frequency of injuries, since fewer claims would be reported. This would also happen with insurance systems where insurance claim access us limited, or where payments for compensation result in a significant increase in the insurance premium. On the other hand, healthcare data may also be prone to bias, since such data only captures those who seek the type of healthcare utilization in question (e.g. emergency care).