Citation

van Beeck EF, Mackenbach JP, Looman CWN, Kunst AE. Int. J. Epidemiol. 1991; 20(3): 698-706.

Affiliation

Department of Public Health and Social Medicine, Erasmus University Rotterdam, The Netherlands.

Copyright

(Copyright © 1991, International Epidemiological Association, Publisher Oxford University Press)

DOI

unavailable

PMID

1955254

Abstract

In the Netherlands, a country with one of the lowest levels of traffic accident mortality in the world, large regional mortality differences can be observed. An analysis was performed of the contribution of regional differences in traffic mobility (kilometers travelled/person-years), injury rate (injured people/kilometre travelled) and case fatality (traffic deaths/injured people). Subsequently, possible determinants of regional differences in traffic accident mortality and its constituent parts were investigated. Both the influence of sociodemographic factors and of factors probably more directly related to traffic deaths (road infrastructure, medical care) was studied. Regional differences in traffic accident mortality in the Netherlands can only to a very limited extent be explained by regional differences in traffic mobility. Regional differences in case fatality seem to make the most important contribution. Of the sociodemographic factors that were used in the analysis, per capita income appears to be the strongest predictor of regional mortality differences. A higher income level is associated with lower mortality levels. Of the factors more directly related to traffic deaths, traffic density and the availability of advanced trauma care (neurosurgery and computerized tomography (CT-Scan)) in the region are the most important predictors of regional mortality differences. Both variables show an inverse relationship with case fatality. Probably a higher traffic density leads to a shift towards less severe injuries. The availability of advanced trauma care could be important in early diagnosis and treatment of head injuries. The results of this study, based on existing data sources, must be interpreted with care. Some potential sources of bias (omitted variables, regional differences in accident reporting) are discussed.

Language: en