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Biomedical subjects

S C Partyka

Publications and source records attributed to S C Partyka.

2 recordsLinked to original sources

Simple models of fatality trends revisited seven years later.

The author's original paper presented simple linear models of fatalities based on data through 1982 and appeared in this journal in 1984. The earlier paper reported good fits through 22 years of fatality counts using population and employment data, after adjusting for the short-term effect of the oil shortage (in 1974) and the long-term effect of the 55 mph speed limit (beginning in 1974). Attempts (reported here) to refit the model through seven additional years were less successful. It may be that the relationships originally reported have changed, that important new factors have been introduced, or that the original fits were partly luck. The recent emphasis on behavioral solutions to safety problems (including programs to decrease alcohol use and increase safety belt use) is one important change, so the effect of the benefits of these programs on the model fits is explored. The original model began to overpredict fatalities just as safety benefits were beginning to accrue from increased safety belt use and decreased driver-alcohol involvement, and both the model overprediction and the benefits of these programs increased over the seven years of data added to the original model. Thus, previous government estimates of the number of lives saved by these behavioral programs are supported by the observed change in the statistical relationship between fatality counts and economic factors.

Accidents, Traffic↗

Differences in reported car weight between fatality and registration data files.

Two national-level data sources are commonly used together to estimate and compare fatality rates by car weight. The weight of each car in a fatal crash is available on the automated files of the National Highway Traffic Safety Administration's Fatal Accident Reporting System; weight is derived by interpreting the Vehicle Identification Number of each car using a computer algorithm developed and maintained by R. L. Polk & Co. Counts of cars in use, by weight, are available on R. L. Polk & Co.'s National Vehicle Population Profile files; weights are coded from information in state vehicle registration files. However, it appears that there are systematic differences in car weight coding that complicate the use of these two sources together for calculating fatality rates (fatalities per registered car). Overall, the registration data appear to describe a car (of a particular make, model, and model year) as about one hundred pounds heavier than that car is described in the fatality data. The effect is to bias the comparison of fatalities per registered vehicle against lighter cars. Failure to consider this difference can lead to very misleading results. For example, the uncorrected data produce an estimate that the number of occupant fatalities per registered minicompact car (those under 1,950 pounds) was five times the rate in the largest cars (those weighing at least 3,950 pounds). Correcting for differences in car weight reporting produces estimates that the fatality rate in minicompact cars was twice that in the largest cars. Differences by car weight remain, but they are much less than would be concluded from the biased comparison.

Accident Prevention↗