Effects of data limitations when modeling fatal occupational injury rates.
Bena-JF; Bailer-AJ; Loomis-D; Richardson-D; Marshall-S
Am J Ind Med 2004 Sep; 46(3):271-283
Occupational fatal injury rate studies are often based upon uncertain and variable data. The numerator in rate calculations is often obtained from surveillance systems that can understate the true number of deaths. Worker-years, the denominator in many occupational rate calculations, are frequently estimated from sources that exhibit different amounts of variability. Effects of these data limitations on analyses of trends in occupational fatal injuries were studied using computer simulation. Fatality counts were generated assuming an undercount. Employment estimates were produced using two different strategies, reflecting either frequent but variable measurements or infrequent, precise estimates with interpolated estimates for intervening years. Poisson regression models were fit to the generated data. A range of empirically motivated fatality rate and employment parameters were studied. Undercounting fatalities resulted in biased estimation of the intercept in the Poisson regression model. Relative bias in the trend estimate was near zero for most situations, but increased when a change in fatality undercounting over time was present. Biases for both the intercept and trend were larger when small employment populations were present. Denominator options resulted in similar rate and trend estimates, except where the interpolated method did not capture true trends in employment. Data quality issues such as consistency of conditions throughout the study period and the size of population being studied affect the size of the bias in parameter estimation.
Injuries; Traumatic-injuries; Occupational-hazards; Occupational-health; Surveillance-programs; Mortality-data; Mortality-rates; Computer-models; Simulation-methods; Models
James F. Bena, Department of Biostatistics and Epidemiology/Wb4, 9500 Euclid Avenue, Cleveland, OH 44195
Research Tools and Approaches: Risk Assessment Methods
American Journal of Industrial Medicine