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  • Title: The effect of rate denominator source on US fatal occupational injury rate estimates.
    Author: Richardson D, Loomis D, Bailer AJ, Bena J.
    Journal: Am J Ind Med; 2004 Sep; 46(3):261-70. PubMed ID: 15307125.
    Abstract:
    BACKGROUND: The Current Population Survey (CPS) is often used as a source of denominator information for analyses of US fatal occupational injury rates. However, given the relatively small sample size of the CPS, analyses that examine the cross-classification of occupation or industry with demographic or geographic characteristics will often produce highly imprecise rate estimates. The Decennial Census of Population provides an alternative source for rate denominator information. We investigate the comparability of fatal injury rates derived using these two sources of rate denominator information. METHODS: Information on fatal occupational injuries that occurred between January 1, 1983 and December 31, 1994 was obtained from the National Traumatic Occupational Fatality surveillance system. Annual estimates of employment by occupation, industry, age, and sex were derived from the CPS, and by linear interpolation and extrapolation from the 1980 and 1990 Census of Population. Fatal injury rates derived using these denominator data were compared. RESULTS: Fatal injury rates calculated using Census-based denominator data were within 10% of rates calculated using CPS data for all major occupation groups except farming/forestry/fishing, for which the fatal injury rate calculated using Census-based denominator data was 24.69/100,000 worker-years and the rate calculated using CPS data was 19.97/100,000 worker-years. The choice of denominator data source had minimal influence on estimates of trends over calendar time in the fatal injury rates for most major occupation and industry groups. CONCLUSIONS: The Census offers a reasonable source for deriving fatal injury rate denominator data in situations where the CPS does not provide sufficiently precise data, although the Census may underestimate the population-at-risk in some industries as a consequence of seasonal variation in employment.
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