Literature DB >> 22473632

States with low non-fatal injury rates have high fatality rates and vice-versa.

John Mendeloff1, Rachel Burns.   

Abstract

BACKGROUND: State-level injury rates or fatality rates are sometimes used in studies of the impact of various safety programs or other state policies. How much does the metric used affect the view of relative occupational risks among U.S. states? This paper uses a measure of severe injuries (fatalities) and of less severe injuries (non-fatal injuries with days away from work, restricted work, or job transfer-DART) to examine that issue.
METHODS: We looked at the correlation between the average DART injury rate (from the BLS Survey of Occupational Injuries and Illnesses) and an adjusted average fatality rate (from the BLS Census of Fatal Occupational Injuries) in the construction sector for states for 2003-2005 and for 2006-2008. The RAND Human Subjects Protection Committee determined that this study was exempt from review.
RESULTS: The correlations between the fatal and non-fatal injury rates were between -0.30 and -0.70 for all construction and for the subsector of special trade contractors. The negative correlation was much smaller between the rate of fatal falls from heights and the rate of non-fatal falls from heights. Adjusting for differences in the industry composition of the construction sector across states had minor effects on these results.
CONCLUSION: Although some have suggested that fatal and non-fatal injury rates should not necessarily be positively correlated, no one has suggested that the correlation is negative, which is what we find. We know that reported non-fatal rates are influenced by workers' compensation benefits and other factors. Fatality rates appear to be a more valid measure of risk. Efforts to explain the variations that we find should be undertaken.
Copyright © 2012 Wiley Periodicals, Inc.

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Year:  2012        PMID: 22473632     DOI: 10.1002/ajim.22047

Source DB:  PubMed          Journal:  Am J Ind Med        ISSN: 0271-3586            Impact factor:   2.214


  6 in total

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2.  Topic Modeling of Social Networking Service Data on Occupational Accidents in Korea: Latent Dirichlet Allocation Analysis.

Authors:  Kyoung-Bok Min; Sung-Hee Song; Jin-Young Min
Journal:  J Med Internet Res       Date:  2020-08-13       Impact factor: 5.428

3.  Exploring the relationship between employer recordkeeping and underreporting in the BLS Survey of Occupational Injuries and Illnesses.

Authors:  Sara E Wuellner; David K Bonauto
Journal:  Am J Ind Med       Date:  2014-08-05       Impact factor: 2.214

4.  Employer reasons for failing to report eligible workers' compensation claims in the BLS survey of occupational injuries and illnesses.

Authors:  Christina L Rappin; Sara E Wuellner; David K Bonauto
Journal:  Am J Ind Med       Date:  2016-03-11       Impact factor: 2.214

5.  Unreported workers' compensation claims to the BLS Survey of Occupational Injuries and Illnesses: Establishment factors.

Authors:  Sara E Wuellner; Darrin A Adams; David K Bonauto
Journal:  Am J Ind Med       Date:  2016-01-21       Impact factor: 2.214

6.  Using Improved Principal Component Analysis to Explore Construction Accident Situations from the Multi-Dimensional Perspective: A Chinese Study.

Authors:  Bo Shao; Zhigen Hu; Dawei Liu
Journal:  Int J Environ Res Public Health       Date:  2019-09-18       Impact factor: 3.390

  6 in total

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