The Impact of Job Loss on Self-Injury Mortality in a Cohort of Autoworkers: Application of a Novel Causal Approach
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2022/05/01
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Description:Background: Recent increases in national rates of suicide and fatal overdose have been linked to a deterioration of economic and social stability. The American auto industry experienced comparable pressures beginning in the 1980s with the emergence of a competitive global market. Methods: Using the United Autoworkers-General Motors (GM) cohort as a case study, we examine the impact of employment loss on these self-injury mortality events. For 29,538 autoworkers employed on or after 1 January 1970, we apply incremental propensity score interventions, a novel causal inference approach, to examine how proportional shifts in the odds of leaving active GM employment affect the cumulative incidence of self-injury mortality. Results: Cumulative incidence of self-injury mortality was 0.87% (255 cases) at the observed odds of leaving active GM employment (d = 1) over a 45-year period. A 10% decrease in the odds of leaving active GM employment (d = 0.9) results in an estimated 8% drop in self-injury mortality (234 cases) while a 10% increase (d = 1.1) results in a 19% increase in self-injury mortality (303 cases). Conclusions: These results are consistent with the hypothesis that leaving active employment at GM increases the risk of death due to suicide or drug overdose. [Description provided by NIOSH]
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ISSN:1044-3983
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Pages in Document:386-394
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Volume:33
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Issue:3
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NIOSHTIC Number:nn:20067928
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Citation:Epidemiology 2022 May; 33(3):386-394
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Contact Point Address:Suzanne M. Dufault, Division of Biostatistics, University of California, Berkeley, 2121 Berkeley Way, Room 5302, Berkeley, CA 94720-7360
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Email:sdufault@berkeley.edu
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Federal Fiscal Year:2022
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Performing Organization:University of California, Berkeley
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Peer Reviewed:True
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Start Date:20050701
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Source Full Name:Epidemiology
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End Date:20250630
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Main Document Checksum:urn:sha-512:170628d4ae07bdd61af60a900061b02b009a6aa880b1c1bd0c20a40289f607eef614ecf7572a47c9eec9008bf075b92c3fd8bc29ede11299e8e390322bb5ce3c
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