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Marginal structural modeling of associations of occupational injuries with voluntary and involuntary job loss among nursing home workers
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Jan 19 2016
Source: Occup Environ Med. 73(3):175-182
Details:
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Alternative Title:Occup Environ Med
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Description:Objectives
Qualitative studies have highlighted the possibility of job loss following occupational injuries for some workers, but prospective investigations are scant. We used a sample of nursing home workers from the Work, Family, and Health Network to prospectively investigate association between occupational injuries and job loss.
Methods
We merged data on 1331 workers assessed four times over an 18-month period with administrative data that include job loss from employers and publicly-available data on their workplaces. Workers self-reported occupational injuries in surveys. Multivariable logistic regression models estimated risk ratios for the impact of occupational injuries on overall job loss, whereas multinomial models were used to estimate odds ratio of voluntary and involuntary job loss. Use of marginal structural models allowed for adjustments of multilevel list of confounders that may be time-varying and/or on the causal pathway.
Results
By 12 months, 30.3% of workers experienced occupational injury, whereas 24.2% experienced job loss by 18 months. Comparing workers who reported occupational injuries to those reporting no injuries, risk ratio of overall job loss within subsequent 6 months was 1.31 (95% CI=0.93–1.86). Comparing the same groups, injured workers had higher odds of experiencing involuntary job loss (OR:2.19; 95% CI:1.27–3.77). Also, compared to uninjured workers, those injured more than once had higher odds of voluntary job loss (OR:1.95; 95% CI:1.03–3.67), while those injured once had higher odds of involuntary job loss (OR:2.19; 95% CI:1.18–4.05).
Conclusions
Despite regulatory protections, occupational injuries were associated with increased risk of voluntary and involuntary job loss for nursing home workers.
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Pubmed ID:26786757
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Pubmed Central ID:PMC4904717
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