The impact of non-fatal workplace injuries and illnesses on mortality

Opioid-related mortality after occupational injury in Washington State: accounting for preinjury opioid use

OBJECTIVES

To estimate the impact of occupational injury and illness on opioid-related mortality while accounting for confounding by preinjury opioid use.

METHODS

We employed a retrospective cohort study design using Washington State workers' compensation data for 1994-2000 injuries linked to US Social Security Administration earnings and mortality data and National Death Index (NDI) cause of death data from 1994 to 2018. We categorised injuries as lost-time versus medical-only, where the former involved more than 3 days off work or permanent disability. We determined death status and cause of death from NDI records. We modelled separate Fine and Gray subdistribution hazard ratios (sHRs) and 95% CIs for injured men and women for opioid-related and all drug-related mortality through 2018. We used quantitative bias analysis to account for unmeasured confounding by preinjury opioid use.

RESULTS

The hazard of opioid-related mortality was elevated for workers with lost-time relative to medical-only injuries: sHR for men: 1.53, 95% CI 1.41 to 1.66; for women: 1.31, 95% CI 1.16 to 1.48. Accounting for preinjury opioid use, effect sizes were reduced but remained elevated: sHR for men was 1.43, 95% simulation interval (SI) 1.20 to 1.69; for women: 1.27, 95% SI 1.10 to 1.45.

CONCLUSIONS

Occupational injuries and illnesses severe enough to require more than 3 days off work are associated with an increase in the hazard of opioid-related mortality. The estimated increase is reduced when we account for preinjury opioid use, but it remains substantial. Reducing work-related injuries and postinjury opioid prescribing and improving employment and income security may decrease opioid-related mortality.

Global, regional and national burdens of occupational injuries, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019

OBJECTIVES

Occupational injuries pose a significant challenge to global health and development. This study aimed to quantify the international and regional burdens of occupational injuries from 1990 to 2019, stratified by specific causes.

METHODS

We analysed global trends in deaths, disability-adjusted life years (DALYs), age-standardised mortality rates (ASMR) and age-standardised DALY rates (ASDR) related to occupational injuries. Specific injuries, including animal contact, drowning, mechanical forces, falls, fire, heat, hot substances, foreign bodies, poisoning and road injuries, were evaluated. Age-stratified and regional analyses were also performed.

RESULTS

Globally, the number of deaths, DALYs, ASMR and ASDR related to occupational injuries declined from 1990 to 2019. The middle Socio-demographic Index (SDI) region exhibited the highest burden, whereas the high SDI region showed the least burden. China and India had the highest occupational injury-related death rates in 2019. Males, particularly those aged 25-44 years, were found to be more vulnerable. Road injuries were the leading cause of death in all age groups. Compared with 1990, mortality numbers and rates decreased significantly by 2019, with the highest burdens experienced in East Asia, South Asia and Southeast Asia.

CONCLUSION

The global decline in occupational injuries is promising; however, certain regions and demographics remain disproportionately affected. Targeted interventions in high-burden areas are crucial to further reduce the impact of occupational injuries.

Increased Mortality Associated With Disability Among Workers' Compensation Claimants With Upper Extremity Neuropathy

OBJECTIVE

The aim of the study was to evaluate and compare mortality after disabling and nondisabling occupational injuries.

METHODS

Vital status was ascertained through 2020 for 2077 individuals with a workers' compensation claim for upper extremity neuropathy in West Virginia in 1998 or 1999. Standardized mortality ratios compared mortality to the West Virginia general population. Hazard ratios (HRs) obtained from Cox regression models compared mortality among those with and without lost work time or permanent disability.

RESULTS

Overall, the standardized mortality ratio for accidental poisoning deaths was elevated (1.75, 95% confidence interval [CI]: 1.08-2.68). All-cause mortality HRs and cancer HRs were elevated for lost work time (HR = 1.09, 95% CI: 0.93-1.28; HR = 1.50, 95% CI: 1.09-2.08, respectively) and permanent disability (HR = 1.22, 95% CI: 1.04-1.44; HR = 1.78, 95% CI: 1.27-2.48, respectively).

CONCLUSIONS

Work-related disability was associated with broad elevations in mortality.

Increased all-cause mortality following occupational injury: a comparison of two states

OBJECTIVES

To measure the impact of lost-time occupational injuries on all-cause mortality in Washington State and, using the same data elements and study design, to determine whether the estimated impact was similar to previous estimates for New Mexico.

METHODS

We linked injuries in the Washington workers' compensation system with Social Security Administration data on earnings and mortality. We estimated Cox survival models of mortality for women and men with lost-time compared with medical-only injuries, adjusting for age, pre-injury earnings and industry. We used quantitative bias analysis to account for confounding by pre-injury smoking and obesity.

RESULTS

The estimated mortality HR was 1.24 for women (95% CI 1.21 to 1.28) and 1.22 for men (95% CI 1.20 to 1.24). After adjusting for unmeasured pre-injury smoking and obesity, the estimated HR for women was 1.10, 95% simulation interval (SI) 1.00 to 1.21; for men, it was 1.15, 95% SI 1.04 to 1.27.

CONCLUSIONS

All-cause mortality for Washington workers with lost-time injuries was higher than for those with medical-only injuries. Estimated HRs for Washington were consistent with those previously estimated for New Mexico, a less populous state with lower median wages and a different workers' compensation insurance mechanism. This suggests that the relationship between workplace injury and long-term mortality may be generalisable to other US states. These findings support greater efforts to enhance safety and to investigate factors that improve postinjury employment opportunities and long-term health. This association should be examined in additional locations, with different study conditions, or using additional data on pre-injury risk factors.

Dynamic prediction of work status for workers with occupational injuries: assessing the value of longitudinal observations

OBJECTIVE

Occupational injuries (OIs) cause an immense burden on the US population. Prediction models help focus resources on those at greatest risk of a delayed return to work (RTW). RTW depends on factors that develop over time; however, existing methods only utilize information collected at the time of injury. We investigate the performance benefits of dynamically estimating RTW, using longitudinal observations of diagnoses and treatments collected beyond the time of initial injury.

MATERIALS AND METHODS

We characterize the difference in predictive performance between an approach that uses information collected at the time of initial injury (baseline model) and a proposed approach that uses longitudinal information collected over the course of the patient's recovery period (proposed model). To control the comparison, both models use the same deep learning architecture and differ only in the information used. We utilize a large longitudinal observation dataset of OI claims and compare the performance of the two approaches in terms of daily prediction of future work state (working vs not working). The performance of these two approaches was assessed in terms of the area under the receiver operator characteristic curve (AUROC) and expected calibration error (ECE).

RESULTS

After subsampling and applying inclusion criteria, our final dataset covered 294 103 OIs, which were split evenly between train, development, and test datasets (1/3, 1/3, 1/3). In terms of discriminative performance on the test dataset, the proposed model had an AUROC of 0.728 (90% confidence interval: 0.723, 0.734) versus the baseline's 0.591 (0.585, 0.598). The proposed model had an ECE of 0.004 (0.003, 0.005) versus the baseline's 0.016 (0.009, 0.018).

CONCLUSION

The longitudinal approach outperforms current practice and shows potential for leveraging observational data to dynamically update predictions of RTW in the setting of OI. This approach may enable physicians and workers' compensation programs to manage large populations of injured workers more effectively.

Mortality following workplace injury: Quantitative bias analysis

PURPOSE

Recent studies have shown increased all-cause mortality among workers following disabling workplace injury. These studies did not account for 2 potentially important confounders, smoking and obesity. We estimated injury-related mortality accounting for these factors.

METHODS

We followed workers receiving New Mexico workers' compensation benefits (1994-2000) through 2013. Using data from the Panel Study of Income Dynamics, we derived the joint distribution of smoking status and obesity for workers with and without lost-time injuries. We conducted a quantitative bias analysis (QBA) to determine the adjusted relationship of injury and mortality.

RESULTS

We observed hazard ratios after adjusting for smoking and obesity of 1.13 for women (95% simulation interval (SI) 0.97 to 1.31) and 1.12 for men (95% SI 1.00 to 1.27). The estimated fully adjusted excess hazard was about half the estimates not adjusted for these factors.

CONCLUSIONS

Using QBA to adjust for smoking and obesity reduced the estimated mortality hazard from lost-time injuries and widened the simulation interval. The adjusted estimate still showed more than a 10 percent increase for both women and men. The change in estimates reveals the importance of accounting for these confounders. Of course, the results depend on the methods and assumptions used.

Drug overdose mortality is associated with employment status and occupation in the National Longitudinal Mortality Study

BACKGROUND

Since 1999, over 702,000 people in the US have died of a drug overdose, and the drug overdose death rate has increased from 6.2 to 21.8 per 100,000. Employment status and occupation may be important social determinants of overdose deaths.

OBJECTIVES

Estimate the risk of drug overdose death by employment status and occupation, controlling for other social and demographic factors known to be associated with overdose deaths.

METHODS

Proportional hazard models were used to study US adults in the National Longitudinal Mortality Study with baseline measurements taken in the early 2000s and up to 6 years of follow-up (n = 438,739, 53% female, 47% male). Comparisons were made between adults with different employment statuses (employed, unemployed, disabled, etc.) and occupations (sales, construction, service occupations, etc.). Models were adjusted for age, sex, race/ethnicity, education, income and marital status.

RESULTS

Adults who were disabled (hazard ratio (HR) = 6.96 (95% CI = 6.81-7.12)), unemployed (HR = 4.20, 95% CI = 4.09-4.32) and retired (HR = 2.94, 95% CI = 2.87-3.00) were at higher risk of overdose death relative to those who were employed. By occupation, those working in service (HR = 2.05, 95% CI = 1.97-2.13); construction and extraction (HR = 1.69, 95% CI = 1.64-1.76); management, business and financial (HR = 1.39, 95% CI = 1.33-1.44); and installation, maintenance and repair (HR = 1.32, 95% CI = 1.25-1.40) occupations displayed higher risk relative to professional occupations.

CONCLUSIONS

In a large national cohort followed prospectively for up to 6 years, several employment statuses and occupations are associated with overdose deaths, independent of a range of other factors. Efforts to prevent overdose deaths may benefit from focusing on these high-risk groups.

Increased overall and cause-specific mortality associated with disability among workers' compensation claimants with low back injuries

BACKGROUND

Mortality tends to be higher among people who do not work than among workers, but the impact of work-related disability on mortality has not been well studied.

METHODS

The vital status through 2015 was ascertained for 14 219 workers with an accepted workers' compensation claim in West Virginia for a low back injury in 1998 or 1999. Mortality among the cohort compared with the West Virginia general population was assessed using standard life table techniques. Associations of mortality and disability-related factors within the cohort were evaluated using Cox proportional hazards regression.

RESULTS

Compared to the general population, mortality from accidental poisoning was significantly elevated among the overall cohort and lost-time claimants. Most deaths from accidental poisoning in the cohort were due to drug overdoses involving opioids. Mortality from intentional self-harm was also significantly elevated among lost-time claimants. In internal analyses, overall mortality and mortality from cancer, heart disease, intentional self-harm, and drug overdoses involving opioids was significantly associated with lost time. Overall mortality and mortality from drug overdoses involving opioids were also significantly associated with amount of lost time, permanent partial disability, and percent permanent disability. Heart disease mortality was also significantly associated with the amount of lost time.

CONCLUSIONS

The results suggest that disability itself may impact mortality risks. If confirmed, these results reinforce the importance of return to work and other efforts to reduce disability.

Suicide and drug-related mortality following occupational injury

BACKGROUND

Drug overdoses and suicides have been rising since 2000 and are major contributors to a 3-year decline in US life expectancy. Studies suggest that injured workers have elevated rates of depression and opioid use, but no studies have measured excess mortality related to these risks.

MATERIALS AND METHODS

We linked New Mexico workers' compensation data for 100 806 workers injured in 1994 through 2000 with Social Security Administration earnings and mortality data through 2013 and National Death Index cause of death data. We then estimated the association between receiving lost-time workers' compensation benefits and mortality hazard ratios (HRs) and 95% confidence intervals (CIs) based on Fine and Gray cause-specific subdistribution hazards for common causes of death and for drug-related, suicide, and alcohol-related mortality.

RESULTS

There was almost a 3-fold increase in combined drug-related and suicide mortality hazard among women (HR = 2.63, 95% CI = 1.91-3.64) and a substantial increase among men (HR = 1.42, 95% CI = 1.13-1.79). Circulatory disease mortality hazard was elevated for men (HR = 1.25, 95% CI = 1.05-1.50).

CONCLUSION

Workplace injuries severe enough to require more than a week off work may impair workers' long-term health and well-being. Drug-related deaths and suicides may be important contributors to the long-term excess mortality of injured workers. Improved workplace conditions, improved pain treatment, better treatment of substance use disorders, and treatment of postinjury depression may substantially reduce mortality consequent to workplace injuries.

Use of Logistic Regression to Identify Factors Influencing the Post-Incident State of Occupational Injuries in Agribusiness Operations

Agribusiness industries are among the most hazardous workplaces for non-fatal occupational injuries. The term “post-incident state” is used to describe the health status of an injured person when a non-fatal occupational injury has occurred, in the post-incident period when the worker returns to work, either immediately with zero days away from work (medical state) or after a disability period (disability state). An analysis of nearly 14,000 occupational incidents in agribusiness operations allowed for the classification of the post-incident state as medical or disability (77% and 23% of the cases, respectively). Due to substantial impacts of occupational incidents on labor-market outcomes, identifying factors that influence the severity of such incidents plays a significant role in improving workplace safety, protecting workers, and reducing costs of the post-incident state of an injury. In addition, the average costs of a disability state are significantly higher than those of a medical state. Therefore, this study aimed to identify the contributory factors to such post-incident states with logistic regression using information from workers’ compensation claims recorded between 2008 and 2016 in the Midwest region of the United States. The logistic regression equation was derived to calculate the odds of disability post-incident state. Results indicated that factors influencing the post-incident state included the injured body parts, injury nature, and worker’s age, experience, and occupation, as well as the industry, and were statistically significant predictors of post-incident states. Specific incidents predicting disability outcomes included being caught in/between/under, fall/slip/trip injury, and strain/injury by. The methodology and estimation results provide insightful understanding of the factors influencing medical/disability injuries, in addition to beneficial references for developing effective countermeasures for prevention of occupational incidents.