BACKGROUND: Work is a key social determinant of health. Without the collection of work-related information in public health data systems, the role of social determinants in creating and reinforcing health disparities cannot be fully assessed. METHODS: The Centers for Disease Control and Prevention (CDC) maintains or supports a number of public health surveillance and health monitoring systems, including surveys, case-based disease and exposure systems, vital status records, and administrative data systems. We evaluated a convenience sample of these systems for inclusion of information in three work-related domains: employment status, industry and occupation, and working conditions. RESULTS: While 12 of 39 data systems were identified as collecting work-related data, this information was often minimal (e.g., only employment status), restricted to a subset of respondents, or only gathered periodically. Information on working conditions was particularly sparse. CONCLUSION: Historically, the limited and inconsistent collection of work-related information in public health data systems has hindered understanding of the role work plays in health disparities. Current CDC data modernization efforts present opportunities to enhance the identification and mitigation of health disparities by prioritizing inclusion of an expanded set of work-related data elements.

OBJECTIVES: To compare opioid prescription incidence, supply days, and cost associated with occupational injury and other injury-caused conditions. METHODS: We used Medical Expenditure Panel Survey (MEPS) data for 2010-2019. MEPS provides information on medical conditions and associated medical encounters, treatments, and treatment costs, as well as demographic, education, health, working status, income, and insurance coverage information. We used descriptive statistics and logistic and two-part regressions. RESULTS: Controlling for covariates and compared to other injury-caused conditions, occupational injury-caused conditions resulted in 33% higher odds of opioid prescribing, 32.8 more opioid prescription supply days, and $134 higher average cost. CONCLUSION: Occupational injuries were associated with higher opioid incidence and costs, and more opioid supply days. These findings point to the need to focus on making work safer and the role employers may play in supporting worker recovery from injury and opioid use disorders.

We write to augment a discussion point from our article1 recently published in AJIM, “Employment Status, Unemployment Duration, and Health-Related Metrics among U.S. Adults of Prime Working Age: Behavioral Risk Factor Surveillance System, 2018-2019.” In that discussion, we noted that “Decoupling these observed associations [between unemployment and the elevated prevalence of multiple adverse health outcomes] will require addressing 1) social and economic factors contributing to unemployment; 2) job and income insecurity; and 3) healthcare access, which in the U.S. is related to employment both directly (through employer-based coverage) and indirectly (through income).”

Measuring the ultimate impact of research on health and economic well-being has presented challenges that have rarely been surmounted, and research on preventing occupational injuries and illnesses is no exception. Nevertheless, there is an increasing need to demonstrate the value of publicly funded research. The National Institute for Occupational Safety and Health (NIOSH) recently contracted with the RAND Corporation to conduct six in-depth case studies that aimed to quantify the benefits of key NIOSH research efforts using economic metrics. These case studies focused on silica exposure in asphalt pavement milling, firefighter cancer risks, a multi-industry matching-grant program for purchase of safety equipment, personal coal dust monitors for coal miners, re-design of ambulance patient compartments for safety, and workplace amputation surveillance. In this article, we summarize what we learned about how measurement of research benefits may be pursued. We summarize the benefit measurement methods that were used and the results of these research efforts in terms of costs saved, injuries and illnesses prevented, and the statistical value of reductions in risk of death or illness. We then distill some observations about the characteristics of research efforts that make measurement of research benefits feasible and suggest steps that could make it feasible to apply the same methods more widely. We also outline key NIOSH activities that appear not to be amenable to benefit measurement but suggest potentials for progress toward at least partial or qualitative benefit assessment. Finally, we discuss implications of the benefit measurement case studies for strategic research planning.

BACKGROUND: While unemployment has been associated with poor health, few recent studies in the United States have comprehensively assessed associations between employment status (including duration unemployed) and healthcare access, health-related behaviors, and specific health outcomes. METHODS: We assessed health-related metrics by employment status in 2018-2019 Behavioral Risk Factor Surveillance System respondents ages 25-54. We calculated the unadjusted prevalence and adjusted prevalence ratios to compare employed workers to respondents who were self-employed, short-term (<12 months) unemployed, long-term unemployed, and unable to work. RESULTS: Adverse health outcomes increased with unemployment duration and were highest for those unable to work. Non-Hispanic Blacks were most likely to be unemployed or unable to work. Short-term unemployment and self-employment were associated with poor healthcare access. Health behaviors and outcomes declined with increasing duration of unemployment and were worst for those unable to work. CONCLUSIONS: In the United States, access to affordable healthcare is problematic for both the self-employed and the short-term unemployed. Short-term unemployment is a particularly important locus for intervention and provision of resources to prevent health declines that may hinder re-employment.

BACKGROUND: The benefits of nonstandard work hours include increased production time and the number of jobs. While for some sectors, such as emergency services, around-the-clock work is a necessary and critical societal obligation, work outside of traditional daytime schedules has been associated with many occupational safety and health hazards and their associated costs. Thus, organizational- and policy-level decisions on nonstandard work hours can be difficult and are based on several factors including economic evaluation. However, there is a lack of systematic knowledge of economic benefits and costs associated with these schedules. METHODS: We conducted a scoping review of the methodology and data used to examine the economic benefits and costs of nonstandard work hours and related interventions to mitigate risks. RESULTS: Ten studies met all our inclusion criteria. Most studies used aggregation and analysis of national and other large datasets. Costs estimated include health-related expenses, productivity losses, and projections of future loss of earnings. Cost analyses of interventions were provided for an obstructive sleep apnea screening program, implementation of an employer-based educational program, and increased staffing to cover overtime hours. CONCLUSIONS: A paucity of studies assess nonstandard work hours using economic terms. Future studies are needed to expand economic evaluations beyond the employer level to include those at the societal level because impacts of nonstandard work go beyond the workplace and are important for policy analysis and formulation. We pose the opportunity for researchers and employers to share data and resources in the development of more analyses that fill these research gaps.

AIMS: Gulf War Illness (GWI), a chronic debilitating disorder characterized by fatigue, joint pain, cognitive, gastrointestinal, respiratory, and skin problems, is currently diagnosed by self-reported symptoms. The Boston Biorepository, Recruitment, and Integrative Network (BBRAIN) is the collaborative effort of expert Gulf War Illness (GWI) researchers who are creating objective diagnostic and pathobiological markers and recommend common data elements for GWI research. MAIN METHODS: BBRAIN is recruiting 300 GWI cases and 200 GW veteran controls for the prospective study. Key data and biological samples from prior GWI studies are being merged and combined into retrospective datasets. They will be made available for data mining by the BBRAIN network and the GWI research community. Prospective questionnaire data include general health and chronic symptoms, demographics, measures of pain, fatigue, medical conditions, deployment and exposure histories. Available repository biospecimens include blood, plasma, serum, saliva, stool, urine, human induced pluripotent stem cells and cerebrospinal fluid. KEY FINDINGS: To date, multiple datasets have been merged and combined from 15 participating study sites. These data and samples have been collated and an online request form for repository requests as well as recommended common data elements have been created. Data and biospecimen sample requests are reviewed by the BBRAIN steering committee members for approval as they are received. SIGNIFICANCE: The BBRAIN repository network serves as a much needed resource for GWI researchers to utilize for identification and validation of objective diagnostic and pathobiological markers of the illness.

OBJECTIVES: We explored the impact of workplace injury on receiving opioid prescriptions from employer-sponsored private group health insurances (GHI) and how long injured workers receive opioid prescriptions after injury. METHODS: We used the difference-in-differences method and MarketScan databases for the years 2013 to 2015. RESULTS: Estimated odds for injured workers relative to non-injured workers to receive opioid prescriptions from the GHI within 60 and 180 days from the index date of injury were 4.9 and 1.5, respectively. In addition, the number of opioid prescriptions received within 60 days of injury was 2.5 times higher. CONCLUSION: Workplace injury could be a risk factor for both short and long-term prescription opioid use. Studies that use only workers' compensation medical claim data likely underestimate the magnitude of the impact of workplace injuries on opioid prescriptions.

OBJECTIVES: We explored the impact of workplace injury on receiving opioid prescriptions from employer-sponsored private group health insurances (GHI) and how long injured workers receive opioid prescriptions after injury. METHODS: We used the difference-in-differences method and MarketScan® databases for the years 2013 to 2015. RESULTS: Estimated odds for injured workers relative to non-injured workers to receive opioid prescriptions from the GHI within 60 and 180 days from the index date of injury were 4.9 and 1.5, respectively. In addition, the number of opioid prescriptions received within 60 days of injury was 2.5 times higher. CONCLUSION: Workplace injury could be a risk factor for both short and long-term prescription opioid use. Studies that use only workers' compensation medical claim data likely underestimate the magnitude of the impact of workplace injuries on opioid prescriptions.

INTRODUCTION: The cost of the Social Security Disability Insurance (DI) program has increased over time though recent reports showed that disability incidence and prevalence rates have started declining. We explored whether occupation was one of the risk factors for the rising number of disabled workers who received DI benefits during 1992-2016. METHODS: We used a cohort of 16 196 Health and Retirement Survey respondents between the age of 51 and 64 years who were followed from their date of entry until they received DI benefits, died, reached full retirement age, or reached the end of the follow-up period (2016). We used the extended stratified Cox proportional hazard model. Because one-third of the respondents in our cohort did not report their longest-held occupation, we used a multiple-imputation method. RESULTS: The hazard of receiving DI benefits was 51%, 78%, 81%, and 85% higher among workers with longest-held occupations in sales, mechanics and repair, protective services, and personal services, respectively than among workers with longest-held occupations in the reference managerial occupation. The hazard of receiving DI benefits was more than double among workers with longest-held occupations in the construction trade and extractors, transportation operation, machine operators, handlers, and food preparation than among workers with the longest-held occupation in the reference managerial occupation. CONCLUSION: Improving the overall working conditions in these occupations would help reduce worker suffering and the number of applicants for DI benefits, thereby reducing the burden of workplace injury and illness on the DI program.

Information on opioids obtained by workers is important for both health and safety. We examined the prevalence and total expenses of obtaining outpatient opioid prescriptions, along with associated sociodemographic, economic, and work characteristics, in national samples of U.S. workers. We used Medical Expenditure Panel Survey data (2007-2016) along with descriptive and multiple logistic regression. During the study period, an estimated 21 million workers (12.6%) aged 16 years or older obtained one or more outpatient opioid prescriptions, at an expense of $2.81 billion per year. Private health insurance covered half of the total opioid expenses for workers. The prevalence of obtaining opioid prescriptions was higher for women than for men, but men had higher opioid expenses. In addition, the prevalence of obtaining opioid prescriptions was higher for workers who were older; non-Hispanic white; divorced, separated, or widowed; and non-college-educated. There is an inverse relationship between family income and the likelihood of obtaining opioids. Compared to workers with private insurance, workers with public health insurance had higher expenses for opioid prescriptions. Finally, workers in occupations at higher risk for injury and illness - including construction and extraction; farming; service; and production, transportation, and material moving occupations - were more likely to obtain opioid prescriptions.