Extreme Heat and Occupational Health Risks.

Climate change poses a significant occupational health hazard. Rising temperatures and more frequent heat waves are expected to cause increasing heat-related morbidity and mortality for workers across the globe. Agricultural, construction, military, firefighting, mining, and manufacturing workers are at particularly high risk for heat-related illness (HRI). Various factors, including ambient temperatures, personal protective equipment, work arrangements, physical exertion, and work with heavy equipment may put workers at higher risk for HRI. While extreme heat will impact workers across the world, workers in low- and middle-income countries will be disproportionately affected. Tracking occupational HRI will be critical to informing prevention and mitigation strategies. Renewed investment in these strategies, including workplace heat prevention programs and regulatory standards for indoor and outdoor workers, will be needed. Additional research is needed to evaluate the effectiveness of interventions in order to successfully reduce the risk of HRI in the workplace.

Risk factors for COVID-19 among Californians working outside the home, November 2020 - May 2021.

BACKGROUND: Higher incidences of COVID-19 mortality and outbreaks have been found in certain industries and occupations. Workplace factors, including working in close proximity to others and contact with the public can facilitate SARS-CoV-2 transmission, especially without appropriate protective measures. Limited information is available about workers at highest risk for SARS-CoV-2 infection. METHODS: A phone-based, nonprobability study was conducted between November 2020 and May 2021 among California workers who were tested for SARS-CoV-2. Participants were asked about demographics and workplace factors, including industry, occupation, and implementation of COVID-19 mitigation measures. Using the SARS-CoV-2 occupational exposure matrix, three exposure metrics and a combination index were used to categorize occupations. We assessed the association between workplace risks and SARS-CoV-2 test positivity using adjusted logistic regression. RESULTS: We enrolled 451 (13%) of 3475 potentially eligible workers in the study: 212 with positive and 239 with negative SARS-CoV-2 test results. Those working very close to others and with the highest combined exposure index had a positive association with SARS-CoV-2 positivity. Primarily indoor workers had a lower odds of test positivity compared to those with any outdoor work. There was no association between public-facing occupations and test positivity. Participants with employers who implemented mitigation measures in all three control categories-engineering, administrative, and personal protective equipment-had lower odds of test positivity than those with fewer mitigation measures. CONCLUSIONS: Worker groups with higher risk factors should be prioritized for outreach. Assessment of occupational risk factors collectively can provide insight to inform preventative actions for workers, employers, and public health entities.

Evaluating the association between in-person work and the risk of SARS-CoV-2 infection through June 2021.

OBJECTIVES: Recent studies have evaluated COVID-19 outbreaks and excess mortality by occupation sectors. Studies on SARS-CoV-2 infection across occupation and occupation-related factors remain lacking. In this study, we estimate the effect of in-person work on SARS-CoV-2 infection risk and describe SARS-CoV-2 seroprevalence among working adults. METHODS: We used Wave 1 data (May to June 2021) from CalScope, a population-based seroprevalence study in California. Occupation data were coded using the National Institute for Occupational Safety and Health Industry and Occupation Computerized Coding System. Dried blood spot specimens were tested for antibodies to establish evidence of prior infection. We estimated the causal effect of in-person work on SARS-CoV-2 infection risk using the g-formula and describe SARS-CoV-2 seroprevalence across occupation-related factors. RESULTS: Among 4335 working adults, 53% worked in person. In-person work was associated with increased risk of prior SARS-CoV-2 infection (risk difference: 0.03; [95% CI: 0.02-0.04]) compared with working remotely. Workers that reported job loss or who were without medical insurance had higher evidence of prior infection. Amongst in-person workers, evidence of prior infection was highest within farming, fishing, and forestry (55%; [95% CI: 26%-81%]); installation, maintenance, and repair (23%; [12%-39%]); building and grounds cleaning and maintenance (23%; [13%-36%]); food preparation and serving related (22% [13%-35%]); and healthcare support (22%; [13%-34%]) occupations. Workers who identified as Latino, reported a household income of <$25K, or who were without a bachelor's degree also had higher evidence of prior infection. CONCLUSIONS: SARS-CoV-2 infection risk varies by occupation. Future vaccination strategies may consider prioritizing in-person workers.

Reported Exposures Among In-Person Workers With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in 6 States, September 2020-June 2021.

BACKGROUND: Surveillance systems lack detailed occupational exposure information from workers with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The National Institute for Occupational Safety and Health partnered with 6 states to collect information from adults diagnosed with SARS-CoV-2 infection who worked in person (outside the home) in non-healthcare settings during the 2 weeks prior to illness onset. METHODS: The survey captured demographic, medical, and occupational characteristics and work- and non-work-related risk factors for SARS-CoV-2 infection. Reported close contact with a person known or suspected to have SARS-CoV-2 infection was categorized by setting as exposure at work, exposure outside of work only, or no known exposure/did not know. Frequencies and percentages of exposure types are compared by respondent characteristics and risk factors. RESULTS: Of 1111 respondents, 19.4% reported exposure at work, 23.4% reported exposure outside of work only, and 57.2% reported no known exposure/did not know. Workers in protective service occupations (48.8%) and public administration industries (35.6%) reported exposure at work most often. More than one third (33.7%) of respondents who experienced close contact with ≥10 coworkers per day and 28.8% of respondents who experienced close contact with ≥10 customers/clients per day reported exposures at work. CONCLUSIONS: Exposure to occupational SARS-CoV-2 was common among respondents. Examining differences in exposures among different worker groups can help identify populations with the greatest need for prevention interventions. The benefits of recording employment characteristics as standard demographic information will remain relevant as new and reemerging public health issues occur.

COVID-19 Outbreaks and Mortality Among Public Transportation Workers - California, January 2020-May 2022.

Work-related factors can contribute to risk for exposure to and infection with SARS-CoV-2, the virus that causes COVID-19, and subsequent COVID-19-attributable outcomes, including death. Comparing COVID-19 metrics across industries can help identify workers at highest risk. Elevated COVID-19 mortality rates have been reported among all transportation workers, as well as specifically in public transportation industries (1-3). The California Department of Public Health (CDPH) calculated public transportation industry-specific COVID-19 outbreak incidence during January 2020-May 2022 and analyzed all laboratory-confirmed COVID-19 deaths among working-age adults in California to calculate public transportation industry-specific mortality rates during the same period. Overall, 340 confirmed COVID-19 outbreaks, 5,641 outbreak-associated cases, and 537 COVID-19-associated deaths were identified among California public transportation industries. Outbreak incidence was 5.2 times as high (129.1 outbreaks per 1,000 establishments) in the bus and urban transit industry and 3.6 times as high in the air transportation industry (87.7) as in all California industries combined (24.7). Mortality rates were 2.1 times as high (237.4 deaths per 100,000 workers) in transportation support services and 1.8 times as high (211.5) in the bus and urban transit industry as in all industries combined (114.4). Workers in public transportation industries are at higher risk for COVID-19 workplace outbreaks and mortality than the general worker population in California and should be prioritized for COVID-19 prevention strategies, including vaccination and enhanced workplace protection measures.

Close physical proximity on the job-An exposure matrix.

BACKGROUND: The workplace is a setting for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission via respiratory droplets and aerosols for those working in close proximity to others. Currently, limited methods exist for assessing SARS-CoV-2 exposure. Since occupation serves as a surrogate measure, job exposure matrices (JEMs) can be useful for population-based exposure assessment for a portion of exposure. METHODS: We developed a JEM to assess physical proximity at work. Scores for questions related to frequency of face-to-face discussions, working closely with others, and working with a team were extracted from a US-based, comprehensive source of descriptive occupational information (Occupational Information Network [O*NET]). We described score distributions using univariate analyses, devised thresholds, and assigned exposure levels for 968 O*NET occupations. Three exposure measures were constructed using combinations of O*NET data, with expert judgment, and accounting for telework. National and California employment estimates were used to assess the workforce proportions by proximity level and demographic characteristics. RESULTS: We categorized 535 US Census occupations (2010) into four-level ordinal exposure levels (not close to very close). Overall, an estimated 56% of the California workforce worked in very close proximity, which decreased to 46% when accounting for telework. The occupational groups working very close across all three measures were: healthcare support, healthcare practitioner, food preparation and serving, building and grounds cleaning and maintenance, and protective service occupations. Latinos and women were overrepresented within occupations working in very close physical proximity. CONCLUSION: JEMs can inform SARS-CoV-2 exposure assessment for epidemiologic studies, assist in resource allocation, and inform prevention strategies.

Childhood leukemia risk in the California Power Line Study: Magnetic fields versus distance from power lines.

Pooled analyses have suggested a small increased risk of childhood leukemia associated with distance and with exposure to high magnetic fields from power transmission lines. Because magnetic fields are correlated with distance from lines, the question of whether the risk is due to magnetic fields exposure or to some other factor associated with distance from lines is unresolved. We used data from a large records-based case-control study to examine several research questions formulated to disentangle the relationships among magnetic fields, distance from high voltage lines, and childhood leukemia risk. In models examining an interaction between distance and magnetic fields exposure, we found that neither close proximity to high voltage lines alone nor exposure to high calculated fields alone were associated with childhood leukemia risk. Rather, elevated risk was confined to the group that was both very close to high voltage lines (<50 m) and had high calculated fields (≥0.4 µT) (odds ratio 4.06, 95% CI 1.16, 14.3). Further, high calculated fields (≥0.4 µT) that were due solely to lower voltage lines (<200 kV) were not associated with elevated risk; rather, risk was confined to high fields attributable to high voltage lines. Whilst other explanations are possible, our findings argue against magnetic fields as a sole explanation for the association between distance and childhood leukemia and in favor of some other explanation linked to characteristics of power lines.

Residential magnetic fields exposure and childhood leukemia: a population-based case-control study in California.

PURPOSE: Studies have reported an increased risk of childhood leukemia associated with exposure to magnetic fields. We conducted a large records-based case-control study of childhood leukemia risk and exposure to magnetic fields from power lines in California. METHODS: The study included 5,788 childhood leukemia cases (born in and diagnosed in California 1986-2008) matched to population-based controls on age and sex. We calculated magnetic fields at birth addresses using geographic information systems, aerial imagery, historical information on load and phasing, and site visits. RESULTS: Based on unconditional logistic regression controlling for age, sex, race/ethnicity, and socioeconomic status using subjects geocoded to a basic standard of accuracy, we report a slight risk deficit in two intermediate exposure groups and a small excess risk in the highest exposure group (odds ratio of 1.50 (95% confidence interval [0.70, 3.23])). Subgroup and sensitivity analyses as well as matched analyses gave similar results. All estimates had wide confidence intervals. CONCLUSION: Our large, statewide, record-based case-control study of childhood leukemia in California does not in itself provide clear evidence of risk associated with greater exposure to magnetic fields from power lines, but could be viewed as consistent with previous findings of increased risk.

Childhood leukaemia and distance from power lines in California: a population-based case-control study.

BACKGROUND: Studies have reported an increased risk of childhood leukaemia associated with living near high-voltage electric power transmission lines that extend to distances at which magnetic fields from lines are negligible. We conducted a large records-based case-control study of childhood leukaemia risk in the population living near power lines in California. METHODS: The study included 5788 childhood leukaemia and 3308 central nervous system (CNS) cancer cases (for comparison) born in and diagnosed in California (1986-2008), and matched to population-based controls by age and sex. We geocoded birth address and estimated the distance from residence to transmission lines using geographic information systems, aerial imagery, and, for some residences, site visits. RESULTS: For leukaemia, there was a slight excess of cases within 50 m of a transmission line over 200 kV (odds ratio 1.4, 95% confidence interval 0.7-2.7). There was no evidence of increased risk for distances beyond 50 m, for lower-voltage lines, or for CNS cancers. CONCLUSIONS: Our findings did not clearly support an increased childhood leukaemia risk associated with close proximity (<50 m) to higher voltage lines, but could be consistent with a small increased risk. Reports of increased risk for distances beyond 50 m were not replicated.

An analysis of fatal and non-fatal injuries and injury severity factors among electric power industry workers.

BACKGROUND: The electric power industry represents a unique subset of the U.S. workforce. We aimed to evaluate the relationships between occupational category, nature of injury, and injury severity among electric power industry workers. METHODS: The Occupational Health and Safety Database (1995-2013) was used to calculate injury rates, assess patterns of injury severity, and identify at-risk occupations in this population. RESULTS: Over the surveillance period, a total of 63,193 injuries were reported. Overall, and severe injury rates were 3.20 and 0.52 per 100 employee-years, respectively. The fatal injury rate was 3.29 per 100,000 employee-years. Line workers experienced the highest risk for fatal injuries and second highest for non-fatal severe injuries, following meter readers. The most severe non-fatal injuries were hernia and rupture; multiple injuries; and CTD/RSI. Fatal injuries were most commonly associated with vehicle collisions and contact with electric current. CONCLUSIONS: Industry specific surveillance and interventions tailored to high-risk occupations are needed to further reduce severe injuries in this population. Am. J. Ind. Med. 59:948-958, 2016. © 2016 Wiley Periodicals, Inc.

Occupational Exposure to Electric Shocks and Magnetic Fields and Amyotrophic Lateral Sclerosis in Sweden.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) has been consistently related to "electric occupations," but associations with magnetic field levels were generally weaker than those with electrical occupations. Exposure to electric shock has been suggested as a possible explanation. Furthermore, studies were generally based on mortality or prevalence of ALS, and studies often had limited statistical power. METHODS: Using two electric shock and three magnetic field job-exposure matrices, we evaluated the relationship of occupational magnetic fields, electric shocks, electric occupations, and incident ALS in a large population-based nested case-control study in Sweden. Subanalyses, specified a priori, were performed for subjects by gender and by age (less than and more than 65 years). RESULTS: Overall, we did not observe any associations between occupational magnetic field or electric shock exposure and ALS. For individuals less than 65 years old, high electric shock exposure was associated with an odds ratio (OR) of 1.22 (95% confidence interval [CI] = 1.03, 1.43). The corresponding result for the age group 65 years or older was OR = 0.92 (95% CI = 0.81, 1.05). Results were similar regardless which job exposure matrices, exposure definitions, or cutpoints were used. For electric occupations, ORs were close to unity, regardless of age. For welders, no association was observed overall, although for welders <65 years the OR was 1.52 (95% CI = 1.05, 2.21). CONCLUSIONS: In this very large population-based study based on incident ALS case subjects, we did not confirm previous observations of higher risk of ALS in electrical occupations, and provided only weak support for associations between electric shocks and ALS.

Estimating magnetic fields of homes near transmission lines in the California Power Line Study.

The California Power Line Study is a case-control study investigating the relation between residences near transmission lines and risk of childhood leukemia. It includes 5788 childhood leukemia cases and 5788 matched primary controls born between 1986 and 2007. We describe the methodology for estimating magnetic fields at study residences as well as for characterizing sources of uncertainty in these estimates. Birth residences of study subjects were geocoded and their distances to transmission lines were ascertained. 302 residences were deemed sufficiently close to transmission lines to have non-zero magnetic fields attributable to the lines. These residences were visited and detailed data, describing the physical configuration and dimensions of the lines contributing to the magnetic field at the residence, were collected. Phasing, loading, and directional load flow data for years of birth and diagnosis for each subject as well as for the day of site visit were obtained from utilities when available; when yearly average load for a particular year was not available, extrapolated values based on expert knowledge and prediction models were obtained. These data were used to estimate the magnetic fields at the center, closest and farthest point of each residence. We found good correlation between calculated fields and spot measurements of fields taken on site during visits. Our modeling strategies yielded similar calculated field estimates, and they were in high agreement with utility extrapolations. Phasing was known for over 90% of the lines. Important sources of uncertainty included a lack of information on the precise location of residences located within apartment buildings or other complexes. Our findings suggest that we were able to achieve high specificity in exposure assessment, which is essential for examining the association between distance to or magnetic fields from power lines and childhood leukemia risk.

Exposure and illness among workers filing for COVID-19 related workers' compensation -- California, 2020.

OBJECTIVES: To characterize the incidence of SARS-CoV-2 exposure and COVID-19 infection among California workers' compensation claims in 2020 and examine risk factors for exposure. METHODS: Using a case-control approach, we combined machine learning techniques and job exposure matrices to assess associations between exposures and illness claims and clusters of claims within specific worksites over a 3-week period. RESULTS: Of the 117,125 COVID-19 claims, most were primarily among younger groups, of shorter tenure, and from healthcare occupations. Illness claims were among older groups with longer tenure. Jobs with very close physical proximity and high physical activity, along with transportation and warehousing industries, were associated with being part of a cluster of claims. CONCLUSIONS: The findings merit further study but indicate respiratory viral transmission and support efforts to systematically incorporate work-related variables into other California data sources.

Unmet Mental Health Needs Among California Workers Since the Start of the COVID-19 Pandemic.

OBJECTIVE: We sought to identify worker groups with high prevalence of unmet mental health needs to inform employer benefits programs and outreach to increase access to care. METHODS: We conducted a repeated cross-sectional study to understand unmet mental health needs among workers since the start of the COVID-19 pandemic using California Health Interview Survey data from 2013-2021. RESULTS: In 2021, 23.4% (CI: 22.4-24.4) reported unmet mental health needs, an absolute increase of 3.9% from 2019. Relative increases were highest among workers in the information industries (prevalence ratio [PR]: 1.89, CI: 1.4-2.5) and older workers (PR: 1.27, CI: 0.9-1.8). Increases in needing help were not met with comparable increases in seeking care. CONCLUSIONS: Unmet mental health needs increased for California workers during the pandemic. Employers should dedicate resources and implement strategies to increase access to care and promote worker well-being.

Increases in Prevalent Depressed Mood and Suicidal Ideation among Workers during the COVID-19 Pandemic-Findings from the California Health Interview Survey.

Limited data exist on COVID-19's mental health impact on non-healthcare workers. We estimated the prevalence of depressed mood and suicidal ideation experienced in the past year among California workers and assessed whether the prevalence changed during the COVID-19 pandemic. We analyzed 2013-2020 California Health Interview Survey data using survey-weighted methods to assess the change in the prevalence of depressed mood and suicidal ideation from 2019 to 2020 for working adults by demographics and occupational groups. We used trend-adjusted quasi-Poisson regressions and report rate ratios (RR), comparing the prevalence of outcomes during 2020 to the pre-pandemic period (2013-2019). We identified priority occupation groups with a higher-than-average outcome prevalence in 2020 and rate increases after adjusting for pre-pandemic trends. Our analysis included 168,768 respondents, of which 65% were workers. Production and service workers were the priority occupation groups for depressed mood (RR: 1.46, CI: 1.1-1.9; RR: 1.23, CI: 1.1-1.4) and suicidal ideation (RR: 1.86, CI: 1.0-3.6; RR: 1.47, CI: 1.1-1.9). Workers aged 45-65 years experienced over a 30% relative increase in both outcomes from 2019 to 2020. Depressed mood and suicidal ideation in the past year increased for production, service, and older workers during the pandemic. These groups should be considered for mental health interventions.

Occupational COVID-19 Exposures and Illnesses among Workers in California-Analysis of a New Occupational COVID-19 Surveillance System.

Little is known about occupational SARS-CoV-2 exposures and COVID-19 outcomes. We established a Doctor's First Reports of Occupational Injury or Illness (DFR)-based surveillance system to study cases of work-related COVID-19 exposures and disease. The surveillance data included demographics, occupation, industry, exposure, and illness, details including hospitalization and lost work. We classified workers into 'healthcare', non-healthcare 'public-facing', or 'other' worker groups, and rural-urban commuting areas (RUCAs). We describe worker exposures and outcomes overall by worker group and RUCA. We analyzed 2848 COVID-19 DFRs representing workers in 22 detailed occupation groups and 19 industry groups. Most DFRs were for workers in metropolitan RUCAs (89%) and those in healthcare (42%) and public-facing (24%) worker groups. While DFRs were from 382 unique worksites, 52% were from four hospitals and one prison. Among 1063 DFRs with a suspected exposure, 73% suspected exposure to a patient or client. Few DFRs indicated hospitalization (3.9%); however, the proportion hospitalized was higher among nonmetropolitan (7.4%) and public-facing (6.7%) workers. While 56% of DFRs indicated some lost work time, the proportion was highest among public-facing (80%) workers. Healthcare and prison workers were the majority of reported occupational COVID-19 exposures and illnesses. The risk of COVID-19 hospitalization and lost work may be highest among nonmetropolitan and public-facing workers.

New electric-shock job exposure matrix.

BACKGROUND: To evaluate a consistent association between jobs in "electric" occupations and amyotrophic lateral sclerosis (ALS), a comprehensive job exposure matrix (JEM) that includes electric shocks and magnetic fields (MF) is needed. METHODS: We used incident electric shocks and electrocutions from two available data sources along with expert judgment to create a JEM that was integrated into an existing MF JEM. The final JEM contained ordinal electric-shock exposure assignments for 501 job titles. RESULTS: Main occupational groups experiencing the electric shocks were precision production, craft, and repair occupations. Specific jobs with the highest proportion of shocks per 100,000 workers were: electrical apprentices (99.7), mechanic and repairer helpers (74.0), hoist and winch operators (63.3), and electrical power installers (52.4). Examples of job titles with low electric-shock exposures were administrative support occupations, data-key entry operators, and waiters and waitresses. CONCLUSIONS: Combining publicly available data with an expert panel is a viable method to construct an electric-shock MF JEM. This JEM will allow an evaluation of association between electric shocks and neurodegenerative diseases.

Developing a job-exposure matrix with exposure uncertainty from expert elicitation and data modeling.

Job exposure matrices (JEMs) are tools used to classify exposures for job titles based on general job tasks in the absence of individual level data. However, exposure uncertainty due to variations in worker practices, job conditions, and the quality of data has never been quantified systematically in a JEM. We describe a methodology for creating a JEM which defines occupational exposures on a continuous scale and utilizes elicitation methods to quantify exposure uncertainty by assigning exposures probability distributions with parameters determined through expert involvement. Experts use their knowledge to develop mathematical models using related exposure surrogate data in the absence of available occupational level data and to adjust model output against other similar occupations. Formal expert elicitation methods provided a consistent, efficient process to incorporate expert judgment into a large, consensus-based JEM. A population-based electric shock JEM was created using these methods, allowing for transparent estimates of exposure.

Job exposure matrix for electric shock risks with their uncertainties.

We present an update to an electric shock job exposure matrix (JEM) that assigned ordinal electric shocks exposure for 501 occupational titles based on electric shocks and electrocutions from two available data sources and expert judgment. Using formal expert elicitation and starting with data on electric injury, we arrive at a consensus-based JEM. In our new JEM, we quantify exposures by adding three new dimensions: (1) the elicited median proportion; (2) the elicited 25th percentile; and (3) and the elicited 75th percentile of those experiencing occupational electric shocks in a working lifetime. We construct the relative interquartile range (rIQR) based on uncertainty interval and the median. Finally, we describe overall results, highlight examples demonstrating the impact of cut point selection on exposure assignment, and evaluate potential impacts of such selection on epidemiologic studies of the electric work environment. In conclusion, novel methods allowed for consistent exposure estimates that move from qualitative to quantitative measures in this population-based JEM. Overlapping ranges of median exposure in various categories reflect our limited knowledge about this exposure.