Bhattacharya A, Syamlal G, Dodd KE. Medical costs and incremental medical costs of asthma among workers in the United States. Am J Ind Med. 2024;67:834-843. doi:10.1002/ajim.23633
In the affiliation of the first author, “Respiratory Health Division” has been corrected to “Office of the Director.”
Anasua Bhattacharya1
Office of the Director, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, Ohio, USA.
We apologize for this error.
Previous studies have shown that job strain is associated with low birthweight (LBW), preterm birth (PTB), and small for gestational age (SGA). We conducted a scoping review and meta-analysis to assess the association between job strain and adverse pregnancy outcomes.
A literature search was performed on PubMed. We included English-language studies that examined the association between job strain (based on the Karasek demand-control model) and pregnancy outcomes. We excluded letters, posters, reviews, and qualitative studies. Random effects meta-analysis was performed. Heterogeneity was assessed using τ2 and I2 statistics. Potential bias was assessed using standard funnel plots. Asymmetry was evaluated by Egger's test. Leave-one-out analysis was performed for sensitivity analyses.
Three eligible studies were found for LBW, seven for PTB, and four for SGA. The number of subjects ranged from 135 to 4889, and the prevalence of high job strain ranged from 6.64% to 33.9%. The pooled odds ratio and 95% confidence interval (CI) for LBW, PTB, and SGA were 1.23 (95% CI: 0.97, 1.56), 1.10 (95% CI: 1.00, 1.22), and 1.16 (95% CI: 0.97, 1.39) respectively, indicating modest associations. Heterogeneity for LBW and PTB may not be important but may be moderate for SGA. No publication bias was detected for LBW and PTB, but possible publication bias exists for SGA.
We found a modest association between job strain and PTB. Since job strain is only one of the many aspects of an unhealthy work environment, interventions that improve working conditions more broadly are needed.
Information on worker occupation and industry is critical to understanding the occupational risks of heat-related illness (HRI), yet few syndromic surveillance systems capture these key data elements. This study evaluates the work data reported through Washington syndromic surveillance for its utility in characterizing HRI ED visits by industry and occupation.
Standard industry and occupation codes were assigned to employer name and occupation descriptions reported in Washington ED visit records maintained within the state's syndromic surveillance system, for visits involving HRI in 2020–2022. HRI ED visits involving workplace heat exposure were identified based on discharge diagnoses or on keywords in the triage note or chief complaint fields. HRI ED visits were summarized by patient characteristics, and visit rates were calculated by industry and occupation.
Employer name or occupation descriptions were reported in 21.5% of HRI ED records among patients age 16 and older, and in 41.2% of records with mention of heat exposure at work. Twice as many records were classified for industry as for occupation. Agriculture, forestry, fishing, and hunting and transportation and warehousing had the highest rates of HRI ED visits. Specific industries with the highest rates included support activities for agriculture and forestry, the postal service, and fruit and vegetable preserving and specialty food manufacturing.
Syndromic surveillance data are a valuable source of occupational health surveillance information when work characteristics are reported, enhancing our understanding of the occupational risks of injuries and illnesses.
Artificial intelligence (AI)—the field of computer science that designs machines to perform tasks that typically require human intelligence—has seen rapid advances in the development of foundation systems such as large language models. In the workplace, the adoption of AI technologies can result in a broad range of hazards and risks to workers, as illustrated by the recent growth in industrial robotics and algorithmic management. Sources of risk from deployment of AI technologies across society and in the workplace have led to numerous government and private sector guidelines that propose principles governing the design and use of trustworthy and ethical AI. As AI capabilities become integrated in devices, machines, and systems across industry sectors, employers, workers, and occupational safety and health practitioners will be challenged to manage AI risks to worker health, safety, and well-being. Five risk management options are presented as ways to assure that only trustworthy and ethical AI enables workplace devices, machinery, and processes. AI technologies will play a significant role in the future of work. The occupational safety and health practice and research communities need to ensure that the promise of these new AI technologies results in benefit, not harm, to workers.
The workplace is an important setting for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure and transmission. Using data from a large case–control study in Colorado during 2021 and 2022, we aimed to evaluate working outside the home and SARS-CoV-2 infection, the racial and ethnic distribution of workers in occupations associated with infection, and workplace face mask use.
Cases were Colorado adults with a positive SARS-CoV-2 test by reverse transcription-polymerase chain reaction (RT-PCR) reported to Colorado's COVID-19 surveillance system selected from surveillance data ≤12 days after their specimen collection date. Control participants were randomly selected adult Coloradans with a RT-PCR-confirmed negative SARS-CoV-2 test result reported to the same surveillance system.
Working outside the home was associated with infection (odds ratio [OR] = 1.46, 95% confidence interval [CI]: 1.39–1.54). Among participants working outside the home, “Food Preparation and Serving Related” (aOR = 2.35, 95% CI: 1.80–3.06), “Transportation and Material Moving” (aOR = 2.09, 95% CI: 1.62–2.69), “Construction and Extraction” (aOR = 1.88, 95% CI: 1.36–2.59), “Protective Service” (aOR = 1.60, 95% CI: 1.15–2.24), and “Sales and Related” (aOR = 1.44, 95% CI: 1.22–1.69) were occupational categories most strongly associated with infection. American Indian/Alaskan Native, Black, and Hispanic/Latino participants were more likely than others to work in occupational categories with the highest odds of infection (p < 0.05). Cases were less likely than controls to report always wearing a mask (31.9% vs. 41.5%) and wearing a KN95/N95/KF94 mask (16.8% vs. 27.2%) at work.
These findings emphasize the importance of occupation and workplace mask use in the COVID-19 pandemic and its disproportionate racial/ethnic impact on workers.
Manual deconstruction—an alternative to mechanical demolition—is a crucial technique in the building industry that facilitates a circular economy for the built environment and achieves sustainable development goals (SDGs). However, the current body of literature lacks a thorough grasp of the OHS (occupational health and safety) hazards related to the deconstruction process. The current work closes this scholarly gap by outlining the deconstruction process as phases and sets of activities and highlighting potential health and safety hazards throughout different activities and phases.
The study uses numerous case studies and applies a descriptive case study technique to gather and analyze primary data from hundreds of photos and notes from over 40 field visits. The primary data are first used to prepare a comprehensive process map of deconstruction. Six construction safety experts and four industrial hygiene experts were then interviewed to identify and characterize health and safety hazards in images representative of the deconstruction activities.
A taxonomy of OHS hazards for deconstruction was developed based on identifying 35 unique safety and 51 unique health hazards. Significant safety hazards in deconstruction activities include “struck-by,” “trip, slip, and fall” hazards, and “lack of personal protective equipment.” Major health hazards include ergonomic concerns, respiratory diseases, and eye strain.
The study highlights the occupational health and safety issues faced by the deconstruction trade with a granularity rarely covered in existing literature. The assessments can be helpful for OHS practitioners to identify potential health and safety improvements across various deconstruction phases.
Epidemiological studies of occupational risk factors for rare disorders require large study populations with adequate exposure estimates. Job exposure matrices (JEMs) linked to national information on standardized job titles may enable such large studies. We aimed to establish and validate a JEM for occupational hand-wrist exposures that could be linked to Danish national register data on job titles and hand-wrist disorders.
We developed a JEM for hand-wrist repetition, force, vibration, and computer work in 96 job groups covering 91% of the 2227 occupational titles in the Danish version of the International Standard Classification of Occupation-88, and examined inter-rater reliability of five expert ratings. Poisson regression models were used to estimate incidence rate ratios for the association of carpal tunnel syndrome (CTS) with the level of repetitive movements, force, vibration, and hours of computer work described by the JEM, adjusted for relevant confounders.
The JEM based on expert ratings had fair to good interrater reliability. The incidence of CTS increased with increasing levels of force, hand-wrist repetition, and vibration, Exposure-response patterns for repetition and vibration became less consistent after adjustment for force. The interaction between repetition and force was complex and did not support an overall positive interaction. Computer work was negatively associated with incident CTS.
The JEM was able to identify known risk factors for CTS consistent with current evidence, and provided further associations on exposure-response patterns, mutual exposure adjustment, and interaction effects between repetition and force. The reliability of expert assessments of hand-wrist physical exposures was fair to good.
A retrospective cohort study was conducted to estimate associations between an ultrafine aluminum powder, McIntyre Powder (MP), and cardiovascular disease incidence in a cohort of mine workers from Ontario, Canada. Disease outcomes included ischemic heart disease (IHD), acute myocardial infarction (AMI), congestive heart failure (CHF), and strokes and transient ischemic attacks (STIA).
Using work history records from the Ontario Mining Master File (MMF) mine workers were followed for disease incidence in administrative health records. The analysis included 25,813 mine workers who were exposed to MP between 1943 and 1979 and followed for cardiovascular disease (CVD) diagnoses between 2006 and 2018. Cardiovascular disease cases were ascertained using physician, hospital, and ambulatory care records. Poisson regression models were used to estimate age and birth-year adjusted incidence rate ratios (RR) and 95% confidence intervals (CI) for associations between MP exposure and CVD outcomes.
Ever-exposure to MP was positively associated with modest increases in the incidence rate of IHD, AMI, and CHF, but not STIA, using both assessment approaches. Duration of self-reported MP exposure was positively associated with monotonically increasing rates of IHD and AMI compared to never-exposed miners, with the greatest association observed among miners with >20 years of exposure (for IHD: RR 1.24, 95% CI: 0.91–1.68; and for AMI: RR 1.52, 95% CI 1.01–2.28).
Mine workers ever-exposed to MP had modestly elevated rates of CVD. The rate of CVD diagnoses appeared to increase with longer duration of exposure when assessed by both self-reported exposure and through historical records.
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