Claudia Corwin MD, MPH, Hillary Waterhouse MPH, CIH, CPH, Jerrold L. Abraham MD, Soma Sanyal MD, Judith A. Crawford PhD, CIH, Matthew Caddell DO, MPH, Michael J. Hodgson MD, MPH
Exposure to aluminum compounds is clearly associated with pulmonary function decrements, and several animal models document possible mechanisms of aluminum- compound-induced pulmonary toxicity. Nevertheless, disagreements remain about the precise mechanism by which exposures lead to damage. We present a strong case for attributing a case of interstitial pulmonary disease to occupational exposure to aluminum trihydrate. This report follows a 2014 publication of another case of interstitial pulmonary disease following a similar exposure. Our patient eventually underwent double lung transplantation nearly 5 years postexposure. Detailed pulmonary particulate elemental analysis suggested that aluminum metal, including aluminum trihydrate, was the most likely cause. A detailed assessment of the worker's relevant occupational exposures accompanies this case report.
{"title":"Interstitial pulmonary disease and aluminum trihydrate exposure: A single case report and detailed workplace analysis","authors":"Claudia Corwin MD, MPH, Hillary Waterhouse MPH, CIH, CPH, Jerrold L. Abraham MD, Soma Sanyal MD, Judith A. Crawford PhD, CIH, Matthew Caddell DO, MPH, Michael J. Hodgson MD, MPH","doi":"10.1002/ajim.23564","DOIUrl":"10.1002/ajim.23564","url":null,"abstract":"<p>Exposure to aluminum compounds is clearly associated with pulmonary function decrements, and several animal models document possible mechanisms of aluminum- compound-induced pulmonary toxicity. Nevertheless, disagreements remain about the precise mechanism by which exposures lead to damage. We present a strong case for attributing a case of interstitial pulmonary disease to occupational exposure to aluminum trihydrate. This report follows a 2014 publication of another case of interstitial pulmonary disease following a similar exposure. Our patient eventually underwent double lung transplantation nearly 5 years postexposure. Detailed pulmonary particulate elemental analysis suggested that aluminum metal, including aluminum trihydrate, was the most likely cause. A detailed assessment of the worker's relevant occupational exposures accompanies this case report.</p>","PeriodicalId":7873,"journal":{"name":"American journal of industrial medicine","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajim.23564","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139519263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chelsea L. Martin, Morgan Richey, David B. Richardson, Maryalice Nocera, John Cantrell, Elizabeth S. McClure, Amelia T. Martin, Stephen W. Marshall, Shabbar I. Ranapurwala
Background
Suicide is a serious public health problem in the United States, but limited evidence is available investigating fatal suicides at work. There is a substantial need to characterize workplace suicides to inform suicide prevention interventions and target high-risk settings. This study aims to examine workplace suicide rates in North Carolina (NC) by worker characteristics, means of suicide used, and industry between 1992 and 2017.
Methods
Fatal workplace suicides were identified from records of the NC Office of the Chief Medical Examiner system and the NC death certificate. Sex, age, race, ethnicity, class of worker, manner of death, and industry were abstracted. Crude and age-standardized homicide rates were calculated as the number of suicides that occurred at work divided by an estimate of worker-years (w-y). Rate ratios and 95% confidence intervals (CIs) were calculated, and trends over calendar time for fatal workplace suicides were examined overall and by industry.
Results
81 suicides over 109,464,430 w-y were observed. Increased rates were observed in workers who were male, self-employed, and 65+ years old. Firearms were the most common means of death (63%) followed by hanging (16%). Gas service station workers experienced the highest fatal occupational suicide rate, 11.5 times (95% CI: 3.62–36.33) the overall fatal workplace suicide rate, followed by Justice, Public Order, and Safety workers at 3.23 times the overall rate (95% CI: 1.31–7.97).
Conclusion
Our findings identify industries and worker demographics that were vulnerable to workplace suicides. Targeted and tailored mitigation strategies for vulnerable industries and workers are recommended.
{"title":"25-Year fatal workplace suicide trends in North Carolina: 1992–2017","authors":"Chelsea L. Martin, Morgan Richey, David B. Richardson, Maryalice Nocera, John Cantrell, Elizabeth S. McClure, Amelia T. Martin, Stephen W. Marshall, Shabbar I. Ranapurwala","doi":"10.1002/ajim.23563","DOIUrl":"10.1002/ajim.23563","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Suicide is a serious public health problem in the United States, but limited evidence is available investigating fatal suicides at work. There is a substantial need to characterize workplace suicides to inform suicide prevention interventions and target high-risk settings. This study aims to examine workplace suicide rates in North Carolina (NC) by worker characteristics, means of suicide used, and industry between 1992 and 2017.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Fatal workplace suicides were identified from records of the NC Office of the Chief Medical Examiner system and the NC death certificate. Sex, age, race, ethnicity, class of worker, manner of death, and industry were abstracted. Crude and age-standardized homicide rates were calculated as the number of suicides that occurred at work divided by an estimate of worker-years (w-y). Rate ratios and 95% confidence intervals (CIs) were calculated, and trends over calendar time for fatal workplace suicides were examined overall and by industry.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>81 suicides over 109,464,430 w-y were observed. Increased rates were observed in workers who were male, self-employed, and 65+ years old. Firearms were the most common means of death (63%) followed by hanging (16%). Gas service station workers experienced the highest fatal occupational suicide rate, 11.5 times (95% CI: 3.62–36.33) the overall fatal workplace suicide rate, followed by Justice, Public Order, and Safety workers at 3.23 times the overall rate (95% CI: 1.31–7.97).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Our findings identify industries and worker demographics that were vulnerable to workplace suicides. Targeted and tailored mitigation strategies for vulnerable industries and workers are recommended.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7873,"journal":{"name":"American journal of industrial medicine","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139401519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mengting Xu PhD, Vikki Ho PhD, Jérôme Lavoué PhD, Ann Olsson PhD, Joachim Schüz PhD, Lesley Richardson MSc, Marie-Elise Parent PhD, John R. McLaughlin PhD, Paul A. Demers PhD, Pascal Guénel PhD, Loredana Radoi PhD, Heinz-Erich Wichmann PhD, Wolfgang Ahrens PhD, Karl-Heinz Jöckel PhD, Dario Consonni PhD, Maria T. Landi PhD, Lorenzo Richiardi PhD, Lorenzo Simonato PhD, Andrea 't' Mannetje PhD, Beata Świątkowska PhD, John K. Field PhD, Neil Pearce PhD, Jack Siemiatycki PhD
Background
Worldwide, lung cancer is the second leading cause of cancer death in women. The present study explored associations between occupational exposures that are prevalent among women, and lung cancer.
Methods
Data from 10 case–control studies of lung cancer from Europe, Canada, and New Zealand conducted between 1988 and 2008 were combined. Lifetime occupational history and information on nonoccupational factors including smoking were available for 3040 incident lung cancer cases and 4187 controls. We linked each reported job to the Canadian Job-Exposure Matrix (CANJEM), which provided estimates of probability, intensity, and frequency of exposure to each selected agent in each job. For this analysis, we selected 15 agents (cleaning agents, biocides, cotton dust, synthetic fibers, formaldehyde, cooking fumes, organic solvents, cellulose, polycyclic aromatic hydrocarbons from petroleum, ammonia, metallic dust, alkanes C18+, iron compounds, isopropanol, and calcium carbonate) that had lifetime exposure prevalence of at least 5% in the combined study population. For each agent, we estimated lung cancer risk in each study center for ever-exposure, by duration of exposure, and by cumulative exposure, using separate logistic regression models adjusted for smoking and other covariates. We then estimated the meta-odds ratios using random-effects meta-analysis.
Results and Conclusions
None of the agents assessed showed consistent and compelling associations with lung cancer among women. The following agents showed elevated odds ratio in some analyses: metallic dust, iron compounds, isopropanol, and organic solvents. Future research into occupational lung cancer risk factors among women should prioritize these agents.
{"title":"Prevalent occupational exposures and risk of lung cancer among women: Results from the application of the Canadian Job-Exposure Matrix (CANJEM) to a combined set of ten case–control studies","authors":"Mengting Xu PhD, Vikki Ho PhD, Jérôme Lavoué PhD, Ann Olsson PhD, Joachim Schüz PhD, Lesley Richardson MSc, Marie-Elise Parent PhD, John R. McLaughlin PhD, Paul A. Demers PhD, Pascal Guénel PhD, Loredana Radoi PhD, Heinz-Erich Wichmann PhD, Wolfgang Ahrens PhD, Karl-Heinz Jöckel PhD, Dario Consonni PhD, Maria T. Landi PhD, Lorenzo Richiardi PhD, Lorenzo Simonato PhD, Andrea 't' Mannetje PhD, Beata Świątkowska PhD, John K. Field PhD, Neil Pearce PhD, Jack Siemiatycki PhD","doi":"10.1002/ajim.23562","DOIUrl":"10.1002/ajim.23562","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Worldwide, lung cancer is the second leading cause of cancer death in women. The present study explored associations between occupational exposures that are prevalent among women, and lung cancer.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Data from 10 case–control studies of lung cancer from Europe, Canada, and New Zealand conducted between 1988 and 2008 were combined. Lifetime occupational history and information on nonoccupational factors including smoking were available for 3040 incident lung cancer cases and 4187 controls. We linked each reported job to the Canadian Job-Exposure Matrix (CANJEM), which provided estimates of probability, intensity, and frequency of exposure to each selected agent in each job. For this analysis, we selected 15 agents (cleaning agents, biocides, cotton dust, synthetic fibers, formaldehyde, cooking fumes, organic solvents, cellulose, polycyclic aromatic hydrocarbons from petroleum, ammonia, metallic dust, alkanes C18+, iron compounds, isopropanol, and calcium carbonate) that had lifetime exposure prevalence of at least 5% in the combined study population. For each agent, we estimated lung cancer risk in each study center for ever-exposure, by duration of exposure, and by cumulative exposure, using separate logistic regression models adjusted for smoking and other covariates. We then estimated the meta-odds ratios using random-effects meta-analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>None of the agents assessed showed consistent and compelling associations with lung cancer among women. The following agents showed elevated odds ratio in some analyses: metallic dust, iron compounds, isopropanol, and organic solvents. Future research into occupational lung cancer risk factors among women should prioritize these agents.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7873,"journal":{"name":"American journal of industrial medicine","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajim.23562","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139401520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mary Jo Reilly MS, Ling Wang PhD, Kenneth D. Rosenman MD, FACE, FACOEM, FACPM
Introduction
In 2014, the Federal Occupational Safety and Health Administration (OSHA) enacted a standard requiring employers to report work-related amputations to OSHA within 24 hours. We studied the characteristics of the injured workers and employer compliance with the regulation in Michigan.
Methods
Two independent data sets were used to compare work-related amputations from 2016 to 2018: employer reports to OSHA and the Michigan Multi-Source Injury and Illness Surveillance System (MMSIISS). We deterministically linked employer reports to OSHA with the MMSIISS by employee name, employer name, date, and type of amputation.
Results
We identified 1366 work-related amputations from 2016 to 2018; 575 were reported by employers to OSHA and 1153 were reported by hospitals to the MMSIISS. An overlap of 362 workers were reported in both systems, while 213 workers were only reported by employers to OSHA and 791 workers were only reported by hospitals. Employer compliance with the regulation was 42.1%. Employer compliance with reporting was significantly less in: agriculture, forestry, fishing, and hunting (14.6%); construction (27.4%); retail trade (20.7%); arts, entertainment, and recreation (7.7%); accommodation and food services (13.0%); and other services (27.0%). Large employers and unionized employers were significantly more likely (67.9% and 92.7%, respectively) and small employers were significantly less likely (18.2%) to comply with the reporting rule. Enforcement inspections at 327 workplaces resulted in 403 violations; of those, 179 (54.7%) employers had not corrected the amputation hazard before the time of inspection.
Discussion
Michigan employers reported less than half of the work-related amputations required by OSHA's reporting regulation. Noncompliance was greatest in small employers, and agriculture, forestry, fishing, and hunting; construction; arts, entertainment, and recreation; accommodation and food services; and retail and other service industries. Inspections found that over half of the employers had not corrected the hazard that caused the amputation at the time of the inspection's initial opening date; in these cases, abatement of any hazards identified would have occurred after the inspection. Improved compliance in employer reporting of work-related amputations will identify hazards posing a high risk of recurrence of injury to other workers from the same injury source. Greater complia
{"title":"Evaluation of the characteristics of injured workers and employer compliance with OSHA's reporting requirement for work-related amputations","authors":"Mary Jo Reilly MS, Ling Wang PhD, Kenneth D. Rosenman MD, FACE, FACOEM, FACPM","doi":"10.1002/ajim.23560","DOIUrl":"10.1002/ajim.23560","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>In 2014, the Federal Occupational Safety and Health Administration (OSHA) enacted a standard requiring employers to report work-related amputations to OSHA within 24 hours. We studied the characteristics of the injured workers and employer compliance with the regulation in Michigan.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Two independent data sets were used to compare work-related amputations from 2016 to 2018: employer reports to OSHA and the Michigan Multi-Source Injury and Illness Surveillance System (MMSIISS). We deterministically linked employer reports to OSHA with the MMSIISS by employee name, employer name, date, and type of amputation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified 1366 work-related amputations from 2016 to 2018; 575 were reported by employers to OSHA and 1153 were reported by hospitals to the MMSIISS. An overlap of 362 workers were reported in both systems, while 213 workers were only reported by employers to OSHA and 791 workers were only reported by hospitals. Employer compliance with the regulation was 42.1%. Employer compliance with reporting was significantly less in: agriculture, forestry, fishing, and hunting (14.6%); construction (27.4%); retail trade (20.7%); arts, entertainment, and recreation (7.7%); accommodation and food services (13.0%); and other services (27.0%). Large employers and unionized employers were significantly more likely (67.9% and 92.7%, respectively) and small employers were significantly less likely (18.2%) to comply with the reporting rule. Enforcement inspections at 327 workplaces resulted in 403 violations; of those, 179 (54.7%) employers had not corrected the amputation hazard before the time of inspection.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>Michigan employers reported less than half of the work-related amputations required by OSHA's reporting regulation. Noncompliance was greatest in small employers, and agriculture, forestry, fishing, and hunting; construction; arts, entertainment, and recreation; accommodation and food services; and retail and other service industries. Inspections found that over half of the employers had not corrected the hazard that caused the amputation at the time of the inspection's initial opening date; in these cases, abatement of any hazards identified would have occurred after the inspection. Improved compliance in employer reporting of work-related amputations will identify hazards posing a high risk of recurrence of injury to other workers from the same injury source. Greater complia","PeriodicalId":7873,"journal":{"name":"American journal of industrial medicine","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajim.23560","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139085567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Camila C. de Sousa PhD, Tânia M. Araújo PhD, Manuela M. Maturino MSc
Background
Previous studies have supported the relevance of using broad and complex approaches, including multiple explanatory categories, to analyze mental disorders in the working population. This study aimed to assess the direct and indirect effects of gender, race, social class, and occupational stressors on mental health.
Methods
A cross-sectional study used a random sample of 3343 health workers. The effort–reward imbalance (ERI) scale measured occupational stressors. The World Health Organization Self-Reporting Questionnaire (SRQ-20) evaluated common mental disorders (CMDs) as outcomes. The role of gender, race/color, and class determinants (level of schooling and income) in the relationship between occupational stressors and CMD was assessed. Structural equation modeling was used to determine associations and effects.
Results
Occupational stressors were directly associated with CMD and mediated the relationship between income and CMD. Gender was directly associated with occupational stressors, income, and domestic overload. Race was associated with education and with CMD through indirect paths mediated by class indicators. Class indicators contributed to increasing exposure to occupational stressors and the occurrence of CMD.
Conclusion
The results highlight the relevance of gender, race/color, and class in understanding the unequal distribution of work stressors and mental illness in health workers.
{"title":"Occupational stressors and mental illness in healthcare work: An intersection between gender, race, and class","authors":"Camila C. de Sousa PhD, Tânia M. Araújo PhD, Manuela M. Maturino MSc","doi":"10.1002/ajim.23558","DOIUrl":"10.1002/ajim.23558","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Previous studies have supported the relevance of using broad and complex approaches, including multiple explanatory categories, to analyze mental disorders in the working population. This study aimed to assess the direct and indirect effects of gender, race, social class, and occupational stressors on mental health.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A cross-sectional study used a random sample of 3343 health workers. The effort–reward imbalance (ERI) scale measured occupational stressors. The World Health Organization Self-Reporting Questionnaire (SRQ-20) evaluated common mental disorders (CMDs) as outcomes. The role of gender, race/color, and class determinants (level of schooling and income) in the relationship between occupational stressors and CMD was assessed. Structural equation modeling was used to determine associations and effects.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Occupational stressors were directly associated with CMD and mediated the relationship between income and CMD. Gender was directly associated with occupational stressors, income, and domestic overload. Race was associated with education and with CMD through indirect paths mediated by class indicators. Class indicators contributed to increasing exposure to occupational stressors and the occurrence of CMD.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The results highlight the relevance of gender, race/color, and class in understanding the unequal distribution of work stressors and mental illness in health workers.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7873,"journal":{"name":"American journal of industrial medicine","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138826121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sharon R. Silver, Marie H. Sweeney, Wayne T. Sanderson, Regina Pana-Cryan, Andrea L. Steege, Brian Quay, Tania Carreón, Michael A. Flynn
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.
{"title":"Assessing the role of social determinants of health in health disparities: The need for data on work","authors":"Sharon R. Silver, Marie H. Sweeney, Wayne T. Sanderson, Regina Pana-Cryan, Andrea L. Steege, Brian Quay, Tania Carreón, Michael A. Flynn","doi":"10.1002/ajim.23557","DOIUrl":"10.1002/ajim.23557","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7873,"journal":{"name":"American journal of industrial medicine","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138716592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sungwon Park PhD, RN, Chang Gi Park PhD, OiSaeng Hong PhD, RN, FAAN, FAAOHN
Background
Working from home (WFH) may affect health behaviors and mental health. The coronavirus disease-2019 (COVID-19) pandemic saw many US employees transition to WFH, which has persisted in various job sectors and significantly impacted employees. However, its effects on health outcomes have remained unclear. We aimed to explore the characteristics and health outcomes of, and health-related differences between, WFH and not-WFH groups.
Methods
Using the 2021 California Health Interview Survey data, we analyzed health behaviors (smoking, alcohol consumption, and fruit-related nutrition) and the mental health status of 12,438 individuals using descriptive statistics, Pearson's χ2 test, and regressions.
Results
A total of 39% were WFH and 61% were not-WFH. Overall, the WFH group had worse health behaviors and mental health than the not-WFH group. Age was associated with smoking in both groups (WFH: b = 0.37; not-WFH: b = 0.35), but with fruit-related nutrition only in the WFH group. Household income and occupation were associated with alcohol consumption in both groups. Age (WFH: b = −1.58; not-WFH: b = −1.39), household income (WFH: b = −0.75; not-WFH: b = −0.34), and job duration (WFH: b = −0.34; not-WFH: b = −0.40) were associated with mental health in both groups; those who were younger and had lower household incomes and job durations had worse mental health.
Conclusion
Health management is a clear necessity for the WFH group. Irrespective of WFH status, young workers with shorter than 5 years' job duration reported mental distress, highlighting a need for distress assessment and management for the young workforce.
{"title":"Exploring the characteristics and health outcomes of working from home: Analysis of 2021 California Health Interview Survey data","authors":"Sungwon Park PhD, RN, Chang Gi Park PhD, OiSaeng Hong PhD, RN, FAAN, FAAOHN","doi":"10.1002/ajim.23556","DOIUrl":"10.1002/ajim.23556","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Working from home (WFH) may affect health behaviors and mental health. The coronavirus disease-2019 (COVID-19) pandemic saw many US employees transition to WFH, which has persisted in various job sectors and significantly impacted employees. However, its effects on health outcomes have remained unclear. We aimed to explore the characteristics and health outcomes of, and health-related differences between, WFH and not-WFH groups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using the 2021 California Health Interview Survey data, we analyzed health behaviors (smoking, alcohol consumption, and fruit-related nutrition) and the mental health status of 12,438 individuals using descriptive statistics, Pearson's <i>χ</i><sup>2</sup> test, and regressions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 39% were WFH and 61% were not-WFH. Overall, the WFH group had worse health behaviors and mental health than the not-WFH group. Age was associated with smoking in both groups (WFH: <i>b</i> = 0.37; not-WFH: <i>b</i> = 0.35), but with fruit-related nutrition only in the WFH group. Household income and occupation were associated with alcohol consumption in both groups. Age (WFH: <i>b</i> = −1.58; not-WFH: <i>b</i> = −1.39), household income (WFH: <i>b</i> = −0.75; not-WFH: <i>b</i> = −0.34), and job duration (WFH: <i>b</i> = −0.34; not-WFH: <i>b</i> = −0.40) were associated with mental health in both groups; those who were younger and had lower household incomes and job durations had worse mental health.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Health management is a clear necessity for the WFH group. Irrespective of WFH status, young workers with shorter than 5 years' job duration reported mental distress, highlighting a need for distress assessment and management for the young workforce.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7873,"journal":{"name":"American journal of industrial medicine","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajim.23556","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138562354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dallas S. Shi MD, PhD, Emily McDonald MD, Melisa Shah MD, MPH, Matthew R. Groenewold PhD, James M. Haynes MPH, Bryan R. Spencer PhD, MPH, Susan L. Stramer PhD, Leora R. Feldstein PhD, MSc, Sharon Saydah PhD, MHS, Jefferson Jones MD, MPH, Sophia K. Chiu MD, MPH, Jessica L. Rinsky PhD, MPH
Background
Work is a social determinant of health that is often overlooked. There are major work-related differences in the risk of severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) infection and death, but there have been few analyses of infection rates across industry groups. To date, only one national assessment of SARS-CoV-2 infection prevalence by industry based on self-report has been completed. No study has looked at seroprevalence of COVID-19 by industry.
Methods
During May–December 2021, blood donors with SARS-CoV-2 antinucleocapsid testing were sent an electronic survey about their work. Free-text industry responses were classified using the North American Industry Classification System. We estimated seroprevalence and 95% confidence intervals (CIs) of SARS-CoV-2 infection by industry.
Results
Of 57,726 donors, 7040 (12%, 95% CI: 11.9%−12.5%) had prior SARS-CoV-2 infection. Seroprevalence was highest among Accommodation & Food Services (19.3%, 95% CI: 17.1%−21.6%), Mining, Quarrying, and Oil and Gas Extraction (19.2%, 95% CI: 12.8%−27.8%), Healthcare & Social Assistance (15.6%, 95% CI: 14.9%−16.4%), and Construction (14.7%, 95% CI: 13.1%−16.3%). Seroprevalence was lowest among Management of Companies & Enterprises (6.5%, 95% CI: 3.5%−11.5%), Professional Scientific & Technical Services (8.4%, 95% CI: 7.7%−9.0%), and Information (9.9%, 95% CI: 8.5%−11.5%).
Conclusions
While workers in all industries had serologic evidence of SARS-CoV-2 infection, certain sectors were disproportionately impacted. Disease surveillance systems should routinely collect work characteristics so public health and industry leaders can address health disparities using sector-specific policies.
{"title":"Prevalence of SARS-CoV-2 infection among US blood donors by industry, May–December 2021","authors":"Dallas S. Shi MD, PhD, Emily McDonald MD, Melisa Shah MD, MPH, Matthew R. Groenewold PhD, James M. Haynes MPH, Bryan R. Spencer PhD, MPH, Susan L. Stramer PhD, Leora R. Feldstein PhD, MSc, Sharon Saydah PhD, MHS, Jefferson Jones MD, MPH, Sophia K. Chiu MD, MPH, Jessica L. Rinsky PhD, MPH","doi":"10.1002/ajim.23552","DOIUrl":"10.1002/ajim.23552","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Work is a social determinant of health that is often overlooked. There are major work-related differences in the risk of severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) infection and death, but there have been few analyses of infection rates across industry groups. To date, only one national assessment of SARS-CoV-2 infection prevalence by industry based on self-report has been completed. No study has looked at seroprevalence of COVID-19 by industry.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>During May–December 2021, blood donors with SARS-CoV-2 antinucleocapsid testing were sent an electronic survey about their work. Free-text industry responses were classified using the North American Industry Classification System. We estimated seroprevalence and 95% confidence intervals (CIs) of SARS-CoV-2 infection by industry.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of 57,726 donors, 7040 (12%, 95% CI: 11.9%−12.5%) had prior SARS-CoV-2 infection. Seroprevalence was highest among Accommodation & Food Services (19.3%, 95% CI: 17.1%−21.6%), Mining, Quarrying, and Oil and Gas Extraction (19.2%, 95% CI: 12.8%−27.8%), Healthcare & Social Assistance (15.6%, 95% CI: 14.9%−16.4%), and Construction (14.7%, 95% CI: 13.1%−16.3%). Seroprevalence was lowest among Management of Companies & Enterprises (6.5%, 95% CI: 3.5%−11.5%), Professional Scientific & Technical Services (8.4%, 95% CI: 7.7%−9.0%), and Information (9.9%, 95% CI: 8.5%−11.5%).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>While workers in all industries had serologic evidence of SARS-CoV-2 infection, certain sectors were disproportionately impacted. Disease surveillance systems should routinely collect work characteristics so public health and industry leaders can address health disparities using sector-specific policies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7873,"journal":{"name":"American journal of industrial medicine","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138476573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Response to Geyer","authors":"Arthur L. Frank","doi":"10.1002/ajim.23555","DOIUrl":"10.1002/ajim.23555","url":null,"abstract":"","PeriodicalId":7873,"journal":{"name":"American journal of industrial medicine","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138457371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号