Forty years of struggle in North Carolina: Workplace segregation and fatal occupational injury rates.

OBJECTIVE: To assess workplace segregation in fatal occupational injury from 1992 to 2017 in North Carolina. METHODS: We calculated occupational fatal injury rates within categories of occupation, industry, race, age, and sex; and estimated expected numbers of fatalities among Black and Hispanic male workers had they experienced the rates of White male workers. We also estimated the contribution of workforce segregation to disparities by estimating the expected number of fatalities among Black and Hispanic male workers had they experienced the industry and occupation patterns of White male workers. We assessed person-years of life-lost, using North Carolina life expectancy estimates. RESULTS: Hispanic workers contributed 32% of their worker-years and experienced 58% of their fatalities in construction. Black workers were most overrepresented in the food manufacturing industry. Hispanic males experienced 2.11 (95% CI: 1.86-2.40) times the mortality rate of White males. The Black-White and Hispanic-White disparities were widest among workers aged 45 and older, and segregation into more dangerous industries and occupations played a substantial role in driving disparities. Hispanic workers who suffered occupational fatalities lost a median 47 life-years, compared to 37 among Black workers and 36 among White workers. CONCLUSIONS: If Hispanic and Black workers experienced the workplace safety of their White counterparts, fatal injury rates would be substantially reduced. Workforce segregation reflects structural racism, which also contributes to mortality disparities. Root causes must be addressed to eliminate disparities.

Sociodemographic inequities in the burden of carcinogenic industrial air emissions in the United States.

BACKGROUND: Industrial facilities are not located uniformly across communities in the United States, but how the burden of exposure to carcinogenic air emissions may vary across population characteristics is unclear. We evaluated differences in carcinogenic industrial pollution among major sociodemographic groups in the United States and Puerto Rico. METHODS: We evaluated cross-sectional associations of population characteristics including race and ethnicity, educational attainment, and poverty at the census tract level with point-source industrial emissions of 21 known human carcinogens using regulatory data from the US Environmental Protection Agency. Odds ratios and 95% confidence intervals comparing the highest emissions (tertile or quintile) to the referent group (zero emissions [ie, nonexposed]) for all sociodemographic characteristics were estimated using multinomial, population density-adjusted logistic regression models. RESULTS: In 2018, approximately 7.4 million people lived in census tracts with nearly 12 million pounds of carcinogenic air releases. The odds of tracts having the greatest burden of benzene, 1,3-butadiene, ethylene oxide, formaldehyde, trichloroethylene, and nickel emissions compared with nonexposed were 10%-20% higher for African American populations, whereas White populations were up to 18% less likely to live in tracts with the highest emissions. Among Hispanic and Latino populations, odds were 16%-21% higher for benzene, 1,3-butadiene, and ethylene oxide. Populations experiencing poverty or with less than high school education were associated with up to 51% higher burden, irrespective of race and ethnicity. CONCLUSIONS: Carcinogenic industrial emissions disproportionately impact African American and Hispanic and Latino populations and people with limited education or experiencing poverty thus representing a source of pollution that may contribute to observed cancer disparities.

Satellite mapping reveals extensive industrial activity at sea.

The world's population increasingly relies on the ocean for food, energy production and global trade1-3, yet human activities at sea are not well quantified4,5. We combine satellite imagery, vessel GPS data and deep-learning models to map industrial vessel activities and offshore energy infrastructure across the world's coastal waters from 2017 to 2021. We find that 72-76% of the world's industrial fishing vessels are not publicly tracked, with much of that fishing taking place around South Asia, Southeast Asia and Africa. We also find that 21-30% of transport and energy vessel activity is missing from public tracking systems. Globally, fishing decreased by 12 ± 1% at the onset of the COVID-19 pandemic in 2020 and had not recovered to pre-pandemic levels by 2021. By contrast, transport and energy vessel activities were relatively unaffected during the same period. Offshore wind is growing rapidly, with most wind turbines confined to small areas of the ocean but surpassing the number of oil structures in 2021. Our map of ocean industrialization reveals changes in some of the most extensive and economically important human activities at sea.

Understanding Financial Relationships Between Orthopedic Surgeons and Industry for Research.

OBJECTIVE: This study sought to understand trends in industry payments for research awarded to orthopedic surgeons. MATERIALS AND METHODS: The Centers for Medicare & Medicaid Services Open Payments database was queried for the years 2016 to 2021 for industry payments for research. Financial analyses were performed to understand temporal trends and differences by orthopedic subspecialty and principal investigator characteristics such as sex. The threshold for statistical significance was set at .05. RESULTS: A total of 2014 orthopedic surgeons were identified, among whom 542 adult reconstruction (27%) and 460 sports medicine (23%) surgeons were major beneficiaries. Seventy-one female orthopedic surgeons comprised the minority (4%). Total research payments awarded during the study period aggregated to $266,633,592, with adult reconstruction ($88,819,047; 33%) and sports medicine ($57,949,822; 22%) receiving the highest amounts. Total research payments awarded trended upward yearly except for a decline in 2020 that subsequently rebounded (P<.001). Median annual research payment per orthopedic surgeon was $13,375. Median total industry payments per orthopedic surgeon differed between specialties (P <.001), with the highest amounts for adult reconstruction ($44,063) and sports medicine ($34,567) and the lowest amounts for hand ($12,052) and foot and ankle ($19,233). Median total payments did not differ significantly when stratified by sex (P=.276) and region (P=.906). Specialties in which the respective top three companies offered the majority of the research funding were musculoskeletal oncology (90%), pediatric orthopedics (66%), and shoulder and elbow (64%). CONCLUSION: These results can be used as a primer for orthopedic surgeons seeking to leverage industry relationships to fund translational research. [Orthopedics. 2024;47(3):172-178.].

Country-specific net-zero strategies of the pulp and paper industry.

The pulp and paper industry is an important contributor to global greenhouse gas emissions1,2. Country-specific strategies are essential for the industry to achieve net-zero emissions by 2050, given its vast heterogeneities across countries3,4. Here we develop a comprehensive bottom-up assessment of net greenhouse gas emissions of the domestic paper-related sectors for 30 major countries from 1961 to 2019-about 3.2% of global anthropogenic greenhouse gas emissions from the same period5-and explore mitigation strategies through 2,160 scenarios covering key factors. Our results show substantial differences across countries in terms of historical emissions evolution trends and structure. All countries can achieve net-zero emissions for their pulp and paper industry by 2050, with a single measure for most developed countries and several measures for most developing countries. Except for energy-efficiency improvement and energy-system decarbonization, tropical developing countries with abundant forest resources should give priority to sustainable forest management, whereas other developing countries should pay more attention to enhancing methane capture rate and reducing recycling. These insights are crucial for developing net-zero strategies tailored to each country and achieving net-zero emissions by 2050 for the pulp and paper industry.

Analysis on influencing factors of carbon emissions from China's pulp and paper industry and carbon peaking prediction.

China's pulp and paper industry (CPPI) has been always the main carbon emission source in recent years. However, the analysis on influencing factors of carbon emissions from this industry is insufficient. To address the issue, the CO2 emissions from CPPI are estimated in the period of 2005-2019, the driving factors of CO2 emissions are investigated by the logarithmic mean Divisia index (LMDI) method, the decoupling state of economic growth and CO2 emissions is determined by Tapio decoupling model, and finally, future CO2 emissions are predicted under four scenarios by the STIRPAT model to explore the potential of carbon peaking. The results show that CPPI exhibits a rapid increase and a fluctuating downward trend in CO2 emissions during the period of 2005-2013 and 2014-2019, respectively. The main promoting and inhibiting factors to the increase of CO2 emission are per capita industrial output value and energy intensity, respectively. There are five decoupling states of CO2 emissions and economic growth during the study period, and the CO2 emissions exhibit a weak decoupling state with the industrial output value growth in most years of the study period. It is very difficult to realize the carbon peaking goal by 2030 under the baseline and fast development scenarios. Therefore, efficient low carbon and strong low-carbon development policies are necessary and urgent for the realization of carbon peaking goal and the sustainable development of CPPI.

The role of modifiable risk factors in incident cancer in transport, rescue, and security industries.

PURPOSE: Examine the risk for site-specific incident cancer across representative transport, rescue, and security industries. METHODS: This Danish nationwide register-based study included all 302,789 workers from transport, rescue and security industries in 2001-2015 and 2,230,877 individuals aged 18-64 years from a total sample of the economically active population for comparison. We used Cox models to estimate the hazard ratios (HRs) of incident cancers. We categorized site-specific cancers by using population-attributable fraction (PAF) estimates from the previous literature. RESULTS: During an average follow-up of 13.4 years, 22,116 incident cancer cases were recorded in these industries. Compared with the reference population, the age-adjusted cancer incidence with a high PAF was higher among men in seafaring (HR 1.28; 95% CI 1.14-1.43), and land transport (HR 1.32; 95% CI: 1.26-1.37), and among women in seafaring (HR 1.26; 95% CI: 1.01-1.57), land transport (HR 1.21; 95% CI: 1.12-1.32), aviation (HR 1.22; 95% CI: 1.05-1.41), and police force (HR 1.21; 95% CI: 1.04-1.40). Overall, tobacco and physical inactivity were the most significant risk factors of cancer. CONCLUSIONS: Regardless of considerable disparities in incident cancer attributable to modifiable risk factors across industries, the total incident cancer rate was elevated in all industries in both sexes.

Characteristics of workers' compensation claim applications for COVID-19 infections in South Korea.

This study aimed to identify the major industries and jobs with the highest proportion of workers' compensation (WC) claims for COVID-19, characterize COVID-19 WC claims in terms of their demographic properties and disease severity, and identify factors influencing the approval of COVID-19 WC claims as occupational disease. A total of 488 workers who submitted COVID-19-related claims to the Korea Workers' Compensation and Welfare Service (KWCWS) from January 2020 to July 2021 were analyzed. A Fisher's exact test was employed to associate the severity of COVID-19 infection with demographic properties. The highest proportion of all COVID-19 WC claims compensated as occupational disease (N=462) were submitted by healthcare workers (HCW=233, 50%), while only 9% (N=41) of the total originated from manufacturing industries. The 5% (N=26) of the COVID-19 WC claims accepted were evaluated as severe (N=15) and acute respiratory distress syndrome (N=9). A total of 71% (N=329) of the COVID-19 patients compensated (N=462) were from workplaces with infection clusters. A total of 26 WC cases were rejected for various reasons, including unclear infection routes, infection at private gatherings (including within families), no diagnosis, and more. Given our findings, we suggest an official system should be established to detect and compensate more job-associated infectious diseases like COVID-19.

How do resource dependence and technological progress affect carbon emissions reduction effect of industrial structure transformation? Empirical research based on the rebound effect in China.

Under the guidance of carbon peak and carbon neutral targets, the industrial structure transformation is vital for carbon emissions reduction in China. However, there is a rebound effect of carbon emissions during the industrial structure transformation. Resource dependence and technological progress have significant impacts on industrial structure transformation and its carbon reduction effect. This paper explores how industrial structure transformation under resource dependence causes the rebound effect from a technological progress perspective. The key results indicate that (1) resource dependence distorts the carbon emissions reduction effect of industrial structure transformation; (2) with the development of technology, the industrial structure upgrading under resource dependence could cause an increase on carbon emissions at the beginning, but the increase would be weakened subsequently, displaying a two-stage feature; (3) the industrial structure rationalization under resource dependence reduces carbon emissions at first, but the reduction would be weakened as the technology develops, then industrial structure's rationalization shows an insignificant impact on carbon emissions, and finally reduces carbon emissions again, presenting a four-stage characteristic; (4) environmental protection technology can correct the distortion effect of resource dependence on the industrial structure rationalization and amplify the industrial structure rationalization's reduction effects on carbon emissions; (5) with the development of energy-saving technology, industrial structure rationalization has a paradoxical impact on carbon emissions, the industrial structure rationalization first reduces, then increases, and finally reduces carbon emissions, indicating an inverted "N" relationship. Finally, policy recommendations for carbon emissions reduction are proposed from the perspective of industrial structure transformation and technological progress.

Recommending blue ocean technologies for subcontractors: A framework based on business reports of prime contractors and patents.

Subcontractors depend heavily on their prime contractor and thus find it very risky to enter a new business on their own. This study proposes a framework for these subcontractors to develop blue ocean technologies related to their prime contractor. First, the primary technologies predicted to be promising are extracted from the business reports of the prime contractor. Sub-technologies are then selected through a patent-based search using keywords and International Patent Classification codes of the primary technologies. From them, blue ocean technologies are proposed by optimizing the weighted mean of the min-max normalized market value, degree of competition in the technology market, and subcontractors' potential technological capabilities for each sub-technology. This study shows that subcontractors can enhance their technology competitiveness by finding a low-risk blue ocean technology. Our empirical research on the subcontractors of a semiconductor firm identified technological patent fields for them to pursue. From our framework, subcontractors can identify blue ocean technologies by considering their prime contractor's future industrial areas and technologies of interest as well as their own technological capabilities. Furthermore, the prime contractors can gain the synergy effect of technology expansion through cooperation.

Impact of the implementation of carbon emission trading on corporate financial performance: Evidence from listed companies in China.

With the development of ecological paradigm coupled with the relentless implementation of myriad environmental policies in China, the rapid development of carbon emission trading and carbon trading market has had a vital impact on the financial performance of enterprises at the microlevel. This study has sampled the A-share listed companies in China, from 2009 to 2018, and adopted the difference-in-difference (DID) method to investigate the effect of the carbon emission trading on corporate financial performance from the microlevel. Evidence showed that the implementation of carbon emission trading effectively improved the total asset-liability ratio of enterprises, though it reduced the value of the current capital market. Moreover, in the regions under strict legal environment, the enhancement effect of the total asset-liability ratio was more obvious, whereas in the regions under loose legal environment, the reduction effect of the value of the capital market was more obvious. Further analysis showed that the implementation of carbon emission trading could not promote Chinese enterprises to increase R&D investment. Hence the implementation of carbon emission trading has improved the level of non-business income of enterprises incorporated into the trading system, but its impact on the investment income of enterprises was not significant.

The Shortest Duration Constrained Hidden Markov Model: Data denoise and forecast optimization on the country-product matrix for the Fitness-Complexity Algorithm.

The Economic Fitness Index describes industrial completeness and comprehensively reflects product diversification with competitiveness and product complexity in production globalization. The Fitness-Complexity Algorithm offers a scientific approach to predicting GDP and obtains fruitful results. As a recursion algorithm, the non-linear iteration processes give novel insights into product complexity and country fitness without noise data. However, the Country-Product Matrix and Revealed Comparative Advantage data have abnormal noises which contradict the relative stability of product diversity and the transformation of global production. The data noise entering the iteration algorithm, combined with positively related Fitness and Complexity, will be amplified in each recursion step. We introduce the Shortest Duration Constrained Hidden Markov Model (SDC-HMM) to denoise the Country-Product Matrix for the first time. After the country-product matrix test, the country case test, the noise estimation test and the panel regression test of national economic fitness indicators to predict GDP growth, we show that the SDC-HMM could reduce abnormal noise by about 25% and identify change points. This article provides intra-sample predictions that theoretically confirm that the SDC-HMM can improve the effectiveness of economic fitness indicators in interpreting economic growth.

Assessing disabling and non-disabling injuries and illnesses using accepted workers compensation claims data to prioritize industries of high risk for Oregon young workers.

INTRODUCTION: Young workers are especially vulnerable to occupational injuries and illnesses. There is a continued need to investigate injury burden among young workers across demographics and industry to inform targeted interventions. Workers compensation (WC) claims are important for quantifying work-related injuries and illnesses, however published studies have focused on disabling claims. This study extended previous research on Oregon young workers by including the most recent WC claims data to identify patterns of injury and high risk industries. METHODS: We obtained all accepted disabling claims (N = 13,360) and a significant portion of non-disabling claims (N = 24,660) on workers aged 24 years and under from 2013 to 2018. Claim count, rate and cost were calculated by year, age, gender, industry, and injury type. A prevention index (PI) method was used to rank industries in order to inform prevention efforts. RESULTS: Average annual disabling and non-disabling claim rates were 111.6 and 401.3 per 10,000 young workers. Workers aged 19-21 (disabling: 119.0 per 10,000 and non-disabling: 429.3) and 22-24 years (115.7 and 396.4) and male workers (145.3 and 509.0) had higher claim rates than workers aged 14-18 (80.6 and 297.0) and female workers (79.8 and 282.9). The most frequent injury types were "struck by/against" (35.6%) and "work-related musculoskeletal disorders (WMSDs)" (19.5%). High risk industries included agriculture, construction, and manufacturing for both genders combined. For female young workers, the highest risk industry was healthcare. CONCLUSIONS: This study demonstrated the added value of non-disabling WC claims data. Using both disabling and non-disabling data and PI method, agriculture, construction, manufacturing and healthcare industries were identified as priority workplaces to prevent common and costly injuries among Oregon young workers. Practical Applications: While the industries identified are considered hazardous for all workers, findings in this study can guide targeted research and prevention efforts specific to young workers.

Analyzing the regional economic changes in a high-tech industrial development zone using machine learning algorithms.

The aims are to improve the efficiency in analyzing the regional economic changes in China's high-tech industrial development zones (IDZs), ensure the industrial structural integrity, and comprehensively understand the roles of capital, technology, and talents in regional economic structural changes. According to previous works, the economic efficiency and impact mechanism of China's high-tech IDZ are analyzed profoundly. The machine learning (ML)-based Data Envelopment Analysis (DEA) and Malmquist index measurement algorithms are adopted to analyze the dynamic and static characteristics of high-tech IDZ's economic data from 2009 to 2019. Furthermore, a high-tech IDZ economic efficiency influencing factor model is built. Based on the detailed data of a high-tech IDZ, the regional economic changes are analyzed from the following dimensions: economic environment, economic structure, number of talents, capital investment, and high-tech IDZ's regional scale, which verifies the effectiveness of the proposed model further. Results demonstrate that the comprehensive economic efficiency of all national high-tech IDZs in China is relatively high. However, there are huge differences among different regions. The economic efficiency of the eastern region is significantly lower than the national average. The economic structure, number of talents, capital investment, and economic efficiency of the high-tech IDZs show a significant positive correlation. The economic changes in high-tech IDZs can be improved through the secondary industry, employee value, and funding input. The ML technology applied can make data processing more efficient, providing proper suggestions for developing China's high-tech industrial parks.

Regional development potentials of Industry 4.0: Open data indicators of the Industry 4.0+ model.

This paper aims to identify the regional potential of Industry 4.0 (I4.0). Although the regional background of a company significantly determines how the concept of I4.0 can be introduced, the regional aspects of digital transformation are often neglected with regard to the analysis of I4.0 readiness. Based on the analysis of the I4.0 readiness models, the external regional success factors of the implementation of I4.0 solutions are determined. An I4.0+ (regional Industry 4.0) readiness model, a specific indicator system is developed to foster medium-term regional I4.0 readiness analysis and foresight planning. The indicator system is based on three types of data sources: (1) open governmental data; (2) alternative metrics like the number of I4.0-related publications and patent applications; and (3) the number of news stories related to economic and industrial development. The indicators are aggregated to the statistical regions (NUTS 2), and their relationships analyzed using the Sum of Ranking Differences (SRD) and Promethee II methods. The developed I4.0+ readiness index correlates with regional economic, innovation and competitiveness indexes, which indicates the importance of boosting regional I4.0 readiness.

Incidence of mesothelioma and asbestosis by occupation in a diverse workforce.

OBJECTIVE: We sought to characterize detailed patterns of mesothelioma and asbestosis incidence in the workforce as part of an occupational disease surveillance program in Ontario, Canada. METHODS: The Occupational Disease Surveillance System (ODSS) cohort was established using workers' compensation claims data and includes 2.18 million workers employed from 1983 to 2014. Workers were followed for mesothelioma and asbestosis diagnoses in Ontario Cancer Registry, physician, hospital, and ambulatory care records through 2016. Trends in incidence rates were estimated over the study period. Cox proportional hazard models were used to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: A total of 854 mesothelioma and 737 asbestosis cases were diagnosed during follow-up. Compared with all other workers in the ODSS, those employed in construction trades occupations had the greatest adjusted incidence rate of both mesothelioma (223 cases; HR, 2.38; 95% CI: 2.03-2.78) and asbestosis (261 cases; HR, 3.64; 95% CI: 3.11-4.25). Rates were particularly elevated for insulators, pipefitters and plumbers, and carpenters. Workers in welding and flame cutting, boiler making, and mechanic and machinery repair occupations, as well as those in industrial chemical and primary metal manufacturing industries, had strongly elevated rates of both diseases. Rates were greater than anticipated for workers in electrical utility occupations and education and related services. CONCLUSIONS: Results substantiate the risk of mesothelioma and asbestosis in occupation and industry groups in the Ontario workforce with known or suspected asbestos exposure. Sustained efforts to prevent the occurrence of additional cases of disease in high-risk groups are warranted.

Assessment of Occupational Injury among Industrial Workers in the Bahir Dar City of Northwest Ethiopia: Institution-Based Cross-Sectional Study.

Background: Ethiopia is one of the economically fastest growing countries in the world. Industries in Ethiopia are booming, and Bahir Dar is one of the industrial zones in the country. The city administration is planning to recruit the majority of the workforce in these industries. However, injuries related to occupations in the industries are not that much studied yet. Therefore, this study aimed to assess the prevalence of occupational injury and its associated factors among industrial workers in the Bahir Dar city of Northwest Ethiopia. Methods and Materials: Institution-based cross-sectional study design was used. Multistage stratified random sampling technique was employed to select 846 study participants from each stratum (small-, medium-, and large-scale industries). Data were analyzed using Statistical Package for Social Sciences (SPSS), version 21. Binary logistic regression was employed to determine the existence of an association between dependent and independent variables. Result: A total of 803 participants were included in the study with a response rate of 95%. The mean age of respondents was 28.9 years (SD ± 8 years). Five hundred nine (63.4%) were occupationally injured in the last 12 months. Sex (AOR = 3.66, 95% CI = (2.53-5.29)), employment status (AOR = 7.33, 95% CI = (3.31-16.22)), regular health and safety supervision (AOR = 2.66, 95% CI= (1.79-3.96)), training prior to entry to actual work (AOR = 3.18, 95% CI= (2.14-4.74)), and use of personal protective equipment (PPE) (AOR = 2.48, 95% CI= (1.74-3.56)) were significantly associated with occupational injury. Conclusion: The prevalence of occupational injury in this research is found to be very high. It is advisable to provide sustainable training and regular occupational health and safety supervision for industrial workers in the city. Moreover, research has to be conducted to know the reasons for the difference in the prevalence of occupational injury between large-, medium-, and small-scale industries.

Beta decoupling relationship between CO2 emissions by GDP, energy consumption, electricity production, value-added industries, and population in China.

The credible sources of fossil energy efficiently are a vital cause of economic growth and considerable influence on adequate security. Whereas radiant energy positively enhances or ostensibly promotes socio-economic stability and the controlled environment. The fossil energy sources supply has become progressively stern in China and reconnoitering the beta decoupling relationships between CO2 emissions, GDP, energy consumption, electricity consumption, value-added industries, and population. The results will be favorable for illustrative the security of the valuable resources. This study adopts the extended stochastic model (STIRPAT) with Beta Decoupling Techniques (BDT). This modern technique merely employs the decoupling situation by the alpha and beta effects from 1989 to 2018 and calculates the % change in CO2 emissions by GDP growth and energy consumption. The estimated results represent negative and economic growth depends on coal and natural gas. First, CO2 emissions annually increasing cause of rapid growth, energy consumption, and electricity production, and the structural contradiction of energy remained static. Second, the Value-added industries estimated that CO2 emissions reduce by primary industries. Third, the decoupling states of CO2 emissions and population show an inverse relationship. This paper tentatively suggests China is sustainable, naturally strengthens energy output, transmutes the energy consumption structure, and advances development policies under environmental circumstances.

Incidence of acute myocardial infarction in the workforce: Findings from the Occupational Disease Surveillance System.

BACKGROUND: Increased risks of acute myocardial infarction (AMI) may be attributable to the workplace, however, associations are not well-established. Using the Occupational Disease Surveillance System (ODSS), we sought to estimate associations between occupation and industry of employment and AMI risk among workers in Ontario, Canada. METHODS: The study population was derived by linking provincial accepted lost-time workers' compensation claims data, to inpatient hospitalization records. Workers aged 15-65 years with an accepted non-AMI compensation claim were followed for an AMI event between 2007 and 2016. Adjusted Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for each industry and occupation group, compared to all other workers in the cohort. Sex-stratified analyses were also performed. RESULTS: In all, 24,514 incident cases of AMI were identified among 1,502,072 Ontario workers. Increased incidence rates of AMI were found across forestry (HR 1.37, 95% CI 1.19-1.58) and wood processing (HR 1.50, 1.27-1.77) job-titles. Elevated rates were also detected within industries and occupations both broadly related to mining and quarrying (HR 1.52, 1.17-1.97), trucking (HR 1.32, 1.27-1.38), construction (HR 1.32, 1.14-1.54), and the manufacturing and processing of metal (HR 1.41, 1.19-1.68), textile (HR 1.41, 1.07-1.88), non-metallic mineral (HR 1.30, 0.82-2.07), and rubber and plastic (HR 1.42, 1.27-1.60) products. Female food service workers also had elevated AMI rates (HR 1.36, 1.23-1.51). CONCLUSION: This study found occupational variation in AMI incidence. Future studies should examine work-related hazards possibly contributing to such excess risks, like noise, vibration, occupational physical activity, shift work, and chemical and particulate exposures.

Disparities in Depression Status Among Different Industries in Transition Economy: A Cross-Sectional Study of Mongolia.

Transition economies tend to rely on rapid growth of specific industries and hence often leads to disparities in health status among the working population. This study aims to determine the depression status in different industries and occupational groups in Mongolia, a country that is experiencing an economic transition. We conducted a cross-sectional survey between July and September 2018 in Ulaanbaatar, Mongolia. A total of 1784 employees from 22 private and public companies were enrolled in this study. The Patient Health Questionnaire-9 (PHQ-9) was used to determine the severity of depression. Prevalence of depression is evaluated using weighted analysis. The association between occupational groups (white, blue, and pink collars), industries, and PHQ-9 score was analyzed using linear regression. In multiple regression, the workers in the transportation, public administration, and education industries exhibited the highest depression scores (P < .001). Traditional variables such as age, sex, and marital status remained significant predictors in our model. Industrial types should not be overlooked in identifying depression in the working population. This is especially true for a transition economy like Mongolia. Analysis by industries is essential to promote stress management in the future among vulnerable groups in specific industries.