Collection Of Occupational Data Research Articles

Decade-long insights: tracking asbestos-related health impacts among formerly exposed workers in Palermo, Italy.

Asbestos is a foremost occupational carcinogen globally. Despite the prohibition under Law 257/1992, Italy persists as one of the European nations most burdened by asbestos-related diseases (ARDs). This research assessed ARD cases in asbestosexposed workers from the Province of Palermo, Italy, spanning 2010-2021. Data acquisition utilized the epidemiological dataset from the 'Service of Prevention and Safety on Work Environment' under the Prevention Department of Palermo's Local Health Authority (LHA). Between 2010 and 2021, we identified 245 ARD instances, comprising 163 Asbestosis/Pleural plaques, 41 Lung Cancers, 38 Mesotheliomas, and 3 unspecified cases. Multivariate analysis indicated a notable decline in temporal exposure for mesothelioma (HR=0.933; 95% CI=0.902-0.965) and lung cancer (HR=0.93; 95% CI=0.90-0.978) relative to pleural plaques/asbestosis. Tobacco use displayed a pronounced correlation with lung cancer (smoker HR=64.520 95% CI=13,075-318.390; former smoker HR=20.917 95% CI=4,913-89.048). A significant link was observed between mesothelioma and pleural plaques/asbestosis in those employed in shipbuilding and repair (HR=0.371 95% CI=0.155-0.892). ARDs persist in clinical observations, even following the 1992 cessation of asbestos-related activities, emphasizing an enduring public health challenge. Enhancing prevention strategies is paramount, focusing on amplifying anamnestic and occupational data collection, thereby facilitating superior early diagnosis strategies for these maladies in the occupationally exposed cohort.

Measuring Work-related Risk of Coronavirus Disease 2019 (COVID-19): Comparison of COVID-19 Incidence by Occupation and Industry-Wisconsin, September 2020 to May 2021.

BackgroundWork-related exposures play an important role in SARS-CoV-2 transmission, yet few studies have measured the risk of COVID-19 across occupations and industries.MethodsDuring September 2020 – May 2021, the Wisconsin Department of Health Services collected occupation and industry data as part of routine COVID-19 case investigations. Adults aged 18-64 years with confirmed or probable COVID-19 in Wisconsin were assigned standardized occupation and industry codes. Cumulative incidence rates were weighted for non-response and calculated using full-time equivalent (FTE) workforce denominators from the 2020 American Community Survey.ResultsAn estimated 11.6% of workers (347,013 of 2.98 million) in Wisconsin, ages 18-64 years, had COVID-19 from September 2020 to May 2021. The highest incidence by occupation (per 100 full-time equivalents) occurred among personal care and services workers (22.4), healthcare practitioners and support staff (20.7), and protective services workers (20.7). High risk sub-groups included nursing assistants and personal care aides (28.8), childcare workers (25.8), food and beverage service workers (25.3), personal appearance workers (24.4), and law enforcement workers (24.1). By industry, incidence was highest in healthcare (18.6); the highest risk sub-sectors were nursing care facilities (30.5) and warehousing (28.5).ConclusionsThis analysis represents one of the most complete examinations to date of COVID-19 incidence by occupation and industry. Our approach demonstrates the value of standardized occupational data collection by public health, and may be a model for improved occupational surveillance elsewhere. Workers at higher risk of SARS-CoV-2 exposure may benefit from targeted workplace COVID-19 vaccination and mitigation efforts.

Research on occupational diseases in the absence of occupational data: a mixed-method study among cancer registries of Western Switzerland.

The contribution of occupation-related diseases to the global burden of disease is greatly underestimated, mainly due to a shortage of occupational exposure data. This problem is particularly salient in Switzerland, where no estimates of occupation-related disease burden exist, even for the well-recognised occupational cancers, such as malignant pleural mesothelioma and lung cancer. To overcome this situation, we launched a research project "Examining Cancers and Labour Indicators to assess the Burden" (ExCaLIBur). Within this project, we aimed to assess the need for and quality (i.e., completeness, accuracy and precision) of occupation registration in all cancer registries of Western Switzerland. We also aimed to find a relevant and feasible strategy to collect this information in the future. We applied a mixed research method. We observed that, independently of the level of precision (5-3-2-1-digit aggregation level), the accuracy was lesser in the registries that were able to actively search and verify occupational information. Overall, the distinction of occupations based on the 3-digit code presents an acceptable compromise in terms of precision. Having such occupations registered in all, or most, Swiss cancer registries routinely would obviously be valuable for epidemiological surveillance of occupational cancers in Switzerland. However, it seems less obvious how these data could fulfill the research objectives, since a better precision than 3-digit occupational coding is challenging to achieve. Currently, the collection of occupational data by the Swiss cancer registries remains feasible in the frame of specific research projects on occupational cancers. However, available data sources, as well as lack of financial and human resources, will continue to affect quality of the collected occupation data. Therefore, the usage of the standardised questionnaire retracing the individual occupational history to enable further assessment of individual exposure to potential occupational hazards is recommended. However, this approach will disable the Swiss registries to insuring their epidemiological surveillance mission with respect to occupational cancers in Switzerland, for which national statistics remain limited.

Occupational impact in COVID-19 pandemic according to one year of compensation claims in Italy.

to evaluate the patterns of occupational COVID-19 cases, based on compensation claims applied to the Italian National Institute for Insurance against Accidents at Work (Inail). descriptive analyses of daily time series of compensation claims applications, geographical distributions, and occupations involved. Multivariate analyses have been performed for identifying significant epidemiological pattern. compensation claims for COVID-19 injuries received by Inail from March 2020 to February 2021 have been analysed. daily time series of compensation claims applications in the first year of pandemic and comparatively with population data, patterns of occupations majorly involved in time, territorial clusters. in the observed period, Inail has received 155,684 workers' compensation claims with a first peak (more than 1,000 daily compensation claims) in March 2020 and a second peak (more than 1,500) in November 2020. A time dependent geographical pattern was identified, with the Northern regions formerly affected in the first phase, followed by a diffusion in the Central and Southern regions during the summer period. Health technicians (32% and 42% in male and female, respectively) and physicians (15%and 6%) were the most involved workers. The timing of infection was found to depend by job, with physicians, nurses, and health technicians firstly involved with a spread of about 2 weeks with respect to other jobs. Trend in health workers' vaccination has been found in a clear inverse relationship with the decreasing number of compensation claims, remaining, since February 2021, under one hundred daily cases of occupational COVID-19 compensation claims. different intensities, timing, and characteristics were found among application claims, which address for different pandemic diffusion paths. Health workers are the firstly and most involved impacted by the pandemic. The use of application claims could be useful and effective in monitoring the occupational component of COVID-19 and his trend in time and space. There is a need to establish an epidemiological surveillance system that includes the assessment of work related risk, supporting the effectiveness of public insurance and welfare system, and to harmonize occupational data collection among countries.

Increases in Health-Related Workplace Absenteeism Among Workers in Essential Critical Infrastructure Occupations During the COVID-19 Pandemic - United States, March-April 2020.

During a pandemic, syndromic methods for monitoring illness outside of health care settings, such as tracking absenteeism trends in schools and workplaces, can be useful adjuncts to conventional disease reporting (1,2). Each month, CDC's National Institute for Occupational Safety and Health (NIOSH) monitors the prevalence of health-related workplace absenteeism among currently employed full-time workers in the United States, overall and by demographic and occupational subgroups, using data from the Current Population Survey (CPS).* This report describes trends in absenteeism during October 2019-April 2020, including March and April 2020, the period of rapidly accelerating transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). Overall, the prevalence of health-related workplace absenteeism in March and April 2020 were similar to their 5-year baselines. However, compared with occupation-specific baselines, absenteeism among workers in several occupational groups that define or contain essential critical infrastructure workforce† categories was significantly higher than expected in April. Significant increases in absenteeism were observed in personal care and service§ (includes child care workers and personal care aides); healthcare support¶; and production** (includes meat, poultry, and fish processing workers). Although health-related workplace absenteeism remained relatively unchanged or decreased in other groups, the increase in absenteeism among workers in occupational groups less able to avoid exposure to SARS-CoV-2 (3) highlights the potential impact of COVID-19 on the essential critical infrastructure workforce because of the risks and concerns of occupational transmission of SARS-CoV-2. More widespread and complete collection of occupational data in COVID-19 surveillance is required to fully understand workers' occupational risks and inform intervention strategies. Employers should follow available recommendations to protect workers' health.

An intelligent hot-desking model harnessing the power of occupancy sensing data

PurposeThe purpose of this paper is to develop a model to harness occupancy sensing in a commercial hot-desking environment. Hot-desking is a method of office resource management designed to reduce the real estate costs of professional practices. However, the shortcoming is often in the suitability and appropriateness of allocated work environments. The Internet of Things could produce new data sets in the office at a resolution, speed and validity of which that they could be factored into desk-allocation, distributing seats based on appropriate noise levels, stay length, equipment requirements, previous presence and proximity to others working on the same project, among many others.Design/methodology/approachThe study utilises primary data from a commercial office environment in Central London (numerical building system data and semi-structured interviews) to feed a discrete events simulator. To test the hypothesis, the authors look at the potential for intelligent hot-desking to use “work type” data to improve the distribution of individuals in the office, increasing productivity through the creation of positive “work type environments” – where those working on specific tasks perform better when grouped with others doing the same task. The simulation runs for a typical work day, and the authors compare the intelligent hot-desking arrangement to a base case.FindingsThe study shows that sensor data can be used for desk allocation in a hot-desking environment utilising activity-based working, with results that outweigh the costs of occupancy detection. The authors are not only able to optimise desk utilisation based on quality occupancy data but also demonstrate how overall productivity increases as individuals are allocated desks of their preference as much as possible among other enabling optimisations that can be applied. Moreover, the authors explore how an increase in occupancy data collection in the private sector could have key advantages for the business as an organization and the city as a whole.Research limitations/implicationsThe research explores only one possible incarnation of intelligent hot-desking, and the authors presume that all data have already been collected, and while not insurmountable, they do not discuss the technical or cultural difficulties to this end. Furthermore, final examination of the productivity benefit – because of the difficulty in defining and measuring the concept – is exploratory rather than definitive. This research suggests that not only human-centric smart building research should be prioritised over energy or space-based themes but also large-scale private sector collection of occupancy data may be imminent, and its potential should be examined.Practical implicationsFindings strongly suggest that the hot-desking may cost more in lost productivity than it gains in reduced rental costs and as such many commercial offices should revaluate the transition, particularly with a view to facilitate intelligent hot-desking. Companies should begin to think strategically about the wider benefits of collecting occupancy data across their real estate portfolio, rather than reviewing use cases in silos. Finally, cities should consider scenarios of widespread collection of occupancy data in the private sector, examining the value these data have to city systems such as transport, and how the city might procure it for these ends.Social implicationsThis paper raises positive and negative social concerns. The value in occupancy data suggested herein, bringing with it the implication it should be collected en mass, has a noted concern that this brings privacy concerns. As such, policy and regulation should heed that current standards should be reviewed to ensure they are sufficient to protect those in offices from being unfairly discriminated, spied or exploited through occupancy data. However, the improved use of occupancy data improving workplaces could indeed make them more enjoyable places to work, and have the potential to become a staple in company’s corporate social responsibility policies.Originality/valueThis paper fulfils an identified need for better understanding the specific uses of occupancy data in the smart building mantra. Several sources suggest the current research focus on energy and rental costs is misguided when the holistic cost of an office is considered, and concepts related to staff – although less understood – may have an order of magnitude bigger impact. This research supports this hypothesis through the example of intelligent hot-desking. The value of this paper lies in redirecting industry and research towards the considering occupancy data in smart building uses cases including – but not limited to– intelligent hot-desking.

How wrong were we? Dependent interviewing, self-reports and measurement error in occupational mobility in panel surveys

Occupation is a central concept in sociology and economics and individual change in occupation is of major importance to literatures on wage determination, human capital, careers and social mobility. The collection of occupational data in surveys, particularly panel surveys, is challenging due to measurement error, and observed rates of occupational mobility are argued to be overestimated. We use a methodological discontinuity in the collection of occupational data from independent interviewing (respondents are asked to describe their occupation each year) to dependent interviewing (respondents are shown their previous response and only asked to describe their occupation if this has changed) and information on self-reported occupational changes in two panel surveys to estimate the degree of error in occupational mobility in panel data. We also test whether observed patterns differ by the level of aggregation of occupational classifications and examine the external validity of different measures of occupational mobility through their predicted impacts on selected labour market outcomes. Results indicate that occupational mobility is dramatically lower under dependent than independent interviewing (particularly for highly disaggregated occupational classifications) and that there is an evident mismatch between respondents’ self-reports of occupational switches and mobility measures inferred from changes in occupational codes. The impacts of occupational changes on earnings and job satisfaction are more consistent with theoretical predictions under dependent than independent interviewing and when occupational mobility is inferred from respondents’ self-reports. These findings have important implications for survey design, question the validity of existing studies on occupational change and call for further research.

Methods and feasibility of collecting occupational data for a large population-based cohort study in the United States: the reasons for geographic and racial differences in stroke study

BackgroundCoronary heart disease and stroke are major contributors to preventable mortality. Evidence links work conditions to these diseases; however, occupational data are perceived to be difficult to collect for large population-based cohorts. We report methodological details and the feasibility of conducting an occupational ancillary study for a large U.S. prospective cohort being followed longitudinally for cardiovascular disease and stroke.MethodsCurrent and historical occupational information were collected from active participants of the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study. A survey was designed to gather quality occupational data among this national cohort of black and white men and women aged 45 years and older (enrolled 2003–2007). Trained staff conducted Computer-Assisted Telephone Interviews (CATI). After a brief pilot period, interviewers received additional training in the collection of narrative industry and occupation data before administering the survey to remaining cohort members. Trained coders used a computer-assisted coding system to assign U.S. Census codes for industry and occupation. All data were double coded; discrepant codes were independently resolved.ResultsOver a 2-year period, 17,648 participants provided consent and completed the occupational survey (87% response rate). A total of 20,427 jobs were assigned Census codes. Inter-rater reliability was 80% for industry and 74% for occupation. Less than 0.5% of the industry and occupation data were uncodable, compared with 12% during the pilot period. Concordance between the current and longest-held jobs was moderately high. The median time to collect employment status plus narrative and descriptive job information by CATI was 1.6 to 2.3 minutes per job. Median time to assign Census codes was 1.3 minutes per rater.ConclusionsThe feasibility of conducting high-quality occupational data collection and coding for a large heterogeneous population-based sample was demonstrated. We found that training for interview staff was important in ensuring that narrative responses for industry and occupation were adequately specified for coding. Estimates of survey administration time and coding from digital records provide an objective basis for planning future studies. The social and environmental conditions of work are important understudied risk factors that can be feasibly integrated into large population-based health studies.

Rapid ongoing decline of Baird's tapir in Cusuco National Park, Honduras

During the International Tapir Symposium 16-21 Oct 2011, the conservation of Baird's tapir (Tapirus bairdii) in Honduras received a boost with the signing of a memorandum of understanding between the Minister Director of the Honduran Institute of Conservation and Forestry (ICF) and the Tapir Specialist Group (TSG). Despite this agreement, accelerating levels of hunting and habitat loss continue to pose a threat to Baird's tapir in Honduras. An ongoing study in Cusuco National Park in northwestern Honduras has been monitoring changes in population dynamics of Baird's tapir since 2006 through the collection of occupancy data. The study has identified an increase in hunting pressure, coinciding with a drastic decline in the encounter rate with Baird's tapir spoor. Here, we examine the significance of a range of demographic variables on Baird's tapir occupancy in Cusuco National Park using the software PRESENCE, and simulate the effects of different management strategies on the future dynamics of the population using the stochastic simulation software VORTEX. The predictions of the theoretical population models are compared to observed changes in occupancy levels. We found that non-intervention resulted in the local extinction of Baird's tapir within a very short time frame, but that various intervention models enabled the population to recover to near carrying capacity. Occupancy and extinction probability were shown to respond markedly to the increase in hunting pressure; and occupancy models supported the future population predictions generated by VORTEX. Our study suggests that immediate intervention is required to reduce hunting pressure to near historical levels to prevent the imminent local extinction of the species.

Occupational Exposure in Lung Cancer Patients: Contribution of Remote Past Work

Occupational exposures have been recognized for a number of years as contributing to disease risk for certain cancers. Although disease risk may be attributed to personal behaviors, such as cigarette smoking, occupational exposure may enhance the risk. Obtaining occupational histories is therefore important to the study of the etiology of cancer. However, the availability of occupational information in the medical record and vital registries can be incomplete or of poor quality and is often restricted to current, most recent, or usual occupation. This article reports the contribution of remote past work, data not ordinarily collected in the medical record, as an exposure source to potential lung carcinogens in a group of lung cancer patients. Twenty-six of the 114 lung cancer patients interviewed (23%) reported remote work consistent with past exposure to lung carcinogens. This occupational risk would have been undetected by usual history-taking methods and highlights the significant limitations of occupational data collection methods by vital registries.