Using the COVID-19 Job Exposure Matrix for Essential Workplace Preparedness

Vitamin D status and COVID-19 prevention in a worker subgroup in Italy

BACKGROUND

Low levels of vitamin D are widespread in the world's population and associated with sun exposure, genetics, and lifestyles. Office workers in different occupational sectors seem more vulnerable than others. Scientific evidence reports a contribution of vitamin D in resistance to infections, opening to supplementation as a preventive action against pathogens, including SARS-CoV-2.

OBJECTIVE

A pilot campaign in the workplace during the coronavirus 2019 (COVID-19) pandemic was conducted based on the preliminary measurement of vitamin D amount and its integration.

METHODS

A preventive action to contrast the deficiency of vitamin D was offered to a population of 700 bank employees. Vitamin D supplementation was performed between April and June 2021, on workers (n = 139) and showed 25(OH)D serum levels ≤ 30 ng/ml. Demographic, anthropometric and lifestyle information were collected by survey and changes in the serum 25(OH)D amounts were monitored.

RESULTS

The adherence of the target population to the prevention campaign was 21%. 75% of the enrolled workers had low levels of vitamin D. After the intervention, serum vitamin D levels increased (1.28-fold;p = 0.0001) and 80% of the subjects reported optimal values > 30 ng/ml. Only 2.9% reported slight flu-like symptoms, but only 0.7% was confirmed as COVID-19, with respect to a ten-fold higher incidence in the general population.

CONCLUSIONS

Vitamin D supplementation can be achieved by simple and noninvasive approaches and can bring along further insights into health literacy on diet and lifestyles, representing an opportunity to protect the population by the widespread state of vitamin deficiency.

Validation of a COVID-19 Job Exposure Matrix (COVID-19-JEM) for Occupational Risk of a SARS-CoV-2 Infection at Work: Using Data of Dutch Workers

OBJECTIVES

A COVID-19 Job Exposure Matrix (COVID-19-JEM) has been developed, consisting of four dimensions on transmission, two on mitigation measures, and two on precarious work. This study aims to validate the COVID-19-JEM by (i) comparing risk scores assigned by the COVID-19-JEM with self-reported data, and (ii) estimating the associations between the COVID-19-JEM risk scores and self-reported COVID-19.

METHODS

Data from measurements 2 (July 2020, n = 7690) and 4 (March 2021, n = 6794) of the Netherlands Working Conditions Survey-COVID-19 (NWCS-COVID-19) cohort study were used. Responses to questions related to the transmission risks and mitigation measures of Measurement 2 were used to calculate self-reported risk scores. These scores were compared with the COVID-19-JEM attributed risk scores, by assessing the percentage agreement and weighted kappa (κ). Based on Measurement 4, logistic regression analyses were conducted to estimate the associations between all COVID-19-JEM risk scores and self-reported COVID-19 (infection in general and infected at work).

RESULTS

The agreement between the COVID-19-JEM and questionnaire-based risk scores was good (κ ≥ 0.70) for most dimensions, except work location (κ = 0.56), and face covering (κ = 0.41). Apart from the precarious work dimensions, higher COVID-19-JEM assigned risk scores had higher odds ratios (ORs; ranging between 1.28 and 1.80) on having had COVID-19. Associations were stronger when the infection were thought to have happened at work (ORs between 2.33 and 11.62).

CONCLUSIONS

Generally, the COVID-19-JEM showed a good agreement with self-reported infection risks and infection rates at work. The next step is to validate the COVID-19-JEM with objective data in the Netherlands and beyond.

Mat-O-Covid: Validation of a SARS-CoV-2 Job Exposure Matrix (JEM) Using Data from a National Compensation System for Occupational COVID-19

Background. We aimed to assess the validity of the Mat-O-Covid Job Exposure Matrix (JEM) on SARS-CoV-2 using compensation data from the French National Health Insurance compensation system for occupational-related COVID-19. Methods. Deidentified compensation data for occupational COVID-19 in France were obtained between August 2020 and August 2021. The case acceptance was considered as the reference. Mat-O-Covid is an expert-based French JEM on workplace exposure to SARS-CoV-2. Bi- and multivariable models were used to study the association between the exposure assessed by Mat-O-Covid and the reference, as well as the area under the curve (AUC), sensitivity, specificity, predictive values, and likelihood ratios. Results. In the 1140 cases included, there was a close association between the Mat-O-Covid index and the reference (p < 0.0001). The overall predictivity was good, with an AUC of 0.78 and an optimal threshold at 13 per thousand. Using Youden’s J statistic resulted in 0.67 sensitivity and 0.87 specificity. Both positive and negative likelihood ratios were significant: 4.9 [2.4−6.4] and 0.4 [0.3−0.4], respectively. Discussion. It was possible to assess Mat-O-Covid’s validity using data from the national compensation system for occupational COVID-19. Though further studies are needed, Mat-O-Covid exposure assessment appears to be accurate enough to be used in research.

Job-Exposure Matrix: A Useful Tool for Incorporating Workplace Exposure Data Into Population Health Research and Practice

Workplace exposures to physical, chemical, and psychosocial factors account for a large burden of chronic diseases. Obtaining useful estimates of current and past workplace exposures is challenging, particularly in large general population studies. Job-exposure matrices (JEMs) are a useful tool for exposure assessment, particularly when no individual level exposure data are available. A JEM provides a cross-tabulation of job titles (sometimes combined with industry) and estimated exposures to workers carrying out these jobs during different time periods. The major limitation of JEMs is that they do not account for individual variation in exposures within the same job. This limitation is offset by the advantages of low cost, wide applicability, lack of bias from self-reporting, and the ability to estimate exposures based on job titles when no other exposure data exist. There is growing use of JEMs in research examining the role of workplace exposures in the development of chronic diseases, and interest in their application to public health practice. This paper provides a scoping review of JEM use, some examples of JEMs, and brief guidance for the application of JEMs in epidemiological research. In conclusion, JEMs provide a useful tool for researchers and public health practitioners to estimate occupational exposures in large scale epidemiological studies relevant to many health conditions.