Effectiveness Of Workplace Health Promotion In Protecting Against COVID Risk

Introduction

The emergence of the COVID-19 pandemic has had health, social and psychological impacts on workers worldwide ^{(1, 2,3).} The Italian National Institute for Insurance against Labour Accidents (INAIL) has developed a classification system for companies ⁽⁴⁾ at high, medium and low Covid risk based on exposure probability, proximity index and aggregation factor.  Exposure measures the probability to be in contact with potential sources of infection during work activities (e.g., health sector, hazardous waste management, research laboratories). Proximity measures the intrinsic features of work activity that cannot guarantee an adequate social distancing (e.g., specific tasks such as in assembly lines) for part or for most of the working time. Aggregation measures work activities that may determine contacts with people other than workmates (e.g., restaurants, retail, entertainment, hospitality, education).

Educational activities have been classified as medium-low risk of transmitting Sars-CoV-2.

Every company had to implement a safety and prevention protocol against Covid-19 in the workplace. The document is based on the shared protocol of April 2020, as amended and supplemented on 6 April 2021, agreed by the employers’ associations and the trade unions for the regulation of measures to contrast and contain the spread of the Covid-19 virus in workplaces (5). In line with such enhanced measures, the University of L’Aquila established a COVID Committee composed of the Employer, the Health and Safety Officer, the Workers’ Health and Safety Representatives, and the occupational health physicians. Various countermeasures were implemented to mitigate the risk of spreading the virus, such as transitioning to virtual instruction, remote working, reduced capacity within the offices and the laboratories at any one time, social distancing, use of face masks, hygienic measures, access controls, contact tracing of possible contacts of confirmed cases of COVID, and monitoring of the mandatory quarantine requirements set forth by the health authority.

In relation to the University’s health promotion programme that has been in place for 5 years, this study aimed at investigating the relationship between the COVID-19 preventive measures and the occupational risk perception and the adoption of more protective health behaviours to mitigate the spread of SARS-COV-2.

Methods and materials

The University Health Care System managed health surveillance with proactive attitude serving as a reference point (also through a helpline) for the identification of persons at risk (contact-tracing), for the recommendation of molecular swab tests, for monitoring the mandatory quarantine and/or isolation requirements, for advising the arrangement of occupational health appointments before returning to work from sick leave, and for the management of vulnerable subjects through a remote work or remote education order.

The survey was conducted from July 2020 to January 2021, as part of the University’s worksite Health Promotion programme, called “Ateneo in salute” (i.e., good health and well-being in the University) that has been in place for five years. The voluntary based programme aims at raising awareness among workers on health promotion measures to prevent the risk of metabolic, cardiovascular diseases (Cuore project – Italian National Health Institute), and of other chronic conditions.

The programme involved the collection of data related to the medical history and lifestyle practices of the respondents, a medical examination along with health counselling and follow-up visits, free access to blood and urine tests to detect any metabolic and blood lipids diseases, electrocardiogram, and promotion of adherence to screening and vaccination campaigns. The collected data were added to a database that was subsequently complemented with the survey questionnaire on COVID-19 risk perception.

The survey used an online questionnaire (Microsoft Form) that was sent through email by the University Health Care System to all the univaq.it domain users.

The questionnaire was designed to collect data on specific medical conditions in relation to Covid-19: symptoms, any history of previous positive molecular nasopharyngeal test or antigen test, any mandatory quarantine or isolation measures. It assessed the pandemic-related risk perception with responses based on a 1-10 scale, with 10 being the highest perceived risk, the individual preventive measures such as hand hygiene, the use of PPE, and of social distancing behaviours. Moreover, the questionnaire aimed to assess the willingness to accept a COVID-19 vaccine if made available.

The merging of the database of Ateneo in Salute with the responses to the questionnaire has generated a complete dataset of 314 records concerning the university employees, including lecturers and technical/administrative staff (137 M and 177 F) divided by age group and role, as reported in Tables 1 and 2.

The statistical analysis examined the frequency measures, the measures of central tendency and the measures of association between the variables. The multivariate logistic regression model was used to determine the association between the variables. The significance associated to the measures was assessed using the Student’s t-test, the Chi-square test, the Fisher exact test, and the Wilcoxon test.

Based on the mean score (7.11±2.26) assigned to the perceived risk for COVID-19 infection, the sample was stratified in two groups: medium low score (1-7) vs high score (8-10). The discrete and nominal variables were expressed as absolute and percentage frequencies, and the difference between the two groups was assessed using the Chi-square test or the Fisher exact test, as appropriate. The continuous variables were reported as mean values to determine the standard deviation, the difference between the two groups was assessed using the independent samples t-test. Where statistical significance was reported, the variables were included into a multivariate logistic regression model to detect the independent factors associated to a higher COVID-19 risk perception. A backward-stepwise selection was performed determined by AIC (Akaike Information Criterion) to select the best multivariate model. The statistical analysis was carried out using STATA/IC statistical software package version 15.1. The chosen level of significance was <0.05.

Results and discussion

Among the 314 respondents, 31% reported undergoing a molecular/PCR test and 49% undergoing an antigen test (Table 3). These percentages are to be correlated to the intensive engagement interventions by the University Health Care System to spread awareness regarding the COVID risk factors among the university employees.

No workplace COVID-19 clusters were detected among the university employees.

Participants assessed their perceived COVID-19 infection risk on a scale from 1 to 10 (mean 7.11±2.26).

Average age is higher in the group that reported a greater perceived risk for COVID-19 (52.05±10.98 vs 46.73±11.26, p<0.001). The respondents who showed a high-risk perception also reported undergoing antibody tests (96.86% vs 90.97%, p=0.029) and implementing protective health behaviours and using PPE more frequently than the respondents who reported a medium-low perceived risk for COVID-19 infection (93.08% vs 83.87%, p=0.010). 

The perceived risk for COVID-19 infection increases with age (OR 1.04, IC 95% 1.02 – 1.06, p=0.001) and decreases where a family history of diabetes was reported (OR 0.53, IC 95% 0.28 – 0.99, p=0.049). The respondents who reported a higher perceived risk (8-10) have a personal medical history of cancer (8.23% vs 3.36%, p=0.069), hypertension (16.03% vs 9.40%, p=0.083), or were prescribed at least one drug for the treatment of a chronic condition (37.34% vs 29.53%, p=0.147). The respondents who had a lower perceived risk (1-7) reported a regular alcohol consumption (36.91% vs 26.75%, p=0.056). 

Thus, chronological age results to be a statistically significant factor associated with a higher perceived risk for COVID-19 infection and a greater health concern. Concern and implementation of protective behaviours increase with age. This association reflects the correlation spread by scientific studies and the mass media among the negative effects of the Sars-Cov-2 and age. ^(6,7,8).

Thus, age and cardiovascular and oncological conditions affect risk perception and the perceived health risks associated with worse prognosis ^(9). 

The correlation between alcohol consumption and the low-risk perception is interesting. We do not know whether alcohol has a calming effect that reduces risk perception or whether the consumption was related to an initial greater risk perception.

Among the participants in the study, the individual sensitive attitudes leading to greater adherence to prevention and awareness campaigns did not imply different perceived risks for Covid-19 infection. Instead, there is a statistically significant relationship between health promoting and Covid risk perception. In line with the requirements of Italian Legislative Decree No. 81/08, workplace health promotion is an effective tool for raising awareness about health in general and about the Sars Cov 2 risk. In order to assess the effectiveness of the health promotion measures, a comparison with other Italian universities would be useful.

References

1. WHO, 2020a. https://www.who.int/emergencies/diseases/novel-coronavirus-2019 .
2. L. Dietz, H.F. Patrick, C. David, F. Mark, J.A. Eisen, V.D.W. Kevin, 2019 novel coronavirus (COVID-19) pandemic: built environment considerations to reduce transmission, M. Systems. 5 (2020), e00245–20. https://doi.org/10.1128/mSystems.00245-20.
3. W. Tan, X. Zhao, X. Ma, A novel coronavirus genome identified in a cluster of pneumonia cases—Wuhan, China 2019–2020, China CDC Weekly 2 (2020) 61–62, https:// doi.org/10.46234/ccdcw2020.017.
4. Documento tecnico sulla possibile rimodulazione delle misure di contenimento del contagio da SARS-CoV-2 nei luoghi di lavoro e strategie di Prevenzione Aprile 2020 ISBN 978-88-7484-911-5; Sergio Iavicoli, Fabio Boccuni, Giuliana Buresti, Diana Gagliardi, Benedetta Persechino, Bruna Maria Rondinone, Antonio Valenti; www. Inail.it
5. Protocollo condiviso di aggiornamento delle misure per il contrasto e il contenimento della diffusione del virus SARS-CoV-2/COVID-19 negli ambienti di lavoro- Accordo sindacale
6. M. Cristina Polidori, Helmut Sies, Luigi Ferrucci, Thomas Benzing COVID-19 mortality as a fingerprint of biological age Ageing Research Reviews 67 2021 101308.
7. Abbatecola, A.M., Antonelli-Incalzi, R., 2020. COVID-19 spiraling of frailty in older italian patients. J. Nutr. Health Aging. https://doi.org/10.1007/s12603-020-1357- 1359.
8. Akbar A.N, Gilrov D W 2020 Aging immunity may esacerbate Covid 2019 Science 369 (6501) 256-257.
9. Yangyang Chen  , Jiahao Feng  , An Chen  , Jae Eun Lee  , Longtian .Risk perception of COVID-19: A comparative analysis of China and South Korea. International Journal of Disaster Risk Reduction 61 2021 (102373).