Sector of Employment and Mortality: A Cohort Based on Different Administrative Archives

Author:

Bauleo Lisa1ORCID,Massari Stefania2ORCID,Gariazzo Claudio2ORCID,Michelozzi Paola1,Dei Bardi Luca13,Zengarini Nicolas4,Maio Sara5,Stafoggia Massimo1,Davoli Marina1,Viegi Giovanni5ORCID,Marinaccio Alessandro2ORCID,Cesaroni Giulia1ORCID

Affiliation:

1. Department of Epidemiology–Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy

2. Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian National Institute for Insurance against Accidents at Work (INAIL), 00143 Rome, Italy

3. Department of Statistical Sciences, Sapienza University of Rome, 00185 Rome, Italy

4. Regional Public Health Observatory (SEPI), ASL TO3, 10095 Grugliasco, Italy

5. Institute of Clinical Physiology, CNR, 56124 Pisa, Italy

Abstract

Administrative data can be precious in connecting information from different sectors. For the first time, we used data from the National Social Insurance Agency (INPS) to investigate the association between the occupational sectors and both non-accidental and accidental mortality. We retrieved information on occupational sectors from 1974 to 2011 for private sector workers included in the 2011 census cohort of Rome. We classified the occupational sectors into 25 categories and analyzed occupational exposure as ever/never have been employed in a sector or as the lifetime prevalent sector. We followed the subjects from the census reference day (9 October 2011) to 31 December 2019. We calculated age-standardized mortality rates for each occupational sector, separately in men and women. We used Cox regression to investigate the association between the occupational sectors and mortality, producing hazard ratios (HRs) and 95% confidence intervals (95%CI). We analyzed 910,559 30+-year-olds (53% males) followed for 7 million person-years. During the follow-up, 59,200 and 2560 died for non-accidental and accidental causes, respectively. Several occupational sectors showed high mortality risks in men in age-adjusted models: food and tobacco production with HR = 1.16 (95%CI: 1.09–8.22), metal processing (HR = 1.66, 95%CI: 1.21–11.8), footwear and wood (HR = 1.19, 95%CI: 1.11–1.28), construction (HR = 1.15, 95%CI: 1.12–1.18), hotels, camping, bars, and restaurants (HR = 1.16, 95%CI: 1.11–1.21) and cleaning (HR = 1.42, 95%CI: 1.33–1.52). In women, the sectors that showed higher mortality than the others were hotels, camping, bars, and restaurants (HR = 1.17, 95%CI: 1.10–1.25) and cleaning services (HR = 1.23, 95%CI: 1.17–1.30). Metal processing and construction sectors showed elevated accidental mortality risks in men. Social Insurance Agency data have the potential to characterize high-risk sectors and identify susceptible groups in the population.

Publisher

MDPI AG

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health

Reference25 articles.

1. (2023, March 13). International Labour Organization World Statistic. Available online: https://www.ilo.org/moscow/areas-of-work/occupational-safety-and-health/WCMS_249278/lang--en/index.htm.

2. WHO/ILO (2021). WHO/ILO Joint Estimate of the Work-Related Burden of Disease and Injury, 2000–2016: Global Monitoring Report.

3. Murray, C.J.L., and Lopez, A.D. (1996). World Health Organization, World Bank & Harvard School of Public Health, The Global Burden of Disease: A Comprehensive Assessment of Mortality and Disability from Diseases, Injuries, and Risk Factors in 1990 and Projected to 2020: Summary.

4. INAIL (2020). Relazione Annuale 2019, INAIL. Available online: https://www.inail.it/cs/internet/docs/alg-relazione-annuale-anno-2019.pdf.

5. Site-specific cancer mortality inequalities by employment and occupational groups: A cohort study among Belgian adults, 2001–2011;Vanthomme;BMJ Open,2017

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