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

Lisa Bauleo, Stefania Massari, Claudio Gariazzo, Paola Michelozzi, Luca Dei Bardi, Nicolas Zengarini, Sara Maio, Massimo Stafoggia, Marina Davoli, Giovanni Viegi, Alessandro Marinaccio and Giulia Cesaroni ()
Additional contact information
Lisa Bauleo: Department of Epidemiology–Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy
Stefania Massari: Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian National Institute for Insurance against Accidents at Work (INAIL), 00143 Rome, Italy
Claudio Gariazzo: Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian National Institute for Insurance against Accidents at Work (INAIL), 00143 Rome, Italy
Paola Michelozzi: Department of Epidemiology–Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy
Luca Dei Bardi: Department of Epidemiology–Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy
Nicolas Zengarini: Regional Public Health Observatory (SEPI), ASL TO3, 10095 Grugliasco, Italy
Sara Maio: Institute of Clinical Physiology, CNR, 56124 Pisa, Italy
Massimo Stafoggia: Department of Epidemiology–Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy
Marina Davoli: Department of Epidemiology–Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy
Giovanni Viegi: Institute of Clinical Physiology, CNR, 56124 Pisa, Italy
Alessandro Marinaccio: Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian National Institute for Insurance against Accidents at Work (INAIL), 00143 Rome, Italy
Giulia Cesaroni: Department of Epidemiology–Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy

IJERPH, 2023, vol. 20, issue 10, 1-16

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.

Keywords: mortality; occupational sector; cohort study; occupational risk factor; routinely collected health data; administrative data (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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