Evidence map›Paper›PMID 37239502›Full record

ArticleInternational journal of environmental research and public health2023

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 and 3 more

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Lisa BauleoDepartment of Epidemiology-Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy.ORCID 0000-0002-2738-6180
Stefania MassariDepartment of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian National Institute for Insurance against Accidents at Work (INAIL), 00143 Rome, Italy.ORCID 0000-0001-6364-2471
Claudio GariazzoDepartment of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian National Institute for Insurance against Accidents at Work (INAIL), 00143 Rome, Italy.ORCID 0000-0003-2287-6364
Paola MichelozziDepartment of Epidemiology-Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy.
Luca Dei BardiDepartment of Epidemiology-Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy.
Nicolas ZengariniRegional Public Health Observatory (SEPI), ASL TO3, 10095 Grugliasco, Italy.
Sara MaioInstitute of Clinical Physiology, CNR, 56124 Pisa, Italy.
Massimo StafoggiaDepartment of Epidemiology-Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy.
Marina DavoliDepartment of Epidemiology-Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy.
Giovanni ViegiInstitute of Clinical Physiology, CNR, 56124 Pisa, Italy.ORCID 0000-0002-1855-4410
Alessandro MarinaccioDepartment of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian National Institute for Insurance against Accidents at Work (INAIL), 00143 Rome, Italy.ORCID 0000-0001-9068-2137
Giulia CesaroniDepartment of Epidemiology-Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy.ORCID 0000-0001-7361-9072
BIGEPI Collaborative Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Occupational DiseasesOccupational ExposureDeathEmploymentFemaleHumansMaleadministrative datacohort studymortalityoccupational risk factoroccupational sectorroutinely collected health data

Identifiers

PMID37239502
PMCPMC10218361

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.