Department of Epidemiology-Lazio Regional Health Service, ASL Roma 1, 00147 Rome, Italy.
Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian National Institute for Insurance against Accidents at Work (INAIL), 00143 Rome, Italy.
Int J Environ Res Public Health. 2023 May 9;20(10):5767. doi: 10.3390/ijerph20105767.
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.
行政数据在连接不同部门的信息方面非常宝贵。我们首次使用国家社会保险局（INPS）的数据，调查职业部门与非意外和意外死亡率之间的关联。我们从 1974 年至 2011 年为罗马 2011 年人口普查队列中的私营部门工人检索了职业部门信息。我们将职业部门分为 25 类，并将职业暴露分析为是否曾在一个部门工作或是否终身从事某个部门的工作。我们从人口普查参考日（2011 年 10 月 9 日）开始对研究对象进行随访，直至 2019 年 12 月 31 日。我们计算了每个职业部门的年龄标准化死亡率，分别在男性和女性中进行。我们使用 Cox 回归分析职业部门与死亡率之间的关联，得出风险比（HR）和 95%置信区间（95%CI）。我们分析了 910,559 名 30 岁及以上（53%为男性）的人群，随访时间为 700 万人年。在随访期间，非意外死亡和意外死亡分别为 59200 人和 2560 人。在年龄调整模型中，几个职业部门的男性死亡率风险较高：食品和烟草生产（HR=1.16，95%CI：1.09-8.22）、金属加工（HR=1.66，95%CI：1.21-11.8）、鞋类和木材（HR=1.19，95%CI：1.11-1.28）、建筑（HR=1.15，95%CI：1.12-1.18）、酒店、露营、酒吧和餐馆（HR=1.16，95%CI：1.11-1.21）和清洁（HR=1.42，95%CI：1.33-1.52）。在女性中，死亡率高于其他人群的部门是酒店、露营、酒吧和餐馆（HR=1.17，95%CI：1.10-1.25）和清洁服务（HR=1.23，95%CI：1.17-1.30）。金属加工和建筑部门的男性意外死亡率风险较高。社会保险局的数据有可能描述高风险部门，并确定人群中的易感群体。
