Department of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway.
Alberto Lleras Camargo School of Government, University of the Andes, Bogotá, Colombia.
Occup Environ Med. 2018 Mar;75(3):227-230. doi: 10.1136/oemed-2017-104349. Epub 2017 Oct 13.
This study aimed to quantify the extent to which health characteristics of workers are related to the potential risk of experiencing job displacement due to automation.
Linking the 2015 Norwegian Statistics on Income and Living Conditions survey (n=6393) with predicted probabilities of automation by occupation, we used Kruskal-Wallis tests and multivariate generalised linear models to assess the association between long-standing illnesses and risk of job automation.
Individuals with long-standing illnesses face substantially greater risks of losing their job due to automation. Whereas the average risk of job automation is 57% for men and 49% for women with long-standing illnesses, the risk is only 50% for men and 44% for women with limitations (p<0.001). Controlling for age, having a long-standing illness significantly increases the relative risk of facing job automation among men (risk ratio (RR) 1.13, 95% CI 1.09 to 1.19), as well as women (RR 1.11, 95% CI 1.05 to 1.17). While, among men, the association between long-standing illness and risk of job automation remains significant when controlling for education and income, it becomes insignificant among women.
Individuals with poor health are likely to carry the highest burden of technological change in terms of worsening employment prospects because of working in occupations disproportionally more likely to be automated. Although the extent of technology-related job displacement will depend on several factors, given the far-reaching negative consequences of job loss on health and well-being, this process represents a significant challenge for public health and social equity.
本研究旨在量化工人的健康特征与因自动化而面临失业风险的潜在风险之间的关系程度。
通过链接 2015 年挪威收入和生活条件调查（n=6393）与职业自动化的预测概率，我们使用 Kruskal-Wallis 检验和多变量广义线性模型来评估慢性病与自动化风险之间的关联。
患有慢性病的个体因自动化而失业的风险大大增加。虽然慢性病男性的平均自动化风险为 57%，女性为 49%，但慢性病限制男性的风险仅为 50%，女性为 44%（p<0.001）。控制年龄后，慢性病显著增加了男性（风险比（RR）1.13，95%置信区间（CI）1.09 至 1.19）和女性（RR 1.11，95%CI 1.05 至 1.17）面临自动化工作的相对风险。虽然在控制教育和收入后，慢性病与男性自动化风险之间的关联仍然显著，但在女性中这种关联变得不显著。
由于从事自动化程度较高的职业，健康状况不佳的个体在就业前景恶化方面可能承担着技术变革带来的最大负担。尽管与技术相关的工作流失程度将取决于几个因素，但鉴于失业对健康和福祉的深远负面影响，这一过程对公共卫生和社会公平构成了重大挑战。
