Institute for Work and Health, Toronto, Ontario, Canada
Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
J Epidemiol Community Health. 2024 Oct 9;78(11):675-681. doi: 10.1136/jech-2024-222373.
To examine the association between precarious employment and risk of work-related COVID-19 infection in Ontario, Canada.
We combined data from an administrative census of workers' compensation claims with corresponding labour force statistics to estimate rates of work-related COVID-19 infection between April 2020 and April 2022. Precarious employment was imputed using a job exposure matrix capturing temporary employment, low wages, irregular hours, involuntary part-time employment and a multidimensional indicator of 'low', 'medium', 'high' and 'very high' overall exposure to precarious employment. We used negative binomial regression models to quantify associations between precarious employment and accepted compensation claims for COVID-19.
We observed a monotonic association between precarious employment and work-related COVID-19 claims. Workers with 'very high' exposure to precarious employment presented a nearly fivefold claim risk in models controlling for age, sex and pandemic wave (rate ratio (RR): 4.90, 95% CI 4.07 to 5.89). Further controlling for occupational exposures (public facing work, working in close proximity to others, indoor work) somewhat attenuated observed associations. After accounting for these factors, workers with 'very high' exposure to precarious employment were still nearly four times as likely to file a successful claim for COVID-19 (RR: 3.78, 95% CI 3.28 to 4.36).
During the first 2 years of the pandemic, precariously employed workers were more likely to acquire a work-related COVID-19 infection resulting in a successful lost-time compensation claim. Strategies aiming to promote an equitable and sustained recovery from the pandemic should consider and address the notable risks associated with precarious employment.
在加拿大安大略省,研究不稳定就业与与工作相关的 COVID-19 感染风险之间的关联。
我们将工人赔偿索赔的行政普查数据与相应的劳动力统计数据相结合,以估算 2020 年 4 月至 2022 年 4 月期间与工作相关的 COVID-19 感染率。不稳定就业是通过一个捕捉临时就业、低工资、不规则工作时间、非自愿兼职和整体不稳定就业“低”、“中”、“高”和“非常高”的多维指标的工作暴露矩阵来推断的。我们使用负二项式回归模型来量化不稳定就业与 COVID-19 接受赔偿的索赔之间的关联。
我们观察到不稳定就业与与工作相关的 COVID-19 索赔之间存在单调关联。在控制年龄、性别和大流行波的模型中,暴露于“非常高”不稳定就业的工人的索赔风险几乎增加了五倍(比率比 (RR):4.90,95%置信区间 (CI):4.07 至 5.89)。进一步控制职业暴露(面向公众的工作、与他人密切接触、室内工作)略微减弱了观察到的关联。在考虑到这些因素后,暴露于“非常高”不稳定就业的工人仍有近四倍的可能性对 COVID-19 提出成功的索赔(RR:3.78,95%CI:3.28 至 4.36)。
在大流行的头 2 年期间,不稳定就业的工人更有可能感染与工作相关的 COVID-19,导致成功的丧失工作时间赔偿索赔。旨在促进从大流行中公平和持续复苏的战略应该考虑并解决与不稳定就业相关的显著风险。