Precarious Work, Job Stress, and Health-related Quality of Life

Quality of work is a central issue in understanding worker well-being [1]. Work is changing due to several factors including technology and demographics and so is the way work is organized and designed. These changes have led to non-standard work arrangements, like gig work, resulting in an increased prevalence of precarious work [2]. While there is no standardized definition of precarious work it can be broadly defined as uncertain, unstable and insecure work in which workers, as opposed to businesses or the government, bear the risks associated with work and receive limited social benefits and statutory protections [3-7]. A NIOSH study constructed a work precariousness scale to address the gap in precarious work research in the United States [8].

Background

Precarious work affects adverse health and well-being through three main pathways [9]. First, precarious work exposes workers to harmful and unsafe working conditions endangering their physical health. Second, precarious work may limit workers’ control over their professional and personal lives, leading to psychosocial stress. Finally, some of the most critical consequences of precarious work are social and economic deprivation, affecting overall well-being. Studies have documented the health, including mental health, consequences of some aspects of precarious work like job insecurity and temporariness [10-15]. Because there is no standard definition there is no unique way to measure precariousness, making it difficult to capture its characteristics and compare studies that assessed precarious work across countries [10, 16-18]. Some aspects of precarious work are captured by other quality-of-work constructs, for example, contingent work and non-standard work arrangements. The concepts of precarious work, contingent work, and work arrangements are not mutually exclusive; for example, some workers in standard work arrangements may experience unfair treatment, a characteristic of precarious work. However, research on non-standard work arrangements rarely addresses concerns regarding precarious work in the United States [19, 20].

Partially due to the lack of standardized definition, it is challenging to estimate the prevalence of precarious work. While efforts are underway to improve data collection, the majority of the available surveys fail to provide data that fully characterizes these concepts and their health and well-being consequences.

Carefully calibrated and disaggregated metrics are needed to better understand the determinants and effects of precarious work. Few precarious work constructs and models have been proposed, mainly in the European context. For example, Amable et al. and Lewchuk et al. considered precarious work as a multidimensional construct, defined across four dimensions of continuity (i.e., temporality), vulnerability (i.e., powerlessness), protection (i.e., limited fringe benefits), and income insufficiency (i.e., low level of earnings) [21, 22]. In another study, Benach et al. classified precarious work based on employment insecurity, individualized bargaining relations between workers and employers, low wages and economic deprivation, limited workplace rights and social protection, and powerlessness to exercise workplace rights [9].

The NIOSH Study

Based upon the employment Precariousness Scale (EPRES) developed by Amable et al. [21], the NIOSH study measured work precariousness among US workers for the first time [8]. Besides measuring precariousness, the study also contributes to understanding precarious work’s health consequences by assessing the individual relationships between

• precarious work and job stress,
• precarious work and unhealthy days (days in poor physical and mental health), and
• precarious work and days with reduced productive functioning (days with activity limitations).

The study used pooled cross-sectional data from the NIOSH‐sponsored Quality of Work-Life module of the General Social Survey (GSS‐QWL) for the years 2002 – 2018. The analyses show how work precariousness has changed over the years and how various work arrangements and industries differ in their share of precarious work. A total of twenty-two survey items were used to construct four different components of the precariousness scale

• temporariness,
• disempowerment,
• vulnerability, and
• wages.

Table 1: Components and variables of our precariousness scale.

Scores from these individual categories were combined to construct an overall precariousness score. Finally, associations of higher precarious scores with elevated job stress, increased unhealthy days, and

increased days of reduced productive functioning were identified. The analyses reported that the percentages of highly precarious work increased from 2002 (32.12%) to 2010 (35.37%) and then decreased in 2014 (30.96%). Precarious work was more common among

• workers in the age group of 25–34 years (39.4%),
• multi‐racial workers (52.3%),
• Black workers (46.0%), and
• Hispanic workers (44.8%).

The study also found that workers engaged in highly precarious work were 57% more likely to report experiencing job stress than those engaged in low precarious work.

From the associations between unhealthy days and work precariousness, the study found that individuals in highly precarious work reported more unhealthy days (0.4 days more within 30 days) than those not engaging in precarious work. From the associations between reduced productive functioning and work precariousness, the study found that individuals in highly precarious work reported experiencing a higher number of days of activity limitation (1.2 more days within 30 days period) than those in low precarious work.

Next Steps

Outcomes of this study provide support for the precariousness scale developed by NIOSH and the scale’s suitability for assessing the health‐related quality of life of workers in different work arrangements. This understanding can help us develop effective interventions to reduce the prevalence of precarious work. Ongoing assessment of the scale’s validity with other data sets capturing both similar and additional variables and components of the scale will allow for further development and exploration of the scale. Future research should examine the psychometric properties of the scale and apply it to other national‐level data to explore the robustness of the scale.

Anasua Bhattacharya, PhD, is an Economist in the Economic Research and Support Office of NIOSH.

Tapas Ray, PhD, is an Economist in the Economic Research and Support Office of NIOSH.

References

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