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Objectives. To investigate the association between layoff experience over 33 peak working years and subsequent premature death. Methods. This open cohort study involved data from 7234 working-age adults who took part in the US National Longitudinal Survey of Youth 1979. Cumulative layoff experience from the ages of 16 to 55 years was operationalized as the number of jobs ending in a layoff from 1979 to 2012. Mortality outcomes were assessed from 2012 to 2022, when the participants were younger than 65 years. Results. Layoff experience was associated with 18.71 (95% confidence interval [CI] = 1.09, 36.23; 1 layoff vs no layoffs) and 32.61 (95% CI = 2.66, 62.56; 2 or more layoffs vs no layoffs) excess deaths per 10 000 person-years. In a fully adjusted Cox proportional hazards model, experiencing 1 layoff and 2 or more layoffs (vs no layoffs) was associated with 1.23 (95% CI = 1.00, 1.51) and 1.30 times (95% CI = 0.96, 1.77) higher hazards of premature death from 2012 to 2022 (P trend = .02). The observed association did not statistically differ by timing of layoffs, sex/gender, or race/ethnicity. Conclusions. Layoffs may be an important determinant of mortality among US workers. (Am J Public Health. Published online ahead of print April 16, 2026:e1-e9. https://doi.org/10.2105/AJPH.2026.308432).
Layoffs may affect the health of those who lose their jobs as well as those who remain employed. Existing studies have found that remaining employed through layoffs is associated with poorer mental health in the short term, but the implications for long-term outcomes such as mortality remain unclear. We estimated adjusted HRs for all-cause and cause-specific mortality associated with layoff intensity while employed among white men, non-white men and women in a cohort of 9761 autoworkers who worked at one of three plants in Michigan between the years 1950 and 1980. We defined layoff intensity as the number of layoff months endured while employed divided by duration of employment. We identified layoff months as those in which the percentage of the workforce leaving employment was 1.96 SD above the predicted value from an autoregressive integrated moving average model. We found statistically significant associations among non-white men but not women or white men. Relative to layoff intensity below the first quartile, the adjusted HR associated with layoff intensity between the first and second quartiles was 1.35 (95% CI 1.05 to 1.74) for all-cause mortality among non-white men. The adjusted HRs associated with layoff intensity between the second and third quartiles were 1.85 (95% CI 1.08 to 3.17) and 2.41 (95% CI 1.00 to 5.84) for death due to all cancers and lung cancer, respectively. Layoffs endured while employed may lead to early mortality among non-white male employees. Reducing workforce instability may reduce racial disparities in health.
Economic downturns are typically associated with fewer traffic accidents due to reduced driving. However, the psychological and social shocks of sudden job loss may counterintuitively increase risk on the road. In this paper, we examine whether mass layoffs announcements are associated with short-term increases in traffic fatalities in the United States using spatial autoregressive models. Merging monthly U.S. county-level data on mass layoffs with motor vehicle fatality counts, we find a significant uptick in monthly traffic fatalities following major layoff events. This pattern persists after accounting for seasonal trends and regional factors, including unemployment rates and weather conditions. These findings suggest that the stress and disruption caused by mass layoffs can have deadly consequences beyond the workplace. We discuss psychological mechanisms (e.g., distress-related driving impairment) and implications linked to short-term rises in traffic fatalities and public health implications for fatal crash risk.
Aging population and rising unemployment risks have emerged as dual challenges for governments worldwide. Using China's 1990s state-owned enterprise layoffs as a natural experiment, we examine causal evidence on how adult children's unemployment affects older parents' health. We particularly analyze how urban-rural social security moderates these effects. Using data from the China Health and Nutrition Survey 1991-2006, we construct three health outcome dimensions for older parents: disease status, daily functional abilities (physical function and instrumental activities of daily living), and body mass index. Econometric analysis uses a two-way fixed effects model and a causal forest model. The layoffs of adult children significantly increased older parents' morbidity risk. Due to disparities in the social security system between urban and rural household registration (hukou), this effect primarily increased health risks-including higher probability of disease, increased risk of hypertension, limitations in daily activities, and underweight conditions-among rural-hukou older parents living in urban areas. In contrast, layoffs of adult children showed no measurable impact on urban-hukou older parents. Mechanistically, layoffs did not reduce daily care provided by children to their parents, but rather diminished household income. Moreover, layoffs of adult children reduced older parents' healthcare utilization and lowered their nutritional intake. Rural-hukou older parents living in urban areas were most affected, with reduced protein and fat consumption. The reduction in family resources caused by adult children's unemployment is detrimental to older parents' health. The social security system serves as a vital safety net for protecting the health of older populations. Strengthening social security is an essential policy complement to mitigate welfare losses in families affected by unemployment.
Layoffs can have lasting effects on the bodyweight trajectories of both genders. However, prior studies usually overlook the nuanced gender differences in health impacts. This study investigates the differential impact of layoffs from State-Owned Enterprises in China on body mass index (BMI) trajectories in men and women over a span of two decades. Our results indicate that being laid-off was associated with higher BMI at mid-age and accelerated BMI growth in women, contrasting with a slower BMI growth in men as they aged. The diverging trends were primarily driven by women and men who were back on the job market and re-employed. Women with post-layoff childcare responsibilities had the least healthy mid-life BMI, and a faster BMI growth compared to their job retainer counterparts. This study emphasizes the importance of considering gendered life course perspectives to understand the health impacts of job loss.
Drawing on protection motivation theory (PMT), this study investigates how employees respond cognitively and behaviorally to layoff threats in China's megacity Internet sector. Study 1 employed a cross-sectional survey of 423 employees from Beijing Internet firms, and Study 2 conducted a scenario-based experiment to strengthen causal inference. Structural equation modeling and path analysis were conducted to test a mediation model linking threat and coping appraisals to extra-role behavior (ERB) via protection motivation. Results show that perceived severity, vulnerability, response efficacy and self-efficacy jointly enhance protection motivation, which in turn promotes adaptive ERB. Perceived organizational support moderates this link, weakening the effect of protection motivation on ERB. These findings extend PMT from explaining defensive reactions to adaptive behaviors, highlighting how employees transform employment threats into proactive engagement. Practical implications emphasize fostering efficacy and balanced support to channel anxiety into constructive motivation.
This study examines the relation between political uncertainty arising from state-level election cycles and the timing of employee dismissal and plant closure notices filed by US firms under the Worker Adjustment and Retraining Notification (WARN) Act of 1988 (hereafter, WARN notices). We appeal to a real options framework to predict that firms delay layoff decisions and the issuance of WARN notices until the resolution of political uncertainty. Using establishment-level data on layoffs disclosed in WARN notices and state elections occurring between 1994 and 2022, we document that the likelihood of issuing WARN notices declines during the election quarter but increases in the subsequent quarter. Cross-sectional findings show that political uncertainty plays a significant role in the timing of WARN notices during election periods while other factors, including partisanship, economic conditions, union strength, and firm visibility, may also play a role. Further, firms that delay WARN notices do not experience a significant deterioration in their medium-term financial performance. Overall, our findings provide evidence that firms delay labor adjustment decisions and the announcements of such decisions in response to political uncertainty.
Whether vaccination refusal is perceived as a social norm violation that affects layoff decisions has not been tested. Also unknown is whether ascribed low-status groups are subject to double standards when they violate norms, experiencing stronger sanctions in layoff preferences and expectations, and whether work performance attenuates such sanctioning. Therefore, we study layoff preferences and expectations using a discrete choice experiment within a large representative online survey in Germany (N = 12,136). Respondents chose between two employee profiles, each with information about ascribed characteristics signaling different status groups (gender, age, and ethnicity), work performance (work quality and quantity, and social skills), and whether the employees refused to vaccinate against COVID-19. We found that employees who refused vaccination were more likely to be preferred and expected to be laid off. Respondents also expected double standards regarding layoffs due to vaccination refusal, hence, harsher treatment of females and older employees. Nonetheless, their preferences did not reflect such double standards. We found little support that high work performance attenuates these sanctions and double standards, opening questions about the conditions under which social biases arise. Our results suggest detrimental consequences of vaccination refusal for individuals, the labor market, and acceptance of health policies.
This study examines the long-term health impacts of massive layoffs from State-Owned Enterprises (SOEs) in transitional China, a period characterized by significant economic, cultural, and policy transformation. Utilizing the China Health and Nutrition Survey data from 1989 to 2014, we employ a life course framework to analyze how macro and interpersonal contexts influence mortality and physical health following job loss. Our analysis reveals that, despite short-term income disruptions and persistent income volatility, laid-off workers restored income and gained improved access to various types of health insurance over two decades. In the medium term, we observed increased mortality and cardiovascular diseases, which subsided after a decade. Notably, hypertension emerged as an outcome only after a decade of job loss. While the expansion of urban health insurance schemes contributed to reducing long-term mortality risks, the impact on other health outcomes was marginal. Contrary to patterns observed in Western developed countries, economic mechanisms in transitional China overall played only a minor role in the adverse effects on physical health outcomes. These findings highlight the importance of considering the temporal dynamics and the heterogeneity of impacts across evolving socio-cultural and policy contexts. We also discuss the social-psychological mechanisms that operate within the rich context of transitional China over several decades.
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This JAMA Forum discusses the scope of cuts made by the Trump administration to the federal workforce, the personal damage to workers, and the future of government service.
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The recent staff layoffs and defunding of the United States' National Institute of Occupational Safety and Health's Hearing Loss Prevention Program are perceived by many occupational hearing loss professionals and stakeholders as an unsettling setback. This Commentary explains how and why ending this federal governmental program's research agenda-even if it is temporary-should not stop progress by the private sector toward secondary prevention of noise-induced hearing loss by leveraging the overabundance of under-utilized raw audiometric data already collected for compliance purposes. The resources needed to accomplish this objective include metrics and statistical methods that transform raw audiometric data into risk-based population analytics, optimization of program delivery, and selective prioritization of cost-effective technology and basic research. Integrating population-based audiometric database analysis into routine business practice will give employers the valuable business intelligence they need to continuously measure the actual effectiveness of and return on investment from their hearing conservation programs. Private sector stakeholders who stand the most to benefit-employers, insurers, and suppliers-can pragmatically implement this solution framework to more efficiently manage noise-related worker health risk for relatively little additional cost compared to what employers already pay to conduct audiometric testing and basic compliance reporting. Government agencies' otherwise traditionally reactive enforcement role can concomitantly evolve into a proactive, risk-reducing resource that enhances their role in regulation and technical support.