Associations Between Poorer Mental Health with Work-Related Effort, Reward, and Overcommitment Among a Sample of Formal US Solid Waste Workers During the COVID-19 Pandemic

Details

• Personal Author:
  Le AB ; Neitzel RL ; Shkembi A
• Description:
  Background: Effort-reward imbalance (ERI) and overcommitment at work have been associated poorer mental health. However, nonlinear and nonadditive effects have not been investigated previously. Methods: The association between effort, reward, and overcommitment with odds of poorer mental health was examined among a sample of 68 formal United States waste workers (87% male). Traditional, logistic regression and Bayesian Kernel machine regression (BKMR) modeling was conducted. Models controlled for age, education level, race, gender, union status, and physical health status. Results: The traditional, logistic regression found only overcommitment was significantly associated with poorer mental health (IQR increase: OR = 6.7; 95% CI: 1.7 to 25.5) when controlling for effort and reward (or ERI alone). Results from the BKMR showed that a simultaneous IQR increase in higher effort, lower reward, and higher overcommitment was associated with 6.6 (95% CI: 1.7 to 33.4) times significantly higher odds of poorer mental health. An IQR increase in overcommitment was associated with 5.6 (95% CI: 1.6 to 24.9) times significantly higher odds of poorer mental health when controlling for effort and reward. Higher effort and lower reward at work may not always be associated with poorer mental health but rather they may have an inverse, U-shaped relationship with mental health. No interaction between effort, reward, or overcommitment was observed. Conclusion: When taking into the consideration the relationship between effort, reward, and overcommitment, overcommitment may be most indicative of poorer mental health. Organizations should assess their workers' perceptions of overcommitment to target potential areas of improvement to enhance mental health outcomes. [Description provided by NIOSH]
• Subjects:
  Communicable Diseases Mental Health Nervous System Occupational Health Safety
• Keywords:
  Author Keywords: Bayesian Kernel Machine Regression BKMR COVID-19 Effort-reward Imbalance Employee Satisfaction Mental Health Psychosocial Factors Solid Waste Industry Waste Disposal Waste Workers
• ISSN:
  2093-7911
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Michigan ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  93-99
• Volume:
  14
• Issue:
  1
• NIOSHTIC Number:
  nn:20067736
• Citation:
  Saf Health Work 2023 Mar; 14(1):93-99
• Contact Point Address:
  Aurora B. Le, Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
• Email:
  aurorale@umich.edu
• Federal Fiscal Year:
  2023
• Performing Organization:
  University of Michigan, Ann Arbor
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Safety and Health at Work
• End Date:
  20280630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:60b4610a85078c778048c868024776db3bfbab7bc96f4bca345069194e5a58862cc034f6ffb67fbb226d30bee0006db3a303b026d709c0767106e2f629aea174
• Download URL:
  https://stacks.cdc.gov/view/cdc/229998/cdc_229998_DS1.pdf
• File Type:
  [PDF - 612.20 KB ]