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Impact of 9/11-related chronic conditions and PTSD comorbidity on early retirement and job loss among World Trade Center disaster rescue and recovery workers.
- Source :
-
American journal of industrial medicine [Am J Ind Med] 2016 Sep; Vol. 59 (9), pp. 731-41. - Publication Year :
- 2016
-
Abstract
- Background: The economic impact of the 9/11 terrorist attacks has rarely been studied. We examined the association between 9/11-related chronic health conditions with or without post-traumatic stress disorder (PTSD) and one important aspect of the economic impact, retirement, and job loss before age 60.<br />Methods: A total of 7,662 workers who participated in the World Trade Center Health Registry surveys were studied. Logistic regression models examined the association of 9/11-related health and labor force exit.<br />Results: Workers with chronic conditions were more likely to experience early retirement and job loss, and the association was stronger in the presence of PTSD comorbidity: the odds ratios for reporting early retirement or job loss were increased considerably when chronic conditions were comorbid with PTSD.<br />Conclusions: Disaster-related health burden directly impacts premature labor force exit and income. Future evaluation of disaster outcome should include its long-term impact on labor force. Am. J. Ind. Med. 59:731-741, 2016. © 2016 Wiley Periodicals, Inc.<br /> (© 2016 Wiley Periodicals, Inc.)
- Subjects :
- Adult
Commerce statistics & numerical data
Comorbidity
Construction Industry statistics & numerical data
Educational Status
Environmental Restoration and Remediation statistics & numerical data
Female
Health Care Sector statistics & numerical data
Health Status
Humans
Income
Male
Marital Status
Middle Aged
Registries
Rescue Work statistics & numerical data
September 11 Terrorist Attacks
Surveys and Questionnaires
Chronic Disease epidemiology
Occupational Diseases epidemiology
Occupational Exposure
Retirement statistics & numerical data
Stress Disorders, Post-Traumatic epidemiology
Unemployment statistics & numerical data
Subjects
Details
- Language :
- English
- ISSN :
- 1097-0274
- Volume :
- 59
- Issue :
- 9
- Database :
- MEDLINE
- Journal :
- American journal of industrial medicine
- Publication Type :
- Academic Journal
- Accession number :
- 27582475
- Full Text :
- https://doi.org/10.1002/ajim.22640