Suchergebnisse

Rates of amyotrophic lateral sclerosis (ALS) have been reported to be higher among US military veterans, who currently number more than 21 million, but the causal factor(s) has not been identified. We conducted a review to examine the weight of evidence for associations between military service, deployments, and exposures and ALS etiology and survival. Thirty articles or abstracts published through 2013 were reviewed. Although the current evidence suggests a positive association with ALS etiology, it is too limited to draw firm conclusions regarding associations between military service and ALS etiology or survival. Some evidence suggests that deployment to the 1990–1991 Persian Gulf War may be associated with ALS etiology, but there is currently no strong evidence that any particular military exposure is associated with ALS etiology. Future studies should address the limitations of previous ones, such as reliance on mortality as a surrogate for incidence, a dearth of survival analyses, lack of clinical data, low statistical power, and limited exposure assessment. The Genes and Environmental Exposures in Veterans with Amyotrophic Lateral Sclerosis (GENEVA) Study is one such study, but additional research is needed to determine whether military-related factors are associated with ALS and to assess potential prevention strategies.

Abstract

Background
Job-exposure matrices (JEMs) are often used for exposure assessment in occupational exposure and epidemiology studies. However, general population JEMs are difficult to find and access for workers in the United States of America.


Objective
We aimed to use publicly available information to develop a JEM-like exposure assessment method to determine exposure to a wide range of occupational agents in a wide range of occupations for US general population studies.


Methods
We used information from the US Department of Labor's Occupational Information Network database (O*NET) for 19,636 job tasks and 974 civilian occupations. We used automated keyword searches to identify 1,804 job tasks that involved exposure to 50 occupational agents. We had 2 reviewers determine whether each identified job task actually involved exposure to the 50 occupational agents. We had a third reviewer, a certified industrial hygienist, assess any job task and exposure for which the first 2 reviewers disagreed. For each U.S. Census 2010 occupation code, we used this information to derive 3 exposure variables for each occupational agent: ever exposure, number of job tasks of exposure, and frequency of exposure.


Results
Our keyword searches identified a median of 10 (interquartile range [IQR]: 43.75) job tasks for each occupational agent, and the maximum was 308. We determined job tasks actually involved exposure to 45 occupational agents, including solvents, air pollution, pesticides, radiation, metals, etc. We derived the 3 exposure variables for these 45 occupational agents for 516 U.S. Census 2010 occupation codes. The median percentage for ever exposure to individual occupational agents was 1.16% (IQR: 1.74%), and the maximum was 11.43%.


Conclusions
Our JEM-like exposure assessment method based on O*NET information can be used to determine exposure to a wide range of occupational agents in a wide range of occupations for the US general population.