Quantifying Classification Exposure Dose From the Pilot Veteran Military Occupational and Environmental Assessment Tool.

INTRODUCTION: Military personnel and Veterans are frequently exposed to complex environmental hazards; however, quantifying these exposures remains a challenge because of the limited availability of objective data and the reliance on subjective reporting. This study introduces the Classification Exposure Dose (Class-ED) framework, a novel method for estimating exposure dose using self-reported data on duration, frequency, and route of exposure. MATERIALS AND METHODS: Class-ED scores were calculated across 3 domains-fuel-related (FUEL), air quality (AQ), and radiation (RADI)-and analyzed in relation to neurobehavioral symptoms and the subdomains of cognitive, affective, somatosensory, and vestibular, along with neurological quality of life in a sample of 52 post-deployed, treatment-seeking Veterans. RESULTS: Generalized linear models revealed Class-ED FUEL exposure was the most consistent environmental predictor of neurological symptom burden, showing significant associations with global neurobehavioral symptoms, and subdomains of cognitive, affective, and vestibular symptoms. Class-ED RADI was significantly associated with subdomains of cognitive symptoms. Class-ED AQ was not significantly associated with most neurobehavioral symptom domains. For quality of life, only Class-ED FUEL showed a marginal negative trend. Additionally, depression emerged as a strong, consistent predictor across all neurobehavioral symptoms and neurological quality of life. CONCLUSIONS: This analysis demonstrates the utility of the Class-ED approach for quantifying aggregate, self-reported military environmental exposures and linking them to neurobehavioral symptom patterns, offering a scalable framework for future research and veteran care integration.