Associations among environmental exposures and physical and psychiatric symptoms in a care-seeking sample of U.S. military Veterans

Abstract: INTRODUCTION: Recent research and policy (e.g., the Sergeant First Class (SFC) Heath Robinson Honoring our Promise to Address Comprehensive Toxics (PACT) Act) have highlighted the potential health consequences of toxic environmental exposures. The purpose of the current study was to assess the self-reported prevalence of such exposures among a sample of U.S. military veterans seeking care at a Veterans Affairs facility and to examine associations between exposures and physical and psychiatric symptoms. MATERIALS AND METHODS: Participants were 4,647 newly enrolling post-9/11 veterans at the VA San Diego Healthcare System who completed standard clinical screening processes between January 2015 and April 2019. Electronic health screening data, including demographic information, military history, environmental exposures, and physical and psychiatric symptoms, were assessed. t-Tests for continuous variables and chi-square tests for categorical variables were used to compare exposed to unexposed veterans on demographic and military characteristics as well as physical and psychiatric symptoms. RESULTS: A total of 2,028 veterans (43.6%) reported exposure to environmental toxins during their military service. Analyses revealed a disproportionate burden of exposure on older, male, educated, combat veterans as well as Asian and Native American veterans. Exposure to any type of environmental toxin was associated with more physical symptoms, particularly pain, fatigue, and insomnia, as well as psychiatric symptoms, including moderate depressive symptomology, mild to moderate anxiety, and scores approaching the threshold for likely post-traumatic stress disorder and alcohol misuse. CONCLUSIONS: The high prevalence and detrimental health correlates of environmental exposures underscore the importance of implementing screening for exposures and providing healthcare services that address the multisystemic nature of exposure-related illness.

Read the full article
Report a problem with this article

Related articles

  • More for Researchers

    Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data

    Abstract: Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use and relapse-critical markers of risk and recovery from opioid use disorder (OUD). In this study, we used natural language processing (NLP) to automate the extraction of opioid relapses, and the timing of these occurrences, from veteran patients' electronic medical record. We then demonstrated the utility of our NLP tool via analysis of pre-/post-COVID-19 opioid relapse trends among veterans with OUD. For this demonstration, we analyzed data from 107,606 veterans OUD enrolled in Veterans Health Administration, comparing a pandemic-exposed cohort (n = 53,803; January 2019-March 2021) to a matched prepandemic cohort (n = 53,803; October 2017-December 2019). The recall of our NLP tool was 75% and our precision was 94%, demonstrating moderate sensitivity and excellent specificity. Using the NLP tool, we found that the odds of opioid relapse postpandemic onset were proportionally higher compared to prepandemic trends, despite patients having fewer mental health encounters from which to derive instances of relapse postpandemic onset. In this research application of the tool, and as hypothesized, we found that opioid relapse risk was elevated postpandemic. The application of NLP Methods: to identify and monitor relapse risk holds promise for future surveillance, risk prevention, and clinical outcome research.

    Mental Health Peer reviewed