The Association of Alcohol Consumption Patterns with Self-related Physical Health and Psychiatric Distress among Afghan and Iraq Era US Veterans
Abstract: Alcohol misuse is associated with negative mental and physical health outcomes, which presents a public health concern in veterans. However, less is known regarding outcomes among veterans with low to moderate alcohol consumption. This study included veterans with military service in Iraq and/or Afghanistan (N = 1083) who resided in the VA Mid-Atlantic region catchment area (North Carolina, Virginia, and parts of West Virginia). Participants completed a mailed survey that inquired about demographics, past-year alcohol consumption, self-rated physical health, and psychiatric symptoms. Logistic regression was used to evaluate associations between alcohol consumption and posttraumatic stress disorder (PTSD), depression, and self-rated physical health. In both bivariate results and adjusted models, non-drinkers and hazardous drinkers were more likely to endorse clinically significant PTSD and depression symptoms than moderate drinkers. Moderate drinkers were also less likely to report fair/poor health, after adjusting for demographics and psychiatric symptoms. Results overall showed a U-shaped curve, such that moderate alcohol use was associated with lower rates of mental health problems and fair/poor health. While the VA routinely screens for alcohol misuse, current results suggest that non-drinkers are also at risk for poor mental and physical health.
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.