Effects of dioxin exposure on reproductive and thyroid hormone levels and male sexual function in airbase military workers in Vietnam

Abstract: Dioxins are endocrine disruptors that may disturb male sexual and reproductive function. Studies on human populations are limited, and their results are controversial. This study evaluated the impact of dioxin exposure on reproductive and thyroid hormone levels and sexual function in men. A total of 140 men working in four military airbases (three bases were formerly contaminated with dioxin by the herbicide spraying campaign in the Vietnam War) were recruited to measure the serum dioxin levels. Four reproductive hormones (testosterone, follicle-stimulating hormone, luteinizing hormone (LH), and prolactin) and three thyroid hormones (free triiodothyronine (FT3), free thyroxin (FT4), and thyroid stimulating hormone) were measured. Male sexual function endpoints including sexual drive, erection, ejaculation, problems, and overall satisfaction were assessed by the Brief Male Sexual Function Inventory. The percentage of subjects with low testosterone and LH levels was 19.6% and 16.7%, respectively. Dioxins, especially 2,3,7,8-tetrachlorodibenzo-P-dioxin and toxic equivalent concentrations of polychlorinated dibenzo-p-dioxins/polychlorinated dibenzofurans, were inversely associated with testosterone and prolactin levels, but positively associated with FT3 and FT4, and showed adverse relationships with sexual function, such as sexual drive, problems, and overall satisfaction. Our results suggested that exposure to dioxin disrupts the homeostasis of reproductive and thyroid hormones leading to adverse effects on male sexual function.

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