Raising the U.S. Army Height-Weight (Body Mass Index) Standards: Quantifying Metabolic Risk.

BACKGROUND & OBJECTIVES: The U.S. Army fell 25% short of its recruitment goal in 2022 and therefore, increasing the eligibility pool for potential recruits is of interest. Raising the body mass index (BMI) standards for eligibility presents a path to increase the recruitable population; however, there may be additional costs incurred due to attendant health risks that may be present in individuals with higher BMI. METHODS: We filtered the 2017-2020 National Health and Nutrition Examination Survey by age (17-25 years) and BMI (up to 30 kg/m2). A k-means cluster analysis was performed on the filtered dataset for the variables used to determine metabolic syndrome. Metabolic syndrome Clusters were characterized through summary statistics and compared over clinical measurements and questionnaire responses. RESULTS: Five distinct clusters were identified and mean BMI in two clusters (Clusters1 and 3) exceeded the current U.S. Army BMI thresholds. Of these two clusters, Cluster 1 members had metabolic syndrome. Cluster 3 members were at higher risk for metabolic syndrome compared to members of Clusters 2, 4, and 5. Mean waist circumference was slightly lower in Cluster 3 compared to Cluster 1. None of the clusters had significant differences in depression scores, poverty index, or frequency of dental visits. CONCLUSIONS: Potential recruits from Cluster 1 have excessive health risk and may incur substantial cost to the U.S. Army if enlisted. However, potential recruits from Cluster 3 appear to add little risk and offer an opportunity to increase the pool for recruiting.

Quantum Dot-Doped Electrospun Polymer Fibers for Explosive Vapor Sensors.

This research seeks to support reconnaissance efforts against homemade explosives (HMEs) and improvised explosive devices (IEDs), which are leading causes of combat casualties in recent conflicts. The successful deployment of a passive sensor to be developed for first responders and military must take expense, training requirements, and physical burden all into consideration. By harnessing the size-dependent luminescence of quantum dots (QDs) being electrospun into polymer fibers, the authors of this work hope to progress toward the development of lightweight, multivariable, inexpensive, easy to use and interpret, field-applicable sensors capable of detecting explosive vapors. The data demonstrate that poly(methyl methacrylate) (PMMA), polystyrene (PS), and polyvinyl chloride (PVC) fibers doped with Fort Orange cadmium selenide (CdSe) QDs, Birch Yellow CdSe QDs, or carbon (C) QDs will quench in the presence of explosive vapors (DNT, TNT, TATP, and RDX). In all cases, the fluorescent signal of the doped fiber continuously quenched upon sustained exposure to the headspace vapors. The simple method for the integration of QDs into the fibers' structure combined with their straightforward visual response, reusability, and durability all present characteristics desired for a field-operable and multimodal sensor with the ability to detect explosive threats.