Development and cross-validation of a circumference-based predictive equation to estimate body fat in an active population.

Objective: The U.S. Army uses sex-specific circumference-based prediction equations to estimate percent body fat (%BF) to evaluate adherence to body composition standards. The equations are periodically evaluated to ensure that they continue to accurately assess %BF in a diverse population. The objective of this study was to develop and validate alternative field expedient equations that may improve upon the current Army Regulation (AR) body fat (%BF) equations. Methods: Body size and composition were evaluated in a representatively sampled cohort of 1904 active-duty Soldiers (1261 Males, 643 Females), using dual-energy X-ray absorptiometry (%BFDXA), and circumferences obtained with 3D imaging and manual measurements. Sex stratified linear prediction equations for %BF were constructed using internal cross validation with %BFDXA as the criterion measure. Prediction equations were evaluated for accuracy and precision using root mean squared error, bias, and intraclass correlations. Equations were externally validated in a convenient sample of 1073 Soldiers. Results: Three new equations were developed using one to three circumference sites. The predictive values of waist, abdomen, hip circumference, weight and height were evaluated. Changing from a 3-site model to a 1-site model had minimal impact on measurements of model accuracy and performance. Male-specific equations demonstrated larger gains in accuracy, whereas female-specific equations resulted in minor improvements in accuracy compared to existing AR equations. Equations performed similarly in the second external validation cohort. Conclusions: The equations developed improved upon the current AR equation while demonstrating robust and consistent results within an external population. The 1-site waist circumference-based equation utilized the abdominal measurement, which aligns with associated obesity related health outcomes. This could be used to identify individuals at risk for negative health outcomes for earlier intervention.

Validation of a human thermoregulatory model during prolonged immersion in warm water.

This study validates the Six Cylinder Thermoregulatory Model (SCTM) during prolonged warm water immersion, which underpins the Probability of Survival Decision Aid (PSDA) currently in use by the United States Coast Guard (USCG). PSDA predicts survival time for hypothermia and dehydration. USCG has been using PSDA for search and rescue operation since 2010. In 2019, USCG organized a workshop to review PSDA performance and concluded that PSDA is an essential tool for operation, although it occasionally overestimates survival times in warm waters above 16 °C. Forty-six human subjects were immersed from the neck down in 18, 22, and 26 °C water for 45 min up to 10 h. Rectal temperature (Tcore), 10-site mean skin temperature (Tsk), and water loss were measured. At the end of immersion, Tcore ranged from 35.2 to 38.0 °C, and Tsk ranged from 19.7 to 27.4 °C. The SCTM-predicted Tcore, Tsk and water loss were compared to the measured values. Root mean squared deviation (RMSD) was used to test for acceptable predictions. Tcore RMSDs were 0.2, 0.14, and 0.3 °C in 18, 22, and 26 °C water respectively. Tsk RMSDs were 1.44, 0.76, and 1.1 °C in 18, 22, and 26 °C water respectively. SCTM underpredicted water loss by 84%. Overall, SCTM predicted Tcore and Tsk with acceptable accuracy in 18 and 22 °C water for up to 10 h, but overpredicted in 26 °C water. Future studies and algorithm development are required to improve water loss prediction as well as Tcore and Tsk prediction in 26 °C water.

The specific heat of the human body is lower than previously believed: The journal Temperature toolbox.

The specific heat capacity of the human body is an important value for heat balance analysis in thermoregulation and metabolism research. The widely used value of 3.47 kJ · kg-1· °C-1 was originally based on assumptions and was not measured or calculated. The purpose of this paper is to calculate the specific heat of the body, defined as the mass-weighted mean of the tissue specific heat. The masses of 24 body tissue types were derived from high-resolution magnetic resonance images of four virtual human models. The specific heat values of each tissue type were obtained from the published tissue thermal property databases. The specific heat of the entire body was calculated to be approximately 2.98 kJ · kg-1 · °C-1 and ranged from 2.44 to 3.39 kJ · kg-1 · °C-1 depending on whether min or max measured tissue values were used for the calculation. To our knowledge, this is the first time specific heat of the body has been calculated from the measured values of individual tissues. The contribution of the muscle to the specific heat of the body is approximately 47%, and the contribution of the fat and skin is approximately 24%. We believe this new information will improve the accuracy of calculations related to human heat balance in future studies of exercise, thermal stress, and related areas.

Finite element model of female thermoregulation with geometry based on medical images.

INTRODUCTION: this study describes the development of a female finite element thermoregulatory model (FETM) METHOD: the female body model was developed from medical image datasets of a median U.S. female and was constructed to be anatomically correct. The body model preserves the geometric shapes of 13 organs and tissues, including skin, muscles, fat, bones, heart, lungs, brain, bladder, intestines, stomach, kidneys, liver, and eyes. Heat balance within the body is described by the bio-heat transfer equation. Heat exchange at the skin surface includes conduction, convection, radiation, and sweat evaporation. Vasodilation, vasoconstriction, sweating, and shivering are controlled by afferent and efferent signals to and from the skin and hypothalamus. RESULTS: the model was validated with measured physiological data during exercise and rest in thermoneutral, hot, and cold conditions. Validations show the model predicted the core temperature (rectal and tympanic temperatures) and mean skin temperatures with acceptable accuracy (within 0.5 °C and 1.6 °C, respectively) CONCLUSION: this female FETM predicted high spatial resolution temperature distribution across the female body, which provides quantitative insights into human thermoregulatory responses in females to non-uniform and transient environmental exposure.

Three dimensional models of human thermoregulation: A review.

Numerous human thermoregulatory models have been developed and widely used in various applications such as aerospace, medicine, public health, and physiology research. This paper is a review of three dimensional (3D) models for human thermoregulation. This review begins with a short introduction of thermoregulatory model development followed by key principles for mathematical description of human thermoregulation systems. Different representations of 3D human bodies are discussed with respect to their detail and prediction capability. The human body was divided into fifteen layered cylinders in early 3D models (cylinder model). Recent 3D models have utilized medical image datasets to develop geometrically correct human models (realistic geometry model). The finite element method is mostly used to solve the governing equations and get numerical solutions. The realistic geometry models provide a high degree of anatomical realism and predict whole-body thermoregulatory responses at high resolution and at organ and tissue levels. Thus, 3D models extend to a wide range of applications where temperature distribution is critical, such as hypothermia/hyperthermia therapy and physiology research. The development of thermoregulatory models will continue with the growth in computational power, advancement in numerical methods and simulation software, advances in modern imaging techniques, and progress in the basic science of thermal physiology.

A geometrically accurate 3 dimensional model of human thermoregulation for transient cold and hot environments.

This paper outlines the development of a finite element human thermoregulatory model using an anatomically and geometrically correct human body model. The finite element body model was constructed from digital Phantoms and is anatomically realistic, including 13 organs and tissues: skin, muscles, fat, bones, heart, lungs, brain, bladder, intestines, stomach, kidneys, liver, and eyes. The model simulates thermal responses through a passive and active system. The passive system describes heat balance within the body and between the skin surface and environment. The active system describes thermoregulatory mechanisms, i.e., vasodilation, vasoconstriction, sweating, and shivering heat production. This model predicts temperature distribution across the body at high spatial resolution, and provides insight into human thermoregulatory responses to non-uniform and transient environments. Predicted temperatures (i.e., core, skin, muscle and fat) at 29 sites were compared with measured values in comfort, hot, and cold conditions. The comprehensive validation shows predictions are accurate and acceptable.