Assessment of Anthropometric Trends and the Effects on Thermal Regulatory Models: Females Versus Males

Abstract

The purpose of this study is to investigate secular change in body dimensions (height, weight, %body fat (%BF)) in U.S. Army female soldiers, by comparing the 2004 and 1988 databases. Identified anthropometric somatotypes were subsequently incorporated in a thermal regulatory model to examine simulated individual differences in core temperature (Tcr) to heat stress (rest for 30 min and walk @ 3mph with 12 kg load in 35 C/50%rh environment for 70 min). The results were also compared to those from the male study. The univariate results indicated that the secular trend, greater increases in weight (3.1kg) and %BF (1.8%) (p < 0.05, after Bonferroni correction) than men were observed in the 2004 database. Multivariate results demonstrated that five primary somatotypes ("tall-fat," "tall-thin," "average," "short-thin," "short-fat") were identified. Despite the increase in "fatness," the secular trend of female body composition in multivariate dimensions and its effects on Tcr were not significantly different between the 1988 and 2004 databases. Anthropometric values in each somatotype differed by gender but surprisingly affected minimal gender differences in predicated Tcr to heat stress simulations..

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2007
Accession Number
ADA474531

Entities

People

  • Gaston P. Bathalon
  • Larry G. Berglund
  • Miyo Yokota

Organizations

  • United States Army Research Institute of Environmental Medicine

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Analysis Of Variance
  • Biomedical Research
  • Body Armor
  • Body Weight
  • Data Science
  • Databases
  • Department Of Defense
  • Environment
  • Factor Analysis
  • Information Science
  • Military Research
  • Multivariate Analysis
  • Observers
  • Stresses
  • Thermal Stresses
  • Two Dimensional

Readers

  • Exercise and Sports Science.
  • Regression Analysis.