Female anthropometric variability and their effects on predicted thermoregulatory responses to work in the heat

The use of thermoregulatory models for assessing physiological responses of workers in thermally stressful situations has been increasing because of the risks and costs related to human studies. In a previous study (Yokota et al. Eur J Appl Physiol 104:297–302, 2008), the effects of anthropometric variability on predicted physiological responses to heat stress in U.S. Army male soldiers were evaluated. Five somatotypes were identified in U.S. Army male multivariate anthropometric distribution. The simulated heat responses, using a thermoregulatory model, were different between somatotypes. The present study further extends this line of research to female soldiers. Anthropometric somatotypes were identified using multivariate analysis height, weight, percent body fat (%BF)] and the predicted physiological responses to simulated exercise and heat stress using a thermoregulatory model were evaluated. The simulated conditions included walking at ~3 mph (4.8 km/h) for 300 min and wearing battle dress uniform and body armor in a 30°C, 25% relative humidity (RH) environment without solar radiation. Five major somatotypes (tall-fat, tall-lean, average, short-lean, and short-fat), identified through multivariate analysis of anthropometric distributions, showed different tolerance levels to simulated heat stress: lean women were predicted to maintain their core temperatures (T_c) lower than short-fat or tall-fat women. The measured T_c of female subjects obtained from two heat studies (data1: 30°C, 32% RH, protective garments, ~225 w·m⁻² walk for 90 min; data2: 32°C, 75% RH, hot weather battle dress uniform, ~378 ± 32 w·m⁻² for 30 min walk/30 min rest cycles for 120 min) were utilized for validation. Validation results agreed with the findings in this study: fat subjects tended to have higher core temperatures than medium individuals (data2) and lean subjects maintained lower core temperatures than medium subjects (data1).