Heat capacity (HC) has an important role in the temperature regulation process, particularly in dealing with the heat load. The actual measurement of the body HC is complicated and is generally estimated by body-composition-specific data. This study compared the previously known HC estimating equations and sought how to define HC using simple anthropometric indices such as weight and body surface area (BSA) in the Korean population. Six hundred participants were randomly selected from a pool of 902 healthy volunteers aged 20 to 70 years for the training set. The remaining 302 participants were used for the test set. Body composition analysis using multi-frequency bioelectrical impedance analysis was used to access body components including body fat, water, protein, and mineral mass. Four different HCs were calculated and compared using a weight-based HC (HC_Eq1), two HCs estimated from fat and fat-free mass (HC_Eq2 and HC_Eq3), and an HC calculated from fat, protein, water, and mineral mass (HC_Eq4). HC_Eq1 generally produced a larger HC than the other HC equations and had a poorer correlation with the other HC equations. HC equations using body composition data were well-correlated to each other. If HC estimated with HC_Eq4 was regarded as a standard, interestingly, the BSA and weight independently contributed to the variation of HC. The model composed of weight, BSA, and gender was able to predict more than a 99% variation of HC_Eq4. Validation analysis on the test set showed a very high satisfactory level of the predictive model. In conclusion, our results suggest that gender, BSA, and weight are the independent factors for calculating HC. For the first time, a predictive equation based on anthropometry data was developed and this equation could be useful for estimating HC in the general Korean population without body-composition measurement.

Although our previously developed anthropometry-based calculation of heat capacity (HC) for adults appeared to be precise and valid, its use in children and adolescents may be associated with bias. This study investigated a large dataset from the Size Korea survey, a national anthropometric survey conducted in 2010, to revalidate our previous HC equation and to develop another one that is appropriate for children and adolescents. We enrolled 12,766 participants aged 7–69 years with body composition data measured by multi-frequency bioelectrical impedance analysis. Age was associated with HC in children aged 7–19 years (R2 = 0.58) but not in adults (R2 = 0.007). Linear regression was appropriate to describe the relationship between HC and body surface area (BSA) in adults, whereas the regression in children and adolescent was quadratic. The previously developed HC equation had high reliability (intra-class correlation coefficient = 0.995) and predictive power (accurate prediction rate = 86.1%) in the >20 age group. The model composed of sex, body weight, BSA, and BSA2 was appropriate for the prediction of HC in young individuals aged 7–19 years. In conclusion, anthropometric-based modelling is a simple, reliable, and useful method for the calculation of HC.