OBJECTIVE: To qualify a 3C approach model of dual-energy X-ray absorptiometry (DXA) to estimate multicomponent resting energy expenditure (REE) referenced by indirect calorimetry (IC). METHODS: A sample of 155 college students, of both sexes (18-30 years old) was evaluated. Anthropometric measures, REE by IC, and whole-body DXA-scans were performed. The REE for each body component was determined after transforming the components from the molecular (DXA) to the organ tissue level. Bland-Altman and proportional bias analyses were used to verify agreement between REE measured (REEIC ) and estimated (REEDXA ). RESULTS: Statistically significant differences were found for all sex comparisons (P < .001), except for age (P = .950). Differences from the final sex-specific models' were not found between REEIC and REEDXA (P > .05). Men also presented greater expenditure (P < .001) in each component, except for adipose tissue. The plots confirmed the validity of the model for both sexes, with low difference values between the measured and estimated REE. The mean of the differences of REEIC and REEDXA showed heteroscedasticity of the data for men (P = .004). The same error tendency was not evident for women (P = .333). CONCLUSIONS: This 3C model, estimating REE from a multicomponent approach, allows a new application of DXA as tool for understanding intraindividual differences in terms of the mass of metabolically active tissue. Sex and populational differences should be taken in account. Consequently, we present qualified sex-specific DXA models that can be applied in different contexts such as health and sports, besides considering interpersonal differences in terms of energy expenditure.
OBJECTIVE: To qualify a 3C approach model of dual-energy X-ray absorptiometry (DXA) to estimate multicomponent resting energy expenditure (REE) referenced by indirect calorimetry (IC). METHODS: A sample of 155 college students, of both sexes (18-30 years old) was evaluated. Anthropometric measures, REE by IC, and whole-body DXA-scans were performed. The REE for each body component was determined after transforming the components from the molecular (DXA) to the organ tissue level. Bland-Altman and proportional bias analyses were used to verify agreement between REE measured (REEIC ) and estimated (REEDXA ). RESULTS: Statistically significant differences were found for all sex comparisons (P < .001), except for age (P = .950). Differences from the final sex-specific models' were not found between REEIC and REEDXA (P > .05). Men also presented greater expenditure (P < .001) in each component, except for adipose tissue. The plots confirmed the validity of the model for both sexes, with low difference values between the measured and estimated REE. The mean of the differences of REEIC and REEDXA showed heteroscedasticity of the data for men (P = .004). The same error tendency was not evident for women (P = .333). CONCLUSIONS: This 3C model, estimating REE from a multicomponent approach, allows a new application of DXA as tool for understanding intraindividual differences in terms of the mass of metabolically active tissue. Sex and populational differences should be taken in account. Consequently, we present qualified sex-specific DXA models that can be applied in different contexts such as health and sports, besides considering interpersonal differences in terms of energy expenditure.