Total daily energy expenditure (“total expenditure”) reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass–adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span.

Objective: To investigate the ability of a newly developed triaxial accelerometer to predict total energy expenditure (EE) (TEE) and activity-related EE (AEE) in free-living conditions. Research Methods and Procedures: Subjects were 29 healthy subjects between the ages of 18 and 40. The Triaxial Accelerometer for Movement Registration (Tracmor) was worn for 15 consecutive days. Tracmor output was defined as activity counts per day (ACD) for the sum of all three axes or each axis separately (ACD-X, ACD-Y, ACD-Z). TEE was measured with the doubly labeled water technique. Sleeping metabolic rate (SMR) was measured during an overnight stay in a respiration chamber. The physical activity level was calculated as TEE ϫ SMR Ϫ1 , and AEE was calculated as [(0.9 ϫ TEE) Ϫ SMR]. Body composition was calculated from body weight, body volume, and total body water using Siri's three-compartment model. Results: Age, height, body mass, and ACD explained 83% of the variation in TEE [standard error of estimate (SEE) ϭ 1.00 MJ/d] and 81% of the variation in AEE (SEE ϭ 0.70 MJ/d). The partial correlations for ACD were 0.73 (p Ͻ 0.001) and 0.79 (p Ͻ 0.001) with TEE and AEE, respectively. When data on SMR or body composition were used with ACD, the explained variation in TEE was 90% (SEE ϭ 0.74 and 0.77 MJ/d, respectively). The increase in the explained variation using three axes instead of one axis (vertical) was 5% (p Ͻ 0.05). Discussion: The correlations between Tracmor output and EE measures are the highest reported so far. To measure daily life activities, the use of triaxial accelerometry seems beneficial to uniaxial.

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In the present exploratory study that used gold standard measurements for AEE and PA but a limited sample size, genetic influence explained a large part of the variation in AEE and PA in daily life, whereas both AEE and PA were influenced by environment only within the confined area of the respiration chamber.