The potential influence of the timing of eating on body weight regulation in humans has attracted substantial research interest. This review aims to critically evaluate the evidence on timed eating for weight loss, considering energetic and behavioural components of the timing of eating in humans. It has been hypothesised that timed eating interventions may alter energy balance in favour of weight loss by enhancing energy expenditure, specifically the thermic effect of food. This energetic effect has been suggested to explain greater weight loss which has been observed with certain timed eating interventions, despite comparable self-reported energy intakes to control diets. However, timed eating interventions have little impact on total daily energy expenditure, and the apparent effect of time of day on the thermic effect of food largely represents an artefact of measurement methods that fail to account for underlying circadian variation in RMR. Differences in weight loss observed in free-living interventions are more likely explainable by real differences in energy intake, notwithstanding similar self-reported energy intakes. In addition, the energetic focus tends to overlook the role of behavioural factors influencing the timing of eating, such as appetite regulation chronotype-environment interactions, which may influence energy intake under free-living conditions. Overall, there is scant evidence that timed eating interventions are superior to general energy restriction for weight loss in humans. However, the role of behavioural factors in influencing energy intake may be relevant for adherence to energy-restricted diets, and this aspect remains understudied in human intervention trials.

The λ model suggests that detailed kinematics arise from changes in control variables and need not be explicitly planned. However, we have shown that when moving a grasped object, grip force is precisely modulated in phase with acceleration-dependent inertial load. This suggests that the motor system can predict detailed kinematics. This prediction may be based on a forward model of the dynamics of the loaded limb.