Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, USA.
Br J Nutr. 2010 Jul;104(1):4-7. doi: 10.1017/S0007114510000206. Epub 2010 Feb 5.
Predicting the magnitude and rate of weight gain for a given increase of energy intake requires a model of whole-body energy expenditure that includes the energy cost of tissue deposition. Here, I introduce a mathematical framework for modelling energy expenditure that elucidates conceptual problems with the classical Kielanowski method for estimating the efficiencies of body fat and protein deposition. An alternative approach uses the theoretical biochemical efficiencies for protein and fat synthesis in combination with models of energy expenditure that include body fat and protein turnover costs. I illustrate this alternative approach using a simple mathematical model applied to previously published data from growing rats and human infants and compare the simple model results with the classical Kielanowski model. While both models fit the data reasonably well (R2>0.87 in rats and R2>0.67 in infants), the Kielanowski method resulted in parameter estimates that varied widely across experiments, had poor precision, and occasionally produced efficiency estimates greater than 1. In contrast, the new method provided precise parameter values and revealed consistencies across different experiments. The proposed mathematical framework has implications for interpreting studies of animal nutrition as well as providing a roadmap for future modelling efforts.
预测给定能量摄入增加时的体重增加幅度和速率需要一个包含组织沉积能量成本的全身能量消耗模型。在这里,我引入了一种用于建模能量消耗的数学框架,阐明了经典 Kielanowski 方法估计体脂肪和蛋白质沉积效率时存在的概念问题。另一种方法是使用蛋白质和脂肪合成的理论生化效率,并结合包含体脂肪和蛋白质周转率成本的能量消耗模型。我使用一个简单的数学模型来说明这种替代方法,并将其应用于以前发表的生长大鼠和人类婴儿的数据,将简单模型的结果与经典 Kielanowski 模型进行比较。虽然两个模型都能很好地拟合数据(大鼠的 R2>0.87,婴儿的 R2>0.67),但 Kielanowski 方法得出的参数估计值在不同实验中差异很大,精度较差,偶尔还会产生效率估计值大于 1。相比之下,新方法提供了精确的参数值,并揭示了不同实验之间的一致性。所提出的数学框架对解释动物营养研究具有重要意义,并为未来的建模工作提供了路线图。