A method for constructing a model for assessing the phenotypic state of a
receiver and a phenotypic
state model, a method for constructing a model for assessing the elastic
homeostasis of a
receiver and an elastic
homeostasis model, a method for assessing the health state of a
receiver, a method for assessing the elastic
homeostasis of a receiver, a method for assessing the risk of a receiver suffering from a
metabolic disease, a method for assessing whether a therapy for treating a
metabolic disease of a receiver is effective, a method and
system for assessing whether a metabolic
health intervention solution of a receiver is effective, and a kit. The method for constructing a model for assessing the phenotypic state of a receiver comprises: selecting a plurality of markers that are involved in or affect a total of four categories of
metabolism, that is, glycometabolism,
lipid metabolism,
amino acid metabolism and metabolic stress; selecting one to several categories as coordinate axes for establishing a model; collecting samples of n healthy receivers and samples of m receivers who are in an impaired-health or sub-healthy condition; measuring the levels of markers related to the selected coordinate axes in each sample; training a
machine learning model by using the levels of the markers; and performing screening to obtain a target marker, and calculating a
weight coefficient of the target marker, so as to establish the model for assessing the phenotypic state of the receiver.