Recent years have seen increased focus from scientists and healthcare providers on the growing problem of obesity. Although some progress has been made in this area of research, the reasons for the increased prevalence have not been fully elucidated. In this context, two conflicting models of obesity, the carbohydrate-insulin model (CIM) and the energy balance model (EBM), have been proposed and used to explain The two conflicting models, the carbohydrate-insulin model (CIM) and the energy balance model (EBM), have been proposed to explain the etiology of obesity.
On April 21, 2023, Professor Jeffrey S. Flier of Harvard Medical School published the opinion piece Moderating "the great debate": the carbohydrate-insulin vs. the energy balance models of obesity, in which the authors neutrally explore the contributions of both models to the inquiry into the causes of obesity and their respective limitations, and while both CIM and EBM provide useful insights, both fail to accomplish the core goals of obesity research—to fully explain the causes of the rising incidence of obesity in humans. The authors suggest that research into the mechanisms underlying the rising incidence of obesity must ultimately incorporate genetic, physiological, and environmental influences, and is likely the result of a combination of different obesity mechanisms.
The CIM model proposes that increased carbohydrate intake causes or at least contributes significantly to the general increase in obesity.
The CIM modality promotes obesity through a continuum of physiological effects, including:
Elevated blood glucose levels following ingestion of rapidly digested carbohydrates
Stimulation of hyperinsulinemia
Promotion of energy storage in adipose tissue and inhibition of energy release
Lack of energy substrates in the blood (reduced glucose, free fatty acids, and ketone bodies) late after a meal
The central nervous system (CNS) senses energy deprivation in the blood or other tissues, stimulating appetite and possibly reducing energy expenditure. Ultimately, a series of physiological effects lead to a "positive energy balance" that triggers obesity.
The CIM model suggests that excessive fat storage is an upstream factor in overeating and obesity, and that enhanced fat synthesis leads to excessive fat storage, causing a lack of circulating energy, which stimulates appetite.
However, it does not yet provide an adequate explanation for the increase in obesity in the population as a whole, and there are still many aspects that need to be studied in depth, including:
The correlation between high-carbohydrate diets and the increased prevalence of obesity in various populations
Low-carbohydrate diets have not been shown to be effective in treating obesity
Whether obese individuals exhibit blood or other energy deficiencies at various stages of progressive obesity that promote overeating
Whether individuals with high insulin secretion are particularly vulnerable to the adverse metabolic effects of dietary carbohydrates.
The CIM model may explain the pathogenesis of obesity in a subset of the population and is particularly suitable to explain the etiology of obesity induced by hyperinsulinemic groups. However, the pathogenesis of obesity may be more heterogeneous, so other mechanisms/models are needed to more broadly elucidate the reasons for the increased prevalence of obesity.
Therefore, some researchers have proposed the EBM model, which posits that homeostatic control centers in the brain integrate signals from peripheral tissues to control food intake and energy expenditure through complex endocrine, metabolic, and neurological signals that result in net energy storage. Peripheral feedback signals such as leptin, neural signals and gut hormones exert their effects on homeostatic control of the CNS. However, with changes in the food environment in recent decades, one or more external factors (e.g., cheap, highly processed foods high in fat and/or sugar but low in protein and fiber) interfere with homeostatic energy homeostasis, leading to the development of obesity.
Although the EBM model provides a relatively broad insight, the current EBM model does not explain why external factors promote obesity only in some individuals and not in all. The authors argue that further development of the EBM model is needed to elucidate the external factors that contribute to obesity, to explain how alterations in specific factors control brain circuits for food intake, and why some people are more likely to develop obesity than others.
It is important for anti-obesity agents to use predictive and convincing data from human-relevant models before entering clinical trials. Non-human primates (NHPs), which naturally resemble human beings in many aspects, are by far the most predictive models available for obesity studies, which share certain advantages in:
Similar features of obesity, dyslipidemia, and other dysmetabolic characteristics
Extensive data can be gathered for analysis of disease procedures and treatment efficacy.
Provide a promising opportunity to observe the onset and course of diseases in a human-like pattern
Make the preclinical data more convincing before entering a clinical trial
Allow dietary studies in NHPs with varying degrees of metabolic dysfunctions