The carbohydrate-insulin model: a physiological perspective on the obesity pandemic. Issue 6 (13th September 2021)

• Record Type: Journal Article
• Authors: Ludwig, David S; Aronne, Louis J; Astrup, Arne; de Cabo, Rafael; Cantley, Lewis C; Friedman, Mark I; Heymsfield, Steven B; Johnson, James D; King, Janet C; Krauss, Ronald M; Lieberman, Daniel E; Taubes, Gary; Volek, Jeff S; Westman, Eric C; Willett, Walter C; Yancy, William S; Ebbeling, Cara B
• Is Part Of: American journal of clinical nutrition. Volume 114:Issue 6(2021)
• Page Start: 1873
• Page End: 1885
• Publication Date: 2021-09-13
• Subjects: obesity -- weight loss -- dietary carbohydrate -- energy balance -- macronutrients -- endocrinology -- insulin -- glucagon -- incretins -- scholarly discourse; Diet therapy -- Periodicals; Nutrition -- Periodicals; Dietetics -- Periodicals; 613.205
• DOI: 10.1093/ajcn/nqab270
• Languages: English
• ISSNs: 0002-9165

Abstract

ABSTRACT: According to a commonly held view, the obesity pandemic is caused by overconsumption of modern, highly palatable, energy-dense processed foods, exacerbated by a sedentary lifestyle. However, obesity rates remain at historic highs, despite a persistent focus on eating less and moving more, as guided by the energy balance model (EBM). This public health failure may arise from a fundamental limitation of the EBM itself. Conceptualizing obesity as a disorder of energy balance restates a principle of physics without considering the biological mechanisms that promote weight gain. An alternative paradigm, the carbohydrate-insulin model (CIM), proposes a reversal of causal direction. According to the CIM, increasing fat deposition in the body—resulting from the hormonal responses to a high-glycemic-load diet—drives positive energy balance. The CIM provides a conceptual framework with testable hypotheses for how various modifiable factors influence energy balance and fat storage. Rigorous research is needed to compare the validity of these 2 models, which have substantially different implications for obesity management, and to generate new models that best encompass the evidence.