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Lower ambient temperature (Ta) requires greater energy expenditure to sustain body temperature. However, effects of Ta on human energetics may be buffered by environmental modification and behavioral compensation. We used the IAEA DLW database for adults in the USA (n = 3213) to determine the effect of Ta (-10 to +30°C) on TEE, basal (BEE) and activity energy expenditure (AEE) and physical activity level (PAL). There were no significant relationships (p > 0.05) between maximum, minimum and average Ta and TEE, BEE, AEE and PAL. After adjustment for fat-free mass, fat mass and age, statistically significant (p

When lean people adopt carbohydrate-restricted diets (CRDs), they may develop a lipid profile consisting of elevated LDL-cholesterol (LDL-C) and HDL-cholesterol (HDL-C) with low triglycerides (TGs). The magnitude of this lipid profile correlates with BMI such that those with lower BMI exhibit larger increases in both LDL-C and HDL-C. The inverse association between BMI and LDL-C and HDL-C change on CRD contributed to the discovery of a subset of individuals-termed Lean Mass Hyper-Responders (LMHR)-who, despite normal pre-diet LDL-C, as compared to non-LMHR (mean levels of 148 and 145 mg/dL, respectively), exhibited a pronounced hyperlipidemic response to a CRD, with mean LDL-C and HDL-C levels increasing to 320 and 99 mg/dL, respectively, in the context of mean TG of 47 mg/dL. In some LMHR, LDL-C levels may be in excess of 500 mg/dL, again, with relatively normal pre-diet LDL-C and absent of genetic findings indicative of familial hypercholesterolemia in those who have been tested. The Lipid Energy Model (LEM) attempts to explain this metabolic phenomenon by positing that, with carbohydrate restriction in lean persons, the increased dependence on fat as a metabolic substrate drives increased hepatic secretion and peripheral uptake of TG contained within very low-density lipoproteins (VLDL) by lipoprotein lipase, resulting in marked elevations of LDL-C and HDL-C, and low TG. Herein, we review the core features of the LEM. We review several existing lines of evidence supporting the model and suggest ways to test the model's predictions.

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.

The doubly labeled water (DLW) method measures total energy expenditure (TEE) in free-living subjects. Several equations are used to convert isotopic data into TEE. Using the International Atomic Energy Agency (IAEA) DLW database (5,756 measurements of adults and children), we show considerable variability is introduced by different equations. The estimated rCO2 is sensitive to the dilution space ratio (DSR) of the two isotopes. Based on performance in validation studies, we propose a new equation based on a new estimate of the mean DSR. The DSR is lower at low body masses (

Summary: Our understanding of the pathophysiology of obesity remains at best incomplete despite a century of research. During this time, two alternative perspectives have helped shape thinking about the etiology of the disorder. The currently prevailing view holds that excessive fat accumulation results because energy intake exceeds energy expenditure, with excessive food consumption being the primary cause of the imbalance. The other perspective attributes the initiating cause of obesity to intrinsic metabolic defects that shift fuel partitioning from pathways for mobilization and oxidation to those for synthesis and storage. The resulting reduction in fuel oxidation and trapping of energy in adipose tissue drives a compensatory increase in energy intake and, under some conditions, a decrease in expenditure. This theory of obesity pathogenesis has historically garnered relatively less attention despite its pedigree. Here, we present an updated comprehensive formulation of the fuel partitioning theory, focused on evidence gathered over the last 80 years from major animal models of obesity showing a redirection of fuel fluxes from oxidation to storage and accumulation of excess body fat with energy intake equal to or even less than that of lean animals. The aim is to inform current discussions about the etiology of obesity and by so doing, help lay new foundations for the design of more efficacious approaches to obesity research, treatment and prevention. [ABSTRACT FROM AUTHOR]

BACKGROUND:A fundamental precept of the carbohydrate-insulin model of obesity is that insulin secretion drives weight gain. However, fasting hyperinsulinemia can also be driven by obesity-induced insulin resistance. We used genetic variation to isolate and estimate the potentially causal effect of insulin secretion on body weight. METHODS:Genetic instruments of variation of insulin secretion [assessed as insulin concentration 30 min after oral glucose (insulin-30)] were used to estimate the causal relationship between increased insulin secretion and body mass index (BMI), using bidirectional Mendelian randomization analysis of genome-wide association studies. Data sources included summary results from the largest published metaanalyses of predominantly European ancestry for insulin secretion (n = 26037) and BMI (n = 322154), as well as individual-level data from the UK Biobank (n = 138541). Data from the Cardiology and Metabolic Patient Cohort study at Massachusetts General Hospital (n = 1675) were used to validate genetic associations with insulin secretion and to test the observational association of insulin secretion and BMI. RESULTS:Higher genetically determined insulin-30 was strongly associated with higher BMI (β = 0.098, P = 2.2 × 10-21), consistent with a causal role in obesity. Similar positive associations were noted in sensitivity analyses using other genetic variants as instrumental variables. By contrast, higher genetically determined BMI was not associated with insulin-30. CONCLUSIONS:Mendelian randomization analyses provide evidence for a causal relationship of glucose-stimulated insulin secretion on body weight, consistent with the carbohydrate-insulin model of obesity.

A large feeding study reported that total energy expenditure (TEE) was greater on a low- versus high-carbohydrate diet, supporting the carbohydrate-insulin model of obesity. Recently, the validity of this finding was challenged in a post-hoc analysis excluding participants with putative non-adherence to the study diets. Here, we show why that analysis, based on a post-randomization variable linked to the outcome, introduced severe confounding bias. With control for confounding, the diet effect on TEE remained strong in a reanalysis. Together with sensitivity analyses demonstrating robustness to plausible levels of non-adherence, these data provide experimental support for a potentially novel metabolic effect of macronutrients that might inform the design of more effective obesity treatment., Author(s): David S. Ludwig [sup.1], Kimberly F. Greco [sup.2], Clement Ma [sup.2] [sup.3], Cara B. Ebbeling [sup.1] Author Affiliations: (1) New Balance Foundation Obesity Prevention Center, Boston Children's Hospital and [...]

ObjectiveThe relation of breakfast intake frequency to metabolic health is not well studied. The aim of this study was to examine breakfast intake frequency with incidence of metabolic conditions.Research design and methodsWe performed an analysis of 3,598 participants from the community-based Coronary Artery Risk Development in Young Adults (CARDIA) study who were free of diabetes in the year 7 examination when breakfast and dietary habits were assessed (1992-1993) and participated in at least one of the five subsequent follow-up examinations over 18 years.ResultsRelative to those with infrequent breakfast consumption (0-3 days/week), participants who reported eating breakfast daily gained 1.9 kg less weight over 18 years (P=0.001). In a Cox regression analysis, there was a stepwise decrease in risk across conditions in frequent breakfast consumers (4-6 days/week) and daily consumers. The results for incidence of abdominal obesity, obesity, metabolic syndrome, and hypertension remained significant after adjustment for baseline measures of adiposity (waist circumference or BMI) in daily breakfast consumers. Hazard ratios (HRs) and 95% CIs for daily breakfast consumption were as follows: abdominal obesity HR 0.78 (95% CI 0.66-0.91), obesity 0.80 (0.67-0.96), metabolic syndrome 0.82 (0.69-0.98), and hypertension 0.84 (0.72-0.99). For type 2 diabetes, the corresponding estimate was 0.81 (0.63-1.05), with a significant stepwise inverse association in black men and white men and women but no association in black women. There was no evidence of differential results for high versus low overall dietary quality.ConclusionsDaily breakfast intake is strongly associated with reduced risk of a spectrum of metabolic conditions.