Relationship between obesity, insulin resistance, and coronary heart disease risk.

By F. Abbasi, B. W. Brown, C. Lamendola, T. McLaughlin, G. Reaven. Journal of the American College of Cardiology, 2002

611 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism, Epidemiology

View Paper: https://www.semanticscholar.org/paper/90b3e77b88b543c2500eb8664760c999b4ad4bb0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cardiology and Cardiovascular Medicine

1. Ralph B. D’Agostino
2. J. Despres
3. Ramachandran S. Vasan
4. Daniel Levy
5. S. Grundy
6. James B. Meigs
7. R. Bonow
8. D. Lloyd‐Jones

In Endocrinology, Diabetes and Metabolism

1. S. Grundy
2. J. Despres
3. Ralph B. D’Agostino
4. R. Eckel
5. I. Lemieux
6. D. Nathan
7. Lisa Sullivan
8. Rury R. Holman

In Epidemiology

1. S. Grundy
2. R. Eckel
3. J. Despres
4. I. Lemieux
5. James B. Meigs
6. Peter W. F. Wilson
7. R. Bonow
8. Ralph B. D’Agostino

Citations in the corpus

• Definition of Metabolic Syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association Conference on Scientific Issues Related to Definition (2004, methodology): “These included (1) the standard Framingham algorithm,11 (2) ATP III metabolic syndrome risk factors alone, (3) metabolic syndrome risk factors age, (4) usual Framingham risk factors unique metabolic syndrome risk factors (obesity, triglycerides, glucose), and (5) usual Framingham risk factors metabo”
• Definition of Metabolic Syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association Conference on Scientific Issues Related to Definition (2004, methodology): “These included (1) the standard Framingham algorithm,11 (2) ATP III metabolic syndrome risk factors alone, (3) metabolic syndrome risk factors age, (4) usual Framingham risk factors unique metabolic syndrome risk factors (obesity, triglycerides, glucose), and (5) usual Framingham risk factors metabo”
• Fatty Acids Composition of Vegetable Oils and Its Contribution to Dietary Energy Intake and Dependence of Cardiovascular Mortality on Dietary Intake of Fatty Acids (2015, background): “Possibly, PUFAs can suppress the risk of CHD by improving both blood lipid levels and insulin resistance in overweight women, whilst TFAs may influence risk of CHD by its adverse effects on blood lipid levels [62,68].”
• Abdominal obesity and metabolic syndrome (2006, background): “Beyond excess body weight Although obesity is a risk factor for insulin resistance and type 2 diabetes, and a significant risk factor for CVD, not every obese patient is insulin resistan”
• Body mass index, metabolic syndrome, and risk of type 2 diabetes or cardiovascular disease. (2006, background): “However, IR at any given degree of obesity has been associated with elevated levels of diabetes and CVD risk factors (36), and dysmetabolism (MetS and diabetes combined) also confers risk for subsequent CVD events independent of BMI (37).”
• Experimenting with Measurement Error: Techniques with Applications to the Caltech Cohort Study (2019, neutral): “46 (Abbasi et al., 2002).”
• Use of Metabolic Markers To Identify Overweight Individuals Who Are Insulin Resistant (2003, background): “A corollary to this basic postulate is that the metabolic abnormalities that increase CVD risk in overweight or obese individuals are seen primarily in persons who are also insulin resistant (19–23), a view that was confirmed in a recently published study of more than 300 persons (39).”