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Metabolic Syndrome and Insulin Resistance: Underlying Causes and Modification by Exercise Training
Open accessAbstract
Metabolic syndrome (MS) is a collection of cardiometabolic risk factors that includes obesity, insulin resistance, hypertension, and dyslipidemia. Although there has been significant debate regarding the criteria and concept of the syndrome, this clustering of risk factors is unequivocally linked to an increased risk of developing type 2 diabetes and cardiovascular disease. Regardless of the true definition, based on current population estimates, nearly 100 million have MS. It is often characterized by insulin resistance, which some have suggested is a major underpinning link between physical inactivity and MS. The purpose of this review is to: (i) provide an overview of the history, causes and clinical aspects of MS, (ii) review the molecular mechanisms of insulin action and the causes of insulin resistance, and (iii) discuss the epidemiological and intervention data on the effects of exercise on MS and insulin sensitivity. © 2013 American Physiological Society.Compr Physiol 3:1‐58, 2013.
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Metadata
- Authors
- Roberts, C. K., Hevener, A. L., & Barnard, R. J.
- Venue
- Comprehensive Physiology
- Publisher
- Wiley
- Published
- 2013-01
- Volume
- 3
- Issue
- 1
- Pages
- 1-58
- ISSN
- 2040-4603 (ISSN-L)
- OpenAlex
- W1699868108
- Cited by
- 831
- References
- 730
- Type
- other
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.