The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Diagnosis of obesity and use of obesity biomarkers in science and clinical medicine
Abstract
The global epidemic of obesity is a major public health problem today. Obesity increases the risk of many chronic diseases, such as type 2 diabetes, coronary heart disease, and certain types of cancer, and is associated with lower life expectancy. The body mass index (BMI), which is currently used to classify obesity, is only an imperfect measure of abnormal or excessive body fat accumulation. Studies have shown that waist circumference as a measure of fat distribution may improve disease prediction. More elaborate techniques such as magnetic resonance imaging are increasingly available to assess body fat distribution, but these measures are not readily available in routine clinical practice, and health-relevant cut-offs not yet been established. The measurement of biomarkers that reflect the underlying biological mechanisms for the increased disease risk may be an alternative approach to characterize the relevant obesity phenotype. The insulin/insulin-like growth factor (IGF) axis and chronic low-grade inflammation have been identified as major pathways. In addition, specific adipokines such as leptin, adiponectin and resistin have been related to obesity-associated health outcomes. This biomarker research, which is currently further developed with the application of high throughput methods, gives important insights in obesity-related disease etiology and pathophysiological pathways and may be used to better characterize obese persons at high risk of disease development and target disease-causing biomarkers in personalized prevention strategies.
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Cites
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“Nevertheless, it is widely reported that CRP represents the most studied inflammatory biomarker in different pathologic processes [88].”
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Metadata
- Authors
- Nimptsch, K., Konigorski, S., & Pischon, T.
- Venue
- Metabolism
- Publisher
- Elsevier BV
- Published
- 2019-03
- Volume
- 92
- Pages
- 61-70
- ISSN
- 0026-0495 (ISSN-L)
- OpenAlex
- W2905742189
- Cited by
- 314
- References
- 21
- FWCI
- 12.44
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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