The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Classification of Obesity and Assessment of Obesity‐Related Health Risks
Abstract
The barriers to the evaluation and treatment of obesity by health‐care providers include a lack of awareness of obesity as an independent risk factor for morbidity and mortality and inadequate training in the medical management of obesity. However, the increased risk of medical disorders and emotional consequences associated with obesity make the disorder a priority for physicians to assess and treat. Obesity researchers have published and promoted the use of evidence‐based, practical guidelines to educate physicians about how best to approach obesity as a medical disorder. The guidelines support classification and assessment of obesity as an important component of the patient's medical care. Assessment begins with classification by body mass index (BMI), with overweight and obesity defined as a BMI of 25 and 30 kg/m 2, respectively. Patients with high‐risk combinations of BMI, waist circumference, and specific cardiovascular risk factors should begin a weight‐loss program if no contraindications are present. Proper assessment also includes evaluation of complicating factors for obesity, such as sleep apnea and type 2 diabetes, psychosocial factors, and the use of medications that may contribute to obesity. Special attention should be paid to elements of the physical examination that often are performed incorrectly in obese patients, such as pelvic exams. Gathering this information will allow the clinician to tailor a weight‐loss program to each patient individually. Although this represents the most challenging component of obesity care, resources are available to guide the clinician.
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Cited by
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Circadian rhythm disruption as a link between Attention-Deficit/Hyperactivity Disorder and obesity?
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Metadata
- Authors
- Aronne, L. J.
- Venue
- Obesity Research
- Publisher
- Wiley
- Published
- 2002-12
- Volume
- 10
- Issue
- S12
- Pages
- 105S-115S
- ISSN
- 1071-7323 (ISSN-L)
- 1550-8528
- OpenAlex
- W2048433033
- Cited by
- 320
- References
- 28
- FWCI
- 5.00
- 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).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.