4.0 Article

Classification of obesity, cardiometabolic risk, and metabolic syndrome in adults with spinal cord injury

期刊

JOURNAL OF SPINAL CORD MEDICINE
卷 43, 期 4, 页码 485-496

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/10790268.2018.1557864

关键词

Spinal cord injuries; Obesity; Veterans; Retrospective studies; Metabolic syndrome

资金

  1. NIDDK NIH HHS [P30 DK079626] Funding Source: Medline

向作者/读者索取更多资源

Objective:To describe and compare (1) classification of obesity using clinical proxies of body composition that are easily accessible in the outpatient clinic setting, (2) cardiometabolic risk using existing screening tools and staging systems, and (3) the presence of metabolic syndrome (MetS) using four commonly-used definitions in adults with spinal cord injury (SCI). Design:Retrospective chart review Setting:Outpatient Veterans Affairs (VA) SCI Annual Evaluation Clinic Participants:Patients who attended an annual evaluation appointment with demographic, anthropometric, and biochemical data documented in their medical records as part of routine medical care. Outcome measures:Obesity classification (body mass index, waist circumference, ideal body weight percentage), cardiometabolic risk scores (Framingham Risk Score, Cardiometabolic Disease Staging System, Edmonton Obesity Staging System), and MetS classification (using four commonly-used definitions) were described and compared. Results:Of the 155 veterans included in this analysis, 93% were considered at risk by at least one of the measurements studied. However, there was considerable variation between the different screening tools. The kappa-agreement between various definitions of MetS ranged from fair to moderate. Conclusion:Screening tools that were developed for the non-SCI population produced variable assessments of risk when applied to veterans with SCI. Due to the fair to moderate inter-rater agreement between MetS definitions, it is unknown which definition is superior to identify MetS in the SCI population. An SCI-specific screening tool is needed to accurately classify obesity, cardiometabolic risk, and MetS in order to provide timely education and intervention.

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