P40 Predicting type 2 diabetes development among patients in general practice – a prospective analysis comparing metabolic syndrome definitions and components. (3rd September 2019)
- Record Type:
- Journal Article
- Title:
- P40 Predicting type 2 diabetes development among patients in general practice – a prospective analysis comparing metabolic syndrome definitions and components. (3rd September 2019)
- Main Title:
- P40 Predicting type 2 diabetes development among patients in general practice – a prospective analysis comparing metabolic syndrome definitions and components
- Authors:
- Millar, SR
Phillips, CM
Harrington, JM
Perry, IJ - Abstract:
- Abstract : Background: A definition of metabolic syndrome (MetS) has been recommended as a tool to help identify individuals at risk of developing type 2 diabetes. However, an agreed protocol for defining MetS does not exist and some studies have shown MetS definitions to be inferior at predicting diabetes compared to a single measurement of fasting glucose. In this study we examined the ability of five proposed MetS definitions to discriminate incident cases in order to determine whether MetS more accurately predicts type 2 diabetes. Methods: This was a prospective study involving a random sample of 1, 754 men and women aged 46–73 years. Receiver operating characteristic curve and net reclassification improvement (NRI) analyses were used to evaluate the ability of MetS definitions and components to accurately classify high-risk subjects. Results: A model including proposed MetS components displayed a significantly (P=0.02) higher area under the curve (AUC) to discriminate diabetes (AUC=0.90, 95% CI: 0.87–0.93) compared to fasting glucose alone (AUC=0.88, 95% CI: 0.83–0.92). Models using the European Group for the Study of Insulin Resistance MetS criterion, and which included glucose as a mandatory component, demonstrated significant overall NRI when compared to recommended and optimal fasting glucose cut-offs. A final model had a sensitivity of 0.91 and a specificity of 0.73. Conclusion: In this population there is evidence that a combination of MetS components may helpAbstract : Background: A definition of metabolic syndrome (MetS) has been recommended as a tool to help identify individuals at risk of developing type 2 diabetes. However, an agreed protocol for defining MetS does not exist and some studies have shown MetS definitions to be inferior at predicting diabetes compared to a single measurement of fasting glucose. In this study we examined the ability of five proposed MetS definitions to discriminate incident cases in order to determine whether MetS more accurately predicts type 2 diabetes. Methods: This was a prospective study involving a random sample of 1, 754 men and women aged 46–73 years. Receiver operating characteristic curve and net reclassification improvement (NRI) analyses were used to evaluate the ability of MetS definitions and components to accurately classify high-risk subjects. Results: A model including proposed MetS components displayed a significantly (P=0.02) higher area under the curve (AUC) to discriminate diabetes (AUC=0.90, 95% CI: 0.87–0.93) compared to fasting glucose alone (AUC=0.88, 95% CI: 0.83–0.92). Models using the European Group for the Study of Insulin Resistance MetS criterion, and which included glucose as a mandatory component, demonstrated significant overall NRI when compared to recommended and optimal fasting glucose cut-offs. A final model had a sensitivity of 0.91 and a specificity of 0.73. Conclusion: In this population there is evidence that a combination of MetS components may help predict diabetes beyond that which is measured by glucose alone. Proposed MetS definitions should include fasting glucose as a mandatory component. … (more)
- Is Part Of:
- Journal of epidemiology and community health. Volume 73(2019)Supplement 1
- Journal:
- Journal of epidemiology and community health
- Issue:
- Volume 73(2019)Supplement 1
- Issue Display:
- Volume 73, Issue 1 (2019)
- Year:
- 2019
- Volume:
- 73
- Issue:
- 1
- Issue Sort Value:
- 2019-0073-0001-0000
- Page Start:
- A89
- Page End:
- A90
- Publication Date:
- 2019-09-03
- Subjects:
- Type 2 Diabetes -- Metabolic Syndrome -- Screening
Public health -- Periodicals
Epidemiology -- Periodicals
614.4 - Journal URLs:
- http://jech.bmj.com/ ↗
http://www.jstor.org/journals/0143005X.html ↗
http://www.pubmedcentral.nih.gov/tocrender.fcgi?journal=165&action=archive ↗
http://www.bmj.com/archive ↗ - DOI:
- 10.1136/jech-2019-SSMabstracts.191 ↗
- Languages:
- English
- ISSNs:
- 0143-005X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 18761.xml