A composite of BMI and waist circumference may be a better obesity metric in Indians with high risk for type 2 diabetes: An analysis of NMB-2017, a nationwide cross-sectional study. (March 2020)
- Record Type:
- Journal Article
- Title:
- A composite of BMI and waist circumference may be a better obesity metric in Indians with high risk for type 2 diabetes: An analysis of NMB-2017, a nationwide cross-sectional study. (March 2020)
- Main Title:
- A composite of BMI and waist circumference may be a better obesity metric in Indians with high risk for type 2 diabetes: An analysis of NMB-2017, a nationwide cross-sectional study
- Authors:
- Venkatrao, Murali
Nagarathna, Raghuram
Patil, Suchitra S.
Singh, Amit
Rajesh, S.K.
Nagendra, Hongasandra - Abstract:
- Highlights: Obesity is a well-established risk factor for diabetes, but the best obesity measure is unclear. General adiposity (BMI), central fat (WC) are usually used, but with varying results. A composite measure combining the two (BMIWC ) is better than either one in isolation. BMIWC improves the Indian Diabetes Risk Score, and potentially other screening scores. Abstract: Aims: Obesity measurement is a vital component of most type 2 diabetes screening tests; while studies had shown that waist circumference (WC) is a better predictor in South Asians, there is evidence that BMI is also effective. Our objective was to evaluate the efficacy of BMIWC, a composite measure, against BMI and WC. Methods: Using data from a nationwide randomized cluster sample survey (NMB-2017), we analyzed 7496 adults at high risk for type 2 diabetes. WC, BMI, and BMIWC were evaluated using Odds Ratio (OR), and Classification scores (Sensitivity, Specificity, and Accuracy). These were validated using Indian Diabetes Risk Score (IDRS) by replacing WC with BMI and BMIWC, and calculating Sensitivity, Specificity, and Accuracy. Results: BMIWC had higher OR (2·300) compared to WC (1·87) and BMI (2·26). WC, BMI, and BMIWC were all highly Sensitive (0·75, 0·81, 0·70 resp.). But BMIWC had significantly higher Specificity (0.36) when compared to WC and BMI (0.27 each). IDRSWC, IDRSBMI, and IDRSBMIWC were all highly Sensitive (0·87, 0·88, 0·82 resp.). But IDRSBMIWC had significantly higher SpecificityHighlights: Obesity is a well-established risk factor for diabetes, but the best obesity measure is unclear. General adiposity (BMI), central fat (WC) are usually used, but with varying results. A composite measure combining the two (BMIWC ) is better than either one in isolation. BMIWC improves the Indian Diabetes Risk Score, and potentially other screening scores. Abstract: Aims: Obesity measurement is a vital component of most type 2 diabetes screening tests; while studies had shown that waist circumference (WC) is a better predictor in South Asians, there is evidence that BMI is also effective. Our objective was to evaluate the efficacy of BMIWC, a composite measure, against BMI and WC. Methods: Using data from a nationwide randomized cluster sample survey (NMB-2017), we analyzed 7496 adults at high risk for type 2 diabetes. WC, BMI, and BMIWC were evaluated using Odds Ratio (OR), and Classification scores (Sensitivity, Specificity, and Accuracy). These were validated using Indian Diabetes Risk Score (IDRS) by replacing WC with BMI and BMIWC, and calculating Sensitivity, Specificity, and Accuracy. Results: BMIWC had higher OR (2·300) compared to WC (1·87) and BMI (2·26). WC, BMI, and BMIWC were all highly Sensitive (0·75, 0·81, 0·70 resp.). But BMIWC had significantly higher Specificity (0.36) when compared to WC and BMI (0.27 each). IDRSWC, IDRSBMI, and IDRSBMIWC were all highly Sensitive (0·87, 0·88, 0·82 resp.). But IDRSBMIWC had significantly higher Specificity (0·39) compared to IDRSWC and IDRSBMI (0·30, 0·31 resp.). Conclusions: Both WC and BMI are good predictors of risk for T2DM, but BMIWC is a better predictor, with higher Specificity; this may indicate that Indians with high values of both central (high WC) and general (BMI > 23) obesity carry higher risk for type 2 diabetes than either one in isolation. Using BMIWC in IDRS improves its performance on Accuracy and Specificity. … (more)
- Is Part Of:
- Diabetes research and clinical practice. Volume 161(2020)
- Journal:
- Diabetes research and clinical practice
- Issue:
- Volume 161(2020)
- Issue Display:
- Volume 161, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 161
- Issue:
- 2020
- Issue Sort Value:
- 2020-0161-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-03
- Subjects:
- Type 2 diabetes -- BMI -- Central fat -- Obesity -- Anthropometric
Diabetes -- Periodicals
Diabetes Mellitus -- Periodicals
616.462 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01688227 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/01688227 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/01688227 ↗
http://www.sciencedirect.com/science/journal/01688227 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.diabres.2020.108037 ↗
- Languages:
- English
- ISSNs:
- 0168-8227
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - 3579.603700
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- 13387.xml