PT  - JOURNAL ARTICLE
AU  - Abulmeaty, Mahmoud M. A.
AU  - Almajwal, Ali M.
AU  - Almadani, Najwa K.
AU  - Aldosari, Mona S.
AU  - Alnajim, Ahmed A.
AU  - Ali, Saeed B.
AU  - Hassan, Heba M.
AU  - Elkatawy, Hany A.
TI  - Anthropometric and central obesity indices as predictors of long-term cardiometabolic risk among Saudi young and middle-aged men and women
AID  - 10.15537/smj.2017.4.18758
DP  - 2017 Apr 01
TA  - Saudi Medical Journal
PG  - 372--380
VI  - 38
IP  - 4
4099  - http://smj.org.sa/content/38/4/372.short
4100  - http://smj.org.sa/content/38/4/372.full
SO  - Saudi Med J2017 Apr 01; 38
AB  - Objectives: To investigate the prediction of long-term cardiometabolic risk using anthropometric and central obesity parameters.Methods: A total of 390 Saudi subjects (men 42.8%) aged 18-50 years were enrolled in a cross-sectional study in King Saud University, Riyadh, Kingdom of Saudi Arabia between August 2014 and January 2016. All participants were instructed to fast for 12 hours before taking blood samples for glucose and lipid panel analyses. A full anthropometric measurement and bioelectric impedance analysis was performed. The anthropometric and central obesity parameters were used for correlation with 30-year Framingham and life-time American College of Cardiology/American Heart Association risk scores. We used receiver operator characteristic curves to select the best predictors with the highest sensitivity and specificity.Results: The best discriminators of the long-term cardiometabolic risk among all the studied variables in men were the visceral adiposity index (VAI) (AUC=0.767), conicity index (CI) (AUC=0.817), and mid-arm muscular area (MAMA) (AUC=0.639). The best predictors for women were body mass index (AUC=0.912), waist circumference (AUC=0.752), and lipid accumulation product (AUC=0.632). The Kappa coefficient and 95% confidence interval ranged from 0.1 to 0.35, which suggests that there is a poor to fair agreement between these indices and cardiovascular risk scores.Conclusion: Long-term cardiometabolic risk can be predicted using simple anthropometric and central obesity indices, and these discriminators were not the same in Saudi men and women.