559 related articles for article (PubMed ID: 23634931)
1. The estimation of visceral adipose tissue with a body composition monitor predicts the metabolic syndrome.
Baudrand R; Domínguez JM; Tabilo C; Figueroa D; Jimenez M; Eugenin C; Carvajal C; Moreno M
J Hum Nutr Diet; 2013 Jul; 26 Suppl 1():154-8. PubMed ID: 23634931
[TBL] [Abstract][Full Text] [Related]
2. Performance of abdominal bioelectrical impedance analysis and comparison with other known parameters in predicting the metabolic syndrome.
Mousa U; Kut A; Bozkus Y; Cicek Demir C; Anil C; Bascil Tutuncu N
Exp Clin Endocrinol Diabetes; 2013 Jul; 121(7):391-6. PubMed ID: 23696479
[TBL] [Abstract][Full Text] [Related]
3. Predicting abdominal adipose tissue among women with familial partial lipodystrophy.
Joy T; Kennedy BA; Al-Attar S; Rutt BK; Hegele RA
Metabolism; 2009 Jun; 58(6):828-34. PubMed ID: 19375764
[TBL] [Abstract][Full Text] [Related]
4. Anthropometric indices of central obesity how discriminators of metabolic syndrome in Brazilian women with polycystic ovary syndrome.
Costa EC; Sá JC; Soares EM; Lemos TM; Maranhão TM; Azevedo GD
Gynecol Endocrinol; 2012 Jan; 28(1):12-5. PubMed ID: 21958393
[TBL] [Abstract][Full Text] [Related]
5. The discriminative ability of waist circumference, body mass index and waist-to-hip ratio in identifying metabolic syndrome: Variations by age, sex and race.
Cheong KC; Ghazali SM; Hock LK; Subenthiran S; Huey TC; Kuay LK; Mustapha FI; Yusoff AF; Mustafa AN
Diabetes Metab Syndr; 2015; 9(2):74-8. PubMed ID: 25819369
[TBL] [Abstract][Full Text] [Related]
6. Quantitative analysis of adipose tissue in single transverse slices for estimation of volumes of relevant fat tissue compartments: a study in a large cohort of subjects at risk for type 2 diabetes by MRI with comparison to anthropometric data.
Schwenzer NF; Machann J; Schraml C; Springer F; Ludescher B; Stefan N; Häring H; Fritsche A; Claussen CD; Schick F
Invest Radiol; 2010 Dec; 45(12):788-94. PubMed ID: 20829704
[TBL] [Abstract][Full Text] [Related]
7. Utility of obesity indices in screening Chinese postmenopausal women for metabolic syndrome.
Liu P; Ma F; Lou H; Zhu Y
Menopause; 2014 May; 21(5):509-14. PubMed ID: 23963310
[TBL] [Abstract][Full Text] [Related]
8. Correlation of fat distribution in whole body MRI with generally used anthropometric data.
Ludescher B; Machann J; Eschweiler GW; Vanhöfen S; Maenz C; Thamer C; Claussen CD; Schick F
Invest Radiol; 2009 Nov; 44(11):712-9. PubMed ID: 19809346
[TBL] [Abstract][Full Text] [Related]
9. Usefulness of measuring both body mass index and waist circumference for the estimation of visceral adiposity and related cardiometabolic risk profile (from the INSPIRE ME IAA study).
Nazare JA; Smith J; Borel AL; Aschner P; Barter P; Van Gaal L; Tan CE; Wittchen HU; Matsuzawa Y; Kadowaki T; Ross R; Brulle-Wohlhueter C; Alméras N; Haffner SM; Balkau B; Després JP;
Am J Cardiol; 2015 Feb; 115(3):307-15. PubMed ID: 25499404
[TBL] [Abstract][Full Text] [Related]
10. The association of anthropometric indices in adolescence with the occurrence of the metabolic syndrome in early adulthood: Tehran Lipid and Glucose Study (TLGS).
Barzin M; Asghari G; Hosseinpanah F; Mirmiran P; Azizi F
Pediatr Obes; 2013 Jun; 8(3):170-7. PubMed ID: 23042576
[TBL] [Abstract][Full Text] [Related]
11. The prevalence of metabolic syndrome in Chinese postmenopausal women and the optimum body composition indices to predict it.
Ruan X; Jin J; Hua L; Liu Y; Wang J; Liu S
Menopause; 2010; 17(3):566-70. PubMed ID: 20054286
[TBL] [Abstract][Full Text] [Related]
12. Abdominal fat sub-depots and energy expenditure: Magnetic resonance imaging study.
Serfaty D; Rein M; Schwarzfuchs D; Shelef I; Gepner Y; Bril N; Cohen N; Shemesh E; Sarusi B; Kovsan J; Kenigsbuch S; Chassidim Y; Golan R; Witkow S; Henkin Y; Stampfer MJ; Rudich A; Shai I
Clin Nutr; 2017 Jun; 36(3):804-811. PubMed ID: 27288327
[TBL] [Abstract][Full Text] [Related]
13. [Evaluation of abdominal visceral obesity from anthropometric parameters using receiver operating characteristic curves].
Jia W; Lu J; Xiang K; Bao Y; Lu H; Chen L
Zhonghua Liu Xing Bing Xue Za Zhi; 2002 Feb; 23(1):20-3. PubMed ID: 12015103
[TBL] [Abstract][Full Text] [Related]
14. [Evaluation of visceral adipose in abdominal obesity and its clinical application].
Pu YF; He HB; Zhao ZG; Chen J; Ni YX; Zhong J; Liu HY; Yan ZC; Zhu ZM
Zhonghua Yi Xue Za Zhi; 2008 Sep; 88(34):2391-4. PubMed ID: 19087712
[TBL] [Abstract][Full Text] [Related]
15. Cut-off value of body fat in association with metabolic syndrome in Thai peri- and postmenopausal women.
Bintvihok W; Chaikittisilpa S; Panyakamlerd K; Jaisamrarn U; Taechakraichana N
Climacteric; 2013 Jun; 16(3):393-7. PubMed ID: 23320744
[TBL] [Abstract][Full Text] [Related]
16. Waist circumference and BMI cut-off points to predict risk factors for metabolic syndrome among outpatients in a district hospital.
Aye M; Sazali M
Singapore Med J; 2012 Aug; 53(8):545-50. PubMed ID: 22941134
[TBL] [Abstract][Full Text] [Related]
17. Does body mass index reflect adequately the body fat content in perimenopausal women?
Kontogianni MD; Panagiotakos DB; Skopouli FN
Maturitas; 2005 Jul; 51(3):307-13. PubMed ID: 15978975
[TBL] [Abstract][Full Text] [Related]
18. Predictors of the metabolic syndrome and correlation with computed axial tomography.
Soto González A; Bellido D; Buño MM; Pértega S; De Luis D; Martínez-Olmos M; Vidal O
Nutrition; 2007 Jan; 23(1):36-45. PubMed ID: 17189089
[TBL] [Abstract][Full Text] [Related]
19. Obesity criteria for identifying metabolic risks.
Wang JW; Hu DY; Sun YH; Wang JH; Wang GL; Xie J; Zhou ZQ
Asia Pac J Clin Nutr; 2009; 18(1):105-13. PubMed ID: 19329403
[TBL] [Abstract][Full Text] [Related]
20. Comparison of anthropometric and body composition measures as predictors of components of the metabolic syndrome in a clinical setting.
Mooney SJ; Baecker A; Rundle AG
Obes Res Clin Pract; 2013; 7(1):e55-66. PubMed ID: 24331682
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]