These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

157 related articles for article (PubMed ID: 27496270)

  • 1. Utility of Body Mass Index in Identifying Excess Adiposity in Youth Across the Obesity Spectrum.
    Ryder JR; Kaizer AM; Rudser KD; Daniels SR; Kelly AS
    J Pediatr; 2016 Oct; 177():255-261.e2. PubMed ID: 27496270
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Disparities by household income and race/ethnicity: the utility of BMI for surveilling excess adiposity in children.
    Weaver RG; Beets MW; Brazendale K; Hunt E
    Ethn Health; 2021 Nov; 26(8):1180-1195. PubMed ID: 30848939
    [No Abstract]   [Full Text] [Related]  

  • 3. Sensitivity and specificity of body mass index and skinfold thicknesses in detecting excess adiposity in children aged 8-12 years.
    Bedogni G; Iughetti L; Ferrari M; Malavolti M; Poli M; Bernasconi S; Battistini N
    Ann Hum Biol; 2003; 30(2):132-9. PubMed ID: 12637189
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DXA-Derived vs Standard Anthropometric Measures for Predicting Cardiometabolic Risk in Middle-Aged Australian Men and Women.
    Zhu K; Walsh JP; Murray K; Hunter M; Hui J; Hung J
    J Clin Densitom; 2022; 25(3):299-307. PubMed ID: 35177350
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Relative Body Mass Index Improves the BMI Percentile Performance for Detection and Monitoring of Excess Adiposity in Adolescents.
    Velasquez-Mieyer PA; Nieto-Martinez R; Neira CP; De Oliveira-Gomes D; Velasquez Rodriguez AE; Ugel E; Cowan PA
    Nutrients; 2024 Feb; 16(5):. PubMed ID: 38474830
    [TBL] [Abstract][Full Text] [Related]  

  • 6. BMI percentiles for the identification of abdominal obesity and metabolic risk in children and adolescents: evidence in support of the CDC 95th percentile.
    Harrington DM; Staiano AE; Broyles ST; Gupta AK; Katzmarzyk PT
    Eur J Clin Nutr; 2013 Feb; 67(2):218-22. PubMed ID: 23232587
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Adding anthropometric measures of regional adiposity to BMI improves prediction of cardiometabolic, inflammatory and adipokines profiles in youths: a cross-sectional study.
    Samouda H; de Beaufort C; Stranges S; Guinhouya BC; Gilson G; Hirsch M; Jacobs J; Leite S; Vaillant M; Dadoun F
    BMC Pediatr; 2015 Oct; 15():168. PubMed ID: 26497052
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Sarcopenic obesity assessed using dual energy X-ray absorptiometry (DXA) can predict cardiovascular disease in patients with type 2 diabetes: a retrospective observational study.
    Fukuda T; Bouchi R; Takeuchi T; Tsujimoto K; Minami I; Yoshimoto T; Ogawa Y
    Cardiovasc Diabetol; 2018 Apr; 17(1):55. PubMed ID: 29636045
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Associations of DXA-measured abdominal adiposity with cardio-metabolic risk and related markers in early adolescence in Project Viva.
    Wu AJ; Rifas-Shiman SL; Taveras EM; Oken E; Hivert MF
    Pediatr Obes; 2021 Feb; 16(2):e12704. PubMed ID: 32761791
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Relationship between indices of obesity obtained by anthropometry and dual-energy X-ray absorptiometry: The Fourth and Fifth Korea National Health and Nutrition Examination Survey (KNHANES IV and V, 2008-2011).
    Kim SG; Ko Kd; Hwang IC; Suh HS; Kay S; Caterson I; Kim KK
    Obes Res Clin Pract; 2015; 9(5):487-98. PubMed ID: 25484303
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Body fat differences among US youth aged 8-19 by race and Hispanic origin, 2011-2018.
    Martin CB; Stierman B; Yanovski JA; Hales CM; Sarafrazi N; Ogden CL
    Pediatr Obes; 2022 Jul; 17(7):e12898. PubMed ID: 35135038
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Body fat reference percentiles on healthy affluent Indian children and adolescents to screen for adiposity.
    Khadilkar AV; Sanwalka NJ; Chiplonkar SA; Khadilkar VV; Pandit D
    Int J Obes (Lond); 2013 Jul; 37(7):947-53. PubMed ID: 23459321
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Relative fat mass assessment estimates changes in adiposity among female older adults with obesity after a 12-month exercise and diet intervention.
    Senkus KE; Crowe-White KM; Locher JL; Ard JD
    Ann Med; 2022 Dec; 54(1):1160-1166. PubMed ID: 35471192
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Is body mass index a useful measure of excess body fatness in adolescents and young adults with Down syndrome?
    Bandini LG; Fleming RK; Scampini R; Gleason J; Must A
    J Intellect Disabil Res; 2013 Nov; 57(11):1050-7. PubMed ID: 22974061
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Cardiometabolic Risk and Body Composition in Youth With Down Syndrome.
    Magge SN; Zemel BS; Pipan ME; Gidding SS; Kelly A
    Pediatrics; 2019 Aug; 144(2):. PubMed ID: 31315916
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Triponderal mass index is as strong as body mass index in the determination of obesity and adiposity.
    Gul Siraz U; Hatipoglu N; Mazicioglu MM; Ozturk A; Cicek B; Kurtoglu S
    Nutrition; 2023 Jan; 105():111846. PubMed ID: 36265325
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The prevalence of metabolically healthy obese subjects defined by BMI and dual-energy X-ray absorptiometry.
    Shea JL; Randell EW; Sun G
    Obesity (Silver Spring); 2011 Mar; 19(3):624-30. PubMed ID: 20706202
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Using weight-for-age percentiles to screen for overweight and obese children and adolescents.
    Gamliel A; Ziv-Baran T; Siegel RM; Fogelman Y; Dubnov-Raz G
    Prev Med; 2015 Dec; 81():174-9. PubMed ID: 26348454
    [TBL] [Abstract][Full Text] [Related]  

  • 19. DXA-measured visceral fat mass and lean body mass reflect abnormal metabolic phenotypes among some obese and nonobese Chinese children and adolescents.
    Ding WQ; Liu JT; Shang YX; Gao B; Zhao XY; Zhao HP; Wu WJ
    Nutr Metab Cardiovasc Dis; 2018 Jun; 28(6):618-628. PubMed ID: 29699814
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Automated body composition estimation from device-agnostic 3D optical scans in pediatric populations.
    Tian IY; Wong MC; Nguyen WM; Kennedy S; McCarthy C; Kelly NN; Liu YE; Garber AK; Heymsfield SB; Curless B; Shepherd JA
    Clin Nutr; 2023 Sep; 42(9):1619-1630. PubMed ID: 37481870
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.