M M Tai1. 1. Obesity Research Center, St. Luke's-Roosevelt Hospital Center, New York, New York.
Abstract
OBJECTIVE: To develop a mathematical model for the determination of total areas under curves from various metabolic studies. RESEARCH DESIGN AND METHODS: In Tai's Model, the total area under a curve is computed by dividing the area under the curve between two designated values on the X-axis (abscissas) into small segments (rectangles and triangles) whose areas can be accurately calculated from their respective geometrical formulas. The total sum of these individual areas thus represents the total area under the curve. Validity of the model is established by comparing total areas obtained from this model to these same areas obtained from graphic method (less than +/- 0.4%). Other formulas widely applied by researchers under- or overestimated total area under a metabolic curve by a great margin. RESULTS: Tai's model proves to be able to 1) determine total area under a curve with precision; 2) calculate area with varied shapes that may or may not intercept on one or both X/Y axes; 3) estimate total area under a curve plotted against varied time intervals (abscissas), whereas other formulas only allow the same time interval; and 4) compare total areas of metabolic curves produced by different studies. CONCLUSIONS: The Tai model allows flexibility in experimental conditions, which means, in the case of the glucose-response curve, samples can be taken with differing time intervals and total area under the curve can still be determined with precision.
OBJECTIVE: To develop a mathematical model for the determination of total areas under curves from various metabolic studies. RESEARCH DESIGN AND METHODS: In Tai's Model, the total area under a curve is computed by dividing the area under the curve between two designated values on the X-axis (abscissas) into small segments (rectangles and triangles) whose areas can be accurately calculated from their respective geometrical formulas. The total sum of these individual areas thus represents the total area under the curve. Validity of the model is established by comparing total areas obtained from this model to these same areas obtained from graphic method (less than +/- 0.4%). Other formulas widely applied by researchers under- or overestimated total area under a metabolic curve by a great margin. RESULTS: Tai's model proves to be able to 1) determine total area under a curve with precision; 2) calculate area with varied shapes that may or may not intercept on one or both X/Y axes; 3) estimate total area under a curve plotted against varied time intervals (abscissas), whereas other formulas only allow the same time interval; and 4) compare total areas of metabolic curves produced by different studies. CONCLUSIONS: The Tai model allows flexibility in experimental conditions, which means, in the case of the glucose-response curve, samples can be taken with differing time intervals and total area under the curve can still be determined with precision.
Authors: Faidon Magkos; David Bradley; J Christopher Eagon; Bruce W Patterson; Samuel Klein Journal: Am J Clin Nutr Date: 2015-11-25 Impact factor: 7.045
Authors: Melissa A Linden; Justin A Fletcher; E Matthew Morris; Grace M Meers; M Harold Laughlin; Frank W Booth; James R Sowers; Jamal A Ibdah; John P Thyfault; R Scott Rector Journal: Med Sci Sports Exerc Date: 2015-03 Impact factor: 5.411
Authors: Melissa A Linden; Justin A Fletcher; E Matthew Morris; Grace M Meers; Monica L Kearney; Jacqueline M Crissey; M Harold Laughlin; Frank W Booth; James R Sowers; Jamal A Ibdah; John P Thyfault; R Scott Rector Journal: Am J Physiol Endocrinol Metab Date: 2013-12-10 Impact factor: 4.310
Authors: T Kasperska-Czyzyk; K Jedynasty; R R Bowsher; D L Holloway; I Stradowska; K Stepień; R Nowaczyk; W Szymczak; A Czyzyk Journal: Diabetologia Date: 1996-07 Impact factor: 10.122
Authors: Barbara J Nicklas; Xuewen Wang; Tongjian You; Mary F Lyles; Jamehl Demons; Linda Easter; Michael J Berry; Leon Lenchik; J Jeffrey Carr Journal: Am J Clin Nutr Date: 2009-02-11 Impact factor: 7.045
Authors: Eliete J B Bighetti; Patrícia R Patrício; Andrea C Casquero; Jairo A Berti; Helena C F Oliveira Journal: Lipids Health Dis Date: 2009-11-23 Impact factor: 3.876
Authors: Ghattu V Krishnaveni; Sargoor R Veena; Jacqueline C Hill; Sarah Kehoe; Samuel C Karat; Caroline H D Fall Journal: Diabetes Care Date: 2009-11-16 Impact factor: 19.112