Establishing Regression Parameters to Simplify Determination of Carbohydrate Intolerance Conference Paper uri icon

abstract

  • Determining carbohydrate intolerance (CI) and insulin sensitivity is vital when selecting the proper diet to maximize results and improve health. This study examined answers to a CI questionnaire (CIQ) and simple health measures to develop a quick method to determine accurate prediction, nonprediction models of CI vs. traditional OGTT outcome measures. 108 women (31.613 yrs, 34.77% body fat, 25.34 kg/m2) donated fasting blood samples, completed a CI inventory, had DEXA body composition and health measures determined, and underwent a 75g, 2hr OGTT. Considering previous Pearson correlations, numerous linear regression models were run to build the best prediction model of CI questions plus health measures for OGTT glucose at 120 minutes (G120) and glucose AUC (GAUC). Results revealed that 2 models demonstrated positive associations for total yes responses to 7 CI questions + 3 health measures: experience headaches, fatigue/exhaustion, crave starchy/sugary foods, drowsiness, meal time hunger, eat 3 meals/day, maintain constant extra body wt, age, body wt (kg), and BMI. G120 = 2.649(CI total yes)+0.019(age)1.399(wt)+7.584(BMI), r2=0.949. GAUC = 7.781(CI total yes)+0.248(age)2.16(wt)+14.253(BMI), r2=0.955. The basic 7 question CI inventory alone (total yes responses) also showed a strong association with G120 (r2=0.866) and GAUC (r2=0.880). These findings show promise for simple CI results without an OGTT.

published proceedings

  • FASEB JOURNAL

author list (cited authors)

  • Levers, K., Rasmussen, C., Greenwood, M., Earnest, C., & Kreider, R.

citation count

  • 0

complete list of authors

  • Levers, K||Rasmussen, C||Greenwood, M||Earnest, C||Kreider, R

publication date

  • April 2015

publisher