Validity of the BodyGem calorimeter and prediction equations for the assessment of resting energy expenditure in overweight and obese Saudi males

To assess the accuracy of resting energy expenditure [REE] measurement in a sample of overweight and obese Saudi males, using the BodyGem device [BG] with whole room calorimetry [WRC] as a reference, and to evaluate the accuracy of predictive equations. Thirty-eight subjects [mean +/- SD, age 26.8 +/- 3.7 years, body mass index 31.0 +/- 4.8] were recruited during the period from 5 February 2007 to 28 March 2008. Resting energy expenditure was measured using a WRC and BG device, and also calculated using 7 prediction equations. Mean differences, bias, percent of bias [%bias], accurate estimation, underestimation and overestimation were calculated. Repeated measures with the BG were not significantly different [accurate prediction: 81.6%;%bias 1.1 +/- 6.3, p>0.24] with limits of agreement ranging from +242 to-200 kcal. Resting energy expenditure measured by BG was significantly less than WRC values [accurate prediction: 47.4%;%bias: 11.0 +/- 14.6, p=0.0001] with unacceptably wide limits of agreement. Harris-Benedict, Schofield and World Health Organization equations were the most accurate, estimating REE within 10% of measured REE, but none seem appropriate to predict the REE of individuals. There was a poor agreement between the REE measured by WRC compared to BG or predictive equations. The BG assessed REE accurately in 47.4% of the subjects on an individual level

Performance of body mass index in predicting diabetes and hypertension in the eastern province of Saudi Arabia

Body mass index [BMI] is the most widely used measure to define obesity and predict its complications, such as diabetes and hypertension, but its accuracy and usefulness in Saudi subjects is unknown. This study aimed to assess the validity of standard BMI cut-point values in the Saudi population. 197 681 adults participated in a cross-sectional study to detect diabetes and hypertension in the Saudi Eastern province in 2004/2005, with blood pressure, fasting blood sugar, height and weight measurements taken. Sensitivities, specificities, areas under the curves, predictive values, likelihood ratios, false positive, false negatives and total misclassification ratios were calculated for various BMI values determined from receiver operating characteristic [ROC] curves. The significance of the association between risk factors and BMI was assessed using regression analysis. For the definition of overweight, ROC curve analysis suggested optimal BMI cut-offs of 28.50 to 29.50 in men and 30.50 to 31.50 in women, but the levels of sensitivity and specificity were too low to be of clinical value and the overall misclassification was unacceptably high across all the selected BMI values [>0.80]. The relationship between BMI and the presence of diabetes and/or hypertension was not improved when a BMI of 25 was used. Using regression analyses, the odds ratios for hypertension and/or diabetes increased significantly from BMI values as low as 21-23 with no improvement in the diagnostic performance of BMI at these cutoffs. In Saudi population, there is an increased risk of diabetes and hypertension relative to BMI, starting at a BMI as low as 21 but overall there is no cutoff BMI level with high predictive value for the development of these chronic diseases, including the WHO definition of obesity at BMI of 30