Article Review Essay

Disease state such as Overweight and obese has become a significant concern in the developing countries. Obesity experienced in litigation of an extra adipose tissue in the body. Since the indirect calorimeter is not daily available for approximating energy requirements, many predicting equations have undergone improvised to rate this energy. Of recent, obese patients are at an alarming rate in the patient population. They do require nutritional support. In order to achieve this nutritional help, the resting energy expenditure of the patients is the most fundamental goal to examine. This helps to provide enough calories prevent the muscle eat up and hinder lack of minerals in the body.

Indirect calorimetric and anthropometry

These readings carried out using the Deltatrac metabolic monitor. It went through regulation on a daily basis before working on it. The patient was in a straight position and not asleep. The readings were in a semi-standard way that went hand in hand with the indirect calorimetric measurements. Those sick did not eat regularly during the measuring period. The readings then carried out at a standard neutral hospital room temperature. Oxygen intake and carbon dioxide released measured and energy use calculated by the weir formula (Moshe, et al 2006 P 973). The activity occurred for about 30 minutes. The use of calibrated electronic stand-up scale assisted in obtaining the weight of the body. Sex, age and the weight of the sick determined through interaction with the patient.

Harris-Benedict Equations

This is the most commonly used technique for obtaining energy use. In order, to change its accuracy stress factors should join hand. In this case, the body weight becomes the first variable. It becomes exact only when the body is in its normal state and when the body fat content is high the predictions become inaccurate. For obese patient’s body, weights undergo change for it to be effective in the equations. Illness and injuries increasingly complicated the estimations of energy requirements. It based largely on the healthy individuals. In the University of California, for example 65 men and 100 women found possessing the BMIs over 30. Measured energy use then divided by an estimated energy expenditure using the HB problem and the Cunningham equation to find the stress factor for injury and illness. They assumed that the stressed factors in most disease categories are in the set of 1.6 to 2.0.

REE Predictive Equations

It employed the concordance correlation coefficient to illustrate the use and the reliability of the forecasting equations. To obtain the CCC, we compute precision with accuracy. When, one foresees a range of 95% – 105%, he would consider it a fair prediction. In addition, a prediction below that value could be viewed as underestimation but above it became overestimation.

Inclusion based on age, sex, weight, and height

The exclusion process had the following, which considered only the youths or the elderly (Peckenpaugh, 2010 P 601). For every study, equations are performed with respect to the high values of explained variance. However, additional equations are also fixed when weight and height come together. The average percentage of REE predictions exhibits a measure of truth on a group standard.

Therefore, the HB problem is the most commonly used predicative case. This is due to its trained personnel. In addition, it can use other clinical conditions such as the presence of chest tubes, which could otherwise be impossible for the calorimetric measurements.