David C. Frankenfield

Limits of body mass index to detect obesity and predict body composition

Body mass index (BMI) is commonly used to identify obesity. In this study, we determined how accurately BMI could determine body composition and identify obese from non-obese individuals. Fat-free mass and body fat were determined with bioelectrical impedance. Adiposity was calculated as body fat per body mass and as body fat divided by body height (m2). Obesity was defined as a BMI of at least 30 kg/m2 or an amount of body fat of at least 25% of total body mass for men and at least 30% for women. Obesity as defined by percentage of body fat was always present with a BMI of at least 30 kg/m2. However, 30% of men and 46% of women with a BMI below 30 kg/m2 had obesity levels of body fat. The greatest variability in the prediction of percentage of body fat and body fat divided by height (m2) from regression equations using BMI was at a BMI below 30 kg/m2. In conclusion, using impedance-derived body-fat mass as the criterion, people with BMI of at least 30 kg/m2 are obese. However, significant numbers of people with a BMI below 30 kg/m2 are also obese and thus misclassified by BMI. Percent of body fat and body fat divided by height (m2) are predictable from BMI, but the accuracy of the prediction is lowest when the BMI is below 30 kg/m2. Therefore, measurement of body fat is a more appropriate way to assess obesity in people with a BMI below 30 kg/m2.

Validation of several established equations for resting metabolic rate in obese and nonobese people

OBJECTIVE To evaluate several equations for predicting resting metabolic rate against measured values in obese and nonobese people. DESIGN Resting metabolic rate was measured with indirect calorimetry. Four calculation standards using various combinations of weight, height, and age were used to predict resting metabolic rate: a) Harris-Benedict equation, b) Harris-Benedict equation using adjusted body weight in obese individuals, c) Owen, and d) Mifflin. Main outcome was percentage of subjects whose calculated metabolic rate was outside a +/-10% limit from measured values. Subjects/Setting 130 nonhospitalized adult volunteers grouped by degree of obesity (range of body mass index, 18.8 to 96.8). Statistical Analysis Performed Analysis of proportions was used to determine differences in the percentage of subjects estimated accurately by each equation; alpha was set at 0.05. RESULTS Calculated resting metabolic rate was more than 10% different from measured in 22% of subjects using the Mifflin equation, 33% using the Harris-Benedict equation (P=.05 vs Mifflin), and 35% using the Owen equation (P<.05 vs Mifflin). The error rate using Harris-Benedict with adjusted weight in obesity was 74% (vs 36% in obese subjects using actual weight in the standard Harris-Benedict equation). APPLICATIONS/CONCLUSION Of the calculation standards tested, the Mifflin standard provided an accurate estimate of actual resting metabolic rate in the largest percentage of nonobese and obese individuals and therefore deserves consideration as the standard for calculating resting metabolic rate in obese and nonobese adults. Use of adjusted body weight in the Harris-Benedict equation led to less overestimation by that equation in obese people at the expense of increased incidence of underestimation.

The Harris-Benedict Studies of Human Basal Metabolism: History and Limitations

In the early part of the 20th century, numerous studies of human basal metabolism were conducted at the Nutrition Laboratory of the Carnegie Institution of Washington in Boston, Mass, under the direction of Francis G. Benedict. Prediction equations for basal energy expenditure (BEE) were developed from these studies. The expressed purpose of these equations was to establish normal standards to serve as a benchmark for comparison with BEE of persons with various disease states such as diabetes, thyroid, and other febrile diseases. The Harris-Benedict equations remain the most common method for calculating BEE for clinical and research purposes. The widespread use of the equations and the relative inaccessibility of the original work highlights the importance of reviewing the data from which the standards were developed. A review of the data reveals that the methods and conclusions of Harris and Benedict appear valid and reasonable, albeit not error free. All of the variables used in the equations have sound physiologic basis for use in predicting BEE. Supplemental data from the Nutrition Laboratory indicates that the original equations can be applied over a wide range of age and body types. The commonly held assumption that the Harris-Benedict equations overestimate BEE in obese persons may not be true for persons who are moderately obese.

Analysis of Estimation Methods for Resting Metabolic Rate in Critically Ill Adults

BACKGROUND Prediction of metabolic rate is an important part of the nutrition assessment of critically ill patients, yet there are limited data regarding the best equation to use to make this prediction. METHODS Standardized indirect calorimetry measurements were made in 202 ventilated, adult critical care patients, and resting metabolic rate was calculated using the following equations: Penn State equation, Faisy, Brandi, Swinamer, Ireton-Jones, Mifflin, Mifflinx1.25, Harris Benedict, Harris Benedictx1.25, Harris Benedict using adjusted weight for obesity, and each of the adjusted weight versions of Harris Benedictx1.25. The subjects were subgrouped by age and obesity status (young nonobese, young obese, elderly nonobese, elderly obese). Performance of each equation was assessed using bias, precision, and accuracy rate statistics. RESULTS Accuracy rates in the study population ranged from 67% for the Penn State equation to 18% for the weight-adjusted Harris Benedict equation (without multiplication). Within subgroups, the highest accuracy rate was 77% in the elderly nonobese using the Penn State equation and the lowest was 0% for the weight-adjusted Harris Benedict equation. The Penn State equation was the only equation that was unbiased and precise across all subgroups. The obese elderly group was the most difficult to predict. Therefore, a separate regression was computed for this group: Mifflin(0.71)+Tmax(85)+Ve(64)-3085. CONCLUSIONS The Penn State equation provides the most accurate assessment of metabolic rate in critically ill patients if indirect calorimetry is unavailable. An alternate form of this equation for elderly obese patients is presented, but has yet to be validated.

Accelerated nitrogen loss after traumatic injury is not attenuated by achievement of energy balance.

BACKGROUND We wanted to determine if achievement of energy balance decreases myofibrillar protein catabolism and nitrogen loss during posttraumatic catabolic illness. METHODS Surgical intensive care unit of a level I trauma center in a university medical center. Trauma patients expected to be mechanically ventilated for at least 4 days were randomly assigned to one of three parenteral feeding groups: (1) nonprotein calorie group: dextrose and lipid intake equal to measured energy expenditure; (2) total calorie group: dextrose, lipid, and protein intake equal to measured energy expenditure; and (3) hypocaloric group: dextrose and lipid intake equal to 50% of measured energy expenditure. Target protein intake for all groups was 1.7 g/kg body wt. On day 4 of nutrition support, a 24-hour balance study was conducted. Urine urea and total nitrogen production, 3-methylhistidine excretion, energy expenditure, and substrate utilization were measured. RESULTS Despite significant differences in nonprotein and total calorie balance among the groups, nitrogen loss, nitrogen balance, and catabolic rate were not significantly different. Nitrogen loss correlated with catabolic rate but not with energy expenditure or energy balance. Catabolic rate was associated with energy expenditure but not with energy balance. Nitrogen loss was positively correlated with the percentage of nonprotein energy expenditure met by nonprotein calorie intake. CONCLUSIONS Achievement of energy balance (nonprotein or total energy) failed to decrease catabolic rate or nitrogen loss acutely in multiple trauma patients. Provision of caloric intake equal to energy expenditure does not seem necessary during the acute phase of posttraumatic catabolic illness.

relationships between resting and total energy expenditure in injured and septic patients

Objective: To quantify resting and total energy expenditure in patients who have suffered severe trauma and sepsis. Design: Prospective, unblinded, observational, nonrandomized study. Setting: Critical care unit of a Level I adult trauma center. Patients: Immediate posttrauma patients or trauma patients exhibiting signs of sepsis with multiple organ dysfunction. Interventions: An indirect calorimeter was used to measure energy expenditure at rest (resting energy expenditure) at 0700 and 1900 hrs. The energy expenditure measurement was then continued for up to 12 hrs (total energy expenditure). Clinical data were collected for computation of an illness severity score. Results: Thirteen trauma and 20 septic patients were studied 240 times. All patients were mechanically ventilated. Morphine or fentanyl was infused during 99% of studies. Neuromuscular blocking agents were used in 42% of septic studies. Both the trauma and septic groups were hypermetabolic (mean trauma resting energy expenditure, 36 ± 6 kcal/kg; mean septic resting energy expenditure, 44 ± 8 kcal/kg; p < .05). Total energy expenditure was similar to resting energy expenditure (trauma total energy expenditure = resting energy expenditure × 1.035 ± 0.078, septic total energy expenditure = resting energy expenditure × 1.039 ± 0.071). Total energy expenditure and resting energy expenditure were linearly related (r2 = .89, p < .0001). Conclusions: Trauma and septic patients are hypermetabolic, even when heavily sedated or medically paralyzed. A measurement of resting energy expenditure is a close approximation of total energy expenditure in most patients. (Crit Care Med 1994; 22:1796–1804)

Correlation Between Measured Energy Expenditure and Clinically Obtained Variables in Trauma and Sepsis Patients

BACKGROUND Indirect calorimetry is the preferred method for determining caloric requirements of patients, but availability of the device is limited by high cost. A study was therefore conducted to determine whether clinically obtainable variables could be used to predict metabolic rate. METHODS Patients with severe trauma or sepsis who required mechanical ventilation were measured by an open-circuit indirect calorimeter. Several clinical variables were obtained simultaneously. Measurements were repeated every 12 hours for up to 10 days. RESULTS Twenty-six trauma and 30 sepsis patients were measured 423 times. Mean resting energy expenditure was 36 +/- 7 kcal/kg (trauma) vs 45 +/- 8 kcal/kg (sepsis) (p < .0001). The single strongest correlate with resting energy expenditure was minute ventilation (R2 = 0.61, p < .0001). Doses of dopamine, dobutamine, morphine, fentanyl, and neuromuscular blocking agents each correlated positively with resting energy expenditure. In the case of the inotropics and neuromuscular blockers, there was a probable covariance with severity of illness. A multiple regression equation was developed using minute ventilation, predicted basal energy expenditure, and the presence or absence of sepsis: resting energy expenditure = -11000 + minute ventilation (100) + basal energy expenditure (1.5) + dobutamine dose (40) + body temperature (250) + diagnosis of sepsis (300) (R2 = 0.77, p < .0001). CONCLUSION Severe trauma and sepsis patients are hypermetabolic, but energy expenditure is predictable from clinical data. The regression equations probably apply only to severe trauma and sepsis. Other studies should be conducted to predict energy expenditure in other patient types.

Validation of 2 approaches to predicting resting metabolic rate in critically ill patients

BACKGROUND Indirect calorimetry is the criterion method for determining resting metabolic rate for nutrition support in critically ill patients. However, calculation equations are more commonly used. In the current study we tested the validity of 2 such calculation systems. METHODS Indirect calorimetry was performed with an open-circuit device in mechanically ventilated surgical, trauma, and medical patients at rest. Feedings were not stopped for the measurements. Two predictive equations by Ireton-Jones and 3 versions of a multivariate equation developed at our institution (referred to as Penn State equations) were then used to estimate resting metabolic rate. These estimates were compared on a percentage basis with the measured value of resting metabolic rate. Estimated resting metabolic rate within 10% of measured was considered accurate, whereas estimations >15% different from measured were considered large errors. RESULTS Forty-seven subjects were measured. A larger percentage of subjects were estimated accurately by the Penn State equations (72% in the best equation) than by the Ireton-Jones equations (60% in the best equation; not significant). The incidence of errors >15% of measured was significantly lower in the Penn State equation (11% of subjects) compared with the Ireton-Jones equation (32% of subjects) (p < .05). CONCLUSIONS The Penn State equation for resting metabolic rate in mechanically ventilated intensive care patients receiving nutrition support appears to be a valid clinical tool for determining energy goals in the absence of or as a supplement to indirect calorimetry. The Ireton-Jones equation performed less well, especially in that a higher number of large errors occurred.

Gut failure : predictor of or contributor to mortality in mechanically ventilated blunt trauma patients ?

UNLABELLED Thirty-seven ventilator-dependent blunt trauma patients (ISS 36 +/- 15) were randomized at 24 hours after injury to receive parenteral (TPN) (n = 15), enteral (TEN) (n = 12), or parenteral plus enteral (PN/EN) (n = 10) nutrition. The TEN and PN/EN patients had endoscopically placed transpyloric feeding tubes. Patients who had nutritional complications were two TPN (13%), three TEN (25%), and five PN/EN (50%). Enteral complications were tube occlusion (two), failed duodenal intubation (one), patient extubation of feeding tube (one), gastric reflux (two), and abdominal distention (two). Mortality rates were not different between the groups, but were significantly related to the nutrition-associated complications (p = 0.01): four deaths in ten (40%) with complications and one death in 27 (3.7%) without complications. All four deaths associated with complications occurred in the four with gastric reflux or abdominal distention. No deaths occurred in the other 18 TEN or PN/EN patients (p = 0.0001). Of the four deaths, three were associated with ARDS and respiratory infection (75%). CONCLUSIONS In mechanically ventilated blunt trauma patients, endoscopic transpyloric tube placement and feeding has a substantial failure rate (36%). Intolerance to duodenal feeding has a remarkably high mortality (100%) in patients in whom gut dysfunction may be a manifestation of injury severity or directly affect survival.

Age-related differences in the metabolic response to injury.

OBJECTIVE To investigate the effect of age on the metabolic response to injury. METHODS Fifty-two trauma patients meeting entrance criteria were prospectively enrolled. Patients were grouped by age: elderly, >60 years; and young, < or =60 years. After 4 days of nutrition support, physiologic and laboratory data were collected. Energy and nitrogen metabolism, and body composition were evaluated. RESULTS Elderly patients demonstrated a reduced incidence of fever (48% vs. 77%,p = 0.027). Independent of body composition, temperature, and injury severity, oxygen consumption was 8% lower in the elderly (p = 0.0032). However, nitrogen loss and myofibrillar catabolic rate was not altered by age. Elderly subjects were more often hyperglycemic (38% vs. 0%, p < 0.0001) and azotemic (62% vs. 22%, p = 0.004), despite similar carbohydrate and protein intake. CONCLUSION Fever is less common and oxygen consumption lower in elderly trauma patients. Postinjury myofibrillar protein catabolism and nitrogen loss are not influenced by aging. Metabolic complications of nutrition support (hyperglycemia, azotemia) are more common in elderly trauma patients.