JACN Did you know that you can get alerts when a new issue is online?
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Cole, C. R.
Right arrow Articles by Lifshitz, F.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Cole, C. R.
Right arrow Articles by Lifshitz, F.
Journal of the American College of Nutrition, Vol. 18, No. 3, 233-241 (1999)
Published by the American College of Nutrition

Original Paper

Comprehensive Assessment of the Components of Energy Expenditure in Infants Using a New Infant Respiratory Chamber

Conrad R. Cole, MD, Russell Rising, PhD, Amin Hakim, MD, Marco Danon, MD, Rajeev Mehta, MD, Shahana Choudhury, MD, Mamatha Sundaresh, MD and Fima Lifshitz, MD

Maimonides Medical Center, Department of Pediatrics, 4802 Tenth Ave (C.R.C., R.R., A.H., M.D., R.M., M.S., F.L.), Interfaith Medical Center, Department of Pediatrics, 1545 Atlantic Ave (S.C.), Brooklyn, New York


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Current methods for energy expenditure (EE) measurements in term infants do not include simultaneous measurements of basal and sleeping metabolic rates (BMR and SMR) or a measure of physical activity (PA). Furthermore, prediction equations for calculating EE are not appropriate for use in infants with metabolic disorders.

Objective: To develop and utilize a new infant respiratory chamber for simultaneous measurements of EE (kJ/d), preprandial BMR (kJ/d), SMR (kJ/d) and an index of PA (oscillations/min/kg body weight) in infants with a variety of metabolic disorders, for up to four hours in a hospital setting, while allowing parental interaction in a comfortable environment.

Methods: We obtained simultaneous measurements of EE, BMR, SMR and PA in 21 infants (66±73 days of age, 4.5±1.7 kg body weight, 55±8 cm in length and 16±7% body fat) using our new infant respiratory chamber. Six of these infants were healthy, seven had thyroid dysfunction, five were HIV-exposed, one had AIDS, one had intrauterine and postnatal growth retardation and one was a hypothermic preterm infant. Energy expenditure, BMR and SMR were extrapolated for 24 hours. Body composition was estimated by skin-fold thickness, using age-appropriate formulae. Basal metabolic rate obtained with the infant respiratory chamber was compared to BMR that was calculated using the appropriate World Health Organization (WHO) equations.

Results: In all infants both extrapolated 24-hour EE and BMR correlated with fat-free mass (r=0.89, p<0.01 and r=0.88, p<0.01 respectively). Twenty-four hour EE also correlated with PA (r=0.52, p<0.05). The HIV-exposed infants had higher BMR (p<0.05) than that calculated by the appropriate WHO equation. We found that the caloric requirements for the infant with growth retardation were underestimated based on the infant’s weight and age.

Conclusions: The infant respiratory chamber can measure all of the main components of EE. Some of the results obtained differed significantly from those obtained by the WHO equations; therefore, the new infant respiratory chamber is necessary for estimating EE in infants with metabolic and growth disorders.

Key words: Energy expenditure, infants, basal metabolic rate, physical activity, HIV, thyroid dysfunction, intra-uterine growth retardation


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Equations to predict resting energy needs are frequently used for clinical care of children with metabolic disorders, even though they were designed to estimate the energy requirements of healthy individuals [1–6]. These equations have been shown not to be as accurate as measurements obtained using indirect calorimetry [7,8]. This is partly due to variable factors involved in energy expenditure, such as physical activity [6], body temperature [9], fat-free mass [6,10,11], fat mass and gender [12]. Paucity of data in infants further limits the application of these equations.

The use of indirect calorimetry in the study of energy requirements dates back to the end of the nineteenth century [13]. With computerization, the methods used have become increasingly more accurate. However, indirect calorimetry has several limitations, and only total energy expenditure is measured in infants. It has been suggested that the resting energy expenditure is nearly impossible to measure in healthy children who weigh less than eight kg, using available techniques, because these children cannot remain at rest or in fasting conditions before and during the test [14]. We have developed an infant respiratory chamber for measurements of energy expenditure (EE), basal metabolic rate (BMR), sleeping metabolic rate (SMR) and an index of physical activity (PA), while allowing parents to interact with their infants in a comfortable environment. The purpose of this study was to [1] determine the feasibility of measuring the main components of EE in infants using the infant respiratory chamber in a hospital setting and (2) compare the results obtained in the infant respiratory chamber with those calculated using the World Health Organization formula.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Subjects
Twenty-one infants (10 males and 11 females) with ages ranging from seven to 336 days were studied between April and December, 1996. These were patients that were referred to our metabolic laboratory during this time period. The pertinent anthropometric and clinical variables for the patients are shown in Table 1. The nature, purpose and possible risks of the study were carefully explained to the parents before consent was obtained. The study was approved by the Institute Review Board (IRB) of Maimonides Medical Center.


View this table:
[in this window]
[in a new window]
  		Table 1. Clinical Status, Physical Characteristics and Thyroid Hormone Levels of the Infants in Each Patient Group1

 
Among the 21 subjects, there were six healthy infants recruited from the pool of infants born at Maimonides Medical Center (MMC), Brooklyn, New York, and attending the well-baby clinic for routine assessment. Inclusion was based on the facts that the parents had no known medical conditions, pregnancy was uncomplicated, delivery was at term and uncomplicated, except for one infant, and the infants were of appropriate size for gestational age [15]. These infants had dried blood specimens obtained on the second or third day of postnatal life as part of the screening for congenital alterations required by New York State. The infants were thriving appropriately and were deemed healthy by a pediatrician on routine examination. One of these patients was being exclusively breast fed, one was exclusively bottle fed, while four were fed formula and human milk.

Seven infants with thyroid dysfunction were included in the study. These infants had dried blood specimens obtained on the second or third day of postnatal life as part of the screening for congenital alterations required by New York State. Their total serum thyroxine (T4) levels by radioimmunoassay (RIA) were below the tenth percentile of the mean; thus, they were also tested for thyroid stimulating hormone (TSH) level. These results were reported to their pediatricians, who then referred the patients to the pediatric endocrine center of Maimonides Medical Center for diagnostic assessment. At that time, their thyroid hormone levels were reevaluated, and they were referred for EE studies. The serum TSH, total triiodothyronine (T3) and T4 levels on the day of the study, along with their final clinical diagnoses, are presented in Table 2. None of these infants had started treatment for hypothyroidism at the time of the EE studies. These seven patients on examination were growing normally and had no obvious symptoms or signs of hypothyroidism. All were being fed breast and milk formula.


View this table:
[in this window]
[in a new window]
  		Table 2. Thyroid and Basal Metabolic Rate Results in the Infants with Thyroid Dysfunction

 
Six infants, whose mothers were infected with the human immunodeficiency virus (HIV), were also included in the study. Of this group of infants, all were HIV seropositive, but only one had AIDS according to the CDC criteria at the time of the study [16]. At the time of the study, the seropositive infants were healthy and growing normally. The infant with AIDS had presented with and was being treated for Pneumocystis carinii pneumonia and failure to thrive at the time of the EE measurement. He was receiving trimethoprim-sulfamethoxazole, azidothymidine (AZT) and dideoxyinosine (ddI) along with 300 kJ/kg body weight of Alimentum® (Ross Products Division, Columbus, Ohio) daily. The five HIV-exposed infants were asymptomatic and growing normally.

Two infants were referred by the neonatology unit for EE measurements. The first infant, delivered preterm at 32 weeks of gestation, had persistent hypothermia of unknown cause with core body temperature less than 34°C (93°F). Septicemia and hypothyroidism as causes of hypothermia had been ruled out. This patient was growing well. The second infant was delivered at term, had intrauterine growth retardation of unknown cause and was growing poorly despite apparently adequate nutrition providing 418 kJ/kg/day. The parents of these two infants had no known medical conditions, and pregnancy and delivery were uncomplicated.

Experimental design
Energy expenditure of the infants was measured for up to four-hours (2.2 to 4.0 hours) by indirect calorimetry using a new infant respiratory chamber. The infants were monitored by one investigator (C.R.C.) for the entire period and an activity log sheet was kept. The activity log determined the amount of time the infant was sleeping, awake and not ingesting formula, playing with toys and the amount of time the infant was crying. This information was necessary for calculating BMR and SMR. The weight and volume of formula consumed by the infant during the period of the study were recorded. Energy expenditure was continuously calculated during the study according to the method of Ravussin et al. [6]. Basal metabolic rate was equal to the sum of all the EE that was calculated while the infant was awake, in a post absorptive state (one to two hours after the last meal, depending on the feeding routine of the infant) and when there was a low index of physical activity. The infant’s state of awakeness was determined by the same investigator by direct observation throughout the study. Sleeping metabolic rate was calculated as previously described [6], but with the following modifications: sleeping metabolic rate was the sum of all the EE calculated during periods of sleep as determined by the investigator through direct observation and by the low index of physical activity. The index of physical activity was calculated by dividing the sum of one-minute oscillations by the infant’s body weight in kilograms. An average of these one minute summaries was determined every five minutes. A low index of physical activity was defined as fewer than 1.4 oscillations/min/kg. Energy expenditure, BMR and SMR were extrapolated for 24 hours and predicted BMR was calculated using appropriate-age WHO equations [4].

Anthropometric measurements of weight, supine length and skin-fold thickness at the subscapular, triceps and flank sites were made on the day of the study. Body weight was the mean of three measurements with an infant scale (Detecto Scales, Inc., Brooklyn, New York). Supine lengths (crown-to-heel) were measured in duplicate with a horizontal stadiometer (Perspective Enterprises, Kalamazoo, Michigan). Skin-fold thickness was the mean of three measurements on the right side of the body using a Lange skin fold caliper (Beta Technology, Cambridge, Maryland) according to standard procedure [17]. All of these measurements were done by the same investigator. Body fat and fat-free mass (FFM) were calculated using equations appropriate for neonates [18] and infants older than one month [19]. Blood samples were drawn for thyroid function tests (T3, T4 and TSH) from all of the infants on the day of the test (results shown in Table 1). Serum T4 level was measured by radioimmunoassay (Diagnostic Products Corporation, Los Angeles, California) while T3 and TSH were measured using chemiluminescent enzyme immunoassay (Immulite® Diagnostic Products Corporation, Los Angeles, California). These were measured at the Pediatric Endocrinology Laboratory at MMC. Reference normal values used by our laboratory are previously described [20]. T-lymphocyte profile and quantitative polymerase chain reaction (PCR) for viral load (SmithKline Beecham Clinical Laboratories) were obtained on the day of the study from the HIV-exposed infants and two weeks before the study in the infant that had AIDS.

Infant Respiratory Chamber
A small plexiglass enclosure measuring one meter3 was used as part of the infant respiratory chamber for infants weighing more than two kilograms (Fig. 1). The plexiglass enclosure for infants weighing less than two kg measured 53x28x38 cm. A portable instrument rack housed the oxygen and carbon dioxide analyzers, flow meter, barometric pressure, temperature and humidity sensors, electric eye controller and computer equipment. The chamber was designed to allow for the storage of formula, diapers and medical supplies necessary for the care of the infant during the study. One unique feature incorporated into the chamber were long rubber gloves installed in six port holes around the entire enclosure. This allowed access to the infant for normal care and medical procedures without corrupting the environment within the chamber. The volume occupied by the gloves during use was corrected for with the aid of an electric eye (Photoswitch® 42GRR/GRL-9000, Allen Bradley, Dominican Republic) whenever its beam was broken by the gloves. The electric eye consisted of two parts (the light source and the receiver), which were positioned so that the infant did not accidentally break the beam. The gloves were stored flat against the outside chamber wall to prevent a similar problem whenever not in use. Only two of the gloves were in use at any one time. To determine the volume displaced by the gloves, ten faculty members within our department placed their arms, up to approximately six inches from the shoulder, in a calibrated bucket of water at room temperature. We found an average water displacement of six liters and incorporated this figure into our software to correct for the volume displaced by the gloves while in use.



View larger version (131K):
[in this window]
[in a new window]
  		Fig. 1. Infant respiratory chamber and related instrumentation. Note the glove ports surrounding the plexiglass enclosure, allowing for parental interaction.

 
Room air was pulled through the chamber and exhausted to the outside via a fan mounted in the exhaust line of the chamber enclosure. The temperature of the air within the chamber could be increased by heaters mounted underneath the enclosure. However, cooling was provided by increasing the air flow rate though the enclosure. Oxygen and carbon dioxide concentrations, flow rate, chamber temperature, barometric pressure and humidity were measured continuously on the exhaust side of the system. Oxygen and carbon dioxide concentrations were determined using two-channel differential analyzers (Hartmann & Braun, Frankfurt, Germany). One channel served as the reference (room air) while the other measured oxygen and carbon dioxide concentrations within the chamber. This allowed for continuous correction of changes in oxygen and carbon dioxide concentrations within the room. The analyzers were sensitive to 0.001%, allowing for measurements of oxygen and carbon dioxide concentrations without the need for large decreases in oxygen or increases in carbon dioxide within the chamber. Barometric pressure, temperature and relative humidity were measured using probes within the exhaust line. Relative humidity, temperature and barometric pressure readings were used to correct the flow rate though the chamber to standard (STPD) conditions. Moisture in the sample air for the oxygen and carbon dioxide analyzers was removed by a sample gas cooler (Hartmann & Braun, Frankfurt, Germany).

Another unique feature was the installation of a Mettler® balance (Model PMK-30, Mettler-Toledo AG, Greifensee, Switzerland). This balance has a continuous digital output which was used for accurate detection and recording of physical activity. A special platform rested on the balance and all infant movements were read as oscillations in weight by the computer. The sensitivity of readouts were adjusted to provide negligible output while the infant was still. The computer software eliminated any period of physical activity when the parents or hospital staff interacted with the infant.

To validate the system we conducted five propane combustion tests in the larger of the two chamber enclosures. We measured oxygen consumption, carbon dioxide production and the respiratory quotient of a known amount of propane (99.2% pure) for four hours. We compared our results to the theoretical values calculated for the amount of propane combusted.

Statistical Analysis
Data were analyzed using the procedures of SPSS software (SPSS Inc, Chicago, IL). Differences between measured and estimated BMR were determined by paired t test in each patient group. Energy expenditure, BMR, SMR, respiratory quotient and physical activity were correlated with body weight, FFM, body fat content, age, thyroid hormones and thyroid stimulating hormone using Pearson correlations. Significant differences were determined at the 5% level of probability (p<0.05). All results are presented as mean±standard deviation except where noted.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
We validated the infant respiratory chamber by conducting five propane combustion tests. In comparison to the theoretical values calculated for a known amount of propane, oxygen and carbon dioxide ventilation rates were overestimated by 6.9±2.4% and 2.8±1.5%, respectively, while the respiratory quotient was underestimated by 3.6±1.9%.

Energy expenditure measured during the study and BMR correlated with FFM (Fig. 2). Sleeping metabolic rate and extrapolated 24-hour EE also correlated with FFM (r=0.91; p<0.01 and r=0.89; p<0.01, respectively, data not shown). Twenty-four hour EE also correlated with PA (r=0.52, p<0.05) (data not shown).



View larger version (18K):
[in this window]
[in a new window]
  		Fig. 2. Correlation between energy expenditure during the test (top plot) and basal metabolic rate (bottom plot) with fat-free mass for all 21 infants. Regression line is the line of best fit determined by regression analysis.

 
During the course of each infant study, EE fluctuated with lower levels observed during sleep. Patient #1 demonstrates that during sleep, physical activity and EE were at the lowest levels (Fig. 3). The converse was also true. Fig. 4 shows the relationship between EE and physical activity for the same infant over the course of the entire EE measurement. Within the confines of the chamber, spontaneous physical activity measured by oscillations/minute/kg of body weight varied widely in the 21 subjects. The mean index of physical activity among individual patients ranged from 0.48 to 9.33 oscillations/minute/kg of body weight (Table 3). There were no differences in RQ between the healthy and any of the patient groups studied.



View larger version (25K):
[in this window]
[in a new window]
  		Fig. 3. Uncorrected index of physical activity (top plot) and energy expenditure (bottom plot) for one infant (Patient #1) over the course of the energy expenditure measurement within the infant respiratory chamber. Large black marks represent the time when parents were interacting with the infant.

 


View larger version (18K):
[in this window]
[in a new window]
  		Fig. 4. Correlation between energy expenditure during the test for one infant (Patient #1) and the index of physical activity. Each data point is the average of five one-minute summaries as described in the text. All data points for this patient are represented. Regression line is the line of best fit determined by regression analysis.

 

View this table:
[in this window]
[in a new window]
  		Table 3. Components of Energy Expenditure in our Patient Groups1

 
In the healthy newborn babies, no significant difference existed between BMR, measured using the infant respiratory chamber, and that calculated by the appropriate WHO equation (Table 3). The babies’ measured BMR, SMR and extrapolated 24-hour EE correlated with FFM (r=0.85; p<0.05, r=0.90; p<0.05 and r=0.91; p<0.05 respectively, data not shown). These infants had normal thyroid function as shown by their normal serum TSH and thyroid hormone levels (Table 1). They were observed to sleep for a mean of 50% of the time spent in the chamber (Table 3).

No significant difference existed between the BMR measured in the group of infants with thyroid dysfunction and that estimated using the WHO equation. All but one infant had measured BMR greater then that estimated by the appropriate WHO equation. Measured BMR in the one infant was half that calculated by the appropriate WHO equation. This infant had slightly elevated TSH (10 µIU/ml) and T4 (9.6 µg/dl) levels. The measured BMR, SMR and 24-hour EE in this group correlated with FFM (r=0.94; p<0.01, r=0.97; p<0.01 and r=0.97; p<0.01, data not shown). All but one of the infants were over nine days of age. All except one infant had serum TSH levels greater than 4.8 µIU/ml (Table 2). The nine-day-old infant had slightly higher then normal T4 levels. Four of them were diagnosed with transient hypothyroidism of infancy and three were diagnosed with congenital hypothyroidism. Two of the infants with congenital hypothyroidism had dysgenetic gland while one had dyshormonogenesis (Table 3).

In the HIV-exposed infants, the measured BMR was higher (p<0.05) than that calculated by the WHO equation and that measured in the healthy babies. Their measured BMR, SMR and extrapolated 24-hour EE also correlated with FFM (r=0.99; p<0.01, r=0.98; p<0.01 and r=0.97; p<0.05, data not shown). These infants had normal thyroid function. The child with AIDS slept the least and had the lowest physical activity of all the infants in the study (Table 3).

The preterm hypothermic infant had normal thyroid function. The EE measured in this infant was higher than that calculated using the WHO equation. The physical activity of the preterm hypothermic infant measured during the study was similar to that in the healthy group of infants (Table 3).

In order to illustrate the clinical application of the chamber, the infant with intrauterine and postnatal growth retardation (Infant #10: 15 days old, 1.3 kg body weight and 3% fat) had two measurements of EE twelve days apart. The extrapolated 24-hour EE and BMR of 515 and 556 kJ/d, respectively, on the first measurement were much higher than the calculated BMR (WHO) of 139 kJ/d (Table 4). Intake was increased to 669 kJ/d which is approximately 23% greater than the BMR of 556 kJ/d, and the patient was monitored by daily measurements of weight and length. During the second measurement, extrapolated 24-hour EE and BMR were 615 and 657 kJ/d, respectively. These results were still higher than that calculated by the WHO equation (246 kJ/d).


View this table:
[in this window]
[in a new window]
  		Table 4. The Components of Energy Expenditure in the Infant with Intrauterine and Postnatal Growth Retardation (Infant #10)

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
This infant respiratory chamber was developed to measure the main components of energy expenditure in infants in a clinical setting. Unique features are measurement of the physical activity index and parental interaction. The major advantage is that parents can interact with their infant anytime during the energy expenditure measurement. By measuring energy expenditure and spontaneous physical activity over time in the chamber, the overall energy expenditure can be divided into its components [6]. In agreement with others [7,8] we found that energy expenditure, estimated by the WHO equations, is not adequate for use in infants with metabolic disorders, hence the need for the infant respiratory chamber for determining metabolic profiles in infants.

This is the first study in term infants using the infant respiratory chamber which measures the main components of energy expenditure. When compared with the methods presently used for measuring energy expenditure for clinical purposes (metabolic cart and the doubly-labeled water method), this method is more practical for getting a realistic estimate of energy expenditure and its components in healthy infants and in infants with metabolic disorders. In our experience and that of others, getting a child less than five years old to cooperate during a basal metabolic rate measurement using the Deltatrac metabolic monitor involves either sedation or attempting to conduct measurements after the child has fallen asleep. There are a few disadvantages of the doubly labeled water method. First, it requires an isotope-ratio mass spectrophotometer; second, the stable isotope of oxygen is expensive; third, it is time consuming (7 to 14 days are needed). For these reasons it is not practical or economical for use in a hospital or clinic setting to assist physicians in determining the caloric requirement of infants.

The infant respiratory chamber provides an accurate measure of energy expenditure. We validated the methodology by conducting five propane calibration tests using instrument-grade propane as our standard. The respiratory quotient and the ventilation rate of carbon dioxide were within five percent of that calculated for propane. The ventilation rate of oxygen was slightly higher and may have been due to the sample cooler’s not removing all of the moisture in the air. These results are similar to those obtained in other studies [6,22,23].

Our estimates of the components of energy expenditure are reliable in spite of the short duration of measurements. The duration of measurements was limited to four hours by the Institute Review Board and by the limited availability of the parents. Some infants’ feeding-sleeping routines, in the age range studied, are every two to four hours [21]. We observed in our study population that they fed-slept and aroused themselves at least once, and sometimes twice, during the measurement period. Based on these observations and the fact that our normal infants had BMR measurements similar to that calculated by the appropriate WHO equation, we feel that we are obtaining a value close to the "real" BMR of the infant. To try to eliminate the thermic effect of food on basal metabolic rate, we waited for one hour of adjustment to the chamber before logging any periods for calculation of basal metabolic rate. However, there was still a possibility of some thermic effect of food in some of the infants studied, and this may account for some of the variability we found in our basal metabolic rate measurements.

In agreement with other studies, energy expenditure and BMR showed a correlation with fat-free mass [10–12]. This further validates our method and shows that fat-free mass is the best predictor of energy expenditure in infants [11,24]. However, when energy expenditure during the study for the entire cohort was plotted against fat-free mass (Fig. 2), 12% of the variance in energy expenditure among the infants was unaccounted for by differences in fat-free mass. This is similar to the variance observed in adults [6], and it can be concluded that, at any given range of fat-free mass, it is possible to find subjects who deviate above or below the regression line. It has been suggested that greater than 50% of the variability in BMR unexplained by differences in fat-free mass, age and gender is due to familial differences [24]. Compositional changes in fat-free mass contribute to its increased metabolic rate seen during infancy. These changes include relative losses of extracellular fluid and increases in body cell mass [25].

Alemzadeh and colleagues [26] observed hypometabolic states in infants with elevated TSH (>7 µU/ml) in spite of normal serum concentrations of thyroxine and triiodothyronine. Our infants had normal thyroid hormone values and were not hypometabolic. This includes the one infant that had normal levels of thyroid stimulating hormone. This suggests a normal thyroid state at the cellular level. One reason for not finding a lower-than-average BMR in our infants with thyroid dysfunction, versus that found by Alemzadeh and colleagues [26], may be due to the age difference between the two groups of infants. The average age of their thyroid dysfunction infants was 25 days while ours was 42 days. It is possible that increasing age may alter the effect that TSH/T4 has on energy metabolism. The one infant that was hypometabolic, as compared to the WHO measure, was the youngest and had the lowest body weight of the group. This same infant also had higher than normal thyroid-stimulating hormone levels along with a slightly lower thyroxine level for age. It is possible that young infants with abnormally high thyroid-stimulating hormone levels may be hypometabolic, even though the thyroxin levels are not in the hypothyroid range. However, this effect may be reversed in older infants of greater body weight.

What then is the reliability of indirect calorimetry as a marker of euthyroid and hypothyroid states in patients with elevations of serum thyroid stimulating hormone? The BMR measured by indirect calorimetry may help identify those infants whom there is an impact of insufficient thyroid hormone on the resting cellular metabolism. Almost 40% of total energy consumption in resting and fasting individuals is regulated by thyroid hormones [27].

The difference seen between our measured and estimated BMR in the one infant that had symptomatic AIDS is similar to that seen in adults [28,29]. This increase in energy expenditure is likely due to the production of tumor necrosis factor- (TNF-alpha) and/or interleukin-1 [30–32]. Another possible cause is opportunistic infection, which had already been treated in this infant. Activity is not the cause of the increased energy expenditure because, as shown in this study, this infant had the lowest physical activity. The cause of increased BMR in HIV-exposed, asymptomatic infants is unknown. In our study, the small number of patients makes it difficult to determine the relationship between HIV status and BMR. In evaluating the differences between the BMR of HIV-exposed infants and the healthy babies in the study population, BMR was not standardized for fat-free mass due to the small size of the group.

In response to concern by the physicians, energy expenditure was measured in the infant with hypothermia. Similarly to some of the infants in the study, BMR was higher than that calculated by the appropriate WHO equation. This provided the physicians with a metabolic profile by which to determine future nutritional intervention.

The infant with intrauterine growth retardation had two energy expenditure measurements twelve days apart. He was referred to the Nutrition and Body Composition Laboratory at the age of 14 days because, despite a calculated dietary intake of 543 kJ/d, the weight gain was far less than that expected [33,34]. Energy expenditure measurements obtained using the infant respiratory chamber showed that the infant’s measured BMR and 24-hour energy expenditure were much higher than that calculated by the appropriate WHO equation. A measured respiratory quotient of 1.03 implies that lipogenesis is occurring and may be due to catch-up growth. At the second measurement (age 26 days), the infant had gained 430 grams and about two cm in length, making the weight gain after the increase in caloric intake appropriate [34]. The second energy expenditure measurement was acceptable, showing a decrease in basal metabolic rate/kg body weight. Further adjustments were made in the diet based on the energy expenditure results. The infant was discharged and is doing well.

The decline in BMR relative to weight or FFM seen during childhood is due to the slower growth of organs with high metabolic rates (e.g., brain, liver and kidney) relative to those with lower metabolic rates (e.g., muscle and bone) [25]. This patient example illustrates that the infant respiratory chamber can be used as a practical clinical tool. Additionally, when patients are referred for measurements of energy expenditure, the results with recommendations can be provided to the clinician promptly.

Our findings suggest that the new infant respiratory chamber can be used to measure the main components of energy expenditure in term infants in a clinical setting. This method has proved to be an accurate and practical clinical tool for estimating caloric requirements in infants with metabolic disorders whose energy expenditure is significantly different from that calculated using the WHO equations. In this study, individual variation in 24-hour energy expenditure and BMR was largely the result of individual differences in fat-free mass. However, 24-hour energy expenditure also varied among individuals because of differences in spontaneous physical activity.


   ACKNOWLEDGMENTS
 
We thank the Maimonides Research and Development Foundation for its generous support of this research. We also thank the families of the infants who volunteered their time and participated in our study. We are grateful to Dr. Solomon Freidman and Ms. Debra Brown for their assistance with the study.


   FOOTNOTES
 
Research supported by the Maimonides Research and Development Foundation.

New address for Conrad R. Cole MD, Russell Rising PhD, Marco Danon MD, and Fima Lifshitz MD: Miami Children’s Hospital, 3100 S.W. 62nd Avenue, Miami, FL 33155.

Address reprint requests to: Reprints not available.

Received October 1, 1998. Accepted February 1, 1999.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Harris JA, Benedict FG: "A Biometric Study of Basal Metabolism in Man." (Publication No. 279.) Washington, DC: Carnegie Institute of Washington, 1919.
  2. Boothby WM, Berkson J, Dunn HL: Studies of the energy metabolism of normal individuals: a standard for basal metabolism with a nomogram for clinical application. Am J Physiol 116: 468–84, 1936.[Free Full Text]
  3. Talbot FB: Basal metabolism standards for children. Am J Dis Child 55: 455–59, 1938.
  4. Joint Food and Agriculture Organization/World Health Organization/United Nations University Expert Consultation on Energy and Protein Requirements: Energy and protein requirements. (WHO Technical Report Series No. 724.) Geneva: World Health Organization, 1985.
  5. Schofield WN: Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 39C(1S): 5–41, 1985.
  6. Ravussin E, Lillioja S, Anderson TE, Christin L, Bogardus C: Determinants of 24-hour energy expenditure in man: methods and results using a respiratory chamber. J Clin Invest 78: 1568–1578, 1986.
  7. Kaplan AS, Zemel BS, Neiswender KM, Stallings VA: Resting energy expenditure in clinical pediatrics: measured versus prediction equations. J Pediatr 127: 200–205, 1995.[Medline]
  8. Mayes T, Gottschlich M, Khoury J, Warden G: Evaluation of predicted and measured energy requirements in burned children. J Am Diet Assoc 96: 24–29, 1996.[Medline]
  9. Rising R, Ancel K, Ravussin E, Bogardus C: Concomitant interindividual variation in body temperature and metabolic rate. Am J Physiol 263: E730–E734, 1992.[Abstract/Free Full Text]
  10. Weinsier RL, Schutz Y, Bracco D: Reexamination of the relationship of resting metabolic rate to fat-free mass and to the metabolically active components of fat-free mass in humans. Am J Clin Nutr 55: 790–94, 1992.[Abstract/Free Full Text]
  11. Ravussin E, Bogardus C: Relationship of genetics, age, and physical fitness to daily energy expenditure and fuel utilization. Am J Clin Nutr 49: 968–975, 1989.
  12. Goran MI, Kaskoun M, Johnson R: Determinants of resting energy expenditure in young children. J Pediatr 125: 362–367, 1994.[Medline]
  13. Rubner M: "Die Gesetze des Energieverbrauchs bei der Ernährung." Leipzig: Deutsche, 1902.
  14. Salas-Salvado J, Martinez SV: Measuring resting energy expenditure in pediatrics. (Letter to the Editor). J Pediatr 128: 587, 1996.
  15. Amini SB, Catalano PM, Hirsch V, Mann LI: An analysis of birth weight by gestational age using a computerized perinatal data base, 1975–1992. Obstet Gynecol 83: 342–352, 1994.[Abstract/Free Full Text]
  16. Centers for Disease Control and Prevention: 1994 revised classification system for HIV infected children (<13 years old). Morb Mortal Wkly Rep 43 (RR-12): 1–10, 1994.
  17. Heyward VH, Stolarczyk LM: Skinfold method. In: "Applied Body Composition Assessment." Champaign, IL: Human Kinetics, pp 21–43, 1996.
  18. Catalano PM, Thomas AJ, Avallone DA, Amini SB: Anthropometric estimation of neonatal body composition. Am J Obstet Gynecol 173: 1176–1181, 1995.[Medline]
  19. De Bruin NC, Van Velthoven KA, Stijnen T, Juttmann R, Degenhart HJ: Body fat and fat free mass in infants: New and classic anthropometric indexes and prediction equations compared with total-body electrical conductivity. Am J Clin Nutr 61: 1195–1205, 1995.[Abstract/Free Full Text]
  20. Soldin SJ, Hicks JM (eds): "Pediatric Reference Ranges." Washington, DC: American Association for Clinical Chemistry Press, 1995.
  21. Balfour-Lynn IM, Valman HB, Brown RJK: "Practical Management of the Newborn." Oxford: Blackwell Scientific Publications, pp 133–141, 1993.
  22. Marks HM, Coen P, Kerrigan JR, Francalancia NA, Nardis EE, Snider MT: The accuracy and precision of an open-circuit system to measure oxygen consumption and carbon dioxide production in neonates. Pediatr Res 21: 58–65, 1987.[Medline]
  23. Dulloo AG, Ismail MN, Ryall M, Melas BA, Geissler CA, Miller DS: A low-budget and easy-to-operate room respirometer for measuring daily energy expenditure in man. Am J Clin Nutr 48: 1367–1374, 1988.[Abstract/Free Full Text]
  24. Bogardus C, Lillioja S, Ravussin E, Abbot W, Zawadzki J, Young A, Knowler W, Jacobowitz R, Moll P: Familial dependence of resting metabolic rate. N Engl J Med 315: 96–100, 1986.[Abstract]
  25. Butte NF, Moon JK, Wong WW, Hopkinson JM, O’Brian Smith E: Energy requirements from infancy to adulthood. Am J Clin Nutr 1995; 62: 1047S–1052S.[Abstract/Free Full Text]
  26. Alemzadeh R, Friedman S, Fort P, Recker B, Lifshitz F: Is there compensated hypothyroidism in infancy? Pediatrics 90: 207–211, 1992.[Abstract/Free Full Text]
  27. Becker DV: Metabolic indices. In: Ingbar SH, Braverman LG (eds): "Werner’s The Thyroid: A Fundamental and Clinical Text," 5th ed. Philadelphia, PA: JB Lippincott Company, pp 524–531, 1986.
  28. Melchior J, Salmon D, Rigaud D, Leport C, Bouvet E, Detruchis P, Vilde J, Vachon F, Coulaud J, Apfelbaum M: Resting energy expenditure is increased in stable, malnourished HIV-infected patients. Am J Clin Nutr 53: 437–441, 1991.[Abstract/Free Full Text]
  29. Grunfeld C, Pang M, Shimizu L, Shigenaga JK, Jensen P, Feingold KR: Resting energy expenditure, caloric intake, and short-term weight change in human immunodeficiency virus infection and the acquired immunodeficiency syndrome. Am J Clin Nutr 55: 455–60, 1992.[Abstract/Free Full Text]
  30. Tracey KJ, Vlassara H, Cerami A: Cachectin/tumor necrosis factor. Lancet 2: 1122–26, 1989.[Medline]
  31. Hober D, Haque A, Wattre P, Beaucaire G, Mouton Y, Capron A: Production of tumor necrosis factor-alpha (TNF-alpha) and interleukin-1 (IL-1) in patients with AIDS. Enhanced level of TNF-alpha is related to a higher cytotoxic activity. Clin Exp Immunol 78: 329–33, 1989.[Medline]
  32. Molina JM, Scadden DT, Byrn R, Dinarello CA, Groopman JE: Production of tumor necrosis factor-alpha and interleukin-1 by monocytic cells infected with human immunodeficiency virus. J Clin Invest 84: 733–737, 1989.
  33. National Research Council, Food and Nutrition Board: Recommended Dietary Allowances, 10th ed. Washington, DC: Academy of Sciences, 1989.
  34. Frank D, Silva M, Needlman R: Failure to thrive: myth and method. Contemp Pediatr 10: 114–133, 1993.



This article has been cited by other articles:


Home page
 Am. J. Clin. Nutr.Home page
M. J Batterham
Investigating heterogeneity in studies of resting energy expenditure in persons with HIV/AIDS: a meta-analysis
Am. J. Clinical Nutrition, March 1, 2005; 81(3): 702 - 713.
[Abstract] [Full Text] [PDF]

Home page
 PediatricsHome page
D. Duro, R. Rising, M. Cedillo, and F. Lifshitz
Association Between Infantile Colic and Carbohydrate Malabsorption From Fruit Juices in Infancy
Pediatrics, May 1, 2002; 109(5): 797 - 805.
[Abstract] [Full Text] [PDF]

Home page
 Arch Pediatr Adolesc MedHome page
C. R. Cole, R. Rising, and F. Lifshitz
Consequences of Incomplete Carbohydrate Absorption From Fruit Juice Consumption in Infants
Arch Pediatr Adolesc Med, October 1, 1999; 153(10): 1098 - 1102.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Cole, C. R.
Right arrow Articles by Lifshitz, F.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Cole, C. R.
Right arrow Articles by Lifshitz, F.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS