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Estimation of resting energy expenditure by anthropometry
CLINICALNUTRITION
(1987) 6: 51-57
Estima .tion of Resting Energy Expenditure by Anthropometry D. T. Hansell, R. Richardson, J. W. L. Davies, H. J. G. Burns University Department of Surgery, Royal Infirmary, Glasgow G31 (Reprint requests to D.T.H.)
The role of anthropometry in estimating resting energy expenditure (REE) has been ABSTRACT assessed in 142 clinically stable patients. Ninety eight patients had cancer (54 weight stable, 44 weight losing) and 44 patients had nonmalignant illness (27 weight stable, 17 weight losing). Mid-arm muscle circumference (MAMC) measurements correlated significantly with REE measured by indirect calorimetry in each of the groups studied. Weight loss significantly affected this correlation whereas cancer did not. The correlation in weight stable patients was poorer than that in weight losing patients, possibly reflecting inaccuracy of anthropometric measurements due to subcutaneous adipose tissue. Significant correlations were also observed between mid-arm circumference (MAC) and REE, and between MAMC and whole body oxygen consumption. REE can be estimated from MAMC measurements in weight stable and weight losing patients with benign or malignant disease. This simple method may be of value in estimating REE where indirect calorimetry facilities are unavailable.
INTRODUCTION
PATIENTS
Clinicians have become aware of the need for accurate estimation of resting energy expenditure (REE) as a basis for nutritional support. Ideally, REE should be measured using indirect calorimetry, but few centres have this facility. In addition, patients may be too unwell to be transported to the calorimeter, and may be unable to tolerate nose-clips, facemasks or a head canopy, even where mobile calorimetry facilities exist [l]. REE can be estimated from various predictive formulae, but most of these have been derived from measurements made in mainly young healthy individuals [2, 31 and have been shown to be inaccurate in many ill patients [4,5]. Simple anthropometric measurements of triceps skinfold thickness (TST), mid-arm circumference (MAC) and calculated mid-arm muscle circumference (MAMC) are extensively used to assess nutritional status. These measurements are easily performed irrespective of the clinical state of the patient, and require no sophisticated equipment. In order to assess the effectiveness of anthropometric measurements in estimating REE, they have been related to REE measured by indirect calorimetry in weight stable and weight losing patients with benign or malignant disease.
One hundred and forty two patients were included in the study. Cancer was proven histologically in 98 patients, and a control group of 44 patients had nonmalignant illness. Of the 98 cancer patients, 54 had lost little or no weight (weight stable) and 44 had lost 10% or more of their pre-illness body weight (weight losing). The controls were similarly divided into 27 weight stable and 17 weight losing patients. Pathological diagnoses are shown in Table 1. Hepatic metastases were found in 20 cancer patients using ultrasound and computerised tomography (11 weight stable, 9 weight losing). Patients who had clinical or bacteriological evidence of infection or obvious oedema or ascites, and those who had undergone surgery, radiotherapy or cytotoxic chemotherapy in the preceding year were not included. None of the patients studied had received nutritional support. Resting energy expenditure (REE) and respiratory quotient (RQ) were measured using an indirect calorimeter with a rigid canopy [6], a sensitive paramagnetic oxygen analyser (Servomex Ltd, Crowborough, Sussex, UK) and an infra-red carbon dioxide analyser (Sieger Ltd, Poole, Dorset, UK). The equipment was calibrated frequently using oxygen-free nitrogen, 0.80% carbon dioxide and air at a known barometric 51
AND METHODS
52
ESTIMATION OF RESTING ENERGY EXPENDITURE BY ANTHROPOMETRY
Table 1 Pathological diagnoses in weight stable and weight losing cancer patients and controls Diagnosis
Cancer Weight stable Weight losing (n = 54) (n = 44) 20 36 14 15 2 5 2 2 _ 2 Control Weight stable Weight losing (n = 27) (n = 17) 1 1 3 5 2 15 3 3 2 3 2 1 _ 1 1 1
Colorectal cancer Gastric cancer Bronchial cancer Oesophagealcancer Pancreatic cancer
Gastric ulceration Duodenal ulceration Pyloric stenosis Cholelithiasis Diverticular disease Benign colorectal polyp Ulcerative colitis Crohn’s disease Hiatus hernia
pressure. The sensitivity and accuracy of the calorimeter was checked periodically by burning butane gas in the canopy. The whole system provides measurements of oxygen consumption (00,) and carbon dioxide production (OCO,) which have an overall error of less than f 5 “&. Estimates of fro, and irC0, were collected every 30s during each patient study, which lasted for 40 min. Recording of data did not commence until a steady trace of oxygen consumption and carbon dioxide production was obtained, usually after 510min. The 80 estimates of ir0, and irC0, collected were processed on line by a microprocessor (PET 2001, CBM Ltd, UK) and converted to mean energy production (watts) and RQ using the abbreviated formula of Weir [7]: REE (kcal/day) where kcal/day VO, \iCO,
= = = =
(3.9vC02 + 1.13COJ1440 watts x 20.65 oxygen consumption (1jmin) carbon dioxide production (l/min) RQ+
2
The measurement period of 40 min was preceded by 30 min acclimatisation in the calorimeter canopy. Prior to each study, patients remained in bed since wakening. Physiotherapy, bed-baths and other nursing procedures were not permitted prior to a calorimetry run. Patients received nil by mouth for 12 h prior to the calorimeter run but received an intravenous infusion of 5 “/”dextrose solution providing 80 ml of fluid (16 kcal) per h to maintain hydration. Lean body mass (LBM) was derived from the measurement of total body water at the time of calorimetry. Tritiated saline (4MBq) was injected intra-
venously and serum samples were obtained 3 and 4 h after injection. During the period of equilibration all urine passed was collected to measure the loss of tritium in urine. LBM was derived from the volume of body water assuming that lean tissue contains 73”/bwater [8]. Triceps skinfold thickness (TST) and mid-arm circumference (MAC) were measured by a single observer (RR) on the day of calorimetry. MAC was measured by marking the midpoint between the acromion and olecranon processes in the dependent nondominant arm with the elbow joint flexed to 90”. A skinfold 1 cm above this point overlying the triceps muscle was pinched between finger and thumb and three readings of the TST were obtained using skin calipers. The mean of the three readings was taken as the TST measurement. Mid-arm muscle circumference (MAMC) was calculated using the formula: MAMC = MAC - (0.314 x TST) where MAMC is in cm MAC is in cm TST is in mm MAMC and TST were expressed as percentages of expected standard values (9) where: MAMC TST
male = 25.3 cm - female = 23.2 cm male = 12.5mm - female = 16.5mm
Where several groups of data were compared, an analysis of variance was used initially to test whether there were any significant differences between groups. However, the non-parametric Mann-Whitney U test was used for pairwise comparisons in order to minimise the risk of detecting spurious differences in data which were not normally distributed. For descriptive purposes, data have been expressed as mean f s.e.m to facilitate comparison with other published results. Linear regression analysis was performed using the method of least squares and correlation coefficients (r) determined. Linear regression equations are in the form: y=a+bx where a is the intercept on the y axis and b is the gradient of the line The slopes of the linear regression lines were compared using Student’s t test. All confidence intervals (CI) quoted are 95”/, CIs. Other statistical tests were used as indicated in the text. Differences were considered significant when the probability of their arising by random sampling error was less than 1 in 20 (P < 0.05). Differences were considered highly significant when this probability was less than 1 in 100 (P < 0.01).
CLINICAL
Table 2
Clinical
details of weight and weight losing cancer patients
,* Male:Female Age (years) Height (cm) Body weight (kg) Body weighPn (kg) Lean body mass (kg) Weight loss (“,,) mean a = P b = P c = P d = P
f < < i <
Table 3
s.e.m. 0.01 versus 0.05 versus 0.05 versus 0.01 versus
Control
stable
Weight
54 38:16 66 f 1.5 164 +z 1.3 64.2 & 1.6b 22.6 f 0.4d 49.8 f 1.7 4 f 0.5
weight stable cancer patients weight losing controls weight stable cancer patients weight losing controls
Anthropometric
and calorimetric
losing
44 20:24 66 f 1.6 161 f 1.3 52.2 + 1.8’ 19.3 f 0.5” 43.6 f 1.6’ 18 f 1.1”
Weight
stable
mean a = P b = P c = P d = P
i i < < <
s.e.m. 0.01 versus 0.01 versus 0.01 versus 0.05 versus
weight weight weight weight
stable stable stable stable
Males
predominated females
Weight
13.9 28.2 23.8 1426 206.7
0.9 0.5 0.4 25.6 3.53
10.1 24.2 21.1 1278 187.3
group in mean weight
(Table
1). There
age and losing
in the weight
predominated mean
cancer
stable
in the weight were height
patients
no significant between had
Weight
stable
Weight
0.7s 0.5” 0.4’ 37.8b 5.27b
19.3 29.9 23.8 1340 193.9
1.7b 0.9 0.5 42.5 5.68b
11.1 24.9 21.4 1279 184.1
stable controls
and weight
stable controls
cancer
group control
differences
the groups.
a significantly
The lower
body weight, body weighPS, and LBM compared with their weight stable counterparts. The weight losing control patients had a significantly lower mean body weight and body weighP5 but no significant difference in LBM compared with their weight stable counterparts. Both weight losing groups had lost in excess of 15% of their pre-illness weight. Anthropometric and calorimetric data are shown in Table 2. Both weight losing groups had significantly lower TST, MAC and MAMC measurements compared with their weight stable counterparts. The weight losing cancer patients had a significantly lower REE and QO, (uncorrected for body size) than their weight stable counterparts, whereas no significant difference in REE and 00, were found between the two control groups (Table 3) mean
f f f & f
losing
and weight
stable
and controls
Control
stable
RESULTS
and
17 8:9 64 f 3.8 162 i 2.6 55.4 f 3.2 20.2 f 0.9 45.9 f 2.3 16 f 1.2’
of weight stable and weight losing cancer patients
Weight
cancer patients cancer patients controls cancer patients
losing
and weight stable controls
measurements
f f * f *
Weight
27 7:20 62 * 2.7 159 f 1.6 66.0 f 2.9b 23.2 f 0.7’ 48.9 f 2.2 1 * 0.5’
Cancer
TST (cm) MAC (cm) MAMC (cm) REE (kcal/day) VO, (ml/min)
53
and controls
Cancer Weight
NUTRITION
f f f f f
losing f f f f f
1.2’ 0.9’ 0.8” 58.0b 8.09b
There was a significant correlation between MAMC and REE for both males and females. No significant differences were found between the slopes of the male and female regression lines (Fig. 1). MAMC and REE also correlated significantly when patients were divided into groups depending on weight status and disease status (Fig. 2). The slope of the cancer weight stable regression line was significantly different from that of the cancer weight losing regression line. The significant correlation between MAMC and REE persisted when all cancer patients were compared with all control patients, with the slopes of the regression lines being almost identical (Fig. 3). When all weight stable patients were compared with all weight losing patients (Fig. 4), the correlation between MAMC and REE remained significant, but on this occasion there was a significant difference between the slopes of the regression lines. MAC also correlated significantly with REE (Fig. 5), but less so than did MAMC. The slopes of the regression lines followed a similar pattern to those relating MAMC to REE. The slope of the cancer weight losing regression line was significantly different from the
54
ESTIMATION OF RESTING ENERGY EXPENDITURE
BY ANTHROPOMETRY
20
Mid-arm
Fig. 1 The relationship between resting energy expenditure and mid-arm muscle circumference in all male patients and all female patients Male n = 73; r = 0.583; P < 0.01 Female n = 69; r = 0.634; P < 0.01
y = 393 95% CI y = 381 95O& CI
+ 45.0x (30.0,59.9) + 39.0x (27.4,50.6)
No significant differences between the slopes.
30
muscle
40
circumference
km)
Fig. 3 The relationship between resting energy expenditure and mid-arm muscle circumference in all cancer patients and all controls Cancer n = 98; r = 0.670; P < 0.01
y = 240 + 49.3x 9S’/&CI (38.2,60.4)
Control n = 44; r = 0.619; P < 0.01
y = 277 f 45.4x 954: CI (27.6,63.2)
No significant differences between the slopes.
cws / /
/
,
/
Weight
stable
/
Weight
losing
/, 20 Mid-arm
Fig. 2 The relationship between resting energy expenditure and mid-arm muscle circumference in each of the groups CWL (cancer weight losing) n = 44; r = 0.751; P < 0.01
y = -213 + 70.5x 95% CI (51.4,89.6)
CWS (cancer weight stable) n = 54; r = 0.511; P < 0.01
y = 628 + 33.3x 95% CI (17.8,48.8)
NCWL (control weight losing) n = 17; r = 0.728; I’ i 0.01
y = 89 + 55.6x 95y0 CI (28.6,82.6)
NCWS (control weight stable) n = 27; r = 0.539; P < 0.01
y = 304 + 43.5x 95% CI (16.4,70.6)
The CWL slope is significantly different from the CWS slope (P < 0.01).
a0 muscle
circumference
[Cm1
Fig. 4 The relationship between resting energy expenditure and mid-arm muscle circumference in all weight stable patients and all weight losing patients Weight stable n = 81; r = 0.513; P < 0.01
y = 518 + 36.8x 95% CI (23.0,50.6)
Weight losing n = 61; r = 0.741; I’ < 0.01
y = - 108 + 65.3x 95% CI (49.9,80.7)
The weight stable slope is significantly weight losing slope (P < 0.01).
different
from the
CLINICAL
2;
15
Mid-arm
Fig. 5
0; cwcumference
4;
(cm)
The relationship between resting energy expenditure
and mid-arm circumference in each of the groups CWL (cancer weight losing) n = 44, r = 0.659; P < 0.01
y = 178 + 45.4x 954; CI (29.4,61.4)
CWS (cancer weight stable) n = 54; r = 0.352; P < 0.01
y = 890 + 19.0x 95Y0 CI (5.0,33.0)
NCWL (control weight losing) n = 17; r = 0.667; P < 0.01
y = 205 +43.1x 959b CI (18.2,68.0)
NCWS (control weight stable) n = 27; r = 0.444; P < 0.05
y = 698 + 21.4x 95qb CI (4.1,38.7)
The CWL slope is significantly different from the CWS slope (P i 0.05).
cancer weight stable line. When all weight stable patients were compared with all weight losing patients, there was a significant difference between the slopes of the regression lines. There was also a significant correlation between MAMC and OO,, but this correlation was not as close as that between MAMC and REE. The correlations between MAMC and \jO, were:
Cancer weight stable: r = 0.437,95% P < 0.01 Cancer weight losing: r = 0.684, 95y0 P < 0.01 Control weight stable: r = 0.486,95”/” P < 0.05 Control weight 1osing:r = 0.726,95”/;, P < 0.01 where CI = confidence interval
CI (1.6,6.0) CI (6.0, 11.8) CI (1.4,9.0) CI (3.9, 11.5)
REE correlated significantly with body weight, body weighP and LBM for each group (Table 4). No significant correlation was found when TST was related to either REE or 00,.
DISCUSSION This study demonstrates a significant correlation between mid-arm muscle circumference (MAMC) and
NUTRITION
55
resting energy expenditure (REE) in both male and female weight stable and weight losing patients with benign or malignant disease. Although the correlations between REE and body weight, body weighPS and LBM were even closer than that between REE and MAMC, it is often impractical to weigh bed-bound patients, and the estimation of LBM requires the use of isotope dilution techniques [8] or total body potassium measurements [lo]. Furthermore, the commonly used predictive formulae have been shown to be inaccurate in predicting REE in many patients [4,5]. Thus, simple MAMC measurements may be of value in the estimation of REE. The reason for assessing the value of anthropometric measurements in estimating REE is based on the observation that skeletal muscle mass relates well to basal heat production [ 111. Furthermore, it is less susceptible to the changes in extracellular fluid volume which occur in malnutrition [ 121. The arm is a useful site for antbropometry, as it is easily accessible and less affected by subcutaneous oedema than is the lower limb or subscapular region [ 121. Brown and colleagues [ 131 reported a closer correlation when whole body oxygen consumption (00,) rather than REE was related to MAMC. In the present study, although MAMC did correlate significantly with OO,, the correlation was not as close as that between REE and MAMC. The uncorrected measurement of mid-arm circumference (MAC) also correlated significantly with REE, but less so than did MAMC, which takes account of mid-arm fat stores. Measurements of MAC have been shown by others [ 141 to be more reproducible and to correlate with weight change better than MAMC, and it has been suggested that the error margin associated with TST measurement is responsible for the poorer performance of MAMC. However, in the present study, MAMC has been shown to correlate more closely with REE than does MAC. A significant finding in the present study is the altered relationship between REE and MAMC in the presence of significant weight loss. The correlation coefficients were considerably higher in both the weight losing groups compared with the weight stable groups. Since both the weight losing groups had smaller TST values than the weight stable groups, it may be that the inaccuracy caused by the presence of mid-arm fat stores was responsible for this difference in correlation. The significant difference in the slopes of the regression lines for all weight stable and all weight losing patients (Fig. 4) should be noted. The significantly steeper slope of the weight losing patients may imply that at low arm muscle circumferences these patients are able to lower their REE to a greater extent than can weight stable patients. This interpretation is consistent with the theory put forward by both this group [ 151 and
ESTIMATION OF RESTING ENERGY EXPENDITURE
56
BY ANTHROPOMETRY
Table 4 Correlation between resting energy expenditure (REE) and different indices of body size in weight stable and weight losing cancer patients and controls Cancer REE related to:
Control
Weight stable
Body weight
Weight losing
0.646 (6.9, 13.5)
Weight stable
Weight losing
0.804 (15.3,19.3)
0.750 (7.2, 15.0)
0.772 (8.1, 19.9)
Body weighto.’
0.645 (25.9,51.3)
0.811 (49.2,77.2)
0.706 (24.3,56.9)
0.778 (29.7,72.3)
Lean body mass
0.559 (5.1,13.1)
0.845 (17.4,26.4)
0.874 (13.5,20.9)
0.887 (16.4,28.6)
correlation coefficient (95Ob confidence interval) P < 0.01 for all values
Lindmark weight REE
and
losing
colleagues cancer
to the weight
Many patients study,
authors
between
those reported
previously
relationship
between with cancer
non-malignant effect
on REE
from
our group
excision ings,
we have
has
It should
calculating
with and without
be remembered in patients
with no evidence
who
of sepsis.
identical
that were Brown
to
who had
the presence
of
no significant
a more that
of hepatic
The
was investigated
to have
shown
role
patients.
[ 151, where the
study,
effect on REE.
avoided
lines for patients performed
In that
nor progression
3), suggest-
with patients
[ 151. Furthermore,
has any significant
(Fig.
to play a major
and REE
compared
in
In the present
by this group
was shown [20]
in REE
3 are virtually
LBM
illness.
metastases
their
recent
study
neither
tumour
metastatic
disease
In view of these findseparate hepatic this
ACKNOWLEDGEMENTS The authors are grateful of Surgery, for help and by the Medical Research Wellcome Trust for their
to Professor D. C. Carrer, Professor encouragement. JWLD is supported Council. We are also grateful to the support.
to alter the re-
seen in cancer
in Figure
in patients hepatic
and REE
is unlikely
in REE
lines
[17-191.
did not appear
MAMC
muscle
in any alteration
that
to adapt
an increase
disease
disease
ing that skeletal
suggested
losing state.
with malignant
regression
who
are able
have reported
malignant
lationship
[16]
patients
regression
metastases.
study
largely
has been
unstressed,
and colleagues
[13]
showed that the relationship between MAMC and whole body oxygen consumption was much poorer in the septic patient. Allowances will therefore have to be made for patients who have been recently stressed by trauma or surgery, and those who display any evidence of sepsis. In conclusion, it would appear that mid-arm muscle circumference can be used to estimate resting energy expenditure in patients with benign or malignant disease, although different relationships exist depending on whether the patient has or has not lost weight. This simple, easily performed measurement may therefore be of value in estimating the resting energy requirements of patients where access to indirect calorimetry facilities are unavailable.
REFERENCES
PI Askanazi J, Silverberg P A, Foster R U et al 1980 Effects
of respiratory apparatus on breathing patterns. Journal of Applied Physiology 48: 577-580 VI Harris J A, Benedict F G 1919 Biometric studies of basal metabolism in man. Carnegie Institute of Washington, Publication no 279 Washington DC [31 Robertson J D, Reid D D 1952 Standards for the basal metabolism of normal people in Britain. Lancet i: 940-943 [41 Roza A M, Shizgal H M 1984 The Harris-Benedict equation re-evaluated: resting energy requirements and the body cell mass. American Journal of Clinical Nurrition 40: 168-182 [51 Feurer I D, Crosby L 0, Mullen J L 1984 Measured and predicred resting energy expenditure in clinically stable patients. Clinical Nutrition 3: 27-34 [61 Kinney J M, Morgan A P, Domingues F J, Gildner K J 1964 A method for continuous measurement of gas exchange and expired radioactivity in acutely ill patients. Metabolism 13: 205-211 171 Weir J B de V 1949 New methods for calculating metabolic rate with special reference to protein metabolism. Journal of Physiology 109: l-9 PI Belcher E H, Vetter H 1971 Radioisotopes in medical diagnosis. 1st editn Butterworths, London, 258-297 PI World Health Organization 1966 Jellife D B. The assessment of the nutritional status of the community. Geneva: World Health Organization UOI Burkinshaw L 1978 Sex-dependent calibration factor of a whole-body radiation counter. International Journal of Applied Radiation and Isotopes 29: 387-390 illI Krebs H 1950 Body size and tissue respiration. Biochemica Biophysics Acta 4: 249-254 [121 Starker P M, Askanazi J, Lasala PA et al 1983 The effect of parenteral nutrition repletion on muscle wafer and electrolytes. Implications for body composition. Annals of Surgery 198: 213-217
CLINICAL NUTRITION
[ 131 Brown R, Gross E, Little R A et al 1984 Whole body oxygen consumption and anthropomerry. Clinical Nutrition 3: 1 l-16 [ 141 Harries A D, Jones L A, Heatley R H V et al 1985 Precision of anthropometric measurements: The value of mid-arm circumference. Clinical Nutrition 4: 77-80 [ 151 Hansel1 D T, Davies J W L, Burns H J G 1986 The relationship between resting energy expenditure and weight loss in benign and malignant disease. Annals of Surgery 203: 240-245 [ 161 Lindmark L, Bemtegard K, Eden E et al 1984 Resting energy expenditure in malnourished patients with and without cancer. Gastroenterology 87: 402-408 [17] Waterhouse C, Fenninger L D, Keutmann E H 1951
57
Nitrogen exchange and caloric expenditure in patients with malignant neoplasms. Cancer 4: 500-514 [ 181 Femtinger L D, Mider G B 1954 Energy and nitrogen metabolism in cancer. Advances in Cancer Research 2: 229-252 [ 191 Bozzetti F, Pagnoni A M, Del Vecchio M 1980 Excessive caloric expenditure as a cause of malnutrition in patients with cancer. Surgery, Gynecology and Obstetrics 150: 229-234 [20] Hansel1 D T, Davies J W L, Burns H J G 1986 Effects of hepatic metastases on resting energy expenditure in patients with colorectal cancer. British Journal of Surgery 73: 659662
Submission date: 3 July 1986. Accepted after revision: 6 October 1986
(1987) 6: 51-57
Estima .tion of Resting Energy Expenditure by Anthropometry D. T. Hansell, R. Richardson, J. W. L. Davies, H. J. G. Burns University Department of Surgery, Royal Infirmary, Glasgow G31 (Reprint requests to D.T.H.)
The role of anthropometry in estimating resting energy expenditure (REE) has been ABSTRACT assessed in 142 clinically stable patients. Ninety eight patients had cancer (54 weight stable, 44 weight losing) and 44 patients had nonmalignant illness (27 weight stable, 17 weight losing). Mid-arm muscle circumference (MAMC) measurements correlated significantly with REE measured by indirect calorimetry in each of the groups studied. Weight loss significantly affected this correlation whereas cancer did not. The correlation in weight stable patients was poorer than that in weight losing patients, possibly reflecting inaccuracy of anthropometric measurements due to subcutaneous adipose tissue. Significant correlations were also observed between mid-arm circumference (MAC) and REE, and between MAMC and whole body oxygen consumption. REE can be estimated from MAMC measurements in weight stable and weight losing patients with benign or malignant disease. This simple method may be of value in estimating REE where indirect calorimetry facilities are unavailable.
INTRODUCTION
PATIENTS
Clinicians have become aware of the need for accurate estimation of resting energy expenditure (REE) as a basis for nutritional support. Ideally, REE should be measured using indirect calorimetry, but few centres have this facility. In addition, patients may be too unwell to be transported to the calorimeter, and may be unable to tolerate nose-clips, facemasks or a head canopy, even where mobile calorimetry facilities exist [l]. REE can be estimated from various predictive formulae, but most of these have been derived from measurements made in mainly young healthy individuals [2, 31 and have been shown to be inaccurate in many ill patients [4,5]. Simple anthropometric measurements of triceps skinfold thickness (TST), mid-arm circumference (MAC) and calculated mid-arm muscle circumference (MAMC) are extensively used to assess nutritional status. These measurements are easily performed irrespective of the clinical state of the patient, and require no sophisticated equipment. In order to assess the effectiveness of anthropometric measurements in estimating REE, they have been related to REE measured by indirect calorimetry in weight stable and weight losing patients with benign or malignant disease.
One hundred and forty two patients were included in the study. Cancer was proven histologically in 98 patients, and a control group of 44 patients had nonmalignant illness. Of the 98 cancer patients, 54 had lost little or no weight (weight stable) and 44 had lost 10% or more of their pre-illness body weight (weight losing). The controls were similarly divided into 27 weight stable and 17 weight losing patients. Pathological diagnoses are shown in Table 1. Hepatic metastases were found in 20 cancer patients using ultrasound and computerised tomography (11 weight stable, 9 weight losing). Patients who had clinical or bacteriological evidence of infection or obvious oedema or ascites, and those who had undergone surgery, radiotherapy or cytotoxic chemotherapy in the preceding year were not included. None of the patients studied had received nutritional support. Resting energy expenditure (REE) and respiratory quotient (RQ) were measured using an indirect calorimeter with a rigid canopy [6], a sensitive paramagnetic oxygen analyser (Servomex Ltd, Crowborough, Sussex, UK) and an infra-red carbon dioxide analyser (Sieger Ltd, Poole, Dorset, UK). The equipment was calibrated frequently using oxygen-free nitrogen, 0.80% carbon dioxide and air at a known barometric 51
AND METHODS
52
ESTIMATION OF RESTING ENERGY EXPENDITURE BY ANTHROPOMETRY
Table 1 Pathological diagnoses in weight stable and weight losing cancer patients and controls Diagnosis
Cancer Weight stable Weight losing (n = 54) (n = 44) 20 36 14 15 2 5 2 2 _ 2 Control Weight stable Weight losing (n = 27) (n = 17) 1 1 3 5 2 15 3 3 2 3 2 1 _ 1 1 1
Colorectal cancer Gastric cancer Bronchial cancer Oesophagealcancer Pancreatic cancer
Gastric ulceration Duodenal ulceration Pyloric stenosis Cholelithiasis Diverticular disease Benign colorectal polyp Ulcerative colitis Crohn’s disease Hiatus hernia
pressure. The sensitivity and accuracy of the calorimeter was checked periodically by burning butane gas in the canopy. The whole system provides measurements of oxygen consumption (00,) and carbon dioxide production (OCO,) which have an overall error of less than f 5 “&. Estimates of fro, and irC0, were collected every 30s during each patient study, which lasted for 40 min. Recording of data did not commence until a steady trace of oxygen consumption and carbon dioxide production was obtained, usually after 510min. The 80 estimates of ir0, and irC0, collected were processed on line by a microprocessor (PET 2001, CBM Ltd, UK) and converted to mean energy production (watts) and RQ using the abbreviated formula of Weir [7]: REE (kcal/day) where kcal/day VO, \iCO,
= = = =
(3.9vC02 + 1.13COJ1440 watts x 20.65 oxygen consumption (1jmin) carbon dioxide production (l/min) RQ+
2
The measurement period of 40 min was preceded by 30 min acclimatisation in the calorimeter canopy. Prior to each study, patients remained in bed since wakening. Physiotherapy, bed-baths and other nursing procedures were not permitted prior to a calorimetry run. Patients received nil by mouth for 12 h prior to the calorimeter run but received an intravenous infusion of 5 “/”dextrose solution providing 80 ml of fluid (16 kcal) per h to maintain hydration. Lean body mass (LBM) was derived from the measurement of total body water at the time of calorimetry. Tritiated saline (4MBq) was injected intra-
venously and serum samples were obtained 3 and 4 h after injection. During the period of equilibration all urine passed was collected to measure the loss of tritium in urine. LBM was derived from the volume of body water assuming that lean tissue contains 73”/bwater [8]. Triceps skinfold thickness (TST) and mid-arm circumference (MAC) were measured by a single observer (RR) on the day of calorimetry. MAC was measured by marking the midpoint between the acromion and olecranon processes in the dependent nondominant arm with the elbow joint flexed to 90”. A skinfold 1 cm above this point overlying the triceps muscle was pinched between finger and thumb and three readings of the TST were obtained using skin calipers. The mean of the three readings was taken as the TST measurement. Mid-arm muscle circumference (MAMC) was calculated using the formula: MAMC = MAC - (0.314 x TST) where MAMC is in cm MAC is in cm TST is in mm MAMC and TST were expressed as percentages of expected standard values (9) where: MAMC TST
male = 25.3 cm - female = 23.2 cm male = 12.5mm - female = 16.5mm
Where several groups of data were compared, an analysis of variance was used initially to test whether there were any significant differences between groups. However, the non-parametric Mann-Whitney U test was used for pairwise comparisons in order to minimise the risk of detecting spurious differences in data which were not normally distributed. For descriptive purposes, data have been expressed as mean f s.e.m to facilitate comparison with other published results. Linear regression analysis was performed using the method of least squares and correlation coefficients (r) determined. Linear regression equations are in the form: y=a+bx where a is the intercept on the y axis and b is the gradient of the line The slopes of the linear regression lines were compared using Student’s t test. All confidence intervals (CI) quoted are 95”/, CIs. Other statistical tests were used as indicated in the text. Differences were considered significant when the probability of their arising by random sampling error was less than 1 in 20 (P < 0.05). Differences were considered highly significant when this probability was less than 1 in 100 (P < 0.01).
CLINICAL
Table 2
Clinical
details of weight and weight losing cancer patients
,* Male:Female Age (years) Height (cm) Body weight (kg) Body weighPn (kg) Lean body mass (kg) Weight loss (“,,) mean a = P b = P c = P d = P
f < < i <
Table 3
s.e.m. 0.01 versus 0.05 versus 0.05 versus 0.01 versus
Control
stable
Weight
54 38:16 66 f 1.5 164 +z 1.3 64.2 & 1.6b 22.6 f 0.4d 49.8 f 1.7 4 f 0.5
weight stable cancer patients weight losing controls weight stable cancer patients weight losing controls
Anthropometric
and calorimetric
losing
44 20:24 66 f 1.6 161 f 1.3 52.2 + 1.8’ 19.3 f 0.5” 43.6 f 1.6’ 18 f 1.1”
Weight
stable
mean a = P b = P c = P d = P
i i < < <
s.e.m. 0.01 versus 0.01 versus 0.01 versus 0.05 versus
weight weight weight weight
stable stable stable stable
Males
predominated females
Weight
13.9 28.2 23.8 1426 206.7
0.9 0.5 0.4 25.6 3.53
10.1 24.2 21.1 1278 187.3
group in mean weight
(Table
1). There
age and losing
in the weight
predominated mean
cancer
stable
in the weight were height
patients
no significant between had
Weight
stable
Weight
0.7s 0.5” 0.4’ 37.8b 5.27b
19.3 29.9 23.8 1340 193.9
1.7b 0.9 0.5 42.5 5.68b
11.1 24.9 21.4 1279 184.1
stable controls
and weight
stable controls
cancer
group control
differences
the groups.
a significantly
The lower
body weight, body weighPS, and LBM compared with their weight stable counterparts. The weight losing control patients had a significantly lower mean body weight and body weighP5 but no significant difference in LBM compared with their weight stable counterparts. Both weight losing groups had lost in excess of 15% of their pre-illness weight. Anthropometric and calorimetric data are shown in Table 2. Both weight losing groups had significantly lower TST, MAC and MAMC measurements compared with their weight stable counterparts. The weight losing cancer patients had a significantly lower REE and QO, (uncorrected for body size) than their weight stable counterparts, whereas no significant difference in REE and 00, were found between the two control groups (Table 3) mean
f f f & f
losing
and weight
stable
and controls
Control
stable
RESULTS
and
17 8:9 64 f 3.8 162 i 2.6 55.4 f 3.2 20.2 f 0.9 45.9 f 2.3 16 f 1.2’
of weight stable and weight losing cancer patients
Weight
cancer patients cancer patients controls cancer patients
losing
and weight stable controls
measurements
f f * f *
Weight
27 7:20 62 * 2.7 159 f 1.6 66.0 f 2.9b 23.2 f 0.7’ 48.9 f 2.2 1 * 0.5’
Cancer
TST (cm) MAC (cm) MAMC (cm) REE (kcal/day) VO, (ml/min)
53
and controls
Cancer Weight
NUTRITION
f f f f f
losing f f f f f
1.2’ 0.9’ 0.8” 58.0b 8.09b
There was a significant correlation between MAMC and REE for both males and females. No significant differences were found between the slopes of the male and female regression lines (Fig. 1). MAMC and REE also correlated significantly when patients were divided into groups depending on weight status and disease status (Fig. 2). The slope of the cancer weight stable regression line was significantly different from that of the cancer weight losing regression line. The significant correlation between MAMC and REE persisted when all cancer patients were compared with all control patients, with the slopes of the regression lines being almost identical (Fig. 3). When all weight stable patients were compared with all weight losing patients (Fig. 4), the correlation between MAMC and REE remained significant, but on this occasion there was a significant difference between the slopes of the regression lines. MAC also correlated significantly with REE (Fig. 5), but less so than did MAMC. The slopes of the regression lines followed a similar pattern to those relating MAMC to REE. The slope of the cancer weight losing regression line was significantly different from the
54
ESTIMATION OF RESTING ENERGY EXPENDITURE
BY ANTHROPOMETRY
20
Mid-arm
Fig. 1 The relationship between resting energy expenditure and mid-arm muscle circumference in all male patients and all female patients Male n = 73; r = 0.583; P < 0.01 Female n = 69; r = 0.634; P < 0.01
y = 393 95% CI y = 381 95O& CI
+ 45.0x (30.0,59.9) + 39.0x (27.4,50.6)
No significant differences between the slopes.
30
muscle
40
circumference
km)
Fig. 3 The relationship between resting energy expenditure and mid-arm muscle circumference in all cancer patients and all controls Cancer n = 98; r = 0.670; P < 0.01
y = 240 + 49.3x 9S’/&CI (38.2,60.4)
Control n = 44; r = 0.619; P < 0.01
y = 277 f 45.4x 954: CI (27.6,63.2)
No significant differences between the slopes.
cws / /
/
,
/
Weight
stable
/
Weight
losing
/, 20 Mid-arm
Fig. 2 The relationship between resting energy expenditure and mid-arm muscle circumference in each of the groups CWL (cancer weight losing) n = 44; r = 0.751; P < 0.01
y = -213 + 70.5x 95% CI (51.4,89.6)
CWS (cancer weight stable) n = 54; r = 0.511; P < 0.01
y = 628 + 33.3x 95% CI (17.8,48.8)
NCWL (control weight losing) n = 17; r = 0.728; I’ i 0.01
y = 89 + 55.6x 95y0 CI (28.6,82.6)
NCWS (control weight stable) n = 27; r = 0.539; P < 0.01
y = 304 + 43.5x 95% CI (16.4,70.6)
The CWL slope is significantly different from the CWS slope (P < 0.01).
a0 muscle
circumference
[Cm1
Fig. 4 The relationship between resting energy expenditure and mid-arm muscle circumference in all weight stable patients and all weight losing patients Weight stable n = 81; r = 0.513; P < 0.01
y = 518 + 36.8x 95% CI (23.0,50.6)
Weight losing n = 61; r = 0.741; I’ < 0.01
y = - 108 + 65.3x 95% CI (49.9,80.7)
The weight stable slope is significantly weight losing slope (P < 0.01).
different
from the
CLINICAL
2;
15
Mid-arm
Fig. 5
0; cwcumference
4;
(cm)
The relationship between resting energy expenditure
and mid-arm circumference in each of the groups CWL (cancer weight losing) n = 44, r = 0.659; P < 0.01
y = 178 + 45.4x 954; CI (29.4,61.4)
CWS (cancer weight stable) n = 54; r = 0.352; P < 0.01
y = 890 + 19.0x 95Y0 CI (5.0,33.0)
NCWL (control weight losing) n = 17; r = 0.667; P < 0.01
y = 205 +43.1x 959b CI (18.2,68.0)
NCWS (control weight stable) n = 27; r = 0.444; P < 0.05
y = 698 + 21.4x 95qb CI (4.1,38.7)
The CWL slope is significantly different from the CWS slope (P i 0.05).
cancer weight stable line. When all weight stable patients were compared with all weight losing patients, there was a significant difference between the slopes of the regression lines. There was also a significant correlation between MAMC and OO,, but this correlation was not as close as that between MAMC and REE. The correlations between MAMC and \jO, were:
Cancer weight stable: r = 0.437,95% P < 0.01 Cancer weight losing: r = 0.684, 95y0 P < 0.01 Control weight stable: r = 0.486,95”/” P < 0.05 Control weight 1osing:r = 0.726,95”/;, P < 0.01 where CI = confidence interval
CI (1.6,6.0) CI (6.0, 11.8) CI (1.4,9.0) CI (3.9, 11.5)
REE correlated significantly with body weight, body weighP and LBM for each group (Table 4). No significant correlation was found when TST was related to either REE or 00,.
DISCUSSION This study demonstrates a significant correlation between mid-arm muscle circumference (MAMC) and
NUTRITION
55
resting energy expenditure (REE) in both male and female weight stable and weight losing patients with benign or malignant disease. Although the correlations between REE and body weight, body weighPS and LBM were even closer than that between REE and MAMC, it is often impractical to weigh bed-bound patients, and the estimation of LBM requires the use of isotope dilution techniques [8] or total body potassium measurements [lo]. Furthermore, the commonly used predictive formulae have been shown to be inaccurate in predicting REE in many patients [4,5]. Thus, simple MAMC measurements may be of value in the estimation of REE. The reason for assessing the value of anthropometric measurements in estimating REE is based on the observation that skeletal muscle mass relates well to basal heat production [ 111. Furthermore, it is less susceptible to the changes in extracellular fluid volume which occur in malnutrition [ 121. The arm is a useful site for antbropometry, as it is easily accessible and less affected by subcutaneous oedema than is the lower limb or subscapular region [ 121. Brown and colleagues [ 131 reported a closer correlation when whole body oxygen consumption (00,) rather than REE was related to MAMC. In the present study, although MAMC did correlate significantly with OO,, the correlation was not as close as that between REE and MAMC. The uncorrected measurement of mid-arm circumference (MAC) also correlated significantly with REE, but less so than did MAMC, which takes account of mid-arm fat stores. Measurements of MAC have been shown by others [ 141 to be more reproducible and to correlate with weight change better than MAMC, and it has been suggested that the error margin associated with TST measurement is responsible for the poorer performance of MAMC. However, in the present study, MAMC has been shown to correlate more closely with REE than does MAC. A significant finding in the present study is the altered relationship between REE and MAMC in the presence of significant weight loss. The correlation coefficients were considerably higher in both the weight losing groups compared with the weight stable groups. Since both the weight losing groups had smaller TST values than the weight stable groups, it may be that the inaccuracy caused by the presence of mid-arm fat stores was responsible for this difference in correlation. The significant difference in the slopes of the regression lines for all weight stable and all weight losing patients (Fig. 4) should be noted. The significantly steeper slope of the weight losing patients may imply that at low arm muscle circumferences these patients are able to lower their REE to a greater extent than can weight stable patients. This interpretation is consistent with the theory put forward by both this group [ 151 and
ESTIMATION OF RESTING ENERGY EXPENDITURE
56
BY ANTHROPOMETRY
Table 4 Correlation between resting energy expenditure (REE) and different indices of body size in weight stable and weight losing cancer patients and controls Cancer REE related to:
Control
Weight stable
Body weight
Weight losing
0.646 (6.9, 13.5)
Weight stable
Weight losing
0.804 (15.3,19.3)
0.750 (7.2, 15.0)
0.772 (8.1, 19.9)
Body weighto.’
0.645 (25.9,51.3)
0.811 (49.2,77.2)
0.706 (24.3,56.9)
0.778 (29.7,72.3)
Lean body mass
0.559 (5.1,13.1)
0.845 (17.4,26.4)
0.874 (13.5,20.9)
0.887 (16.4,28.6)
correlation coefficient (95Ob confidence interval) P < 0.01 for all values
Lindmark weight REE
and
losing
colleagues cancer
to the weight
Many patients study,
authors
between
those reported
previously
relationship
between with cancer
non-malignant effect
on REE
from
our group
excision ings,
we have
has
It should
calculating
with and without
be remembered in patients
with no evidence
who
of sepsis.
identical
that were Brown
to
who had
the presence
of
no significant
a more that
of hepatic
The
was investigated
to have
shown
role
patients.
[ 151, where the
study,
effect on REE.
avoided
lines for patients performed
In that
nor progression
3), suggest-
with patients
[ 151. Furthermore,
has any significant
(Fig.
to play a major
and REE
compared
in
In the present
by this group
was shown [20]
in REE
3 are virtually
LBM
illness.
metastases
their
recent
study
neither
tumour
metastatic
disease
In view of these findseparate hepatic this
ACKNOWLEDGEMENTS The authors are grateful of Surgery, for help and by the Medical Research Wellcome Trust for their
to Professor D. C. Carrer, Professor encouragement. JWLD is supported Council. We are also grateful to the support.
to alter the re-
seen in cancer
in Figure
in patients hepatic
and REE
is unlikely
in REE
lines
[17-191.
did not appear
MAMC
muscle
in any alteration
that
to adapt
an increase
disease
disease
ing that skeletal
suggested
losing state.
with malignant
regression
who
are able
have reported
malignant
lationship
[16]
patients
regression
metastases.
study
largely
has been
unstressed,
and colleagues
[13]
showed that the relationship between MAMC and whole body oxygen consumption was much poorer in the septic patient. Allowances will therefore have to be made for patients who have been recently stressed by trauma or surgery, and those who display any evidence of sepsis. In conclusion, it would appear that mid-arm muscle circumference can be used to estimate resting energy expenditure in patients with benign or malignant disease, although different relationships exist depending on whether the patient has or has not lost weight. This simple, easily performed measurement may therefore be of value in estimating the resting energy requirements of patients where access to indirect calorimetry facilities are unavailable.
REFERENCES
PI Askanazi J, Silverberg P A, Foster R U et al 1980 Effects
of respiratory apparatus on breathing patterns. Journal of Applied Physiology 48: 577-580 VI Harris J A, Benedict F G 1919 Biometric studies of basal metabolism in man. Carnegie Institute of Washington, Publication no 279 Washington DC [31 Robertson J D, Reid D D 1952 Standards for the basal metabolism of normal people in Britain. Lancet i: 940-943 [41 Roza A M, Shizgal H M 1984 The Harris-Benedict equation re-evaluated: resting energy requirements and the body cell mass. American Journal of Clinical Nurrition 40: 168-182 [51 Feurer I D, Crosby L 0, Mullen J L 1984 Measured and predicred resting energy expenditure in clinically stable patients. Clinical Nutrition 3: 27-34 [61 Kinney J M, Morgan A P, Domingues F J, Gildner K J 1964 A method for continuous measurement of gas exchange and expired radioactivity in acutely ill patients. Metabolism 13: 205-211 171 Weir J B de V 1949 New methods for calculating metabolic rate with special reference to protein metabolism. Journal of Physiology 109: l-9 PI Belcher E H, Vetter H 1971 Radioisotopes in medical diagnosis. 1st editn Butterworths, London, 258-297 PI World Health Organization 1966 Jellife D B. The assessment of the nutritional status of the community. Geneva: World Health Organization UOI Burkinshaw L 1978 Sex-dependent calibration factor of a whole-body radiation counter. International Journal of Applied Radiation and Isotopes 29: 387-390 illI Krebs H 1950 Body size and tissue respiration. Biochemica Biophysics Acta 4: 249-254 [121 Starker P M, Askanazi J, Lasala PA et al 1983 The effect of parenteral nutrition repletion on muscle wafer and electrolytes. Implications for body composition. Annals of Surgery 198: 213-217
CLINICAL NUTRITION
[ 131 Brown R, Gross E, Little R A et al 1984 Whole body oxygen consumption and anthropomerry. Clinical Nutrition 3: 1 l-16 [ 141 Harries A D, Jones L A, Heatley R H V et al 1985 Precision of anthropometric measurements: The value of mid-arm circumference. Clinical Nutrition 4: 77-80 [ 151 Hansel1 D T, Davies J W L, Burns H J G 1986 The relationship between resting energy expenditure and weight loss in benign and malignant disease. Annals of Surgery 203: 240-245 [ 161 Lindmark L, Bemtegard K, Eden E et al 1984 Resting energy expenditure in malnourished patients with and without cancer. Gastroenterology 87: 402-408 [17] Waterhouse C, Fenninger L D, Keutmann E H 1951
57
Nitrogen exchange and caloric expenditure in patients with malignant neoplasms. Cancer 4: 500-514 [ 181 Femtinger L D, Mider G B 1954 Energy and nitrogen metabolism in cancer. Advances in Cancer Research 2: 229-252 [ 191 Bozzetti F, Pagnoni A M, Del Vecchio M 1980 Excessive caloric expenditure as a cause of malnutrition in patients with cancer. Surgery, Gynecology and Obstetrics 150: 229-234 [20] Hansel1 D T, Davies J W L, Burns H J G 1986 Effects of hepatic metastases on resting energy expenditure in patients with colorectal cancer. British Journal of Surgery 73: 659662
Submission date: 3 July 1986. Accepted after revision: 6 October 1986