NUTRITIONAL STATUS IN HOSPITALIZED PATIENTS
ASSESSMENT OF NUTRITIONAL STATUS IN A POPULATION OF
RECENTLY HOSPITALIZED PATIENTS
DIEGO F. WYSZYNSKI1,
ADRIANA CRIVELLI2, SILVIA EZQUERRO2, ADRIANA RODRIGUEZ2
Epidemiology, School of Hygiene and Public Health, The John Hopkins
University, Baltimore MD, USA; 2División de Gastroenterología,
Hospital General de Agudos Mario V. Larrain, Berisso, Provincia de
Key words: hospital-related malnutrition, serum albumin,
in the hospital is not a new or rare problem, however, it is often
unrecognized. In order to determine the baseline nutritional
characteristics of recently hospitalized patients, we assessed the
nutritional status of all medical in-patients between April and
December 1994 in a large hospital in the province of Buenos Aires. One
hundred and seventy patients were derived from the Internal Medicine
ward and 176 patients from the General Surgery ward. Surgery patients
were younger (median: 46 years vs 58 years of the Medicine patients).
Among Medicine patients, cardiovascular and respiratory afflictions
were the most common (30%), while gastrointestinal disorders were more
often seen in Surgical patients (71%). A weight loss of more than 10%
(%WL) was found in 12% of the Medicine and Surgery patients and a body
mass index (BMI) of less than 19 kg/m2 was observed in about 5% of
both groups. Ten percent of the Medicine patients and 14% of the
Surgery patients were overweight. A mid-upper arm muscle circumference
(MUAMC) less than the fifth percentile was found in 11% of the
Medicine patients but in only 3% of the Surgery patients. These
results suggest that this population of recently hospitalized patients
is at high-risk for medical complications. Therefore, early nutrition
assessment and appropriate nutrition intervention are required to
improve clinical outcome and help reduce the cost of health care.
del estado nutricional de una población de pacientes recientemente
hospitalizados. La malnutrición hospitalaria no es un problema nuevo
o infrecuente, sin embargo es comunmente no diagnosticada. Con el
objetivo de determinar las características nutricionales basales de
pacientes recientemente hospitalizados, evaluamos la composición
nutricional de todos los pacientes internados entre abril y diciembre
de 1994 en un hospital de la Provincia de Buenos Aires. La muestra
consistió en 170 pacientes internados en Clínica Médica y 176 en
Cirugía General. Los pacientes quirúrgicos eran más jóvenes
(mediana: 46 años vs 58 años de los pacientes de Clínica). Entre
los pacientes de Clínica, las afecciones cardiorespiratorias fueron
las más frecuentes (30%), en tanto que trastornos gastrointestinales
fueron más comunes entre los pacientes quirúrgicos (71%). Una
pérdida de peso de más de 10% se halló en 12% de los pacientes de
Clínica y Cirugía, y un índice de masa corporal de menos de 19
kg/m2 fue observado en cerca del 5% de ambos grupos. Diez por ciento
de los pacientes de Clínica y 14% de los quirúrgicos tenían
sobrepeso. Una circunferencia muscular braquial menor al quinto
percentilo fue hallada en 11% de los pacientes de Clínica pero sólo
en 3% de los pacientes quirúrgicos. Estos resultados sugieren que
esta población de pacientes recientemente hospitalizados está en
alto riesgo de complicaciones médicas. Por lo tanto, la evaluación e
intervención nutricional tempranas son necesarias para mejorar el
cuadro clínico y reducir los costos de salud.
Postal address: Dr. Diego F. Wyszynski, Department of
Epidemiology, The John Hopkins School of Public Health, 615 N. Wolfe
Street, Baltimore, MD 212051, USA,
Fax: (410) 550-7513; e-mail: email@example.com
Received: 5-VI-1997 Accepted: 13-VIII-1997
It is a well known fact that the prevalence of malnutrition in
hospitalized patients, especially among surgical ones, is high.1-7
Malnutrition occurs when the intake and/or absorption of nutrients is
less than the metabolic requirements so that an impairment of
physiological function results.8 Since nutritional status is an
important factor influencing clinical outcome, early recognition and
treatment of malnourished patients may reduce the incidence of pre-
and post-operative complications; morbidity and mortality; and the
patient’s cost per day and length of hospital admission.9-15 It is
thus beneficial both for quality of care and for economic reasons to
detect and treat malnutrition.8
Anthropometric measurements are widely used in the assessment of
nutritional status, particularly when an imbalance between intakes of
protein and energy occurs. Such disturbances modify the patterns of
physical growth and the relative proportions of the body tissue such
as fat, muscle, and total body water.16 Clinically important
malnutrition is also frequently diagnosed if serum albumin level is
less than 3.5 g/dl, total lymphocyte count is less than 1800 mm3, or
body weight has involuntarily decreased more than 15%.17
Recently, Nightingale et al.8 assessed the nutritional status of
eighty-four in-patients at the Leicester Royal Infirmary (Leicester,
England). They concluded that using percentage weight loss (%WL), body
mass index (BMI), and mid-upper arm muscle circumference (MUAMC), the
prevalence of malnutrition on their general medical ward was 35%. Only
28% of the malnourished patients had been diagnosed as such by a
Malnutrition acquired in the hospital setting remains a serious
problem around the world.18 In Argentina, data to substantiate this
assertion are scarce. In order to determine fluctuations of body
weight during the time of hospitalization, it is necessary to have a
baseline measurement at entry. The purpose of this work was four-fold:
(1) to estimate prospectively the nutritional status of newly
hospitalized patients in a hospital of the province of Buenos Aires,
(2) to identify the prevalence of malnutrition and obesity in patients
hospitalized in the Medicine and Surgery wards of this hospital, (3)
to determine whether there are significant nutritional differences
between the two groups of inpatients, and (4) to assess whether %WL,
BMI, and MUAMC are reliable measurements for the identification of
malnourished patients in this population.
Patients and methods
All hospitalized patients seen at the Internal Medicine and General
Surgery clinics of the Hospital General de Agudos Mario V. Larrain
(city of Berisso, province of Buenos Aires, Argentina) between April
and December 1994, were entered in the study. Three hundred and
forty-six patients were assessed (170 from the Internal Medicine ward
and 176 from the General Surgery ward). Procedures were in accordance
with guidelines provided by the Hospital Ethics Committee.
Patients underwent nutritional assessment within 72 hours of
admission. Weight, height, triceps skinfold thickness (TSF) and
mid-upper arm circumference (MUAC) were measured. Calculations for
percentage weight loss (%WL), body mass index (BMI), and mid-upper arm
muscle circumference (MUAMC) were performed as follows:
%WL = previous weight (kg) - current weight (kg) x 100 / previous
BMI (kg/m2) = current weight (kg) / height (m)2
MUAMC (cm) = MUAC (cm) - [3.14 x TSF (cm)]
Previous weight was defined as the usual weight during the previous
year. The MUAC (the mid-way between the tip of the acromion and
olecranon processes) and the TSF measurements were carried out by one
observer on the relaxed non-dominant arm. MUAC values were obtained
using a non-extensible tape measure and TSF values were measured using
Lange skinfold calipers. The average of three measurements was
computed for both MUAC and TSF.
Aliquots of serum were obtained and stored at -20ºC until analysis.
Serum albumin determinations were made using a spectrophotometric
method based on the binding of bromocresol to albumin. Hemoglobin and
total lymphocyte measurements were carried out by the hospital
laboratory using standard Coulter counter methods.
Differences between Medicine and Surgery patients were assessed via
the chi-square test (for categorical variables) and the Mann- Whitney
test (for continuous variables). Normality was investigated using
Royston’s extension of the Shapiro-Wilk W test.19-20 Where
necessary, the data were transformed logarithmically to normalize
their distributions. Sex-adjusted partial correlation coefficients
were obtained following Theil’s method.21 Multiple linear regression
was performed to investigate which variables (e.g., age, TS, MUAC, WC,
and sex) might contribute to BMI. All analysis were performed using
STATA statistical software.22
Baseline group characteristics
Over the 9-month study, 346 patients were admitted to the hospital
and constituted the study population. On admission to the hospital, or
up to 72 hours after admission, 170 patients (49.1%) were hospitalized
in the Internal Medicine ward and 176 patients (50.9%) were
hospitalized in the General Surgery ward. Baseline characteristics for
the study population are presented in Table 1.
The male to female ratio reflects the proportion of beds available for
each sex rather than the sex ratio and the morbidity in the general
population. Participants were predominantly middle-aged, although the
age range was wide (14-95 for Medicine patients, 15-83 for Surgery
patients). Medicine patients were older (median, Medicine patients: 58
years, Surgery patients: 46 years; p < 0.001). The skewed
proportion of gastrointestinal patients admitted for surgery (71% of
all surgical patients) is a reflection of the expertise of the
surgeons of this hospital in performing laparoscopic
cholecystectomies. This observation is also consistent with the
shorter hospital stay for Surgery patients when contrasted to Medicine
patients (Surgery participants, median hospital stay: 7 days, range 1
- 67; Medicine patients, median: 9 days, range 1-83; p = 0.0175).
Baseline nutritional characteristics of the Medicine and Surgery
patients are reported in Table 2. Body mass index (p < 0.05),
triceps skinfold thickness (p < 0.05), mid-upper arm circumference
(p < 0.001), mid-upper arm muscle circumference (p < 0.001), and
albumin (p < 0.001) were all significantly greater in Surgery
patients compared to Medicine patients. Current weight was higher than
ideal by 10.4% for Medicine subjects and by 14.3% for Surgery
subjects. This excess of body weight was also identified using BMI,
which categorized both groups as “slightly overweight” with “acceptable
but not desirable” weight.23
The average anthropometric data and serum albumin, hemoglobin, and
total lymphocytes are consistent with good nutritional status.
However, 27 Medicine patients (16%) presented a BMI above 30 kg/m2
(obese), while 51 surgery patients (29%) were above that level. The
difference in BMI between these two groups was not statistically
significant. Eight Medicine (5%) and 10 Surgery (6%) patients were
considered malnourished (BMI < 19 kg/m2). In both groups, a modest
average decrease in body weight, about 3%, was experienced in the
previous year. Twenty-one patients (12%) in each group, however, had
lost more than 10 percent of their weight. A MUAMC less than the 5th
percentile and within the reference age range24 detected 18 Medicine
(11%) and 5 Surgery (3%) patients to be malnourished.
When patients with diagnosed forms of cancer were compared to
non-cancer patients, only TS (p = 0.01) and hemoglobin (p = 0.0005)
were significantly higher in the latter. Current weight, BMI, UAC,
UAMC, WC, and total lymphocytes were not significantly different
between one group and the other.
The sex-adjusted partial correlation coefficients for body mass
index versus other selected variables are shown in table 3. In both
groups, body mass index increased with current body weight, triceps
skinfold thickness, mid-upper arm circumference, mid-upper arm muscle
circumference, wrist circumference, and hemoglobin. Body mass index
was also correlated with age in the Surgery group.
Multiple regression analyzes were performed to investigate what
variables contributed significantly to a model in which body mass
index was the dependent variable. The results are presented in table
4. Age, triceps skinfold thickness, mid-upper arm circumference, and
wrist circumference contributed significantly to the model in both
groups, indicating a relatively greater body mass index for increasing
values of each variable when the others were held constant. A
significant positive regression was found for sex in Surgery subjects,
thereby indicating that for the same age, triceps skinfold thickness,
mid-upper arm circumference, and wrist circumference, women had a
higher body mass index compared with men. The combination of these
variables explained 70 and 76 percent of the variance in body mass
index in Medicine and Surgery patients, respectively.
Comparison of methods for the identification of malnourishment
Venn diagrams showing the number of patients detected as
malnourished by measuring % WL, BMI, and MUAMC are depicted in fig. 2.
For the Medicine group, no patients were detected as malnourished by
all three methods. %WL detected the most patients as malnourished
(18/170, 11%). Fourteen patients (8%) were declared malnourished by
MUAMC alone and 3 (2%) by BMI alone. For the Surgery group, only 2
patients (1%) were identified as malnourished by all three methods,
while %WL alone identified 15 (9%), MUAMC alone 5 (3%), and BMI alone
The present study investigated a cohort of recently hospitalized
subjects using a multicomponent body composition model to estimate
their nutritional status. Results suggest that, in this population,
patients admitted to the Medicine and Surgery wards are, on average,
slightly overweight, as expressed by their BMI. No substantial
differences in nutritional status were found between these two groups,
suggesting that medical variables (i.e., patient’s diagnosis) might
be poor nutritional predictors.
In interpreting these observations, we must consider several points.
Potential confounders, such as tobacco and alcohol use, fat and
caloric consumption, daily physical activity, and social class of the
patients were not collected as part of the present study. The
explained variances of the regression models developed in Medicine and
Surgery patients were high (~70 and 76 percent, respectively),
however, this does not imply that the models can be used to predict
BMI. No advanced model building techniques were used to develop the
best prediction models.
Although there is considerable overlap between the techniques for
detecting malnutrition, each has advantages and drawbacks. Both %WL
and BMI depend upon patients being mobile enough to be weighed on
accurate scales. Eighty-one percent of the Medicine patients and 95%
of the Surgery participants could be weighed. The % WL relies upon
patients ‘knowing’ their previous weight and then not over or
under estimating it.8 The %WL detects as malnourished many patients
who are or who have been overweight, but because they have
unintentionally lost weight quickly, they have lost mainly lean body
mass.25 These patients, who may also be detected by MUAMC, need
nutritional support by they are rarely recognized. Another
methodological limitation is that serum albumin is a negative acute
phase protein, and the serum concentration is influenced by fluid
shifts26, which we have not assessed in this study.
The method of combining % WL, BMI, and MUAMC, proposed by Nightingale
et al.8, proved not to be reliable in our population. We strongly
support the idea that obtaining data to assess the nutritional status
of patients is essential to optimal patient care, especially for
patients at high risk of malnutrition.27 However, their method showed,
with few exceptions, that each measurement identified different
individuals as being malnourished. Furthermore, emphasis should be
placed on the fact that it is not enough to assess and identify
malnutrition. Outcomes are improved and costs are saved only when
appropriate nutritional intervention is made available to those who
need it. Dietitians are ideally positioned to assess and recommend
appropriate, timely, and cost-effective nutrition.28 As shown in this
paper, more attention should be paid to the nutritional status of
every hospitalized patient. Therefore, we believe all hospitals should
include a nutrition support team. When fulfilled, these objectives
will lead to a better outcome for the patients, and ultimately to a
significant cut in the health care costs for the community in general.
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TABLE 1.- Baseline characteristics of Medicine and Surgery ward
Medicine Patients Surgery Patients
(n = 170) (n = 176)
n %* n %
Male 103 60.6 97 55.1
Female 67 39.4 79 44.9
< 25 14 8.2 22 12.5
25-39 24 14.1 47 26.7
40-49 24 14.1 32 18.1
50-59 26 15.3 36 20.5
60-69 27 15.9 27 15.3
70+ 55 32.4 12 6.8
Type of Disorder
Gastrointestinal 21 12.4 125 71.0
Neurologic 7 4.1 - -
Urologic 14 8.2 14 8.0
Cardiovascular-Respiratory 51 30.0 5 2.8
Infectious 25 14.7 - -
Endocrinologic 14 8.2 4 2.3
Psychiatric 10 5.9 - -
Traumatologic 11 6.5 10 5.7
Hematologic 6 3.5 4 2.3
Rheumatologic 3 1.8 - -
Dermatologic 8 4.7 1 0.6
Other 6 3.5 13 7.4
* Percentages do not sum up to 100 because of rounding.
TABLE 2.- Comparison of nutritional status in Medicine and Surgery
Medicine Patients Surgery Patients
(n = 170) (n = 176)
Mean SDa Mean SD
Current body weight (kg) 71.1 18.0 72.6 15.1
Ideal Absolute weight (kg) 64.1 7.0 63.6 7.3
Deviation from Ideal Weight (%) + 10.4 b + 14.3
Usual Weight (kg) 73.9 17.0 74.9 15.5
Deviation from Usual Weight (%) -3.3 -3.5
Height (cm) 165.1 9.9 164.6 10.1
Body Mass Index (kg/m2) 26.5 5.9 26.8 5.2
Triceps skinfelt thikness (cm) 14.9 16.3 16.9 * 16.2
Mid-upper Arm circumference (cm) 26.9 4.5 28.9 ** 3.8
Mid-upper Arm Muscle
Circumference (cm) 22.2 3.7 23.6 ** 3.4
Wrist Circumference (cm) 16.8 1.8 16.9 1.9
Body size 9.9 0.8 9.9 0.9
Albumin 3.6 0.6 3.8 c 0.5
Hemoglobin 13.2 2.7 13.5 2.1
Total Lymphocytes 1876.3 756.3 2033.3 809.1
aSD, standard deviation.
ba positive (+) sign indicates gain in weight, a negative sign (-)
indicates loss of weight.
cp < 0.001 using the Mann-Whitney test on normally distributed data
*p < 0.05, **p < 0.001 comparing Medicine and Surgery patients
using the Mann-Whitney test on log-transformed data
TABLE 3.- Sex-adjusted partial correlation coefficients for body
mass index and other variables,
Source Medicine Surgery
Age -0.1213 -0.3224***
Current body weight (kg) -0.9354*** -0.9024***
Height (cm) -0.0495 -0.0551
Triceps Skinfold Thickness (TS,cm) -0.6989*** -0.6547***
Mid-upper Arm Muscle Circumference (MUAC,cm) -0.7294*** -0.8162***
Mid-upper Arm Muscle Circumference (MUAMC,cm) -0.1848* -0.4659***
Wrist Circumference (WC,cm) -0.7054*** -0.5865***
Body Size -0.7176*** -0.6250***
Albumin -0.0332 -0.1249
Hemoglobin 0.1786* 0.1058
Total Lymphocytes -0.0028 -0.0664
aWhere necessary, variables were log-transformed.
*p < 0.05; **p < 0.01; *** p < 0.001.
TABLE 4.- Multiple regression of body mass index (BMI) versus
Coefficient ± SEb Coefficient ± SE
Intercept -0.579 ± 0.325 -1.007 ± 0.275***
Age 0.097 ± 0.024*** 0.093 ± 0.019***
Triceps Skinfold Thickness (TS,cm) 0.143 ± 0.019*** 0.088 ± 0.020***
Mid-upper Arm Circumference (MUAC,cm) 0.483 ± 0.102*** 0.803 ±
Wrist Circumference (WC,cm) 0.526 ± 0.154** 0.323 ± 0.090***
Sexc N.S. 0.058 ± 0.023*
r2d 0.698 0.762
aBMI, age, TS, MUAC, and WC were log-transformed; only the most
parsimonious models are presented.
bSE, standard error.
c1 = male; 2 = female.
r2d, explained variance of the model.
*p < 0.05; **p < 0.01; *** p 0.001.
N.S., not significant
Fig. 1.- Model of the effect of nutrition intervention on outcomes
and cost savings. Adapted from Mason M, ed. Costs and Benefits of
Nutritional Care, Phase I. Chicago, III: American Dietetic
Fig. 2.- Venn diagram showing the number of patients detected as
malnourished by the three methods, in 170 Internal Medicine and 176
General Surgery ward patients in whom percentage weight loss (%WL),
body mass index (BMI) and mid-upper arm muscle circumference (MUAMC)
could be determined.