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Journal of the American College of Nutrition
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/uacn20
Phase Angle Evaluation of Lung Disease Patients
and Its Relationship with Nutritional and
Functional Parameters
Priscila Berti Zanella , Camila Coutinho Àvila , Fernanda Cardoso Chaves ,
Marcelo Basso Gazzana , Danilo Cortozi Berton , Marli Maria Knorst &
Carolina Guerini de Souza
To cite this article: Priscila Berti Zanella , Camila Coutinho Àvila , Fernanda Cardoso Chaves ,
Marcelo Basso Gazzana , Danilo Cortozi Berton , Marli Maria Knorst & Carolina Guerini de
Souza (2020): Phase Angle Evaluation of Lung Disease Patients and Its Relationship with
Nutritional and Functional Parameters, Journal of the American College of Nutrition, DOI:
10.1080/07315724.2020.1801535
To link to this article: https://doi.org/10.1080/07315724.2020.1801535
Published online: 11 Aug 2020.
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Phase Angle Evaluation of Lung Disease Patients and Its Relationship with
Nutritional and Functional Parameters
Priscila Berti Zanella
a
, Camila Coutinho
Avila
a
, Fernanda Cardoso Chaves
b
, Marcelo Basso Gazzana
c
,
Danilo Cortozi Berton
a,c
, Marli Maria Knorst
a,c
, and Carolina Guerini de Souza
a,b,d
a
Postgraduate Program in Pulmonary Sciences, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil;
b
Department of
Nutrition, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil;
c
Pulmonology Unit –Hospital de Cl
ınicas de Porto
Alegre (HCPA), Porto Alegr, RS, Brazil;
d
Food and Nutrition Research Center, Hospital de Clinicas de Porto Alegre, Universidade Federal do
Rio Grande do Sul, Porto Alegre, RS, Brazil
ABSTRACT
Background: This study aimed to determine the value of phase angle (PhA) in patients with
chronic obstructive pulmonary disease (COPD) and pulmonary hypertension (PH) and its associ-
ation with nutritional and functional parameters.
Methods: A cross-sectional study of 77 patients under follow-up at the pulmonary outpatient
clinic of a public hospital. Anthropometric measurements and functional assessments of physical
and pulmonary capacity were performed, and a regular physical activity questionnaire was
administered.
Results: The sample consisted of 38 patients with COPD (mean age, 63.8 ± 9.9 years; 68.4% female)
and 39 patients with PH (mean age, 46.6 ± 14.4 years; 79.5% female). There was no difference in
anthropometric measurements between patients with COPD and PH. Patients with COPD had mild
to moderate limitations of pulmonary function, while patients with PH had only mild limitations
(p <0.01). Although the median distance covered in the 6-minute walk test (6MWT) was different
between the COPD and PH groups (p <0.05), it was considered adequate for these populations.
Mean PhA was within the range considered adequate in patients with COPD (6.3±1) and PH
(6.2±0.8)(p>0.05). In the statistical analyses, although the correlations were weak, adequate
PhA correlated with fat free mass index, 6MWT, disease staging, forced vital capacity, and forced
expiratory volume in the first second.
Conclusion: The anthropometric profile of both patient groups was very similar, and PhA values
were within the expected range. Despite weak correlations, PhA is a clinical component to be fol-
lowed and investigated in patients with lung disease.
ARTICLE HISTORY
Received 23 May 2020
Accepted 21 July 2020
KEYWORDS
Anthropometry; electric
impedance; lung diseases;
nutritional status;
vital capacity
Introduction
Chronic respiratory diseases have an economic, social, and
quality-of-life impact on affected individuals (1). Chronic
obstructive pulmonary disease (COPD) and pulmonary
hypertension (PH) are two examples of this group. COPD is
a highly prevalent health problem worldwide, characterized
by persistent airflow limitation that is usually progressive
and associated with an increased inflammatory airway
response to toxic particles and gases (2). Cough and dyspnea
are the main symptoms, with the latter being most com-
monly related to disability and worsened quality of life (3).
Not as prevalent as COPD but with equal influence on qual-
ity of life, PH is a chronic lung disease defined as an
increase in resting mean pulmonary artery pressure (PAP >
25 mm Hg) and clinically characterized by causing dyspnea
and tiredness (4). Both COPD and PH may affect nutritional
status due to changes in energy metabolism and functional
disability caused by lung disease (5).
In recent years, bioelectrical impedance analysis (BIA)
has been widely used for body composition analysis in dif-
ferent patient groups, as it is a noninvasive, practical, low-
cost method whose results are easily reproducible and
quickly obtained (6,7). The method consists in the passage
of a high-frequency, low-amplitude electric current through
the body, which acts as a biological conductor (8). The body
offers two types of resistance to electric current, capacitive
resistance or reactance (Xc) and resistive resistance (R), and
impedance is the term used to describe the combination of
these two types of resistance. R reflects the opposition to
current flow exerted by intracellular and extracellular con-
tents, being directly related to the water content. Xc results
from the opposition to current flow exerted by cell mem-
branes and tissue interfaces by means of capacitance, i.e.,
the membranes store the energy of the electric current for a
short time, and this “slows down”their conduction, generat-
ing a drop in voltage and a phase shift (9). This phase shift
is geometrically quantified by the arctangent of the Xc/R
CONTACT Priscila Berti Zanella priscila_zanella@hotmail.com Postgraduate Program in Pulmonary Sciences, Universidade Federal do Rio Grande do Sul,
Rua Ramiro Barcelos 2400 - 2andar, Santa Cec
ılia 90035-003, Porto Alegre, Rio Grande do Sul, Brazil
ß2020 American College of Nutrition
JOURNAL OF THE AMERICAN COLLEGE OF NUTRITION
https://doi.org/10.1080/07315724.2020.1801535
ratio, which is called phase angle (PhA) (10). Thus, PhA is
positively associated with Xc, where higher values reflect
better cellularity, cell membrane integrity, and cell size and
function (9,11). Although its biological significance is not
yet fully clear, PhA has been considered an indicator of cell
membrane function (permeability, electrical properties) and
of changes in the quantity and quality of soft tissues (10,11).
Many studies have demonstrated the value of PhA as an
indicator of prognosis and survival in various clinical set-
tings, such as heart failure (12), renal failure (13), liver cir-
rhosis (14), amyotrophic lateral sclerosis (15), and many
types of cancer (16,17), in addition to showing an associ-
ation with nutritional status and muscle functionality (18).
Considering the applicability of PhA in several chronic dis-
eases, the objective of this study was to determine the value
of PhA in patients with COPD and PH and its association
with nutritional and functional parameters.
Materials and methods
Design and sample
This was a cross-sectional study of 77 patients with a diag-
nosis of COPD or PH treated at the specialized pulmonary
outpatient clinic of a public hospital. Eligible participants
were all patients aged 18 years or over and literate. Patients
with acute or chronic kidney disease, heart failure, malig-
nant neoplasms, liver disease, ascites, and edema were
excluded because these diseases/disorders are known to alter
the measurement of PhA. Oxygen users and those present-
ing with cognitive or functional impairment that could com-
promise the proposed assessments or to be unable to
perform them were also excluded. Patients with PH were
recruited and paired with patients with COPD, by conveni-
ence sampling. The study was conducted in accordance with
ethical guidelines and regulatory standards for research
involving human subjects (Resolution CNS/MS 466/13) and
approved by the institutional research ethics committee
(approval number: CAAE 40726915.6.0000.5327). Written
informed consent was obtained from all individual partici-
pants included in the study.
Nutritional parameters
Anthropometric measurements included weight measured
on a FilizolaV
Ranthropometric scale with maximum capacity
of 150 kg and resolution of 50 g, height measured with a 2-
m wall-mounted stadiometer, waist circumference (WC)
measured at the level of the umbilical scar with a non-
stretchable tape measure, and adductor pollicis muscle thick-
ness (APMT) measured in triplicate using a CescorfV
Rscien-
tific skinfold caliper. All measurements were performed by a
previously trained evaluator. Body mass index (BMI) was
calculated from measured weight and height and classified
according to the cutoff points proposed by the World
Health Organization (WHO) (1995) (19) for patients with
PH and the BODE index (20) for patients with COPD. The
cutoff points used for WC was 94 cm for male and 80 cm
for female proposed by the WHO (1997) (21), and APMT
thickness was that proposed Lameu et al. (22) being
12.5 mm for male and 10.5 mm for female.
A bioelectrical impedance analyzer (Biodynamics 450V
R;
Biodynamics Corp., Seattle, Washington, USA) was used for
BIA and PhA measurements, with an alternating current of
800 microA and a frequency of 50 kHz. Measurements were
performed with the patient in the supine position, barefoot,
with the lower limbs slightly apart and without metal objects
attached to the body, with two electrodes on the hand and
two on the foot, both on the right side of the body.
Participants were instructed not to engage in physical activ-
ity and not to consume caffeine-containing foods and bever-
ages on the day before the examination and to be on an 8-
hour fast. PhA was calculated by the following equation:
PhA()¼arctangent (Xc/R) (180/p)
3
. Body fat percent-
age (BF) and fat-free mass (FFM) in kg were also deter-
mined and used to calculate the fat-free mass index (FFMI)
by the formula FFM (kg)/height (m)
2
.
The cutoff points used for PhA were those proposed by
Bosy-Westphal et al. (2006) (23). For statistical analysis pur-
poses, it was established that the PhA values between 5th
percentile and 95th percentile were adequate, and the values
outside this range were inadequate. BF and FFMI were eval-
uated according to the cutoff points proposed by Morrow
et al. (2003) (24) and Franssen et al. (2014) (25), respect-
ively. The same evaluator also applied the Subjective Global
Assessment (SGA) tool using the model proposed by Detsky
et al. (1987) (26) in order to complement anthropomet-
ric data.
Functional parameters
Participants performed the 6-minute walk test (6MWT) on a
previously measured surface, 30 m in length, without oxygen
supplementation, with verbal encouragement at the begin-
ning of the test (27). According to the European Society of
Cardiology (28) parameters, based on the study by Sitbon
et al. (29), the values obtained in this test are satisfactory
when the walking distance is longer than 380 m. In addition,
respiratory capacity was assessed by forced expiratory vol-
ume in the first second (FEV
1
) and forced vital capacity
(FVC), measured by spirometry, using a computerized sys-
tem (GmbH, Wuerzburg, Germany).
Regular physical activity (RPA) was estimated by using a
questionnaire based on the one proposed by Neder and
Nery (30) for assessment of RPA levels. The total question-
naire score ranges from 3 to 15, and higher scores indicate
higher levels of physical activity.
Statistical analysis
Data were analyzed using SPSS, version 22.0. The normality
of data distribution was assessed by the Shapiro-Wilk test.
After this definition, specific tests were used for parametric
data (one-sample Student’sttest, Student’sttest for inde-
pendent samples, and Pearson’s correlation test) and non-
parametric data (Mann-Whitney U test and Spearman’s
2 P. B. ZANELLA ET AL.
correlation test). The level of statistical significance was set
at 5% (p <0.05) for all analyses, and the results are
expressed as percentage, mean and standard deviation, and
median (minimum –maximum).
Results
The sample consisted of 77 patients, 38 with COPD (68.4%
female) and 39 with PH (79.5% female). The mean age of
patients with COPD was 63.8 ± 9.9 years and of those with
PH was 46.6 ± 14.4 years (p <0.01). Mean time since diagno-
sis was 4.9 ± 2.1 years for patients with COPD and
3.0 ± 1.3 years for patients with PH. COPD staging, accord-
ing to the functional status score, identified 15.8% of
patients in class I, 18.4% in class II, 34.2% in class III, and
31.6% in class IV. For patients with PH, 30.8% were identi-
fied in functional class I, 38.5% in class II, 20.5% in class
III, and only 10.2% in class IV.
As there was no difference in anthropometric measure-
ments between patients with COPD and PH (p >0.05), their
distribution by sex is shown in Table 1. Mean BMI did not
differ between patients aged <60 years (n ¼47; 27.2 ± 6.6 kg/
m
2
) and patients aged 60 years and older (n ¼30;
27.1 ± 3.9 kg/m
2
)(p>0.05). Anthropometrically, more than
half of the participants were overweight, 16.9% were obese,
and 79.2% were overweight with a WC above the proposed
cutoff points (p <0.05). Complementing these data, 64.9%
of patients had BF above the proposed mean values, accord-
ing to sex and age. Mean APMT thickness and FFMI were
above the reference values (p <0.05), indicating no impair-
ment in the lean mass of these patients. In addition, none of
the patients were at nutritional risk according to SGA, and
all of them were considered well-nourished.
Table 2 shows the results of functional assessment related
to pulmonary function, including FVC, FEV
1
, and submaxi-
mal functional capacity evaluated by the 6MWT. The FVC
values of patients with COPD and PH indicated that both
groups had mild airflow limitation. FEV
1
values indicated
moderate airflow limitation in patients with COPD and mild
limitation in those with PH. The distance covered in the
6MWT by patients with COPD and PH was considered
adequate for these populations. The mean score obtained in
the RPA questionnaire was similar in the two patient groups
(COPD: 6.1 ± 1.6 vs. PH: 6.3 ± 1.2; p >0.05).
The mean PhA value was similar in the two patient
groups and within the range considered adequate (COPD:
6.3±1vs. PH: 6.2±0.8;p>0.05). However, in the CPOD
and PA male vs. female analysis, the groups showed
different PhA values (6.5±1.1vs. 6.0±0.7, respectively;
p<0.05). Similarly, there was a difference in PhA values
between eutrophic and overweight patients based on BMI
(5.9±0.6vs. 6.5±1.0, respectively; p <0.05). Regarding
disease staging, there was no difference in PhA between
patients with less severe (class I and II) and more severe
(class III and IV) disease (6.3±0.9vs. 6.1±0.9, respect-
ively; p >0.05), nor between patients aged <60 years and
patients aged 60 years and older (6.3±0.9vs. 6.2±0.9,
respectively; p >0.05). The distribution of PhA values is
shown in Figure 1.
Several weak correlations were found between age and
disease staging, age and FVC, and age and FEV
1
; between
6MWT and disease staging and 6MWT and RPA; and
between body composition and lung function parameters
(r <0.5, p <0.05, data not shown). Adequate PhA correlated
with FFMI, 6MWT, disease staging, FVC, and FEV
1
, but all
correlations were also weak. The crude PhA values corre-
lated with age.
Discussion
In the sample evaluated in this study, consisting mostly of
women aged <60 years, patients with COPD were signifi-
cantly older than those with PH and were in a higher func-
tional class of disease, a finding supported by functional
assessments, where the COPD group was shown to be sig-
nificantly more compromised. Despite functional differences,
the two groups did not differ in anthropometric measure-
ments: patients were considered well-nourished and with
adequate muscle mass, although they presented a significant
rate of overweight, increased BF and WC above the desir-
able range, in addition to being little active. PhA values
were considered to be within the normal range in
both groups.
The differences in age, disease staging, and pulmonary
involvement between patients with COPD and PH were
expected due to the characteristics of each lung disease, as
well as their causes (2,4). Similarly, previous studies have
shown that overweight is increasingly prevalent in lung dis-
ease (31,32), and these data are also supported by a previous
study that included only patients with PH (33), where the
level of physical activity was similar to that found in the
present sample.
In the healthy population, PhA usually ranges from 5to
7, being affected by age (reduced with aging), sex (lower in
women), and BMI (increased with increasing weight) (9,34).
In the analysis by sex, PhA was within the normal range in
both groups (male: 6.5vs. female: 6.0), similarly the
Table 1. Anthropometric Characterization of Patients with Lung
Disease (n ¼77).
Male Female Reference value
WC (cm) 101.1 ± 18.8
#
93.4 ± 12.3
#
M94
1
F80
1
APMT (mm) 14.4 ± 2.3
#
11.8 ± 3.4
#
M¼12.5
2
F¼10.5
2
FFMI (kg/m
2
)19.9 ± 3.7
#
17.5 ± 2.7
#
M16
4
F15
4
FFMI: fat-free mass index; APMT: adductor pollicis muscle thickness; WC: waist
circumference; Data are presented as mean± standard deviation.
1
cutoff
point for WC;
2
cutoff point for APMT;
3
cutoff point for FFMI.
#
statistical
difference between groups, p <0.05. References for the cutoff points are
provided in the Materials and Methods section.
Table 2. Functional Assessment of Patients with COPD and PH (n ¼77).
COPD PH P
FVC (%of predicted) 63.7 ± 19 82.6 ± 17.8 <0.01
VEF
1
(%of predicted) 50.7 ± 24.4 79 ± 18 <0.01
6MWT (m) 368.7 ± 118 419.3 ± 92.8 <0.05
6MWT (%of predicted) 66.2 ± 27.4 73.7 ± 14.7 0.42
6MWT: 6-minute walk test; COPD: chronic obstructive pulmonary disease; FVC:
forced vital capacity; PH: pulmonary hypertension; VEF
1
: forced expiratory
volume in the first second. Data are presented as mean ± stan-
dard deviation.
JOURNAL OF THE AMERICAN COLLEGE OF NUTRITION 3
limited data on PhA in lung disease, which show that, in
COPD, PhA is higher in men than in women (35–37). A
significantly higher PhA was found in overweight patients,
but the same was not observed in relation to age. One pos-
sible explanation for this finding is that, regardless of age,
patients in our sample had good nutritional status and
maintained their physical capacity, which generally decreases
over time and influences PhA.
Although several PhA reference values have been pub-
lished (38–40), only the reference values generated in a
healthy German population (n ¼214,732 adults) were strati-
fied by sex, age, and BMI, which are, as mentioned above,
the main determinants of PhA (23). According to this classi-
fication, the PhA values of the patients with lung disease
evaluated in the present study were very close to the values
reported for the healthy population, which may explain the
weak correlation found between PhA and the functional
markers of PH and COPD. Nevertheless, the clinical rele-
vance of PhA has been well documented over the years and
is important for nutritional assessment, as it may reflect cell
membrane integrity and cell function (9,18). In this respect,
PhA has been applied in many clinical settings, such as mal-
nutrition (41), preoperative and postoperative evaluation
(42), liver disease (43), cancer (17), renal failure (44), and
Crohn’s disease (45).
Although our study also showed a weak correlation
between PhA and lung disease staging, where adequate PhA
correlated with lower disease stages, the prognostic value of
this marker in relation to morbidity and mortality has been
consistently demonstrated (46,47). Toso et al. (48) reported
the association between PhA and survival of patients with
lung cancer, where the mean PhA value was chosen as the
cutoff point, with an average survival of 4 months in patients
with PhA 4.5vs. 12 months in patients with PhA >4.5.
Gupta et al. (2009) (47), also in a study of patients with
lung cancer, showed that patients with a PhA higher than
the median (5.3) had a significantly higher mean survival
rate (12.4 months) than those with the median or lower PhA
(7.6 months). They also reported sex-specific differences in
PhA values, where men had significantly higher values than
women (5.6vs. 4.9)(47). These data lead us to believe
that the weak correlation found between PhA values and
disease staging in the present study may be due to the small
sample size. Furthermore, the correlation found in our sam-
ple between adequate PhA and preserved lung capacity, as
assessed by FVC and FEV
1
, is consistent with the data
reported in the study by Blasio et al. (49), in which a multi-
variate analysis (R
2
0.333) showed that age, BMI, height,
weight, and FEV
1
were positively associated with PhA values
in men, while in women only height was positively associ-
ated with PhA; however, only the correlation with FEV
1
was
significant. In the same study, regarding respiratory muscle
strength, there was a significant association of maximal
inspiratory pressure with PhA in all patients, but of maximal
expiratory pressure with PhA only in men (49).
Regarding the BIA-related variables, resistance and react-
ance, both have been shown to be predictors of muscle
strength (50), and a direct correlation between lower limb
muscle strength and PhA has been reported (37). In the pre-
sent study, a weak but significant correlation was found
between PhA and FFMI, which directly expresses muscle
mass distribution in relation to patient height. In addition,
the PhA values of patients with PH and COPD were simi-
larly associated with their functional capacity by a direct
correlation with better performance in the 6MWT. In this
respect, Navigante et al. (2013) (51), in a study of cancer
patients with fatigue, showed a significant association of
PhA with hand grip strength, another important parameter
of muscle strength and functional capacity: when patients
were divided into subgroups according to PhA, the sub-
group with lower PhA values (<4) also had lower hand
grip strength values compared with patients with higher
PhA (>4).
The authors are unaware of a previous study that investi-
gated PhA in patients with PH. Although these patients
were in less severe functional classes of the disease and sig-
nificantly younger than patients with COPD, PhA in both
groups was very similar. This may suggest that the mainten-
ance of nutritional status and functional capacity, together
with disease treatment, may preserve cellular functionality
even in those patients with COPD with a more compro-
mised pulmonary function.
Some limitations of this study should be addressed. In
addition to the small sample size, the participants were
recruited by convenience sampling from an outpatient popu-
lation, which may not reflect the characteristics of the gen-
eral population. The sample consisted predominantly of
women and all participants were well-nourished, which cer-
tainly reflected on their functional characteristics. The cutoff
points used to assess the PhA were validated for a popula-
tion similar to ours, but not our population. Nevertheless,
we believe that reporting the results is important for a better
understanding of the relationships between lung disease and
the variables under study.
In this sense, could be interesting the evaluation of PhA
routinely, as part of nutritional assessment. BIA evaluation
is a fast, practical, noninvasiveness and relatively low cost
Figure 1. Phase angle (PhA) distribution of patients with chronic obstructive
pulmonary disease (COPD) and pulmonary hypertension (PH).
4 P. B. ZANELLA ET AL.
exam. At the same time, its reproducibility is reliable and
having a BIA device able to measure PhA is the only pre-
requisite. However, to health institutions with scarce finan-
cial resources, the cost of this type of BIA device could be
a limitation.
In a practical way, hospitalized patients who must
undergo nutritional screening to define nutritional care dur-
ing hospitalization, BIA assessment could be included at the
nutritional screening moment, and again at each nutritional
reassessment, to monitoring patients during hospitalization.
In outpatients BIA could be performed at each nutritional
or medical follow-up visit, if the health system does not pro-
vides nutritional care. Summarizing, PhA follow-up scheme
would be:
Hospitalized patients: a) in the first 24 hours after hospi-
talization together with nutritional screening; b) along with
the nutritional reassessment, following the protocol of nutri-
tional monitoring; c) before hospital discharge;
Outpatient: concomitant evaluation with the follow-up
visits of nutritional or medical care.
Conclusion
The PhA of patients with COPD and PH was within the
normal range, with no difference between the two patient
groups but significantly higher in men than in women.
Despite weak correlations, it is suggested that PhA is an
important clinical component to be followed and investi-
gated in patients with lung disease.
Disclosure statement
No potential conflict of interest was reported by the author(s).
References
1. Wang Y, Ghoshal AG, Muttalif ARBA, Lin HC,
Thanaviratananich S, Bagga S, Faruqi R, Sajjan S, Brnabic AJM,
Dehle FC, et al. Quality of life and economic burden of respira-
tory disease in Asia-Pacific-Asia-Pacific Burden of Respiratory
Diseases Study. Value Health Reg Issues. 2016;9:72–7. doi:10.
1016/j.vhri.2015.11.004.
2. Vogelmeier CF, Criner GJ, Martinez FJ, Anzueto A, Barnes PJ,
Bourbeau J, Celli BR, Chen R, Decramer M, Fabbri LM, et al.
Global strategy for the diagnosis, management, and Prevention
of Chronic Obstructive Lung Disease 2017 Report. GOLD execu-
tive summary. Am J Respir Crit Care Med. 2017;195(5):557–82.
doi:10.1164/rccm.201701-0218PP.
3. Arikan H, Savci S, Kutukcu EC, Vardar-Yagli N, Saglam M,
Inal-Ince D, Coplu L. The relationship between cough-specific
quality of life and abdominal muscle endurance, fatigue, and
depression in patients with COPD. Int J Chron Obstruct
Pulmon Dis. 2015;10:1829–35.
4. Gali
e N, Humbert M, Vachiery JL, Gibbs S, Lang I, Torbicki A,
Simonneau G, Peacock A, Noordegraaf AV, Beghetti M, et al.
2015 ESC/ERS Guidelines for the diagnosis and treatment of
pulmonary hypertension: The Joint Task Force for the Diagnosis
and Treatment of Pulmonary Hypertension of the European
Society of Cardiology (ESC) and the European Respiratory
Society (ERS): Endorsed by: Association for European Paediatric
and Congenital Cardiology (AEPC), International Society for
Heart and Lung Transplantation (ISHLT) . Eur Respir J. 2015;
46(4):903–75. doi:10.1183/13993003.01032-2015.
5. Gea J, Sancho-Mu~
noz A, Chalela R. Nutritional status and
muscle dysfunction in chronic respiratory diseases: stable phase
versus acute exacerbations. J Thorac Dis. 2018;10(Suppl 12):
S1332–S1354. doi:10.21037/jtd.2018.02.66.
6. Mulasi U, Kuchnia AJ, Cole AJ, Earthman CP. Bioimpedance at
the bedside: current applications, limitations, and opportunities.
Nutr Clin Pract. 2015;30(2):180–93. doi:10.1177/
0884533614568155.
7. Park JH, Jo YI, Lee JH. Clinical usefulness of bioimpedance ana-
lysis for assessing volume status in patients receiving mainten-
ance dialysis. Korean J Intern Med. 2018;33(4):660–9. doi:10.
3904/kjim.2018.197.
8. Nalepa D, Czarkowska M, Załuska W, Jakubowska K, Chru
sciel
P. Electrical bioimpedance in patients after ischemic stroke, a
civilization disease. Ann Agric Environ Med. 2019;26(1):46–50.
doi:10.26444/aaem/84849.
9. Norman K, Stob€
aus N, Pirlich M, Bosy-Westphal A. Bioelectrical
phase angle and impedance vector analysis-clinical relevance and
applicability of impedance parameters. Clin Nutr. 2012;31(6):
854–61. doi:10.1016/j.clnu.2012.05.008.
10. Mart
ın MAC, Silleras BM, Selva LN, Ortega SB, Rodr
ıguez LD,
Del R
ıo MPR. Bioimpedance vector analysis and conventional
bioimpedance to assess body composition in older adults with
dementia. Nutrition. 2015;31(1):155–9.
11. Giorgi A, Vicini M, Pollastri L, Lombardi E, Magni E,
Andreazzoli A, Orsini M, Bonifazi M, Lukaski H, Gatterer H.
Bioimpedance patterns and bioelectrical impedance vector ana-
lysis (BIVA) of road cyclists. J Sports Sci. 2018;36(22):2608–13.
doi:10.1080/02640414.2018.1470597.
12. Alves FD, Souza GC, Clausell N, Biolo A. Prognostic role of
phase angle in hospitalized patients with acute decompensated
heart failure. Clin Nutr. 2016;35(6):1530–4. doi:10.1016/j.clnu.
2016.04.007.
13. Shin JH, Kim CR, Park KH, Hwang JH, Kim SH. Predicting clin-
ical outcomes using phase angle as assessed by bioelectrical
impedance analysis in maintenance hemodialysis patients.
Nutrition. 2017;41:7–13. doi:10.1016/j.nut.2017.02.013.
14. Belarmino G, Gonzalez MC, Torrinhas RS, Sala P, Andraus W,
D’Albuquerque LAC, Pereira RMR, Caparbo VF, Ravacci GR,
Damiani L, et al. Phase angle obtained by bioelectrical imped-
ance analysis independently predicts mortality in patients with
cirrhosis. World J Hepatol. 2017;9(7):401–8. doi:10.4254/wjh.v9.
i7.401.
15. Roubeau V, Blasco H, Maillot F, Corcia P, Praline J. Nutritional
assessment of amyotrophic lateral sclerosis in routine practice:
value of weighing and bioelectrical impedance analysis. Muscle
Nerve. 2015;51(4):479–84. doi:10.1002/mus.24419.
16. Hui D, Dev R, Pimental L, Park M, Cerana MA, Liu D, Bruera
E. Association between multi-frequency phase angle and survival
in patients with advanced cancer. J Pain Symptom Manage.
2017;53(3):571–7. doi:10.1016/j.jpainsymman.2016.09.016.
17. B€
untzel J, Micke O, Kisters K, B€
untzel J, M€
ucke R. Malnutrition
and survival - bioimpedance data in head neck cancer patients.
In Vivo. 2019;33(3):979–82. doi:10.21873/invivo.11567.
18. Player EL, Morris P, Thomas T, Chan WY, Vyas R, Dutton J,
Tang J, Alexandre L, A, Forbes A. Bioelectrical impedance ana-
lysis (BIA)-derived phase angle (PA) is a practical aid to nutri-
tional assessment in hospital in-patients. Clin Nutr. 2019;38(4):
1700–6. doi:10.1016/j.clnu.2018.08.003.
19. World Health Organization. Physical status: the use and inter-
pretation of anthropometry. Technical Report Series, n. 854.
Geneva, 1995.
20. Celli BR, Cote CG, Marin JM, Casanova C, Oca MM, Mendez
RA, Plata VP, Cabral HJ. The body-mass index, airflow obstruc-
tion, dyspnea, and exercise capacity index in chronic obstructive
pulmonary disease. N Engl J Med. 2004;350(10):1005–12. doi:10.
1056/NEJMoa021322.
JOURNAL OF THE AMERICAN COLLEGE OF NUTRITION 5
21. World Health Organization. Obesity: Preventing and managing
the global epidemic. report. Geneva; 1997.
22. Lameu EB, Gerude MF, Corr^
ea RC, Lima KA. Adductor pollicis
muscle: a new anthropometric parameter. Rev Hosp Clin Fac
Med Sao Paulo. 2004;59(2):5967–2.
23. Bosy-Westphal A, Danielzik S, Dorhofer RP, Later W, Wiese S,
Muller MJ. Phase angle from bioelectrical impedance analysis:
population reference values by age, sex, and body mass index.
JPEN J Parenter Enteral Nutr. 2006;30(4):309–16. doi:10.1177/
0148607106030004309.
24. Morrow JRJ, Jackson AW, Disch JG, Mood DP. Medida e
avaliac¸~
ao do desempenho humano. 2a ed. Porto Alegre: Artmed.
2003.
25. Franssen FM, Rutten EP, Groenen MT, Vanfleteren LE, Wouters
EF, Spruit MA. New reference values for body composition by
bioelectrical impedance analysis in the general population: results
from the UK Biobank. J Am Med Dir Assoc. 2014;15:448.
26. Detsky AS, Mclaughlin JR, Baker JP, Johnston N, Whittaker S,
Mendelson RA, Jeejeebhoy KN. What is subjective global assess-
ment of nutritional status? JPEN J Parenter Enteral Nutr. 1987;
11(1):8–13. doi:10.1177/014860718701100108.
27. ATS statement: guidelines for the six-minute walk test. Am J
Respir Crit Care Med. 2002;166:111–7.
28. European Society Cardiology. Guidelines for the diagnosis and
treatment of pulmonary arterial hypertension. Eur Heart J. 2009;
30:2493–537.
29. Sitbon O, Humbert M, Nunes H, Parent F, Garcia G, Herv
eP,
Rainisio M, Simonneau G. Long-term intravenous epoprostenol
infusion in primary pulmonary hypertension: prognostic factors
and survival. J Am Coll Cardiol. 2002;40(4):780–8. doi:10.1016/
S0735-1097(02)02012-0.
30. Neder AJ, Nery L. Fisiologia cl
ınica do exerc
ıcio teoria e pr
atica.
S~
ao Paulo: Artes M
edicas, 2003.
31. Peters U, Suratt BT, Bates JHT, Dixon AE. Beyond BMI: obesity
and lung disease. Chest. 2018;153(3):702–9. doi:10.1016/j.chest.
2017.07.010.
32. Rubinsztajn R, Przybyłowski T, Grabicki M, Karwat K, Maskey-
WarzeRchowska M, Batura-Gabryel H, Chazan R. Comorbidities
in chronic obstructive pulmonary disease: Results of a national
multicenter research project. Adv Clin Exp Med. 2019;28(3):
319–24. doi:10.17219/acem/78024.
33. Zanella PB,
Avila CC, Souza CG. Anthropometric Evaluation
and functional assessment of patients with pulmonary hyperten-
sion and its relationship with pulmonary circulation parameters
and functional performance. J Am Coll Nutr. 2018;37(5):1–6.
34. Stobaus N, Pirlich M, Valentini L, Schulzke JD, Norman K.
Determinants of ebioelectrical phase angle in disease. Br J Nutr.
2012;107(8):1217e20. doi:10.1017/S0007114511004028.
35. Abbatecola AM, Fumagalli A, Spazzafumo L, Betti V, Misuraca
C, Corsonello A, Cherubini A, Guffanti EE, Lattanzio F. Body
composition markers in older persons with COPD. Age Ageing.
2014;43(4):548–53. doi:10.1093/ageing/aft196.
36. Blasio F, Santaniello MG, de Blasio F, Berlingieri GM, Bellofiore
B, Scalfi L. Bioelectrical impedance analysis (BIA) in the assess-
ment of muscular function in patients suffering from COPD.
Chest. 2014;145(3):468A. doi:10.1378/chest.1829906.
37. Maddocks M, Kon SS, Jones SE, Canavan JL, Nolan CM,
Higginson IJ, Gao W, Polkey MI, Man WDC. Bioelectrical
impedance phase angle relates to function, disease severity and
prognosis in stable chronic obstructive pulmonary disease. Clin
Nutr. 2015;34(6):1245–50. doi:10.1016/j.clnu.2014.12.020.
38. Barbosa-Silva MC, Barros AJ, Wang J, Heymsfield SP, Pierson
RNJ. Bioelectrical impedance analysis: population reference
values for phase angle by age and sex. Am J Clin Nutr. 2005a;
82(1):49–52. doi:10.1093/ajcn/82.1.49.
39. Saragat B, Buffa R, Mereu E, Rui M, Coin A, Sergi G, Marini E.
Specific bioelectrical impedance vector reference values for
assessing body composition in the Italian elderly. Exp Gerontol.
2014;50:52–6. doi:10.1016/j.exger.2013.11.016.
40. Kuchnia AJ, Teigen LM, Cole AJ, Mulasi U, Gonzalez MC,
Heymsfield SB, Vock DM, Earthman CP. Phase angle and
impedance ratio: reference cut-points from the United States
National Health and Nutrition Examination Survey 1999–2004
from bioimpedance spectroscopy data. J Parenter Enteral Nutr.
2017;41(8):1310–5. doi:10.1177/0148607116670378.
41. Jansen AK, Gattermann T, Fink JS, Saldanha MF, Rocha CDN,
Moreira THS, Silva FM. Low standardized phase angle predicts
prolonged hospitalization in critically ill patients. Clin Nutr
Espen. 2019;34:68–72. doi:10.1016/j.clnesp.2019.08.011.
42. Silva TK, Perry IDS, Brauner JS, Wender OCB, Souza GC, Vieira
SRR. Performance evaluation of phase angle and handgrip
strength in patients undergoing cardiac surgery: prospective
cohort study. Aust Crit Care. 2018;31(5):284–90. doi:10.1016/j.
aucc.2017.09.002.
43. Dorna MS, Costa NA, Oliveira EP, Sassaki LY, Romeiro FG,
Paiva SAR, Minicucci MF, Silva GF. Association between phase
angle, anthropometric measurements, and lipid profile in HCV-
infected patients. Clinics (Sao Paulo). 2013;68(12):1555–8. doi:10.
6061/clinics/2013(12)13.
44. Han BG, Lee JY, Kim JS, Yang JW. Clinical significance of phase
angle in non-dialysis CKD stage 5 and peritoneal dialysis
patients. Nutrients. 2018;10(9):1331. doi:10.3390/nu10091331.
45. Cioffi I, Marra M, Imperatore N, Pagano MC, Santarpia L,
Alfonsi L, Testa A, Sammarco R, Contaldo F, Castiglione F,
et al. Assessment of bioelectrical phase angle as a predictor of
nutritional status in patients with Crohn’s disease: A cross sec-
tional study. Clin Nutr. 2020; 39(5):1564–71. doi:10.1016/j.clnu.
2019.06.023.
46. Gupta D, Lammersfeld CA, Vashi PG, King J, Dahlk SL, Grutsch
JF, Lis CG. Bioelectrical impedance phase angle as a prognostic
indicator in breast cancer. BMC Cancer. 2008;8(1):249. doi:10.
1186/1471-2407-8-249.
47. Gupta D, Lammersfeld CA, Vashi PG, King J, Dahlk SL, Grutsch
JF, Lis CG. Bioelectrical impedance phase angle in clinical prac-
tice: implications for prognosis in stage IIIB and IV non-small
cell lung cancer. BMC Cancer. 2009;9(1):37. doi:10.1186/1471-
2407-9-37.
48. Toso S, Piccoli A, Gusella M, Menon D, Bononi A, Crepaldi G,
Ferrazzi E. Altered tissue electric properties in lung cancer
patients as detected by bioelectric impedance vector analysis.
Nutrition. 2000;16(2):120–4. doi:10.1016/S0899-9007(99)00230-0.
49. Blasio F, Santaniello MG, Blasio F, Mazzarella G, Bianco A,
Lionetti L, Franssen FME, Scalfi L. Raw BIA variables are predic-
tors of muscle strength in patients with chronic obstructive pul-
monary disease. Eur J Clin Nutr. 2017;71(11):1336–40. doi:10.
1038/ejcn.2017.147.
50. Norman K, Pirlich M, Sorensen J, Christensen P, Kemps M,
Sch€
utz T, Lochs H, Kondrup J. Bioimpedance vector analysis as
a measure of muscle function. Clin Nutr. 2009;28(1):78–82. doi:
10.1016/j.clnu.2008.11.001.
51. Navigante A, Morgado PC, Casbarien O, Delgado NL, Giglio R,
Perman M. Relationship between weakness and phase angle in
advanced cancer patients with fatigue. Support Care Cancer.
2013;21(6):1685–90. doi:10.1007/s00520-012-1714-2.
6 P. B. ZANELLA ET AL.
