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EDITED BY
Roberto Cannataro,
University of Calabria, Italy
REVIEWED BY
Andrea Giorgi,
Azienda USL Toscana Sud Est, Italy
Catarina Matias,
Lusofona University, Portugal
*CORRESPONDENCE
Francesco Campa
francesco.campa@unipd.it
RECEIVED 27 May 2024
ACCEPTED 24 June 2024
PUBLISHED 08 July 2024
CITATION
Holway FE, Campa F, Petri C, Spena LR and
Szydlowski NY (2024) Kinanthropometry and
dietary habits of non-professional rugby
players.
Front. Sports Act. Living 6:1439358.
doi: 10.3389/fspor.2024.1439358
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Kinanthropometry and dietary
habits of non-professional
rugby players
Francis E. Holway1, Francesco Campa2*, Cristian Petri3,4,
Luciano R. Spena5and Natalia Y. Szydlowski6
1
Departamento de Medicina Aplicada a los Deportes, Club Atlético River Plate, Buenos Aires, Argentina,
2
Department of Biomedical Sciences, University of Padua, Padova, Italy,
3
Department of Sport and
Informatics, Section of Physical Education and Sport, Pablo de Olavide University, Sevilla, Spain,
4
Medical Department of A.C.F. Fiorentina S.r.l., Florence, Italy,
5
Departamento de Nutrición, Universidad
de Morón, Buenos Aires, Argentina,
6
Departamento de Medicina, CEFAR, Buenos Aires, Argentina
Introduction: Evaluating the body composition and dietary habits of non-
professional athletes can help identify areas for improvement to enhance sports
performance. The present study aimed to describe the anthropometric and
body composition features, as well as the dietary habits, of non-professional
rugby players in Argentina.
Methods: Fifty-seven rugby players from a Group III Club of the Unión de Rugby de
Buenos Aires (URBA) were assessed using extensive anthropometric measurements
according to the International Society for the Advancement of Kinanthropometry
(ISAK) protocol. Reference data from professional rugby players in Group I clubs
were used as a control for body composition comparisons. Dietary intake was
evaluated using the 24-h recall method, and nutrient analysis was performed with
SARA software.
Results: Non-professional rugby players were shorter (Forwards: 175.9 vs. 181.5 cm;
Backs: 172.5 vs. 175.7 cm), had higher body fat percentages (Forwards: 16.4 vs. 12.3%;
Backs: 11.0 vs. 9.3%), and were less muscular (Forwards: 46.0 vs. 48.8%; Backs: 48.4 vs.
50.2%) compared to professional rugby players. The average dietary intake
was 3,363 Kcal, with protein and carbohydrate intakes of 1.4 g kg
−1
day
−1
and
4.1 g kg
−1
day
−1
, respectively, and 35% of energy intake from fat. Backs reported a
higher caloric intake than forwards (3,682 vs. 2,827 Kcal). There was a high
prevalence of insufficient intake of calcium (58%), vitamin A (49%), and vitamin C
(65%), the latter two corresponding with a low intake of fruits and vegetables (6% of
total energy intake). Meal pattern analysis showed that 46% of total energy was
ingested at dinner.
Conclusions: The body composition of non-professional rugby players from low-
income clubs could be improved to enhance rugby performance, as compared to
players in more competitive tiers. Economic constraints might contribute to a
sub-optimal nutritional profile, potentially affecting body composition and on-
field performance negatively. Recommendations to improve dietary intake
should be made considering the budget constraints of these players.
KEYWORDS
body composition, anthropometry, nutrition, sports team, multicomponent models
1 Introduction
Body composition describes the various components that make up body mass. These
components can be described and organized according to increasing levels of complexity,
divided into five distinct levels (1), as shown in Figure 1. For example, an oxygen atom
combined with two hydrogen atoms forms a water molecule, which is then incorporated
TYPE Original Research
PUBLISHED 08 July 2024
|
DOI 10.3389/fspor.2024.1439358
Frontiers in Sports and Active Living 01 frontiersin.org
into different cells, albeit in varying quantities, as well as into
extracellular spaces. Different groups of cells are then organized
to form tissues, which generate organs and result in systems that
are part of the fourth level of organization. Regarding this fourth
level, each component results from the sum of different types of
molecules. For instance, visceral and internal adipose tissue not
only include non-essential lipids that constitute fat mass at the
molecular level but also small amounts of water, proteins, and
other molecules that combine to form vessels and connective
components, which are part of the adipose tissue (2).
The quantification of body composition parameters can be
achieved through indirect methods or using predictive formulas
based on anthropometric or bioimpedance measurements and is
generally tailored to the specific needs of the groups being
assessed. In sports, it is common to consider parameters such as
fat mass, body water, adipose tissue, and muscle tissue.
Additionally, raw parameters based on anthropometric
measurements can be used in a qualitative approach by assessing
somatotype components or simply comparing them with
reference values using z-scores (3).
Rugby is a high-intensity intermittent contact sport that
relies on glycogen as a principal fuel source and requires a
moderate-to-high carbohydrate intake (7–8gkg
−1
day
−1
)to
replenish stores (4,5). Additionally, the evolution of rugby
players’physiques, especially since the adoption of
professionalism in 1995, necessitates dietary and exercise
FIGURE 1
The five levels of body composition.
Holway et al. 10.3389/fspor.2024.1439358
Frontiers in Sports and Active Living 02 frontiersin.org
intervention programs to increase size and muscle mass and reduce
body fat (6). The dimensional characteristics of players can result by
selection pressures, with lower competitive gradient leagues
presenting smaller players (7). Different playing positions in rugby
can also lead to variations in the size and body composition of the
players. For instance, forwards, who are often involved in physical
confrontations and scrums, tend to have greater body mass and
higher fat percentages compared to backs, who generally require
more speed and agility and thus have leaner and more muscular
physiques (8).
The nutritional recommendations for increasing muscle mass
include consuming 1.2–1.6 g kg
−1
day
−1
of protein, along with
sufficient energy and carbohydrate intake to support growth.
These dietary guidelines should be combined with proper
resistance training programs to maximize muscle hypertrophy
(9). To optimize muscle growth, it is recommended that
moderate protein intake should come from high-quality sources
such as milk, eggs, and meat (10). Although health concerns
regarding fat, saturated fat, and cholesterol intake have been
highlighted in American football and rugby league, the primary
focus of nutrition for athletes has been on performance.
Consequently, the recommended total fat intake for athletes is
between 20% and 25% of their energy intake (5).
Sport-specific nutrition recommendations may be influenced
by socio-economic factors affecting food choices. Non-
professional athletes with limited budgets might opt for high-
energy density foods, particularly in low socio-economic status
areas of countries like Argentina, where rugby has not yet fully
embraced professionalism (11,12). Despite the worldwide
popularity of rugby, there is a lack of studies pertaining to the
dietary intake of these athletes (13,14).
Therefore, the purpose of this study is to present the dietary
intake and anthropometric profile of non-professional rugby
players in Argentina. This research aims to fill the gap in dietary
information on this sport and highlight how low budgets
influence food selection and nutrient composition.
2 Materials and methods
2.1 Subjects
A battery of anthropometric variables (body mass, height,
sitting height, bone breadths, limb and trunk girths, and
skinfolds) was collected on 57 rugby union players from a Group
III Club of the Unión de Rugby de Buenos Aires (URBA) set in
a low-income neighborhood. Measurements were performed by
level 2 and 3 anthropometrists who adhered to the International
Society for the Advancement of Kinanthropometry (ISAK)
protocol (15).
2.2 Anthropometry
Anthropometric tools included an Aspen EB6571 digital strain-
gauge scale (Jinli Electronic, Zhongshan, China), wall-mounted
portable stadiometers with headboards (Rosscraft SRL,
Argentina), a 50-cm sturdy wooden box for sitting height, bone
breadth calipers (Rosscraft SRL, Argentina), measuring tapes
(Rosscraft, Canada), and Holtain skinfold calipers (Crymych,
UK). Body composition was assessed using the Five-Way
Fractionation Method (16) which divided the body into
anatomically defined tissue masses: adipose, muscle, residual,
bone, and skin. Fat mass was estimated using the Yuhasz percent
fat equation (17). Body mass index (BMI), weight/height
2
, sum
of six skinfolds (S6skf) as the sum in millimeters of triceps,
subscapular, supra-spinale, abdominal, front thigh and medial
calf skinfolds, and muscle-to-bone ratio (MBR) as muscle mass/
skeletal mass (8) were calculated. Registered dietitians
interviewed the players to record a 24-hour dietary recall of the
previous day’s (a Friday) food and beverage intake, using
memory cues and strategies to optimize recall. Diet analysis
(energy, macro-, micro-nutrients, meal, and food-type energy
distribution) was carried out using the SARA nutrition software
(version 1.2.12, Ministerio de Salud, Argentina; http://www.msal.
gov.ar/htm/Site/ennys/site/sara.asp). Micro-nutrient adequacy was
established by comparing the reported intakes with the Daily
Reference Intakes (DRI) for adult males suggested by the Food
and Nutrition Board, Institute of Medicine, USA (http://www.
nap.edu/catalog/dri/). Additional information on weekly training
and daily activities was collected to estimate a physical activity
level (PAL) using the Factorial Method (Energy and protein
requirements. Report of a joint FAO/WHO/UNU Expert
Consultation., 1985). Total energy expenditure estimation (TEE)
was calculated by multiplying the PAL by the estimated basal
metabolic rate (BMR) using the Schofield equation (18). Validity
of reported food intakes was assessed using the suggestions of
Black (19), comparing reported energy intake (EI) against
calculated TEE. To avoid over-estimating BMR in over-fat
players, the Hamwi formula was used to adjust the body weight
used in calculating BMR (20). Before testing, the purpose of the
study was explained to the players, who signed an informed
consent form. Approval for the study was obtained from the
Ethics Board at the Departamento de Medicina at River Plate Club.
2.3 Statistical analysis
The SPSS software (v27.0.0.0, SPSS Inc., Chicago, USA) was
used for all statistical analyses. Data were presented as the
mean ± standard deviation (SD). Assumptions of normality were
verified using the Shapiro-Wilk test and student’s independent
t-test and Mann-Whitney U-test were used for comparison
analyses. For all analyses, the criterion for significance was set at
an alpha level of p< 0.05.
3 Results
The participants trained for two hours on Tuesdays and
Thursdays and played games on Saturdays. They began playing
Holway et al. 10.3389/fspor.2024.1439358
Frontiers in Sports and Active Living 03 frontiersin.org
rugby at an average age of 15.9 ± 5.2 years, with an average rugby-
playing history of 11.7 ± 7.4 years. PAL was 1.83 ± 0.23.
Table 1 presents body composition characteristics and
comparison analyses for Group III non-professional players (G3)
against reference data of Group I players (G1) (8). Figure 2
schematizes the main body mass components for the two groups.
Energy and macro-nutrient intake were reported in Table 2.
Backs players presented a higher energy intake than forward
players, resulting from higher macro-nutrients intake. Micro-
nutrient intake was reported in Table 3.
Twenty-three percent of the players surveyed skipped breakfast,
while another 37% consumed less than 10% of their daily energy
TABLE 1 Body composition features by position of group III non-professional players (G3) against professional group I reference players (G1). Data are
mean ± standard deviation.
Variable
Forwards Backs
G3
n=31
G1
n=70
Dif. p-value G3
n=26
G1
n=63
Dif. p-value
Age (years) 28.2 ± 6.8 24.5 ± 3.5 3.7 0.007* 26.4 ± 8.1 24.2 ± 3.6 2.2 0.198
Weight (kg) 100.3 ± 16.6 98.1 ± 10.7 2.1 0.516 78.9 ± 6.5 79.8 ± 8.2 −0.9 0.612
Height (cm) 175.9 ± 4.8 181.5 ± 6.8 −5.7 0.000* 172.5 ± 5.2 175.7 ± 6.7 −3.2 0.031*
% adipose tissue 27.8 ± 4.6 24.4 ± 3.4 3.4 0.000* 24.1 ± 4.7 21.9 ± 3.0 2.2 0.036*
% muscle mass 46.0 ± 3.9 48.8 ± 2.9 −2.8 0.000* 48.4 ± 4.2 50.2 ± 2.4 −1.8 0.049*
% residual 12.1 ± 1.0 11.7 ± 0.7 0.4 0.069 11.9 ± 0.9 11.8 ± 0.8 0.2 0.381
% skeletal mass 10.6 ± 0.9 10.6 ± 0.9 0.0 0.876 11.4 ± 0.9 11.2 ± 1.0 0.1 0.635
% skin 3.5 ± 0.5 4.5 ± 0.3 −1.0 0.000* 4.3 ± 0.4 5.0 ± 0.3 −0.7 0.000*
Kg adipose tissue 28.4 ± 8.5 24.1 ± 5.0 4.3 0.013* 19.0 ± 4.1 17.5 ± 3.4 1.5 0.077
Kg muscle mass 45.8 ± 6.1 47.8 ± 5.3 −2.1 0.083 38.2 ± 4.4 40.0 ± 4.4 −1.9 0.071
Kg residual 12.2 ± 2.6 11.5 ± 1.5 0.7 0.186 9.4 ± 1.1 9.4 ± 1.1 0.0 0.924
Kg skeletal mass 10.6 ± 1.5 10.3 ± 1.2 0.2 0.428 8.9 ± 0.8 9.0 ± 1.0 0.0 0.967
Kg skin 3.4 ± 0.1 4.4 ± 0.3 −1.0 0.000* 3.4 ± 0.2 3.9 ± 0.3 −0.6 0.000*
BMI Kg/m
2
32.4 ± 5.1 29.8 ± 3.3 2.6 0.012* 26.5 ± 2.1 25.8 ± 2.0 0.7 0.134
S6skf mm 131.1 ± 52.7 92.9 ± 28.8 38.3 0.001* 79.6 ± 26.5 63.5 ± 19.1 16.1 0.008*
MBR 4.3 ± 0.4 4.7 ± 0.5 −0.3 0.004* 4.3 ± 0.5 4.5 ± 0.5 −0.2 0.058
% Fat Yuhasz 16.4 ± 5.5 12.3 ± 3.0 4.0 0.001* 11.0 ± 2.9 9.3 ± 2.0 1.7 0.008*
*Statistically significant difference (p< 0.05). BMI, body mass index; S6, sum of six; MBR, muscle-to-bone ratio.
FIGURE 2
Body composition characteristics of professional and non-professional rugby players grouped by roles.
Holway et al. 10.3389/fspor.2024.1439358
Frontiers in Sports and Active Living 04 frontiersin.org
intake during this meal. This means that 60% of the players had
deficient breakfasts. Figure 3 illustrates the average distribution of
energy intake per meal.
Five players reported to have drunk alcohol on the recorded
day, with beer as the main option, followed by wine and spirits,
as shown in Figure 4.
4 Discussion
The objective of the study was to present the anthropometric
characteristics of non-professional rugby players along with their
dietary habits. Understanding the characteristics of athletes
included in low-income teams can help guide specific training or
nutritional programs aimed at improving health status and
sports performance.
4.1 Size and body composition
When compared to professional rugby players (Table 1),
both forwards and backs from the non-professional team were
shorter, had more adiposity, and possessed less muscle mass.
These differences were anticipated due to the less competitive
TABLE 2 Energy and macro-nutrient intake.
Forwards n= 31 Backs n=26
Dif. p-value
All players n=57
Median Range Median Range Median Range
Energy Kcal 2,827 1,220–6,228 3,682 2,104–7,982 −855 0.044* 3,363 1,220–7,982
Protein
g 117 56–329 136 47–292 −19 0.249 119 47–329
% 16.0% 7%−43% 14% 7%−32% 1.7% 0.491 15% 7%−43%
g·kg
−1
·day
−1
1.1 0.5–3.6 1.8 0.7–3.5 −0.7 0.002* 1.4 0.5–3.6
Carbohydrates
g 342 107–821 401 177–828 −59 0.269 373 107–828
% 50.0% 27%−79% 46% 25%−62% 3.9% 0.089 48% 25%−79%
g·kg
−1
·day
−1
3.3 1.1–8.0 5.3 2.3–10.0 −2.1 0.006* 4.1 1.1–10.0
Fats
g 104 33–334 149 70–428 −45 0.012* 143 33–428
% 32.0% 14%−54% 39% 25%−62% −6.4% 0.016* 35% 14%−62%
g·kg
−1
·day
−1
1.0 0.3–3.7 1.9 1.0–4.8 −0.9 0.000* 1.5 0.3–4.8
Fiber g 17 8–38 17 6–41 0 0.328 17 6–41
*Statistically significant difference (p< 0.05).
TABLE 3 Micro-nutrient intake of non-professional rugby players showing adequacy and prevalence of insufficient and excessive intakes.
Micro-nutrient Median Range
% RDA
a
Prev < EAR
b
Prev > UL
c
Median 95% C.I. Cases % Cases %
Minerals
Iron mg 66 10–68 313% 37% 0 0% 4 7%
Sodium mg 2,526 4,856–14,069 168% 40% 9 16% 31 54%
Potassium mg 2,862 916–7,185 124% 18% 8 14%
Calcium mg 738 199–2,435 74% 13% 33 58% 0 0%
Phosphorus mg 1,886 788–3,596 269% 26% 0 0% 0 0%
Zinc mg 19 7–42 169% 24% 10 18% 3 5%
Vitamins
Niacin mg 38 11–94 239% 31% 1 2% 34 60%
Folate μg 777 129–2,555 194% 32% 7 12% 17 30%
Vitamin A μg 626 76–2,257 70% 13% 28 49% 0 0%
Thiamin mg 3.8 1.1–11.1 314% 42% 0 0%
Riboflavin mg 3.1 0.6–19.3 241% 61% 2 4%
Vitamin B12 μg 8.0 1.5–32.4 333% 71% 2 4%
Vitamin C mg 51 0–458 56% 29% 37 65% 0 0%
a
RDA, recommended dietary allowance.
b
EAR, estimated average requirements.
c
UL, tolerable upper intake levels.
Holway et al. 10.3389/fspor.2024.1439358
Frontiers in Sports and Active Living 05 frontiersin.org
nature of their rugby environment, where such physical
attributes are crucial for performance (7). The reasons for
these disparities may include selection processes, living in
disadvantaged socio-economic settings, genetics, the amount
of training, and/or nutrition.
The use of the five-way fractionation model allowed for the
quantification of important components such as muscle, bone,
and adipose tissue. This enabled the calculation of the MBR, an
index that can be particularly useful since muscle mass is
correlated with strength and performance (21). Adipose tissue is
defined as the anatomical entity, encompassing lipids, proteins,
electrolytes, and water, and differs from chemically-defined fat
mass which only refers to lipids (22). This explained why
adiposity values were higher than percent fat values, as shown in
Table 1. Considering previous findings, the fat mass calculated in
the participants included in this study show resulted higher
compared to elite rugby players as well as athletes from other
sports teams (3,23,24).
FIGURE 3
Average distribution of energy intake per meal. Error bars are 95% C.I.
FIGURE 4
Average distribution of energy intake per type of food. Error bars are 95% C.I.
Holway et al. 10.3389/fspor.2024.1439358
Frontiers in Sports and Active Living 06 frontiersin.org
4.2 Energy and macronutrients
Back players had a higher energy intake compared to the
heavier forward players (Table 2). The median energy intake was
3,363 Kcal (range 1,220–7,982), which is lower than that of
Australian rugby league players, whose median intake is
4,230 Kcal (range 2,671–6,917 Kcal) (13), presumably because the
amateur players trained less. Since the PAL was not different
between the two groups (Forwards 1.84, Backs 1.83), there may
have been over-reporting of food intake by backs and/or under-
reporting by forwards. When the ratio of energy intake to basal
metabolic rate was derived, forwards had a ratio of 1.68 ± 0.67,
which was less than the backs’ratio of 2.11 ± 0.63. These ratios
suggest that the heavier forwards might have been
underestimating their food intake, and backs overestimating it,
assuming accurate food intake assessment would result in values
similar to their PAL values.
Macronutrient intake (protein, carbohydrate, and fat) was
higher in backs (1.8, 5.3, and 1.9 g kg
−1
day
−1
, respectively)
compared to forwards (1.1, 3.3, and 1.0 g kg
−1
day
−1
,
respectively). This discrepancy was expected since forwards were
heavier and possibly under-reported their intake. The protein
and carbohydrate intake for forwards were below the
recommended values of 1.6 and 7–8gkg
−1
day
−1
.Itmaybe
worth considering that larger athletes might require smaller per-
kilogram nutrient recommendations, or that some adjustment for
lean mass could be necessary.
4.3 Micronutrient intake
The median values for the whole group exceeded the RDAs for
all vitamins and minerals (Table 3), except for calcium (74%),
vitamin A (70%), and vitamin C (56%). For these three
micronutrients, the prevalence of players consuming less than the
Estimated Average Requirement (EAR) was also the highest.
Although the median calcium intake was 738 mg, which is not
particularly low, the recommended daily allowance (RDA) of
1,000 mg is considered by some to be excessively high and is a
topic of ongoing debate (25). The low intake of vitamins A and
C, along with the low fiber intake, indicated a low intake of
fruits and vegetables (Figure 4). The participants of this study
reported a low intake of calcium and vitamin C than professional
(13) and semi-professional rugby players (26) who reported
consuming 1,400–1700 mg of calcium and 150–200 mg of
vitamin C.
4.4 Energy intake per meal and type of food
Figure 3 showed that almost half of the daily energy intake was
at dinner, while only 13% was at breakfast, with 23% of the
participants used to skip breakfast. Training sessions for these
players were schedule at night and were followed by dinner. This
eating pattern may not optimize the balance between exercise
and nutrition, as it involves insufficient intake before training
and excessive consumption afterward. Although dietary
periodicity studies are not very common, research including team
sport athletes in Australia also found that these athletes tended
to eat larger meals at night (27). Cereal and starches contributed
most of the energy to the diets of these rugby players, followed
by meat and eggs, sweets and sugars, and fats and oils (Figure 4).
Less energy came from dairy products, and fruits and vegetables.
Alcohol contributed 1% of energy intake, less than the 4%–5%
reported by Lundy et al. (13), but this figure most likely
underestimated real intake since the survey included a Friday
before Saturday morning training. One of the impacts of a
restricted budget on dietary choices was increasing the
consumption of inexpensive starches, sugars, and oils, while
diminishing that of higher-priced, nutrient-dense meats, dairy,
fruits, and vegetables, as was found with these players, except for
the high meat intake, which, although declining, is abundant in
Argentina (28).
Some study limitations should be listed. For example, the 24-h
dietary recall method had many pitfalls, including under-reporting
by fatter individuals, and the software used for nutrient analysis
might have had its own limitations; for instance, we were
perplexed by the median value for iron intake, which at 66 mg
was about two to three times larger than that data reported in
previous studies (13,26). Future studies should aim to obtain
nutritional data from three-day weighted food records.
5 Conclusions
Rugby players from a low socio-economic area playing in a
third-division level in Argentina were shorter, fatter, and had less
muscle than their division one counterparts, and their diets were
high in starches, sugars, and fats, and low in fruits and
vegetables. To improve health, body composition, and sport-
specific performance, this information might aid dietitians in
suggesting food intake patterns and choices that improve this
nutritional scenario within the budget constraints of the players.
Data availability statement
The raw data supporting the conclusions of this article will be
made available by the authors, without undue reservation.
Ethics statement
The studies involving humans were approved by approval for
the study was obtained from the Ethics Board at the
Departamento de Medicina at River Plate Club. The studies were
conducted in accordance with the local legislation and
institutional requirements. The participants provided their
written informed consent to participate in this study.
Holway et al. 10.3389/fspor.2024.1439358
Frontiers in Sports and Active Living 07 frontiersin.org
Author contributions
FH: Conceptualization, Investigation, Methodology,
Project administration, Writing –original draft. FC: Data
curation, Formal Analysis, Methodology, Writing –original
draft, Writing –review & editing. CP: Methodology,
Supervision, Writing –review & editing. LS: Conceptualization,
Investigation, Methodology, Writing –review & editing.
NS: Methodology, Supervision, Visualization, Writing –
review & editing.
Funding
The author(s) declare that financial support was received for
the research, authorship, and/or publication of this article.
Open Access funding provided by Università degli Studi di
Padova | University of Padua, Open Science Committee.
Conflict of interest
The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
The reviewer CM declared a past co-authorship with the
author FC to the handling editor.
The author(s) declared that they were an editorial board
member of Frontiers, at the time of submission. This had no
impact on the peer review process and the final decision.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their affiliated organizations,
or those of the publisher, the editors and the reviewers. Any product
that may be evaluated in this article, or claim that may be made by its
manufacturer, is not guaranteed or endorsed by the publisher.
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