Associations between Anthropometrics,Cardiorespiratory Fitness,and Metabolic Syndrome Components in Brazilian Adolescents with Obesity

Abstract

Purpose:

To describe the presence of metabolic syndrome (MS) in Brazilian adolescents with obesity, and to compare anthropometric and cardiorespiratory fitness measurements in relation to the presence of MS.

Methods:

Sixty-seven adolescents (13–18 years, 36 girls) with obesity (body mass index z-score ≥2.0) were enrolled. The following were assessed for each participant: anthropometrics, body composition, lipid profile, glucose, serum insulin, insulin resistance, blood pressure (BP), and cardiorespiratory fitness.

Results:

The presence of MS was found in 47.76% of the sample. The following abnormal measurements were most frequently reported: waist circumference (WC) (100.0%), BP (85.07%), and triglycerides (TG) (50.75%). Boys with obesity were more likely to meet MS criteria when compared to girls (P = 0.040; odds ratio = 2.80 [1.04–7.56]).

Conclusion:

The presence of MS in Brazilian adolescents with obesity in this study was 47.76%. Among this sample, the most frequently reported MS variables above the established cutoffs were WC (100%), followed by altered BP (85%) and TG (50%). These data further support previously published studies that low levels of cardiorespiratory fitness may increase the risk of MS among adolescents with obesity.

Introduction

The global childhood obesity epidemic is associated with increased health complications among youth. Common comorbidities such as atherosclerosis, dyslipidemia, hypertension, hyperglycemia, and peripheral insulin resistance (IR) are typical among children and adolescents with obesity.¹ Some of these comorbidities may increase an individual's risk for metabolic syndrome (MS). MS diagnosis in children and adolescents is based on the combination of overweight (according to the child's body mass index [BMI]) or central adiposity, arterial hypertension, elevated triglycerides (TG), decreased high-density lipoprotein cholesterol (HDL-c), and glucose intolerance, IR, and type 2 diabetes mellitus. MS is a growing health concern among children and adolescents.^2

–6

This study therefore considers the diagnosis of MS with the presence of at least three of the following criteria: elevated waist circumference (WC) according to sex and age, TG ≥100.0 mg/dL, HDL-c ≤40.0 mg/dL, fasting plasma glucose (FG) ≥110.0 mg/dL, and blood pressure (BP) ≥90th percentile (according to sex, age. and height).⁷

MS during childhood is associated with an increased risk for cardiovascular disease (CVD), abnormal glucose metabolism, liver and gastrointestinal disorders, sleep apnea, orthopedic complications, psychosocial problems, and disorders in motor development.⁸ In addition, these long-term health risks tend to persist into adulthood.⁹ MS is also correlated with chronic renal diseases, nonalcoholic fatty liver disease (NAFLD), polycystic ovary syndrome, and cancer.^10

–14 In recent years, the increase in the number of children with obesity in developing countries is an alarming public health issue and, consequently, may lead to a high socioeconomic burden among nations' citizens in the near future.¹⁵ The prevalence of MS ranges in children and adolescents from 6% to 39% depending on the diagnostic criteria used.¹⁶

Few studies have been conducted within developing countries examining the incidence of MS in children and adolescents. A previous review study revealed the prevalence of MS in Mexico ranged from 0% to 42% (nationally), and that MS was more common in those who were overweight or obese.¹⁷ In Brazilian adolescents with obesity, MS was diagnosed in 45.5% of patients and 29.1% among those with IR.¹⁸ The diagnostic criteria differed among these studies; however, Brazilian children and adolescents meet many of the criteria commonly used in these studies. Caranti et al.⁶ demonstrated that among Brazilian and Italian adolescents with obesity, MS represents an emerging health problem and that risk factors related to MS are highly correlated with the degree of obesity. This study aimed to describe the presence of MS in Brazilian adolescents with obesity, and to compare anthropometric and cardiorespiratory fitness measurements in relation to the presence of MS.

Materials and Methods

Study design

Urban Brazilian adolescents with obesity were recruited through local television, newspapers, and radio advertisements, in Santos city, São Paulo, Brazil, between March and April 2018. The inclusion criteria were adolescents between 13 and 18 years of age, and a BMI z-score ≥2.0.⁸ A total of 248 adolescents volunteered for the study. Seventy-five did not meet the inclusion criteria and 99 declined to participate after the screening phase. Sixty-seven adolescents were included in the sample. Adolescents enrolled in the study completed a rest and effort electrocardiogram. All volunteers completed the anthropometric, biochemical, and blood measurements at baseline and after 24 weeks of intervention. The exclusion criteria included diagnosis of another metabolic disease, alcohol or illegal drug use (self-reported), pregnancy, and restrictions to physical activity (Physical Activity Readiness Questionnaire). This study was conducted in accordance with the Declaration of Helsinki, and was approved by the Ethics Committee of the Federal University of São Paulo (No. 1394/2017). Informed consent and assent were obtained from the legal guardians and the participants, respectively.

MS definition criteria

For the diagnosis of MS, the modified definition of the National Cholesterol Education Program—Adult Treatment Panel III,⁷ was incorporated using the established cutoff points for children and adolescents. Thus, the diagnosis of MS was established by the presence of at least three of the following criteria: elevated WC according to sex and age, TG ≥100.0 mg/dL, HDL-c ≤40.0 mg/dL, FG ≥110.0 mg/dL, and BP ≥90th percentile (according to sex, age, and height).

Anthropometric and biochemical measurements

To determine height, a SANNY^® (São Paulo, Brazil) fixed stadiometer with a 0.1 cm measurement scale was used. Body mass (BM) was obtained using a BALMAK^® (São Paulo, Brazil) digital anthropometric scale (model BK 300 GC, series 2120 with capacity for 300 kg) with an accuracy within 100 g. BMI was determined and z-score values for BMI according to sex and age were calculated (AnthroPlus program of the World Health Organization).¹⁹ Triceps (TriS) and subscapular (SubS) skinfold thicknesses were measured in triplicate on the right side of the body to the nearest 0.1 mm using a CESCORF^® scientific caliper, using techniques that were standardized and recommended by Lohman et al.²⁰ The median of the triplicate values was used in the analysis. Body fat percentage (%BF) was calculated using equations developed by Slaughter et al.²¹ Sums of the TriS and SubS skinfolds were also used [∑TriS+SubS (mm)]. WC was assessed using the minimum measurement between the last rib and the upper border of the iliac crest, using a flexible and inelastic measuring tape, and after a normal exhalation. Hip circumference was measured at the maximum width of the buttocks above the gluteal fold, and the Waist-to-Hip (W/H) ratio was calculated, as described by Taylor et al.²² Both waist and hip circumferences were assessed in duplicate. Waist-to-height (W/Ht) ratio also was calculated [W (cm)/height (cm)], as described by McCarthy and Ashwell.²³

Blood samples (12-hr fasting)

Glucose, fasting insulin, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), very low-density lipoprotein cholesterol (VLDL-c), HDL-c, and TG were quantified by enzymatic methodology using automated equipment (BTS 370 BioSystems^®, Connecticut). LDL-c was estimated by the Friedewald equation.²⁴ TG/HDL-c ratio was calculated from plasma TG (mg/dL) and HDL-c (mg/dL). Serum insulin was assessed by calorimetric method, and insulin by chemiluminescence using the Immulite 2000 systems^® reagent system (Siemens Healthcare Diagnostics, Newark, NJ). IR was estimated using means of the homeostatic model assessment of insulin resistance (HOMA-IR), as follows: [HOMA-IR = fasting serum insulin (μU/mL) × fasting serum glucose (mg/dL)/405] as indicated in Mathews et al.²⁵ The cutoff point adopted was >3.16.²⁵

BP measurement

Baseline BP was assessed using the right arm by the auscultatory method and a mercury sphygmomanometer (Unitec^®, São Paulo, Brazil) after participants rested for 10 min in a supine position. Phases I and V of the Korotkoff sounds were used to identify systolic blood pressure (SBP) and diastolic blood pressure (DBP), respectively. Three consecutive measurements were performed with 1-min intervals between each one. The average of the last two measurements was recorded. Heart rate (HR) was measured concurrently using an HR sensor (POLAR, RS 800CX, USA). Rate pressure product (RPP) was calculated using the Atherosclerosis Prevention Guidelines for Children and Adolescents.²⁶ RPP = SBP × HR.

Cardiorespiratory assessment

Direct gas analysis was used to assess respiratory variables breath-by-breath, and displayed every 20 sec (VO2000—Medgraphics^®, St. Paul, Minneapolis, MN), during a maximal graded exercise test on a treadmill (Super ATL; Inbrasport^®, Porto Alegre, Brazil). The initial workload was set at 3.0 km/hr for 3 min (warm-up), with incremental increases by 1 km/hr every minute thereafter, and a constant incline of 1%, as previously published.^27
–29 Adolescents were verbally encouraged to achieve their maximum effort during the test. The ending criteria were as follows: volitional fatigue, respiratory quotient above 1.15, or subjective sensation of exertion above 18 on the Borg scale.³⁰ The highest oxygen uptake obtained before the interruption of the test was considered the peak oxygen uptake (V̇O_2peak).

Statistical analysis

Descriptive analyses were initially performed. Means, standard deviations, medians, and interquartile ranges were analyzed using the continuous variables, whereas categorical variables were assessed using absolute and relative frequencies. Student's t tests were applied to compare clinical, biochemical, and metabolic characteristics in relation to sex and the presence of MS. When test assumptions were not satisfied, the Mann–Whitney test was applied. To test the association between sex and the presence of MS, chi-square tests and odds ratios (ORs) with corresponding confidence intervals were used to explain the degree of association between the variables. For all analyses, a significance level of 5% was established. The data were analyzed using the R Core Team 2020 (Vienna, Austria) software.

Results

Of the 74 adolescents enrolled in the study, seven were lost to follow-up before their measurements were assessed. The final sample consisted of 67 adolescents (age = 15 ± 1 years), 53.73% (n = 36 girls), and 42.26% (n = 28 boys), with a mean BMI = 35.1 ± 4.6 kg/m². The sample's physical characteristics according to sex are shown in Table 1. Anthropometrics, including height, BM, BMI, z-score BMI, TriS, SubS, ∑ TriS+SubS, WC, Hip, as well as W/H ratio, %BF, FM, and LM (P ≤ 0.05), are also presented (Table 1).

Table 1.

Physical Characteristics of Adolescents with Obesity, According to Sex

	Total sex (n = 67)				P
	Female (n = 36)		Male (n = 31)
	Mean (SD)	Median (Q1–Q3)	Mean (SD)	Median (Q1–Q3)
Age (years)	15.7 (1.6)	15.9 (14.3–17.0)	15.1 (1.5)	14.7 (14.0–15.9)	0.093^*
Height (cm)	162.0 (5.6)	162.5 (158.5–166.6)	171.1 (8.3)	171.3 (165.1–176.1)	<0.001
BM (kg)	93.9 (11.9)	97.9 (86.6–102.5)	100.9 (19.8)	98.8 (87.8–112.0)	0.091
BMI (kg/m²)	35.8 (4.4)	35.5 (33.1–37.5)	34.3 (48)	33.9 (30.1–36.7)	0.175
z-Score BMI	3.0 (0.6)	3.0 (2.8–3.3)	3.1 (0.6)	3.1 (2.7–3.3)	0.925^*
TriS (mm)	30.9 (6.2)	30.3 (27.1–35.5)	27.1 (6.5)	26.0 (23.8–29.8)	0.018
SubS (mm)	30.8 (6.3)	30.6 (25.6–35.0)	28.6 (7.2)	27.5 (23.6–32.9)	0.194
∑ TriS+SubS (mm)	61.6 (11.1)	62.2 (52.5–70.9)	55.7 (13.2)	54.2 (48.3–62.4)	0.052
WC (cm)	105.7 (9.3)	105.0 (100.5–113.1)	110.1 (13.2)	107.0 (101.0–120.0)	0.129
Hip (cm)	119.2 (8.9)	120.6 (115.1–124.5)	116.5 (9.7)	116.5 (110.0–123.1)	0.247
W/H	0.9 (0.1)	0.9 (0.8–0.9)	0.9 (0.1)	0.9 (0.9–1.0)	0.016
%BF	49.9 (8.7)	50.3 (42.7–57.1)	45.2 (10.3)	44.1 (39.4–50.5)	0.052
FM (kg)	47.4 (12.5)	47.2 (36.5–57.4)	46.5 (16.9)	44.1 (33.9–58.9)	0.812
LM (kg)	46.6 (7.2)	45.3 (41.5–50.7)	54.4 (10.9)	52.2 (47.5–62.8)	0.002^*

Mann–Whitney test.

%BF, body fat percentage; ∑ TriS+SubS, triceps skinfold and subscapular skinfold sum; BM, body mass; BMI, body mass index; FM, fat mass; LM, lean mass; SD, standard deviation; SubS, subscapular skinfold; TriS, triceps skinfold; W/H, waist/hip ratio; WC, waist circumference.

SBP, DBP, FG, TC, HDL-c, LDL-c, VLDL-c, TG, and TG/HDL-c, and metabolic parameters VO_2peak Abs and VO_2peak Rel are presented in Table 2. A significant difference was observed between sex for the anthropometric parameters (height, TriS, W/H ratio, W/Ht ratio, and LM), SBP, and VO_2peak Abs (P ≤ 0.05).

Table 2.

Clinical and Metabolic Characteristics of Adolescents with Obesity, According to Sex

Variables	Total sex (n = 67)				P
	Female (n = 36)		Male (n = 31)
	Mean (SD)	Median (Q1–Q3)	Mean (SD)	Median (Q1–Q3)
SBP (mmHg)	126.7 (11.0)	123.5 (120.7–130.2)	133.4 (13.9)	130.3 (123.6–140.5)	0.038^*
DBP (mmHg)	79.7 (7.9)	80.0 (77.2–80.8)	81.8 (7.1)	80.0 (79.3–2.2)	0.105^*
FG (mg/dL)	83.9 (8.0)	85.0 (77.7–89.0)	82.7 (10.7)	83.0 (78.5–8.5)	0.826^*
TC (mg/dL)	157.5 (31.4)	154.5 (140.7–177.0)	150.6 (28.2)	144.0 (133.0–172.5)	0.347
HDL-c (mg/dL)	55.1 (12.4)	52.0 (47.0–61.2)	50.6 (10.5)	50.0 (44.0–54.0)	0.100^*
LDL-c (mg/dL)	81.6 (29.7)	83.0 (62.0–100.5)	73.9 (25.7)	71.0 (62.0–93.5)	0.260
VLDL-c (mg/dL)	20.8 (11.5)	17.5 (14.0–23.2)	26.1 (15.7)	25.0 (14.5–29.0)	0.096^*
TG (mg/dL)	104.2 (56.9)	88.5 (72.0–116.0)	130.5 (78.5)	126.0 (73.0–144.0)	0.105^*
TG/HDL-c ratio	2.08 (1.40)	1.58 (1.14–2.56)	2.76 (2.07)	2.50 (1.43–3.46)	0.072^*
VO_2peak Abs (L/min)	2.02 (0.45)	1.99 (1.69–2.25)	2.76 (0.79)	2.60 (2.21–3.33)	0.002^*
VO_2peak Rel [mL/(kg·min)]	21.96 (5.14)	21.45 (17.10–26.33)	25.84 (9.04)	27.10 (21.60–29.58)	0.113

Mann–Whitney U test.

DBP, diastolic blood pressure; FG, fasting plasma glucose; HDL-c, high-density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; SBP, systolic blood pressure; TC, total cholesterol; TG, triglycerides; VLDL-c, very low-density lipoprotein cholesterol; VO_2peak Abs, absolute peak oxygen uptake; VO_2peak Rel, relative peak oxygen uptake.

Using the adopted criteria, the presence of MS was found in 47.76% of the sample. The remaining variables and their respective percentages can be seen in Table 3. Most often, the following variables (% incidence among the sample) were reported as being above the established cutoffs: WC (100.0%), BP (85.07%), and TG (50.75%).

Table 3.

Distribution of Metabolic Syndrome Components, Presence and Number of Components

	n	%
MS
Absence	35	52.24
Presence	32	47.76
Components
FG^a	0	0.00
HDL-c^b	7	10.45
TG^c	34	50.75
WC^d	67	100.00
BP^e	57	85.07
Number of components
0	0	0.00
1	6	8.96
2	29	43.28
3	27	40.30
4	5	7.46
5	0	0.00

≥110 mg/dL.

≤40 mg/dL.

≥100 mg/dL.

≥P80 for age and gender.

≥P90 for age, gender, and height.

BP, blood pressure; MS, metabolic syndrome; WC, waist circumference.

There were differences in TC and VLDL-c between those with MS and those without (Table 4). Thus, those with MS had higher mean TC and VLDL-c levels when compared to those without MS.

Table 4.

Descriptive Characteristics of the Sample, According to Metabolic Syndrome

Variables	Total (n = 67)				P
	Absence (n = 35)		Presence (n = 32)
	Mean (SD)	Median (Q1–Q3)	Mean (SD)	Median (Q1–Q3)
Age (years)	15.8 (1.6)	15.7 (14.2–16.7)	15.1 (1.5)	15.0 (14.3–16.5)	0.739^*
Height (cm)	164.67 (8.16)	165.00 (158.75–169.35)	167.89 (8.26)	166.75 (162.58–71.53)	0.114
BM (kg)	95.85 (15.66)	97.80 (86.50–104.20)	98.69 (17.05)	98.10 (89.95–102.9)	0.481
BMI (kg/m²)	35.34 (5.21)	35.19 (31.27–38.67)	34.84 (3.94)	34.97 (31.36–36.97)	0.658
z-Score BMI	3.08 (0.65)	3.01 (2.73–3.37)	3.06 (0.52)	3.00 (2.77–3.16)	0.758^*
TriS (mm)	29.60 (6.91)	29.10 (26.40–34.25)	28.59 (6.2)	28.25 (25.13–31.88)	0.528
SubS (mm)	30.47 (7.18)	29.70 (25.65–35.05)	29.02 (6.36)	28.35 (24.13–34.05)	0.385
∑ TriS+SubS (mm)	60.08 (12.84)	59.33 (51.19–71.63)	57.59 (11.92)	56.28 (49.98–66.17)	0.414
Hip (cm)	118.91 (10.07)	121.00 (111.75–124.6)	116.86 (8.47)	117.00 (112.65–122.00)	0.370
W/H	0.90 (0.07)	0.91 (0.85–0.95)	0.93 (0.08)	0.96 (0.86–0.98)	0.114
W/Ht	0.65 (0.07)	0.64 (0.61–0.71)	0.65 (0.05)	0.64 (0.61–0.67)	0.903
%BF	48.64 (10.06)	48.06 (41.68–57.69)	46.70 (9.33)	45.67 (40.73–53.41)	0.414
FM (kg)	47.33 (14.8)	45.87 (35.86–60.77)	46.63 (14.68)	44.46 (34.09–55.63)	0.846
LM (kg)	48.52 (9.24)	47.23 (41.42–51.57)	52.07 (10.37)	49.64 (44.11–58.24)	0.173^*
TC (mg/dL)	145.66 (20.37)	142.00 (132.00–157.50)	163.72 (35.73)	169.00 (144.25–185.00)	0.015
LDL-c (mg/dL)	73.11 (23.03)	74.00 (61.00–90.00)	83.34 (32.04)	85.50 (68.75–106)	0.142
VLDL-c (mg/dL)	14.89 (3.88)	15.00 (12.00–7.00)	32.44 (14.81)	27.00 (24.75–37.25)	<0.001^*
VO_2peak Abs (L/min)	2.19 (0.74)	1.92 (1.67–2.48)	2.43 (0.67)	2.24 (2.04–2.73)	0.186^*
VO_2peak Rel [mL/kg·min)]	23.61 (7.77)	23.00 (17.10–28.10)	23.48 (6.75)	24.10 (20.25–27.60)	0.951

Mann–Whitney U test.

W/Ht, waist/height ratio.

There was a significant association between sex and the presence of MS (P = 0.040; OR = 2.80 [1.04–7.56]). Specifically, boys with obesity were more likely to have MS. Figure 1 presents the frequency of MS by sex.

FIG. 1.

Joint distribution of the variables sex and the presence of MS. MS, metabolic syndrome.

Discussion

This study was conducted to evaluate factors associated with MS in Brazilian adolescents with obesity and to determine the level of association between anthropometrics and cardiorespiratory fitness in these individuals. The main findings were as follows: (1) 47.76% of the sample met the adopted criteria for MS; (2) WC (100.0%), BP (85.07%), and TG (50.75%) were most often reported as being above the recommended cutoffs; (3) males with obesity were more likely to have MS (P = 0.040; OR = 2.80 [1.04–7.56]); (4) there were significant differences between sex for height, TriS, W/H ratio, LM, SBP, and VO_2peak Abs; and (5) there was a significant difference between TC and VLDL-c among those with and without MS.

The concept of MS in the pediatric population is difficult to define due to the physiological changes that occur during their growth and development. Data from clinical trials are scarce, and to the best of our knowledge, a universally accepted set of criteria for MS for children and adolescents does not exist. Instead, adaptations of the standardized MS criteria for adults have been applied among clinical trials for youth, which may be contributing to inconsistencies in MS diagnoses.^31,32 The prevalence of MS in adolescents in the United States is >10% (2000–2010).³³ However, depending on which diagnostic criteria are used, the prevalence can vary between 0.9% and 11.4%.^34
–36 We found 47.76% of the sample met the adopted criteria for MS. This coincides with previously published data conducted among Brazilian adolescents with obesity, where MS prevalence ranged from 0% to 42%.¹⁷ Despite this large range, our findings are concerning.

Following the criteria adopted in this study,⁷ the following variables (% incidence among the sample) were reported most often as being above the recommended cutoffs: WC (100.0%), BP (85.07%), and TG (50.75%). Findings from the Masquio et al.³⁷ study demonstrated a significantly higher prevalence of altered WC, BP, HDL-c, TG, and BP in adolescents with MS when compared to non-MS adolescents with obesity. WC is considered a valid anthropometric measure of obesity correlated with visceral adiposity.³⁸ Although visceral adiposity was not measured in this study, visceral fat is often the focus of CVD and NAFLD prevention in adolescents with obesity.^38,39 In addition, high BP and TG values predispose this population to comorbidities such as CVD.^40,41

We observed that male individuals with obesity are more likely to have MS (P = 0.040; OR = 2.80 [1.04–7.56]). According to Brazilian census data, obesity rates among Brazilian adolescents have increased 14-fold for males and almost sixfold for females over the last 20 years, which is comparable to this study, in that, we observed higher rates of obesity among urban Brazilian youth (5.4%) when compared to their rural counterparts (3.0%).⁴² Also, it is estimated that between 20% and 80% of adolescents with obesity will remain obese into adulthood.^42,43

We also determined a significant difference existed between males and females for height, TriS, W/H ratio, LM, SBP, and VO_2peak Abs. Cardiorespiratory fitness is partly determined by genetic traits and partly by the amount of physical activity performed, which may improve VO_2max and thereby increase the cardiorespiratory fitness level. A recent study⁴⁴ hypothesized that (1) high levels of cardiorespiratory fitness prevents accumulation of abdominal obesity and consequently inhibits the network of inflammatory pathways and (2) this anti-inflammatory effect of cardiorespiratory fitness would inhibit the development of MS. Data suggest that cardiorespiratory fitness has anti-inflammatory effects that are partly explained by a reduction in abdominal obesity and a decrease in the MS risk profile.⁴⁴

A significant difference between TC and VLDL-c in those with and without MS was found. These data support previously published studies conducted in adolescents with obesity.^44,45 Although some argue that there is no convincing evidence linking high fitness levels in childhood and adolescence to desirable BP, lipid profiles, or glucose homeostasis in adulthood, higher physical fitness levels during childhood and adolescence appear to be associated with lower risks of future overweight, fatness, and MS.⁴⁵

Conclusions

The presence of MS in Brazilian adolescents with obesity participating in this study was 47.76% (61.30% for boys and 36.10% for girls). Among this sample, the most frequently reported MS variables above the established cutoffs were WC (100%), followed by altered BP (85%) and TG (50%). These data reinforce the idea that low levels of cardiorespiratory fitness may increase the risk of MS among adolescents.

Footnotes

Authors' Contributions

E.C., M.C.L.P., A.C.L., and W.L.P. contributed conception and design of the study. E.C., M.C.L.P., and A.C.L. organized the database. E.C., F.G.S., and W.L.P. performed the statistical analysis. E.C. and F.G.S. wrote the first draft of the article. E.C., F.G.S., J.P.B., N.M., M.C.L.P., A.C.L., and W.L.P. wrote sections of the article. All authors contributed to article revision, and read and approved the submitted version.

Acknowledgment

We acknowledge the volunteers and their parents for participation in this study.

Author Disclosure Statement

No conflicting financial interests exist.

Funding Information

No funding was received for this article.

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