Contents
Associated Data
- Supplementary Materials
- S1 Database VAT: Patient database. ( XLSX )pone.0180614.s001.xlsx ( 71K ) GUID : 1987BC24-3264-4396-8C11-5A31CBB4431F
- Data Availability Statement
- All relevant data are within the paper and its Supporting information files .
Abstract
Dual energy x-ray absorptiometry ( DXA ) is an established proficiency used in clinical and inquiry settings to evaluate total and regional fatty. additionally, recently developed software allow to quantify intuitive adipose weave ( VAT ). presently, there are no reference book values available for GE Healthcare DXA systems for VAT. The draw a bead on of this study was to develop reference values for VAT in healthy european adults aged 20–30 years using a GE Healthcare Prodigy densitometer along with the dedicate CoreScan application. We besides assessed the associations of VAT with traditional cardiometabolic hazard factors. In 421 participants ( 207 men ; 214 women ), we performed DXA whole-body scans and calculate sum body fatty ( BF ) and VAT ( in gender-specific percentiles ). We besides measured lineage atmospheric pressure and fasting glucose, insulin, and blood lipids. Males, in comparison with females, had 2-fold greater VAT both in units of mass ( 542 ± 451 deoxyguanosine monophosphate ; 95 % CI : 479.6‒605.1 gigabyte vs. 258 ± 226 gigabyte ; 95 % CI : 226.9‒288.6 thousand ) and book ( 570 ± 468 cm3 ; 95 % CI : 505.1‒635.2 cm3 vs. 273 ± 237 cm3 ; 95 % CI : 240.6‒305.3 cm3 ). They besides had significantly higher the VAT/BF proportion. VAT showed a stronger convinced correlation coefficient than BF with lineage press, triglycerides, LDL-cholesterol, glucose, insulin, and homeostasis model assessment-insulin immunity index and a stronger negative correlation with HDL-cholesterol. Among these variables, VAT had the highest area under the curve for triglycerides ≥150 mg/dL ( 0.727 in males and 0.712 in females ). In conclusion, we provide reference book values for VAT obtained from healthy adults using the GE Healthcare DXA. These values may be useful in the diagnosis of intuitive fleshiness, for identifying subjects with high obesity-related risks, in epidemiologic studies, as a aim for therapies, and in physically train individuals. In both genders, VAT was associated with traditional cardiometabolic risk factors, peculiarly hypertriglyceridemia .
Introduction
The excessive accretion of intuitive adipose weave ( VAT ) leads to visceral fleshiness and induces low-grade systemic inflammation, which is mediated by fat-infiltrating immune cells and increased release of proinflammatory cytokines [ 1 – 4 ]. Although the claim mechanisms that initiate VAT collection have not been in full elucidated, it is broadly believed that excess VAT is closely associated with the development of a cluster of metabolic derangements, high blood pressure, cardiovascular disease, and malignancies. intuitive fleshiness can be estimated using several foster methods based on anthropometric measures, such as waist circumference, waist-to-hip ratio, waist-to-height proportion, or sagittal abdominal diameter. however, these indices do not allow distinguishing between VAT and hypodermic abdominal fatty and, in general, are basically inaccurate in quantifying VAT [ 5 ]. VAT is a relatively small component of sum body fatty ; however, due to known metabolic effects of VAT, there is constantly increasing concern in this fat terminal as an attractive aim for non-pharmacological [ 6, 7 ] and pharmacological interventions [ 8 ]. VAT can be accurately measured using magnetic resonance ( MRI ) and computed imaging ( CT ) imaging. however, these techniques are dearly-won and may be associated with elongated scan prison term or risk of radiation exposure to patients. consequently, other imaging techniques have been developed to quantify VAT. Of them, dual-energy x ray absorptiometry ( DXA ) offers a simpleton, rapid and accurate estimate of VAT mass and volume [ 9, 10 ]. This modality uses the differential gear attenuation of x-ray beams at two freestanding energies to calculate the soft weave musical composition and can be used to estimate both whole-body and regional distribution of the fat and lean tissues with a relatively low ( approximately 1.5 mrem ) radiation acid. GE Healthcare and Hologic are the two leading worldwide DXA manufacturers. recently, both manufacturers enhanced traditional body composing estimated in the whole-body scan by dedicate applications, which automatically calculate VAT by subtracting abdominal hypodermic fatness from full abdominal fatness. VAT measured by DXA showed a firm correlation coefficient with VAT measured both by CT ( R2 = 0.957 ) [ 9 ] and MRI ( R2 = 0.82 for females ; R2 = 0.86 for males ) [ 10 ]. however, there are two important limitations in comparing VAT measures using CT, MRI, and DXA. first, all the modalities quantify VAT in different units–area ( cm2 ), volume ( cm3 ), or mass ( deoxyguanosine monophosphate ), making interpretation of results difficult. second, there are no age-, gender-, and race-specific, universally recognized standards for key VAT variables in healthy adults measured by each of these methods, including DXA. As GE Healthcare DXA is widely used in clinical commit and research investigations, reference standards are needed to define intuitive fleshiness and to evaluate the cardiometabolic risks associated with excess VAT quantified by this instrument. The aim of this study was to develop mention values for VAT mass and bulk in healthy young adults using the GE Healthcare Lunar Prodigy instrument along with the give CoreScan application. additionally, we assessed the associations of DXA-VAT with traditional cardiometabolic hazard factors and a surrogate measure of insulin resistance .
Material and methods
Study participants
All participants were residents of a bombastic urban area in northwestern Poland. The study population was recruited from March 2014 to June 2016 from 1 ) participants of the home health-related plan evaluating the prevalence of metabolic fleshiness among the youthful polish population ( N = 162 ) ; this group was randomly selected based on the local electoral roll as report elsewhere [ 11 ] ; 2 ) volunteers from university students recruited by local announcements ( N = 182 ) ; and 3 ) self-referrals to the Densitometry Unit of the Pomeranian Medical University ( N = 77 ). The inclusion body criteria included the follow : age between 20 and 30 years, miss of aesculapian conditions that required pharmacological or other treatments, regular menstruation in females, no history of malignancy, abnormal glucose tolerance or rapid weight changes ( above 3.0 kilogram ) within the last 12 months, and no apparent abnormalities in the everyday physical interrogation. due to DXA-specific technical limitations, participants were excluded if their width exceeded the scanner field or their weight exceeded the limits of the scanner sleep together. overall, we included 421 participants ( 207 men ; 214 women ). The learn complied with all applicable institutional and governmental regulations regarding to the ethical function in homo volunteers and with the terms of the Declaration of Helsinki. The Pomeranian Medical University Ethics Committee approved the discipline protocol, and all the recruit participants gave their written consent .
Procedures
In all participants, we measured altitude, burden, and waist and hip circumferences. Blood pressure was measured at least two times in a sitting situation using an automatize meter, in accordance with current guidelines [ 12 ]. Using routine automated methods, we measured fasting plasma glucose, insulin, low- ( LDL ) and high-density ( HDL ) lipoproteins, and triglycerides. From insulin and glucose measurements, a homeostasis model assessment-insulin resistance ( HOMA-IR ) index was calculated. We used the HOMA-IR rate of 2.5 as a cutoff for the risk of metabolic syndrome in non-diabetic population [ 13 ]. From waist circumference and triglycerides, the lipid accretion product ( LAP ) was calculated using the follow rule : LAP = ( Waist circumference– 65 ) x triglycerides [ mM/L ] in males ; and LAP = ( Waist circumference– 58 ) ten triglycerides [ mM/L ] in females. LAP has been shown as a foster index of abnormal metabolic visibility [ 14 ]. Based on the International Diabetes Federation ( IDF ) race- and gender-specific diagnostic criteria for metabolic syndrome [ 15 ], we evaluated the presence of the play along risk factors : 1 ) shank circumference ≥94 curium in men and ≥80 centimeter in women ( for the European population ) ; 2 ) systolic blood pressure ≥130 millimeter Hg or diastolic blood pressure ≥85 millimeter Hg ; 3 ) raised triglyceride degree ≥150 mg/dL ( 1.7 mmol/L ) ; 4 ) raised fasting plasma glucose ≥100 mg/dL ( 5.6 mmol/L ) ; and 5 ) reduced HDL-cholesterol level < 50 mg/dL ( 1.29 mmol/L ) in women and < 40 mg/dl ( 1.03 mmol/L ) in men. Body composition parameters, including bone mineral content, lean mass, total body ( BF ), and android and gynoid fat, were measured by GE-Healthcare Lunar Prodigy Advance ( software encore ; adaptation 14.1 ) using the automatic whole-body scan modality. All scans were performed and analyzed by a individual trained technician per a standard protocol provided by the manufacturer. From BF measures, fat multitude index ( FMI ) as BF ( kilogram ) divided by altitude ( m2 ) was calculated ( normal ranges : 3‒6 kg/m2 in males and 5‒9 kg/m2 in females at historic period 25 [ 16 ] ). VAT expressed both in grams and cm3 was calculated mechanically by the CoreScan application. The software algorithm works through detection of the width hypodermic fatty layer within android region of interest on the lateral part of abdomen and the interior-posterior thickness of the abdomen, which can be assessed using x-ray attenuation. From VAT measures, we calculated the comply ratios : VAT/BF, VAT/weight, and VAT/Lean. Instrument timbre control was performed on a regular footing using the manufacturer ’ south block apparition scanned every working sidereal day and the Hologic Spine Phantom scanned three times per workweek. There was no meaning drift in calibration for the study menstruation .
Statistical analysis
descriptive measures were reported as means ± standard deviation ( SD ). Data were checked for normality using the Shapiro-Wilk ’ sulfur test. In the case of normal distribution, means were compared using Student ’ s t-test ; otherwise, the non-parametric Mann-Whitney U-test was used. Chi-square trial for independence with Yates ’ correction was used to determine if qualitative variables were related. The relationship between pairs of quantitative variables with convention distribution was presented using Pearson ’ s linear correlation coefficient, whereas Spearman ’ s rank correlation coefficient was calculated for pairs with non-normal distribution. VAT was calculated in the units of aggregate ( guanine ) and volume ( cm3 ) and presented as sex-specific percentiles. Quantile arrested development coefficients were computed to compare each VAT percentile between males and females. A telephone receiver operating characteristic ( ROC ) curve psychoanalysis was used to assess the accuracy for each component of metabolic syndrome defined by the IDF criteria [ 15 ], LDL-cholesterol, and HOMA-IR. The accuracy was measured using the area under the curve ( AUC ) with a 95 % assurance interval ( CI ). To determine the appropriate gender-specific cut-off point for VAT, the score with the highest combination of sensitivity and specificity ( Youden ’ mho index, sensitivity + specificity ‒ 1 ) was considered the optimum cut-off mark. statistical analyses were performed using SPSS interpretation 23.0 and R Statistics translation 3.3.2 ( available from : www.cran.r-project.org ) .
Results
Baseline characteristics of study participants are shown in .
Table 1
All (N = 421)Males (N = 207)Females (N = 214)P value males vs. femalesAge (years)26.52 ± 3.1825.04 ± 3.0627.95 ± 2.59<0.001Height (cm)173.43 ± 10.42181.80 ± 6.98165.34 ± 5.75<0.001Weight (kg)70.94 ± 13.8881.03 ± 11.1761.23 ± 8.11<0.001Body Mass Index (kg/m2)
≤18.4
18.5–24.9
25.0–29.9
≥30.023.37 ± 2.74
5 (1.2%)
328 (77.9%)
79 (18.7%)
9 (2.1%)24.46 ± 2.65
0
139 (67.1%)
64 (30.9%)
4 (1.93%)22.33 ± 2.40
5 (2.3%)
189 (88.3%)
15 (7.0%)
5 (2.3%)<0.001
0.026
<0.001
<0.001
0.082Waist circumference (cm)81.72 ± 10.0987.35 ± 9.0776.28 ± 7.79<0.001Hip circumference (cm)95.43 ± 6.7895.46 ± 7.0895.40 ± 6.500.936Waist-to-hip ratio0.86 ± 0.090.92 ± 0.070.80 ± 0.07<0.001Total body fat (g)19491.6 ± 6260.819201.77 ± 7066.919770.39 ± 5375.60.361Total body fat (%)28.23 ± 7.2524.16 ± 6.5532.15 ± 5.53<0.001Lean mass (g)48753.9 ± 1145558671.06 ± 7001.839216.50 ± 4944.8<0.001Android fat (g)1439.94 ± 768.131558.46 ± 886.491325.95 ± 614.750.002Gynoid fat (g)3826.29 ± 1500.43223.77 ± 1151.324408.53 ± 1569.54<0.001VAT (cm3)418.72 ± 397.13570.24 ± 467.75273.00 ± 237.09<0.001VAT (g)397.27 ± 381.82542.31 ± 451.09257.78 ± 226.11<0.001VAT/BF ratio (%)1.85 ± 1.362.55 ± 1.481.18 ± 0.78<0.001VAT/Weight ratio (%)0.52 ± 0.420.64 ± 0.470.40 ± 0.31<0.001VAT/Lean ratio (%)0.78 ± 0.670.92 ± 0.750.65 ± 0.55<0.001Fat Mass Index (kg/m2)6.51 ± 2.115.80 ± 2.087.21 ± 1.89<0.001Glucose (mg/dL)89.42 ± 7.7789.98 ± 8.0389.07 ± 7.600.297Insulin (IU/mL)7.27 ± 3.728.19 ± 3.676.72 ± 3.650.001HOMA-IR1.61 ± 0.861.82 ± 0.821.48 ± 0.860.001Triglycerides (mg/dL)84.00 ± 41.65102.54 ± 50.8272.51 ± 29.54<0.001Lipid Accumulation Product21.08 ± 18.2430.10 ± 23.2215.46 ± 11.11<0.001HDL-cholesterol (mg/dL)60.43 ± 15.5353.54 ± 12.7564.69 ± 15.60<0.001LDL-cholesterol (mg/dL)105.89 ± 31.16109.12 ± 30.81103.90 ± 31.280.137Systolic blood pressure (mm Hg)124.14 ± 16.95131.38 ± 16.38117.01 ± 14.29<0.001Diastolic blood pressure (mm Hg)77.38 ± 9.5878.57 ± 9.3576.21 ± 9.690.015Open in a separate window The mean senesce of the sample distribution was 26.5 ± 3.2 years ( range : 20.1‒30.0 years ) and BMI ranged from 17.1 to 40.2 kg/m2. Based on the BMI classification, 78 % of participants had normal soundbox system of weights. The frequency of scraggy was higher in females, while corpulence was more frequent among males. The mean values of FMI in males and females were within normal reference point ranges at old age 25 [ 16 ].
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In comparison with females, males had lower BF % and gynoid fat but higher thin batch, android fat, and VAT bulk and volume. VAT was a relatively humble part of the body and accounted for lone 2.6 % and 1.2 % of BF and 0.6 % and 0.4 % of weight unit in men and women, respectively. The VAT/Lean ratio was besides greater in men. In both genders, mean values of IDF-metabolic syndrome components angstrom well as fasting insulin and HOMA-IR were within normal ranges. however, despite alike fasting glucose levels in both genders, males had higher fast insulin concentration and HOMA-IR. They besides had importantly higher blood pressure, triglyceride level, and LAP calculated from triglycerides and shank circumference. The entail values and percentiles ( from the 10th to the 90th ) of VAT and the VAT/BF ratios for males and females are displayed in. Males, in comparison with females, had two times greater VAT in both units of mass ( 542 ± 451 g vs. 258 ± 226 g ) and volume ( 570 ± 468 cm3 vs. 273 ± 237 cm3 ). They besides had importantly higher VAT/BF ratios ( phosphorus < 0.001 ) .
Table 2
MeanSD95% CI10th20th30th40th50th60th70th80th90thMalesVAT (g)542.31451.09479.6; 605.1103.4187.4251.8307.8391.0484.8676.8891.41259.4VAT (cm3)570.24467.75505.1; 635.2109.4198.4266.8325.8414.0514.0717.2945.01335.6VAT/BF Ratio2.551.482.34; 2.750.711.201.632.112.342.703.173.834.55FemalesVAT (g)257.78226.11226.9; 288.620.073.0125.0162.0204.0258.0324.0405.0515.0VAT (cm3)272.99237.09240.6; 305.318.076.0133.0172.0216.0273.0343.0429.0545.0VAT/BF Ratio1.180.781.08; 1.290.120.510.740.911.071.321.551.822.14Open in a separate window As summarized in, in contrast to BF, VAT and the VAT/BF ratio did not correlate with long time. furthermore, VAT showed a stronger positivist correlation than BF with insulin, glucose, HOMA-IR, systolic and diastolic lineage coerce, LAP, and rake lipids ( specially triglycerides ) ( positively ) and a stronger negative correlation with HDL-cholesterol. Like VAT, the VAT/BF ratio showed moderate to potent correlations with most cardiometabolic hazard factors .
Table 3
VariablesVAT (g)VAT (cm3)BF (g)BF (%)VAT/BF ratioAge (years)0.0960.0970.186 c0.378 c0.028Weight (g)0.655 c0.659 c0.523 c- 0.0720.605 cWaist circumference (cm)0.758 c0.761 c0.635 c0.162 c0.666 cHip circumference (cm)0.412 c0.413 c0.630 c0.401 c0.243 cWaist-to-hip ratio0.604 c0.607 c0.315 c- 0.0890.617 cLean mass(g)0.390 c0.391 c0.091- 0.501 c0.461 cVAT/Lean ratio (%)0.960 c0.960 c0.728 c0.494 c0.873 cAndroid fat (g)0.827 c0.831 c0.908 c0.641 c0.624 cGynoid fat (g)0.238 c0.240 c0.676 c0.749 c0.011Body Mass Index (kg/m2)0.716 c0.718 c0.726 c0.294 c0.580 cFat Mass Index (kg/m2)0.536 c0.539 c0.926 c0.930 c0.265 cSystolic blood pressure (mm Hg)0.289 c0.289 c0.0780.170 b0.327 cDiastolic blood pressure (mm Hg)0.247 c0.247 c0.191 c0.0950.211 cTriglycerides (mm Hg)0.525 c0.526 c0.330 c0.0810.506 cLipid Accumulation Product0.767 c0.769 c0.613 c0.244 c0.676 cHDL-cholesterol (mg/dL)- 0.361 c- 0.364 c- 0.250 c- 0.023- 0.375 cLDL-cholesterol (mg/dL)0.295 c0.295 c0.251 c0.185 c0.239 cGlucose (mg/dL)0.126 a0.125 a0.022- 0.0020.124 aInsulin (IU/mL)0.410 c0.418 c0.378 c0.190 c0.337 cHOMA-IR0.396 c0.403 c0.360 c0.175 b0.331 cOpen in a separate window We adjacent attempted to calculate gender-specific VAT cutoffs for the analyzed cardiometabolic hazard factors. In the AUC analysis, VAT in both sexes was a weak to moderate forecaster of most IDF-metabolic syndrome components, LDL-cholesterol, and insulin resistance evaluated by HOMA-IR ( ) .
Table 4
AUC95% CIP valueCut offSensitivitySpecificityYounden’s IndexSystolic blood pressure ≥130 mm HgMales0.6280.501; 0.7220.0015960.4600.7210.181Females0.6110.496; 0.8040.0013990.5210.7820.303Diastolic blood pressure ≥85 mm HgMales0.6210.525; 0.8120.0013310.4640.7220.186Females0.6190.491; 0.7680.0011610.4860.7340.112Waist circumferenceMales ≥94 cm0.9140.856; 0.9630.0017620.8090.8900.698Females ≥80 cm0.8390.776; 0.9010.0012560.8210.7520.538LDL-cholesterol ≥100 mg/dlMales0.6280.513; 0.9010.0016720.4240.8650.289Females0.6360.544; 0.8270.0013260.4680.8200.288HDL-cholesterolMales <40 mg/dl0.6720.552; 0.8310.0047590.6940.6880.372Females <50 mg/dl0.6590.543; 0.7550.0023450.5810.7560.336Glucose ≥100 mg/dlMales0.6330.541; 0.7250.0048120.4690.7340.265Females0.6210.523; 0.6280.0044080.4980.7250.227Triglycerides ≥150 mg/dlMales0.7870.681; 0.8730.0017620.7730.7240.497Females0.7370.595; 0.8790.0362291.00.5550.555HOMA-IR ≥2.5Males0.7270.638; 0.8160.00110820.4050.7710.366Females0.7120.611; 0.8060.0014990.5120.8400.328Open in a separate window however, values of the Youden ’ south Index, which was used as a measure of timbre for the definition of the optimum cutoffs, were relatively low for these factors. As expected, VAT had the highest area under the curve for gender-specific shank circumference ( AUX = 0.914 for males and 0.839 for females ), which corresponded to the values above the 70th and 50th percentiles of VAT volume for men and women, respectively. VAT was besides importantly associated with triglyceride flat. The VAT cutoffs predicting triglycerides ≥150 mg/dL were similar to those predicting an elevated shank circumference ≥94 centimeter in males and ≥80 curium in females ( 761 cm3 and 239 cm3, respectively ). ROC bend analyses of VAT for prediction of abdominal fleshiness defined by shank circumference and hypertriglyceridemia are displayed in and, respectively .Open in a separate windowOpen in a separate window
Discussion
In this cross-sectional study using the GE Healthcare Lunar Prodigy densitometer, we developed reference point values for VAT derived from a homogeneous group of healthy european adults aged 20–30 years. These address values may be utilitarian for identifying subjects with excess intuitive fat and high obesity-related risks, in epidemiologic studies, as a target for therapies, and in physically aim individuals. however, whether the definition of visceral fleshiness based on the cutoffs calculated in this study is useful and allow requires further investigation. future research should look at visceral obesity-related morbidity and outcomes using the same modality. This is because body composition is not alone influenced by sexual activity, long time, geographic placement, and ethnicity [ 16 – 19 ] but besides the method acting of assessment. The VAT indices measured by CT, MRI, and DXA, although strongly correlated, may differ both in absolute values and type of units as they may be expressed in units of multitude, area, or volume. even if the lapp method acting is used but the measures are performed on instruments from different manufacturers, the results may vary significantly. Regarding DXA, inter-device differences in soundbox composition between two prevailing manufacturers ( GE Healthcare and Hologic ) have been demonstrated [ 20, 21 ], suggesting possible similar inter-machine differences in assessing VAT. Therefore, DXA-VAT reference values should be developed as specific for each manufacturer until they are cross-validated. To our best cognition, this survey is the first report providing reference standards for VAT measured by Lunar Prodigy and CoreScan software in healthy european population aged 20–30 years. We found that males had 2-fold greater VAT, expressed both in units of mass ( 542 ± 451 g vs. 258 ± 226 deoxyguanosine monophosphate ) and volume ( 570 ± 468 cm3 vs. 273 ± 237 cm3 ), than healthy females. similarly, the VAT-to-fat, VAT-to-weight, and VAT-to-Lean ratios were significantly higher in males. In our previous research [ 22 ], we determined VAT by the same car in the population of lean women ( BMI < 25.0 kg/m2 ) aged 20–40 years and found slightly lower VAT mass ( 236 ± 183 deoxyguanosine monophosphate ) and volume ( 250 ± 195 cm3 ) in comparison with women in the current sketch. As in both studies VAT was strongly correlated with BF %, these differences may reflect a positive kinship of VAT with full adiposity. Such a relationship was besides suggested by early reports [ 4, 23 ]. We found that VAT correlated more strongly than BF with all evaluated cardiometabolic risk factors, including blood pressure, lipids, insulin and glucose, and HOMA-IR. former reports univocally demonstrated the affiliation of excess VAT with the risk of cardiovascular and metabolic disorders, which are primarily driven by insulin resistor [ 1, 4, 13, 17, 18, 24 ]. Our findings suggest that, evening in young and obviously healthy individuals, VAT might be an early marker of high blood pressure, atherogenic lipid profiles, and insulin resistance. It has been suggested that the accumulation of triglycerides and free fatso acids in the adjacent abdominal organs ( i, in the liver and pancreas ) as a leave of increased lipolysis induced by VAT plays a crucial function in the development of insulin resistance [ 25, 26 ]. Our results seem to confirm this scenario, because in males and females without known metabolic diseases, VAT was powerfully correlated with triglyceride levels, and VAT values above the 70th percentile in males and the fiftieth percentile in females were robust predictors of hypertriglyceridemia. like conclusion may be drawn from earlier reports [ 4, 17 ]. Our study has some limitations. first, we assessed healthy polish population aged 20–30 years and consequently, the presented reference standards for VAT may not apply to other populations. Second, there was over-representation in our cohort of normal weight unit subjects ( 78 % ) and relatively a humble phone number of corpulence and corpulent. This was partially caused by technical limitations in performing the whole-body scan in subjects whose body size or weight exceed the DXA limits. ultimately, our reference values were developed using GE the Healthcare Lunar Prodigy densitometer and therefore, they may not apply to VAT obtained by other methods, including DXA from other manufacturers. however, they may be used when comparing VAT obtained by another GE Healthcare device, iDXA. Both Prodigy and iDXA use the lapp CoreScan lotion to quantify VAT. In summation, studies comparing DXA-VAT measured by Prodigy and iDXA showed a alike preciseness and good agreement between both devices [ 27 ]. This analyze had some strengths, including the rigorously selected homogeneous population studied across a stove of BMIs and FMIs. additionally, all whole-body DXA scans were analyzed by a individual technician and all of them required no manual correction for the accuracy of android and gynoid regions of interest, which minimized observer error.
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In conclusion, the results from this study provide character values for VAT obtained from a homogeneous group of goodly adults using the GE Healthcare Lunar Prodigy instrument. In both genders, VAT was associated with traditional cardiometabolic risk factors, particularly hypertriglyceridemia .
Funding Statement
This study was financially supported by funding grant from the polish Osteoporosis Foundation. The funders had no character in study design, data solicitation and analysis, decisiveness to publish, or formulation of the manuscript .
Data Availability
All relevant data are within the newspaper and its Supporting information files .