Anthropometric measures are satisfactory substitutes for the DXA-derived visceral adipose tissue in the association with cardiometabolic risk-The Tromsø Study 2015-2016.
cardiometabolic health
dual energy x‐ray absorptiometry
obesity
overweight
population studies
visceral adipose tissue
Journal
Obesity science & practice
ISSN: 2055-2238
Titre abrégé: Obes Sci Pract
Pays: United States
ID NLM: 101675151
Informations de publication
Date de publication:
Oct 2021
Oct 2021
Historique:
received:
30
11
2020
revised:
16
04
2021
accepted:
19
04
2021
entrez:
11
10
2021
pubmed:
12
10
2021
medline:
12
10
2021
Statut:
epublish
Résumé
Body mass index (BMI) increases while cardiometabolic risk factors decrease in individuals in high-income countries. This paradoxical observation raises the question of whether current measures of overweight and obesity properly identify cardiometabolic risk. A total of 3675 participants (59% women) aged 40-84 years with whole-body dual-energy x-ray absorptiometry scans from the seventh survey of the Tromsø Study were included to examine the association between visceral adipose tissue (VAT) in grams and BMI, waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Further, their association with single cardiometabolic risk factors (blood pressure, triglycerides, total cholesterol, high-density lipoprotein [HDL] cholesterol, glycated hemoglobin, high-sensitivity C-reactive protein), modified single components from the ATP Ⅲ criteria for metabolic syndrome (hypertension, diabetes, high triglycerides, and low HDL cholesterol), and metabolic syndrome were examined. VAT mass was strongly correlated with BMI ( Although VAT mass showed statistically stronger associations with cardiometabolic risk compared to traditional anthropometrics, the clinical importance was likely small. Simple, clinically available tools seem to satisfactory substitute for VAT to identify cardiometabolic risk.
Sections du résumé
BACKGROUND
BACKGROUND
Body mass index (BMI) increases while cardiometabolic risk factors decrease in individuals in high-income countries. This paradoxical observation raises the question of whether current measures of overweight and obesity properly identify cardiometabolic risk.
METHODS
METHODS
A total of 3675 participants (59% women) aged 40-84 years with whole-body dual-energy x-ray absorptiometry scans from the seventh survey of the Tromsø Study were included to examine the association between visceral adipose tissue (VAT) in grams and BMI, waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Further, their association with single cardiometabolic risk factors (blood pressure, triglycerides, total cholesterol, high-density lipoprotein [HDL] cholesterol, glycated hemoglobin, high-sensitivity C-reactive protein), modified single components from the ATP Ⅲ criteria for metabolic syndrome (hypertension, diabetes, high triglycerides, and low HDL cholesterol), and metabolic syndrome were examined.
RESULTS
RESULTS
VAT mass was strongly correlated with BMI (
CONCLUSION
CONCLUSIONS
Although VAT mass showed statistically stronger associations with cardiometabolic risk compared to traditional anthropometrics, the clinical importance was likely small. Simple, clinically available tools seem to satisfactory substitute for VAT to identify cardiometabolic risk.
Identifiants
pubmed: 34631131
doi: 10.1002/osp4.517
pii: OSP4517
pmc: PMC8488451
doi:
Types de publication
Journal Article
Langues
eng
Pagination
525-534Informations de copyright
© 2021 The Authors. Obesity Science & Practice published by World Obesity and The Obesity Society and John Wiley & Sons Ltd.
Déclaration de conflit d'intérêts
The authors have no competing interests.
Références
Kardiol Pol. 2017;75(11):1185-1191
pubmed: 28715064
PLoS One. 2014 Mar 13;9(3):e91586
pubmed: 24626110
PLoS One. 2017 May 11;12(5):e0177175
pubmed: 28493988
Int J Obes (Lond). 2020 Feb;44(2):289-296
pubmed: 31201361
Obes Rev. 2001 Aug;2(3):141-7
pubmed: 12120099
Diabetes Res Clin Pract. 2018 Sep;143:310-319
pubmed: 30086371
Int J Obes (Lond). 2018 Apr;42(4):850-857
pubmed: 29151596
PLoS One. 2014 Dec 05;9(12):e114112
pubmed: 25479351
Obesity (Silver Spring). 2013 Sep;21(9):1798-802
pubmed: 23696250
Obes Rev. 2012 Mar;13(3):275-86
pubmed: 22106927
PLoS One. 2017 Jul 6;12(7):e0180614
pubmed: 28683146
Med J Armed Forces India. 2020 Jan;76(1):41-46
pubmed: 32020967
Aging Clin Exp Res. 2017 Feb;29(1):11-17
pubmed: 28155183
Am J Clin Nutr. 2013 Mar;97(3):480-6
pubmed: 23364010
J Am Coll Cardiol. 2017 Jul 4;70(1):1-25
pubmed: 28527533
Nutr Today. 2015 May;50(3):117-128
pubmed: 27340299
Obesity (Silver Spring). 2018 Mar;26(3):505-512
pubmed: 29286209
Front Endocrinol (Lausanne). 2020 Jan 14;10:861
pubmed: 31993018
Circ Res. 2017 Sep 1;121(6):677-694
pubmed: 28860318
Obesity (Silver Spring). 2011 Feb;19(2):402-8
pubmed: 20948514
Circ Res. 2017 Jan 20;120(2):366-380
pubmed: 28104770
BMJ Open. 2016 Mar 14;6(3):e010159
pubmed: 26975935
Dis Model Mech. 2009 May-Jun;2(5-6):231-7
pubmed: 19407331
Int J Epidemiol. 2012 Aug;41(4):961-7
pubmed: 21422063
Int J Obes (Lond). 2016 Aug;40(8):1325-8
pubmed: 27003112
Lancet. 2011 Feb 12;377(9765):578-86
pubmed: 21295847
Br J Radiol. 2012 Jan;85(1009):1-10
pubmed: 21937614
Lancet. 2017 Jan 7;389(10064):37-55
pubmed: 27863813
Obesity (Silver Spring). 2012 Jun;20(6):1313-8
pubmed: 22282048