Restricted accessResearch articleFirst published online 2019-12-03
Optimal cutoff values of fat mass index,body fat percentage and visceral fat area for identifying metabolic syndrome in the Kurdish population: Results from an Iranian RaNCD cohort study
Obesity and high body fat are related to metabolic syndrome (MetS) risk factors in all ethnic groups.
OBJECTIVE:
The present study aimed to determine optimal cutoff points for the Fat Mass Index (FMI), Body Fat Percentage (BF%), and Visceral Fat Area (VFA) in the prediction of MetS.
METHODS:
This cross-sectional study was performed on 10063 individuals aged from 35–65 years, recruited in Ravansar Non-Communicable Diseases (RaNCD) cohort. The anthropometric indices were measured using an appropriate validated methods and body composition was measured using Bio-Impedance Analyzer (Inbody 770, Inbody Co, Seoul, Korea). The receiver operating characteristic curve analysis was used to compare the predictive validity and determine optimal cutoff values.
RESULTS:
The optimal cutoff points for FMI, BF% and VFA were 7.2 kg/m2, 26.7 and 91.6 cm2 respectively in men for the prediction of MetS, but they were 11.3 kg/m2, 39.8 and 139.1cm2 respectively in women. Cutoff points were lower in rural populations than urban populations. In men and women with FMIs of higher than the optimal cutoff point, the risk of MetS was respectively 4.01 and 1.85 times higher than those with FMIs of lower than the cutoff point. In men and women with BF% of higher than the optimal cutoff point, the risk was respectively 3.62 and 1.70 times higher than those with BF% of lower than the cutoff point.
CONCLUSION:
The present study revealed that the FMI, BF%, and VFA indices were appropriate predictors of risk of MetS. The diagnostic power of the indicators was better in men and villagers.
Organization. WH. Obesity: Preventing and managing the global epidemic. Report of a WHO consultation on obesity, Geneva, 3-5. Geneva: World Health Organization; 1998. June 1997.
2.
EyreH, KahnR, RobertsonRM, ClarkNG, DoyleC, HongY, et al.Preventing cancer, cardiovascular disease, and diabetes: A common agenda for the American Cancer Society, the American Diabetes Association, and the American Heart Association. Circulation. 2004;109(25):3244–55. doi: 10.1161/01.CIR.0000133321.00456.00
3.
MatteiJ, Sotres-AlvarezD, DaviglusML, GalloLC, GellmanM, HuFB, et al.Diet Quality and Its Association with Cardiometabolic Risk Factors Vary by Hispanic and Latino Ethnic Background in the Hispanic Community Health Study/Study of Latinos–3. The Journal of nutrition. 2016;146(10):2035–44. doi: 10.3945/jn.116.231209
4.
SnijderMB, NicolaouM, ValkengoedIG, BrewsterLM, StronksK. Newly proposed body adiposity index (bai) by Bergman et al. is not strongly related to cardiovascular health risk. Obesity. 2012;20(6):1138–9. doi: 10.1038/oby.2011.338
5.
ChoeSS, HuhJY, HwangIJ, KimJI, KimJB. Adipose tissue remodeling: Its role in energy metabolism and metabolic disorders. Frontiers in Endocrinology. 2016;7:30. doi: 10.3389/fendo.2016.00030
6.
MancusoP. The role of adipokines in chronic inflammation. ImmunoTargets and Therapy. 2016;5:47–56. doi: 10.2147/ITT.S73223
7.
RaderDJ. Effect of insulin resistance, dyslipidemia, and intra-abdominal adiposity on the development of cardiovascular disease and diabetes mellitus. The American Journal of Medicine. 2007;120(3):S12–S8. doi: 10.1016/j.amjmed.2007.01.003
8.
Lancet NRFCJT. Trends in adult body-mass index in 200 countries from 1975 to 2014: A pooled analysis of 1698 population-based measurement studies with 192 million participants. 2016;387(10026):1377–96. doi: 10.1016/S0140-6736(16)30054-X
9.
AmatoMC, GiordanoC, GaliaM, CriscimannaA, VitabileS, MidiriM, et al.Visceral Adiposity Index: A reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care. 2010;33(4):920–2. doi: 10.2337/dc09-1825
10.
FrankenfieldDC, RoweWA, CooneyRN, SmithJS, BeckerD. Limits of body mass index to detect obesity and predict body composition. Nutrition. 2001;17(1):26–30.
11.
Ramírez-VélezR, Correa-BautistaJE, González-RuízK, VivasA, García-HermosoA, Triana-ReinaHR. Predictive validity of the body adiposity index in overweight and obese adults using dual-energy X-ray absorptiometry. Nutrients. 2016;8(12):737. doi: 10.3390/nu8120737
12.
MeeuwsenS, HorganG, EliaM. The relationship between BMI and percent body fat, measured by bioelectrical impedance, in a large adult sample is curvilinear and influenced by age and sex. Clinical nutrition. 2010;29(5):560–6. doi: 10.1016/j.clnu.2009.12.011
13.
Ramírez-VélezR, Correa-BautistaJE, Sanders-TordecillaA, Ojeda-PardoML, Cobo-MejíaEA, Castellanos-VegaRdP, et al.Percentage of Body Fat and Fat Mass Index as a Screening Tool for MetS Prediction in Colombian University Students. Nutrients. 2017;9(9):1009. doi: 10.3390/nu9091009
14.
VanItallieT, YangM-U, HeymsfieldSB, FunkRC, BoileauRA. Height-normalized indices of the body’s fat-free mass and fat mass: Potentially useful indicators of nutritional status. The American Journal of Clinical Nutrition. 1990;52(6):953–9. doi: 10.1093/ajcn/52.6.953
15.
LiuP, MaF, LouH, LiuY. The utility of fat mass index vs. body mass index and percentage of body fat in the screening of MetS. BMC Public Health. 2013;13(1):629. doi: 10.1186/1471-2458-13-629
16.
LovejoyJ, ChampagneC, De JongeL, XieH, SmithS. Increased visceral fat and decreased energy expenditure during the menopausal transition. International Journal of Obesity. 2008;32(6):949. doi: 10.1038/ijo.2008.25
17.
HadaeghF, ZabetianA, SarbakhshP, KhaliliD, JamesW, AziziF. Appropriate cutoff values of anthropometric variables to predict cardiovascular outcomes: 7.6 years follow-up in an Iranian population. International Journal of Obesity. 2009;33(12):1437. doi: 10.1038/ijo.2009.180
18.
PourshahidiL, WallaceJ, MulhernMS, HoriganG, StrainJ, McSorleyE, et al.Indices of adiposity as predictors of cardiometabolic risk and inflammation in young adults. Journal of Human Nutrition and Dietetics. 2016;29(1):26–37. doi: 10.1111/jhn.12295
19.
LiY, WangH, WangK, WangW, DongF, QianY, GongH, XuG, LiG, PanL, ZhuG. Optimal body fat percentage cut-off values for identifying cardiovascular risk factors in Mongolian and Han adults: A population-based cross-sectional study in Inner Mongolia, China. BMJ Open. 2017;7(4):e014675. doi: 10.1136/bmjopen-2016-014675
PasdarY, NajafiF, MoradinazarM, ShakibaE, KarimH, HamzehB, et al.Cohort profile: Ravansar Non-Communicable Disease cohort study: The first cohort study in a Kurdish population. International Journal of Epidemiology. 2019. doi: 10.1093/ije/dyy296
22.
PoustchiH, EghtesadS, KamangarF, EtemadiA, KeshtkarA-A, HekmatdoostA, et al.Prospective Epidemiological Research Studies in Iran (the PERSIAN Cohort Study): Rationale, Objectives, and Design2017;187(4):647–55. doi: 10.1093/aje/kwx314
23.
GrundySM, CleemanJI, DanielsSR, DonatoKA, EckelRH, FranklinBA, et al.Diagnosis and management of the MetS: An American Heart Association/National Heart, Lung, and Blood Institute scientific statement. Circulation. 2005;112(17):2735–52. doi: 10.1161/CIRCULATIONAHA.105.169404
24.
GlaserA. High-yield biostatics, epidemiology and public health. 4th ed. Philadelphia, USA: Lippincott, Williams & Wilkins; 2013.
25.
YoudenW. Index for rating diagnostic tests. Cancer. 1950;3(3).
26.
BintvihokW, ChaikittisilpaS, PanyakamlerdK, JaisamrarnU, TaechakraichanaN. Cut-off value of body fat in association with MetS in Thai peri-and postmenopausal women. Climacteric. 2013;16(3):393–7. doi: 10.3109/13697137.2012.762762
27.
JosephL, WasirJS, MisraA, VikramNK, GoelK, PandeyRM, ChandraM, PoddarP, KondalD. Appropriate values of adiposity and lean body mass indices to detect cardiovascular risk factors in Asian Indians. Diabetes Technology & Therapeutics. 2011;13(9):899–906. doi: 10.1089/dia.2011.0014
28.
LiL, WangC, BaoY, PengL, GuH, JiaW. Optimal body fat percentage cut-offs for obesity in C hinese adults. Clinical and Experimental Pharmacology and Physiology. 2012;39(4):393–8. doi: 10.1111/j.1440-1681.2012.05684.x
29.
HayashiT, BoykoEJ, McNeelyMJ, LeonettiDL, KahnSE, FujimotoWY. Minimum waist and visceral fat values for identifying Japanese Americans at risk for the MetS. Diabetes Care. 2007;30(1):120–7. doi: 10.2337/dc06-0739
30.
SeoJA, KimBG, ChoH, KimHS, ParkJ, BaikSH, et al.The cutoff values of visceral fat area and waist circumference for identifying subjects at risk for MetS in elderly Korean: Ansan Geriatric (AGE) cohort study. BMC Public Health. 2009;9(1):443. doi: 10.1186/1471-2458-9-443
31.
SoleimaniA, PourmoghaddasA, SadeghiM, RoohafzaH, TalaeiM, DianatkhahM, et al.Risk and Age of Cardiovascular Event in Women with MetS: Menopause Age in Focus. MetS and Related Disorders. 2018;16(3):127–34. doi: 10.1089/met.2017.0096
32.
WhayneTFJr, MukherjeeD. Women, the menopause, hormone replacement therapy and coronary heart disease. Current Opinion in Cardiology. 2015;30(4):432–8. doi: 10.1097/HCO.0000000000000157
33.
WangJ, RennieKL, GuW, LiH, YuZ, LinX. Independent associations of body-size adjusted fat mass and fat-free mass with the MetS in Chinese. Annals of Human Biology. 2009;36(1):110–21. doi: 10.1080/03014460802585079
34.
KnowlesK, PaivaL, SanchezS, RevillaL, LopezT, YasudaM, et al.Waist circumference, body mass index, and other measures of adiposity in predicting cardiovascular disease risk factors among Peruvian adults. International Journal of Hypertension. 2011;2011. doi: 10.4061/2011/931402
35.
RuizÁJ, AschnerPJ, PuertaMF, CristanchoRA. IDEA study (International Day for the Evaluation of Abdominal Obesity): Primary care study of the prevalence of abdominal obesity and associated risk factors in Colombia. Biomedica. 2012;32(4):610–6. doi: 10.1590/S0120-41572012000400016
36.
RuanoCN, MeloJP, MogrovejoLF, DeKP, EspinozaCR. Prevalence of metabolic syndrome and associated risk factors in ecuadorian university students. Nutricion Hospitalaria. 2015;31(4):1574–81. doi: 10.3305/nh.2015.31.4.8371
37.
JaffrinMY, MorelH. Body fluid volumes measurements by impedance: A review of bioimpedance spectroscopy (BIS) and bioimpedance analysis (BIA) methods. Medical Engineering & Physics. 2008;30(10):1257–69. doi: 10.1016/j.medengphy.2008.06.009
