Prevalence of Metabolic Syndrome and Its Prediction by Simple Adiposity Indices in Thai Adults
DOI:
https://doi.org/10.31584/jhsmr.2021791Keywords:
adiposity index, cut-off point, metabolic syndrome, lipid accumulation product, Thai adultsAbstract
Objective: Thai adults, have increased risk of being diagnosed with metabolic syndrome (MetS). Hence, early discrimination of MetS, with a simple and high accuracy index, appears necessary. However, the application of the discriminating ability of Lipid Accumulation Product (LAP), which is an emergent indicator of central lipid accumulation, to MetS among Thai people has not been investigated. This present study’s purposes were to investigate the nationwide prevalence of MetS, and the ability of LAP in discriminating this disorder.
Material and Methods: Cross-sectional secondary data analysis was performed in 2018, using primary data from the Thai National Health Examination Survey, 2009. A total of 18,642 Thailanders ≥18 years were recruited. MetS was diagnosed by the National Cholesterol Education Program/Adult Treatment Panel III (NCEP/ATP) and International Diabetes Federation (IDF).
Results: Overall, the prevalence of MetS-NCEP/ATP and MetS-IDF in Thai adults was 20.0% and 27.0%, respectively. LAP showed outstanding discriminating ability for MetS in both definitions (the cut-off point of 34.38 and 37.96 cm.mmol/L; area under the curve of 0.889 and 0.915 for NCEP/ATP and IDF, respectively). LAP performed the closest agreement in discriminating MetS-NCEP/ATP (κ=0.598, p-value<0.001) and MetS-IDF (κ=0.577, p-value<0.001). Logistic regression analysis exhibited a strong association of the LAP cut-off point with MetS, with the odds ratio being from 23.37 to 27.22 (p-value<0.001).
Conclusion: These study results revealed that LAP was strongly associated with MetS, had an outstanding and reliable diagnostic accuracy for discriminating MetS in Thai adults, which might be helpful for early detection of MetS among vulnerable populations.
References
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Kahn HS. The "lipid accumulation product" performs better than the body mass index for recognizing cardiovascular risk: a population-based comparison. BMC Cardiovasc Disord. 2005;5:26.
Taverna MJ, Martinez-Larrad MT, Frechtel GD, Serrano-Rios M. Lipid accumulation product: a powerful marker of metabolic syndrome in healthy population. Eur J Endocrinol 2011; 164:559-67.
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Kishida K, Funahashi T, Matsuzawa Y, Shimomura I. Visceral adiposity as a target for the management of the metabolic syndrome. Ann Med 2012;44:233–41.
Freedland ES. Role of a critical visceral adipose tissue threshold (CVATT) in metabolic syndrome: implications for controlling dietary carbohydrates: a review. Nutr Metab (Lond) 2004;1:12.
Carobbio S, Rodriguez-Cuenca S, Vidal-Puig A. Origins of metabolic complications in obesity: ectopic fat accumulation. The importance of the qualitative aspect of lipotoxicity. Curr Opin Clin Nutr Metab Care 2011;14:520–6.
Molarius A, Seidell JC. Selection of anthropometric indicators for classification of abdominal fatness--a critical review. Int J Obes Relat Metab Disord 1998;22:719-27.
Huang CY, Huang HL, Yang KC, Lee LT, Yang WS, Huang KC, et al. Serum triglyceride levels independently contribute to the estimation of visceral fat amount among nondiabetic obese adults. Medicine (Baltimore) 2015;94:e965.
Nguyen-Duy TB, Nichaman MZ, Church TS, Blair SN, Ross R. Visceral fat and liver fat are independent predictors of metabolic risk factors in men. Am J Physiol Endocrinol Metab 2003; 284:E1065-71.
Czech MP, Tencerova M, Pedersen DJ, Aouadi M. Insulin signalling mechanisms for triacylglycerol storage. Diabetologia 2013;56:949–64.
Sam S, Haffner S, Davidson MH, D'Agostino RB Sr, Feinstein S, Kondos G, et al. Hypertriglyceridemic waist phenotype predicts increased visceral fat in subjects with type 2 diabetes. Diabetes Care 2009;32:1916-20.
Zainuddin LR, Isa N, Muda WM, Mohamed HJ. The prevalence of metabolic syndrome according to various definitions and hypertriglyceridemic-waist in malaysian adults. Int J Prev Med 2011;2:229-37.
Ford ES, Li C, Sattar N. Metabolic syndrome and incident diabetes: current state of the evidence. Diabetes Care 2008; 31:1898-904.
Wu SH, Liu Z, Ho SC. Metabolic syndrome and all-cause mortality: a meta-analysis of prospective cohort studies. Eur J Epidemiol 2010;25:375-84.
Aekplakorn W, Chongsuvivatwong V, Tatsanavivat P, Suriyawongpaisal P. Prevalence of metabolic syndrome defined by the International Diabetes Federation and National Cholesterol Education Program criteria among Thai adults. Asia Pac J Public Health 2011;23:792-800.
Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998;15:539-53.
Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009;120:1640-5.
Jung UJ, Choi MS. Obesity and its metabolic complications: the role of adipokines and the relationship between obesity, inflammation, insulin resistance, dyslipidemia and nonalcoholic fatty liver disease. Int J Mol Sci 2014;15:6184-223.
Kahn HS. The "lipid accumulation product" performs better than the body mass index for recognizing cardiovascular risk: a population-based comparison. BMC Cardiovasc Disord. 2005;5:26.
Taverna MJ, Martinez-Larrad MT, Frechtel GD, Serrano-Rios M. Lipid accumulation product: a powerful marker of metabolic syndrome in healthy population. Eur J Endocrinol 2011; 164:559-67.
Motamed N, Razmjou S, Hemmasi G, Maadi M, Zamani F. Lipid accumulation product and metabolic syndrome: a populationbased study in northern Iran, Amol. J Endocrinol Invest 2016; 39:375-82.
Tellechea ML, Aranguren F, Martinez-Larrad MT, Serrano-Rios M, Taverna MJ, Frechtel GD. Ability of lipid accumulation product to identify metabolic syndrome in healthy men from Buenos Aires. Diabetes Care 2009;32:e85.
Chiang JK, Koo M. Lipid accumulation product: a simple and accurate index for predicting metabolic syndrome in Taiwanese people aged 50 and over. BMC Cardiovasc Disord 2012;12:78.
Lim U, Ernst T, Buchthal SD, Latch M, Albright CL, Wilkens LR, et al. Asian women have greater abdominal and visceral adiposity than Caucasian women with similar body mass index. Nutr Diabetes 2011;1:e6.
Pi-Sunyer FX. The epidemiology of central fat distribution in relation to disease. Nutr Rev 2004;62:S120-6.
Aekplakorn W, Chariyalertsak S, Kessomboon P, Sangthong R, Inthawong R, Putwatana P, et al. Prevalence and management of diabetes and metabolic risk factors in Thai adults: the Thai National Health Examination Survey IV, 2009. Diabetes Care 2011;34:1980-5.
Wakabayashi I, Daimon T. The "cardiometabolic index" as a new marker determined by adiposity and blood lipids for discrimination of diabetes mellitus. Clin Chim Acta 2015;438: 274-8.
Amato MC, Giordano C. Visceral adiposity index: an indicator of adipose tissue dysfunction. Int J Endocrinol 2014;2014: 730827.
Youden WJ. Index for rating diagnostic tests. Cancer 1950;3: 32-5.
Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982;143:29-36.
Lu J, Wang L, Li M, Xu Y, Jiang Y, Wang W, et al. Metabolic Syndrome Among Adults in China: The 2010 China Noncommunicable Disease Surveillance. J Clin Endocrinol Metab 2017;102:507-15.
Hong AR, Lim S. Clinical characteristics of metabolic syndrome in Korea, and its comparison with other Asian countries. J Diabetes Investig 2015;6:508-15.
Chackrewarthy S, Gunasekera D, Pathmeswaren A, Wijekoon CN, Ranawaka UK, Kato N, et al. A Comparison between Revised NCEP ATP III and IDF Definitions in Diagnosing Metabolic Syndrome in an Urban Sri Lankan Population: The Ragama Health Study. ISRN Endocrinol 2013;2013:320176.
Scuteri A, Laurent S, Cucca F, Cockcroft J, Cunha PG, Mañas LR, et al. Metabolic syndrome across Europe: different clusters of risk factors. Eur J Prev Cardiol 2015;22:486–91.
Nazare JA, Smith JD, Borel AL, Haffner SM, Balkau B, Ross R, et al. Ethnic influences on the relations between abdominal subcutaneous and visceral adiposity, liver fat, and cardiometabolic risk profile: the International Study of Prediction of Intra-Abdominal Adiposity and Its Relationship With Cardiometabolic Risk/Intra-Abdominal Adiposity. Am J Clin Nutr 2012; 96:714-26.
Li R, Li Q, Cui M, Yin Z, Li L, Zhong T, et al. Clinical surrogate markers for predicting metabolic syndrome in middle-aged and elderly Chinese. J Diabetes Investig 2018;9:411-8.
Browning LM, Hsieh SD, Ashwell M. A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0.5 could be a suitable global boundary value. Nutr Res Rev 2010;23:247-69.
Hamdy O, Porramatikul S, Al-Ozairi E. Metabolic obesity: the paradox between visceral and subcutaneous fat. Curr Diabetes Rev 2006;2:367-73.
Kishida K, Funahashi T, Matsuzawa Y, Shimomura I. Visceral adiposity as a target for the management of the metabolic syndrome. Ann Med 2012;44:233–41.
Freedland ES. Role of a critical visceral adipose tissue threshold (CVATT) in metabolic syndrome: implications for controlling dietary carbohydrates: a review. Nutr Metab (Lond) 2004;1:12.
Carobbio S, Rodriguez-Cuenca S, Vidal-Puig A. Origins of metabolic complications in obesity: ectopic fat accumulation. The importance of the qualitative aspect of lipotoxicity. Curr Opin Clin Nutr Metab Care 2011;14:520–6.
Molarius A, Seidell JC. Selection of anthropometric indicators for classification of abdominal fatness--a critical review. Int J Obes Relat Metab Disord 1998;22:719-27.
Huang CY, Huang HL, Yang KC, Lee LT, Yang WS, Huang KC, et al. Serum triglyceride levels independently contribute to the estimation of visceral fat amount among nondiabetic obese adults. Medicine (Baltimore) 2015;94:e965.
Nguyen-Duy TB, Nichaman MZ, Church TS, Blair SN, Ross R. Visceral fat and liver fat are independent predictors of metabolic risk factors in men. Am J Physiol Endocrinol Metab 2003; 284:E1065-71.
Czech MP, Tencerova M, Pedersen DJ, Aouadi M. Insulin signalling mechanisms for triacylglycerol storage. Diabetologia 2013;56:949–64.
Sam S, Haffner S, Davidson MH, D'Agostino RB Sr, Feinstein S, Kondos G, et al. Hypertriglyceridemic waist phenotype predicts increased visceral fat in subjects with type 2 diabetes. Diabetes Care 2009;32:1916-20.
Zainuddin LR, Isa N, Muda WM, Mohamed HJ. The prevalence of metabolic syndrome according to various definitions and hypertriglyceridemic-waist in malaysian adults. Int J Prev Med 2011;2:229-37.
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Published
2021-06-01
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Nguyen Ngoc H, Kriengsinyos W, Rojroongwasinkul N, Aekplakorn W. Prevalence of Metabolic Syndrome and Its Prediction by Simple Adiposity Indices in Thai Adults. J Health Sci Med Res [Internet]. 2021 Jun. 1 [cited 2024 Nov. 22];39(4):345-51. Available from: https://he01.tci-thaijo.org/index.php/jhsmr/article/view/250162
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