Evaluation of waist-to-height ratio as a predictor of insulin resistance in non-diabetic obese individuals. A cross-sectional study
Keywords:
Anthropometry, Obesity, Diabetes mellitusAbstract
BACKGROUND: Insulin resistance (IR) and progressive pancreatic β-cell dysfunction have been identified as the two fundamental features in the pathogenesis of obesity and non-insulin-dependent diabetes mellitus. We aimed to investigate correlations between anthropometric indices of obesity and IR in nondiabetic obese individuals, and the cutoff value from receiver operating characteristic (ROC) curve analysis. DESIGN AND SETTING: Cross-sectional study conducted in a private clinic. METHODS: We included obese individuals (body mass index, BMI ≥ 30 kg/m2) with no diabetes mellitus (fasting glucose levels ≤ 126 mg/dl). The participants were evaluated for the presence of cardiovascular risk factors and through anthropometric measurements and biochemical tests. Furthermore, IR was assessed indirectly using the homeostatic model assessment (HOMA)-IR and HOMA-β indexes. The area under the curve (AUC) of the variables was compared. The sensitivity, specificity and cutoff of each variable for diagnosing IR were calculated. RESULTS: The most promising anthropometric parameters for indicating IR in non-diabetic obese individuals were waist-to-height ratio (WHtR), waist circumference (WC) and BMI. WHtR proved to be an independent predictor of IR, with risk increased by 0.53% in HOMA-IR, 5.3% in HOMA-β and 1.14% in insulin. For HOMA-IR, WHtR had the highest AUC value (0.98), followed by WC (0.93) and BMI (0.81). For HOMA-β, WHtR also had the highest AUC value (0.83), followed by WC (0.75) and BMI (0.73). The optimal WHtR cutoff was 0.65 for HOMA-IR and 0.67 for HOMA-β. CONCLUSION: Among anthropometric obesity indicators, WHtR was most closely associated with occurrences of IR and predicted the onset of diabetes in obese individuals.
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References
Goldfine AB, Conlin PR, Halperln F, et al. A randomised trial of salsalate for Insulin resistance and cardiovascular risk factors in persons with abnormal glucose tolerance. Diabetologia. 2013;56(4):714-23.
Carneiro IBP, Sampaio HAC, Carioca AAF, Pinto FJM, Damasceno NRT. Antigos e novos Indicadores antropométricos como preditores de resistência à Insulina em adolescentes [Old and new anthropometric Indices as Insulin resistance predictors In adolescentes]. Arq Bras Endocrinol Metabol. 2014;58(8):838-43.
Matthews DR. Insulin resistance and beta-cell function-a clinical perspective. Diabetes Obes Metab. 2001;3 Suppl 1:S28-33.
Song Y, Manson JE, Tinker L, et al. Insulin sensitivity and Insulin secretion determined by homeostasis model assessment and risk of diabetes In a multiethnic cohort of women: the Women's Health Initiative Observational Study. Diabetes Care. 2007;30(7):1747-52.
Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care. 2004;27(6):1487-95.
Matthews DR, Hosker JP, Rudenskl AS, et al. Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and Insulin concentrations In man. Diabetologla. 1985;28(7):412-9.
de Koning L, Merchant AT, Pogue J, Anand SS. Waist circumference and walst-to-hip ratio as predictors of cardiovascularevents: meta-regression analysis of prospective studies. Eur Heart J. 2007;28(7):850-6.
Vázquez-Vela ME, Torres N,Tovar AR. White adipose tissue as endocrine organ and Its role In obesity. Arch Med Res. 2008;39(8):715-28.
Um SM, Choi DP, RheeY, Kim HC. Association between Obesity Indices and Insulin Resistance among Healthy Korean Adolescents:The JS High School Study. PLoS One. 2015; 10(5):e0125238.
Vlkram NK, Latifi AN, Misra A, et al. Waist-to-Height Ratio Compared to Standard Obesity Measures as Predictor of Cardiometabolic Risk Factors In Asian Indians In North India. Metab Syndr Relat Disord. 2016;14(10):492-499.
Behboudi-Gandevani S, Ramezani Tehrani F, Cheraghi L, Azizl F Could "a body shape ¡ndex"and"waistto height ratio"predict Insulin resistance and metabolic syndrome in polycystic ovary syndrome? Eur J Obstet Gynecol Reprod Biol. 2016; 205:110-4.
Vasques AC, Geloneze B, Rosado L, et al. Indicadores antropométricos de resistência à Insulina [Anthropometric Indicators of Insulin resistance]. Arq Bras Cardiol. 2010;95(1):e14-e23.
American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014;37 Suppl 1:S81-90.
Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign: Human Kinetics Books; 1988.
Ben-Noun L, Sohar E, Laor A.Neckcircumference as a simplescreening measure for identifying overweight and obese patients. Obes Res. 2001;9(8):470-7.
Krakauer NY, Krakauer JC. A new body shape index predicts mortality hazard independently of body mass index. PLoS One. 2012;7(7):e39504.
Esteghamati A, Ashraf H, Esteghamati AR, et al. Optimal threshold of homeostasis model assessment for insulin resistance in an Iranian population: the implication of metabolic syndrome to detect insulin resistance. Diabetes Res Clin Pract. 2009;84(3):279-87.
Bravata DM, Wells CK, Concato J, et al.Two measures of insulin sensitivity provided similar information in a U.S. population. J Clin Epidemiol. 2004;57(11):1214-7.
Lee JM, Okumura MJ, Davis MM, Herman WH, Gurney JG. Prevalence and determinants of insulin resistance among U.S. adolescents: a population-based study. Diabetes Care. 2006;29(11):2427-32.
Geloneze B, Tambascia MA. Avaliação laboratorial e diagnóstico da resistência insulínica [Laboratorial evaluation and diagnosis of insulin resistance]. Arq Bras Endocrinol Metabol. 2006;50(2):208-15.
Geloneze B, Repetto EM, Geloneze SR, Tambascia MA, Ermetice MN. The threshold value for insulin resistance (HOMA-IR) in an admixtured population IR in the Brazilian Metabolic Syndrome Study. Diabetes Res Clin Pract. 2006;72(2):219-20.
Oliveira EP, Souza MLA, Lima MDA. Índice HOMA (homeostasis model assessment) na prática clínica: uma revisão [HOMA (homeostasis model assessment) index in clinical practice: a review]. J Bras Patol Med Lab. 2005;41(4):237-43.
Thompson WR, Gordon NF, Pescatello LS. ACSM's Guidelines for Exercise Testing and Prescription. 8th edition. Philadelphia: Lippincott Williams & Wilkins;2010.
Ashwell M, Lejeune S, McPherson K. Ratio of waist circumference to height may be better indicator of need for weight management. BMJ. 1996;312(7027):377.
Nazare JA, Smith JD, Borel AL, et al. Ethnic influences on the relations between abdominal subcutaneous and visceral adiposity, liverfat, and cardiometabolic risk profile: the International Study of Prediction of Intra-Abdominal Adiposity and Its Relationship With Cardiometabolic Risk/lntra-Abdominal Adiposity. Am J Clin Nutr. 2012;96(4):714-26.
Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev. 2012;13(3):275-86.
Matos LN, Giorelli Gde V, Dias CB. Correlation of anthropometric indicators for identifying insulin sensitivity and resistance. Sao Paulo Med J. 2011;129(1):30-5.
Nadeem A, Naveed AK, Hussain MM, Raza SI. Cut-off values of anthropometric indices to determine insulin resistance in Pakistani adults. J Pak Med Assoc. 2013;63(10):1220-5.
Hadaegh F, Shafiee G, Azizi F. Anthropometric predictors of incident type 2 diabetes mellitus in Iranian women. Ann Saudi Med. 2009;29(3):194-200.
Wang F,Wu S, Song Y, et aI. Waist circumference, body mass index and waist to hip ratio for prediction of the metabolic syndrome in Chinese. Nutr Metab Cardiovasc Dis. 2009;19(8):542-7.
Hadaegh F, Zabetian A, Harati H, Azizi F. Waist/height ratio as a better predictor of type 2 diabetes compared to body mass index InTehranian adult men-a 3.6-year prospective study. Exp Clin Endocrinol Diabetes. 2006;114(06):310-5.
Savva SC, Lamnisos D, Kafatos AG. Predicting cardiometabolic risk: waist-to-height ratio or BMI. A meta-analysis. Diabetes Metab Syndr Obes. 2013;6:403-19.
Després JP, Cartier A, Côté M, Arsenault BJ. The concept of cardiometabolic risk: Bridging the fields of diabetology and cardiology. Ann Med. 2008;40(7):514-23.
Primeau V, Coderre L, Karelis AD, et al. Characterizing the profile of obese patients who are metabolically healthy. Int J Obes (Lond). 2011;35(7):971-81.
Stefan N, Häring HU, Hu FB, Schulze MB. Metabolically healthy obesity: epidemiology, mechanisms, and clinical implications. Lancet Diabetes Endocrinol. 2013;1 (2):152-62.
Gaiţǎ D, Moşteoru S. Metabolically healthy versus unhealthy obesity and riskfordiabetes mellitus and cardiovascular diseases. Cardiovascular Endocrinology. 2017;6(1):23-6. Available from: http://journals. lww.com/cardiovascularendocrinology/Abstract/2017/03000/ Metabolically_healthy_versus_unhealthy_obesity_and.6.aspx Accessed in 2017 (Jul 13).
