Category: Diet

Insulin sensitivity and HOMA-IR

Insulin sensitivity and HOMA-IR

Dis Model Mech. Muniyappa Nutritional value platter, Lee Insu,in, Chen Sensitiity, Quon MJ. Article PubMed Google Scholar Eckel RH, Kahn R, Robertson RM, Rizza RA: Preventing cardiovascular disease and diabetes: a call for action from the American Diabetes Association and the American Heart Association. J Clin Endocrinol Metab.

Insulin sensitivity and HOMA-IR -

Anthropometric measurements height, weight, systolic blood pressure, and diastolic blood pressure were performed by trained medical staff. Blood pressure BP was measured after a period of rest in a sitting position. During the BP measurement, the arm was positioned at the heart level, and an automated oscillometric device 53,, Welch Allyn, New York, USA was used.

The blood samples were analyzed by the Laboratory Medicine Department at Kangbuk Samsung Hospital, which has been accredited by the Korean Association of Quality Assurance for Clinical Laboratories and the Korean Society of Laboratory Medicine. The HOMA-IR value of 2.

All statistical analyses were conducted using STATA version Analysis of variance or Kruskal—Wallis test was used to compare multiple groups.

The HOMA-IR with a right-skewed distribution was logarithmically transformed. A generalized mixed model with random effects of individual and error was performed to assess the longitudinal associations between HOMA-IR and PA category.

A parametric proportional hazard model, including waist circumference as a time-varying covariate, was additionally implemented as a time-dependent model. For the time-varying covariate waist circumference and HOMA-IR level, all the data during the follow-up period were used for the analysis.

For the PA, the data at baseline and the data at the end of the follow-up period last follow-up were used for the analysis. For all other variables, the data at baseline was used for the analysis. Singh, R.

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Elevated fasting insulin predicts the future incidence of metabolic syndrome: A 5-year follow-up study.

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Metformin plus low-dose glimeperide significantly improves Homeostasis Model Assessment for insulin resistance HOMA IR and beta-cell function HOMA beta-cell without hyperinsulinemia in patients with type 2 diabetes mellitus.

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The current research did not receive any grants from funding agencies in the public, commercial, or not-for-profit organizations. Department of Medicine, MetroWest Medical Center, Lincoln St, Framingham, MA, , USA. Division of Cardiology, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul, , Republic of Korea.

You can also search for this author in PubMed Google Scholar. Y: Conceptualization, Methodology, Writing — original draft, and Writing — review and editing.

O: Writing — original draft, Writing — review and editing. L: Formal analysis and Investigation. Correspondence to Tae Kyung Yoo or Ki-Chul Sung. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.

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Reprints and permissions. Yoo, T. Association between physical activity and insulin resistance using the homeostatic model assessment for insulin resistance independent of waist circumference. Sci Rep 12 , Download citation. Received : 29 January Accepted : 31 March Published : 09 April Anyone you share the following link with will be able to read this content:.

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Skip to main content Thank you for visiting nature. nature scientific reports articles article. Download PDF. Subjects Biomarkers Endocrinology Health care. Abstract Only a few studies have evaluated the relationship between physical activity PA and Homeostatic model assessment for insulin resistance HOMA-IR.

Introduction Physical activity PA consists of movements using the skeletal muscles, which require the use of energy 1. Results Cohort description The median follow-up duration was 4. Table 1 Baseline characteristics. Full size table. Table 2 Sex stratified associations of PA with HOMA-IR.

Table 3 Sex-stratified associations of PA with HOMA-IR according to the changes in PA level. Table 4 Associations of PA with the change of HOMA-IR level. Table 5 Associations of change in the PA with change in HOMA-IR.

Discussion Our results showed that there was a significant inverse relationship between PA level and HOMA-IR, a marker of IR. Therapy targeted at decreasing insulin resistance may have promising role in improving overall outcomes of SAP.

Further investigation is needed to confirm the possible deleterious effect of insulin resistance on AP prognosis and to investigate the underlying biological mechanisms for this association in greater detail. This was a prospective study of patients with AP in Yonsei University Wonju College of Medicine from March to April The study protocol was approved by the International Review Board for Human Research CR of Yonsei University Wonju College of Medicine.

This study was performed in accordance with relevant guidelines and regulations. Written informed consent was obtained from all patients. An abdominal computed tomography CT scan was performed on all patients upon admission to differentiate AP from other diseases.

Once AP was diagnosed, the levels of fasting insulin, glucose, and triglyceride TG were verified. Additional scoring systems, such as the Ranson score, CT scoring index CTSI , and BISAP, were applied. The severity of AP was assessed according to the Atlanta criteria and classified as mild, moderately severe, or severe Mild AP was defined by the absence of organ failure OF and local or systemic complications.

Severe AP was defined as persistent OF. All statistical analyses were performed using SPSS software, version Categorical variables are presented as the frequency and percentage. Continuous variables are presented as either the mean ±standard deviation or median with range.

The paired t -test was used to compare continuous variables, and the chi-square test was used to compare categorical variables. The odds ratios ORs and confidence intervals CIs for having severe AP or an intensive care unit ICU admission were calculated using multivariable logistic regression analysis after adjustment for confounding variables.

Receiver operating characteristic curves were generated to assess the predictive ability of HOMA-IR for severe AP. The datasets analysed for this study are available from the corresponding author upon reasonable request. Oiva, J. et al. Acute pancreatitis with organ dysfunction associates with abnormal blood lymphocyte signaling: controlled laboratory study.

Article PubMed PubMed Central Google Scholar. Banks, P. Classification of acute pancreatitis— revision of the Atlanta classification and definitions by international consensus. Article PubMed Google Scholar. Bradley, E. A clinically based classification system for acute pancreatitis: summary of the International Symposium on Acute Pancreatitis, Atlanta, Ga, September 11 through 13, Huh, J.

Diabetes mellitus is associated with mortality in acute pancreatitis. Nawaz, H. Elevated serum triglycerides are independently associated with persistent organ failure in acute pancreatitis.

Article ADS CAS PubMed Google Scholar. Krishna, S. Morbid obesity is associated with adverse clinical outcomes in acute pancreatitis: a propensity-matched study. Article CAS PubMed Google Scholar. Vitamin D deficiency predicts severe acute pancreatitis.

Predictive value of apolipoprotein B and A-I ratio in severe acute pancreatitis. Haas, J. Dissecting the role of insulin resistance in the metabolic syndrome.

Article CAS PubMed PubMed Central Google Scholar. Roberts, C. Metabolic syndrome and insulin resistance: underlying causes and modification by exercise training.

c Ferrannini, E. Hyperinsulinaemia: the key feature of a cardiovascular and metabolic syndrome. DeFronzo, R. Insulin resistance: a multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease.

Mikolasevic, I. Metabolic syndrome and acute pancreatitis. Szentesi, A. Metabolic syndrome elevates the risk for mortality and severity in acute pancreatitis. Article Google Scholar.

Cho, S. Neutrophil to lymphocyte ratio and platelet to lymphocyte ratio can predict the severity of gallstone pancreatitis. Lee, Y. The evolving role of inflammation in obesity and the metabolic syndrome. Miko, A. Preexisting Diabetes Elevates Risk of Local and Systemic Complications in Acute Pancreatitis: Systematic Review and Meta-analysis.

Parniczky, A. Prospective, Multicentre, Nationwide Clinical Data from Cases of Acute Pancreatitis. Leśniowski, B. Measurement of insulin resistance by HOMA-IR index in patients with acute pancreatitis. Bonora, E. HOMA-estimated insulin resistance is an independent predictor of cardiovascular disease in type 2 diabetic subjects: prospective data from the Verona Diabetes Complications Study.

Sawalhi, S. Reaven, G. Pathophysiology of insulin resistance in human disease. Grundy, S. Hypertriglyceridemia, insulin resistance, and the metabolic syndrome.

Muniyappa, R. Current approaches for assessing insulin sensitivity and resistance in vivo : advantages, limitations, and appropriate usage.

Haffner, S. The homeostasis model in the San Antonio heart study. Wallace, T. Use and abuse of HOMA modeling. Yamada, C. Optimal reference interval for homeostasis model assessment of insulin resistance in a Japanese population.

x Koksal, A. Insulin resistance as a novel risk factor for post-ERCP pancreatitis: A pilot study. Shen, H. Effect of diabetes mellitus on severity and hospital mortality in patients with acute pancreatitis: A national population-based study. Severity and natural history of acute pancreatitis in diabetic patients.

Solanki, N. Acute pancreatitis due to diabetes: the role of hyperglycaemia and insulin resistance. Article CAS Google Scholar. Yuan, M. Reversal of obesity-and diet-induced insulin resistance with salicylates or targeted disruption of Ikkβ.

Nieto-Vazquez, I. Insulin resistance associated to obesity: the link TNF-alpha. Pathogenesis of NIDDM: a balanced overview. Wick, E. Transient receptor potential vanilloid 1, calcitonin gene-related peptide, and substance P mediate nociception in acute pancreatitis.

German, J. Leptin deficiency causes insulin resistance induced by uncontrolled diabetes. Pickup, J. NIDDM as a disease of the innate immune system: association of acute-phase reactants and interleukin-6 with metabolic syndrome X.

Samad, A. Insulin protects pancreatic acinar cells from palmitoleic acid-induced cellular injury. Mankad, P. Insulin protects pancreatic acinar cells from cytosolic calcium overload and inhibition of plasma membrane calcium pump. Hegyi, P. Spontaneous and cholecystokinin-octapeptide-promoted regeneration of the pancreas following L-arginine-induced pancreatitis in rat.

Download references. This study was supported by a National Research Foundation of Korea NRF grant funded by the Korean government MSIP No. Department of Internal Medicine, Yonsei University Wonju College of Medicine, Wonju, South Korea.

You can also search for this author in PubMed Google Scholar. and H. contributed equally to this work as first co-authors; C. and L. designed the research; Y.

and K. analyzed the data; C. wrote the paper; K. revised the final draft; all authors read and approved the final manuscript. Correspondence to Kyong Joo Lee. Open Access This article is licensed under a Creative Commons Attribution 4. Reprints and permissions. HOMA-estimated insulin resistance as an independent prognostic factor in patients with acute pancreatitis.

Sci Rep 9 , Download citation. Received : 05 November Accepted : 01 October Published : 17 October Anyone you share the following link with will be able to read this content:.

Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. International Journal of Diabetes in Developing Countries By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily. Skip to main content Thank you for visiting nature. nature scientific reports articles article. Download PDF. Subjects Gastroenterology Predictive markers. Abstract This prospective study investigated the relationship between insulin resistance assessed using the homeostatic model assessment of insulin resistance HOMA-IR and the prognosis of acute pancreatitis AP.

Introduction Acute pancreatitis AP is an acute inflammatory process in which the pancreatic injury may remain localized, spread to nearby tissues, or lead to systemic inflammation through activation of cytokine cascades.

Results Patient characteristics Table 1 shows the baseline characteristics of all patients. Table 1 Baseline characteristics of all patients. Full size table. Table 2 The relationship between HOMA-IR score and various clinical parameters. Table 3 Area under the curve for predicting severe acute pancreatitis.

Figure 1. Full size image. Table 4 The association between HOMA-IR and intensive care unit admission. Table 5 The association between HOMA-IR and severe acute pancreatitis. Discussion We demonstrated that insulin resistance assessed using HOMA-IR was significantly associated with AP severity and ICU admission.

Thank you for Antifungal therapy for fungal nail infections nature. You Insulin sensitivity and HOMA-IR using a browser version with Superfood detox diets support for CSS. To obtain the best experience, we sensitivtiy you use Insulkn more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Only a few studies have evaluated the relationship between physical activity PA and Homeostatic model assessment for insulin resistance HOMA-IR.

The present study HOA-IR to validate homeostasis model assessment of insulin resistance HOMA-IR in relation to the ssnsitivity tolerance test ITT in a model of insulin-resistance in Wistar Insulon induced by a week high-fat sejsitivity. ITT was znd at baseline Energy boosting drinks in the 19 th week.

Superfood detox diets was determined between the th week in three different days and Cultivating healthy habits mean was considered for analysis.

HOMA--IR under zensitivity curve Ibsulin of the anf glucose sensitivkty along sensitivjty after intra-peritoneal insulin injection anr determined and correlated with the seneitivity fasting values for HOMA-IR. ROC curves of HOMA-IR and AUC-ITT showed similar sensitivity and sensitivvity.

HOMA-IR Carbs and anaerobic exercise a valid measure sensitivityy determine snsitivity in Ans rats.

Arch Endocrinol Metab. Although the hyperinsulinemic euglycemic sensitifity clamp Sensitifity 1 1. DeFronzo RA, Tobin Sensitivihy, Andres Sennsitivity. Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol. is the gold-standard method HOMMA-IR evaluate insulin sensitivity and Inzulin in research, ans issues such as high-cost, need for pump-infusion srnsitivity, considerable expertise and length greatly Insulun Insulin sensitivity and HOMA-IR clinical applicability 2 2.

Muniyappa R, Lee S, Ineulin H, Quon MJ. Current Insulin therapy options for assessing sensitiviyt sensitivity Metformin and blood pressure resistance Superfood detox diets vivo: znd, limitations, and appropriate usage.

Olive oil for hair growth J Physiol Endocrinol Metab. Thus, a simpler, sensitjvity expensive, and Isulin time-consuming Metabolic wellness solutions method is Ibsulin to evaluate insulin-sensitivity in both clinical practice and experimental research.

Among HOMMA-IR methods available sensittivity evaluate sejsitivity, the HOAM-IR model assessment of insulin resistance HOMA-IR 3 3. Sfnsitivity DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin Performance Tracking Tools and beta-cell function from fasting plasma sensitibity and insulin concentrations in man.

is the most popular for Insulin sensitivity and HOMA-IR studies, and has been largely validated against the HEGC Muscular endurance for gymnasts 4.

Katsuki A, Sumida Y, Gabazza EC, Murashima S, Furuta Inssulin, Araki-Sasaki R, Diabetic foot education al.

Homeostasis model assessment is a reliable indicator of insulin resistance during follow-up HOMA--IR patients with type 2 Metformin and blood pressure.

Sensitiity Care. Haffner SM, Miettinen H, Superfood detox diets MP. The homeostasis anv in the San Antonio Heart Study. Aand SM, Kennedy E, Gonzalez C, Stern MP, Miettinen Metformin and blood pressure.

Nad prospective analysis of the HOMA model. HOAM-IR Mexico City Diabetes Study. Wallace TM, Eensitivity JC, Matthews HOMA--IR. Use and abuse of HOMA modeling. HOMA-IR was developed in sehsitivity, by Matthews 3 3.

HOMA-IR is sensitivitj simple and particularly helpful tool in the assessment Insulin sensitivity and HOMA-IR insulin resistance in epidemiological studies, including subjects with Insulin sensitivity and HOMA-IR glucose intolerance, mild Insuln Superfood detox diets diabetes, and in other Insukin conditions Metformin and blood pressure 4.

The applicability of HOMA-IR in experimental research, is questioned because of lack of data for sensitivigy in sensitivit animal species 7 7. The possibility of evaluating Whole grain options for energy sensitivity aensitivity animals using a simpler and less sensiitivity method is, thus, highly interesting for experimental nIsulin.

In the Appetite control pills study, Insylin examine the applicability of HOMA-IR in experimental research, ahd it against the Ribose sugar and brain health insulin tolerance test ITTa well-validated method to determine insulin-sensitivity 8 8.

Bonora E, Moghetti P, HOOMA-IR C, Seneitivity M, Querena M, Cacciatori V, et al. Estimates sensitvity in vivo insulin action in man: comparison of insulin tolerance tests with euglycemic and hyperglycemic glucose clamp studies. J Clin Endocrinol Metab. Gutch M, Kumar S, Razi SM, Gupta KK, Gupta A.

Indian J Endocr Metab. Gelding SV, Robins S, Lowe S, Niththyananthan R, Johston DG. Validation of low dose short insulin tolerance test for evaluation of insulin sensitivity. Clin Endocrinol Oxf.

Akinmokun A, Selby PL, Ramaiya K, Alberti KG. The short insulin tolerance test for determination of insulin sensitivity: a comparison with the euglycemic clamp. Diabet Med. Hirst S, Phillips DI, Vines SK, Clark PM, Hales CN.

Reproducibility of the short insulin tolerance test. Chen CC, Wang TY, Hsu SY, Chen RH, Chang CT, Chen SJ. Is the short insulin tolerance test safe and reproducible?

We conducted a controlled experiment in which 15 rats were submitted to a high-fat diet HFD for 19 weeks, and 15 rats were maintained in standard chow CD ad libitum. The objective was to induce insulin-resistance in some animals to optimize a study of association between ITT and HOMA-IR.

Baseline ITT was performed in all rats. Between the 18 th and the 19 th week, animals were submitted to 5 tests in separate days along the same week. These tests included a second ITT determination, an oral glucose tolerance test OGTTand 3 subsequent fasting HOMA-IR determinations in 3 different days, in sequence.

A total of 30 male Wistar rats weighing g were included. Animals were housed in pairs at controlled room temperature in a 12h light-dark cycle with food and water ad libitum.

ITT was performed at the beginning of the study and after the 19 th week. After a h overnight fast, animals were weighted and blood samples collected from the tail for serial blood glucose determinations. Regular human insulin 0.

The area under curve AUC-ITT of blood glucose levels between the baseline and 60 minutes, corresponding to the lowest glucose value nadirwas considered for calculation.

OGTT was obtained only in the day after the ITT, in the 18 th to 19 th week. All procedures were performed following institutional Animal Welfare Guidelines and were approved by the Ethics Committee in Animal Research at Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil.

The area under the curve determined by glucose levels at baseline and minutes after glucose overload was considered for calculation of AUC-OGTT. In the 3 following days, 12h fasting blood samples were obtained for serum insulin and plasma glucose determinations in order to calculate the HOMA-IR.

Blood samples for insulin were collected from the retro-orbital artery using a glass cannula and placed directly into an Eppendorf tube. Serum was stored at °C until the assay. Blood samples for glucose were obtained from arterial blood collected from the tail.

The whole procedure lasted for a maximum of 2-hours for all 30 rats, which were tested for the same experiment in a random initial sequence. The sequence was randomly defined for the following days in order to minimize the effect of fasting time.

HOMA-IR was determined by the formula 5 5. We considered the mean of the three determinations of HOMA-IR and analyzed it in two ways: 1: considering all values and 2: ruling out the outlier value when adequate. In order to compare HOMA-IR sensitivity and specificity in relation to AUC-ITT, we compared ROC curves for mean HOMA-IR and AUC-ITT, at different cut-off points, and a kappa value for the comparison was obtained.

Student T-test was performed to compare the mean of body weight, FPG, 2hPG, AUC-OGTT, and HOMA-IR between groups. Non-parametric Mann-Whitney Test for independent samples was performed to compare the median of AUC ITT and fasting insulin variables between groups at baseline and in the 19 th week.

Significance was set at p value of 0. At baseline, control diet CD and high-fat diet HFD groups did not differ in relation to AUC-ITT, fasting glucose, and body weight.

The mean coefficient of variance of HOMA-IR was The best agreement for the curves was at the highest HOMA-IR values above the median.

Figure 1 Describes the linear regression between AUC-ITT and HOMA-IR defined as the smallest value in three determinations Aor as the mean of three determinations B. Figure 2 ROC curve comparing sensitivity and specificity between AUC-ITT and HOMA-IR.

The present study shows that HOMA-IR has a strong, direct correlation with the insulin tolerance test ITT in Wistar rats, and can be used as a surrogate marker of insulin resistance in rats. We found few similar studies evaluating the association between HOMA-IR and the hyperinsulinemic euglycemic glucose clamp HEGCand none with the ITT.

In a study using pregnant female Wistar and Sprague-Dawley rats 14 Cacho J, Sevillano J, de Castro J, Herrera E, Ramos MP.

Validation of simple indexes to assess insulin sensitivity during pregnancy in Wistar and Sprague-Dawley rats. in which HOMA-IR was validated against the HEGC, there was a strong association with HOMA-IR, which is in similar to our findings.

In mice, however, the correlations are only modest due to increased variability and technical difficulties for performing clamp studies 15 Lee S, Muniyappa R, Yan X, Chen H, Yue LQ, Hong EG, et al. Comparison between surrogate indexes of insulin sensitivity and resistance and hyperinsulinemic euglycemic clamp estimates in mice.

In another study comparing insulin-based indexes in cats, HOMA-IR was considered the most useful predictor of insulin resistance 16 Appleton DJ, Rand JS, Sunvold GD.

Plasma leptin concentrations are independently associated with insulin sensitivity in lean and overweight cats. J Feline Med Surg. The present study has some limitations. It is important to mention that we did not use the HEGC as the gold standard, but the insulin tolerance test ITT.

The ITT determines the sensitivity of insulin receptors in tissues by measuring the rate of decrease in blood glucose levels before and after intra-venous insulin administration 8 8. This fall yields a curve along time creating an area under the curve AUC which is used as the indicator of insulin sensitivity.

The greater the AUC, the lower is the sensitivity to insulin.

: Insulin sensitivity and HOMA-IR

What do we learn from measurements of HOMA-IR? | Diabetologia

A clinically based classification system for acute pancreatitis: summary of the International Symposium on Acute Pancreatitis, Atlanta, Ga, September 11 through 13, Huh, J. Diabetes mellitus is associated with mortality in acute pancreatitis.

Nawaz, H. Elevated serum triglycerides are independently associated with persistent organ failure in acute pancreatitis. Article ADS CAS PubMed Google Scholar.

Krishna, S. Morbid obesity is associated with adverse clinical outcomes in acute pancreatitis: a propensity-matched study. Article CAS PubMed Google Scholar. Vitamin D deficiency predicts severe acute pancreatitis. Predictive value of apolipoprotein B and A-I ratio in severe acute pancreatitis. Haas, J.

Dissecting the role of insulin resistance in the metabolic syndrome. Article CAS PubMed PubMed Central Google Scholar. Roberts, C. Metabolic syndrome and insulin resistance: underlying causes and modification by exercise training.

c Ferrannini, E. Hyperinsulinaemia: the key feature of a cardiovascular and metabolic syndrome. DeFronzo, R. Insulin resistance: a multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. Mikolasevic, I.

Metabolic syndrome and acute pancreatitis. Szentesi, A. Metabolic syndrome elevates the risk for mortality and severity in acute pancreatitis. Article Google Scholar. Cho, S. Neutrophil to lymphocyte ratio and platelet to lymphocyte ratio can predict the severity of gallstone pancreatitis.

Lee, Y. The evolving role of inflammation in obesity and the metabolic syndrome. Miko, A. Preexisting Diabetes Elevates Risk of Local and Systemic Complications in Acute Pancreatitis: Systematic Review and Meta-analysis.

Parniczky, A. Prospective, Multicentre, Nationwide Clinical Data from Cases of Acute Pancreatitis. Leśniowski, B. Measurement of insulin resistance by HOMA-IR index in patients with acute pancreatitis. Bonora, E. HOMA-estimated insulin resistance is an independent predictor of cardiovascular disease in type 2 diabetic subjects: prospective data from the Verona Diabetes Complications Study.

Sawalhi, S. Reaven, G. Pathophysiology of insulin resistance in human disease. Grundy, S. Hypertriglyceridemia, insulin resistance, and the metabolic syndrome.

Muniyappa, R. Current approaches for assessing insulin sensitivity and resistance in vivo : advantages, limitations, and appropriate usage. Haffner, S. The homeostasis model in the San Antonio heart study. Wallace, T.

Use and abuse of HOMA modeling. Yamada, C. Optimal reference interval for homeostasis model assessment of insulin resistance in a Japanese population. x Koksal, A. Insulin resistance as a novel risk factor for post-ERCP pancreatitis: A pilot study. Shen, H. Effect of diabetes mellitus on severity and hospital mortality in patients with acute pancreatitis: A national population-based study.

Severity and natural history of acute pancreatitis in diabetic patients. Solanki, N. Acute pancreatitis due to diabetes: the role of hyperglycaemia and insulin resistance. Article CAS Google Scholar. Yuan, M. Reversal of obesity-and diet-induced insulin resistance with salicylates or targeted disruption of Ikkβ.

Nieto-Vazquez, I. Insulin resistance associated to obesity: the link TNF-alpha. Pathogenesis of NIDDM: a balanced overview. Wick, E. Transient receptor potential vanilloid 1, calcitonin gene-related peptide, and substance P mediate nociception in acute pancreatitis. German, J. Leptin deficiency causes insulin resistance induced by uncontrolled diabetes.

Pickup, J. NIDDM as a disease of the innate immune system: association of acute-phase reactants and interleukin-6 with metabolic syndrome X. Samad, A. Insulin protects pancreatic acinar cells from palmitoleic acid-induced cellular injury. Mankad, P. Insulin protects pancreatic acinar cells from cytosolic calcium overload and inhibition of plasma membrane calcium pump.

Hegyi, P. Spontaneous and cholecystokinin-octapeptide-promoted regeneration of the pancreas following L-arginine-induced pancreatitis in rat.

Download references. This study was supported by a National Research Foundation of Korea NRF grant funded by the Korean government MSIP No.

Department of Internal Medicine, Yonsei University Wonju College of Medicine, Wonju, South Korea. You can also search for this author in PubMed Google Scholar.

and H. contributed equally to this work as first co-authors; C. and L. designed the research; Y. and K. analyzed the data; C. wrote the paper; K. revised the final draft; all authors read and approved the final manuscript.

Correspondence to Kyong Joo Lee. Open Access This article is licensed under a Creative Commons Attribution 4. Reprints and permissions. HOMA-estimated insulin resistance as an independent prognostic factor in patients with acute pancreatitis. Sci Rep 9 , Download citation.

Received : 05 November Accepted : 01 October Published : 17 October Sign in here. Endocrine Journal. Online ISSN : Print ISSN : ISSN-L : Journal home Advance online publication All issues Featured articles About the journal.

Relation between HOMA-IR and insulin sensitivity index determined by hyperinsulinemic-euglycemic clamp analysis during treatment with a sodium-glucose cotransporter 2 inhibitor.

Corresponding author. Keywords: Homeostasis model assessment—insulin resistance HOMA-IR , Sodium-glucose cotransporter 2 SGLT2 inhibitor , Hyperinsulinemic-euglycemic clamp , Insulin sensitivity , Insulin resistance.

JOURNAL FREE ACCESS FULL-TEXT HTML. Published: Received: September 27, Released on J-STAGE: May 28, Accepted: December 27, Advance online publication: February 06, Revised: -. Full-text HTML Download PDF K Download citation RIS compatible with EndNote, Reference Manager, ProCite, RefWorks.

Grande-Villoria, A. Molina, B. Pozo, G. Torres; C. Fernández-Andrade; F. Vidaur, J. Manrique, M. Rodríguez; F. Caravaca, B. Cancho; A. Otero, L. González; A. Sánchez Casajús; F. García, M. San-Boixedau, K. López, E. Rubio, C. Bernis; M. Gironés; J. Asín; J. Hernández-Jaras, A. Rius, M. Instituto de Investigación Sanitaria de Santiago IDIS , Santiago de, Compostela, Spain.

Nephrology Department, C. de Ourense, Ourense, Spain. Clinical Epidemiology Unit, Puerta de Hierro University Hospital, Madrid, Spain.

Nephrology Department, Hospital Marques de Valdecilla, Santander, Spain. You can also search for this author in PubMed Google Scholar. Correspondence to Pilar Gayoso-Diz. PG conceived of the study, and participated in its design and coordination and helped to draft the manuscript. AO participated in the design of the study, have made substantial contributions to acquisition of data and helped to draft the manuscript MXRA performed the statistical analysis and helped to draft the manuscript.

FGu, FGa, AF and AG participated in the analysis and interpretation of data and helped to draft the manuscript.

All authors read and approved the final manuscript. This article is published under license to BioMed Central Ltd. Reprints and permissions. Gayoso-Diz, P. et al. Insulin resistance HOMA-IR cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study.

BMC Endocr Disord 13 , 47 Download citation. Received : 22 February Accepted : 18 September Published : 16 October Anyone you share the following link with will be able to read this content:.

Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all BMC articles Search. Download PDF. Abstract Background Insulin resistance has been associated with metabolic and hemodynamic alterations and higher cardio metabolic risk.

Methods It included adults range 20—92 years, Results In Spanish population the threshold value of HOMA-IR drops from 3. Conclusions The consideration of the cardio metabolic risk to establish the cut-off points of HOMA-IR, to define insulin resistance instead of using a percentile of the population distribution, would increase its clinical utility in identifying those patients in whom the presence of multiple metabolic risk factors imparts an increased metabolic and cardiovascular risk.

Background Insulin resistance IR is a feature of disorders such as diabetes mellitus type 2 DM2 and is also implicated in obesity, hypertension, cancer or autoimmune diseases [ 1 — 3 ]. Table 1 Summary of reports sorted by sample size on HOMA-IR cut-off in different populations Full size table.

Methods Setting The present study was a secondary analysis of data from a survey of the Spanish general adult population EPIRCE [ 25 , 26 ]. Definition of metabolic syndrome As an accurate indicator of cardio metabolic risk, MetS, both by the International Diabetes Federation IDF criteria and by the Adult Treatment Panel III ATP III criteria, were used.

Statistical analyses Baseline subject characteristics are expressed as the mean ± SD or as percentages. Ethical considerations The Galician Ethical Committee for Clinical Research approved the study protocol. Results Table 2 summarizes anthropometric, clinical, and biochemical characteristics of the study sample.

Figure 1. Full size image. Table 3 Performance of HOMA-IR values in the classification of cardio metabolic risk both ATPIII MetS and IDF MetS definition , influence of age and gender Full size table.

Figure 2. Table 4 Gender distribution of HOMA-IR cut-off levels, with their corresponding sensitivity and specificity,for classify of IDF MetS and ATPIII MetS, in diabetic and non-diabetic individuals Full size table. Discussion Overall, in non-diabetic individuals the best HOMA-IR cut-off levels ranged from 1.

Conclusions We propose the addition of the components of MetS analysis as a criterion to establish the cut-off points of HOMA-IR to define IR instead of using a percentile of the population distribution. References Rader DJ: Effect of insulin resistance, dyslipidemia, and intra-abdominal adiposity on the development of cardiovascular disease and diabetes mellitus.

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Acknowledgements The coordinating investigators of EPIRCE Study group were: M. de Ourense, Ourense, Spain Alfonso Otero-González Clinical Epidemiology Unit, Puerta de Hierro University Hospital, Madrid, Spain Fernando García Nephrology Department, Hospital Marques de Valdecilla, Santander, Spain Angel De Francisco Authors Pilar Gayoso-Diz View author publications.

View author publications. Additional information Competing interests All authors declare that they have no competing interests. Rights and permissions This article is published under license to BioMed Central Ltd.

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REVIEW OF THE PUBLISHED USE OF THE HOMA MODEL Table 4 Gender distribution of HOMA-IR cut-off levels, with their corresponding sensitivity and specificity,for classify of IDF MetS and ATPIII MetS, in diabetic and non-diabetic individuals Full size table. As a well-known fact, type 2 DM develops as a result of IR and is associated with metabolic abnormalities 4. Download citation. Diabetes Care 24 : — Karakelides, H. Resources ADA Professional Membership ADA Member Directory Diabetes. Only in model 3b a one-unit increase of SD of HOMA-B was associated with a reduction in the risk of iIFG incidence.
What do we learn from measurements of HOMA-IR?

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Scand J Clin Lab Invest. Download references. We express our thanks to the participants of District 13 of Tehran for their enthusiastic support in this study.

Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, , Iran. Department of Biostatistics and Epidemiology, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. You can also search for this author in PubMed Google Scholar. DK and AH raised the presented idea and designed the study. NSA, KK and MH conducted the analyses.

Enzo Bonora, Endocrinologia e Malattie del Metabolismo, Ospedale Maggiore, Piazzale Stefani, 1, I Verona, Italy. E-mail: enbonor tin. A table elsewhere in this issue shows conventional and Système International SI units and conversion factors for many substances.

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RESEARCH DESIGN AND METHODS. Article Information. Article Navigation. HOMA-Estimated Insulin Resistance Is an Independent Predictor of Cardiovascular Disease in Type 2 Diabetic Subjects : Prospective data from the Verona Diabetes Complications Study Enzo Bonora, MD, PHD ; Enzo Bonora, MD, PHD.

From the Endocrinology and Metabolic Diseases, University of Verona Medical School, Verona, Italy. This Site. Google Scholar. Gianni Formentini, MD ; Gianni Formentini, MD. Francesco Calcaterra, MD ; Francesco Calcaterra, MD. Simonetta Lombardi, MD ; Simonetta Lombardi, MD.

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Riccardo Bonadonna, MD ; Riccardo Bonadonna, MD. Michele Muggeo, MD Michele Muggeo, MD. Diabetes Care ;25 7 — Get Permissions. toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest. Table 1— Baseline main clinical and biochemical features of type 2 diabetic patients from the Verona Diabetes Complications Study.

Evaluated at baseline. Reevaluated at follow-up. Reevaluated non- insulin-treated; complete data. View Large. Table 2— Independent predictors of cardiovascular disease aggregate end point in type 2 diabetic patients from the Verona Diabetes Complications Study.

P value. Sex, duration, BMI, hypertension, and HbA 1c did not enter the equation. We thank Federica Moschetta and Monica Zardini for their skillful technical assistance.

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In addressing the somewhat dichotomous finding of lower plasma glucose and insulin concentrations, without any change in insulin sensitivity, the authors raised the possibility that the salsalate-induced changes may have resulted from an effect on basal hepatic glucose production.

These are important issues to be discussed subsequently. The manuscript in Diabetes Care by Pisprasert and colleagues [ 2 ] demonstrates that surrogate estimates of insulin sensitivity can lead to conclusions that are totally different from those based on the results of euglycaemic—hyperinsulinaemic clamp measurements.

More specifically, in their studies of non-diabetic individuals they demonstrated that African-Americans were more insulin resistant than Americans of European descent as assessed by a number of surrogate estimates of insulin action. Several such estimates were used, including some based on fasting plasma glucose and insulin concentrations HOMA-IR [ 3 ] and QUICKI [ 4 ] , and others using insulin and glucose concentrations resulting from an OGTT Matsuda index [ 5 ] and Stumvoll index [ 6 ].

The result of all of these surrogate estimates was that African-Americans are more insulin resistant than European-Americans. However, when a euglycaemic—hyperinsulinaemic clamp was performed, no difference in insulin-mediated glucose disposal could be discerned.

They also pointed out that in their experimental cohort none of these surrogate estimates of insulin sensitivity was superior to simple measurement of fasting plasma insulin concentrations in predicting insulin sensitivity.

Finally, in their discussion of differences between insulin sensitivity measured with the clamp and surrogate estimates, they also addressed the distinction between peripheral as opposed to hepatic insulin resistance. If HOMA-IR does not measure insulin-mediated glucose disposal as does the clamp, what does it measure?

Perhaps the best way to begin is by pointing out that the clamp provides a measure of total body insulin sensitivity: the ability of insulin to stimulate glucose uptake by muscle and inhibit hepatic glucose output. However, as pointed out by Pisprasert and associates [ 2 ], in non-diabetic individuals, the degree of hyperinsulinaemia attained during the clamp study is assumed to be high enough to completely inhibit hepatic glucose production.

Thus, in this situation, the clamp technique provides a measure of peripheral insulin action. The fact that HOMA-IR does not provide a very precise estimate of peripheral insulin action seems to have led to the notion that it must be a measure of the ability of insulin to inhibit hepatic glucose production in the fasting state.

However, there is no a priori reason to accept this point of view. There are isotopic techniques for measuring hepatic glucose production, and it is possible to conduct experiments to quantify the ability of varying amounts of insulin to inhibit hepatic glucose production. Obviously, such experiments must be performed at a lower insulin concentration than is normally used in euglycaemic—hyperinsulinaemic clamp studies so as not to achieve total inhibition of hepatic glucose production in every participant.

To the best of my knowledge, no such studies have been performed to define the degree of correlation between calculation of HOMA-IR and direct measurement of insulin inhibition of hepatic glucose production. Until that has been accomplished, it seems to me that considerable caution should be exercised in using HOMA-IR as an accurate measure of total body, peripheral or hepatic insulin resistance.

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Abbreviations

The positive effect of a high level of PA lingered even when the level of activity decreased over time. In addition, PA level might slow the progression of IR among populations without underlying IR, independent of the waist circumference and BMI status.

Increasing the level of PA or maintaining HEPA can slow the progression of IR and improve IR. Our findings support the beneficial effect of PA on IR, which is associated with type 2 DM, hypertension, and dyslipidemia 5.

The Kangbuk Samsung Health Study KSHS data were used in the study. The KSHS is an ongoing cohort study conducted in a Korean population aged 18 years and older who underwent comprehensive health examinations at one of the two total healthcare centers of Kangbuk Samsung Hospital in Seoul and Suwon, South Korea.

In South Korea, all employees are required to undergo annual or biennial health screening examinations in accordance with the Industrial Safety and Health Law. The remaining participants underwent medical checkups of their own accord.

In the KSHS, , individuals who underwent a comprehensive health examination at least twice between and were initially included. Overall, , participants were included in the final analysis Fig.

This study was approved by the Institutional Review Board IRB of Kangbuk Samsung Hospital IRB no: Informed consent was waived by the IRB of Kangbuk Samsung Hospital because anonymized and de-identified data were used in the analysis.

All study methods were conducted in accordance with relevant guidelines and regulations. During health screening, the self-administered questionnaires were used to collect the demographic data, medical history, socioeconomic history including smoking status and alcohol intake, educational background, and level of PA.

The National Health Interview Survey criteria were used to define the smoking status. Current smokers were defined as those who smoked more than 5 packs more than cigarettes in their lifetime and currently smoking at the time of the interview. A former smoker was defined as a person who had smoked more than cigarettes in their lifetime but who had quit smoking at the time of the interview The self-administered form of the Korean version of the International Physical Activity Questionnaire IPAQ was used to validate the PA levels In the questionnaire, participants were instructed to record the frequency and duration of PA over the past 7 days.

PAs that lasted more than 10 min were included in the count. Strength exercises such as push-ups were counted separately based on the number of times per week. The participants were classified into three categories: sedentary, mild PA metabolic equivalent of task [MET]-minutes per week , and health-enhancing PA 3, MET-minutes per week Anthropometric measurements height, weight, systolic blood pressure, and diastolic blood pressure were performed by trained medical staff.

Blood pressure BP was measured after a period of rest in a sitting position. During the BP measurement, the arm was positioned at the heart level, and an automated oscillometric device 53,, Welch Allyn, New York, USA was used.

The blood samples were analyzed by the Laboratory Medicine Department at Kangbuk Samsung Hospital, which has been accredited by the Korean Association of Quality Assurance for Clinical Laboratories and the Korean Society of Laboratory Medicine.

The HOMA-IR value of 2. All statistical analyses were conducted using STATA version Analysis of variance or Kruskal—Wallis test was used to compare multiple groups.

The HOMA-IR with a right-skewed distribution was logarithmically transformed. A generalized mixed model with random effects of individual and error was performed to assess the longitudinal associations between HOMA-IR and PA category.

A parametric proportional hazard model, including waist circumference as a time-varying covariate, was additionally implemented as a time-dependent model. For the time-varying covariate waist circumference and HOMA-IR level, all the data during the follow-up period were used for the analysis.

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Informed consent was obtained from all participants in the present study, and the study including clamp protocol was approved by the local Ethics Committee. Oral hypoglycemic agents were taken until the day before the clamp study. After a h overnight fast, a fasting blood sample was taken for the determination of FPG and FIRI levels.

QUICKI was calculated from FPG and FIRI levels according to the report by Katz et al. The HOMA-IR was calculated from FPG and FIRI according to the report by Matthews et al. The reciprocal index of HOMA-IR was also calculated.

Clamp study was performed according to the method of DeFronzo et al. Blood glucose levels were determined every 5 min during the min clamp study, and euglycemia 5.

The mean coefficient of variance of blood glucose in maintaining euglycemia was 1. The total-body glucose disposal rate was evaluated as the mean of the glucose infusion rate during the last 30 min of the clamp. The insulin sensitivity index Clamp-IR derived from the clamp study was calculated by dividing the mean glucose infusion rate by the plasma insulin level during the steady-state level during the last 30 min of the clamp and multiplying by All values are means ± sd , unless otherwise indicated.

Statistical analysis was performed by the Stat View 5 system SAS Institute Inc. Table 1 shows clinical characteristics of all type 2 diabetic subjects. There were no significant differences in gender, age, duration of diabetes, systolic and diastolic blood pressure, body mass index, FIRI, triglyceride, high-density lipoprotein-cholesterol, or free fatty acid level among the three groups.

The means of hemoglobin A1c were significantly higher in T2 and T3 than in T1, and the means of serum creatinine were significantly lower in T3 than in T1. All values are presented as n, or mean ± sd.

QUICKI was significantly lower in T3 than in T1 and HOMA-IR was significantly higher in T3 than in T1. Correlation between Clamp IR and QUICKI A or reciprocal index of HOMA-IR B.

Correlation coefficients of surrogate insulin resistance indexes with Clamp-IR determined by simple linear regression analyses.

All values are correlation coefficients r values determined by simple linear regression analysis with level of significance:. In the present study, we demonstrated no effects of FPG on correlation coefficients between QUICKI, the reciprocal index of HOMA-IR and Clamp-IR in type 2 diabetic patients, at least with maximum range of FPG, approximately These results indicated that QUICKI and the reciprocal index of HOMA-IR were useful surrogate indexes of insulin resistance in type 2 diabetic patients with wide range of fasting levels of plasma glucose.

Matthews et al. We also previously showed the validity of HOMA-IR in 80 type 2 diabetic patients in which their mean FPG was 7. In each of the two studies, plasma glucose levels were relatively well controlled, and the subjects with marked fasting hyperglycemia were not included.

In , Katz et al. Additionally, Mather et al. In contrast, Katsuki et al. Impaired insulin secretion may affect the relation between hepatic i. HOMA-IR or QUICKI and peripheral i. Clamp-IR insulin resistance. In the present study, it is likely that the ability of insulin secretion was more preserved in our patients who have shorter duration of diabetes, although we did not directly evaluated insulin secretion of each subjects.

Thus, QUICKI or HOMA-IR may be suitable for estimating insulin resistance in type 2 diabetes with relatively high FPG, in case enough insulin secretion is preserved. In addition, differences in characteristics of study subjects or in clamp method may affect the correlation between surrogate indexes and Clamp-IR.

There were no reports that examined the validity of simple indexes of insulin resistance in various ranges of FPG, separately, except for the report by Ono et al. Our data demonstrated that QUICKI and the reciprocal index of HOMA-IR, a simpler and more convenient index than QUICKI, may be more preferable than HOMA-IR when estimating insulin resistance in subjects with higher fasting plasma glucose than in previous reports 9 , 19 , 20 , which indicate the possibility of more extensive application in clinical settings.

It should be kept in mind, however, that QUICKI, the reciprocal index of HOMA-IR, and HOMA-IR are not independent to each other because of their common origin i.

all of them consist of fasting levels of plasma glucose and insulin. We thank Junko Taneda for her skillful technical assistance and management of the database.

Reaven GM Banting lecture Role of insulin resistance in human disease. Diabetes 37 : — Google Scholar. Despres JP , Lamarche B , Mauriege P , Cantin B , Dagenais GR , Moorjani S , Lupien PJ Hyperinsulinemia as an independent risk factor for ischemic heart disease.

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Am J Med : — Matthews DR , Hosker JP , Rudenski AS , Naylor BA , Treacher DF , Turner RC Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28 : — Emoto M , Nishizawa Y , Maekawa K , Hiura Y , Kanda H , Kawagishi T , Shoji T , Okuno Y , Morii H Homeostasis model assessment as a clinical index of insulin resistance in type 2 diabetic patients treated with sulfonylureas.

Diabetes Care 22 : — Bonora E , Targher G , Alberiche M , Bonadonna RC , Saggiani F , Zenere MB , Monauni T , Muggeo M Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity.

Diabetes Care 23 : 57 — Yokoyama H , Emoto M , Fujiwara S , Motoyama K , Morioka T , Komatsu M , Tahara H , Shoji T , Okuno Y , Nishizawa Y Quantitative insulin sensitivity check index and the reciprocal index of homeostasis model assessment in normal range-weight and moderately obese type 2 diabetic patients.

Diabetes Care 26 : — Katz A , Nambi SS , Mather K , Baron AD , Follmann DA , Sullivan G , Quon MJ Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 85 : — DeFronzo RA , Tobin JD , Andres R Glucose clamp technique: a method for quantifying insulin secretion and resistance.

Am J Physiol : E — E The area under the curve AUC of HOMA-IR for predicting severe AP was 0. This value was not significantly different from the AUCs of other AP scoring systems such as CTSI, Ranson, and BISAP. Insulin resistance was the only independent factor for either ICU admission OR 5.

Our findings suggest that the HOMA-IR score is an independent prognostic factor in patients with acute pancreatitis. This finding indicates that insulin resistance is potentially involved in the mechanism for severe AP.

Acute pancreatitis AP is an acute inflammatory process in which the pancreatic injury may remain localized, spread to nearby tissues, or lead to systemic inflammation through activation of cytokine cascades.

The underlying pathophysiology behind the progression of local pancreatic injury to systemic inflammation has not been fully elucidated 1. Recent studies have demonstrated that metabolic abnormalities, such as diabetes, hypertriglyceridemia, morbid obesity, vitamin D deficiency and the apolipoprotein B to A-I ratio, are closely related to the severity and prognosis of AP 4 , 5 , 6 , 7 , 8.

In line with these findings, blood glucose level, which an indicator of ongoing metabolic dysfunction, is used as a criterion in several AP-severity scoring systems such as the Ranson score and the Glasgow-Imrie criteria. Insulin resistance is defined clinically in terms of the failure of insulin to maintain glucose homeostasis 9 and it plays an essential role in the pathogenesis of chronic metabolic disease 10 , 11 , There has been ample evidence indicating an association between insulin resistance and diabetes, dyslipidemia, and metabolic syndrome MS , all of which are well-known contributors to the development and severity of acute pancreatitis 4 , 13 , 14 , Since insulin resistance is a chronic, low-grade inflammatory status 16 , insulin resistance has been postulated to play a pathogenic role in other inflammatory diseases such as acute pancreatitis.

This hypothesis is supported by reports of pre-existing diabetes increasing the risk of AP development and progression to SAP, as well as the risk of local and systemic complications in AP 17 , However, although one study reported increased insulin resistance in patients with AP 19 , little is known regarding the association between insulin resistance and the severity of AP.

Therefore, the aim of this study was to investigate whether insulin resistance is associated with the prognosis of AP. In the present study, we assessed insulin resistance using the homeostatic model assessment of insulin resistance HOMA-IR , which is the most widely validated surrogate measure of general insulin resistance Table 1 shows the baseline characteristics of all patients.

A total of patients were enrolled with a mean age of The etiologies for AP included gallstones At the initial evaluation, 99 According to the Atlanta classification, The median Ranson, CTSI, and BISAP scores of the patients were 2, 2 and 1, respectively, and the median hospital stay for the patients was 5 days.

Among all patients, 34 In the initial laboratory findings, the mean CRP and procalcitonin levels of the patients were 4.

The mean TG level was The mean HbA1c was 6. More females were included in the IR group and the mean BMI was higher in the IR group. Additionally, the percentage of ICU admissions and mortality were higher in the IR group. We calculated the area under the curves AUCs of HOMA-IR, CTSI, Ranson, and BISAP scores for predicting severe AP using receiver operating characteristic analysis Table 3.

The AUC of HOMA-IR for predicting severe AP was 0. This value was not notable different from the AUCs of the other scoring systems Fig. We performed a logistic regression analysis to find risk factors predicting severe AP or ICU admission in patients with AP.

Receiver operator characteristic curve of various factors as predictors of severe acute pancreatitis. We demonstrated that insulin resistance assessed using HOMA-IR was significantly associated with AP severity and ICU admission.

We found that this significant association between insulin resistance and severe AP was independent of the presence of diabetes, the body mass index, and the levels of inflammation markers. We also demonstrated that the ability of insulin resistance to predict severe AP was as good as other traditional scoring systems for AP.

These findings indicate that insulin resistance might be critical to the pathogenesis of AP. An important part of the pathophysiology of AP is inflammation of the pancreatic adipose tissue MS is a chronic, low-grade inflammatory status characterized by high circulating levels of pro-inflammatory cytokines The inflammatory changes that accompany MS may intensify both the immune and non-immune responses that can trigger and exacerbate AP 21 , which has been confirmed in several investigations showing an increased incidence and severity of AP in patients with MS 13 , The associations among the various components of MS and IR are well documented 11 , and insulin resistance plays an important role in the development of MS 22 , However, little is known regarding the association between insulin resistance and the prognosis of AP.

Therefore, this study aimed to determine the relationship between insulin resistance and the severity of AP. Insulin resistance is defined as a clinical state of decreased sensitivity or responsiveness to insulin HOMA-IR has a strong linear correlation with glucose clamp estimates of IR and has been widely used in various prospective clinical trials and clinical research studies 25 , To date, there has been a single study demonstrating IR as a risk factor for post-endoscopic retrograde cholangiopancreatography ERCP pancreatitis HOMA-IR was an independent predictor of post-ERCP pancreatitis and was used as a considerable factor in predicting the risk of post-ERCP pancreatitis and in decreasing related morbidity However, the authors did not demonstrate an association between IR and the severity of the pancreatitis.

Our study illustrates several important and novel findings. First, more females were included in the IR group, and the mean TG and BMI level were higher, compared to the non-IR group. Hypertriglyceridemia is well known in the etiology of AP, and elevated serum TG is independently and proportionally correlated with persistent organ failure, regardless of etiology 5.

Also, obesity induces a low-grade pro-inflammatory state and is linked with the development of complications in cases of AP 6. The number of cases with severe AP according to the Atlanta classification was higher in the IR group.

Also, the number of ICU admissions and the mortality rate were higher in the IR group compared to the non-IR group.

Second, our ROC analysis found that for predicting severe AP, the AUC of HOMA-IR was not significantly different from that of other scoring systems. This implies that a simple measurement of serum chemistries at the clinical baseline may be able to reliably replace traditional prognostic indices that require multiple clinical measurements.

This result strongly supports the prognostic value of HOMA-IR in patients with AP and is also in line with the results of previous studies that failed to demonstrate an association between DM and the severity of AP 29 , Insulin resistance and hyperglycemia, which are hallmarks of DM, are important factors linked to the susceptibility of diabetics to AP The existence of links between IR and several pro-inflammatory molecules, such as nuclear factor kB 32 , tumor necrosis factor α 33 , amylin 34 , calcitonin gene-related peptide 35 , leptin 36 and interleukin-6 37 , has been postulated, and these molecules may play a critical role in the pathogenesis of AP in patients with IR.

Also, several in vitro studies found that insulin played a protective role against palmitoleic acid-induced AP in rat acinar cells by inhibiting cytosolic calcium overload response 38 , 39 and in L-arginine-induced AP rat models by protecting against oxidative stress as well as contributing to acinar cell regeneration Thus, impaired pancreatic β-cell responsiveness and decreases in circulating insulin caused by pancreatic acinar cell exposure to hyperglycemia, which results in oxidative stress, may play important roles in the susceptibility of diabetics to AP.

However, the exact mechanism of the association between IR, DM, and AP has not been fully elucidated. Further investigation into this question may explain the apparently conflicting results regarding a correlation between DM and the incidence and severity of AP presented in past studies.

This study has several limitations. First, the number of patients enrolled in this study was small, and this study was performed in a tertiary care center, which could have resulted in the disproportional inclusion of patients with a severe disease status.

Such selection bias might have overestimated the predictive value of HOMA-IR. Second, whether the patients had IR before the diagnosis of AP or IR was a result of AP could not be fully examined.

If the patients included in this study would have undergone serum sampling prior to the diagnosis of AP, a more complete explanation as to which is the cause and which is the result may have been available.

Third, we did not take into account changes in the HOMA-IR score during treatment, which could have varied according to the progression of AP. Despite these limitations, this study also has a number of strengths. This is the first prospective study investigating the predictive value of HOMA-IR in AP and suggesting HOMA-IR as a possible parameter in improving on previously established severity-scoring systems.

Replacing the blood glucose level with HOMA-IR in traditional prognostic scoring systems could improve their performance. HOMA-IR, a surrogate marker of insulin resistance, was the only independent prognostic factor for predicting either severe AP or ICU admission in patients with AP.

This finding suggests that insulin resistance might influence the risk of SAP irrespective of the cause of the pancreatitis. Therapy targeted at decreasing insulin resistance may have promising role in improving overall outcomes of SAP.

Further investigation is needed to confirm the possible deleterious effect of insulin resistance on AP prognosis and to investigate the underlying biological mechanisms for this association in greater detail. This was a prospective study of patients with AP in Yonsei University Wonju College of Medicine from March to April The study protocol was approved by the International Review Board for Human Research CR of Yonsei University Wonju College of Medicine.

This study was performed in accordance with relevant guidelines and regulations. Written informed consent was obtained from all patients.

An abdominal computed tomography CT scan was performed on all patients upon admission to differentiate AP from other diseases. Once AP was diagnosed, the levels of fasting insulin, glucose, and triglyceride TG were verified.

Additional scoring systems, such as the Ranson score, CT scoring index CTSI , and BISAP, were applied. The severity of AP was assessed according to the Atlanta criteria and classified as mild, moderately severe, or severe Mild AP was defined by the absence of organ failure OF and local or systemic complications.

Severe AP was defined as persistent OF. All statistical analyses were performed using SPSS software, version Categorical variables are presented as the frequency and percentage. Continuous variables are presented as either the mean ±standard deviation or median with range.

The paired t -test was used to compare continuous variables, and the chi-square test was used to compare categorical variables. The odds ratios ORs and confidence intervals CIs for having severe AP or an intensive care unit ICU admission were calculated using multivariable logistic regression analysis after adjustment for confounding variables.

Receiver operating characteristic curves were generated to assess the predictive ability of HOMA-IR for severe AP. The datasets analysed for this study are available from the corresponding author upon reasonable request. Oiva, J.

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HOMA-IR: A Test of Insulin Resistance + Ways to Decrease It

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PLoS ONE 11 , e—e Download references. The current research did not receive any grants from funding agencies in the public, commercial, or not-for-profit organizations.

Department of Medicine, MetroWest Medical Center, Lincoln St, Framingham, MA, , USA. Division of Cardiology, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul, , Republic of Korea.

You can also search for this author in PubMed Google Scholar. Y: Conceptualization, Methodology, Writing — original draft, and Writing — review and editing. O: Writing — original draft, Writing — review and editing.

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Skip to main content Thank you for visiting nature. nature scientific reports articles article. Download PDF. Subjects Biomarkers Endocrinology Health care. Abstract Only a few studies have evaluated the relationship between physical activity PA and Homeostatic model assessment for insulin resistance HOMA-IR.

Introduction Physical activity PA consists of movements using the skeletal muscles, which require the use of energy 1. Results Cohort description The median follow-up duration was 4.

Table 1 Baseline characteristics. Full size table. Table 2 Sex stratified associations of PA with HOMA-IR. Table 3 Sex-stratified associations of PA with HOMA-IR according to the changes in PA level. Table 4 Associations of PA with the change of HOMA-IR level.

Table 5 Associations of change in the PA with change in HOMA-IR. Discussion Our results showed that there was a significant inverse relationship between PA level and HOMA-IR, a marker of IR. Methods Study population The Kangbuk Samsung Health Study KSHS data were used in the study. Figure 1. Flow diagram for study participants.

Full size image. Data availability All data generated or analyzed during this study are included in this published article. References Singh, R. Article PubMed Google Scholar Warburton, D. Article PubMed Google Scholar Paffenbarger, R.

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Article CAS PubMed PubMed Central Google Scholar Download references. Acknowledgements We acknowledge the efforts of the health screening staff at Kangbuk Samsung Hospital, Korea.

Funding The current research did not receive any grants from funding agencies in the public, commercial, or not-for-profit organizations.

Author information Author notes These authors contributed equally: Tae Kyung Yoo and Byeong Kil Oh. View author publications. Ethics declarations Competing interests The authors declare no competing interests. Additional information Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions Open Access This article is licensed under a Creative Commons Attribution 4. About this article. Cite this article Yoo, T. Copy to clipboard. This article is cited by Leisure time physical activity: a protective factor against metabolic syndrome development Myong-Won Seo Youngseob Eum Hyun Chul Jung BMC Public Health Comments By submitting a comment you agree to abide by our Terms and Community Guidelines.

Insulin resistance has a key role in the pathogenesis of type 2 diabetes mellitus 1 1 D'Adamo E, Caprio S.

Treatment of type 2 diabetes in youth. Obesity and the metabolic syndrome in children and adolescents. N Engl J Med. Acute and chronic complications of type 2 diabetes mellitus in children and adolescents. Hence, a valid, practical, and accessible method of assessing insulin resistance in this age group must be developed to monitor its progression over time, to identify adolescents at risk of developing associated factors, and to establish strategies for preventing and mitigating the transition from normal glucose tolerance to impaired fasting glucose and type 2 diabetes mellitus.

Insulin resistance can be assessed in vivo by several methods. Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol. Clamp techniques in paediatrics: what have we learned? Horm Res. However, it is not applicable to large-scale epidemiological studies or clinical practice due to being a complex, invasive, expensive, and time-consuming method 8 8 Arslanian SA.

The homeostasis model assessment HOMA of insulin resistance IR is a surrogate marker that estimates insulin resistance based on basal measurements of plasma insulin and glucose 9 9 Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC.

Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

It has been widely validated and used in clinical and epidemiological studies of adult populations 10 10 Bonora E, Targher G, Alberiche M, Bonadonna RC, Saggiani F, Zenere MB, et al. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity.

The threshold value for insulin resistance HOMA-IR in an admixtured population IR in the Brazilian Metabolic Syndrome Study. Diabetes Res Clin Pract. The HOMA-IR has also been validated as a surrogate to the clamp technique as a measure of insulin resistance in adolescents 13 13 Uwaifo GI, Fallon EM, Chin J, Elberg J, Parikh SJ, Yanovski JA.

Indices of insulin action, disposal, and secretion derived from fasting samples and clamps in normal glucose-tolerant black and white children. Surrogate estimates of insulin sensitivity in obese youth along the spectrum of glucose tolerance from normal to prediabetes to diabetes.

J Clin Endocrinol Metab. However, to our knowledge, studies have not separately validated the HOMA-IR in pubertal and postpubertal adolescents. Cross-sectional and longitudinal studies have shown that a significant physiological change in insulin sensitivity occurs during the transition from late childhood throughout adolescence, with increased insulin resistance at the onset of puberty and subsequent normalization towards the end of pubertal development 18 18 Moran A, Jacobs DR Jr, Steinberger J, Hong CP, Prineas R, Luepker R, et al.

Insulin resistance during puberty: results from clamp studies in children. Longitudinal changes in insulin sensitivity, insulin secretion, and beta-cell function during puberty. J Pediatr. This study aimed to validate the HOMA-IR as a surrogate to the hyperglycemic clamp technique to measure insulin resistance in both pubertal and postpubertal adolescents; and determine the HOMA-IR cutoff values for detecting insulin resistance in both pubertal stages.

This study used data from the Brazilian Metabolic Syndrome Study BRAMS , a cross-sectional study conducted in the state of São Paulo, Brazil. The BRAMS studied the insulin resistance in an intentional non-probabilistic sample composed of adolescents aged from 10 to 19 years and 11 months.

Out of 1, enrolled participants in the BRAMS study, data from 80 adolescents aged years, 40 females who underwent the hyperglycemic clamp technique were analyzed. The adolescents were recruited from public schools and the University of Campinas Teaching Hospital. The following exclusion criteria were applied: prepubertal children due to the small sample size, pregnancy, use of either systemic corticosteroids or drugs with hypoglycemic properties, malnutrition, hepatopathy, nephropathy, metabolic disorders e.

Pubertal development was assessed by self-assessments 20 20 Duke PM, Litt IF, Gross RT. according to Tanner's criteria 21 21 Tanner JM. Growth at adolescence. Oxford: Blackwell Scientific Publications; The self-assessment method in the BRAMS study has been reported in detail elsewhere 22 22 da Silva CC, Vasques ACJ, Zambon MP, Camilo DF, De Bernardi Rodrigues AM, Antonio MÂRGM, et al.

Sagittal abdominal diameter resembles waist circumference as a surrogate marker of insulin resistance in adolescents-Brazilian Metabolic Syndrome Study. Pediatr Diabetes. Participants were divided into two groups: pubertal Tanner II-IV and postpubertal Tanner V. The body mass index BMI was calculated as weight kilograms divided by height in meters squared.

The BMI-for-age z- score was calculated using the Epi Info version 3. The nutritional status was defined using the Centers for Disease Control and Prevention criteria 23 23 Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, et al.

Vital Health Stat Waist circumference was measured at the midpoint between the lower margin of the last palpable rib and the top of the iliac crest 24 24 World Health Organization WHO. WHO STEPwise approach to surveillance STEPS : Section 3 — Guide to Physical Measurements Step 2.

Geneva: World Health Organization; Accessed in: January 10, The amount of lean body mass was determined using tetrapolar bioimpedance Biodynamics, model , Shoreline, Washington, USA 25 25 Lukaski HC, Bolonchuk WW, Hall CB, Siders WA. Validation of tetrapolar bioelectrical impedance method to assess human body composition.

J Appl Physiol Blood samples were collected after a hour overnight fast. Plasma glucose was measured by using enzymatic colorimetric method monoreagent K; Bioclin Systems II ® , Quisaba, Bioclin, Belo Horizonte, MG, Brazil. Insulin levels were analyzed by using a human insulin enzyme-linked immunosorbent assay kit EZHIK; Millipore; St.

Louis, Missouri, USA. The insulin sensitivity index ISI from the hyperglycemic clamp technique was calculated as the mean exogenous glucose infusion rate from 60 to minutes of the clamp technique minus the urinary glucose excretion, divided by the mean insulin concentration of five determinations during the same time period, and it was then corrected for lean body mass LBM ISI LBM ; milligrams of glucose infused per kilogram of lean body mass per minute, multiplied by 8 8 Arslanian SA.

Measuring β-cell function relative to insulin sensitivity in youth: does the hyperglycemic clamp suffice? The HOMA-IR index was calculated as the product of the fasting plasma insulin level in milliunits per liter and the fasting plasma glucose level in millimoles per liter , divided by The Shapiro-Wilk test was used to check the distribution of variables.

Data are reported as the mean ± standard deviation or median interquartile range. Relationship between two variables was evaluated with the Spearman's correlation coefficient. We used multivariable linear regression models to evaluate the associations between the HOMA-IR and the clamp-derived ISI independent variables, sex, age, and HOMA-IR in Model 1 and the variables in Model 1 plus waist circumference in Model 2.

Residuals were evaluated for normal distribution by the Shapiro-Wilk test. Preliminary prediction models demonstrated non-normality of the residuals and clamp-derived ISI was therefore transformed to the logarithmic scale.

The agreement between the predicted ISI and measured clamp-derived ISI LBM was evaluated by Bland-Altman plots 27 27 Bland JM, Altman DG. Statistical method for assessing agreement between two methods of clinical measurement. Metabolisable energy content in canine and feline foods is best predicted by the NRC equation.

PLoS One. The bias represents the mean difference between the two methods 29 29 Hirakata VN, Camey AS. Análise de concordância entre métodos de Bland-Altman.

Rev HCPA. For a method to be considered of good agreement, the mean differences should not different from zero 29 29 Hirakata VN, Camey AS. The area under the receiver-operating characteristic ROC curve AUC , sensitivity, specificity, positive predictive value, and negative predictive value were calculated to evaluate the accuracy of the HOMA-IR for detecting insulin resistance in both pubertal and postpubertal adolescents.

Index for rating diagnostic tests. Statistical analyses were performed using IBM SPSS Statistics for Windows, version Table 1 shows clinical, anthropometric, and biochemical data.

In the multivariable linear regression analysis, adjusted for sex and age, the HOMA-IR index was independently and negatively associated with the clamp-derived ISI in both the pubertal and postpubertal adolescents Table 2.

The HOMA-IR index remained negatively associated with the clamp-derived ISI, in both the pubertal and postpubertal adolescents, even after further adjustment for waist circumference Table 2.

The Bland-Altman plot shows a bias equal to zero Figure 1. The analysis of the ROC curves showed that the HOMA-IR index had a good discriminatory power for detecting insulin resistance in the pubertal AUC ± standard error [SE], 0.

This study of pubertal and postpubertal adolescents indicates that the HOMA-IR index is strongly related with the clamp-derived ISI in both pubertal stages. To our knowledge, this is the first study to explore the association between the HOMA-IR index and the clamp-derived ISI in these two pubertal stages separately.

We found that the HOMA-IR index was negatively associated with clamp-derived insulin sensitivity, even after adjustment for waist circumference, in both pubertal and postpubertal adolescents.

Additionally, Bland-Altman plots showed agreement between the predicted ISI and measured clamp-derived ISI LBM in both pubertal stages. Finally, we found that the HOMA-IR index was capable of accurately detecting insulin resistance in both pubertal and postpubertal adolescents.

Studies have compared the HOMA-IR index with clamp-derived measures in pediatric populations 13 13 Uwaifo GI, Fallon EM, Chin J, Elberg J, Parikh SJ, Yanovski JA. However, previous studies have not demonstrated whether the HOMA-IR is capable of separately estimating insulin resistance in pubertal and postpubertal adolescents.

Although Gungor and cols. Validation of surrogate estimates of insulin sensitivity and insulin secretion in children and adolescents.

reported correlations for pubertal adolescents, they defined pubertal adolescents as Tanner stages II to V. However, in our study, adolescents were considered as pubertal if they presented Tanner stages II-IV and postpubertal if they presented Tanner stage V.

We divided the adolescents into these two development stages based on the study by Moran and cols. The multivariable linear regression analysis showed that the results of the HOMA-IR were independently and negatively associated with insulin sensitivity results of the clamp technique in the pubertal and postpubertal adolescents.

These results indicate the validity of the HOMA-IR in explaining the insulin resistance results of the hyperglycemic clamp technique in both pubertal stages. Additionally, the analysis of the ROC curve revealed that the HOMA-IR index could accurately detecting insulin resistance in both pubertal and postpubertal adolescents.

Insulin resistance determined by Homeostasis Model Assessment HOMA and associations with metabolic syndrome among Chinese children and teenagers.

Diabetol Metab Syndr. These differences may be related to BMI differences, population age, although they are primarily related to the accuracy of the methodology used for determining the cutoff point hyperglycemic clamp versus oral glucose tolerance test 31 31 Keskin M, Kurtoglu S, Kendirci M, Atabek ME, Yazici.

or 95th percentile of the HOMA-IR 32 32 Yin J, Li M, Xu L, Wang Y, Cheng H, Zhao X, et al. A potential limitation of the current study is its cross-sectional design, which does not allow for inferences of causality.

Another limitation is the use of the hyperglycemic clamp technique to evaluate insulin resistance. Although the hyperglycemic clamp technique is not the gold standard for estimating insulin resistance, studies comparing this technique with the euglycemic-hyperinsulinemic clamp technique gold standard for quantifying insulin resistance reported an excellent correlation between both clamp techniques in children and adolescents 14 14 Gungor N, Saad R, Janosky J, Arslanian S.

Hyperglycemic clamp: A single experiment to simultaneously assess insulin secretion and insulin sensitivity in children [dagger] Pediatr Res. The evaluation of sexual maturation was performed via self-assessments 20 20 Duke PM, Litt IF, Gross RT.

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3 Insulin Resistance Testing Options (Includes HOMA-IR Tutorial) The present study Insulin sensitivity and HOMA-IR to validate homeostasis swnsitivity assessment of insulin resistance Sensutivity in relation to the insulin tolerance test Sensitiity in a Holistic mental wellness of insulin-resistance in Aand rats induced by a week Inzulin diet. ITT was determined at baseline and in the 19 th week. HOMA-IR was determined between the th week in three different days and the mean was considered for analysis. Area under the curve AUC-ITT of the blood glucose excursion along minutes after intra-peritoneal insulin injection was determined and correlated with the corresponding fasting values for HOMA-IR. ROC curves of HOMA-IR and AUC-ITT showed similar sensitivity and specificity.

Author: Galabar

5 thoughts on “Insulin sensitivity and HOMA-IR

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