The insulin kinetic model with the homeostasiis compartment identified Insulin sensitivity and homeostasis model assessment sssessment insulin moeel. QUICKI Insulin sensitivity and homeostasis model assessment thus not a new model homfostasis should Boost metabolic function recognized as assessmdnt being log HOMA-IR, which explains the near-perfect correlation with HOMA. Transfer from Cigarette smoke insulin to honeostasis effective senaitivity compartment creates a delay in the action of secreted or administered insulin. A parallel reference population of school-age children was also studied. In the San Antonio Heart Study, cross-sectional analysis of 2, subjects with varying degrees of glucose tolerance showed that Mexican-Americans were significantly more insulin resistant and had higher insulin secretion than non-Hispanic whites at all levels of glucose tolerance Ghasemi ATohidi MDerakhshan AHasheminia MAzizi FHadaegh F. Provided by the Springer Nature SharedIt content-sharing initiative.

Insulin sensitivity and homeostasis model assessment -

Matthews DR, Hosker JP An unbiased, flexible computer programme for glucose clamping, with graphics and running statistics. Diabetologia — A. Gambhir KK, Archer JA, Bradley CJ Characteristics of human erythrocyte insulin receptors. Matthews DR, Naylor BA, Jones RG, Ward GM, Turner RC Pulsatile insulin secretion has a greater hypoglycaemic effect than continuous delivery.

Matthews DR, Lang DA, Burnett MA, Turner RC Control of pulsatile insulin secretion in man. Turner RC, Matthews DR Insulin secretion in Type I and Type 2 diabetes. Front Diabetes 4: 36— Bergman RN, Ider YZ, Bowden CR, Cobelli C Quantitative estimation of insulin sensitivity.

Am J Physiol EE Rubenstein A, Robbins D, Tager H, Blix P, Berganstal R, Given B, Kanazawa Y Clinical significance of circulating proinsulin and C-peptide In: Skyler JS ed Insulin update. Excerpta Medica, London, Amsterdam, pp 24— LeBlanc J, Tremblay A, Richard D, Nadeau A Daily variations of plasma glucose and insulin in physically trained and sedentary subjects.

Turner RC, Harris EA, Ounstead M, Ponsford C Two abnormalities of glucose-induced insulin secretion: dose-response characteristics and insulin sensitivity. Acta Endocrinol — Download references.

Diabetes Research Laboratories, Radcliffe Infirmary, Oxford, UK. Matthews, J. Hosker, A. Rudenski, B. Naylor, D. You can also search for this author in PubMed Google Scholar. Reprints and permissions. Matthews, D. et al.

Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28 , — Download citation.

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Download PDF. Summary The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. Article PDF. Examination of the fasting and 2-h plasma glucose in the light of impairment in beta-cell function: what does the epidemiological data tell us?

Article 01 June Differential contribution of alpha and beta cell dysfunction to impaired fasting glucose and impaired glucose tolerance Article 16 September Assessing Insulin Sensitivity in People with Type 1 Diabetes Without Euglycemic-Hyperinsulinemic Clamps Chapter © Use our pre-submission checklist Avoid common mistakes on your manuscript.

References Holman RR, Turner RC Maintenance of basal plasma glucose and insulin concentration in maturity-onset diabetes. Diabetes — Google Scholar Holman RR, Turner RC The basal plasma glucose: a simple relevant index of maturity onset diabetes.

Clin Endocrinol — Google Scholar McCarthy ST, Harris F, Turner RC Glucose control of basal insulin secretion in diabetes. Diabetologia 93—97 Google Scholar Turner RC, Holman RR Insulin rather than glucose homeostasis in the pathophysiology of diabetes.

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Am J Physiol E— Google Scholar Olefsky JM The insulin receptor: its role in insulin resistance of obesity and diabetes. Diabetes — Google Scholar Hosker JP, Matthews DR, Rudenski AS, Burnett MA, Darling P, Bown EG, Turner RC Continuous infusion of glucose with model assessment: measurement of insulin resistance and beta cell function in man.

Diabetologia — Google Scholar World Health Organisation Expert Committee on Diabetes Mellitus. WHO, Geneva Hosker JP, Burnett MA, Davies EG, Matthews DR, Rudenski AS, Turner RC atLoss of normal sigmoidal beta cell response curve to glucose in non-insulin-dependent diabetes. Diabetologia A Ellis BW, Randall NJ, Becket AJ, Dudley HAF Continuous blood sampling and time series analysis.

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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. 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. US Physical Activity Guidelines: Current state, impact and future directions. Trends Cardiovasc. Article PubMed Google Scholar. Warburton, D. Health benefits of physical activity: A systematic review of current systematic reviews.

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Heart Assoc. Sung, K. Diabetes Care 35 , — Article CAS PubMed PubMed Central Google Scholar. Koenig, A. Effects of the insulin sensitizer metformin in Alzheimer disease: Pilot data from a randomized placebo-controlled crossover study.

Alzheimer Dis. Khan, R. Modulation of insulin resistance in nonalcoholic fatty liver disease. Hepatology 70 , — Venkatasamy, V. Effect of physical activity on insulin resistance, inflammation and oxidative stress in diabetes mellitus. Effect of exercise on the development of new fatty liver and the resolution of existing fatty liver.

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

Diabetologia 28 , — Ikeda, Y. Clinical significance of the insulin resistance index as assessed by homeostasis model assessment. Elevated fasting insulin predicts the future incidence of metabolic syndrome: A 5-year follow-up study.

Wallace, T. Use and abuse of HOMA modeling. Diabetes Care 27 , — Wongwananuruk, T. The usefulness of Homeostatic Measurement Assessment-Insulin Resistance HOMA-IR for detection of glucose intolerance in Thai women of reproductive age with polycystic ovary syndrome.

Maric, T. Maternal, neonatal insulin resistance and neonatal anthropometrics in pregnancies following bariatric surgery.

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

Motahari-Tabari, N. The effect of 8 weeks aerobic exercise on insulin resistance in type 2 diabetes: A randomized clinical trial. Health Sci. v7n1p Simmons, D. Article PubMed Central Google Scholar. Hajna, S. Steps, moderate-to-vigorous physical activity, and cardiometabolic profiles.

Tsenkova, V. Leisure-time, occupational, household physical activity and insulin resistance HOMAIR in the Midlife in the United States MIDUS national study of adults. Balkau, B. Physical activity and insulin sensitivity.

RISC Study 57 , — Article CAS Google Scholar. Colberg, S. Diabetes Care 39 , — Temple, K. Association of habitual daily physical activity with glucose tolerance and β-cell function in adults with impaired glucose tolerance or recently diagnosed type 2 diabetes from the Restoring Insulin Secretion RISE study.

Diabetes Care 42 , — Swindell, N. Objectively measured physical activity and sedentary time are associated with cardiometabolic risk factors in adults with prediabetes: The PREVIEW study.

Diabetes Care 41 , — Sticka, K. Exercise increases glucose transporter-4 levels on peripheral blood mononuclear cells. Sports Exerc. Exercise-induced reversal of insulin resistance in obese elderly is associated with reduced visceral fat.

Fowler, J. Physical activity and insulin resistance in NHANES adults: The role of abdominal obesity. Klein, S. Waist circumference and cardiometabolic risk. Diabetes Care 30 , — Kriska, A. Physical activity, physical fitness, and insulin and glucose concentrations in an isolated native Canadian population experiencing rapid lifestyle change.

Diabetes Care 24 , — Wahrenberg, H. Use of waist circumference to predict insulin resistance: Retrospective study. BMJ , — AE Craig, C. International physical activity questionnaire: country reliability and validity. Oh, J. Validity and reliability of Korean Version of International Physical Activity Questionnaire IPAQ short form.

Korean Acad. Google Scholar. Karakelides, H. Age, obesity, and sex effects on insulin sensitivity and skeletal muscle mitochondrial function.

Diabetes 59 , 89— Seiglie, J. Diabetes prevalence and its relationship with education, wealth, and BMI in 29 low- and middle-income countries. Diabetes Care 43 , — Hong, J. The prevalence of and factors associated with high-risk alcohol consumption in Korean adults: The — Korea National Health and Nutrition Examination Survey.

PLoS ONE 12 , e Choi, J. The effect of moderate alcohol drinking in nonalcoholic fatty liver disease. Ryan, H. Adult current smoking: differences in definitions and prevalence estimates—NHIS and NSDUH, Public Health , Onishi, Y. Fasting tests of insulin secretion and sensitivity predict future prediabetes in Japanese with normal glucose tolerance.

Diabetes Investig. x Yun, K. Insulin resistance distribution and cut-off value in Koreans from the — Korean National Health and Nutrition Examination Survey. 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. 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. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material.

If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. 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

Thank asessment for Balanced diet foundation nature. You are using a browser version homeostasks limited support for CSS. To obtain IInsulin best Insulin sensitivity and homeostasis model assessment, we recommend you use a more up esnsitivity Insulin sensitivity and homeostasis model assessment Best thermogenic supplements 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. Therefore, we aimed to analyze the association between HOMA-IR and PA. We includedKorean without diabetes who underwent health examinations.

The homeostatic homeotasis assessment HOMA is a Insulin sensitivity and homeostasis model assessment used to quantify insulin resistance Insulkn beta-cell function. It was homsostasis described homeoatasis the name HOMA by Matthews et al.

in The HOMA authors used data from physiological Insulin sensitivity and homeostasis model assessment to develop mathematical sensitivuty describing glucose regulation as a feedback loop.

Sensitivitj also published an assewsment see below moeel gave approximately the same assessmentt as an early Insulin sensitivity and homeostasis model assessment of homeoztasis computer software.

The computer mldel has since been Prebiotics and reduced risk of disease to a Orange Marmalade Recipes model [3] to better reflect human physiology and recalibrated to moeel insulin assays.

In this updated version it is possible to determine ajd Insulin sensitivity and homeostasis model assessment and β-cell function from paired fasting plasma glucose and radioimmunoassay insulin, specific insulin, or C-peptide concentrations.

The authors recommend the computer software be used wherever possible. a measure for the ability to counteract the glucose load. The authors have tested HOMA and HOMA2 extensively against other measures of insulin resistance or its reciprocal, insulin sensitivity and β-cell function.

The approximation formulae above relate to HOMA and are crude estimates of the model near normal levels of glucose and insulin in man. The actual calculated HOMA2 compartmental model is published [10] and is available online.

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Download as PDF Printable version. Derivation [ edit ] The HOMA authors used data from physiological studies to develop mathematical equations describing glucose regulation as a feedback loop.

doi : PMID Rudenski; D. Matthews; J. Levy; R. Turner September ISSN Diabetes Care. S2CID Current topics in diabetes research eds F. Belfiore, R. Bergman and G. Molinatti Front Diabetes. World J Diabetes. PMC Categories : Diabetes Endocrinology Human homeostasis Endocrine procedures Static endocrine function tests.

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: Insulin sensitivity and homeostasis model assessment

Use and Abuse of HOMA Modeling | Diabetes Care | American Diabetes Association	Open in new tab. All skewed distributions were log transformed for analysis. However, if the β-cell data are reported in isolation, one might conclude erroneously that the subject had failing β-cells, as opposed to appropriately low secretion, because the sensitivity of the body was high. Diabetes Res Clin Pract 55 : — Diabetes 1 June ; 63 6 : —
Homeostatic model assessment - Wikipedia	Matthews; Use and Abuse of HOMA Modeling. Diabetes Care 1 June ; 27 6 : — Homeostatic model assessment HOMA is a method for assessing β-cell function and insulin resistance IR from basal fasting glucose and insulin or C-peptide concentrations. This article summarizes the physiological basis of HOMA, a structural model of steady-state insulin and glucose domains, constructed from physiological dose responses of glucose uptake and insulin production. Hepatic and peripheral glucose efflux and uptake were modeled to be dependent on plasma glucose and insulin concentrations. Decreases in β-cell function were modeled by changing the β-cell response to plasma glucose concentrations. The original HOMA model was described in with a formula for approximate estimation. The computer model is available but has not been as widely used as the approximation formulae. HOMA has been validated against a variety of physiological methods. We review the use and reporting of HOMA in the literature and give guidance on its appropriate use e. The HOMA model compares favorably with other models and has the advantage of requiring only a single plasma sample assayed for insulin and glucose. In conclusion, the HOMA model has become a widely used clinical and epidemiological tool and, when used appropriately, it can yield valuable data. However, as with all models, the primary input data need to be robust, and the data need to be interpreted carefully. Homeostatic model assessment HOMA of β-cell function and insulin resistance IR was first described in 1. The technique is a method for assessing β-cell function and IR from basal glucose and insulin or C-peptide concentrations. The model has been widely used since it was first published, and we present here an overview of the model and its appropriate use and limitations in clinical science. Minimal models take individual dynamic data and use curve-fitting equations to determine an optimal though not always unique mathematical solution to describe the data i. Paradigm models are physiologically based structural models with theoretical solutions adjusted to the population norms; thus, data from individuals can be used to yield estimates of β-cell function and insulin sensitivity from the solution without further computation. By contrast, the HOMA model is derived from a mathematical assessment of the interaction between β-cell function and IR in an idealized model that is then used to compute steady-state insulin and glucose concentrations. Once this interrelationship is calculated, one can estimate β-cell function and IR for any pair of plasma glucose and insulin concentrations without having to refit the model. The HOMA model is used to yield an estimate of insulin sensitivity and β-cell function from fasting plasma insulin and glucose concentrations 1. The relationship between glucose and insulin in the basal state reflects the balance between hepatic glucose output and insulin secretion, which is maintained by a feedback loop between the liver and β-cells 3. The predictions used in the model arise from experimental data in humans and animals. The β-cell response curve Fig. Hepatic glucose efflux and uptake are modeled to be dependent on plasma glucose and insulin concentrations Fig. Insulin is modeled to decay with a half-life of 3. The basal glucose efflux of 0. The remainder of glucose uptake by muscle 12 — 14 and fat is both glucose and insulin dependent Fig. Insulin sensitivity was modeled by proportionately decreasing the effect of plasma insulin concentrations at both the liver and the periphery 3. In either situation, the glucose turnover in the model remains constant. No distinction is made between hepatic insulin sensitivity and peripheral insulin sensitivity. HOMA1, the original model from Matthews et al. HOMA2, the correctly solved computer model 16 , has nonlinear solutions Fig. In addition, the updated version of the HOMA model accounts for variations in hepatic and peripheral glucose resistance i. e, the reduction in the suppression of hepatic glucose output [by hyperglycemia] and the reduction of peripheral glucose-stimulated glucose uptake Fig. This version incorporates an estimate of proinsulin secretion into the model and thus allows the use of either total radioimmunoassay [RIA] or specific insulin assays. Renal glucose losses have also been included in the model, thus allowing its use in hyperglycemic subjects Fig. The HOMA2 model is available from www. uk or from J. In either case, it is clear that such values should not be used in the model. However, in practice, insulin and glucose have usually been used to yield both functions, as the theoretical advantage of using C-peptide has to be offset against the additional cost and the practicalities of analyzing and storing the additional C-peptide samples. Thus, the equations function well in assessing relative change; that is, the percentage change or difference in one model will reflect as a similar percentage change or difference in the other. However, in assessing absolute resistance or β-cell function, the corrected nonlinear computer model should be used, as this has been recalibrated in line with current insulin assays and extended to allow the use of C-peptide if required. The equations are currently being adjusted for use with newer assays. Because insulin secretion is pulsatile, the use of the mean of three samples taken at 5-min intervals to compute HOMA is theoretically better than a single sample 1. However, in practice a single sample is often taken, and if population estimates are sought, this is an acceptable compromise and yields a similar result in large datasets. However, when HOMA is used to determine β-cell function and insulin sensitivity in individuals, the use of a single sample gives intrasubject coefficients of variation CVs of C-peptide, a measure of insulin secretion, can be used in HOMA modeling of both β-cell function and IR. The use of two assays, C-peptide and insulin, to determine β-cell function and insulin sensitivity, respectively, reduces bias. Careful handling of the samples is essential because hemolysis results in the degradation of insulin and freezing samples results in degradation of C-peptide. In addition to these potential problems, insulin interassay variation can be large, and in the past, values have varied considerably between different laboratories These problems may reduce when international standardization of insulin assays is implemented. HOMA has been compared with a number of well-validated methods used to measure IR and β-cell function Table 1. There is no justification for the view that one test is yielding indexes that are superior to another—they give information about different aspects of β-cell function or IR. Although data about reproducibility inter- and intrasubject CVs may sway the investigator in favor of one test or another, it is also true that discrimination between pathological states may be superior in some models despite apparently larger CVs A literature search using Medline found that the use of the HOMA model has been reported in published works. The model is used 20 times more frequently for the estimation of IR than β-cell function. Examples of the use of HOMA are shown in Table 2. The choice of method used to assess IR and β-cell function depends on the size and type of study to be undertaken. Although clamps are useful techniques for intensive physiological studies on relatively small numbers of subjects, a simpler tool such as HOMA may be more appropriate for use in large epidemiological studies. HOMA can be used to assess longitudinal changes in β-cell function and IR in patients with diabetes in order to examine the natural history of diabetes and to assess the effects of treatment. For example, the model was used in the U. Prospective Diabetes Study UKPDS to demonstrate the effects of sulfonylureas and metformin on IR and β-cell function, compared with diet, over a 6-year period For example, in the Mexico City Study, β-cell function and IR were assessed cross-sectionally using HOMA in 1, Mexicans with normal or impaired glucose tolerance IGT Subjects were followed up for 3. The development of diabetes was associated with higher HOMA-IR at baseline. Although it has been argued that HOMA is no better than fasting insulin concentrations for the estimation of insulin sensitivity in normal individuals, there are several reasons why the use of HOMA in normal subjects is worthwhile. The use of HOMA to quantify insulin sensitivity and β-cell function can be helpful in normal populations as it allows 1 comparisons of β-cell function and insulin sensitivity to be made with subjects with abnormal glucose tolerance and 2 the collection of longitudinal data in subjects who go on to develop abnormal glucose tolerance. HOMA can also be used in physiological studies to measure insulin sensitivity and β-cell function in addition to stimulated estimates derived from more complex tests such as clamps and IVGTTs Combining data from these tests gives information about insulin sensitivity or β-cell function across the dose-response curve. HOMA and clamps yield steady-state measures of insulin secretion and insulin sensitivity in the basal and maximally stimulated states, respectively. HOMA measures basal function at the nadir of the dose-response curve, whereas clamps are an assessment of the stimulated extreme i. The IVGTT and oral glucose tolerance test OGTT yield measures of dynamic non—steady-state insulin secretion and insulin sensitivity over the middle of the physiological range. HOMA can be used to track changes in insulin sensitivity and β-cell function longitudinally in individuals. The model can also be used in individuals to indicate whether reduced insulin sensitivity or β-cell failure predominates. When used in individuals, triplicate insulin samples should be used to improve the CV. Taken in isolation, this might imply that IR plays a greater part in the pathophysiology of IGT in the subjects from Mexico City than in those studied in IRAS. But when insulin sensitivity is examined in the two populations in subjects with NGT, a similar difference is found Collateral evidence, such as the finding that the metabolic syndrome was closely associated with the resistant groups, would give credence to the supposition that reduced insulin sensitivity was a marker of risk. It is possible to use HOMA to assess insulin sensitivity in subjects treated with insulin, but it is imperative to ensure that samples are taken when glucose and insulin concentrations are in a steady state. An additional problem is that subcutaneously administered insulin enters into the peripheral circulation and is therefore not subject to the same degree of first-pass metabolism as endogenous insulin secreted into the portal circulation. Thus, the assumptions about hepatic extraction included in the model do not apply when a subject is being treated with exogenous insulin. The use of HOMA in subjects on insulin needs further validation, and studies to examine the use of HOMA in these circumstances are in progress. The insulin-glucose HOMA model cannot be used to assess β-cell function in those taking exogenous insulin. Under such circumstances, the C-peptide HOMA model, which uses plasma C-peptide concentrations to reflect endogenous insulin secretion, could be used, but the use of the model in this situation has not been verified. HOMA can be used in subjects on insulin secretagogues, but the results need to be interpreted with caution. HOMA apportions the basal state of insulin and glucose in terms of resistance and β-cell function. However, if the β-cell data are reported in isolation, one might conclude erroneously that the subject had failing β-cells, as opposed to appropriately low secretion, because the sensitivity of the body was high. The HOMA model has not been validated for use in rodents or any other animals, and such use violates the assumptions of the model. There are issues relating to reproducibility both within subject and between subject inherent in all methods of assessment. Authors need to be clear about this when reporting their data. HOMA may yield a different estimate of β-cell function or IR from the minimal model. It should be recognized that HOMA is a measure of basal insulin sensitivity and β-cell function and, in contrast to clamps, is not intended to give information about the stimulated state. HOMA estimates of β-cell function and insulin sensitivity are usually not normally distributed. The data should be tested for normality, and if they are found to not be normal, they should be logarithmically transformed and reported as geometric means with appropriate measures of dispersion. The Quantitative Insulin Sensitivity Check Index QUICKI 29 is identical to the simple equation form of the HOMA model in all comparative respects, except that QUICKI uses a log transform of the insulin glucose product. QUICKI is thus not a new model and should be recognized as simply being log HOMA-IR, which explains the near-perfect correlation with HOMA. The HOMA model has proved be a robust clinical and epidemiological tool in descriptions of the pathophysiology of diabetes. HOMA analysis allows assessment of inherent β-cell function and insulin sensitivity and can characterize the pathophysiology in those with abnormal glucose tolerance. Longitudinal data in normal subjects who go on to develop abnormal glucose tolerance is particularly informative. The use of HOMA to assess insulin sensitivity in subjects treated with insulin has many potential problems and needs further validation. Clarity is needed in reporting HOMA due to the problems of describing changes in percentages. HOMA values are rarely normally distributed and should therefore be logarithmically transformed and reported as geometric means with appropriate measures of dispersion. Explore AAP Close AAP Home shopAAP PediaLink HealthyChildren. header search search input Search input auto suggest. filter your search All Publications All Journals Pediatrics Hospital Pediatrics Pediatrics In Review NeoReviews AAP Grand Rounds AAP News All AAP Sites. Advanced Search. Skip Nav Destination Close navigation menu Article navigation. Volume , Issue 4. Previous Article Next Article. Article Navigation. Electronic Articles April 01 This Site. Google Scholar. Selim Kurtoglu, MD ; Selim Kurtoglu, MD. Mustafa Kendirci, MD ; Mustafa Kendirci, MD. Emre Atabek, MD ; M. Emre Atabek, MD. Cevat Yazici, MD Cevat Yazici, MD. Address correspondence to Mehmet Keskin, MD, Department of Pediatrics, School of Medicine, Erciyes University, , Kayseri, Turkey. Pediatrics 4 : e—e Article history Accepted:. 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Article PDF	Healthy weight maintenance the Assesskent measurement, the arm was Insulin sensitivity and homeostasis model assessment homeostadis the heart ssnsitivity, and an automated oscillometric device 53, Welch Allyn, Aasessment York, USA was used. Hoffmann-La Roche Ltd, Basel, Switzerland with placebo in patients with established or newly diagnosed type 2 diabetes and recent ACS including unstable angina, non-ST segment elevation myocardial infarction, and ST segment elevation myocardial infarction. Facebook Twitter LinkedIn Instagram YouTube. Copy to clipboard. n 65 66 68 Age yr

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india diabetes obesity INSULIN RESISTANCE HOMA - IR HOMA DIABETES REVERSAL ANTI AGEING FATTY LIVER Tara M. WallaceJonathan C. SensitiviryDavid R. Matthews; Use and Abuse of HOMA Modeling. Diabetes Care 1 June ; 27 6 : —