The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index; 1 of the 6 sources its claims cite were checked for support.
Homeostasis model assessment: insulin resistance and ?-cell function from fasting plasma glucose and insulin concentrations in man
Open accessAbstract
The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
15 Own result · 7 Own interpretation · 3 No full text of the sources · 1 Partly supported · 1 No basis given · accuracy not yet measured
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“The fasting plasma insulin concentration is largely determined by the glucose concentration [3]”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
What the sources say
- Partly supportedcites [3] McCarthy ST, Harris F, Turner RC (1977) Glucose control of basal insulin secretion in diabetes. Diabetologia 13: 93?97 sourceExperimental — accuracy not yet measured
The Results and Discussion (page unavailable in our copy) show that changing plasma glucose affects basal insulin secretion. But they also report markedly impaired responses in diabetic subjects, including cases where insulin remained nearly constant despite a substantial glucose decrease. The paper therefore supports glucose as an influence, but not the unqualified claim that it largely determines fasting insulin concentration. (LLM, conf=0.84)
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The estimate of deficient/3cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (R~ = 0.61, p< 0.01)”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (R~=0.88,p<0.0001)”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There was no correlation with any aspect of insulin-receptor binding.”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the fasting insulin concentration (P~ = 0.81, p < 0.0001)”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The mean coefficient of variation over the two studies was 32%.”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Reproducibility of estimate of /3-cell function by HOMA
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“in both groups together (1% 0.61, p < 0.01 : Fig. 3).”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Comparisons of methods of assessing ~3-cell function
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and with the estimate from the intravenous glucose tolerance test (R~ = 0.64, p < 0.05).”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and in both groups together: 1% = 0.64, p< 0.05; Fig. 3).”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > HOMA compared with intravenous glucose tolerance test.
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Neither receptor numbers or any aspect of high or low affinity binding correlated with other measures of insulin resistance (HOMA, clamp, basal insulin or CIGMA: ~ all < 0.55; NS).”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > HOMA compared with the hyperglycaemic clamp. The
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
- It may state two separate claims as one. 2
- The quote only partly states this claim. 1
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for/3-cell deficit) limits its use”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The mean coefficient of variation over the two studies was 31%.”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Hyperglycaemic clamp : ~-cell function (%)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The degree of the hyperglycaemia does not correlate significantly with either the degrees of abnormal fl-cell function or insulin resistance.”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
The authors state this as an assumption.
Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
“Assuming that normal-weight normal subjects aged < 35 years have 100% r-cell function, and an insulin resistance of 1, the values for a patient can be assessed from the insulin and glucose concentrations by the formulae: r-cell”
The paper relies on this without support.
The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
“The plasma glucose:insulin response for normal subjects, equivalent to the C-peptide response, is insulin = 5 (glucose-3.5).”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Surrogate markers of peripheral insulin activity, such as homeostasis model assessment and whole-body insulin sensitivity indexes, could be useful as well in the early identification of patients with IR, before overt DM sets in ().”
From Glucose Metabolism Abnormalities in Cushing Syndrome: From Molecular Basis to Clinical Management (2017) · cites this paper as [240]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“After the unprocessed diet, fasting glucose and insulin levels tended to decrease compared to baseline and the homeostasis model assessment of insulin resistance (HOMA-IR) (Matthews et al., 1985) was significantly decreased compared to baseline.”
From Ultra-Processed Diets Cause Excess Calorie Intake and Weight Gain: An Inpatient Randomized Controlled Trial of Ad Libitum Food Intake (2019) · cites this paper as Matthews et al., 1985
The cited source says what the claim attributes to it.
In the citing paper
“The Homeostasis Model Assessment of Insulin Resistance (HoMA-IR) was calculated according to Matthews et al. [25].”
From Chronotype: A Tool to Screen Eating Habits in Polycystic Ovary Syndrome? (2022) · cites this paper as [25]
The cited source says what the claim attributes to it.
In the citing paper
“AAV9-mTERT treated mice also showed a trend for an improved glucose uptake and a better homeostatic model assessment (HOMA (Heikkinen et al, 2007; Matthews et al, 1985)) compared to the AAV9-eGFP controls, although differences did not reach statistical significance (Supporting Information Fig S4D and E).”
From Telomerase gene therapy in adult and old mice delays aging and increases longevity without increasing cancer (2012) · cites this paper as Matthews et al, 1985
In the citing paper
“ndirect estimates of insulin resistance, such as HOMA-IR 63 and QUICKI, 64 are derived from fasting S-insulin and glucose concentrations and have been widely used in both nondiabetic and type 2 diabetic subjects as surrogates of insulin sensitivity.65,66”
From Increased liver fat, impaired insulin clearance, and hepatic and adipose tissue insulin resistance in type 2 diabetes. (2008) · cites this paper as [63]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Subjects and procedures
“The same 12 normal subjects and 11 Type 2 diabetic patients came to the hospital fasting on a separate day for a continuous infusion”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > HOMA compared with the hyperglycaemic clamp. The
“HOMA compared with CIGMA.The HOMA estimate of insulin resistance from the mean of 15 stressed fasting samples before the CIGMA correlated with that measured by CIGMA in 11 normal subjects (R~ = 0.69, p < 0.02), in 12 diabetic subjects (R~ 0.97, p < 0.0001)”
Citations
Cites
Glucose clamp technique: a method for quantifying insulin secretion and resistance.
DeFronzo, R. A., Tobin, J. D., & Andres, R. (1979) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.1979.237.3.e214 · Cited by 7,425
Quantitative estimation of insulin sensitivity.
Bergman, R. N., Ider, Y. Z., Bowden, C. R., & Cobelli, C. (1979) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.1979.236.6.e667 · Cited by 1,874 · cited 1×
“This use of modelling to provide a reference graph contrasts with other models where an individual patient's data have to be entered into a computer to determine the relationships between rapidly changing variables, such as occur after an intravenous glucose test [19].”
Method[WHO Expert Committee on diabetes mellitus].
Reitsma, W. D., & Terpstra, J. (1981) · PubMed · Cited by 556
Turner, R. C., Holman, R. R., Matthews, D., Hockaday, T. D. R., & Peto, J. (1979) · Metabolism · doi:10.1016/0026-0495(79)90146-x · Cited by 388
Self-citationCharacteristics of Human Erythrocyte Insulin Receptors
Gambhir, K. K., Archer, J. A., & BRADLEY, C. J. (1978) · Diabetes · doi:10.2337/diab.27.7.701 · Cited by 290
The Insulin Receptor: Its Role in Insulin Resistance of Obesity and Diabetes
Olefsky, J. M. (1976) · Diabetes · doi:10.2337/diab.25.12.1154 · Cited by 289
Hosker, J. P., Matthews, D. R., Rudenski, A. S., Burnett, M. A., Darling, P., Bown, E. G., & Turner, R. C. (1985) · Diabetologia · doi:10.1007/bf00280882 · Cited by 287
Self-citationPulsatile Insulin Has Greater Hypoglycemic Effect Than Continuous Delivery
Matthews, D. R., Naylor, B. A., Jones, R., Ward, G. M., & Turner, R. C. (1983) · Diabetes · doi:10.2337/diab.32.7.617 · Cited by 256
Self-citationControl of pulsatile insulin secretion in man
Matthews, D. R., Lang, D. A., Burnett, M. A., & Turner, R. C. (1983) · Diabetologia · doi:10.1007/bf00282705 · Cited by 175
Self-citationTHE BASAL PLASMA GLUCOSE: A SIMPLE RELEVANT INDEX OF MATURITY‐ONSET DIABETES
HOLMAN, R. R., & TURNER, R. C. (1981) · Clinical Endocrinology · doi:10.1111/j.1365-2265.1981.tb00196.x · Cited by 64
Self-citation
Research works printed but not linked: 2
- Metropolitan Life Assurance Co (1959) Net weight standard for men and women. Stat Bull Metrol Life Found 40: 1?4
- Matthews DR, Hosker JP (1984) An unbiased, flexible computer programme for glucose clamping, with graphics and running statistics. Diabetologia 27: 308?309 A
Cited by
Sorted by citations
Items 19,101–19,200 of 31,469
Type 2 Diabetes in Octogenarians Is Associated with Decreased Low Molecular Weight Adiponectin
Graessler, J., Grüber, M., Radke, R.-B., Kopprasch, S., Schwarz, P. E. H., Kamke, W., Bornstein, S. R., & Fischer, S. (2010) · Gerontology · doi:10.1159/000316575 · Cited by 13
Polgreen, L. E., Thomas, W. T. B., MacMillan, M. L., Wagner, J. E., Moran, A., & Petryk, A. (2009) · Pediatric Blood & Cancer · doi:10.1002/pbc.22043 · Cited by 13
Lack of association of PTPN1 gene polymorphisms with type 2 diabetes in south Indians
Bodhini, D., Radha, V., Ghosh, S., et al. (2011) · Journal of Genetics · doi:10.1007/s12041-011-0060-3 · Cited by 13
Ükinç, K., Ersöz, H. Ö., Erem, C., Hacıhasanoğlu, A., & Karti, S. S. (2009) · Endocrine · doi:10.1007/s12020-009-9157-3 · Cited by 13
Choi, I. K., Kim, D. H., & Kim, H.-S. (2005) · European Journal of Pediatrics · doi:10.1007/s00431-005-1643-x · Cited by 14
Abe, Y., Okada, T., Iguchi, H., Saito, E., Kuromori, Y., Iwata, F., Hara, M., Mugishima, H., & Kitamura, Y. (2012) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.12476 · Cited by 13
Farias, D. R., Franco‐Sena, A. B., Rebelo, F. M., Schlüssel, M. M., Salles, G. F., & Kac, G. (2013) · Journal of Hypertension · doi:10.1097/hjh.0000000000000037 · Cited by 13
“Study Group on Obesity” of the Italian Society of Endocrinology, Putignano, P., Brunani, A., Dubini, A., Bertolini, M., Pasquali, R., & Cavagnini, F. (2003) · Journal of Endocrinological Investigation · doi:10.1007/bf03345137 · Cited by 13
Kang, L., Chen, C., Cheng, Y.-C., Chang, C., Lee, C., Chang, J., Cheng, J., & Chang, F. (2012) · Menopause The Journal of The North American Menopause Society · doi:10.1097/gme.0b013e31823a40d9 · Cited by 13
Stewart, M., Humphriss, D. B., Mitcheson, J., Webster, J. M., Walker, M., & Laker, M. F. (1998) · Atherosclerosis · doi:10.1016/s0021-9150(98)00065-3 · Cited by 13
Metoprolol Succinate, a Selective β‐Adrenergic Blocker, Has No Effect on Insulin Sensitivity
Falkner, B. E., Francos, G. C., & Kushner, H. (2006) · Journal of Clinical Hypertension · doi:10.1111/j.1524-6175.2006.05247.x · Cited by 13
Alssema, M., Schindhelm, R. K., Dekker, J. M., Diamant, M., Nijpels, G., Teerlink, T., Scheffer, P. G., Kostense, P. J., & Heine, R. J. (2008) · Metabolism · doi:10.1016/j.metabol.2008.04.022 · Cited by 13
Mild Gestational Hyperglycemia and the Metabolic Syndrome in Later Life
Bo, S., Menato, G., Botto, C., Cotrino, I., Bardelli, C., Gambino, R., Cassader, M., Durazzo, M., Signorile, A., Massobrio, M., et al. (2006) · Metabolic Syndrome and Related Disorders · doi:10.1089/met.2006.4.113 · Cited by 12
Bhoj, E. J. K., Romeo, S., Baroni, M. G., Bartov, G., Schultz, R. A., & Zinn, A. R. (2009) · Molecular Cytogenetics · doi:10.1186/1755-8166-2-5 · Cited by 13
Utsunomiya, K., Takamatsu, K., Fukuta, I., et al. (2009) · Internal Medicine · doi:10.2169/internalmedicine.48.2287 · Cited by 13
Relationship between Insulin Resistance and Coronary Artery Calcium in Young Men and Women
Sung, K., Choi, J., Gwon, H., Choi, S., Kim, B., Kwag, H. J., & Kim, S. H. (2013) · PLoS ONE · doi:10.1371/journal.pone.0053316 · Cited by 13
Insulin Resistance and the Metabolic Syndrome in Obese Children Referred to an Obesity Center
Rotteveel, J., Felius, A., van Weissenbruch, M. M., & de Waal, H. A. D. (2010) · Journal of Pediatric Endocrinology and Metabolism · doi:10.1515/jpem.2010.151 · Cited by 13
Ono, S., Suzuki, Y., Fukui, N., Sugai, T., Watanabe, J., Tsuneyama, N., & Someya, T. (2011) · The Pharmacogenomics Journal · doi:10.1038/tpj.2011.28 · Cited by 12
Chu, Y., Cui, Q., Feng, G., Song, Z., & Jiang, X. (2009) · Journal of Huazhong University of Science and Technology [Medical Sciences] · doi:10.1007/s11596-009-0521-6 · Cited by 13
Legedz, L., Bricca, G., Lantelme, P., et al. (2006) · Vascular Health and Risk Management · doi:10.2147/vhrm.2006.2.4.485 · Cited by 13
Zhang, X., Xiao, Z., Yu, H., Zhang, X.-X., Cheng, Z., & Tian, H. (2013) · Archives of Medical Research · doi:10.1016/j.arcmed.2013.07.004 · Cited by 13
Li, G., Fan, L., Zhang, L., Zhang, W., & Huang, X. (2010) · Journal of Perinatal Medicine · doi:10.1515/jpm.2010.034 · Cited by 12
Mijares, A. H., Fortuny, C. R., Triguero, M. L. M., et al. (2004) · Revista Española de Cardiología · doi:10.1016/s0300-8932(04)77210-3 · Cited by 13
Prostaglandin E synthase 2 (PTGES2) Arg298His polymorphism and parameters of the metabolic syndrome
Lindner, I., Helwig, U., Rubin, D. C., et al. (2007) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.200700144 · Cited by 13
Evaluation of reproductive safety of β-sitosterol on the American mink (Neovison vison)
Nieminen, P., Pölönen, I., Ikonen, K., et al. (2007) · Chemosphere · doi:10.1016/j.chemosphere.2007.10.011 · Cited by 13
PATEL, D., LI, S., Chen, W., SRINIVASAN, S., Boerwinkle, E., & Berenson, G. S. (2005) · American Journal of Hypertension · doi:10.1016/j.amjhyper.2005.05.031 · Cited by 13
Estimation of β-cell function from the data of the oral glucose tolerance test
Sakaue, S., 石丸伸司, Ikeda, D., Ohtsuka, Y., Honda, T., Suzuki, J.-I., Kawakami, Y., Ishii, J., & Nishimura, M. (2007) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00341.2006 · Cited by 13
Liu, J., Tung, T., Tsai, S., Chou, P., Chuang, S., Chen, S., Lee, F.-L., Shih, H., & Li, W. (2006) · Ophthalmologica · doi:10.1159/000093080 · Cited by 13
Miceli, D., Gallelli, M., Blatter, M. F. C., Martiarena, B., Brañas, M., Ortemberg, L., Gómez, N., & Castillo, V. (2012) · Research in Veterinary Science · doi:10.1016/j.rvsc.2011.07.003 · Cited by 16
Hileman, C. O., Carman, T. L., Gripshover, B., et al. (2010) · AIDS · doi:10.1097/qad.0b013e32833c3251 · Cited by 13
Ota, T., & Osawa, K. (2003) · Diabetic Medicine · doi:10.1046/j.1464-5491.2003.009173.x · Cited by 13
Kramer, C. K., Leitão, C. B., Pinto, L. C. F., Boza, J. C., Silveiro, S. P., Gross, J. L., & Canani, L. H. S. (2009) · Revista da Associação Médica Brasileira · doi:10.1590/s0104-42302009000300024 · Cited by 13
Galvin, V. B., Barakat, H. A., Kemeny, G., et al. (2005) · Metabolism · doi:10.1016/j.metabol.2005.04.028 · Cited by 13
Adiponectin is related to intramyocellular lipid content in non-diabetic adults
Godoy‐Matos, A. F., Bahia, L., Domingues, R. C., Sicuro, F. L., Tambascia, M. A., Geloneze, B., Kraemer‐Aguiar, L. G., & Bouskela, E. (2009) · Journal of Endocrinological Investigation · doi:10.1007/bf03346608 · Cited by 13
Impact of chronic diuretic treatment on glucose homeostasis
Buscemi, S., Nicolucci, A., Lucisano, G., Galvano, F., Grosso, G., Massenti, F. M., Amodio, E., Bonura, A., Sprini, D., & Rini, G. B. (2013) · Diabetology & Metabolic Syndrome · doi:10.1186/1758-5996-5-80 · Cited by 13
Ikeda, Y., Suehiro, T., Ohsaki, F., et al. (2003) · Diabetes Research and Clinical Practice · doi:10.1016/s0168-8227(02)00280-2 · Cited by 13
Irving, R. R., Mills, J. L., Choo-Kang, E. G., Morrison, E., Kulkarni, S., Wright-Pascoe, R. A., & McLaughlin, W. A. (2008) · Revista Panamericana de Salud Pública · doi:10.1590/s1020-49892008000200003 · Cited by 13
Insulin Secretion and Sensitivity during Oral Glucose Tolerance Test in Korean Lean Elderly Women
Kim, J., Choi, S., Kong, B., Oh, Y.-S., & Shinn, S.-H. (2001) · Journal of Korean Medical Science · doi:10.3346/jkms.2001.16.5.592 · Cited by 13
de Roos, B., Wanders, A. J., Wood, S. G., Horgan, G. W., Rucklige, G., Reid, M., Siebelink, E., & Brouwer, I. A. (2011) · PROTEOMICS · doi:10.1002/pmic.201100163 · Cited by 12
Increased leucine turnover in women during the third trimester of uncomplicated pregnancy
Jolly, M., Bertie, J., Gray, R., et al. (2004) · Metabolism · doi:10.1016/j.metabol.2003.12.001 · Cited by 13
Indinavir alters regulators of protein anabolism and catabolism in skeletal muscle
Hong‐Brown, L. Q., Pruznak, A. M., Frost, R. A., Vary, T. C., & Lang, C. H. (2005) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00591.2004 · Cited by 13
Johansson, A., Olsson, T., Cederquist, K., Forsberg, H., Holst, J. J., Seckl, J. R., & Ahren, B. (2002) · European Journal of Endocrinology · doi:10.1530/eje.0.1460397 · Cited by 13
Sayer, J., Marchant, B., Gelding, S. V., Cooper, J. A., & Timmis, A. (2000) · Heart · doi:10.1136/heart.83.2.210 · Cited by 13
Domingo, P., Cabeza, M. C., Pruvost, A., et al. (2011) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.01589-10 · Cited by 13
Bhuiyan, A. R., Srinivasan, S. R., Chen, W., Fernandez, C., Xu, J.-H., & Berenson, G. S. (2015) · Annals of Epidemiology · doi:10.1016/j.annepidem.2015.02.001 · Cited by 13
Glucose Metabolism and Visceral Fat in GH Deficient Adults: Two Years of GH-Replacement
Spina, L. D. C., Soares, D. V., Brasil, R. R. L. O., Lobo, P. M., Conceição, F. L., & Vaisman, M. (2004) · Pituitary · doi:10.1007/s11102-005-5065-6 · Cited by 13
Livadas, S., Boutzios, G., Economou, F., Alexandraki, K., Xyrafis, X., Christou, M., Zerva, A., Karachalios, A., Tantalaki, E., & Diamanti‐Kandarakis, E. (2009) · Fertility and Sterility · doi:10.1016/j.fertnstert.2009.02.073 · Cited by 14
Tinahones, F. J., Cardona, F., Rojo‐Martínez, G., Almaraz, M. C., Cardona, I., Vázquez‐Mellado, J., Garrido‐Sánchez, L., Collantes‐Estévez, E., & Soriguer, F. (2007) · British Journal Of Nutrition · doi:10.1017/s0007114507787470 · Cited by 13
Vervita, V., Saltamavros, A. D., Adonakis, G. L., Tsapanos, V., Decavalas, G., & Georgopoulos, N. A. (2009) · Gynecological Endocrinology · doi:10.1080/09513590903015486 · Cited by 13
Lecke, S. B., Morsch, D. M., & Spritzer, P. M. (2013) · Reproductive Biology and Endocrinology · doi:10.1186/1477-7827-11-77 · Cited by 13
FETAL ORIGINS OF ADULT DISEASE: WHERE DO WE STAND?
Yajnik, C. S. (2001) · Cited by 14
Effects of short term metformin administration on androgens in normal men.
Shegem, N., Nasir, A. M., Jbour, A.-K., Batieha, A., el-Khateeb, M. S., & Ajlouni, K. (2002) · Saudi Medical Journal · doi:10.15537/1658-3175.1787 · Cited by 15
St‐Onge, M., Newcomer, B. R., Buchthal, S. D., Aban, I., Allison, D. B., Bosarge, A., & Gower, B. A. (2007) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/86.5.1316 · Cited by 13
Diabese youngsters have 3.7 more chances in developing metabolic syndrome compared with the obese
Galli‐Τsinopoulou, A., Grammatikopoulou, M. G., Stylianou, C., Emmanouilidou, E., & Kokka, P. (2010) · Journal of Endocrinological Investigation · doi:10.1007/bf03346646 · Cited by 13
Vendramini, M. F., Ferreira, S. R. G., Gimeno, S. G. A., Kasamatsu, T. S., Miranda, W. L., & Moisés, R. S. (2006) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2006.02.002 · Cited by 13
Obesity and Insulin Resistance in Childhood
Pastucha, D., Malinčíková, J., Hyjánek, J., Horáková, D., Čížek, L., Janoutová, G., & Janout, V. (2007) · Central European Journal of Public Health · doi:10.21101/cejph.a3437 · Cited by 13
Komatsu, T., Yaguchi, I., Komatsu, S., et al. (2015) · Texas Heart Institute Journal · doi:10.14503/thij-14-4393 · Cited by 13
Bağır, G. Ş., Bakıner, O., Bozkırlı, E., Cavlak, G., Serinsöz, H., & Ertörer, M. E. (2015) · Medical Principles and Practice · doi:10.1159/000440810 · Cited by 13
Tang, L., Lü, Q., Cao, H., Qiu, Y., & Tong, N. (2016) · Gene · doi:10.1016/j.gene.2016.02.035 · Cited by 13
Jiménez‐Pavón, D., Sesé, M. A., Valtueña, J., Cuenca‐García, M., González‐Gross, M., Gottrand, F., Kafatos, A., Μanios, Y., Widhalm, K., Henauw, S. D., et al. (2013) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2013-0250 · Cited by 13
Hussain, M., Jangorbhani, M., Schuette, S. A., et al. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0151 · Cited by 13
Casiglia, E., Tikhonoff, V., Boschetti, G., et al. (2012) · American Journal of Hypertension · doi:10.1038/ajh.2011.257 · Cited by 13
Kim, S. H., Reaven, G. M., & Lindley, S. E. (2010) · International Clinical Psychopharmacology · doi:10.1097/yic.0b013e3283400cd3 · Cited by 13
Li, J., Yang, Z., Wu, S., & Kong, J. (2012) · Journal of International Medical Research · doi:10.1177/147323001204000232 · Cited by 13
The Effects of Intermittent Energy Restriction on Indices of Cardiometabolic Health
Antoni, R., Johnston, K. L., Collins, A. L., & Robertson, M. D. (2014) · Research in Endocrinology · doi:10.5171/2014.459119 · Cited by 12
Acute high-intensity interval rowing increases thrombin generation in healthy men
Sedgwick, M. J., Thompson, M., Garnham, J. O., Thackray, A. E., Barrett, L. A., Powis, M., & Stensel, D. J. (2016) · European Journal of Applied Physiology · doi:10.1007/s00421-016-3370-6 · Cited by 13
Celık, T., Yılmaz, M. İ., Balta, Ş., et al. (2016) · Clinical and Applied Thrombosis/Hemostasis · doi:10.1177/1076029616634888 · Cited by 13
Momin, A. A., Bankar, M. P., & Bhoite, G. M. (2016) · Indian Journal of Clinical Biochemistry · doi:10.1007/s12291-016-0573-x · Cited by 13
Gama, R. M., Norris, F., Morgan, L., Hampton, S. M., Wright, J., & Marks, V. (1997) · Clinical Science · doi:10.1042/cs0930343 · Cited by 13
Zhao-feng, L. I., Zhou, D., Pan, W., et al. (2013) · Chinese Medical Journal · doi:10.3760/cma.j.issn.0366-6999.20123353 · Cited by 13
Insulin resistance is related with oxidative stress in systemic lupus erythematosus.
Koca, S. S., Karaca, I., Yavuzkır, M. F., Dağlı, N., Özgen, M., Üstündağ, B., & Işık, A. T. (2009) · PubMed · Cited by 13
Renal inflammatory and oxidative and metabolic changes after 6 weeks of cafeteria diet in rats
Navarro, M. E. L., dos Santos, K. C., do Nascimento, A. F., Francisqueti‐Ferron, F. V., Minatel, I. O., Pierine, D. T., Luvizotto, R. D. A. M., Ferreira, A. L. A., de Campos, D. H. S., & Corrêa, C. R. (2016) · Brazilian Journal of Nephrology · doi:10.5935/0101-2800.20160003 · Cited by 13
Barreiro-Ribeiro, F., Vasques, A., da Silva, C. D. C., Zambon, M., Rodrigues, A. M. D. B., Camilo, D. F., Antônio, M. Â. R. D. G. M., Dâmaso, A., Campos, R. M. D. S., Tufik, S., et al. (2016) · Childhood Obesity · doi:10.1089/chi.2016.0180 · Cited by 13
Prakash, J., Mittal, B., Srivastava, A. N., Awasthi, S., Srivastava, P., & Srivastava, N. (2017) · Iranian Biomedical Journal · doi:10.18869/acadpub.ibj.21.4.261 · Cited by 13
Insulin-like growth factor-1 is a negative modulator of glucagon secretion
Mancuso, E., Mannino, G. C., Fatta, C. D., Fuoco, A., Spiga, R., Andreozzi, F., & Sesti, G. (2017) · Oncotarget · doi:10.18632/oncotarget.18514 · Cited by 12
Zhang, P., Zhu, D., Zhang, Y., Li, L., Chen, X., Zhang, W., Shi, R., Tao, J., Han, B., & Xu, Z. (2018) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201700771 · Cited by 14
Relationship among obesity, blood lipids and insulin resistance in Bangladeshi adults
Malik, S. U. F., Mahmud, Z., Alam, J., Islam, M. S., & Azad, A. K. (2018) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2018.10.015 · Cited by 14
Yegnanarayan, R., Suryavanshi, M., Singh, M., et al. (2008) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2006.09.001 · Cited by 13
The Gly1057Asp polymorphism in IRS-2 interacts with obesity to affect beta cell function
Stefan, N., Fritsche, A., Machicao, F. E., Tschritter, O., H�ring, H. U., & Stümvoll, M. (2004) · Diabetologia · doi:10.1007/s00125-003-1302-6 · Cited by 13
Clinical effect of combination therapy of pioglitazone and an α-glucosidase inhibitor
Seino, H., Yamaguchi, H., Misaki, A., Sakata, Y., Kitagawa, M., Yamazaki, T., Kikuchi, H., & Abe, R. (2003) · Current Medical Research and Opinion · doi:10.1185/030079903125002423 · Cited by 14
Glucose Dysregulation in Obese Children: Predictive, Risk, and Potential Protective Factors
Xekouki, P., Nikolakopoulou, N. M., Papageorgiou, A., Livadas, S., Voutetakis, A., Magiakou, M. A., Chrousos, G. P., Spiliotis, B. E., & Dacou‐Voutetakis, C. (2007) · Obesity · doi:10.1038/oby.2007.600 · Cited by 13
Acton, R. T., Bell, D. S. H., Collins, J. M., et al. (1997) · Transplantation Proceedings · doi:10.1016/s0041-1345(97)01079-8 · Cited by 13
Kawano, Y., Okuda, N., Minami, J., Takishita, S., & Omae, T. (2000) · Journal of Hypertension · doi:10.1097/00004872-200018100-00013 · Cited by 13
Myocardial Mechanics and Titin in Experimental Insulin-resistant Rats.
Hsu, K.-L., Tsai, C., Chiang, F., et al. (1997) · Japanese Heart Journal · doi:10.1536/ihj.38.717 · Cited by 13
African American Women, Metabolic Syndrome, and National Cholesterol Education Program Criteria
Appel, S. J., Floyd, N. A., Giger, J. N., Weaver, M. T., Luo, H., Hannah, T., & Ovalle, F. (2005) · Nursing Research · doi:10.1097/00006199-200509000-00008 · Cited by 13
The metabolic syndrome in Spanish migrants to Brazil: Unexpected results
Pousada, J. M. D. C., Britto, M. M. S., Cruz, T., Lima, M. D. L., Lessa, Í., Lemaire, D. C., Carvalho, R. H., Martinez-Larrad, M. T., Torres, E. C., & Serrano‐Ríos, M. (2005) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2005.09.006 · Cited by 13
da Costa, A. M., Fernández‐Real, J. M., Vendrell, J. J., Broch, M., Casamitjana, R., Ricart, W., & Conget, I. (2003) · Metabolism · doi:10.1016/s0026-0495(03)00108-2 · Cited by 13
Chen, L., Peng, L., Lin, M.-H., Lai, H., Hwang, S., & Chiou, S.-T. (2009) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.794 · Cited by 13
Association of sex hormone-binding globulin and insulin resistance among Japanese-American subjects
Okubo, M., Tokui, M., Egusa, G., & Yamakido, M. (2000) · Diabetes Research and Clinical Practice · doi:10.1016/s0168-8227(99)00106-0 · Cited by 13
Bonet, B., Viana, M., Sánchez‐Vera, I., Quintanar, A., Martínez, J., & Espino, M. (2007) · Diabetic Medicine · doi:10.1111/j.1464-5491.2007.02230.x · Cited by 13
Effects of the Magenstrasse and Mill operation for obesity on plasma leptin and insulin resistance
Carmichael, A. R., Johnston, D. A., King, R. F. G. J., & Sue-Ling, H. M. (2001) · Diabetes Obesity and Metabolism · doi:10.1046/j.1463-1326.2001.00129.x · Cited by 13
Foss‐Freitas, M. C., & Foss, M. C. (2004) · Brazilian Journal of Medical and Biological Research · doi:10.1590/s0100-879x2004000500006 · Cited by 14
Ohya, Y., Maruhashi, S., & Ouchi, T. (1998) · Macromolecular Chemistry and Physics · doi:10.1002/(sici)1521-3935(19980901)199:9 · Cited by 58
Casano, P., López‐Bermejo, A., Fernández‐Real, J. M., Monrós, E., Valls, C., Rodríguez‐González, F., Ricart, W., & Ibáñez, L. (2006) · Clinical Endocrinology · doi:10.1111/j.1365-2265.2006.02434.x · Cited by 13
Nilsson, P. M., Hedblad, B., Donaldson, J., & Berglund, G. L. (2007) · Blood Pressure · doi:10.1080/08037050701396652 · Cited by 13
Florez, J. C., Sjögren, M., Agapakis, C. M., Burtt, N. P., Almgren, P.-E., Lindblad, U., Berglund, G., Tuomilehto, J., Gaudet, D., Daly, M. J., et al. (2007) · Diabetologia · doi:10.1007/s00125-007-0657-5 · Cited by 13
The association between leptin and proinsulin is lost with central obesity
Söderberg, S., Åhrén, B., Eliasson, M., Dinesen, B., & Olsson, T. (2002) · Journal of Internal Medicine · doi:10.1046/j.1365-2796.2002.01018.x · Cited by 13
Goacutemez-Peacuterez, F. J., Aguilar-Salinas, C. A., V[aacute]zquez-Ch[aacute]vez, C., nel-Salmoacuten, G. F., Gallegos-Mart[iacute]nez, J., Goacutemez-Diaz, R. A., Orozco, S. S., Chavira-Loacutepez, I. J., Saacutenchez-Reyes, L., Torres-Acosta, E. M., et al. (2002) · Metabolism · doi:10.1053/meta.2002.29024 · Cited by 13
Wong, T. Y. H., Chan, J. C. N., Szeto, C., et al. (1999) · American Journal of Kidney Diseases · doi:10.1016/s0272-6386(99)70080-6 · Cited by 13
Maumus, S., Bastien, B., Vincent‐Viry, M., et al. (2006) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2006.04.003 · Cited by 13
Metadata
- Authors
- Matthews, D. R., Hosker, J. P., Rudenski, A. S., Naylor, B. A., Treacher, D. F., & Turner, R. C.
- Affiliations
- University of Oxford (GB)
- ORCID
- Matthews, D. R.
- Venue
- Diabetologia
- Published
- 1985-07
- Volume
- 28
- Issue
- 7
- Pages
- 412-419
- ISSN
- 0012-186X (ISSN-L)
- 1432-0428
- OpenAlex
- W2160234571
- Cited by
- 31,502
- References
- 21
- Citations by year
- 2026: 933 · 2025: 1060 · 2024: 1240 · 2023: 1291 · 2022: 1489 · 2021: 1528 · 2020: 1424 · 2019: 1427 · 2018: 1456 · 2017: 1440 · 2016: 1481 · 2015: 1682 · 2014: 1693 · 2013: 1621 · 2012: 1518
- FWCI
- 7.91
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Diabetologia (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Medical Research Council
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Pancreatic function and diabetes
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- HOMA, insulin resistance, beta-cell function, fasting blood glucose, fasting insulin, hyperglycaemic clamp, euglycaemic clamp, intravenous glucose tolerance test, insulin receptor binding, type 2 diabetes
- MeSH terms
- Adult, Blood Glucose, Computers, Diabetes Mellitus, Type 2, Erythrocytes, Fasting, Homeostasis, Humans, Insulin, Insulin Resistance, Islets of Langerhans, Middle Aged, Monocytes, Receptor, Insulin
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-14, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-14 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review