# Calculate Insulin Resistance

Estimate insulin resistance from a single pair of fasting glucose and fasting insulin values. Instant, transparent, and grounded in the original 1985 model, with reference ranges anchored to German population data, not a made-up universal cutoff.

## Key figures

- Insulin-sensitive (< 1.5): No indication of insulin resistance. Your value sits at or below the level seen in metabolically healthy German adults (Gutenberg Health Study median 1.09).
- Borderline (1.5 to < 2.35): An orientation, not a finding. Many perfectly healthy adults land here: the German healthy reference reaches up to 2.35, so a large share of normal people sit in this band. It is a reason to keep an eye on sleep, movement, body composition and diet, and to mention a persistent value to your doctor, not a sign that something is wrong.
- Above the reference range (≥ 2.35): Above the healthy German reference range and consistent with the classic European Bruneck cutoff (2.77). This is a screening signal to confirm with a physician, not a diagnosis.

## What HOMA-IR actually measures

HOMA-IR (the Homeostasis Model Assessment of Insulin Resistance) estimates how hard your body has to work to keep blood sugar in check. It was derived in 1985 by Matthews and colleagues in Oxford [1], and it has become the most widely used way to gauge insulin resistance from a routine blood test, because it needs only two fasting values: glucose and insulin. The idea is simple. In a healthy person, a modest amount of insulin keeps fasting glucose normal. When cells stop responding well to insulin (insulin resistance), the pancreas compensates by secreting more, so fasting insulin creeps up, often years before fasting glucose does. HOMA-IR captures that imbalance as a single number, calibrated so a metabolically normal reference person scores 1.0 [1]. It is a screening surrogate, not a gold-standard measurement. The reference method (the hyperinsulinaemic-euglycaemic clamp) is impractical outside research, and HOMA-IR agrees with it only moderately at the individual level [2]. Think of HOMA-IR as a useful orientation, not a verdict.

- Estimates insulin resistance from fasting glucose + fasting insulin only.
- Calibrated so a normal reference person = 1.0; higher means more resistant.
- A screening surrogate, not a diagnostic test.

## How it is calculated

There are two algebraically identical forms of the formula. They differ only by the glucose unit: Conventional (glucose in mg/dL): HOMA-IR = fasting insulin (µU/mL) × fasting glucose (mg/dL) ÷ 405. SI (glucose in mmol/L): HOMA-IR = fasting insulin (mU/L) × fasting glucose (mmol/L) ÷ 22.5. The two denominators are linked by the glucose conversion factor: 405 = 22.5 × 18. Insulin in µU/mL, µIU/mL and mU/L are all numerically identical (1:1), so no conversion is needed there. If your lab reports insulin in pmol/L, this calculator divides by 6.0 to get µU/mL. The insulin-standardisation literature (Knopp and colleagues 2019 [9]; the ADA SI table) argues 6.0 is the more defensible factor than the widely-copied 6.945, which would understate your insulin (and so your HOMA-IR) by about 14%. The choice is assumption-dependent and the field is not fully standardised, and it only matters when a lab reports in pmol/L. The same inputs also yield two companion numbers. HOMA-%B, steady-state beta-cell function (normal ≈ 100%), is part of the original 1985 model [1]. The sensitivity figure we label HOMA-%S is simply 100 ÷ HOMA-IR, so a normal subject reads 100%; strictly, the named "%S" output belongs to the later HOMA2 computer model, but for HOMA1 this reciprocal carries the same meaning.

## How to read your result

Here is the most important thing most calculators won't tell you: there is no single universal HOMA-IR cutoff. The threshold for "insulin resistance" depends on the population studied, the insulin assay used, and which percentile you call abnormal. Published cutoffs range from roughly 1.4 to 3.9 [7][8]. The traffic-light bands below are a screening orientation for a general European/German adult audience, anchored to German population data (the Gutenberg Health Study reported a healthy median of 1.09 and a 97.5th-percentile upper reference limit of 2.35 [5]), with the upper band consistent with the classic European Bruneck cutoff of 2.77 [6]. They apply to HOMA1-IR (this calculator) only. Some European cohorts that anchor the cutoff to metabolic-syndrome outcomes land lower, around 1.85 to 2.0 (these usually take the top quartile of fasting insulin or HOMA-IR rather than a fixed value), so treat 2.35 as the conservative end of the grey zone. Because insulin immunoassays are not standardised, the same blood sample can give HOMA-IR values that differ almost two-fold between labs [10][11]. Always read your number against your own laboratory's reference range rather than treating any fixed value as absolute.

## The honest limitations

HOMA-IR is genuinely useful, but it is easy to over-read. Keep these caveats in mind:

- It needs true fasting values (about 10 to 12 hours). Non-fasting numbers are meaningless.
- A single sample is imprecise: insulin is secreted in pulses, and the original authors recommend the mean of three fasting samples drawn 5 minutes apart [1][2].
- Insulin assays are not standardised: the same sample can vary almost two-fold between labs, so values are not comparable across laboratories or studies [10][11].
- It does not work if you take insulin, or have type 1 diabetes or advanced beta-cell failure, where the C-peptide-based HOMA model is used instead [2].
- It is a screening surrogate, not a diagnosis, and does not replace a clinical work-up [2].
- It is not validated for pregnancy: insulin resistance rises naturally in later pregnancy, so the usual reference ranges do not apply and an elevated value should be read with your care team.
- Cutoffs are population- and ethnicity-dependent (Asian and some other populations have lower thresholds, often around 1.4 to 2.5); there is no externally validated universal cutoff [8].
- No major guideline (ADA, EASD) endorses a single HOMA-IR cutoff or routine clinical use, and the 405 / 22.5 constants were calibrated against a 1970s-era assay, so read your value against a local, assay-matched reference rather than as an absolute truth.

## HOMA1 vs HOMA2: which this is

The formula above is HOMA1: the original 1985 linear approximation. It is fast, transparent and matches the most familiar published cutoffs, which is exactly what this calculator gives you. The original authors later showed that the "correct" evaluation uses a non-linear computer model, HOMA2 [3], refined further as iHOMA2 [4]. HOMA2 is more accurate for modern insulin assays and across the full clinical range, and it also accounts for things the linear model can't. The trade-off: it can't be reduced to a simple equation. It is solved iteratively by the official Oxford Diabetes Trials Unit calculator. One rule matters above all: never cross-apply cutoffs. HOMA2-IR runs systematically lower than HOMA1-IR: a HOMA1 threshold near 2.7 corresponds to roughly HOMA2-IR 1.8 [8]. If your glucose or insulin is at the extremes, this calculator points you to the Oxford HOMA2 tool, because that is where the linear approximation is least trustworthy [2].

## Beyond HOMA-IR: open advanced indices

HOMA-IR is the familiar baseline, but it is not the only fasting model, and the most advanced one is not actually Oxford's HOMA2. HOMA2 is a closed, licensed program whose constants were never fully published, so nobody can reproduce it faithfully. That is why this tool links out to the official Oxford calculator for the rare extreme cases, rather than shipping a look-alike that would quietly be wrong. Instead, the advanced panel above computes SPINA-Carb, an open, mechanistic model (Dietrich et al. 2022, 2024) that reconstructs the structural constants of the glucose-insulin control loop from the same two fasting values [12][13]. It returns insulin sensitivity (SPINA-GR), beta-cell capacity (SPINA-GBeta), and a fasting disposition index (SPINA-DI) that mimics what normally needs an oral glucose tolerance test. In the originating studies, SPINA-DI separated people with and without diabetes better than HOMA-IR, QUICKI and even the dynamic (OGTT) disposition index [13]; that was a single research group, and independent validation is still limited, so read it as promising rather than settled. SPINA-Carb is also much newer than HOMA and far less independently replicated, whereas HOMA has 40+ years of clamp-comparison evidence behind it. Two insulin-free surrogates round it out for people who only have a basic panel: the triglyceride-glucose index (TyG), the most widely studied insulin-free marker [14], and METS-IR, which adds HDL and BMI and is also validated against the euglycemic clamp [15]. All of these are open published formulas with no license burden, computed natively here, which is how we can be a richer reference than a single linked-out tool.

- SPINA-Carb is an open, mechanistic alternative to the closed Oxford HOMA2, from the same two fasting values.
- TyG and METS-IR are insulin-free, so they work from a basic lipid and glucose panel.
- All are research screening surrogates with population-dependent reference values, not a diagnosis.


## FAQ

### How do I read a HOMA-IR result?

HOMA-IR can flag whether your fasting numbers point toward insulin resistance, but it can't tell you for sure. For HOMA1-IR in European/German adults, below 1.5 is reassuring, 1.5 to 2.35 is a borderline band that many healthy adults fall in, and above 2.35 sits above the German healthy reference range (the 97.5th-percentile upper reference limit), which is worth confirming rather than a diagnosis [5][6]. It is a screening signal, not a finding. Confirm a value above the reference range by repeating the test and discussing it with your doctor.

### What is a good HOMA-IR value?

For HOMA1-IR in European/German adults, below about 1.5 is reassuring (the Gutenberg Health Study healthy median was 1.09), 1.5 to 2.35 is a borderline band that many healthy adults fall in (the healthy reference reaches up to 2.35), and above 2.35 sits above the German healthy reference range, worth confirming rather than a diagnosis [5][6]. There is no universal cutoff, so compare your value to your own lab's reference range.

### Do I need to be fasting?

Yes. HOMA-IR is only valid on fasting (basal) glucose and insulin from the same blood draw, ideally after 10 to 12 hours without food. Non-fasting values make the result meaningless.

### My lab reports insulin in pmol/L. What do I enter?

Enter the pmol/L value and switch the unit toggle to pmol/L; the calculator divides by 6.0 to convert to µU/mL. The literature (Knopp 2019 [9]; the ADA SI table) argues 6.0 is more defensible than the widely-copied 6.945, which would understate your insulin and HOMA-IR by about 14%. The factor only matters when your lab reports pmol/L; if it reports µU/mL or mU/L there is no conversion.

### Why can the same blood give different HOMA-IR at two labs?

Because insulin immunoassays are not standardised. Across 11 commercial assays the same samples produced almost two-fold differences in HOMA-IR [10][11]. That is why you should read your number against the reference range of the lab that measured it.

### Is HOMA-IR a diagnosis of insulin resistance or prediabetes?

No. It is a screening surrogate, not a diagnostic test, and it does not replace a clinical assessment or the gold-standard clamp study [2]. Treat an elevated result as a prompt to repeat the test and talk to your doctor.

### Should I use HOMA1 or HOMA2?

This calculator gives HOMA1: instant and transparent. For values at the extremes, or for the most accurate modern estimate, use the non-linear HOMA2 model from Oxford [3][4]. Never apply HOMA1 cutoffs to a HOMA2 result, or vice versa [8].

### Is this a HOMA2 calculator, and does it give HOMA-β (beta-cell function)?

This is a HOMA1 calculator: from the same fasting glucose and insulin it returns HOMA-IR plus HOMA-%B (beta-cell function, from the original 1985 model [1]) and HOMA-%S, the insulin-sensitivity figure (the reciprocal 100 / HOMA-IR). It is not the non-linear HOMA2 computer model. HOMA2-IR, HOMA2-%B and HOMA2-%S come from the Oxford HOMA2 program, which we link to for values at the extremes; never mix HOMA1 and HOMA2 cutoffs [8]. For an open, mechanistic beta-cell and sensitivity read, the advanced panel also computes SPINA-Carb natively.

### What is the HOMA index, and is it the same as HOMA-IR?

"HOMA index" is the common shorthand for HOMA-IR, the Homeostasis Model Assessment of Insulin Resistance. This tool is a HOMA index calculator: enter fasting glucose and insulin, and it returns your HOMA-IR value with a German-referenced orientation band so you can read it against real population data rather than a made-up universal cutoff.

### Can I use C-peptide instead of fasting insulin?

Not in this HOMA1 calculator, which needs fasting insulin. C-peptide is used by the Oxford HOMA2 model, which has a dedicated C-peptide mode. That is the right tool if you only have C-peptide, or if you take insulin or have type 1 diabetes, where the insulin-based HOMA does not apply [2][3]. Use the Oxford HOMA2 link above for the C-peptide variant.

## Sources

- Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. (1985). Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. https://doi.org/10.1007/BF00280883
- Wallace TM, Levy JC, Matthews DR. (2004). Use and Abuse of HOMA Modeling. Diabetes Care. https://doi.org/10.2337/diacare.27.6.1487
- Levy JC, Matthews DR, Hermans MP. (1998). Correct Homeostasis Model Assessment (HOMA) Evaluation Uses the Computer Program. Diabetes Care. https://doi.org/10.2337/diacare.21.12.2191
- Hill NR, Levy JC, Matthews DR. (2013). Expansion of the Homeostasis Model Assessment of beta-Cell Function and Insulin Resistance to Enable Clinical Trial Outcome Modeling Through the Interactive Adjustment of Physiology and Treatment Effects: iHOMA2. Diabetes Care. https://doi.org/10.2337/dc12-0607
- Matli B, Schulz A, Koeck T, Falter T, Lotz J, Rossmann H, Pfeiffer N, Beutel M, Münzel T, Strauch K, Wild PS, Lackner KJ. (2021). Distribution of HOMA-IR in a population-based cohort and proposal for reference intervals. Clinical Chemistry and Laboratory Medicine (CCLM). https://doi.org/10.1515/cclm-2021-0643
- Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Targher G, Alberiche M, Bonadonna RC, Muggeo M. (1998). Prevalence of insulin resistance in metabolic disorders: the Bruneck Study. Diabetes. https://doi.org/10.2337/diabetes.47.10.1643
- Gayoso-Diz P, Otero-González A, Rodriguez-Álvarez MX, Gude F, García F, De Francisco A, González-Quintela A. (2013). 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 Endocrine Disorders. https://doi.org/10.1186/1472-6823-13-47
- Geloneze B, Vasques ACJ, Stabe CFC, Pareja JC, Rosado LEFPL, Queiroz EC, Tambascia MA. (2009). HOMA1-IR and HOMA2-IR indexes in identifying insulin resistance and metabolic syndrome: Brazilian Metabolic Syndrome Study (BRAMS). Arquivos Brasileiros de Endocrinologia & Metabologia. https://doi.org/10.1590/S0004-27302009000200020
- Knopp JL, Holder-Pearson L, Chase JG. (2019). Insulin Units and Conversion Factors: A Story of Truth, Boots, and Faster Half-Truths. Journal of Diabetes Science and Technology. https://doi.org/10.1177/1932296818805074
- Manley SE, Stratton IM, Clark PM, Luzio SD. (2007). Comparison of 11 Human Insulin Assays: Implications for Clinical Investigation and Research. Clinical Chemistry. https://doi.org/10.1373/clinchem.2006.077784
- Manley SE, Luzio SD, Stratton IM, Wallace TM, Clark PMS. (2008). Preanalytical, Analytical, and Computational Factors Affect Homeostasis Model Assessment Estimates. Diabetes Care. https://doi.org/10.2337/dc08-0097
- Dietrich JW, Dasgupta R, Anoop S, Jebasingh FK, Kurian ME, Inbakumari M, Boehm BO, Thomas N. (2022). SPINA Carb: a simple mathematical model supporting fast in-vivo estimation of insulin sensitivity and beta cell function. Scientific Reports. https://doi.org/10.1038/s41598-022-22531-3
- Dietrich JW, Abood A, Dasgupta R, Anoop S, Jebasingh FK, Spurgeon R, Thomas N, Boehm BO. (2024). A novel simple disposition index (SPINA-DI) from fasting insulin and glucose concentration as a robust measure of carbohydrate homeostasis. Journal of Diabetes. https://doi.org/10.1111/1753-0407.13525
- Simental-Mendía LE, Rodríguez-Morán M, Guerrero-Romero F. (2008). The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metabolic Syndrome and Related Disorders. https://doi.org/10.1089/met.2008.0034
- Bello-Chavolla OY, Almeda-Valdés P, Gómez-Velasco D, Viveros-Ruiz T, Cruz-Bautista I, Romo-Romo A, Sánchez-Lázaro D, Meza-Oviedo D, Vargas-Vázquez A, Aguilar-Salinas CA. (2018). METS-IR, a novel score to evaluate insulin sensitivity, is predictive of visceral adiposity and incident type 2 diabetes. European Journal of Endocrinology. https://doi.org/10.1530/EJE-17-0883

_Full tool: https://longevity-germany.com/en/tools/homa-ir_

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_Canonical: https://longevity-germany.com/en/tools/homa-ir · Part of Longevity Cities · Updated 2026-06-14_