Google Search Results: “HOMA-IR (Homeostasis Model Assessment of Insulin Resistance)”

Today, I review, link to, and excerpt from Google Search Results: “HOMA-IR (Homeostasis Model Assessment of Insulin Resistance)”.

All that follows is from the above resource.

AI Overview

HOMA-IR (Homeostasis Model Assessment of Insulin Resistance) is a widely used formula that estimates insulin resistance by using your fasting glucose and fasting insulin levels, helping assess risk for conditions like type 2 diabetes or metabolic syndrome. A higher HOMA-IR score indicates greater insulin resistance, meaning your body struggles to use insulin effectively, while lower scores suggest better insulin sensitivity. It’s calculated by multiplying fasting glucose (mg/dL) by fasting insulin (μU/mL) and dividing by 22.5, with values generally above 1.9 suggesting early resistance. 

How it works

• Formula:(Fasting Glucose (mg/dL) x Fasting Insulin (μU/mL)) / 22.5.

• Fasting Requirement:You must fast for 8-10 hours (only water allowed) for an accurate blood sample.

What the numbers mean (General Guidelines)

• < 1.0:Insulin sensitive (good).

• ~1.0:Optimal.

• > 1.9:Early insulin resistance.

• > 2.9:Significant insulin resistance.

• Note:Cut-off points can vary by population and BMI, with higher BMIs often showing higher HOMA-IR values.

What it’s used for

• Assessing risk for metabolic syndrome, type 2 diabetes, and cardiovascular disease.

• Monitoring effectiveness of lifestyle changes or medications.

• Epidemiological studies to understand population health trends.

Limitations

• It’s an estimate, not a direct measure, and can be less accurate in certain groups (e.g., those with normal BMI, elderly).

• It’s not recommended for patients already taking insulin.

From MDCalc:

HOMA-IR (Homeostatic Model Assessment for Insulin Resistance) Approximates insulin resistance:

Fig1 when server ready.

Next Steps:

ADVICE

• There is no universally accepted single cutoff:
  • Values between 2.0 and 3.0 are commonly used in U.S. clinical and research settings.
  • A cutoff of ≥2.5 is used in NHANES (National Health and Nutrition Examination Survey) to indicate insulin resistance.
• Consider the population and context of use:
  • A study of U.S. adults without diabetes (NHANES III) found a HOMA-IR median of 2.2, mean of 2.8, and a standard deviation of 2.4.
  • A study of U.S. adolescents found a mean HOMA-IR of 2.3 in normal-weight individuals and 4.9 in individuals with obesity (>50% of whom had insulin resistance).
  • Internationally, cutoffs for metabolic syndrome and dysglycemia are lower in Asian populations, typically ranging from 1.4 to 2.5.

MANAGEMENT

• There are no validated management algorithms or guidelines that use this score; however, lifestyle modification is the foundation for reversing early-onset insulin resistance.
• High-intensity interval training (HIIT) or concurrent resistance training combined with a Mediterranean or plant-based diet yields the greatest improvement in HOMA-IR, with practical implementation involving 2–3 sessions per week and a diet rich in fiber, whole grains, fruits, vegetables, and unsaturated fats.
• If lifestyle modifications are insufficient, pharmacological therapy targeting weight loss and cardiovascular comorbidities should be employed.
  • Weight loss of 5%–10% can substantially improve insulin sensitivity; for this reason, glucagon-like peptide-1 (GLP-1)  receptor agonists or dual GLP-1/glucose-dependent insulinotropic polypeptide (GIP) agonists, such as tirzepatide, can be prescribed.
  • Metformin can also play a role, but it is generally less effective than GLP-1 receptor agonists or dual agonists.

Evidence:

FORMULA

Score = (Fasting insulin, uIU/mL)*(Fasting glucose, mg/dL) / 405

Facts & Figures

A score of ≥2.5 is generally considered indicative of insulin resistance, but the optimal cutoff may vary by population and clinical context.

Evidence Appraisal

The HOMA-IR calculator was developed in 1985 through a comparative study using a computer-solved model. The study was a mathematical modeling analysis based on published physiological data rather than a clinical trial with direct patient enrollment. The estimated insulin resistance obtained by the calculator correlated well with estimates obtained using the euglycemic clamp (Spearman’s rank correlation coefficient/Rs = 0.88, p <0.0001), the fasting insulin concentration (Rs = 0.81, p <0.0001), and the hyperglycemic clamp, (Rs = 0.69, p <0.01). The study introduced a novel, noninvasive surrogate for insulin resistance with strong correlations to gold standard measures. However, it was based on a simplified feedback loop that may not have captured dynamic physiology. In addition, the coefficients of variation were high (31% for insulin resistance and 32% for β-cell function) indicating poor reproducibility and insufficient accuracy for therapeutic decision-making.

The calculator was validated in a study published in 2000 by Bonora et al. This cross-sectional validation study included 53 patients with diabetes and 62 patients without diabetes and evaluated whether HOMA-IR is a reliable surrogate measure of in vivo insulin sensitivity in humans. Patients receiving insulin therapy, those with recent acute illness, or those with clinical evidence of cardiovascular, kidney, or liver disease were excluded. The study demonstrated a strong correlation between HOMA-IR and clamp-derived glucose disposal (overall r = −0.82, p <0.0001), with no substantial differences in correlation between patients with and without diabetes. The authors concluded that HOMA-IR can be reliably used in large-scale or epidemiological studies. Katsuki et al., using a univariate regression analysis, further validated the calculator by demonstrating a significant correlation between log-transformed HOMA-IR and log-transformed clamp insulin resistance both before (r = -0.613, p <0.0001) and after treatment (r = -0.734, p <0.0001) in 55 Japanese patients with type 2 diabetes. Ikeda et al. and Sarafidis et al. reported similar findings in patients with diabetes and hypertension.

A more recent meta-analysis conducted by Otten et al. showed that log-transformed HOMA-IR had a pooled correlation coefficient of −0.60 (95% CI: −0.66 to −0.53) across 22 studies. Although the correlation was significant, it was lower than that observed with other fasting indices of insulin resistance, such as revised QUICKI (r = 0.68), and OGTT-based indices, such as the Matsuda and Stumvoll MCR indices (r ≈ 0.70).

Importantly, no major clinical guidelines from prominent organizations like the American Diabetes Association or the European Association for the Study of Diabetes endorse HOMA-IR for routine clinical use. An impact analysis by Wallace et al. demonstrated that while HOMA-IR is validated against gold standard methods and useful for large-scale studies, its reliability depends on input data quality and appropriate interpretation. The authors also caution against using HOMA-IR to assess β-cell function in isolation or in clinical scenarios where dynamic testing is more appropriate.