Insulin resistance is the quiet overture to some of the most consequential diseases of modern life. Long before blood sugar climbs into the diabetic range, the body’s tissues begin to ignore insulin’s signals, forcing the pancreas to pump out ever-larger quantities of the hormone to keep glucose in check. Detecting this hidden state early could transform prevention, yet the gold-standard assessments remain cumbersome for everyday clinical practice. A new cross-sectional study published in BMC Endocrine Disorders offers a refreshingly pragmatic answer: two numbers that already sit on almost every routine blood panel—triglycerides and the ratio of triglycerides to high-density lipoprotein cholesterol—may help flag insulin resistance in people who do not have diabetes.
The research, led by Özden Gökdemir of the Department of Family Medicine at İzmir University of Economics together with Olgu Aygün and Ayça Asma Sakallı, took a retrospective look at the medical records of adults who attended the Göztepe District Family Medicine Outpatient Clinic of Bozyaka Training and Research Hospital in Turkey between August 2021 and August 2023. From that window, the team assembled a cohort of 1,532 individuals aged 18 and over, all of whom had the laboratory measurements needed to calculate insulin resistance directly. Crucially, rather than relying on values recorded in the charts, the investigators recalculated the homeostatic model assessment of insulin resistance, or HOMA-IR, for every participant from the raw fasting glucose and fasting insulin measurements using the standard formula: fasting glucose in milligrams per deciliter multiplied by fasting insulin in microunits per milliliter, divided by 405.
HOMA-IR is a mathematical shorthand for how hard the pancreas must work to maintain normal blood sugar. Higher values indicate that more insulin is required to achieve the same glucose control, which is the essence of insulin resistance. The researchers drew a line at 2.5, a commonly used threshold: participants above it formed the case group of 428 people, while the 1,104 participants at or below it served as controls. This stratification allowed the team to ask a deceptively simple question—which routinely measured blood parameters separate insulin-resistant individuals from their insulin-sensitive peers?
The answer, at first glance, was a familiar cast of metabolic suspects. Compared with controls, the insulin-resistant group was significantly older and showed higher neutrophil counts, fasting glucose, glycated hemoglobin (HbA1c), triglycerides, insulin, HOMA-IR, and triglyceride-to-HDL cholesterol ratios, alongside lower levels of high-density lipoprotein cholesterol, the so-called good cholesterol. Total cholesterol and low-density lipoprotein cholesterol, the targets of most conventional cholesterol screening, did not differ significantly between the groups. That last detail carries a subtle but important message: the standard lipid panel’s headline numbers may look reassuring in someone whose metabolism is quietly unraveling, while the relationship between triglycerides and HDL cholesterol tells a more revealing story.
Sex mattered as well. Women had significantly higher HDL cholesterol levels than men in both groups, a difference that held with a p-value below 0.001. This biological gap is well recognized—estrogen tends to raise HDL cholesterol—and it underscores why sex-adjusted interpretation of lipid markers matters when clinicians are trying to gauge metabolic risk. The study’s statistical machinery accounted for this by adjusting its final models for both age and sex, ensuring that the associations reported were not merely artifacts of demographic differences between the groups.
Correlation analysis revealed one of the strongest relationships in the dataset: triglycerides and the TG/HDL-C ratio moved together almost in lockstep, with a correlation coefficient of roughly 0.9 in both the case and control groups and a p-value below 0.001. This near-identity is not surprising to lipid biochemists, since the ratio is literally constructed from triglyceride levels divided by HDL cholesterol, but it raises a practical question—if the two measures carry nearly the same information, does the ratio add anything beyond triglycerides alone? The answer lies in how each performs as a screening tool and how they behave in multivariable models, where the ratio ultimately outlasted its components.
To quantify how well each candidate marker could discriminate between insulin-resistant and insulin-sensitive individuals, the team turned to receiver operating characteristic, or ROC, curve analysis. This technique plots true-positive rates against false-positive rates across all possible cut-off values, and the area under the resulting curve, or AUC, expresses discriminative ability on a scale from 0.5, equivalent to a coin flip, to 1.0, perfect classification. Triglycerides achieved an AUC of 0.641, with a 95 percent confidence interval of 0.610 to 0.672, and an optimal cut-off of at least 106 milligrams per deciliter. The TG/HDL-C ratio performed comparably, with an AUC of 0.644 (95 percent confidence interval 0.612 to 0.675) and a cut-off of at least 1.96. These are modest numbers—useful signal, but far from diagnostic certainty.
The neutrophil-to-lymphocyte ratio, or NLR, told a very different story. This marker, calculated simply by dividing the absolute neutrophil count by the absolute lymphocyte count from a standard complete blood count, has attracted enormous attention in recent years as a cheap, widely available proxy for systemic inflammation. Because low-grade inflammation is implicated in the pathogenesis of insulin resistance and type 2 diabetes, many researchers have hoped the NLR could serve as an early-warning flag. In this cohort, the hope did not materialize. The NLR showed an AUC of just 0.517—statistically indistinguishable from random guessing—and in the multivariable logistic regression adjusted for age and sex, it carried an odds ratio of 0.99 with a p-value of 0.712, meaning it contributed essentially nothing to predicting insulin resistance once other factors were considered.
The TG/HDL-C ratio, by contrast, remained independently associated with insulin resistance even after adjustment, with an odds ratio of 1.20 per unit increase (95 percent confidence interval 1.13 to 1.27; p < 0.001). In plain terms, every one-unit rise in the ratio was associated with a 20 percent increase in the odds of being insulin resistant. This durability across statistical models matters, because it suggests the association is not simply explained by the insulin-resistant group being older or by sex differences in lipid physiology. The result aligns with a growing international literature linking the TG/HDL-C ratio—and related indices such as the triglyceride-glucose index and its body mass index and waist circumference variants—to metabolic dysfunction across diverse populations.
Why would this particular ratio track insulin resistance so faithfully? The mechanistic story begins in the liver. When insulin’s ability to suppress fat breakdown in adipose tissue falters, more free fatty acids flood the liver, driving hepatic triglyceride production and the release of triglyceride-rich very-low-density lipoprotein particles into the bloodstream. At the same time, insulin resistance is entangled with lower HDL cholesterol, partly through the activity of cholesteryl ester transfer protein, which shuttles lipids between lipoprotein classes and tends to deplete HDL of its cholesterol cargo when triglycerides are abundant. The result is a lipid signature—high triglycerides, low HDL—that is both a consequence and a companion of insulin resistance, and the TG/HDL-C ratio captures it in a single, easily computed figure.
The authors are careful about what their findings do and do not support. With AUC values hovering in the mid-0.6s, neither triglycerides nor the TG/HDL-C ratio can stand alone as a diagnostic test for insulin resistance; their discriminative ability is too modest for that burden. Instead, the study positions them as adjunctive screening indices—simple, practical, and accessible numbers that a family physician can glance at during a routine visit and use to decide whether deeper investigation, such as fasting insulin measurement and formal HOMA-IR calculation, is warranted. In primary care settings where specialized metabolic testing is scarce or costly, that kind of triage tool has genuine value.
The study’s design also imposes limits worth keeping in view. As a retrospective, cross-sectional analysis of a single outpatient clinic population, it captures a snapshot rather than a trajectory, and it cannot establish that lipid changes precede insulin resistance rather than accompany it. The cohort is drawn from one Turkish hospital network, and the cut-off values identified—106 milligrams per deciliter for triglycerides and 1.96 for the ratio—may require recalibration in populations with different ancestry, diet, and baseline metabolic risk. The HOMA-IR threshold of 2.5, while widely used, is itself a convention rather than a universal biological constant.
Even with those caveats, the message for the public is compelling. Millions of people walk around with undiagnosed insulin resistance, feeling perfectly well while their metabolism quietly drifts toward type 2 diabetes, fatty liver disease, and cardiovascular trouble. This study suggests that the first clue may already be sitting in the blood work ordered at an ordinary checkup. A triglyceride level creeping past 106 milligrams per deciliter, or a TG/HDL-C ratio above roughly 2, is not a diagnosis—but it is a nudge, a cheap and early signal that the conversation about metabolic health should happen now, not after glucose numbers cross the line.
Subject of Research: The association between lipid parameters, the neutrophil-to-lymphocyte ratio, and insulin resistance in non-diabetic individuals
Article Title: Evaluation of the relationship between lipid parameters, neutrophil-to-lymphocyte ratio, and insulin resistance in non-diabetic individuals: a cross-sectional analysis
Article References: Evaluation of the relationship between lipid parameters, neutrophil-to-lymphocyte ratio, and insulin resistance in non-diabetic individuals: a cross-sectional analysis. (n.d.). https://doi.org/10.1186/s12902-026-02566-7
Image Credits: AI Generated
DOI: 10.1186/s12902-026-02566-7
Keywords: insulin resistance, triglycerides, TG/HDL-C ratio, neutrophil-to-lymphocyte ratio, HOMA-IR, HDL cholesterol, metabolic syndrome, prediabetes, type 2 diabetes, cross-sectional study, primary care, lipid metabolism
Daisy Hatcher. (October 4, 2026). Simple Blood Fat Ratio Flags Hidden Insulin Resistance Before Diabetes Strikes. Scienmag.
