A Simple Blood Test Index May Flag Hidden Diabetes Risk in Lean Adults

Being slim has long been treated as a free pass at the doctor’s office. A new study suggests that assumption may be dangerously misleading for millions of middle-aged and older adults. Researchers analyzing health screening data from nearly 20,000 normal-weight Chinese adults found that a simple, inexpensive index calculated from three routine blood measurements—total cholesterol, high-density lipoprotein cholesterol, and fasting plasma glucose—strongly predicted who would go on to develop prediabetes or diabetes. The findings, published in Frontiers in Nutrition, are striking not just because the index worked, but because of how it worked: the relationship was sharply nonlinear, with risk climbing steeply up to a specific threshold and then flattening out entirely.

The index in question, known as the CHG index, is calculated as the natural logarithm of total cholesterol multiplied by fasting plasma glucose, divided by twice the HDL cholesterol level. Each component captures a different facet of metabolic health. Fasting glucose reflects how well the liver regulates blood sugar and how effectively pancreatic beta cells are functioning. Total cholesterol and HDL cholesterol together describe the lipid environment: high total cholesterol paired with low HDL is the classic signature of atherogenic dyslipidemia, the lipid disturbance that typically accompanies insulin resistance. By multiplying these values together, the index integrates lipid burden, reverse cholesterol transport capacity, and glycemic status into a single number that can be derived from blood tests already performed in virtually every health checkup.

What makes the new research notable is the population it examined. Most studies of metabolic risk indices have included people across all body mass index categories or focused on those who are overweight or obese. Lean individuals have been largely marginalized in metabolic research, precisely because their normal weight is assumed to signal metabolic health. Yet clinicians have long recognized a phenotype called metabolically obese normal weight—people who appear lean on the outside but harbor visceral fat accumulation and peripheral insulin resistance on the inside. Their cardiovascular and atherosclerotic risks can rival those of people with overt obesity, but because conventional risk scoring relies heavily on anthropometric measures like BMI, this population is chronically underidentified.

The research team, led by Junling Ding and Zhimao Cai of Shenzhen Second People’s Hospital, drew on a multicenter retrospective cohort of health examination participants screened between 2010 and 2016 at 32 sites across 11 Chinese cities. From an initial pool of more than 211,000 adults, they applied strict eligibility criteria: participants had to be at least 45 years old, have a BMI between 18.5 and 23.9 kilograms per square meter, and be free of prediabetes and diabetes at baseline. After excluding those with missing or implausible laboratory values, the final analytic cohort comprised 19,981 adults with a mean age of about 56 years, roughly 43 percent of them men. Participants were followed for an average of 3.19 years, during which the researchers tracked new cases of prediabetes, defined as fasting glucose reaching 5.6 millimoles per liter or higher, and self-reported diagnosed diabetes.

The results were unambiguous. In fully adjusted Cox proportional hazards models that accounted for age, sex, blood pressure, BMI, LDL cholesterol, kidney and liver markers, and family history of diabetes, each one-unit increase in the CHG index was associated with a 2.20-fold increase in the hazard of developing prediabetes or diabetes. When participants were divided into quartiles, those in the second, third, and fourth quartiles faced 42 percent, 86 percent, and 91 percent higher risks, respectively, compared with the lowest quartile. Kaplan-Meier survival curves showed the groups diverging early in follow-up, with the highest-quartile group consistently showing the lowest probability of remaining free of dysglycemia.

The most intriguing finding emerged when the researchers used smooth curve fitting and two-piecewise regression to probe the shape of the relationship. Rather than a straight line, the association displayed a clear inflection point at a CHG index value of 5.07. Below that threshold, each unit increase in the index was associated with a staggering 6.39-fold increase in risk. Above it, the association essentially vanished, with a hazard ratio of 1.02 that was statistically indistinguishable from no effect. A log-likelihood ratio test confirmed that the nonlinear model fit the data significantly better than a linear one.

The authors interpret this threshold effect as a possible biological saturation phenomenon. In the early phase of metabolic deterioration, rising fasting glucose, increasing total cholesterol, and falling HDL cholesterol jointly reflect accelerating insulin resistance and progressive beta-cell exhaustion, so each increment in the index corresponds to a disproportionately rapid rise in disease risk. Once metabolic dysregulation passes a critical severity, the system may have already entered a state of advanced decompensation, where further increases in the index no longer translate into additional risk elevation. In other words, the index may be most useful precisely in the window when intervention can still prevent disease—a potentially valuable property for a screening tool.

Subgroup analyses added further nuance. The association was stronger in women than in men, with hazard ratios of 2.65 and 1.77 respectively, and stronger in participants under 60 than in those 60 and older, with hazard ratios of 2.51 and 1.65. The authors suggest that sex differences in body fat distribution, which are well documented and linked to differential cardiometabolic risk, may explain the gender gap, while age-related changes such as sarcopenia, hormonal shifts, and cumulative exposure to multiple risk factors may dilute the relative contribution of the CHG index in older adults. Family history of diabetes did not meaningfully modify the association. A sensitivity analysis using E-values, which quantify how strong an unmeasured confounder would need to be to explain away an observed association, yielded a value of 3.82, suggesting the findings are reasonably robust.

Mechanistically, the index makes physiological sense. Elevated fasting glucose directly signals impaired hepatic glucose homeostasis and declining beta-cell function. In insulin-resistant states, increased hepatic de novo lipogenesis and very-low-density lipoprotein secretion, combined with reduced reverse cholesterol transport, produce exactly the pattern of raised total cholesterol and reduced HDL that pushes the index upward. These lipid abnormalities not only promote atherosclerosis but also exacerbate pancreatic lipotoxicity, further compromising beta-cell function. Chronic low-grade inflammation and oxidative stress, which are intertwined with both dyslipidemia and hyperglycemia, may mediate part of the pathway, and the authors note that related molecular mechanisms—including sirtuin proteins, inflammatory cascades, and programmed cell death pathways—are increasingly implicated in diabetic complications.

The study has limitations that temper enthusiasm. As a retrospective observational cohort, it cannot establish causality, and because the population was exclusively Chinese, generalizability to other ethnic groups remains uncertain. Residual confounding from unmeasured factors such as diet, physical activity, and socioeconomic status cannot be excluded, and smoking and drinking data were missing for more than 76 percent of participants, preventing their inclusion in adjusted models. The average follow-up of just over three years may also miss longer-term risk trajectories. Still, the core message is compelling: a number that costs almost nothing to compute from routine blood work may reveal hidden metabolic vulnerability in lean adults whom conventional screening would overlook. The authors call for large prospective cohorts to confirm the findings and establish causality, but if the results hold, the CHG index could become a practical tool for catching prediabetes early in a population that has too often been told its normal weight means it has nothing to worry about.

Subject of Research: The nonlinear association between the CHG metabolic index and incident prediabetes and diabetes in normal-weight middle-aged and older Chinese adults

Article Title: Nonlinear association of cholesterol, high-density lipoprotein, and glucose index with the risk of prediabetes and diabetes in normal-weight middle-aged and older Chinese adults: a multicenter retrospective cohort study

Article References: Ding, J., Cai, Z., Wang, X., Qin, L., & Chen, W. (2026). Nonlinear association of cholesterol, high-density lipoprotein, and glucose index with the risk of prediabetes and diabetes in normal-weight middle-aged and older Chinese adults: a multicenter retrospective cohort study. Frontiers in Nutrition, 13, Article 1949954. https://doi.org/10.3389/fnut.2026.1949954

Image Credits: AI Generated

DOI: 10.3389/fnut.2026.1949954

Keywords: CHG index, prediabetes, diabetes, normal weight, insulin resistance, HDL cholesterol, fasting glucose, cohort study, nonlinear association, threshold effect, metabolic health, China