Researchers studied over 9,700 American adults to understand what body measurements and blood markers predict prediabetes—a condition where blood sugar is higher than normal but not yet diabetic. They found that people with more belly fat (adjusted for body weight) and an unhealthy cholesterol ratio had significantly higher chances of developing prediabetes. Interestingly, the cholesterol ratio appeared to explain about 10% of how belly fat increases prediabetes risk. These findings suggest that doctors could use these two simple measurements to identify people at risk early, before they develop diabetes, allowing them to make lifestyle changes to prevent the disease.

The Quick Take

  • What they studied: Whether belly fat (measured in a special way) and cholesterol ratios can predict who will develop prediabetes
  • Who participated: 9,713 American adults aged 20-80 years old (average age 51), representing a mix of the general U.S. population from national health surveys
  • Key finding: People with higher belly fat measurements were 55% more likely to have prediabetes, and those with worse cholesterol ratios were 20% more likely to have it. The cholesterol ratio explained about 10% of the belly fat effect.
  • What it means for you: If you have excess belly fat or unhealthy cholesterol levels, you may want to talk with your doctor about prediabetes screening and consider lifestyle changes like diet and exercise. However, these measurements alone don’t diagnose prediabetes—only a blood test can do that.

The Research Details

This was a cross-sectional study, meaning researchers looked at a large group of people at one point in time rather than following them over years. They used data from NHANES (National Health and Nutrition Examination Survey), which is a nationally representative sample of American adults. Researchers measured belly fat using a special calculation called the weight-adjusted waist circumference index (WWI), which accounts for how much someone weighs. They also calculated a cholesterol ratio by dividing ‘bad’ cholesterol (non-HDL) by ‘good’ cholesterol (HDL). Then they used statistical methods to see which people had prediabetes and whether these measurements predicted it.

The researchers used several analytical approaches to understand the relationships. They performed logistic regression to calculate how much each measurement increased prediabetes risk. They also did subgroup analyses to see if the findings held true for men versus women, and different age groups. They used a special curved analysis to check if the relationships were linear or more complex. Finally, they performed mediation analysis to understand how much of the belly fat effect worked through the cholesterol ratio.

This research approach is important because it uses real-world data from a representative sample of Americans rather than a small, selected group. The large sample size (over 9,700 people) makes the findings more reliable. By examining multiple factors and their relationships, the study provides a more complete picture of prediabetes risk than looking at just one measurement alone. The mediation analysis is particularly valuable because it shows not just that two things are related, but how one might work through the other.

Strengths: The study used a large, nationally representative sample, which means findings likely apply to many Americans. Multiple statistical methods were used to verify findings. The researchers adjusted for many other factors that could affect results. Limitations: This is a snapshot in time, so we can’t prove that belly fat causes prediabetes—only that they’re associated. The study can’t account for unmeasured factors that might explain the relationship. The findings are specific to U.S. adults and may not apply to other populations.

What the Results Show

The study found that weight-adjusted belly fat measurement (WWI) was strongly linked to prediabetes risk. For every unit increase in this measurement, the odds of having prediabetes increased by 55% (with a 95% confidence interval of 46-64%). This means the relationship is fairly consistent and unlikely to be due to chance.

The cholesterol ratio (bad cholesterol divided by good cholesterol) was also significantly linked to prediabetes. For every unit increase in this ratio, the odds of having prediabetes increased by 20% (with a 95% confidence interval of 16-25%). This suggests that an unhealthy cholesterol profile is an independent risk factor.

When the researchers looked at different groups—men versus women, different age groups, and people with different body weights—the findings generally held true. This suggests these relationships are fairly consistent across different populations.

The relationship between both belly fat and cholesterol ratio with prediabetes was not perfectly linear. This means the risk doesn’t increase at a steady rate; instead, the risk may increase more sharply at certain levels.

The mediation analysis revealed that the cholesterol ratio explained approximately 10% of the effect of belly fat on prediabetes risk. This means that while belly fat increases prediabetes risk directly, some of that effect works through worsening the cholesterol ratio. The remaining 90% of belly fat’s effect works through other mechanisms not measured in this study, such as inflammation or insulin resistance.

These findings align with previous research showing that belly fat is particularly harmful for metabolic health, even more so than overall body weight. The link between cholesterol ratios and prediabetes has also been documented before. However, this study adds new information by showing how these two factors work together and quantifying the cholesterol ratio’s role in the belly fat-prediabetes relationship. The finding that cholesterol ratio partially mediates the belly fat effect provides a more detailed understanding of the biological pathway.

This study has several important limitations. First, it’s a snapshot study, so we can’t prove that belly fat causes prediabetes—only that they occur together. Second, the study only included U.S. adults, so findings may not apply to other countries or populations. Third, unmeasured factors (like physical activity, diet quality, or stress) could explain some of the relationships. Fourth, the study couldn’t account for medications people were taking that might affect cholesterol or blood sugar. Finally, the mediation analysis can only suggest how factors might work together, not prove causation.

The Bottom Line

Based on this research (moderate confidence): Have your doctor check your blood sugar and cholesterol levels if you have excess belly fat or an unhealthy cholesterol ratio. Consider lifestyle changes including regular physical activity (at least 150 minutes per week), eating a balanced diet rich in whole grains and vegetables, and maintaining a healthy weight. These changes may help reduce both belly fat and improve cholesterol ratios, potentially lowering prediabetes risk. Talk with your doctor or a registered dietitian about personalized recommendations.

This research is most relevant for adults aged 20-80 who are concerned about their metabolic health or have family history of diabetes. It’s particularly important for people who know they have excess belly fat or abnormal cholesterol levels. Healthcare providers should consider using these measurements for early screening. People without these risk factors may still benefit from general healthy lifestyle habits but don’t need to be overly concerned based on this study alone.

Changes in belly fat and cholesterol typically take 3-6 months of consistent lifestyle changes to show meaningful improvement. Prediabetes progression to diabetes usually takes several years, so there’s time to make changes. However, the sooner you address these risk factors, the better your chances of preventing or delaying diabetes development.

Want to Apply This Research?

  • Track waist circumference monthly (measure at the level of your belly button while standing) and record cholesterol levels from blood tests every 3-6 months. Monitor these alongside weight to calculate your weight-adjusted waist circumference trend.
  • Set a goal to reduce waist circumference by 1-2 inches over 3 months through a combination of 30 minutes of daily activity and reducing processed foods. Log daily physical activity and meals in the app to stay accountable.
  • Create a dashboard showing your waist circumference trend, cholesterol ratio (if available from lab results), and weight over time. Set reminders for quarterly blood work and monthly waist measurements. Track lifestyle behaviors (exercise minutes, vegetable servings) that directly influence these measurements.

This research provides observational evidence about associations between body measurements and prediabetes risk, but does not prove causation. These findings should not be used for self-diagnosis. Only a healthcare provider can diagnose prediabetes through blood tests (fasting glucose, A1C, or glucose tolerance test). If you have concerns about your metabolic health, belly fat, or cholesterol levels, consult with your doctor or a registered dietitian before making significant lifestyle changes. This information is for educational purposes and should not replace professional medical advice.