These 4 Factors May Increase Stroke Risk

Stroke is one of the leading causes of death worldwide, and though there were years of progress in reducing its impact, in recent years, strokes have become more and more common. Insulin resistance, a condition where the body becomes less sensitive to insulin, plays a key role in stroke recurrence and poor recovery, often linked to obesity and metabolic syndrome. With rising global obesity rates, conditions like insulin resistance and related stroke risks are becoming more common.

Measures like the triglyceride glucose (TyG) index, which indicates insulin resistance, and the weight-adjusted waist index (WWI), which evaluates fat distribution, have been shown to predict stroke risk. A new combined measure, the TyG-WWI index, has recently been linked to a higher risk of stroke in people with prediabetes, but its role in the general population is still unclear. Understanding how these markers work together could help improve stroke prevention.

To bridge this knowledge gap, researchers explored whether the TyG-WWI index health measure is linked to stroke risk in the general population. The goal was to find better ways to assess stroke risk, improve healthcare management and develop timely strategies to help people who are at high risk of having a stroke, and these results were published in the Journal of Stroke and Cerebrovascular Diseases.

How Was This Study Conducted?

The NHANES (National Health and Nutrition Examination Survey) is a large U.S. health study that collects data to monitor the nation’s health and nutrition. It uses a special sampling method to ensure the results represent the entire population. 

For this study, researchers analyzed NHANES data from 1999 to 2018, focusing on adults, resulting in 22,615 adults in the analysis. The main focus was on the health measure the TyG-WWI index, which combines triglyceride levels, blood sugar, body weight and waist size to assess health risks. Blood samples and body measurements were taken by trained professionals. 

Factors like age, sex, ethnicity, education, income and health conditions (such as diabetes, high blood pressure and heart disease) were also considered to better understand stroke risk. The data was then analyzed. 

What Did The Study Find?

The study looked at how TyG-WWI values—which reflect both the triglyceride glucose index and the weight-adjusted waist index—are linked to stroke risk. Researchers found that as TyG-WWI values increased, so did the risk of stroke. Initially, without considering any other factors, a rise in TyG-WWI values was linked to a 65% higher stroke risk. After accounting for age and sex, the increased risk dropped to 24%, and when all other factors were considered, it was 15%. 

To make it easier to compare, participants were divided into four groups based on their TyG-WWI values. Compared to the group with the lowest scores, the other groups had higher stroke risks: 37% higher in the group with the second lowest values, and 38% higher in the group with the very highest values. This finding indicates that higher TyG-WWI values were consistently linked to a greater risk of stroke.

The researchers also found a clear, linear relationship: as TyG-WWI values increased, so did stroke risk. This pattern was especially strong in younger participants and those without coronary heart disease. Other factors like sex, ethnicity, education and smoking or drinking habits didn’t significantly change this relationship.

This study has a few limitations to consider before applying the findings to the general population. First, because it was based on data collected at a single point in time, it is not possible to determine whether higher TyG-WWI values directly cause an increased risk of stroke. To establish a clear cause-and-effect relationship, future studies that follow participants over time are needed. 

Second, while we accounted for many factors that could influence the results, it’s possible that unknown factors still played a role, which the researchers couldn’t fully control for. Lastly, since this research focused on data from the U.S. population, it’s uncertain whether the findings apply to people in other countries. More studies are needed to confirm whether these results are consistent across different populations and settings.

How Does This Apply to Real Life?

The connection between the TyG-WWI index and stroke risk has real-world implications that could change how we approach stroke prevention. Think of the TyG-WWI index as a health “check engine” light; it combines key factors like blood sugar, triglycerides, body weight and waist size to give a snapshot of your metabolic health. 

For health care providers, this could become a powerful tool to spot people at higher risk of stroke early, even before any warning signs appear. For the rest of us, it’s a wake-up call to pay attention to things like weight management, blood sugar levels and fat distribution. With obesity and metabolic concerns on the rise, this kind of early detection could make a significant difference in preventing strokes and improving recovery outcomes.

If you’re concerned about your own blood sugar or cholesterol levels, checking in with a healthcare professional can be a good first step. You can also try to shake up your routine to incorporate more exercise and more healthy meals. We love using short, adaptable meal plans—like our weeklong No-Sugar High-Fiber Meal Plan for Insulin Resistance and our seven-day High-Fiber, No-Sugar Meal Plan for Weight Loss—as a simple and delicious way to reset your routine and discover new recipes.

Our Expert Take

This study published in the Journal of Stroke and Cerebrovascular Diseases sheds light on the important role the TyG-WWI index could play in understanding and managing stroke risk. By combining key health markers like blood sugar, triglycerides, body weight and waist size, this index offers a practical way to assess metabolic health and identify individuals who may be at higher risk of stroke. While more research is needed to confirm these findings across different populations and to establish a clear cause-and-effect relationship, the results are a step forward in improving how we approach stroke prevention.