Association between the changes in the C-reactive protein-triglyceride-glucose index and future cardiometabolic multimorbidity risk: a nationwide cohort study

For millions of people, the path to a serious health crisis does not begin with a single, sudden event. Instead, it often starts as a slow, quiet accumulation of small metabolic problems. Two of the most common drivers of this process are insulin resistance and chronic inflammation. Insulin resistance occurs when the body's cells stop responding properly to insulin, the hormone that regulates blood sugar, forcing the pancreas to work harder and eventually leading to conditions like diabetes. Chronic inflammation is a state where the body's immune system remains constantly active at a low level, damaging blood vessels and tissues over time. While doctors have long known that these two processes often travel together, measuring them has usually meant looking at them separately. A patient might get a blood test for inflammation markers and another for blood sugar, but these snapshots rarely tell the full story of how these forces interact over years to create a perfect storm for heart disease, stroke, and diabetes.

A new study published by researchers from the China-Japan Friendship Hospital and the Chinese Academy of Medical Sciences seeks to bridge this gap by looking at the long-term dance between inflammation and metabolism. The researchers focused on a specific group of people in China, tracking them over nearly a decade to see if a combined measure of these two factors could predict who would develop cardiometabolic multimorbidity. This condition, which the study defines as having at least two of the major diseases—diabetes, heart disease, or stroke—at the same time, is particularly dangerous because it drastically increases the risk of death and disability compared to having just one of these conditions. By moving beyond a single test and instead looking at how these numbers change over time, the team hoped to find a better way to spot trouble before it becomes irreversible.

The researchers turned to the China Health and Retirement Longitudinal Study, a massive, nationally representative survey that follows adults aged 45 and older across the country. From an initial pool of over 17,000 participants, they carefully selected 4,425 people who were healthy enough at the start of the study to not already have the combination of diseases they were looking for. These volunteers had their blood drawn and their health histories recorded at multiple points between 2011 and 2020. The team calculated a new score for each person, which they called the C-reactive protein-triglyceride-glucose index. This score was not a magic number but a practical combination of two existing measurements: a blood test for C-reactive protein, which signals inflammation, and a calculation based on fasting triglycerides and glucose, which reflects insulin resistance. By merging these two distinct biological signals into one metric, the researchers created a tool designed to capture the total burden of metabolic and inflammatory stress on the body.

To understand how this score predicts future health, the team did not just look at a single measurement taken at the beginning of the study. They examined three different ways the score could be used. First, they looked at the baseline level, or the score a person had when the study began. Second, they calculated a cumulative burden, which essentially averaged the scores over the years to see how much total exposure a person had to high levels of inflammation and insulin resistance. Third, they tracked the trajectory, or the pattern of change, to see if a person's score stayed high, went up, went down, or fluctuated. They then followed these 4,425 individuals for several years to see who developed the combination of heart disease, stroke, or diabetes.

The results were clear and consistent. During the follow-up period, 423 participants, or about 9.6% of the group, developed the multimorbidity condition. The risk of this happening was strongly linked to the scores. People who started with the highest levels of the combined index were significantly more likely to develop the diseases than those with the lowest levels. Specifically, those in the highest quarter of the group had more than two and a half times the risk of developing the condition compared to those in the lowest quarter. This relationship held true even after the researchers adjusted for other factors like age, sex, smoking, alcohol use, and body mass index. The study also found that the cumulative burden was an even stronger predictor; people who maintained high scores over time faced nearly three times the risk of those with low cumulative scores.

Perhaps the most revealing part of the study was the analysis of how these scores changed over time. The researchers identified four distinct patterns of change among the participants. One group maintained low scores throughout the study, while another group started low but saw their scores rise. A third group started high and stayed high, and a fourth group had consistently high levels from the start. The group that faced the greatest danger was the one with persistently high scores. These individuals, who maintained high levels of inflammation and insulin resistance year after year, had the highest risk of developing the combined diseases. This finding suggests that it is not just a single bad blood test that matters, but the sustained pressure of these biological stressors on the body over many years.

The study also compared this new combined index against the individual components used to build it. When the researchers tested how well the combined score predicted future disease compared to looking at inflammation alone or insulin resistance alone, the combined score performed better. It was able to distinguish between those who would get sick and those who would not with greater accuracy. Furthermore, the cumulative version of the score, which accounted for exposure over time, proved to be the most accurate predictor of all. This suggests that tracking these numbers repeatedly over time provides a much clearer picture of risk than a single snapshot ever could.

The researchers also looked at whether these findings held up in different groups of people. They found that the link between high scores and disease risk was consistent across men and women, younger and older adults, and those living in rural or urban areas. Interestingly, the association was actually stronger in people who did not already have diagnosed diabetes or high blood pressure. This implies that the combined score might be particularly useful for identifying risk in people who appear healthy on the surface but are carrying a hidden metabolic burden. For those who already have diagnosed conditions, the link was weaker, possibly because they were already receiving treatment that altered their blood markers or slowed the progression of the disease.

While the study offers compelling evidence, the authors are careful to note its limitations. Because the data came from self-reported diagnoses and a specific population in China, the results may not apply perfectly to every person everywhere. Additionally, because this was an observational study, it shows a strong connection but cannot prove that the high scores directly cause the diseases. However, the consistency of the results across different statistical models and the robust nature of the data provide a strong foundation for future research. The study concludes that monitoring this combined index over time could be a practical and effective way to identify people at high risk for serious health problems long before they become apparent. By catching the early signs of this metabolic and inflammatory struggle, doctors and patients might be able to intervene sooner, potentially preventing the onset of multiple chronic diseases and improving the quality of life for millions of people.