Long-term body roundness patterns predict type 2 diabetes risk

Researchers analyzing data from the China Health and Retirement Longitudinal Study have identified distinct longitudinal patterns in the Body Roundness Index that independently predict the development of type 2 diabetes in middle-aged and older adults. The study, published in Diabetology & Metabolic Syndrome, utilized group-based trajectory modeling to characterize these patterns over a five-year period and assessed their association with incident diabetes cases during a subsequent four-year follow-up.

The Body Roundness Index is described as an anthropometric measure that assesses visceral adiposity, offering a potentially superior alternative to traditional body mass index for this specific purpose. The research team focused on a cohort of 4,965 participants aged 45 years and older from the CHARLS dataset. By applying group-based trajectory modeling to data collected between 2011 and 2016, the investigators were able to categorize participants into distinct groups based on their evolving BRI values. This methodological approach allowed for the identification of stable patterns in body roundness over time, which were then linked to health outcomes observed in later years.

The analysis revealed three distinct BRI trajectory patterns among the participants: a low-stable group comprising 43.8% of the cohort, a moderate-stable group comprising 37.8%, and a high-stable group comprising 18.4%. These groups represented consistent levels of body roundness over the initial observation period. During the follow-up period from 2017 to 2020, which averaged 4.92 years, 387 cases of incident type 2 diabetes were identified through self-reported physician diagnosis. The incidence rate of new diabetes cases in this cohort was 7.79%, providing the outcome variable for the subsequent risk analysis.

Using Cox proportional hazards regression, the study examined the association between the identified BRI trajectory patterns and the risk of developing diabetes. When compared to the low-stable group, both the moderate-stable and high-stable trajectories demonstrated progressively elevated risks. The fully adjusted hazard ratio for the moderate-stable group was 1.71, with a 95% confidence interval ranging from 1.29 to 2.26. For the high-stable group, the fully adjusted hazard ratio was 2.61, with a 95% confidence interval ranging from 1.78 to 3.84. The P-value for trend was less than 0.001, indicating a statistically significant dose-response relationship between higher BRI trajectory levels and increased diabetes risk.

The study also evaluated the incremental predictive value of incorporating BRI trajectories into existing risk models. Receiver operating characteristic curve analysis showed that adding BRI trajectories improved the area under the curve from 0.613 to 0.635, with a P-value of 0.011. Additionally, the continuous Net Reclassification Improvement was 27.62%, with a P-value less than 0.001, and the Integrated Discrimination Index was also assessed to determine the enhancement in predictive capacity. These statistical measures suggest that longitudinal BRI patterns provide additional information beyond conventional risk factors for predicting incident type 2 diabetes.

The findings suggest that long-term monitoring of Body Roundness Index trajectories may enhance diabetes risk stratification and inform prevention strategies. The clear dose-response relationship observed between BRI patterns and diabetes incidence supports the utility of this anthropometric measure in longitudinal health assessments.

The study was conducted using data from the China Health and Retirement Longitudinal Study, a large-scale survey of Chinese adults aged 45 and older.

Limitations of the study include the reliance on self-reported data for diabetes diagnosis and the specific demographic context of the CHARLS cohort. The findings are based on associations and predictive models, and while the dose-response relationship is strong, causation cannot be definitively established from this observational design. The study contributes to the growing body of evidence supporting the use of advanced anthropometric measures in chronic disease risk prediction, particularly in Chinese populations where traditional BMI may not fully capture visceral adiposity risks.

Subject of Research: Longitudinal association between Body Roundness Index trajectories and incident type 2 diabetes in a Chinese cohort

Article Title: Body roundness index trajectories and incident type 2 diabetes: a longitudinal analysis from the China Health and Retirement Longitudinal Study

Article References: Huang, L., Zeng, J., Zhang, S., Lu, J., & Zhu, Y. (2026). Body roundness index trajectories and incident type 2 diabetes: a longitudinal analysis from the China Health and Retirement Longitudinal Study. Diabetology & Metabolic Syndrome. https://doi.org/10.1186/s13098-026-02298-7

Image Credits: AI Generated

DOI: 10.1186/s13098-026-02298-7

Keywords: Body Roundness Index, Type 2 Diabetes, China Health and Retirement Longitudinal Study, Visceral Adiposity, Trajectory Modeling, Epidemiology, Risk Prediction, Anthropometry, Body, roundness, index, trajectories