# Fasting blood glucose trajectories and atherosclerosis risk: a longitudinal cohort study with threshold analysis in Chongqing, China

**Authors:** Na Li, Chun-Mei Fei, Feng Tang, Xian-Shu Lin, Bing-Rui Yang, Jun Guo, Li-An-Sheng Wu, Yin-Yin Xia, Chuan Zhang, Li Xu

PMC · DOI: 10.1186/s41043-025-01193-7 · Journal of Health, Population, and Nutrition · 2026-03-05

## TL;DR

This study shows that long-term blood sugar patterns are linked to heart disease risk, with lower thresholds in women and younger people in Chongqing, China.

## Contribution

The study identifies population-specific thresholds for fasting blood glucose linked to atherosclerosis risk, revealing a lower threshold than international standards.

## Key findings

- Prediabetes blood glucose patterns are linked to higher atherosclerosis risk prevalence and incidence.
- Atherosclerosis risk increases non-linearly with fasting blood glucose, with a threshold at 5.10 mmol/L.
- Women and younger individuals have lower thresholds for atherosclerosis risk.

## Abstract

Atherosclerosis, the primary pathological basis of cardiovascular diseases, exhibits a strong association with glucose metabolism dysregulation. While cross-sectional studies have linked fasting blood glucose (FBG) to atherosclerosis risk, the dose-response relationship and threshold characteristics of long-term FBG trajectories remain poorly characterized. This retrospective cohort study aimed to investigate longitudinal FBG trajectory patterns and their associations with atherosclerosis risk prevalence, incidence, and recovery in Chongqing, China, while also identifying population-specific risk thresholds.

Based on the three-year longitudinal follow-up data collected annually from 2017 to 2019, a population-based trajectory model (GBTM) was adopted to identify the dynamic trajectory of FBG. The association between FBG and atherosclerosis risk was analyzed using multivariable logistic regression. Restricted cubic splines (RCS) were used to assess the non-linear relationship between FBG and atherosclerosis risk and to determine risk thresholds. Confounding factors such as age, sex, body mass index (BMI), blood pressure, and lipids were adjusted for in the regression models, and subgroup analyses were performed to examine the interactions of age, sex, and BMI.

Longitudinal analysis showed that compared with the Trajectory Normal Glucose Regulation (NGR) group, the Trajectory Prediabetes Mellitus group (Pre-DM) group had significantly higher prevalence (OR: 2.02, 95% CI: 1.63–2.51) and incidence (OR: 1.66, 95% CI: 1.15–2.39) of atherosclerosis risk. The Trajectory Pre-DM group also had a significantly lower likelihood of atherosclerosis risk recovery than the Trajectory NGR group (OR: 0.55, 95% CI: 0.39–0.79). Dose-response analysis revealed a non-linear association between FBG and atherosclerosis risk prevalence, with a risk threshold at 5.10 mmol/L. This suggests that the atherosclerosis risk threshold in Chongqing is significantly lower than the international prediabetes standard of 5.60 mmol/L. Subgroup analyses showed sex and age differences, with lower thresholds in women and younger individuals.

Long-term elevation of FBG was associated with increased atherosclerosis risk. The study suggests that intervention strategies should be based on dynamic blood glucose trajectories and population-specific thresholds, especially lower thresholds for women and younger individuals. This study provides evidence-based support for regional atherosclerosis risk prevention and control.

The online version contains supplementary material available at 10.1186/s41043-025-01193-7.

## Linked entities

- **Diseases:** atherosclerosis (MONDO:0005311), prediabetes (MONDO:0006920)

## Full-text entities

- **Diseases:** DM (MESH:D009223), Prediabetes Mellitus (MESH:D011236), cardiovascular diseases (MESH:D002318), Atherosclerosis (MESH:D050197)
- **Chemicals:** blood glucose (MESH:D001786), Glucose (MESH:D005947), lipids (MESH:D008055), FBG (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13020111/full.md

## References

4 references — full list in the complete paper: https://tomesphere.com/paper/PMC13020111/full.md

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Source: https://tomesphere.com/paper/PMC13020111