Association between the triacylglycerol–glucose index, TyG-BMI and hypertension in children and adolescents: a cross-sectional study with machine-learning-based risk stratification
7 affiliations
- 1Department of Cardiology, Henan Provincial People’s Hospital, Zhengzhou University People’s Hospital
- 2Department of Hypertension, Henan Provincial People’s Hospital, Zhengzhou University People’s Hospital
- 3Clinical medicine, Henan University of Science and Technology
- 4Henan Province Hypertension Precision Prevention and Control Engineering Research Center, Henan Provincial People’s Hospital, Zhengzhou University People’s Hospital
- 5Department of Research and International Affairs, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital
- 6Henan Provincial Center for Disease Control and Prevention
- 7Henan Engineering Technology Research Center for Prevention and Treatment of Panvascular Diseases, Henan Provincial People’s Hospital, Zhengzhou University People’s Hospital
Abstract
Background: Hypertension in children and adolescents is closely linked to obesity and metabolic disturbance. The triacylglycerol–glucose (TyG) index and TyG-BMI are surrogate markers of insulin resistance, but their associations with pediatric hypertension remain incompletely characterized.
Methods: This cross-sectional study included 25,886 children and adolescents aged 7–17 years from 18 prefecture-level cities in Henan Province, China. The TyG index was calculated as ln[triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2] and TyG-BMI as TyG × BMI. Hypertension was defined as a blood pressure at or above the 95th percentile for age, sex and height (mean of the last two of three measurements). Logistic regression (Models I–IV) estimated odds ratios (ORs) per 1 SD and across quartiles, with non-linearity and effect modification assessed on both scales. Eleven machine-learning models were developed on a stratified 70:30 split, with imputation and feature selection performed strictly within the training set and discrimination (area under the receiver-operating characteristic curve, AUC) evaluated in the held-out validation set.
Results: Among 25,886 participants, 1,798 (6.95%) had hypertension. Median TyG was 8.05 (IQR 7.77–8.35) and median TyG-BMI 154 (IQR 133–180). Each 1-SD increment in TyG was associated with hypertension in all models (Model IV 1.306 (95% CI 1.145–1.489)), and the association was graded across quartiles; TyG-BMI showed stronger associations (Model IV 2.109 (95% CI 1.985–2.241)). No multiplicative product term was significant after correction, whereas on the additive scale all six relative excess risk estimates were positive with confidence intervals excluding zero. In the held-out validation set, discrimination was moderate (best AUC 0.7544, 95% CI 0.7302–0.7777, for TyG and 0.7534, 0.7298–0.7759, for TyG-BMI), and adding either index to the same baseline model already containing BMI increased discrimination only marginally (about 0.003 in AUC).
Conclusions: Higher TyG and TyG-BMI were associated with hypertension in Chinese children and adolescents, more strongly for TyG-BMI. No multiplicative interaction survived correction, but all additive-scale estimates were positive, so effect modification cannot be excluded. Machine-learning models built from routinely available variables showed only moderate discrimination and remain hypothesis-generating tools for risk stratification rather than validated prediction models. Longitudinal studies are needed to assess causality.
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BibTeX
@article{zhu2026association,
title = {{Association between the triacylglycerol–glucose index, TyG-BMI and hypertension in children and adolescents: a cross-sectional study with machine-learning-based risk stratification}},
author = {Jialiang Zhu and Chen Zhang and Jialin Sun and Huiyu Du and Wenxin Zhao and Gang Tian and Jingge Zhao and Dandan Tian and Mengwei Wang and Zhanfeng Liu and Min Liu and Yibin Hao},
journal = {Frontiers in Endocrinology},
year = {2026},
month = oct,
doi = {10.3389/fendo.2026.1964709},
url = {https://www.frontiersin.org/articles/10.3389/fendo.2026.1964709/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Association between the triacylglycerol–glucose index, TyG-BMI and hypertension in children and adolescents: a cross-sectional study with machine-learning-based risk stratification
AU - Jialiang Zhu
AU - Chen Zhang
AU - Jialin Sun
AU - Huiyu Du
AU - Wenxin Zhao
AU - Gang Tian
AU - Jingge Zhao
AU - Dandan Tian
AU - Mengwei Wang
AU - Zhanfeng Liu
AU - Min Liu
AU - Yibin Hao
PY - 2026
DA - 2026/10/16
JO - Frontiers in Endocrinology
DO - 10.3389/fendo.2026.1964709
UR - https://www.frontiersin.org/articles/10.3389/fendo.2026.1964709/full
AB - Background: Hypertension in children and adolescents is closely linked to obesity and metabolic disturbance. The triacylglycerol–glucose (TyG) index and TyG-BMI are surrogate markers of insulin resistance, but their associations with pediatric hypertension remain incompletely characterized. Methods: This cross-sectional study included 25,886 children and adolescents aged 7–17 years from 18 prefecture-level cities in Henan Province, China. The TyG index was calculated as ln[triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2] and TyG-BMI as TyG × BMI. Hypertension was defined as a blood pressure at or above the 95th percentile for age, sex and height (mean of the last two of three measurements). Logistic regression (Models I–IV) estimated odds ratios (ORs) per 1 SD and across quartiles, with non-linearity and effect modification assessed on both scales. Eleven machine-learning models were developed on a stratified 70:30 split, with imputation and feature selection performed strictly within the training set and discrimination (area under the receiver-operating characteristic curve, AUC) evaluated in the held-out validation set. Results: Among 25,886 participants, 1,798 (6.95%) had hypertension. Median TyG was 8.05 (IQR 7.77–8.35) and median TyG-BMI 154 (IQR 133–180). Each 1-SD increment in TyG was associated with hypertension in all models (Model IV 1.306 (95% CI 1.145–1.489)), and the association was graded across quartiles; TyG-BMI showed stronger associations (Model IV 2.109 (95% CI 1.985–2.241)). No multiplicative product term was significant after correction, whereas on the additive scale all six relative excess risk estimates were positive with confidence intervals excluding zero. In the held-out validation set, discrimination was moderate (best AUC 0.7544, 95% CI 0.7302–0.7777, for TyG and 0.7534, 0.7298–0.7759, for TyG-BMI), and adding either index to the same baseline model already containing BMI increased discrimination only marginally (about 0.003 in AUC). Conclusions: Higher TyG and TyG-BMI were associated with hypertension in Chinese children and adolescents, more strongly for TyG-BMI. No multiplicative interaction survived correction, but all additive-scale estimates were positive, so effect modification cannot be excluded. Machine-learning models built from routinely available variables showed only moderate discrimination and remain hypothesis-generating tools for risk stratification rather than validated prediction models. Longitudinal studies are needed to assess causality.
SN - 1664-2392
ER -