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Updated: Jun 5, 2025

Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method
Published on: February 19, 2021
Chrononutrition behaviors and cardiometabolic risk in adolescence: an ecological momentary assessment study
Yu-Ting Shen1, Qi Li1, Yu-Xiang Xu1
1Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Purpose:
To investigate the potential associations between unhealthy chrononutrition behaviors (meal timing, frequency, and regularity) and their combined impact on cardiometabolic risk in adolescence.
Methods:
Chrononutrition behaviors were assessed using a 7-day ecological momentary assessment (EMA). The unhealthy chrononutrition score (ranging from 0 to 8) was determined based on late meal timing, low meal frequency, and meal irregularity. The cardiometabolic (CM)-risk z score was calculated utilizing age- and sex-specific reference values for waist circumference (WC), mean arterial pressure (MAP), homeostatic model assessment of insulin resistance (HOMA-IR), triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C). Restricted cubic splines were employed to estimate the dose-response relationships between the unhealthy chrononutrition score and outcomes.
Results:
Among 458 participants [mean (SD) age, 17.9 (0.7) years; 340 (74.2%) Female], 14.3% had an unhealthy chrononutrition score ≥ 6, who exhibited higher MAP (β = 3.86; 95% CI 1.24, 6.47), higher CM-risk scores (β = 1.80; 95% CI 0.70, 2.90), and lower HDL-C (β = 0.18; 95% CI - 0.30, - 0.06), as opposed to those with a healthy score ≤ 2 (n = 136, 31.4%). Moreover, late breakfast (later than 9AM compared to earlier than 8AM), low meal frequency (eating two or fewer meals versus three meals a day), and meal irregularity (score of 3-5 compared to a good score of 6-9) were associated with an increased risk of CM-risk outcomes.
Conclusion:
The findings suggest a clustering of unhealthy chrononutrition behaviors that collectively impact cardiometabolic health in adolescence. Further prospective and interventional investigations is necessary to validate these findings and explore the underlying mechanisms.
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