Hormones (Athens). 2026 Jun 8. doi: 10.1007/s42000-026-00794-z. Online ahead of print.
ABSTRACT
OBJECTIVE: The aim of this study is to comprehensively investigate the independent associations between a wide array of novel metabolic indices and the prevalence of circadian syndrome (CircS), as well as to explore, within a cross‑sectional framework, whether the C‑reactive protein triglyceride glucose index (CTI) shows statistical associations consistent with mediation.
METHODS: A cross‑sectional analysis was conducted using data from the China Health and Retirement Longitudinal Study (CHARLS) 2015 wave, involving 6,507 participants aged ≥ 45 years. Multivariable logistic regression, restricted cubic splines, and mediation analyses were employed to assess associations, non‑linearity, and indirect effects (cross‑sectionally consistent with mediation).
RESULTS: In fully adjusted models, multiple metabolic indices – including dynapenic abdominal obesity, frailty, TyG‑related indices, and the cardiometabolic index (CMI) – showed significant positive associations with CircS prevalence (all P < 0.001), while CCR was inversely associated. Restricted cubic spline analyses revealed significant non‑linear relationships for all indices (log‑likelihood ratio test P < 0.001). Mediation analysis indicated that CTI had a statistically significant indirect effect (cross‑sectionally consistent with mediation), with the proportion of the total effect statistically attributable to CTI ranging from 20.8% to 86.5%.
CONCLUSION: This large‑scale cross‑sectional study identified significant, often non‑linear, associations between multiple novel metabolic indices and CircS. CTI, a composite marker of inflammation and metabolism, showed a substantial indirect effect cross‑sectionally consistent with mediation in these associations. These hypothesis‑generating findings highlight the potential importance of the “metabolic‑inflammatory” axis in relation to CircS and offer epidemiological clues for early identification and risk stratification. Prospective studies are needed to assess temporality and causality.
PMID:42260226 | DOI:10.1007/s42000-026-00794-z
