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March 21, 2026Nutrients2 citationsOpen Access

Associations of TyG-Derived Indices with Cardiometabolic Multimorbidity Risk in Community-Dwelling Older Adults: A Longitudinal Analysis Based on the GOLD-Health Cohort

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CLChuming LiaoHLHui LiuSXSuqi Xu

Key Result

TyG-WHtR demonstrated the strongest association with incident cardiometabolic multimorbidity in older adults, yielding a hazard ratio of 2.15 for the highest versus lowest quartile.

Key Points

  • The aim is to investigate the role of TyG-derived indices in predicting cardiometabolic multimorbidity risk among older adults.
  • Analyzed data from 304,586 community-dwelling adults aged ≥65 years free of cardiometabolic multimorbidity at baseline.
  • Utilized multivariable Cox proportional hazards models to evaluate incident cardiometabolic multimorbidity risk across quartiles of six TyG-derived indices.
  • Conducted mediation analysis to examine the role of atherogenic index of plasma.
  • After 4.3 years, 7816 participants developed cardiometabolic multimorbidity.
  • All six TyG-derived indices were significantly associated with increased CMM risk.
  • TyG-WHtR showed the strongest association with a hazard ratio of 2.150.
  • AIP explained 7.5–33.0% of the associations, especially for the Chinese visceral adiposity index.

Structured PICO

Do high TyG-derived indices predict incident cardiometabolic multimorbidity in community-dwelling older adults?

P
Population
Community-dwelling adults aged ≥65 years free of cardiometabolic multimorbidity at baseline
I
Intervention
Highest quartile of TyG-derived indices (e.g., TyG-WHtR, TyG-BMI)
C
Comparator
Lowest quartile of TyG-derived indices
O
Outcome
Incident cardiometabolic multimorbidity (coexistence of ≥2 cardiometabolic diseases)composite

TyG-derived adiposity indices, particularly TyG-WHtR and TyG-BMI, are robust independent risk markers for incident cardiometabolic multimorbidity in older adults.

Abstract

Background/Objectives: Cardiometabolic multimorbidity (CMM) significantly reduces healthy life expectancy in older adults. The specific role of adiposity indices derived from the triglyceride-glucose (TyG) index, body mass index (BMI), and waist-to-height ratio (WHtR) in predicting incident CMM has not been fully elucidated in longitudinal settings. We investigated these associations and the mediating role of the atherogenic index of plasma (AIP). Methods: We analyzed 304,586 community-dwelling adults aged ≥65 years from the prospective Guangzhou Older Longitudinal Dynamic Health (GOLD-Health) cohort (2018–2019), who were free of CMM at baseline. Multivariable Cox proportional hazards models evaluated the risk of incident CMM (coexistence of ≥2 cardiometabolic diseases) across quartiles of six TyG-derived indices. Mediation analysis quantified the contribution of atherogenic dyslipidemia via AIP. Results: Following a median observation time of 4.3 years, the study recorded 7816 participants who developed CMM. All six indices showed significant positive associations with CMM risk. TyG-WHtR demonstrated the strongest association (Hazard Ratio HR comparing highest vs. lowest quartile = 2.150; 95% Confidence Interval CI 1.998–2.314), closely followed by TyG-BMI (HR = 2.146). AIP significantly mediated the associations, explaining 7.5–33.0% of the effect, with the highest proportion observed for TyG using the Chinese visceral adiposity index (CVAI). Conclusions: TyG-derived adiposity indices, particularly TyG-WHtR and TyG-BMI, are robust independent risk markers for incident CMM in older adults. The substantial mediating role of AIP suggests that targeting atherogenic dyslipidemia may be a key strategy to interrupt the progression from insulin resistance to multimorbidity. These accessible metrics hold promise for large-scale risk stratification and early intervention in primary care settings.

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Cite This Study

Liao et al. (2026) studied this question. TyG-WHtR demonstrated the strongest association with incident cardiometabolic multimorbidity in older adults, yielding a hazard ratio of 2.15 for the highest versus lowest quartile.

synapsesocial.com/papers/69be35e66e48c4981c674747https://doi.org/10.3390/nu18060985
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