Lipids & metabolic liver disease
Associations of nine insulin resistance-related indices with the incidence and progression of cardiovascular-liver-metabolic multimorbidity: a large prospective cohort study
Authors' conclusion
Nine IR-related indices were positively associated with the incidence and progression of CLMM, with TyG-WHtR and TyG-WC showing comparatively stronger associations and better predictive performance. These findings support their relevance for comparative CLMM risk assessment, while further validation is warranted. Exploratory biomarker analyses provided hypothesis-generating clues regarding biological domains potentially relevant to the associations.
Study context
- Population
- UK Biobank participants from England, Scotland and Wales, recruited 2006–2010, free of cardiovascular-liver-metabolic (CLM) diseases at baseline8,651 developed CLM multimorbidity (CLMM)
- Participants
- 371,207 participants
- Exposure
- Per-SD increase in nine insulin resistance (IR)-related indices
- Outcome
- Incidence and progression of CLM multimorbidity (CLMM; coexistence of ≥ 2 CLM conditions)
- Follow-up
- Median 16.4 years
Methodological detailsUK Biobank, Cox proportional hazards and multistate models
- UK Biobank
- Cox proportional hazards and multistate models
Main finding
As reported in the abstract
TyG-WHtR, HR per SD
2.08
95% CI 2.04–2.12
TyG-WC, HR per SD
2.14
95% CI 2.10–2.19
Observational data: associations, not effects.
Further findings
Multistate: healthy to first CLM disease, per SD increase
- TyG-WHtR, HR
- 1.59 (95% CI 1.58-1.60)
- TyG-WC, HR
- 1.62 (95% CI 1.61-1.63)
Multistate: progression to CLMM, per SD increase
- TyG-WHtR, HR
- 1.44 (95% CI 1.41-1.46)
- TyG-WC, HR
- 1.44 (95% CI 1.41-1.47)
Multistate: progression to triple CLM diseases, per SD increase
- TyG-WHtR, HR
- 1.24 (95% CI 1.15-1.34)
- TyG-WC, HR
- 1.22 (95% CI 1.13-1.31)
Predictive performance
- All indices significantly improved incremental value and discrimination; TyG-WHtR and TyG-WC performed comparatively better (all P < 0.001)
Mediation by biomarkers
- Systemic inflammation and liver- and kidney-related biomarkers might statistically contribute to the associations
- Exploratory, hypothesis-generating
Original publication
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