Association of Insulin Resistance, Sarcopenia, and Risk of Cardiovascular Disease: Findings From the China Health and Retirement Longitudinal Study
Bibliographic record
Abstract
Background: Cardiovascular disease (CVD) is the main cause of death in middle-aged and older people in China. The interplay between sarcopenia and insulin resistance (IR) in driving CVD risk has not been fully understood, particularly regarding sarcopenia severity and IR heterogeneity. Objective: This study aimed to investigate the relationship between IR and sarcopenia and the risk of new-onset CVD. Methods: Using data from the China Health and Retirement Longitudinal Study (CHARLS). Cox proportional hazards models were used to assess associations of sarcopenia status (nonsarcopenia, possible sarcopenia, sarcopenia, and severe sarcopenia) and 6 IR indices (triglyceride-glucose, TyG; TyG-BMI; TyG-waist circumference; TyG-waist-to-height ratio; triglyceride/high-density lipoprotein cholesterol, TG/HDL-C; and metabolic score for insulin resistance, METS-IR) with incident CVD. Additive and multiplicative interaction analyses and subgroup analyses by age and sex were performed. Receiver operating characteristic analysis was used to determine clinically relevant cutoffs. Results: In this study, during a median 9-year follow-up, we included 5514 middle- and older-aged (≥45 y) residents, of whom 550 presented with CVD incidence. Participants with possible sarcopenia and high IR exhibited 1.24-1.85-fold higher CVD risk versus nonsarcopenia and low-IR counterparts (P<.05) after adjustment for potential confounders. While TyG-BMI and TyG-waist circumference were the strongest independent predictors, formal interaction analysis revealed that the TG/HDL-C ratio and METS-IR demonstrated the most consistent synergistic effects with possible sarcopenia (relative excess risk due to interaction=0.139 and 0.074, respectively). In subgroups of different ages and sexes, the combination of IR and sarcopenia is associated with the highest risk of CVD. Receiver operating characteristic analysis provided clinically applicable cutoffs for these indices, including TG/HDL-C ≥2.09 and METS-IR ≥34.26. Conclusions: We found that IR and sarcopenia, especially early-stage sarcopenia, synergistically increase the incidence of CVD in older adults. These findings advocate for dual-targeted CVD interventions (muscle preservation and IR mitigation) in aging societies, particularly during the transitional phase of possible sarcopenia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".