Exploring the association between sarcopenic obesity and cardiovascular risk: a summary of findings from longitudinal studies and potential mechanisms
Bibliographic record
Abstract
It is estimated that more than one-tenth of adults aged ≥60 years are now classified as having sarcopenic obesity (SO), a clinical condition characterised by the concurrent presence of sarcopenia (low muscle mass and weakness) and obesity (excessive fat mass). Independently, sarcopenia and obesity are associated with a high risk of numerous adverse health outcomes including CVD and neurological conditions (e.g. dementia), but SO may confer a greater risk, exceeding either condition alone. This imposes a substantial burden on individuals, healthcare systems and society. In recent years, an increasing number of observational studies have explored the association between SO and the risk of CVD; however, results are mixed. Moreover, the pathophysiology of SO is governed by a complex interplay of multiple mechanisms including insulin resistance, inflammation, oxidative stress, hormonal shifts and alteration of energy balance, which may also play a role in the occurrence of various CVD. Yet, the exact mechanisms underlying the pathological connection between these two complex conditions remain largely unexplored. The aim of this review is to examine the association between SO and CVD. Specifically, we seek to: (1) discuss the definition, epidemiology and diagnosis of SO; (2) reconcile previously inconsistent findings by synthesising evidence from longitudinal studies on the epidemiological link between SO and CVD and (3) discuss critical mechanisms that may elucidate the complex and potentially bidirectional relationships between SO and CVD.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".