Association of sarcopenic obesity with dementia risk in a cohort of older women
Bibliographic record
Abstract
BACKGROUND AND AIMS: Longitudinal studies have explored the association between sarcopenic obesity (SO) and the risk of cognitive impairment, yet findings remain mixed. This study aimed to investigate the associations of SO with risk of incident dementia in older women, using two diagnostic models: the Sarcopenic Obesity Global Leadership Initiative (SOGLI) and the load-capacity model. METHODS: We analysed data from 900 community-dwelling women (aged ≥70 years). SO was defined using two models: (1) the SOGLI criteria, based on low handgrip strength (HGS), low appendicular lean soft tissue to body weight (ALST/W) ratio, and high fat mass percentage (%FM); and (2) the load-capacity model, based on a high truncal fat mass to ALST (TrFM/ALST) ratio. Incident dementia events (hospitalisation and/or death) over 9.5 years were identified through linked health records using International Classification of Diseases (ICD) codes. Cox proportional hazards and Fine-Gray sub-distribution models were applied. RESULTS: (n = 67) or %FM below the 15th percentile (n = 135), and after further adjustment for age at highest education level.. CONCLUSION: This is the first longitudinal study to examine the association between SO and dementia using either the SOGLI or load-capacity models. In this cohort of older women, SO was associated with a lower risk of dementia-related hospitalisation. These findings suggest that the relationship between obesity and dementia risk in late life may differ from current evidence regarding midlife, indicating potential age-specific effects. Further research is needed to clarify the underlying mechanisms and generalisability of these observations to broader populations..
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".