P1‐106: Reduction in body fat mass is independently associated with improved executive function
Bibliographic record
Abstract
Cognitive decline is a pressing health care issue. Physical activity is a promising strategy for combating cognitive decline at a population level. Results from intervention studies suggest that targeted exercise training enhances cognitive performance and functional plasticity in older adults. The neuroprotective nature of regular physical activity largely stems from reducing the risk of chronic conditions, such as type 2 diabetes, hypertension, and cerebrovascular disease. Regular physical activity may also improve cognitive function in older adults by reducing adipose tissue. Recent evidence suggests that increased adiposity is independently associated with reduced cognitive performance. Whether reduced adiposity is a potential mechanism by which exercise promotes cognitive function in older adults has not been explored extensively to date. The purpose of this study was to investigate the independent association of change in fat mass and cognitive performance in a subset of women aged 65 to 75 years old who participated in a 12-month randomized controlled trial of exercise. This secondary analysis included 114 of the 155 participants who underwent whole body dual-energy x-ray absorptiometry (DXA). Our primary outcome measure was the executive cognitive process of selective attention and conflict resolution, as measured by the Stroop Test. Using multivariate regression analysis, we assessed the independent contribution of change in fat mass (grams) as measured by DXA to Stroop performance at trial completion after accounting for baseline Stroop performance, experimental group, baseline global cognitive state, and baseline functional comorbidity index. Our results showed that reduced fat mass was independently associated with improved Stroop Test performance at trial completion (P = 0.01). Interestingly, change in lean mass was not significantly associated with Stroop Test performance at trial completion. These results suggest that reduced fat mass—not increased lean mass —is a mechanism whereby physical activity promotes executive functions in older adults. Future studies are needed to provide a better understanding of the interplay between adiposity, physical activity, and cognitive function.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".