Bidirectional Associations Between Adiposity and Cognitive Function: A Prospective Analysis of the Canadian Longitudinal Study on Aging (CLSA)
Bibliographic record
Abstract
BACKGROUND: Theoretical perspectives suggest that adiposity and cognitive function may be bidirectionally associated, but this has not been examined in a large-scale data set. The current investigation aims to fill this gap using a large, representative sample of middle-aged and older adults. METHODS: Using data from the Canadian Longitudinal Study on Aging (N = 25 854), the bidirectional hypothesis was examined with 3 indicators of cognitive function (ie, executive function, processing speed, and verbal fluency) and adiposity (ie, waist circumference [WC], body mass index [BMI], and total fat mass). We used multivariate multivariable regression and structural equation modeling to assess the prospective associations between adiposity and cognitive indicators. RESULTS: Analyses revealed that higher baseline WC was associated with higher Stroop interference at follow-up for both middle-aged (standardized estimate, β = 0.08, 95% confidence interval [CI] 0.06, 0.10) and older adults (β = 0.07, 95% CI 0.04, 0.09). Similarly, higher baseline Stroop interference was also associated with higher follow-up WC in middle-aged (β = 0.08, 95% CI 0.06, 0.10) and older adults (β = 0.03, 95% CI 0.01, 0.06). Effects involving semantic fluency and processing speed were less consistent. The earlier effects were similar to those observed using other adiposity indicators (eg, BMI and total fat mass) and were robust to adjustment for demographics and other cofounders, and when using latent variable modeling of the adiposity variable. CONCLUSION: Evidence for a bidirectional relationship between adiposity and cognitive function exists, though the associations are most reliable for executive function and primarily evident at midlife.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".