Cognitive Function Is Associated With Multiple Indices of Adiposity in the Canadian Longitudinal Study on Aging: A Cross-Sectional Analysis
Bibliographic record
Abstract
OBJECTIVE: Prior studies have suggested reciprocal relationships between cognitive function and adiposity, but this has not been investigated with population representative data sets. The purpose of this study was to examine the association between cognitive function and adiposity in a large population-based sample of middle-aged and older adults. It was hypothesized that better scores on tests of cognitive function would be associated with lower adiposity, and this association would be primarily mediated through life-style behavior and physical health status. METHODS: Using baseline data from the Canadian Longitudinal Study on Aging ( N = 30,097), we tested our hypotheses using three indicators of cognitive function (animal fluency, Stroop interference, and reaction time) and four indicators of adiposity (body mass index, total fat mass, waist circumference, and waist-hip ratio). Hierarchical multivariable linear regression modeling was conducted followed by tests for moderation by socioeconomic status and mediation through diet, physical activity, hypertension, and diabetes status. RESULTS: All measures of cognitive indicators were significantly associated with adiposity after adjusting for confounders. In general, superior performance on animal fluency, Stroop, and reaction time tasks were associated with lower adiposity by most metrics. Stroop interference was associated with lower adiposity across all metrics, including body mass index ( b = - 0.04, 95 % confidence interval [CI] = - 0.06 to - 0.01), total fat mass ( b = 19.35, 95 % CI = 8.57 to 30.12), waist circumference ( b = 33.83, 95 % CI = 10.08 to 57.58), and waist-hip ratio ( b = 0.13, 95 % CI = 0.01 to 0.24). These associations were more substantial for moderate- and high-income subpopulations. Mediation analyses suggested that the aforementioned effects were mediated through life-style behavior (e.g., diet and physical activity) and physical health conditions (e.g., diabetes and hypertension). CONCLUSIONS: Reliable associations exist between cognitive function and adiposity in middle-aged and older adults. The associations seem to be mediated through life-style behavior and physical health conditions.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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".