Walking for Cognitive Health: Previous Parity Moderates the Relationship Between Self-Reported Walking and Cognition
Bibliographic record
Abstract
BACKGROUND: Older females show greater cognitive gains from physical activity (PA) than males, which may be related to long-term consequences of female-specific reproductive events (eg, pregnancy) on cognitive health. METHODS: To determine whether previous parity could moderate the relationship between PA and cognitive decline in older women, we conducted secondary analyses of data from the Health, Aging, and Body Composition Study. We tested whether the association between average PA over 10 years and cognition (Modified Mini-Mental State Examination [3MS]) and executive functioning (digit symbol substitution test [DSST]) over 10 years varied by previous parity (nulliparity, low parity, medium parity, and grand multiparity). An analysis of covariance was performed with cognition (average and change over 10 years) as the dependent variables, parity as a categorical predictor, average PA as a continuous predictor, and a set of relevant covariates. RESULTS: Significant interactions were found between PA and parity group for all 4 comparisons: average 3MS (p = .014), average DSST (p = .032), change in 3MS (p = .016), and change in DSST (p = .017). Simple slope analyses indicated the positive relationship between PA and average 3MS and DSST was only significant in the nulliparity and grand multiparity groups, and the positive relationship between PA and change in 3MS and DSST was only significant in the grand multiparity group. CONCLUSION: The findings suggest the relationship between self-reported walking and cognitive performance was strongest in the groups at risk for cognitive decline and dementia, the nulliparous and grand multiparous groups.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".