Abstract P228: Accelerometer-Derived Daily Steps, Cognition, and Cognitive Impairment in U.S. Community-Dwelling Older Adults: The Atherosclerosis Risk in Communities Study
Bibliographic record
Abstract
Introduction: Higher physical activity levels have been shown to preserve cognitive function and prevent cognitive impairment (CI). Whether daily steps, an easily interpretable physical activity metric, is associated with measures of brain health has not been widely studied. Hypothesis: Higher daily step count is associated with better cognitive function and lower odds of CI. Methods: Cross-sectional analysis of ARIC participants (mean age: 78 years, 41% male, 19% Black) who wore an accelerometer (ActiGraph GT3X) on the waist for ≥10 hours on ≥3 days between 2016-17. Daily steps were derived and examined continuously and by quartiles. Global and domain-specific (memory, language, executive function) factor scores were estimated from a battery of cognitive tests. Participants were classified as having CI if they had an adjudicated diagnosis of mild CI or dementia. Hypotheses were tested using linear and logistic regression models, adjusted for age, sex, race, education, and accelerometer wear time. Results: Among 454 participants, 88 (19.4%) had CI. The mean number of daily steps was 3,501 (SD=1,974). In adjusted models, a higher daily step count was associated with better global cognition and executive function factor scores (e.g., those in the 4 th daily-step quartile [≥4,499 steps] vs. 1 st [<2074 steps] had a 0.43 [95% confidence interval: 0.24 to 0.61] higher executive function score). Associations of step count with memory or language scores were not supported. The odds of CI were lower for participants who had a higher daily steps count (e.g., those in the 4 th daily-step quartile vs. 1 st had 62% [odds ratio (OR)=0.38, 95% confidence interval: 0.16 to 0.90] lower odds of CI. The OR of CI for continuous daily steps shown in the Figure. Conclusions: Higher daily steps were associated with better cognitive function and may be a helpful marker in identifying participants with CI. Prospective studies of accelerometer-measured physical activity and cognitive outcomes are needed to understand the direction of these associations.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".