Walking-friendly built environments and objectively measured physical function in older adults
Bibliographic record
Abstract
BACKGROUND: Few studies have examined the associations between urban design attributes and older adults' physical function. Especially, it is not well known how built-environment attributes may influence physical function in Asian cities. The aim of this study was to examine associations between objectively measured environmental attributes of walkability and objectively assessed physical function in a sample of Japanese older adults. METHODS: Cross-sectional data collected in 2013 from 314 older residents (aged 65-84 years) living in Japan were used. Physical function was estimated from objectively measured upper- and lower-body function, mobility, and balance by a trained research team member. A comprehensive list of built-environment attributes, including population density, availability of destinations, intersection density, and distance to the nearest public transport station, were objectively calculated. Walk Score as a composite measure of neighborhood walkability was also obtained. RESULTS: Among men, higher population density, availability of destinations, and intersection density were significantly associated with better physical function performance (1-legged stance with eyes open). Higher Walk Score was also marginally associated with better physical function performance (1-legged stance with eyes open). None of the environmental attributes were associated with physical function in elderly women. CONCLUSION: Our findings indicate that environmental attributes of walkability are associated with the physical function of elderly men in the context of Asia. Walking-friendly neighborhoods can not only promote older adults' active behaviors but can also support their physical 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".