Modifiable factors related to life-space mobility in community-dwelling older adults: results from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
BACKGROUND: The most common methods for measuring mobility in older adulthood include performance-based tests, such as the Timed-Up-and-Go and gait speed. While these measures have strong predictive validity for adverse outcomes, they are limited to assessing what older adults do in standardized settings, rather than what they do in their daily life. Life-space mobility, which is the ability to move within environments that expand from one's home to the greater community, has been proposed as a more comprehensive measure of mobility. The aim of this study was to determine the association between modifiable factors and life-space mobility in older adults enrolled in the Canadian Longitudinal Study on Aging (CLSA). METHODS: Life-space mobility was measured using the Life Space Index (LSI). Explanatory factors included physical, psychosocial and cognitive determinants, as well as pain, fatigue, driving status, nutrition, body mass index, smoking status, and vision. To estimate the association between the LSI and explanatory variables, univariate and multivariable ordinary least squares regression analyses were performed. RESULTS: All adults 65 years and older (n = 12,646) were included in the analysis. Fifty percent were women and the mean age was 73.0 (SD5.7). The mean LSI score was 80.5, indicating that, on average, the sample was able to move outside of their neighborhood independently. All explanatory variables were significantly associated with the LSI except for balance and memory. The top 3 variables that explained the most variation in the LSI were driving, social support and walking speed. CONCLUSION: To our knowledge, this was the first study to examine the association between life-space mobility and a comprehensive set of modifiable factors that were selected based on a theoretical framework and existing research evidence. This study had two important messages. First, driving, social support and walking speed emerged as the most significant correlates of life-space mobility in older adults. Second, life-space mobility is multifactorial and interventions that are pragmatic in their design and testing are needed that consider the complexity involved. A multi-disciplinary approach to examining life-space mobility in older adults is needed to optimize opportunities for healthy aging and develop strategies that support mobility in older adulthood.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".