Fitness correlates of body image in middle-to older aged adults
Bibliographic record
Abstract
Research has shown physical activity leads to improvements in body image, but it has primarily focused on appearance-related outcomes and relatively little work has investigated this relationship in older populations. This study examined the relationships between body satisfaction and fitness among middle to older aged (53 to 88 years) men (n = 73) and women (n = 184). Participants completed measures of satisfaction with body appearance and body function. In addition, measures of body composition (i.e., hip and waist circumference), fitness (i.e., indicators of cardiovascular endurance, upper and lower body muscular endurance, upper and lower body flexibility) and balance (i.e., functional reach) were assessed objectively. Correlations showed that satisfaction with body appearance was positively related to age and negatively to waist circumference. Satisfaction with body function was positively correlated with age, cardiovascular endurance, and muscular endurance in the upper and lower body. A linear regression predicting satisfaction with body appearance was significant, F (9, 242) = 4.80, p < 0.0001, R2ad j= 0.12 with age and cardiovascular endurance significant predictors. The regression predicting satisfaction with body function was also significant, F (9, 244) = 4.83, p < 0.0001, R2adj = 0.12. Age, cardiovascular endurance, lower body muscular endurance, and lower body flexibility were significant predictors. These findings suggest that multiple components of fitness are more strongly associated with satisfaction with body function compared to satisfaction with body appearance in middle to older aged adults. Emphasizing fitness benefits related to body function may improve body image in older populations.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".