Body Image, Body Composition, and Aging in Women: Insights into an Older Adult Problem
Bibliographic record
Abstract
Body image is understudied in aging women. The present perspective article reviews body image, body composition, and aging in women. Sarcopenia, a condition of low muscle mass, is associated with aging, and sarcopenia in combination with excessive body fat causes sarcopenic obesity. Findings of improved health in people with a higher body mass index, known as the obesity paradox, are due to misclassifying healthy people as overweight according to height and body weight instead of according to fat mass and fat-free mass. Body fat infiltrates internal organs in aging adults as increasing levels of body fat are redistributed into the trunk, especially in the abdomen, while subcutaneous fat in the appendages decreases. Accuracy of body image perceptions can determine an individual’s control of body weight. Aging women can protect against sarcopenic obesity by increasing fat-free mass with resistance training and by lowering body fat levels with weight management knowledge and skills. Healthy dietary patterns are low in ultra-processed foods that stimulate excessive consumption of calories and increase body fat levels. In combination with the phosphate additives in ultra-processed food which increase sarcopenia and aging, the present article proposes an etiological pathway in which ultra-processed food consumption eventually leads to aging-related sarcopenic obesity.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".