The Association Between Dietary Energy Density and Musculoskeletal Pain in Adult Men and Women
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Musculoskeletal pains (MPs), defined as persistent or recurrent pain, is a complex health problem. High overall calorie and fat intake have been related to obesity and MPs. Dietary energy density (DED), defined as energy content of food and beverages (in kcal) per unit total weight, has been associated with chronic muscle, cartilage, bone damage and pain. Thus, the purpose of this study is to investigate the association between DED and MPs in adult men and women. A total of 175 men and women (> 18 years) with MP participated in the study. A validated short form physical activity (PA) questionnaire, demographic, and McGill Pain Questionnaire were used. Anthropometric measurements were evaluated via standard protocols. Furthermore, a seven-day 24-hour recall of diet was used to determine the dietary intake. Total DED was calculated and divided into quartiles. Linear regression was used to discern the association between DED and MPs in adults. Participants assigned in the highest category of DED were characterized by lower intake of potassium, magnesium, vitamin C, folate, and fiber. However, results showed displayed higher intake of sodium, vitamin E, vitamin B3, fat, protein, cholesterol, saturated fatty acids, monounsaturated fatty acids, and polyunsaturated fatty acids (p < 0.001). Finally, after adjustment for confounders such as age, gender, PA, body mass index, waist circumference, education, job, marital status, history of some chronic diseases and vitamin C supplementation, a significant positive association was detected between DED and pain intensity. There was no significant association between DED and pain frequency in all models.
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.
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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it