Diet quality, diet-related factors and disability status among male adults of reproductive age in the USA
Bibliographic record
Abstract
OBJECTIVE: To examine diet quality and diet-related factors among male adults of reproductive age with and without disabilities. DESIGN: Cross-sectional data from the National Health and Nutrition Examination Surveys, 2013-2018. SETTING: Disability was reported as serious difficulty hearing, seeing, concentrating, walking, dressing and/or running errands due to physical, mental or emotional conditions. Diet quality was assessed by the Healthy Eating Index (HEI)-2015 and diet-related factors included self-rated diet healthfulness, food security and food assistance programmes. Multivariable linear regression estimated differences in HEI-2015 scores. Multivariable Poisson regression estimated adjusted prevalence ratios (aPR) and 95 % CI for diet-related factors. PARTICIPANTS: In total, 3249 males, 18-44 years; of whom, 441 (13·4 %) reported having disabilities. RESULTS: Compared with males without disabilities, those with disabilities had a 2·69-point (95 % CI: -4·18, -1·20) lower mean total HEI-2015 score and approximately one-third to half of a point lower HEI-2015 component scores for greens and beans, total protein foods, seafood and plant proteins, fatty acids and added sugars. Males with any disabilities were more likely to have low food security (aPR = 1·57; 95 % CI: 1·28, 2·92); household participation in food assistance programmes (aPR = 1·61; 95 % CI: 1·34, 1·93) and consume fast food meals during the previous week (1-3 meals: aPR = 1·11; 95 % CI: 1·01-1·21 and 4 or more meals: aPR = 1·18; 95 % CI: 1·01-1·38) compared with males with no disabilities. CONCLUSIONS: Factors affecting diet and other modifiable health behaviours among male adults of reproductive age with disabilities require further investigation. Health promotion strategies that are adaptive to diverse populations within the disability community are needed.
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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".