Patterns of dietary supplement use among United States patients with steatotic liver disease: Vitamins, minerals and botanicals
Bibliographic record
Abstract
BACKGROUND: Dietary supplement (DS) usage among United States adults has significantly increased. Patients with steatotic liver disease (SLD) may have unique motivations to take DS in light of their liver condition and co-morbidities. AIM: To characterize DS use in SLD patients and explore motivations for their use. METHODS: Adults ≥ 18 years old with complete transient elastography and dietary data from the National Health and Nutrition Examination Survey between January 2017 and March 2020 were studied. SLD was defined using consensus criteria, combining clinical indicators with elastography thresholds. The DS Questionnaire (DSQ) was used to record participants' use of DSQ. Sample weights were applied to estimate national prevalence. RESULTS: Of 2413 participants with SLD, 1058 reported using DS, for an estimated prevalence of 44.8% [standard error (SE) 2.4] with an average of 2.6 (SE 0.2) DS per person. Among SLD participants taking DSQ, 53.2% (SE 3.3) reported using non-vitamin/non-mineral ones, with an average of 1.8 (SE 0.1) such supplements per person. DS users were more likely to be female, have higher levels of education, and have greater food security (P < 0.02 for all). The most common motivations for using DS were to follow doctor's advice (36.7%, SE 1.8), to improve overall health (22.1%, SE 2.0), and to maintain health (19.2%, SE 1.9). CONCLUSION: Nearly half of individuals with SLD report taking DS. This study underscores the pressing need to deepen our understanding of DS use/motivations to develop tailored patient counseling strategies.
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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 | 0.001 | 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) | 0.002 | 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".