Prevalence and Characterization of Natural Health Product Use in Adults with Type 2 Diabetes
Bibliographic record
Abstract
Natural Health Products (NHPs) have received attention for their role in human health and disease. Type 2 diabetes is of interest due to its increasing incidence and potential role of NHPs in its management. The objectives of this study were to determine the prevalence and predictors of NHP use, and to characterize beliefs and attitudes about NHPs, in adults with type 2 diabetes. Adults with type 2 diabetes (n=150) completed an interviewer‐administered questionnaire exploring the prevalence of NHP use, attitudes and beliefs about NHPs, as well as general health, medical and demographic data. NHP users were older (p=0.003), more educated (p=0.03) and tended to have a lower body weight (p=0.06) than non‐users. Although NHP users had been diagnosed with diabetes for longer relative to non‐users (p=0.02), there were no significant differences in plasma glucose, HbA1c or other diabetes management characteristics. The prevalence of NHP use was 77.3% with the three most common NHPs including multi‐vitamins/minerals (48.3%), calcium (36.2%) and vitamin C (31.9%). The number one rationale for NHP use was general health (60.3%) with diabetes ranked as fourth (12.1%). The majority of NHP users (81.9%) had their NHPs recommended to them, most often from a physician (39.7%). The most common sources of NHP information were magazines/books (19.8%), word of mouth (19.8%) and physicians (17%), although the majority of NHP users (63.8%) reported they did not need more information. The high prevalence of NHP use (77.3%) observed justifies the value of these data to improving the overall health care of adults with type 2 diabetes. Supported by the Natural Health Products Directorate of Health Canada.
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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 | 0.002 |
| 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 | 0.001 |
| 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".