Diagnosis, Symptoms, and Calcium Intakes of Individuals with Self-Reported Lactose Intolerance
Bibliographic record
Abstract
OBJECTIVE: To determine methods of diagnosis, symptoms, and calcium intake from food and supplements for individuals with self-reported lactose intolerance. METHODS/DESIGN: Cross-sectional survey using a mailed questionnaire. SUBJECTS/SETTING: A convenience sample of 189 adults with self-reported lactose intolerance living in the metropolitan area of Vancouver Canada responded to posters or advertisements, and 159 returned completed questionnaires. MEASURES OF OUTCOME: Methods of diagnosis, symptoms experienced and their severity were self-reported. Estimated calcium intake from food and supplements was assessed using a food frequency questionnaire. Data were analyzed using descriptive statistics, chi-square, Pearson correlation analysis, t-tests and Analysis of Variance. RESULTS: Participants were 47 +/- 15 years of age; 72% female and 28% male; 67% Caucasian; and 54% had self-diagnosed their lactose intolerance. Of the 42% diagnosed by a physician, only 10% had been diagnosed by valid tests. Mean estimated food calcium intake was 591 +/- 382 mg/d and did not differ between those who were self- or physician-diagnosed. Only 11.5% of participants met their age-appropriate Adequate Intake (AI) from food calcium sources alone. Calcium supplements were used by 65% and provided an average of 746 +/- 703 mg calcium/day to those who used them; mean intakes of this group met the AI. CONCLUSIONS: Calcium intake from food sources alone is inadequate to meet the AI in individuals with self-reported lactose intolerance. Physicians managing lactose intolerance need current information on how the AI can be met through appropriate food choices and possible supplementation.
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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 | 0.000 |
| 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 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".