Is dietary deficiency of calcium a factor in rickets? Use of current evidence for our understanding of the disease in the past
Bibliographic record
Abstract
OBJECTIVE: Rickets is considered an indicator of vitamin D deficiency in palaeopathology, but a strand of biomedical thought maintains that dietary calcium deficiency may sometimes play a part in its causation. Our aim is to evaluate the extent to which low calcium intake should be considered as a factor in biocultural interpretations of rickets. METHODS: We assess published modern epidemiological studies that provide primary data to support claims for a role for dietary calcium deficiency in rickets. We also consider how we might identify, via indicators of calcium intake, populations at risk of calcium deficiency in the past. RESULTS: Support for dietary calcium deficiency as a cause of rickets is equivocal. Direct measurement of dietary calcium in the past is not possible, but exposure to risk factors for low calcium intake can to some extent be identified. CONCLUSION: Whilst there is little evidence to alter the view that rickets is essentially an indicator of a population's vitamin D status, occasionally, in very low calcium intake groups, dietary calcium deficiency may play a synergistic role by accentuating the need for vitamin D. SIGNIFICANCE: The notion that dietary calcium deficiency may be a cause of rickets appears to be gaining currency in bioarchaeological studies. This paper shows that it is unusual for this to be the case, and even then the role of vitamin D remains crucial. LIMITATIONS: This paper attempts to summarise the current state of biomedical study in an area that is subject to continuing investigation.
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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 | 0.002 |
| 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".