Dioxin-like compounds are not associated with bone strength measured by ultrasonography in Inuit women from Nunavik (Canada): results of a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Bone strength in Inuit people appears lower than that of non-Aboriginals. Inuit are exposed to persistent organic pollutants including dioxin-like compounds (DLCs) through their traditional diet that comprises predatory fish and marine mammal fat. Results from experimental and population studies suggest that some DLCs can alter bone metabolism and increase bone fragility. OBJECTIVE: This cross-sectional descriptive study was conducted to examine the relationship between the stiffness index (SI) and plasma concentrations of total DLCs or specific dioxin-like polychlorinated biphenyls (DL-PCBs) in Inuit women of Nunavik (Northern Quebec, Canada). METHODS: SI was determined by ultrasonography at the right calcaneus of 194 Inuit women aged 35-72 years who participated to Qanuippitaa? How Are We? Nunavik Inuit Health Survey in 2004. Plasma total DLC levels were quantified by measuring the aryl hydrocarbon receptor-mediated transcriptional activity elicited by plasma sample extracts in a cell-based reporter gene assay. Plasma concentrations of DL-PCBs nos. 105, 118, 156, 157, 167 and 189 were measured by gas chromatography-mass spectrometry. We used multiple linear regression analyses to investigate relations between total DLCs or specific DL-PCBs and SI, taking into consideration several potential confounders. RESULTS: Neither total plasma DLCs nor specific DL-PCBs were associated with SI after adjustment for several confounders and covariates. CONCLUSION: Our results do not support a relation between exposure to DLCs and bone strength measured by ultrasonography in Inuit women of Nunavik.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".