Bone mineral content among Inuit – a systematic review of data
Bibliographic record
Abstract
Inuit are a distinct ethnic group living in an environment likely to influence calcium metabolism and skeletal health. Bone mineral content (BMC) is a marker of skeletal health and fracture risk. Age is a dominant risk factor for osteoporosis, emphasising the importance of skeletal health in the ageing Inuit populations. This systematic review aims to provide an overview of data on BMC among Inuit. We performed a systematic search for data on BMC among Inuit guided by an experienced librarian. The search identified 211 studies, of which six provided data on BMC among Inuit living in Alaska or Canada. In men/women, BMC peaked around the age of 25 years in distal radius at 1.55/1.07 g/cm2 and in distal ulna at 0.81/0.54 g/cm2. Diaphysis of ulna, humerus, and tibia peaked around 10 years later. The 23% to 30% sex differences in BMC were similar across studies. Age related changes were parallel to other populations. In conclusion, BMC in Inuit is presented for easy viewing and comparison. BMC was similar between Inuit populations, and sex and age-related differences were comparable to other populations. New scientific studies should update data, include spine and hip, describe bone structure, and consider fracture risk beyond BMC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".