Does sitting height ratio affect estimates of obesity prevalence among Canadian Inuit? results from the 2007–2008 Inuit health survey
Bibliographic record
Abstract
OBJECTIVES: High sitting height ratio (SHR) is a characteristic commonly associated with Inuit morphology. Inuit are described as having short leg lengths and high trunk-to-stature proportions such that cutoffs for obesity derived from European populations may not adequately describe thresholds of disease risk. Further, high SHR may help explain the reduced impact of BMI on metabolic risk factors among Inuit relative to comparison populations. This study investigates the relationship between SHR and body mass index (BMI) in Inuit. METHODS: Subjects are 2,168 individuals (837 males and 1,331 females) from 36 Inuit communities in the Canadian Arctic. Mean age is 42.63 ± 14.86 years in males and 41.71 ± 14.83 years in females. We use linear regression to examine the association between age, sex, height, sitting height, SHR, waist circumference (WC), and BMI. We then evaluate the efficacy of the relative sitting height adjustment as a method of correcting observed BMI to a population-standardized SHR. RESULTS: Mean BMI is significantly higher than among non-Inuit Canadians. Obesity prevalence is high, particularly among Inuit women. In the regression, only age and WC are significant predictors of BMI. While SHR is significantly greater than that of the US population, there is substantial agreement between overweight and obesity prevalence using observed and corrected BMI. CONCLUSIONS: We find no consistent relationship between SHR and BMI and suggest the unique anthropometric and metabolic profile observed in Inuit arise from factors not yet delineated. More complex anthropometric and imaging studies in Inuit are needed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".