Birth Weight and Risk of Adiposity among Adult Inuit in Greenland
Bibliographic record
Abstract
OBJECTIVE: The Inuit population in Greenland has undergone rapid socioeconomic and nutritional changes simultaneously with an increasing prevalence of obesity. Therefore, the objective was to examine fetal programming as part of the aetiology of obesity among Inuit in Greenland by investigating the association between birth weight and measures of body composition and fat distribution in adulthood. METHODS: The study was based on cross-sectional data from a total of 1,473 adults aged 18-61 years in two population-based surveys conducted in Greenland between 1999-2001 and 2005-2010. Information on birth weight was collected from birth records. Adiposity was assessed by anthropometry, fat mass index (FMI), fat-free mass index (FFMI), and visceral (VAT) and subcutaneous adipose tissue (SAT) estimated by ultrasound. The associations to birth weight were analyzed using linear regression models and quadratic splines. Analyses were stratified by sex, and adjusted for age, birthplace, ancestry and family history of obesity. RESULTS: Spline analyses showed linear relations between birth weight and adult adiposity. In multiple regression analyses, birth weight was positively associated with BMI, waist circumference, FMI, FFMI and SAT with generally weaker associations among women compared to men. Birth weight was only associated with VAT after additional adjustment for waist circumference and appeared to be specific and inverse for men only. CONCLUSIONS: Higher birth weight among Inuit was associated with adiposity in adulthood. More studies are needed to explore a potential inverse association between birth size and VAT.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".