Reproductive factors, lifestyle and dietary habits among pregnant women in Greenland: The ACCEPT sub-study 2013–2015
Bibliographic record
Abstract
BACKGROUND: During past decades the formerly active lifestyle in Greenland has become sedentary, and the intake of traditional food has gradually been replaced with imported food. These lifestyle and dietary habits may affect pregnant women. AIM: To describe age and regional differences in reproductive factors, lifestyle and diet among Greenlandic pregnant women in their first trimester. METHODS: A cross-sectional study during 2013-2015 including 373 pregnant women was conducted in five Greenlandic regions (West, Disko Bay, South, North and East). Interview-based questionnaires on reproductive factors, lifestyle and dietary habits were compared in relation to two age groups (median age ≤28 years and >28 years). RESULTS: , 29.0% were smoking during pregnancy and 54.6% had used hashish. BMI, educational level, personal income, previous pregnancies and planned breastfeeding period were significantly higher in the age group >28 years of age compared to the age group ≤28 years of age. In region Disko Bay, 90.9% were Inuit, in region South more had a university degree (37.9%) and region East had the highest number of previous pregnancies, the highest number of smokers during pregnancy and the most frequent intake of sauce with hot meals and fast-food. CONCLUSIONS: Overall a high BMI and a high smoking frequency were found. Age differences were found for BMI and planned breastfeeding period, while regional differences were found for smoking and intake of sauce with hot meals and fast-food. Future recommendations aimed at pregnant women in Greenland should focus on these health issues.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".