Behavioral risk factors for obesity during health transition in Vanuatu, South Pacific
Bibliographic record
Abstract
UNLABELLED: The South Pacific archipelago of Vanuatu, like many developing countries, is currently experiencing a shift in disease burdens from infectious to chronic diseases with economic development. A rapid increase in obesity prevalence represents one component of this "health transition." OBJECTIVE: To identify behaviors associated with measures of obesity in Vanuatu. DESIGN AND METHODS: Five hundred and thirty four adults from three islands varying in level of economic development were surveyed. Height, weight, waist, and hip circumferences; triceps, subscapular and suprailiac skinfolds; and percent body fat (%BF) by bioelectrical impedance were measured. Diet through 24-h dietary recall and physical activity patterns using a survey were assessed. We analyzed prevalence of obesity and central obesity based on multiple indicators (body mass index, %BF, waist circumference, and waist-to-height ratio), and analyzed differences among islands and associations with behavioral patterns. RESULTS: Obesity prevalence was lowest among rural and highest among suburban participants. Prevalence of central obesity was particularly high among women (up to 73.9%), even in rural areas (ranging from 14.7 to 41.2% depending on the measure used). Heavier reliance on animal protein and incorporation of Western foods in the diet-specifically, tinned fish and instant noodles-was significantly associated with increased obesity risk. CONCLUSIONS: Even in rural areas where diets and lifestyles remain largely traditional, modest incorporation of Western foods in the diet can contribute to increased risk of obesity. Early prevention efforts are thus particularly important during health transition. Where public health resources are limited, education about dietary change could be the best target for prevention.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".