Ownership of consumer electronics is associated with measures of adiposity during health transition in Vanuatu
Bibliographic record
Abstract
OBJECTIVE: The Republic of Vanuatu, like many developing nations, is undergoing a rapid health transition. Our previous study identified several behavioral risk factors for the rising prevalence of obesity. Unexpectedly, daily time spent using television and radio was revealed as a protective factor for obesity in 2007. In this study, we sought to explore associations between ownership of consumer electronics (CE) and measures of adiposity in Vanuatu in 2011. METHODS: We surveyed 873 adults from five islands varying in level of economic development. Height, weight, and waist circumferences; triceps, subscapular, and suprailiac skinfolds; and percent body fat by bioelectrical impedance were measured. Ownership of eight types of CE, diet through 24-h dietary recall and leisure-time activity patterns were assessed using a questionnaire. RESULTS: Participants from more developed islands owned more types of CE, and revealed higher measures of adiposity on average as well as higher prevalence of obesity/central obesity. When controlling for demographic factors, and dietary and activity patterns, increased measures of adiposity and risk for obesity/central obesity were associated with ownership of cellphones, music players, televisions, video players, microwaves, and/or refrigerators. Positive correlations between CE ownership and measures of adiposity were mainly observed among men on the two most developed islands. CONCLUSIONS: The results of this study indicate a possible role of CE use in the rising prevalence of obesity and the shift to a sedentary lifestyle in Vanuatu and many other modernizing regions, where prevention efforts including education on healthy use of CE are imperative.
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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 | 0.000 |
| 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".