Coming to grips with economic development: Variation in adult hand grip strength during health transition in Vanuatu
Bibliographic record
Abstract
OBJECTIVES: To determine whether (1) maximal handgrip strength (HGS) is associated with inter-island level of economic development in Vanuatu, (2) how associations between island of residence and HGS are mediated by age, sex, body size/composition, and individual sociodeomographic variation, and (3) whether HGS is predictive of hypertension. MATERIAL AND METHODS: HGS was collected from 833 adult (aged 18 and older) men and women on five islands representing a continuum of economic development in Vanuatu. HGS was measured using a handheld dynamometer. Participants were administered in an extensive sociobehavioral questionnaire and were also assessed for height, weight, percent body fat, forearm skinfold thickness, forearm circumference, and blood pressure. RESULTS: HGS was significantly greater in men than in women regardless of island of residence. HGS was also significantly positively associated with inter-island level of economic development. Grip strength-to-weight ratio was not different across islands except in older individuals, where age-related decline occurred primarily on islands with greater economic development. HGS significantly declined with age in both men and women. CONCLUSION: HGS is positively associated with modernization in Vanuatu, but the relationship between HGS and modernization is largely due to an association of both variables with increased body size on more modernized islands. Further research on the role of individual variation in diet and physical activity are necessary to clarify the relationship between HGS and modernization.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".