Traditional lifestyles, transition, and implications for healthy aging: An Example from the remote island of Pohnpei, Micronesia
Bibliographic record
Abstract
Lifestyle-related, non-communicable diseases, such as diabetes, hypertension, and obesity have become critical concerns in the Pacific islands of Micronesia. We investigated the relationship between the diminution of traditional lifestyle practices and the decline in the health of the population in the State of Pohnpei, Federated States of Micronesia. To assess this, our interdisciplinary team developed two scales, one to rank individuals on how traditional their lifestyles were and one to rank individuals on the healthiness of their lifestyles. Participants' locations were categorized as living on a remote atoll, living on the main island, or as a transitional population. Pohnpeians living in transitional communities (e.g. recently moved from a remote atoll to the main island, or the reverse) ranked lowest on both the tradition and health scales, rather than ranking intermediate between the remote and main island groups as we had hypothesized. As predicted, individuals residing on the remote atolls were living the most traditional lifestyles and also had the healthiest lifestyles, based on our rating system. The higher an individual scored on the tradition scale, e.g. the more traditional life they lived, the higher they scored on the health scale, suggesting the importance of traditional lifestyle practices for maintaining health. These findings have significant implications for promoting health and longevity of Micronesians and other Pacific Island peoples. We suggest the process of transition be recognized as a significant lifestyle and health risk and be given the attention we give to other risk factors that negatively influence our health. Based on our findings, we discuss and recommend the revitalization of particular traditional lifestyle practices, which may advance healthy aging among Pohnpeians.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".