Lifestyle-Related Behavior and Self-Reported Health Status Among Seventh-Day Adventists
Bibliographic record
Abstract
Longevity and lower incidence of chronic disease of Seventh-day Adventists in North America are well documented. Seventh-day Adventists, in general, follow healthy lifestyle compared to the general population even though there is some variation among themselves. The objective of our study was to assess the degree to which differences in adherence to the healthy lifestyle impacts self-reported health status. Our sample consisted of 58,866 individuals in the Adventist Health Study-2 cohort recruited between 2002-2007 in the United States and Canada who answered the baseline questionnaire. In this study, we used a framework developed by Grossman to estimate health outcomes relative to behavior. Our data were based on self-reported health status, demographic and lifestyle questions, and ordered probit technique was used to measure the health investment equation. Our findings showed that lifestyles aligned with health principles of this group, particularly in nutrition, exercise, and restraint from tobacco, were associated with a higher reported health status. The predictions based on variables such as age and education were also validated in this group. Interaction between variables including race and gender show results similar to other findings. Our study shows that practices consistent with the group's norms have higher probability of reporting excellent health.
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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 | 0.002 |
| 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".