Egg consumption associated with all-cause mortality in rural China: a 14-year follow-up study
Bibliographic record
Abstract
BACKGROUND: Dietary recommendations regarding egg intake remain controversial topic for public health. We hypothesized that there was a positive association between egg consumption and all-cause mortality. METHODS: To test this hypothesis, we enrolled 9885 adults from a community-based cohort in Anhui Province, China during 2003-05. Egg consumption was assessed by food questionnaire. Stratified analyses were performed for age, sex, body mass index (BMI), blood pressure, smoking, drinking and laboratory tests. RESULTS: After an average follow-up of 14.1 years, 9444 participants were included for analysis. A total of 814 deaths were recorded. Participants' BMI and lipid profile had no significantly difference between three egg consumption groups. BMI was 21.6±2.7 of the whole population, especially BMI>24 was only 17.3%. A bivariate association of egg consumption >6/week with increased all-cause mortality was observed compared with ≤6/week (RR: 1.35, 95% CI: 1.05, 1.73, P = 0.018). A significant interaction was observed for BMI ≥ 21.2 kg/m2 vs. BMI<21.2 kg/m2 (P for interaction: 0.001). No other significant interactions were found. CONCLUSIONS: In this study, consuming >6 eggs/week increased risk of all-cause mortality, even among lean participants, especially who with BMI ≥ 21.2 kg/m2. Eggs are an easily accessible and constitute an affordable food source in underdeveloped regions. Consuming <6 eggs/week may be the most suitable intake mode.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 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) | 0.000 | 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 teacher head, 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".