Health, Happiness and Eating Together: What Can a Large Thai Cohort Study Tell Us?
Bibliographic record
Abstract
Our research investigates the significance of frequent solo consumption of main meals and the association with a holistic wellbeing measure of happiness using data from 39820 Thai Cohort Study members who completed 8-year follow-up in 2013. This nationwide cohort has been under study since 2005 to analyse the dynamics and determinants of the health-risk transition from infectious to chronic diseases. Here we analyse data from the 2009 and 2013 follow-ups. Approximately 11% reported eating more than half of the main meals per week alone. Sociodemographic attributes associated with eating alone were being male, older age, unmarried, smaller household, lower income, and urban residence. Dissatisfaction with amount of spare time (ie 'busyness') was also linked to eating alone. In the multivariate cross-sectional model, reporting being unhappy was associated with frequent solo eating (Adjusted Odds Ratio - AOR 1.54, 95% Confidence Intervals 1.30-1.83). Stratified by age and sex groups, the effects were strongest among females (AOR 1.90 1.52-2.38). A monotonic relationship linked frequent eating alone and 4-year longitudinal unhappiness. The larger the dose of unhappiness the greater the odds of eating alone - AOR 1.29, 1.31, 1.72 after controlling for potential covariates. Having a meal is not only important for nutritional and health outcomes; it is also a vital part of daily social interaction. Our study provided empirical evidence from a non-Western setting that sharing meals could contribute to increasing happiness.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.019 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".