Association between alcohol consumption and body mass index in university students
Bibliographic record
Abstract
Objective: The aim of this study was to determine the correlation between alcohol consumption and body mass index in university students in Eastern Thailand.Methods: Undergraduate students (19-23 years, n = 396) were randomly surveyed via questionnaires, which included general information, alcohol consumption, and unhealthy food consumption.Average daily alcohol consumption was then calculated from grams of ethanol consumed per day.A subject, who has body mass index (BMI) more than 23 kg/m 2 , was defined as excessive weight.Difference between genders of each variable was compared using independent t-test.Mean of each variable between groups was compared using analysis of variance (ANOVA).The correlation between average daily alcohol consumption and BMI, unhealthy consumption and BMI were analyzed by applying Pearson correlation coefficient.Results: 229 university students consumed alcohol (58%).After 229 subjects were divided into three categories, the average daily alcohol consumption of the overweight group was significantly higher than the underweight and normal weight groups in women; meanwhile, unhealthy food consumption frequencies was not different between groups.Average daily alcohol consumption levels for overweight group were 74.17 and 73.45 g/day in men and women, respectively.Furthermore, higher daily alcohol consumption was independently associated with higher BMI (95% confidence interval [CI] R = 0.161: p = 0.015; men R = 0.120: p = 0.236; women R = 0.214: p = 0.015).Conclusion: There was a positive relationship between alcohol consumption and BMI in university students in Eastern Thailand.This study supports that the daily alcohol consumption is a risk factor for excessive weight and gender may contribute to the correlation.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".