Effect of sex/gender on obesity traits in Canadian first year university students: The GENEiUS study
Bibliographic record
Abstract
BACKGROUND: While weight gain during first year of university has been well documented in North America, literature on sex-specific effects is scarce and inconsistent. The objective of this investigation was to explore sex-specific changes in obesity traits during first year of university at McMaster University (Ontario, Canada). METHODS: 245 first-year students (80.4% females) were followed longitudinally with data collected early in the academic year and towards the end of the year. Obesity parameters including weight, waist and hip circumferences, BMI, and waist to hip ratio were investigated. The Mann-Whitney U test and the Wilcoxon signed-rank test were used for pairwise comparison of traits in the absence of adjustments. Additionally, the repeated-measures ANOVA test was used with covariate adjustments to investigate the interaction between sex and time. RESULTS: Overall sample trends indicated a significant increase in mean weight by 1.55 kg (95% CI: 1.24-1.86) over the school year (p<0.001). This was accompanied by significant gains in BMI, and waist and hip circumferences (p<0.001) in the overall sample. At baseline, males presented with higher body weight, BMI, waist and hip circumferences, and WHR, as compared to their females counterparts (p<0.01). Additionally, sex-stratified analysis indicated significant gains in weight, BMI, and waist and hip circumferences in both males and females (p<0.01). However, a comparison of the magnitude of change over time between the two sex groups revealed no significant difference for any of the investigated traits (p>0.05). CONCLUSION: While our study confirms significant weight gain in both male and female first year university students in Ontario, Canada, it does not show sex specific differences within this context. Our investigation highlights the importance of accounting for sex and gender in health research and supports the need of further studies in this area.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".