Gender Differences in Self-Rated Health among University Students in England, Wales and Northern Ireland: Do Confounding Variables Matter?
Bibliographic record
Abstract
INTRODUCTION: We assessed gender differences in self-rated health (SRH) while considering physical health, health complaints, health service use, wider wellbeing, and health behaviours. METHODS: 3706 undergraduates at 7 Universities in the United Kingdom completed a self-administered questionnaire (2009–2008). Logistic regressions with excellent/very good SRH as dependent variable assessed the variables that explained the SRH sex difference. RESULTS: Females had more health complaints, illness periods, lower quality of life, more burdens, and took medication/s more often. The crude (unadjusted) odds ratio (OR) proposed that females were less likely to report excellent/very good SRH than males [OR 0.79, 95% CI 0.68-0.94]. Adjusting only for physical health and health service use, females’ OR increased considerably, and the association between female sex and SRH was no longer significant. Also, when adjusting only for wider well-being or when adjusting only for health behaviour, the negative association between females and SRH was no longer significant. Adjusting for all the variables simultaneously (physical health, health service use, wider well-being, health behaviours) resulted in considerable increase of females’ OR indicating now a positive association between female sex and SRH [OR 1.33, 95% CI 1.04-1.74]. CONCLUSION: Females’ lower SRH found in the crude analyses was confounded by their higher stress level, lower quality of life, lower physical activity and by more illnesses or health complaints when compared with males. Gender-related SRH research should control for many potential confounders to prevent overestimation of the gender effect. Health promotion programs should consider these factors when tackling gender health disparities.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".