Exploring the longitudinal associations between census division income inequality and BMI trajectories among Canadian adolescent: Is gender an effect modifier?
Bibliographic record
Abstract
Background: Income inequality is a structural determinant of health linked to increased risk of overweight and obesity, although its links to the health of adolescent populations are not well understood. This study investigated the longitudinal associations between census-division-level (CD) income inequality and BMI trajectories among Canadian adolescents, and determine if these associations vary by gender. Methods: Study data are from the Cannabis use, Obesity, Mental health, Physical Activity, Alcohol use, Smoking, and Sedentary behaviour (COMPASS) cohort of adolescents attending secondary schools in Canada. Our sample included 14,675 adolescents who were followed up across three waves of the COMPASS study (2016-2017, 2017-2018, and 2018-2019) and linked to 30 CDs. Measures of income inequality and other area-level covariates were derived and linked to COMPASS participants using data from the 2016 Canadian Census. We utilized multilevel mixed-effects linear regression modelling to quantify the associations between income inequality and BMI and test for effect modification by gender. Sensitivity analyses were run excluding those with BMI scores in the range considered overweight or obesity at baseline. Results: Higher CD income inequality was significantly associated with higher z-transformed BMI scores (β = 0.11, 95% CI = 0.034 to 0.19). The interaction term between income inequality and time was not statistically significant, indicating that this association remained constant over time. Once stratified by gender, the association between inequality and BMI became stronger for males (β = 0.14, 95% CI = 0.060 to 0.022) and attenuated for females (β = 0.063, 95% CI = -0.047 to 0.17). Conclusion: Attending schools in CDs with higher income inequality was associated with higher BMI scores among male but not female adolescents. Further work is needed to investigate this discrepancy and identify the structural mechanisms that mediate the relationship between inequality and adolescent health.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".