Examining the Association between Income Inequality and Physical Activity among Canadian Youth during the COVID-19 Pandemic
Bibliographic record
Abstract
Background Physical inactivity among Canadian adolescents has become an increasing concern in recent years. This trend has been further exacerbated by periods of societal disruption, such as the COVID-19 pandemic. However, the influence of broader contextual factors—particularly income inequality—on adolescent health behaviors during such crises remains unclear. The pandemic provides a unique opportunity to examine how socioeconomic disparities may have contributed to reduced physical activity levels among youth. Objectives The influence of contextual factors on adolescent health outcomes during times of crisis remains poorly understood. This study examines changes in physical activity levels among a sample of Canadian adolescents following the onset of the COVID-19 pandemic and investigates whether income inequality at the census division (CD) level contributed to physical activity changes, with a focus on gender-specific patterns. Methods Longitudinal data from 8,812 students aged 12 to 18 within 35 CDs were obtained from three waves (2020-21, 2021-22, 2022-23) of the Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, and Sedentary behaviour (COMPASS) study. CD-level income inequality was measured using Gini coefficients. Gender stratified multilevel models were used to analyze physical activity changes across survey waves and to quantify the association between income inequality and physical activity over the study period. Results Among the full sample, CD-level income inequality at the baseline was significantly associated with higher physical activity levels in both follow-up waves (2021-22: β = 0.042; 95% CI: 0.012, 0.072; 2022-23: β = 0.039; 95% CI: 0.009, 0.069). However, in the gender stratified analyses, income inequality was not significantly associated with physical activity in any survey wave for both males and females. Significant trends in physical activity levels among females (β = 0.057; 95% CI: 0.032, 0.081; β = 0.062; 95% CI: 0.038, 0.086) were observed across the two follow-up waves but not among males (β = 0.039; 95% CI: -0.004, 0.082; β = 0.034; 95% CI: -0.003, 0.082). Conclusion Physical activity levels increased among only females throughout the two follow-up waves. The association between income inequality and physical activity were significant in the full sample of adolescents. These unexpected findings emphasize the need for further research into how the mechanisms of income inequality and health related behaviours may have been affected by the COVID-19 pandemic.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".