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Record W7106037699 · doi:10.7939/83262

Examining the Association between Income Inequality and Physical Activity among Canadian Youth during the COVID-19 Pandemic

2025· dissertation· en· W7106037699 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic inequalitySocioeconomic statusInequalityMultilevel modelPhysical activityPandemicSocial inequalityHealth equityAssociation (psychology)Gini coefficient

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.053
GPT teacher head0.311
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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