Association Between Public Transit Use and Happiness Across Four Canadian Cities: A Multilevel Analysis Using Longitudinal Data
Bibliographic record
Abstract
Introduction: Our daily travel habits can affect how we feel. For cities to be resilient and habitable, sustainable transportation is essential. As cities are increasingly interested in well-being, better understanding the impact of people’s use of public transit can help design happier cities. This research explores how transit use is linked to happiness, specifically accounting for gender and educational attainment. Objectives: The objective of my research is to examine the relationship between residents’ use of public transit and happiness in four Canadian cities (Victoria, Vancouver, Montréal, and Saskatoon). I hope to contribute to the literature examining sustainable transportation by bringing attention to the possible association between public transit and happiness. Research Questions: I investigated three key questions: 1. What is the association between public transit use and happiness in four Canadian cities? 2. Do gender and educational attainment modify or interact with the association between public transit use and happiness in four Canadian cities? 3. Do gender and educational attainment mediate the relationship between public transit use and happiness? Methods: I used data collected from four Canadian cities (Victoria, Vancouver, Montréal, and Saskatoon) over two waves between May 2017 and February 2021 from 3,539 participants of the INTERACT (The INTerventions, Equity, Research, and Action in Cities Team) study. INTERACT is a population health urban intervention research program. The outcome variable, happiness, was measured using the Subjective Happiness Scale (SHS), which captures individuals’ overall self-evaluation of happiness and reflects the hedonic dimension of happiness—emphasizing pleasure, life satisfaction, and positive emotional states. I conducted multilevel linear models (MLMs) regression to examine the association between happiness and self-reported use of public transit. In separate models, I examined the association between frequency of public transit use, among public transit users, and happiness. I further tested the potential effect-modifying and mediating roles of gender and educational attainment in the association between public transit use and happiness. Results: Descriptive analyses revealed that most participants reported moderate to high happiness levels, with notable differences by gender, education, and city. In multilevel models including all transportation users, transit use was not significantly associated with happiness overall. Among transit users only, more frequent transit use was associated with lower happiness, although this effect was attenuated after adjusting for covariates. Mediation analyses showed that education significantly mediated the transit–happiness relationship, while gender had a weaker, marginal effect. Adjusted models consistently demonstrated better fit and more normally distributed residuals, supporting the robustness of the findings. Conclusion: Knowing the relationship between public transit and happiness can help guide decisions regarding policy and urban development strategies. This research aims to support happy and sustainable communities by improving transit systems and making them more appealing and efficient. Urban areas can improve their overall livability and quality of life by putting their citizens’ happiness first when designing transportation systems.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.011 |
| Open science | 0.001 | 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".