Reassessing the non-linear causal link between long-duration commuting and self-rated health: do behavioral preferences and built environment matter? Article Swipe
Ning Qiu
,
Wen Li
,
Dinghe Cui
,
Mengbing Du
,
Zibo Xing
,
Dongxu Cui
,
Han Xinyu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3389/fpubh.2024.1452014
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3389/fpubh.2024.1452014
Introduction Long-duration commuting is widely recognized for its significant influence on health. However, while research has traditionally focused on direct impacts, there remains a critical need to explore the nonlinear dynamics of this relationship. This study aims to deepen our understanding of how behavioral preferences and built environments contribute to these complex interactions. Methods This study was conducted in Jinan, China’s most congested city, using data from the “Jinan Residents Commuting Survey” of 1,755 participants aged 19 to 59. We applied Generalized Propensity Score Matching (GPSM) to explore the nonlinear effects of commuting time on self-rated health, adjusting for participants’ sociodemographic characteristics. Variables related to active commuting, physical activity, and perceived built environment were also examined for their potential moderating effects. Results Commuting for less than 21 minutes enhances health, but negative effects intensify and peak at 60 minutes. Heterogeneity analysis reveals that women and older adults, especially those with higher incomes, are more susceptible to long commutes, experiencing a delayed onset of adverse effects. While active commuting offers health benefits, it may exacerbate health issues if prolonged. Conversely, regular physical activity consistently improves health outcomes related to commuting. Additionally, factors like residential greenery and walkability help alleviate commuting-related stress, improving the overall commuting-health dynamic. Discussion This study clarifies the commuting-health relationship by identifying key time thresholds and the positive effects of active commuting and physical activity on mitigating longer commute impacts. The findings inform healthier commuting behaviors and offer practical guidelines for urban planning and policy-making to enhance commuter well-being.
Related Topics
Concepts
Built environment
Environmental health
Occupational safety and health
Matching (statistics)
Walkability
Duration (music)
Psychology
Human factors and ergonomics
Injury prevention
Gerontology
Level design
Poison control
Medicine
Ecology
Computer science
Human–computer interaction
Game design
Literature
Biology
Pathology
Art
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fpubh.2024.1452014
- OA Status
- gold
- Cited By
- 1
- References
- 61
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403080263
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4403080263Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fpubh.2024.1452014Digital Object Identifier
- Title
-
Reassessing the non-linear causal link between long-duration commuting and self-rated health: do behavioral preferences and built environment matter?Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-10-02Full publication date if available
- Authors
-
Ning Qiu, Wen Li, Dinghe Cui, Mengbing Du, Zibo Xing, Dongxu Cui, Han XinyuList of authors in order
- Landing page
-
https://doi.org/10.3389/fpubh.2024.1452014Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.3389/fpubh.2024.1452014Direct OA link when available
- Concepts
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Built environment, Environmental health, Occupational safety and health, Matching (statistics), Walkability, Duration (music), Psychology, Human factors and ergonomics, Injury prevention, Gerontology, Level design, Poison control, Medicine, Ecology, Computer science, Human–computer interaction, Game design, Literature, Biology, Pathology, ArtTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- References (count)
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61Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.examined | 115 |
| abstract_inverted_index.findings | 233 |
| abstract_inverted_index.greenery | 193 |
| abstract_inverted_index.impacts, | 20 |
| abstract_inverted_index.impacts. | 231 |
| abstract_inverted_index.improves | 183 |
| abstract_inverted_index.incomes, | 151 |
| abstract_inverted_index.minutes. | 138 |
| abstract_inverted_index.negative | 131 |
| abstract_inverted_index.outcomes | 185 |
| abstract_inverted_index.physical | 107, 180, 225 |
| abstract_inverted_index.planning | 244 |
| abstract_inverted_index.positive | 219 |
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| abstract_inverted_index.China’s | 60 |
| abstract_inverted_index.Commuting | 70, 122 |
| abstract_inverted_index.Residents | 69 |
| abstract_inverted_index.Survey” | 71 |
| abstract_inverted_index.Variables | 102 |
| abstract_inverted_index.activity, | 108 |
| abstract_inverted_index.adjusting | 97 |
| abstract_inverted_index.alleviate | 197 |
| abstract_inverted_index.behaviors | 237 |
| abstract_inverted_index.benefits, | 170 |
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| abstract_inverted_index.commutes, | 157 |
| abstract_inverted_index.commuting | 2, 92, 167, 223, 236 |
| abstract_inverted_index.conducted | 57 |
| abstract_inverted_index.congested | 62 |
| abstract_inverted_index.healthier | 235 |
| abstract_inverted_index.improving | 200 |
| abstract_inverted_index.influence | 9 |
| abstract_inverted_index.intensify | 133 |
| abstract_inverted_index.nonlinear | 29, 89 |
| abstract_inverted_index.perceived | 110 |
| abstract_inverted_index.potential | 118 |
| abstract_inverted_index.practical | 240 |
| abstract_inverted_index.Discussion | 205 |
| abstract_inverted_index.Propensity | 82 |
| abstract_inverted_index.behavioral | 43 |
| abstract_inverted_index.commuting, | 106 |
| abstract_inverted_index.commuting. | 188 |
| abstract_inverted_index.contribute | 48 |
| abstract_inverted_index.especially | 147 |
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| abstract_inverted_index.guidelines | 241 |
| abstract_inverted_index.mitigating | 228 |
| abstract_inverted_index.moderating | 119 |
| abstract_inverted_index.prolonged. | 177 |
| abstract_inverted_index.recognized | 5 |
| abstract_inverted_index.self-rated | 95 |
| abstract_inverted_index.thresholds | 216 |
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| abstract_inverted_index.Generalized | 81 |
| abstract_inverted_index.environment | 112 |
| abstract_inverted_index.identifying | 213 |
| abstract_inverted_index.preferences | 44 |
| abstract_inverted_index.residential | 192 |
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| abstract_inverted_index.walkability | 195 |
| abstract_inverted_index.well-being. | 250 |
| abstract_inverted_index.Introduction | 0 |
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| abstract_inverted_index.experiencing | 158 |
| abstract_inverted_index.participants | 74 |
| abstract_inverted_index.relationship | 211 |
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| abstract_inverted_index.Heterogeneity | 139 |
| abstract_inverted_index.Long-duration | 1 |
| abstract_inverted_index.interactions. | 52 |
| abstract_inverted_index.policy-making | 246 |
| abstract_inverted_index.relationship. | 33 |
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| abstract_inverted_index.sociodemographic | 100 |
| abstract_inverted_index.commuting-related | 198 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.5899999737739563 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.7947466 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |