How mobility-based exposure measures may mitigate the underestimation of the association between green space exposures and health
Bibliographic Data
| ID | 4593382 |
|---|---|
| Authors | Yang Liu (0000-0003-1220-7044, Chinese University of Hong Kong), Mei-Po Kwan (0000-0001-8602-9258, Chinese University of Hong Kong), Liuyi Song (0000-0001-6018-6466, Chinese University of Hong Kong), Changda Yu (0000-0002-1688-490X, Chinese University of Hong Kong), Yuhan Cui (0009-0006-4946-4553, Chinese University of Hong Kong) |
| Year | 2025 |
| Volume | 379 |
| Pages | 118190 |
| Publication date | 2025-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Science & Medicine (JOURNAL) |
| Journal identifiers | ISSN: 0277-9536 • E-ISSN: 1873-5347 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.socscimed.2025.118190 |
| PMID | 40381281 |
| OpenAlex | W4410274724 |
| Language | EN |
| Citations received | 6 |
| References cited | 38 |
Recent urban green space research highlighted that mobility-based measures of green space exposure may significantly mitigate a particular type of exposure measurement error (contextual errors) of residence-based measures. In this study, we examined an important manifestation of the contextual errors of residence-based measures: neighborhood effect averaging. We analytically illustrated that the contextual errors of residence-based measures may lead to a considerable underestimation of the associations between green space exposures and human health, and the reduction of such underestimation can be quantified through a mitigating factor. We employed data from a cross-sectional survey to assess the usefulness of our analytics. Based on participants' 7-day GPS trajectories, we derived residence-based and mobility-based measures of participants' exposures to green space using a spatiotemporally weighted approach. Logistic regression was employed to estimate the associations between green space exposures and participants' overall health. We derived consistent and significant mitigating factors based on our analytics from the magnitudes of the estimated associations or the variances of green space exposure distributions. Our results indicate that mobility-based measures reduced about 20.9 % - 52.3 % of the underestimation of the associations between green space exposure and health, which reflected the considerable influence of exposure measurement errors. Our study sheds light on how contextual errors may obfuscate the association between green space exposures and human health, which may also be true for other mobility-dependent environmental factors. This has crucial implications for a broad range of environmental and public health studies that need accurate estimation of health impacts
Association (psychology · Environmental health · Public health · Sociology · Air Quality and Health Impacts · Computer Science · Demography · Medicine · Noise Effects and Management · Psychology · Urban Transport and Accessibility
Spectral configurations and interferences in outdoor artificial light at night (Alan) exposure measurements and sleep quality modeling
Analytical Derivations of the Neighborhood Effect Averaging Problem ( Neap ) and Its Two Variants
Quantifying noise complaint intensity via multi-LLM and revealing vertical greenery mitigation thresholds
Sampling the City
Unequal pathways
Pilot Investigation of the Social Group with Low Mobility and Doubly Disadvantageous Co-Exposure to Green Space and Outdoor Artificial Light at Night (Alan)
APA handbook of research methods in psychology, Vol 2
Analytical approaches to testing pathways linking greenspace to health
Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data
Trackintel
Investigating the neighborhood effect averaging problem (Neap) in greenspace exposure
Inconsistent Association between Perceived Air Quality and Self-Reported Respiratory Symptoms
Beyond Commuting
The Neighborhood Effect Averaging Problem (Neap)
The role of urban green space for human well-being
Current methods for evaluating people's exposure to green space
Nonstationary relationships among individuals’ concurrent exposures to noise, air pollution and greenspace
Conceptualization and measurement of environmental exposure in epidemiology
Understanding the relationships among individual-based momentary measured noise, perceived noise, and psychological stress
Cross-validation between GPS-derived trajectories and activity-travel diaries for transport geography studies
The Uncertain Geographic Context Problem
Algorithmic Geographies
Assessing momentary stress responses to dynamic real-time greenspace exposure
Examining individual-level tri-exposure to greenspace and air/noise pollution using individual-level GPS-based real-time sensing data
The spatial dimensions of neighborhood effects
Assessing patterns of spatial behavior in health studies
Uncertainties in the Assessment of Covid-19 Risk
How Neighborhood Effect Averaging Might Affect Assessment of Individual Exposures to Air Pollution
How Mobility and Temporal Contexts May Affect Environmental Exposure Measurements
| Unique citing works | 6 |
|---|---|
| Citations per year | 6 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 5 |