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April 3, 2026Social Science & MedicineOpen Access

Profiling Spatiotemporal Contexts Associated with Compound Exposure Disadvantages in Noise and Greenery: A Study Using Mobile Sensors and Explainable Machine Learning

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Authors

LWLinsen WangMKMei-Po Kwan

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Overview

Examines compound disadvantages from noise and greenery exposure in daily mobility, suggesting socioeconomic factors influence these outcomes.

Key Points

  • The aim is to explore the nonlinear relationships between spatiotemporal contexts and compound disadvantages from noise and greenery exposure using mobile sensors.
  • Utilized mobile sensors, GPS, satellite imagery, and activity diaries to gather data on noise and greenery exposures.
  • Developed a compound disadvantage index based on daily mobility patterns identified through stay and move event sequences.
  • Applied a novel framework incorporating GPBoost, residual-based bootstraps, and SHAP to analyze data.
  • Investigated sociodemographic factors such as socioeconomic and employment status in relation to compound disadvantages.
  • Observed the neighborhood effect averaging problem in noise and greenery measurements.
  • Identified socioeconomic status and spatiotemporal contexts as significant predictors of compound disadvantages.
  • Found employment status to be the primary socioeconomic predictor of compound disadvantages.
  • Bootstrapped SHAP methodology highlighted key spatiotemporal contexts and interactions with socioeconomic status.

Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69cf5d055a333a821460a9fchttps://doi.org/10.1016/j.socscimed.2026.119254
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Also Consider

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  3. 3Daily active-mobility green space exposure and subjective health: An age-comparative perspective2026
  4. 4Green Space and Healthy Aging: Evidence from Static and Dynamic Green Space Exposure Measurements2025
  5. 5Demographic Associations with GPS-Inferred Routine Activity Spaces: Data from the Everyday Environments and Experiences (E3) Study2026