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Spatial scale analysis for the relationships between the built environment and cardiovascular disease based on

Jiwei Xu1, Ying Jing2, Xinkun Xu3

  • 1School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, PR China.

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Built environment characteristics impact cardiovascular disease risk. Multiscale analysis reveals global factors like socioeconomic deprivation and local factors like urban density influence health differently across spatial scales.

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Area of Science:

  • Environmental health
  • Urban planning
  • Epidemiology

Background:

  • Investigating built environment's impact on human health is crucial.
  • Existing research often overlooks the influence of spatial scales on built environment-health associations.
  • Understanding these multiscale relationships is key for targeted health interventions.

Purpose of the Study:

  • To analyze how built environment characteristics influence cardiovascular disease (CVD) risk across different spatial scales.
  • To identify which built environment attributes have global (large-scale) versus local (small-scale) effects on CVD.
  • To evaluate the effectiveness of multiscale geographically weighted regression (MGWR) for this analysis.

Main Methods:

  • Selected 18 variables from multi-source data, reduced to 8 built environment attributes using principal component analysis.
  • Attributes included socioeconomic deprivation, urban density, street walkability, land-use diversity, blue-green space, transportation convenience, ageing, and street insecurity.
  • Employed multiscale geographically weighted regression (MGWR) to model relationships between built environment attributes and cardiovascular disease at various spatial scales.

Main Results:

  • MGWR demonstrated a superior fit for built environment-cardiovascular disease associations compared to OLS and GWR.
  • Built environment variables were categorized into global (large-scale) and local (small-scale) factors impacting cardiovascular disease.
  • Global variables (socioeconomic deprivation, walkability, land-use diversity, blue-green space, transportation, ageing) showed minimal spatial variation, while local variables (urban density, street insecurity) exhibited significant spatial gradients.

Conclusions:

  • MGWR is an effective approach for analyzing built environment-health associations across multiple spatial scales.
  • Different built environment attributes exert influence at distinct spatial scales, impacting cardiovascular disease risk.
  • Findings underscore the need for hierarchical and place-specific policy development for health interventions in urban settings.