International Journal For Multidisciplinary Research

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The PE-Environment Mismatch: A GIS Spatiotemporal Analysis of School Physical Education Quality and Neighborhood Built Environments

Author(s) Dr. Anil Kumar N, Dr. Neena Thekka N
Country India
Abstract Institutional school-based Physical Education (PE) programs are primary policy instruments for combating adolescent sedentary behavior. However, pedagogical interventions frequently produce inconsistent longitudinal outcomes, which traditional kinesiology literature often at-tributes to micro-level instructional variables. This study introduces a broader socio-ecological perspective by examining the structural interaction between school PE quality and neighbor-hood built environments.
Using a cross-sectional stratified design involving N = 2400 adolescents aged 13–15 years across 35 school clusters, objective physical activity data obtained through seven-day triaxial accelerometry were integrated with Geographic Information System (GIS) indicators including walkability indices, intersection density, and Normalized Difference Vegetation Index (NDVI) measurements.
A three-level Hierarchical Linear Model (HLM) was employed to partition variance across student, school, and neighborhood levels. Findings revealed that environmental resistance sig-nificantly moderates the effectiveness of high-quality PE programs. Students residing in highly walkable neighborhoods demonstrated substantially higher Moderate-to-Vigorous Physical Ac-tivity (MVPA) levels, whereas students living in low-connectivity “sidewalk desert” environ-ments experienced marked reductions in post-school activity participation.
The findings suggest that physical literacy cannot be developed solely through institutional interventions. Educational policy, urban planning, and public health initiatives must operate collaboratively to create environments that support lifelong physical activity behaviors.
Keywords Physical Education, Built Environment, Geographic Information Systems, Walka-bility, Accelerometry, Hierarchical Linear Modeling, Urban Health, Physical Activity
Published In Volume 8, Issue 5, September-October 2026
Published On 2026-09-04
DOI https://doi.org/10.36948/ijfmr.2026.v08i05.87077
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