Reorienting Age-Friendly Frameworks for Rural Contexts: A Spatial Competence-Press Framework for Aging in Chinese Villages

TL;DR

This paper introduces a GIS-based spatial stress framework tailored for rural aging in China, addressing the limitations of urban-centric models by quantifying terrain, infrastructure, climate, and agricultural burdens to inform targeted interventions.

Contribution

It develops a novel spatial competence-press model for rural aging, incorporating four key indicators and classifying villages by intervention needs, filling methodological gaps in rural aging research.

Findings

Significant variation in spatial stressors across villages.

Identification of distinct village typologies based on stress patterns.

Provision of practical tools for targeted rural aging interventions.

Abstract

While frameworks such as the WHO Age-Friendly Cities have advanced urban aging policy, rural contexts demand fundamentally different analytical approaches. The spatial dispersion, terrain variability, and agricultural labor dependencies that characterize rural aging experiences require moving beyond service-domain frameworks toward spatial stress assessment models. Current research on rural aging in China exhibits methodological gaps, systematically underrepresenting the spatial stressors that older adults face daily, including terrain barriers, infrastructure limitations, climate exposure, and agricultural labor burdens. Existing rural revitalization policies emphasize standardized interventions while inadequately addressing spatial heterogeneity and the spatially-differentiated needs of aging populations. This study developed a GIS-based spatial stress analysis framework that applies Lawton and Nahemow's competence-press model to quantify aging-related stressors and classify rural villages by intervention needs. Using data from 27 villages in Mamuchi Township, Shandong Province, we established four spatial stress indicators: slope gradient index (SGI), solar radiation exposure index (SREI), walkability index (WI), and agricultural intensity index (AII). Analysis of variance and hierarchical clustering revealed significant variation in spatial pressures across villages and identified distinct typologies that require targeted intervention strategies. The framework produces both quantitative stress measurements for individual villages and a classification system that groups villages with similar stress patterns, providing planners and policymakers with practical tools for designing spatially-targeted age-friendly interventions in rural China and similar contexts.