BMC public health · 2025
The effect of the urban built environment on the prevalence rate of chronic diseases in the community neighborhood level: a case study in Qingdao, China.
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Zhao Tianyi, Zhang Ao, Liu Yawen, Yin Yue, Xia Tianyu, Cheng Siqi, Shao Xin, Zhang Jinguang, Ding Kang
Аннотация
BACKGROUND: Chronic diseases such as hypertension (HTN) and type 2 diabetes mellitus (T2DM) are escalating global health burdens, particularly in rapidly urbanizing, high-density regions. While individual, socioeconomic, and behavioral risk factors are well-established, evidence on the influence of the urban built environment remains limited, especially in low- and middle-income countries (LMICs).
METHODS: This study applied the comprehensive 5D built environment framework to systematically analyze the associations between built environment characteristics and community-level prevalence of HTN and T2DM in Shibei District, Qingdao, a high-density urban area in China. We integrated official health records, socioeconomic data, remote sensing imagery, and geographic information systems. Key built environment metrics, including land use diversity, density and distribution of POIs, destination accessibility, distance to transit, and design of greenery, were evaluated alongside air quality and government fiscal resources. Statistical analyses including Pearson correlations, multivariable linear regressions, and spatial autocorrelation were conducted.
RESULTS: Higher vegetation coverage (NDVI) and increased local government revenue were significantly associated with lower HTN and T2DM prevalence, whereas higher road network density and PM10 concentrations were linked to increased disease risk. No significant associations were found for distance to blue spaces. Spatial autocorrelation analyses showed weak geographic clustering of disease prevalence.
CONCLUSION: The findings highlight that optimizing community green spaces, mitigating air pollution, and strategic public investment can reduce chronic disease burdens in high-density urban contexts. This study provides locally relevant empirical evidence for health-oriented urban planning in LMICs and underscores the necessity of integrating environmental, social, and health policies to promote urban health equity.
METHODS: This study applied the comprehensive 5D built environment framework to systematically analyze the associations between built environment characteristics and community-level prevalence of HTN and T2DM in Shibei District, Qingdao, a high-density urban area in China. We integrated official health records, socioeconomic data, remote sensing imagery, and geographic information systems. Key built environment metrics, including land use diversity, density and distribution of POIs, destination accessibility, distance to transit, and design of greenery, were evaluated alongside air quality and government fiscal resources. Statistical analyses including Pearson correlations, multivariable linear regressions, and spatial autocorrelation were conducted.
RESULTS: Higher vegetation coverage (NDVI) and increased local government revenue were significantly associated with lower HTN and T2DM prevalence, whereas higher road network density and PM10 concentrations were linked to increased disease risk. No significant associations were found for distance to blue spaces. Spatial autocorrelation analyses showed weak geographic clustering of disease prevalence.
CONCLUSION: The findings highlight that optimizing community green spaces, mitigating air pollution, and strategic public investment can reduce chronic disease burdens in high-density urban contexts. This study provides locally relevant empirical evidence for health-oriented urban planning in LMICs and underscores the necessity of integrating environmental, social, and health policies to promote urban health equity.