Paper
21 March 2023 Study on the influence factors of community built environment on residents’ hypertension
Yao Jing, Jingjing Tang, Yu Tai, Yuwei Li, Xinran Wang, Beichen Wang
Author Affiliations +
Proceedings Volume 12609, International Conference on Computer Application and Information Security (ICCAIS 2022); 126091X (2023) https://doi.org/10.1117/12.2671682
Event: International Conference on Computer Application and Information Security (ICCAIS 2022), 2022, ONLINE, ONLINE
Abstract
The improvement of urban built-up environment is conducive to constructing a green city, promoting residents’ active life, and preventing and relieving hypertension. Based on the questionnaire and blood pressure measurement data, this paper constructs a structural equation model of multiple intermediaries in built-up environment, health behavior and hypertension, so as to analyze the influential factors of built-up environment on residents’ hypertension and clarify its path for influencing behavior. Research shows that the built-up environment in urban community has a significant impact on residents’ hypertension, and is not disturbed by individual health status. High-density supermarkets, convenience stores, parks and squares as well as low-density clinics and hospitals are likely to increase residents’ risk of hypertension and affect hypertension through healthy behaviors. Therefore, to improve the built-up environment in urban community will help to change the hygienic behavior, and improve the general level of the health, of residents.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yao Jing, Jingjing Tang, Yu Tai, Yuwei Li, Xinran Wang, and Beichen Wang "Study on the influence factors of community built environment on residents’ hypertension", Proc. SPIE 12609, International Conference on Computer Application and Information Security (ICCAIS 2022), 126091X (21 March 2023); https://doi.org/10.1117/12.2671682
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KEYWORDS
Cardiovascular disorders

Roads

Blood pressure

Data modeling

Analytical research

Statistical modeling

Pollution

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