Objective Building a healthy China is an important part of urban construction. At present, respiratory diseases have become one of the diseases that seriously affect the physical and mental health of residents, unhealthy living environments, especially unhealthy neighborhood environments where people live for a long time, are important triggers of respiratory diseases. Exploring the impact of the neighborhood environment on respiratory diseases has become a key concern in the construction of a healthy China.
Methods Based on the hospitalization information about respiratory diseases in the respiratory department of a tertiary hospital in a prefecture-level city during the period from 2015 to 2018, this research probes into the influence of neighborhood environment on respiratory health. Specifically, the research statistically analyzes relevant data on the patients with respiratory disease and derives the overall characteristics thereof using the SPSS software, explores the spatial distribution characteristics of such diseased population using the spatial regression analysis method, and analyzes the local Moran’s I using the GeoDa software. In addition, the research selects some potential influencing factors in the neighborhood environment, and investigates the correlation between respiratory diseases and the neighborhood environment by virtue of the ordered logistic regression model.
Results 1) The proportion of male patients in the diseased population mentioned above is significantly higher than that of female ones, the number of elderly male patients and middle-aged female ones is relatively high, and seasonal changes have a greater impact on children’s illnesses without any significant impact on other age groups. 2) The spatial distribution of patients is characterized by scattered clustering, and the southern part of the research area is characterized by significant high-aggregation clustering. As to spatial clustering characteristics, the diseased population presents significant high-high aggregation characteristic. 3) Respiratory diseases are affected by a number of neighborhood environment factors. For example, high-density living environment may affect the health of human respiratory system, perfect transportation service facilities are a powerful means to reduce air pollution and promote respiratory health, and street greening can significantly improve people’s respiratory health at the community level. 4) Community L, a representative community with high prevalence of respiratory disease, is selected as an example for optimization design of neighborhood environment from the four aspects of walking space, building space, green space and street scale, so as to provide a reference for researches on the relationship between neighborhood environment and respiratory health and on the healthy design of neighborhood environment.
Conclusion Respiratory diseases are influenced by factors such as neighborhood environment, social environment, and distributional characteristics of community groups. In this research, it was found that floor area ratio is the main negative factor affecting the respiratory health of residents; the density of transportation facilities, street view greenness, and sky openness can all have a positive impact on respiratory health to a certain extent. In summary, this research explores specific paths for optimizing the design of healthy neighborhood environments, and explores the combination of tool analysis language and spatial design language in the interdisciplinary research field of urban environment and respiratory health, providing reference and inspiration for the development of healthy city construction and related research.
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