Cognitive impairment has emerged as a critical global public health issue. This study investigated the association between community and residential environments and the risk of cognitive impairment among Chinese middle-aged and older adults. The study included a final sample of 10,471 participants from the 2011–2020 The China Health and Retirement Longitudinal Study (CHARLS) cohort. Community and residential environment, and cognitive impairment, were assessed using several cognitive tests. The analyzed using the Cox Proportional Hazards Mode adjusting for age, gender, education level, marital status, residence areas, Body Mass Index (BMI), smoking status, alcohol consumption and chronic disease status. After adjusting for all Covariates, participants residing in relaxed community-based residential environments exhibited a 3.8% increased risk of cognitive impairment compared to those in crowded community environments (HR = 1.038). Middle-aged and older adults with access to garbage disposal services had a 19.3% reduced risk of cognitive impairment (HR = 0.807). Community environments featuring age-friendly facilities, such as open-air fitness equipment (HR = 0.834) and accessibility for handicapped individuals (HR = 0.948), were associated with a 16.6% and 5.2% reduction in the risk of cognitive impairment, respectively. In community social support environments, having a social organization for the older adults was associated with a 16.2% reduction in cognitive impairment risk among middle-aged and older adults (HR = 0.838). Regarding housing factors, concrete and steel buildings were associated with an 18.7% lower risk of cognitive impairment compared to adobe or other types of buildings (HR = 0.813). Domestic amenities, including running water supply (HR = 0.847), broadband connectivity (HR = 0.650), and use of clean energy (HR = 0.957), were associated with a 15.3%, 35%, and 4.3% reduction in the risk of cognitive impairment, respectively. Additionally, indoor tidiness (HR = 0.875) was associated with a 12.5% reduction in cognitive impairment risk. The good community and residential environment are correlated with the lower risk of cognitive impairment in middle-aged and older Chinese adults. Specifically, for the prevention and control of cognitive impairment, community and residential planning and construction should prioritize both the basic social and environmental factors and the internal built environment.

As a concept to describe the characteristics of urban spatial forms, urban grain emphasizes the size of urban parcels. Fine grain and coarse grain are considered essential attributes. Fine grain plays a crucial role in promoting the adaptability of urban development, improving urban vitality, and helping achieve sustainable urban development. Current research on urban grain is scattered and difficult to apply to solve practical urban problems. Therefore, this paper aims to identify the spatial indicators that affect the urban grain, to solve urban problems by adjusting spatial indicators. It contains significant suggestions for improving urban design theory and promoting sustainable urban development. This study primarily uses the comparative method to identify spatial indicators influencing urban grain by comparing coarse- and fine-grain study areas. This study screens relevant spatial indicators (building density, road network density, age of housing structures, building façade width along streets, number of entrances and exits along streets, and function mixture) affecting urban grain through a review and measurements, and it visualizes the representation of spatial indicators using the grid method, determining the correlation between spatial indicators and urban grain. The results show that all six indicators have an impact on urban grain.

Skywells are crucial for climate regulation in traditional Chinese dwelling architecture, exhibiting significant variations across climatic regions. This study focuses on humid–hot China, using Huangshan, to explore skywell parameters’ impact on thermal comfort and energy efficiency. Field research on 24 buildings in the World Heritage Site Xidi, Hong Villages, and Chinese Historical Pingshan Village, combined with Grasshopper’s Ladybug tool, established a parametric model. Using orthogonal design, performance simulation, and Python-based machine learning, six morphological parameters were analyzed: width-to-length ratio, height-to-width ratio, orientation, hall depth, wing width, and shading width. After NSGA-II multi-objective optimization, the summer Percentage of Time Comfortable (P_TC) increased by 5.3%, 38.14 h; the Universal Thermal Climate Index (UTCI) relatively improved by 2%; energy consumption decreased by 8.6%, 0.14 kWh/m²; and the useful daylight illuminance increased by 28%, 128.4 h. This confirms the climate adaptability of courtyard-style buildings in humid–hot China and identifies optimized skywell parameters within the study scope.

The industrial small-town development process in Shandong is influenced by the urban agglomeration strategy and the regional collaborative production, thereby resulting in a challenge of growth boundary planning. How to build a growth forecast decision support system to help small industrial towns maintain sustainable development with limited trial and error costs is an essential topic in the current research of small town-related fields. Empirical analysis reveals that the growth factors of small towns differ from the factors of cities due to the other-organization planning management system and self-organization construction activities that coexist in small towns. Besides, due to the size of small towns, the impact of policy changes in small towns is more significant than in cities. Furthermore, as part of the regional production chain, small industrial towns are most vulnerable to uncertain external disturbances. Therefore, it is necessary to formulate different development scenarios according to possible disturbances and output corresponding development forecasts. The research aims to build a decision-making support system for Shandong’s small-town planning based on an urban modeling approach using geographic information technology and scenario planning. Considering the mutually driving effects of the objective environment and subjective policies of Shandong’s industrial towns, as well as the corresponding dynamic mechanisms and comparing the theoretical basis and limitations of the different modeling approaches, this essay constructs a model system based on a mathematical model and a system dynamics model. It is also an interactive model accompanied by applicable rules and factors so that initial information and relevant development goals can be inputted into the model system to simulate the influence of different policies and identify the small industrial town growth scenarios.

Currently, the dominant gated communities (GCs) in Chinese cities have fragmented the urban road network, causing traffic congestion, energy consumption, carbon emissions, and environmental pollution. The morphological elements of GCs are key factors affecting road network connectivity. This paper aimed to explore the influence of the morphological elements of GCs on road network connectivity, to provide a quantitative basis for the evaluation and renovation of the connectivity of GCs, and to provide insights for urban planning and policy. This paper quantitatively analyzed the connectivity of GCs using 120 samples from the central districts of Jinan, China. Morphological elements were the independent variables, while route directness (RD) and the network distance (D) to the nearest entrance were the dependent variables. RD measured the internal connectivity, and D measured the connectivity between the internal and external road networks of GCs. GIS was used to measure RD and D, and SPSS was used to conduct a correlation analysis to identify significant variables. Multiple linear regression and LASSO regression were used to test the influence of these factors on RD and D. LASSO regression was employed to construct prediction models for RD and D. We found that intersection density had the greatest impact on RD, while the number of entrances and exits, and the scale of GCs, had the greatest impact on D. Using thresholds of D = 250 and RD = 1.3, the four types of GCs were classified and corresponding renovation measures were proposed.