Environmental deterioration in urbanizing areas increases the risks of sudden death as well as chronic, infectious, and psychological diseases. Quantifying health-related physical environment can assess the health risk of urban residents. This study uses an integrated evaluation method to simulate the health-related physical environment in the four dimensions of acoustic, wind, thermal, and landscape. According to the case study of one university campus in an urbanizing area in China, results show that (1) areas with unqualified equivalent A sound levels are generally the sports area, green square 1 and laboratory areas, and residents who stay in these areas for a long time suffer the risks of hearing loss and mental stress. (2) The windless area ratio of teaching area 1 and dormitory area 4 is larger than 20%, and respiratory health risks increase because these areas relate to relatively wind discomfort. (3) The high-temperature zone ratio of sports area and green square 2 is larger than 50%, and heatstroke risks increase since these areas relate with low thermal comfort. (4) The overall landscape perception level of dormitories and dining areas is lower than that of the teaching area, and it can cause anxiety and irritability. (5) The sports area has the lowest average overall score of the health-related physical environment among all functional areas, followed by laboratory areas. These findings indicate that the proposed model and method can be valuable tools for the pre-evaluation and optimization of urban planning. It can reduce the health risks of residents in urbanizing areas and can benefit residents' health and urban sustainable development.

The COVID-19 pandemic introduced risks and challenges to global food and nutrition security. In this paper, we examine the impact of the COVID-19 pandemic on the nutritional intake of China’s rural residents using panel data and a fixed effects model. The data were collected in 2019 and 2020 and covered nine provinces and 2631 households in rural China. The results reveal that an increase of 100 confirmed cases in a county resulted in a 1.30% (p < 0.01), 1.42% (p < 0.01), 1.65% (p < 0.01), and 1.15% (p < 0.01) decrease in per capita intake of dietary energy, carbohydrates, fats, and proteins, respectively. Moreover, the COVID-19 pandemic had a significant and negative effect on dietary macronutrient intake in the low-income group at the 5% level of significance. Our study indicates that the potential insufficient nutrition situation, nutritional imbalance, and dietary imbalance of low-income rural residents should be addressed appropriately.