An aging population is one of the greatest global challenges, and it is estimated that the world’s population over the age of 60 years will reach nearly 2 billion by 2050. In particular, China’s population is aging dramatically, and mental health in old age has become an important social concern. In China, the number of so-called empty-nest elderly families is increasing, and has shown links to negative emotions related to aging, such as disappointment, loneliness, anxiety, and depression. Moreover, mood disorders are significantly associated with the development of dementia and could lead to higher morbidity and mortality in old age.
This study aimed to investigate the relationship between residential outdoor environments of different qualities and mood in the elderly. Nine residential neighborhoods across three different quality levels of the outdoor environment in Guangzhou, China, were surveyed. Measures included demographic characteristics, assessment of the residential outdoor environment, and mood status of the elderly. We constructed a group of multiple regression models to investigate influencing environmental factors of participants’ mood. Results revealed that the environmental factors influencing mood in the elderly are different across the three types of residential outdoor environments: function and cleanliness of the site showed a significant correlation with mood in high-quality residences, while pavement was significantly correlated with mood in medium-quality residences. In contrast, transparency, enclosure, greenness, temperature, and humidity were significantly correlated with mood in poor-quality residences. To promote mental health in the elderly, we recommend that different qualities of residential outdoor environments should be considered individually rather than aggregated as simply “outdoor space.” The findings of this study are expected to contribute to create age-friendly communities for an aging society.
负责人/Lead Designer：Chongxian Chen
成员/Team：Weijing Luo, Haiwei Li,Wangying Liang, Zhushen Chen, Peiyao Xiao, Yongqi Hou, Junjian Yu, Siyin Luo and Yu Xia