Machine Learning Approach to Examine the Influence of the Community Environment on the Quality of Life of the Elderly

The quality of life (QoL) of the elderly has gradually become the focus of contemporary research. Elderly spent certain time staying at the community in their daily life, while studies have claimed the close relationships between built environment and the QoL of the elderly. With the advancement in the analytical tools, this paper aims to apply the machine learning approach to empirically examine the influence of the community environment on the QoL of the elderly. After extensive literature of relevant knowledge, a questionnaire survey was administered among the elderly. The collected quantitative data were subjected to a series of mathematical and statistical analysis analyses, and regression models for the relationship between community environment and the QoL of the elderly were established through support vector machine method. The results show that: 1) both the factors related the space and environment of the community can influence the QoL of the elderly; and 2) it was interesting to note that none of the facilities factor in the community imposes impact on their QoL. Practical recommendations are put forward according the research results in order to improve the community environment for the elderly, including building enough space, optimizing layout of monitoring equipment, maintaining ventilation to ensure air quality, and so on. This paper mainly contributes to apply the machine learning approach for examining the influence of community environment on the QoL of the elderly, which should enhance current body knowledge about the research related to the built environment for the elderly. The research findings should be helpful for the policy makers, facilities managers and academics to effectively improve existing practices regarding the management of community environment for better QoL of the elderly.