基于理性选择理论的广州不同类型社区老年人独立居住特征及影响因素

已有研究表明,中国城市有独立居住意愿和实现独立居住安排的老年人比例不断上升,这将对家庭养老和社区治理产生影响。本文基于理性选择理论,利用2018—2019年在广州旧街坊社区、单位社区、保障房社区、商品房社区、城中村社区和城郊农村社区收集的老年人问卷调查数据,从个人理性、家庭理性和社区理性三个层次出发,选取人口、健康、经济、代际关系和社区关系因素构建指标体系,用ANOVA单因素方差法分析独立居住老年人的特征及其社区分异,构建二元Logistic回归模型分析老年人独立居住的影响因素及其社区分异。研究发现：① 与和子女同住的老年人相比,独立居住的老年人年龄大、受教育程度高、拥有本地户口、个人经济能力强、有住房所有权、代际关系松散以及社区关系紧密等特征更明显。② 老年人的人口特征、社会经济属性和居住选择在不同类型社区中表现出明显的差异性。③ 老年人的个人理性、家庭理性和社区理性按不同的方式组合,形成了差异化的选择机制。

Characteristics and influencing factors of elderly people's independent living in different communities of Guangzhou based on rational choice theory

Previous studies have noted that not only the proportion of elderly people who are willing to live independently but also the proportion of those who truly live independently has continued to increase in Chinese cities in recent years. This trend will produce a great impact on family support of elderly people and community governance in aging society. In order to figure out the characteristics of elderly people's independent living and the factors influencing their choice to live independently, the research team designed a questionnaire and conducted a survey in Guangzhou’s communities in 2018-2019. Variables from this questionnaire were selected to establish an index system for analysis. The index system combined the three levels of rational choice theory, namely individual, family, and community rationality. First, the surveyed communities were classified into six types, namely old town, enterprises or institutions, affordable housing, commercial housing, urban village, and suburban rural communities. Second, the respondents’ characteristics in terms of demographics, health, finances, intergenerational relations, and community relations were compared among the six community types by using one-way analysis of variance. Through binary logistic regression, one model was developed to analyze the factors influencing independent living arrangements among all elderly people, and six models were developed to analyze the factors influencing independent living arrangements among elderly people in the six community types. Finally, on the basis of the estimations made by the seven models, this study explored the mechanisms of elderly people’s decision to live independently in different communities. The following are conclusions out of the analysis of this paper: (1) Compared with elderly people who live with their children or caretakers, those who live independently are more likely to be older, be better educated, be local residents, have stronger finances, be homeowners, have looser intergenerational relationships, and have stronger community attachments. (2) The demographic, socioeconomic, and residential characteristics of elderly people vary by community type. (3) Individual, family, and community rationality interact differently among the population of elderly adults, resulting in different rational selection mechanisms in the six community types.