农村儿童留守的多维影响因素研究——基于Logistic回归模型的分析

A Study on Multidimensional Influencing Factors of Rural Left-Behind Children—An Analysis Based on a Logistic Regression Model

摘要: 本研究基于韶关市516份农村家庭问卷调查数据，采用二元Logistic回归模型，从儿童个人、家庭、农民工生存状态及社会四个维度实证分析农村儿童留守的影响因素。研究发现：儿童年龄增长会显著提升留守风险；父母职业稳定性高与家庭收入增加是重要保护因素；务工迁移距离远加剧留守，而务工年限长则促进随迁；务工地优质教学资源显著降低留守发生比。研究表明，农村儿童留守是家庭在个体发展、经济资本、就业状态与公共服务等多重约束下的复杂决策结果，破解这一困境需系统推进公共服务均等化、农村产业升级与社区支持网络构建。

Abstract: Based on questionnaire data from 516 rural households in Shaoguan City, this study employs a binary logistic regression model to empirically analyze the influencing factors of rural left-behind children from four dimensions: individual characteristics of the children, family attributes, migrant workers’ living conditions, and social context. The findings indicate that older children face a significantly higher risk of being left behind. Higher occupational stability of parents and increased household income serve as important protective factors, while longer migration distance of migrant workers increases the likelihood of children being left behind. In contrast, longer duration of migrant work promotes child accompaniment. Moreover, better teaching resources in destination areas significantly reduce the odds of children being left behind. The study concludes that the phenomenon of rural left-behind children stems from a complex decision-making process by households under multiple constraints, including child development, economic capital, employment status, and public service accessibility. Resolving this issue requires systematic improvements in equal access to public services, upgrading of rural industries, and the establishment of community-based support networks.