利用双机器学习重新审视独立移动和健康老龄化的联系

IF 3.2 3区 工程技术 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Yuexia Chen, Wanru Du, Peng Jing, Yaqi Liu, Jie Ye, Huiqian Sun
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引用次数: 0

摘要

人口的快速老龄化给医疗资源带来了巨大压力,阻碍了健康老龄化。学者们强调了独立行动与健康老龄化之间的关键联系,因为它使老年人能够积极参与社会和社区生活。虽然现有的研究通常通过驾驶能力来评估独立出行能力,但它们往往忽视了其他出行方式的影响,比如公共交通和步行。常用出行方式的差异可能会影响老年人对独立出行的看法,从而影响其对健康老龄化的影响。方法采用双机器学习方法分析自主活动能力对健康老龄化的因果关系,并探讨社会参与在其中的中介作用。结果独立活动能力对健康老龄化的影响存在多个维度,其中焦虑对健康老龄化的影响最为显著。此外,社会活动,如太极和广场舞,表现出统计显著的中介效应。结论这些研究结果为政策制定者提供了有价值的见解,强调需要在促进社会参与的同时改善公共交通和行人基础设施,以促进老年人健康老龄化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Revisiting independent mobility and healthy aging connection using a double machine learning

Introduction

The rapid aging of the population has placed significant pressure on medical resources and hindered healthy aging. Scholars highlight the critical link between independent mobility and healthy aging, as it enables older adults to actively engage in social and community life. While existing studies often assess independent mobility through driving ability, they tend to overlook the impact of other travel patterns, such as public transport and walking. Differences in commonly used travel patterns may shape older adults’ perceptions of independent mobility, thereby influencing its effect on healthy aging.

Methods

This paper utilizes Double Machine Learning to analyze the causal effects of independent mobility on healthy aging and explores the mediation role of social participation in this relationship.

Results

The findings show that independent mobility impacts healthy aging in multiple dimensions, with anxiety being the most significantly affected. Additionally, social activities, such as tai chi and square dancing, exhibit a statistically significant mediation effect.

Conclusion

These results provide valuable insights for policymakers, emphasizing the need to improve public transportation and pedestrian infrastructure while promoting social participation to enhance healthy aging among older adults.
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来源期刊
CiteScore
6.10
自引率
11.10%
发文量
196
审稿时长
69 days
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