得克萨斯州奥斯汀市中产阶级化社区的心理健康结构方程模型

A. Iyanda, Yongmei Lu
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引用次数: 3

摘要

心理健康状况不佳可能危及生命,与之相关的问题在美国各地的社区都很普遍。奥斯汀市是美国正在经历快速中产阶级化的十个城市之一;然而,这一过程对居民健康影响的实证证据不足。因此,本研究利用从两个高档化地区招募的331名居民的数据,探索了风化和生命历程视角的概念,以评估高档化对健康的影响。我们使用三角测量方法,包括单变量、双变量相关,以及通过结构方程模型实现的多元线性回归,来检验三种健康结果(测量压力、自评心理健康和抑郁症状)的复杂途径。双变量Pearson相关分析表明,高档化评分与心理健康症状和压力之间存在显著正相关。然而,在因果/路径模型中,中产阶级化与抑郁之间的直接联系消失了。为了支持风化假说,本研究发现压力得分与成年期抑郁得分直接相关。因此,这项研究建立在美国快速变化的物质和社会文化环境中环境压力和心理健康的积累证据的基础上。因此,实施和保障资源的社会公平,无论是在家庭层面还是在市政府层面,都将提高居民的健康水平,降低医疗支出成本。
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Structural equation modeling of mental health in gentrifying neighborhoods in Austin, Texas
Abstract Having poor mental health can be life-threatening, and problems tied to it are prevalent in communities across the United States (US). The city of Austin is one of the ten cities in the US undergoing rapid urban gentrification; however, there is insufficient empirical evidence on the impact of this process on residents’ health. Consequently, this study explored the concept of weathering and life course perspective using data of 331 residents recruited from two regions endemic with gentrification to assess the health impacts of gentrification. We used a triangulation method including univariate, bivariate correlation, and multiple linear regression implemented through the structural equation model to examine the complex pathways to three health outcomes—measured stress, self-rated mental health, and depression symptoms. Bivariate Pearson’s correlation indicated a significant positive association between gentrification score and mental health symptoms and stress. However, the direct association between gentrification and depression disappeared in the causal/path model. In support of the weathering hypothesis, this study found that stress score was directly related to the adulthood depression score. Therefore, this research builds on the accumulating evidence of environmental stress and mental health in the US’s rapidly changing physical and sociocultural environment. Hence, implementing and guaranteeing social equity of resources will improve residents’ health and reduce the cost of health care spending at both the household level and the city government level.
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