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量化贫困与健康之间的相互关系:结合因果回路图与纵向结构方程模型。

Quantifying reciprocal relationships between poverty and health: combining a causal loop diagram with longitudinal structural equation modelling.

机构信息

Department of Health Services Research, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands.

National Institute for Public Health and the Environment, Bilthoven, The Netherlands.

出版信息

Int J Equity Health. 2024 May 1;23(1):87. doi: 10.1186/s12939-024-02172-w.

Abstract

BACKGROUND

This study takes on the challenge of quantifying a complex causal loop diagram describing how poverty and health affect each other, and does so using longitudinal data from The Netherlands. Furthermore, this paper elaborates on its methodological approach in order to facilitate replication and methodological advancement.

METHODS

After adapting a causal loop diagram that was built by stakeholders, a longitudinal structural equation modelling approach was used. A cross-lagged panel model with nine endogenous variables, of which two latent variables, and three time-invariant exogenous variables was constructed. With this model, directional effects are estimated in a Granger-causal manner, using data from 2015 to 2019. Both the direct effects (with a one-year lag) and total effects over multiple (up to eight) years were calculated. Five sensitivity analyses were conducted. Two of these focus on lower-income and lower-wealth individuals. The other three each added one exogenous variable: work status, level of education, and home ownership.

RESULTS

The effects of income and financial wealth on health are present, but are relatively weak for the overall population. Sensitivity analyses show that these effects are stronger for those with lower incomes or wealth. Physical capability does seem to have strong positive effects on both income and financial wealth. There are a number of other results as well, as the estimated models are extensive. Many of the estimated effects only become substantial after several years.

CONCLUSIONS

Income and financial wealth appear to have limited effects on the health of the overall population of The Netherlands. However, there are indications that these effects may be stronger for individuals who are closer to the poverty threshold. Since the estimated effects of physical capability on income and financial wealth are more substantial, a broad recommendation would be that including physical capability in efforts that are aimed at improving income and financial wealth could be useful and effective. The methodological approach described in this paper could also be applied to other research settings or topics.

摘要

背景

本研究旨在利用荷兰的纵向数据,对描述贫困与健康如何相互影响的复杂因果回路图进行量化,这是一项极具挑战性的工作。此外,本文详细阐述了其方法学方法,以促进复制和方法学的发展。

方法

在适应利益相关者构建的因果回路图之后,使用了纵向结构方程模型方法。构建了一个具有九个内生变量的交叉滞后面板模型,其中两个是潜变量,三个是时间不变的外生变量。使用该模型,以格兰杰因果关系的方式估计了方向效应,使用了 2015 年至 2019 年的数据。计算了直接效应(滞后一年)和多年(最多八年)的总效应。进行了五项敏感性分析。其中两项侧重于低收入和低财富人群。另外三项分别增加了一个外生变量:工作状况、教育程度和住房拥有率。

结果

收入和金融财富对健康的影响是存在的,但对于整个人群来说相对较弱。敏感性分析表明,对于收入或财富较低的人群,这些影响更强。身体能力似乎对收入和金融财富都有很强的积极影响。还有其他一些结果,因为估计的模型非常广泛。许多估计的影响只有在几年后才变得显著。

结论

收入和金融财富似乎对荷兰整个人口的健康影响有限。然而,有迹象表明,对于那些接近贫困线的人,这些影响可能更强。由于身体能力对收入和金融财富的影响更为显著,因此一个广泛的建议是,在旨在提高收入和金融财富的努力中纳入身体能力可能是有用和有效的。本文中描述的方法学方法也可以应用于其他研究环境或主题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2003/11061969/bf909bfeee27/12939_2024_2172_Fig1_HTML.jpg

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