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

Area of Science:

• Socioeconomic Determinants of Health
• Longitudinal Data Analysis
• Causal Loop Modeling

Background:

• Investigates the intricate causal relationship between poverty and health using longitudinal data from the Netherlands.
• Addresses the challenge of quantifying complex socioeconomic and health interdependencies.
• Emphasizes methodological transparency for replication and advancement.

Purpose of the Study:

• To quantify the bidirectional effects between poverty and health indicators over time.
• To analyze the influence of socioeconomic factors on health outcomes and vice versa.
• To provide a robust methodological framework for similar research.

Main Methods:

• Adapted a stakeholder-developed causal loop diagram.
• Employed longitudinal structural equation modeling with a cross-lagged panel design (2015-2019).
• Estimated Granger-causal effects, including direct and total effects over multiple years, with sensitivity analyses.

Main Results:

• Income and financial wealth exhibit weak direct effects on overall population health.
• Effects of income and wealth on health are more pronounced for lower-income and lower-wealth individuals.
• Physical capability demonstrates substantial positive effects on income and financial wealth.

Conclusions:

• Socioeconomic status has a limited impact on the general population's health in the Netherlands.
• Individuals near the poverty threshold may experience stronger effects of socioeconomic status on health.
• Enhancing physical capability is a promising strategy for improving income and financial wealth, with potential indirect health benefits.