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

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.

Keywords: Causal loop diagram; Financial wealth; Income; Indirect effects; Latent variables; Longitudinal; Poverty; Quantification; Social determinants of health; Structural equation modelling.

Fig. 1

The causal loop diagram constructed using group model building in the previous study [9]

Fig. 2

Flowchart showing the five steps of the quantification process

Fig. 3

An adaptation of the causal loop diagram, based on comments from scientific experts and literature

Fig. 4

Measurement model (CFA) for latent variable mental health at one time point, using the five MHI-5 items [31]. The error terms of the indicators ‘e1’ to ‘e5’ are also shown, as well as the residual ‘r1’ for the latent variable

Fig. 5

Final CLD structure with all variables and hypothesised effects that were eventually quantified. The three variables that are used to indicate unhealthy behaviour (BMI, alcohol use, and smoking) are not shown separately in this diagram for simplicity’s sake

Fig. 6

Two-variable CLPM structure with one latent variable and one observed continuous variable at three time points. The error terms (e) of the observed indicators are allowed to covary over time (not shown for simplicity’s sake). The residuals (r) are allowed to covary with the residuals of other variables at the same time point

Fig. 7

Model with standardised direct effects from the primary model. The three coefficients accompanying every arrow from and to unhealthy behaviour indicate individual relationships with BMI, alcohol use, and smoking, in that order. There were no predictions in the CLD regarding the relationships between these variables making up unhealthy behaviour (the box in the bottom right corner), so these were not compared to any prior expectations