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.

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Main Authors: Reumers, Laurens, Hameleers, Niels, Hilderink, Henk, Bekker, Marleen, Jansen, Maria, Ruwaard, Dirk
Format: Dataset biblioteca
Published: Wageningen University & Research
Subjects:FOS: Mathematics, Statistics,
Online Access:https://research.wur.nl/en/datasets/quantifying-reciprocal-relationships-between-poverty-and-health-c
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spelling dig-wur-nl-wurpubs-6391842024-12-18 Reumers, Laurens Hameleers, Niels Hilderink, Henk Bekker, Marleen Jansen, Maria Ruwaard, Dirk Dataset Quantifying reciprocal relationships between poverty and health: combining a causal loop diagram with longitudinal structural equation modelling 2024 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. Wageningen University & Research text/html https://research.wur.nl/en/datasets/quantifying-reciprocal-relationships-between-poverty-and-health-c 10.6084/m9.figshare.c.7210396 https://edepot.wur.nl/683934 FOS: Mathematics Statistics Wageningen University & Research
institution WUR NL
collection DSpace
country Países bajos
countrycode NL
component Bibliográfico
access En linea
databasecode dig-wur-nl
tag biblioteca
region Europa del Oeste
libraryname WUR Library Netherlands
topic FOS: Mathematics
Statistics
FOS: Mathematics
Statistics
spellingShingle FOS: Mathematics
Statistics
FOS: Mathematics
Statistics
Reumers, Laurens
Hameleers, Niels
Hilderink, Henk
Bekker, Marleen
Jansen, Maria
Ruwaard, Dirk
Quantifying reciprocal relationships between poverty and health: combining a causal loop diagram with longitudinal structural equation modelling
description 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.
format Dataset
topic_facet FOS: Mathematics
Statistics
author Reumers, Laurens
Hameleers, Niels
Hilderink, Henk
Bekker, Marleen
Jansen, Maria
Ruwaard, Dirk
author_facet Reumers, Laurens
Hameleers, Niels
Hilderink, Henk
Bekker, Marleen
Jansen, Maria
Ruwaard, Dirk
author_sort Reumers, Laurens
title Quantifying reciprocal relationships between poverty and health: combining a causal loop diagram with longitudinal structural equation modelling
title_short Quantifying reciprocal relationships between poverty and health: combining a causal loop diagram with longitudinal structural equation modelling
title_full Quantifying reciprocal relationships between poverty and health: combining a causal loop diagram with longitudinal structural equation modelling
title_fullStr Quantifying reciprocal relationships between poverty and health: combining a causal loop diagram with longitudinal structural equation modelling
title_full_unstemmed Quantifying reciprocal relationships between poverty and health: combining a causal loop diagram with longitudinal structural equation modelling
title_sort quantifying reciprocal relationships between poverty and health: combining a causal loop diagram with longitudinal structural equation modelling
publisher Wageningen University & Research
url https://research.wur.nl/en/datasets/quantifying-reciprocal-relationships-between-poverty-and-health-c
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