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Exploration of the Relationships between Men’s Healthy Life Expectancy in Japan and Regional Variables by Integrating Statistical Learning Methods

A quantitative understanding of the relationship between comprehensive health levels, such as healthy life expectancy and their related factors, through a highly explanatory model is important in both health research and health policy making. In this study, we developed a regression model that combi...

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Detalles Bibliográficos
Autores principales: Sato, Fumiya, Nakamura, Keiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10530847/
https://www.ncbi.nlm.nih.gov/pubmed/37754641
http://dx.doi.org/10.3390/ijerph20186782
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author Sato, Fumiya
Nakamura, Keiko
author_facet Sato, Fumiya
Nakamura, Keiko
author_sort Sato, Fumiya
collection PubMed
description A quantitative understanding of the relationship between comprehensive health levels, such as healthy life expectancy and their related factors, through a highly explanatory model is important in both health research and health policy making. In this study, we developed a regression model that combines multiple linear regression and a random forest model, exploring the relationship between men’s healthy life expectancy in Japan and regional variables from open sources at the city level as an illustrative case. Optimization of node-splitting in each decision tree was based on the total mean-squared error of multiple regression models in binary-split child nodes. Variations of standardized partial regression coefficients for each city were obtained as the ensemble of multiple trees and visualized on scatter plots. By considering them, interaction terms with piecewise linear functions were exploratorily introduced into a final multiple regression model. The plots showed that the relationship between the healthy life expectancy and the explanatory variables could differ depending on the cities’ characteristics. The procedure implemented here was suggested as a useful exploratory method for flexibly implementing interactions in multiple regression models while maintaining interpretability.
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spelling pubmed-105308472023-09-28 Exploration of the Relationships between Men’s Healthy Life Expectancy in Japan and Regional Variables by Integrating Statistical Learning Methods Sato, Fumiya Nakamura, Keiko Int J Environ Res Public Health Article A quantitative understanding of the relationship between comprehensive health levels, such as healthy life expectancy and their related factors, through a highly explanatory model is important in both health research and health policy making. In this study, we developed a regression model that combines multiple linear regression and a random forest model, exploring the relationship between men’s healthy life expectancy in Japan and regional variables from open sources at the city level as an illustrative case. Optimization of node-splitting in each decision tree was based on the total mean-squared error of multiple regression models in binary-split child nodes. Variations of standardized partial regression coefficients for each city were obtained as the ensemble of multiple trees and visualized on scatter plots. By considering them, interaction terms with piecewise linear functions were exploratorily introduced into a final multiple regression model. The plots showed that the relationship between the healthy life expectancy and the explanatory variables could differ depending on the cities’ characteristics. The procedure implemented here was suggested as a useful exploratory method for flexibly implementing interactions in multiple regression models while maintaining interpretability. MDPI 2023-09-19 /pmc/articles/PMC10530847/ /pubmed/37754641 http://dx.doi.org/10.3390/ijerph20186782 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sato, Fumiya
Nakamura, Keiko
Exploration of the Relationships between Men’s Healthy Life Expectancy in Japan and Regional Variables by Integrating Statistical Learning Methods
title Exploration of the Relationships between Men’s Healthy Life Expectancy in Japan and Regional Variables by Integrating Statistical Learning Methods
title_full Exploration of the Relationships between Men’s Healthy Life Expectancy in Japan and Regional Variables by Integrating Statistical Learning Methods
title_fullStr Exploration of the Relationships between Men’s Healthy Life Expectancy in Japan and Regional Variables by Integrating Statistical Learning Methods
title_full_unstemmed Exploration of the Relationships between Men’s Healthy Life Expectancy in Japan and Regional Variables by Integrating Statistical Learning Methods
title_short Exploration of the Relationships between Men’s Healthy Life Expectancy in Japan and Regional Variables by Integrating Statistical Learning Methods
title_sort exploration of the relationships between men’s healthy life expectancy in japan and regional variables by integrating statistical learning methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10530847/
https://www.ncbi.nlm.nih.gov/pubmed/37754641
http://dx.doi.org/10.3390/ijerph20186782
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