Quantitative Impact Analysis of Climate Change on Residents' Health Conditions with Improving Eco-Efficiency in China: A Machine Learning Perspective.

Xianning Wang,Jingrong Dong,Zhengang Ma

doi:10.3390/ijerph182312842

Abstract

Climate change affects public health, and improving eco-efficiency means reducing the various pollutants that are the result of economic activities. This study provided empirical evidence of the quantitative impact analysis of climate change on the health conditions of residents across China due to improvements that have been made to eco-efficiency. First, the indicators that were collected present adequate graphical trends and regional differences with a priori evidence about their relationships to each other; second, the present study applied Sensitivity Evaluation with Support Vector Machines (SE-SVM) to Chinese provincial panel data, taking the Visits to Hospitals, Outpatients with Emergency Treatment, and Number of Inpatients as proxy variables for the health conditions of the residents in each area and temperature, humidity, precipitation, and sunshine as the climate change variables, simultaneously incorporating the calculated eco-efficiency with six controlling indicators; third, we compared in-sample forecasting to acquire the optimal model in order to conduct elasticity analysis. The results showed that (1) temperature, humidity, precipitation, and sunshine performed well in forecasting the health conditions of the residents and that climate change was a good forecaster for resident health conditions; (2) from the national perspective, climate change had a positive relationship with Visits to Hospitals and Outpatients with Emergency Treatment but a negative relationship with the Number of Inpatients; (3) An increase in regional eco-efficiency of 1% increase the need for Visits to Hospitals and Outpatients with Emergency Treatment by 0.2242% and 0.2688%, respectively, but decreased the Number of Inpatients by 0.6272%; (4) increasing the regional eco-efficiency did not show any positive effects for any individual region because a variety of local activities, resource endowment, and the level of medical technology available in each region played different roles. The main findings of the present study are helpful for decision makers who are trying to optimize policy formulation and implementation measures in the cross-domains of economic, environmental, and public health.

Highlights

This article is an open access articleDecision makers are constantly weighing the relationships between climate change, public health, and economic development with environmental sustainability
Regional Resident health conditions (RHC) are affected by local geological conditions, natural resources, customs, economic development, population density, cultural and educational background factors, etc., it is important to compare the spatial characteristics that are subject to geographic location, and climate change demonstrates the same spatial differences, meaning that these two aspects interact within a specific spatial range
These results demonstrate results that are similar to those that have been obtained in the past: (1) Climate change is a good predictor for predicting resident health, as it takes into account improved REE and other control variables that reflect regional heterogeneity; (2) better model settings can be found by comparing the average MPE, MSE, and SDE for temperature, humidity, precipitation, sunshine together; (3) considering the real situation where temperature, humidity, precipitation, and sunshine interact, we chose the Sensitivity Evaluation with Support Vector Machines (SE-SVM) with four indicators to be the basic model for elastic analysis and incorporated the improving eco-efficiency and other control variables

Summary

Introduction

This article is an open access article. Decision makers are constantly weighing the relationships between climate change, public health, and economic development with environmental sustainability The quantitative impact analysis of climate change on public health when considering the human initiatives to improve eco-efficiency in China is a hot and important interdisciplinary topic. It is crucial to acquire empirical evidence in order for scholars, distributed under the terms and conditions of the Creative Commons.

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