Dynamic Linkages among Economic Development, Energy Consumption, Environment and Health Sustainable in EU and Non-EU Countries

Feng, Yan; Yu, Xinye; Chiu, Yung‐ho; Chang, Tzu‐Han

doi:10.3390/healthcare7040138

Cited by 14 publications

(16 citation statements)

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“…The impact of air pollution on children's health has also been widely examined. For example, Feng et al [14] employed a two-stage meta-frontier dynamic network DEA (TMDN-DEA) model to explore the influence of energy consumption and the associated environmental pollution on the mortality of children and adults in 28 EU countries and 53 non-EU countries from 2010 to 2014, Lee et al [24] used a generalized additive model (GAM) time series analysis to explore the effect of multiple air pollutants (sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), ozone (O 3 ), carbon monoxide (CO) and aerodynamic diameter (PM 10 )) on the health of the children under 15 years old in Seoul from 1997 to 1999, and found that nitrogen dioxide and ozone were the main contributors to childhood asthma. In more recent research, Chen et al [6] found that PM 2.5 and PM 10 affected the health and lung function of primary school children, Fioravanti et al [15] found that traffic air pollution had no effect on childhood obesity in children aged 4 and 8 years in Rome, and Knibbs et al [22] found that exposure to outdoor NO 2 affected the respiratory systems of children aged 7-11 in Australia.…”

Section: Impact Of Air Pollution On Human Healthmentioning

confidence: 99%

“…Most of the above research only focused on one or two aspects, with no studies having analyzed the relationships between economic development, energy, environmental pollution and human health. Therefore, to fill this gap, the method proposed in Feng et al [14] was used to develop a modified Undesirable Meta Dynamic Network DEA model to examine the economic development, energy, environmental pollution and human health efficiencies in 31 Chinese cities in China, identify the regional differences, and provide suggestions for improvement.…”

Section: Literature Review Summarymentioning

confidence: 99%

“…Second stage: health treatment stage Input variables: health expenditure Output variables: Birth rate; respiratory diseases; mortality rate. Figure 1 shows the Network Dynamic Model framework from Feng et al [14] that was employed to explore the inter-period energy consumption, economic growth, air pollution and health efficiencies in 31 Chinese cities.…”

Section: Output Variables Gdp (Gross Domestic Product)mentioning

confidence: 99%

“…In reference to the empirical framework in Feng et al [14], Table 2 shows the annual efficiencies in China's eastern, central, northeastern and western regions. The annual average overall efficiency in the eastern region was the highest, but at 0.665, there was a great need for improvements.…”

Section: Overall Efficiency Analysismentioning

confidence: 99%

“…Even though it is well known that different cities and different regions have different development levels, a majority of past studies have failed to provide such regional comparisons. While Feng et al [14] recently employed a two-stage meta-frontier dynamic network data envelopment analysis (TMDN-DEA) model to explore energy consumption's environmental pollution effects on child and adult mortality in 28 EU countries and 53 non-EU countries from 2010 to 2014, the research was mainly focused on the EU and non-EU countries. Therefore, to go some way to filling this gap, this study proposes a modified Undesirable Meta Dynamic Network model to explore the economic, energy, environmental, and human health efficiencies in 31 Chinese cities.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic linkages among economic development, environmental pollution and human health in Chinese

Liu

Lin

Chiu

2020

Cost Eff Resour Alloc

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Background Research on the relationships between economic development, energy consumption, environmental pollution, and human health has tended to focus on the relationships between economic growth and air pollution, energy and air pollution, or the impact of air pollution on human health. However, there has been little past research focused on all the above associations. Methods The few studies that have examined the interconnections between the economy, energy consumption, environmental pollution and health have tended to employ regression analyses, DEA (Data Envelopment Analysis), or DEA efficiency analyses; however, as these are static analysis tools, the analyses did not fully reveal the sustainable economic, energy, environmental or health developments over time, did not consider the regional differences, and most often ignored community health factors. To go some way to filling this gap, this paper developed a modified two stage Undesirable Meta Dynamic Network model to jointly analyze energy consumption, economic growth, air pollution and health treatment data in 31 Chinese high-income and upper-middle income cities from 2013–2016, for which the overall efficiency, production efficiency, healthcare resource utilization efficiency and technology gap ratio (TGR) for all input and output variables were calculated. Results It was found that: (1) the annual average overall efficiency in China’s eastern region was the highest; (2) the production stage efficiencies were higher than the healthcare resource utilization stage efficiencies in most cities; (3) the high-income cities had lower TGRs than the upper–middle income cities; (4) the high-income cities had higher average energy consumption efficiencies than the upper-middle income cities; (5) the health expenditure efficiencies were the lowest of all inputs; (6) the high-income cities’ respiratory disease and mortality rate efficiencies were higher than in the upper–middle income cities, which had improving mortality rate efficiencies; and (7) there were significant regional differences in the annual average input and output indicator efficiencies. Conclusions First, the high-income cities had higher average efficiencies than the upper-middle income cities. Of the ten eastern region high-income cities, Guangzhou and Shanghai had average efficiencies of 1, with the least efficient being Shijiazhuang. In the other regions, the upper-middle income cities required greater technology and health treatment investments. Second, Guangzhou, Lhasa, Nanning, and Shanghai had production efficiencies of 1, and Guangzhou, Lhasa, Nanning, Shanghai and Fuzhou had healthcare resource utilization efficiencies of 1. As the average production stage efficiencies in most cities were higher than the healthcare resource utilization stage efficiencies, greater efforts are needed to improve the healthcare resource utilization. Third, the technology gap ratios (TGRs) in the high-income cities were slightly higher than in the upper-middle income cities. Therefore, the upper-middle income cities need to learn from the high-income cities to improve their general health treatment TGRs. Fourth, while the high-income cities had higher energy consumption efficiencies than the upper-middle income cities, these were decreasing in most cities. There were few respiratory disease efficiency differences between the high-income and upper-middle income cities, the high-income cities had falling mortality rate efficiencies, and the upper-middle income cities had increasing mortality rate efficiencies. Overall, therefore, most cities needed to strengthen their health governance to balance economic growth and urban expansion. Fifth, the average AQI efficiencies in both the high-income and upper-middle income cities were higher than the average CO2 efficiencies. However, the high-income cities had lower average CO2 emissions and AQI efficiencies than the upper-middle income cities, with the AQI efficiency differences between the two city groups expanding. As most cities were focusing more on air pollution controls than carbon dioxide emissions, greater efforts were needed in coordinating the air pollution and carbon dioxide emissions treatments. Therefore, the following suggestions are given. (1) The government should reform the hospital and medical systems. (2) Local governments need to strengthen their air pollution and disease education. (3) High-income cities need to improve their healthcare governance to reduce the incidence of respiratory diseases and the associated mortality. (4) Healthcare governance efficiency needs to be prioritized in 17 upper-middle income cities, such as Hangzhou, Changchun, Harbin, Chengdu, Guiyang, Kunming and Xi’an, by establishing sound medical management systems and emergency environmental pollution treatments, and by increasing capital asset medical investments. (5) Upper-middle income cities need to adapt their treatment controls to local conditions and design medium to long-term development strategies. (6) Upper-middle income cities need to actively learn from the technological and governance experiences in the more efficient higher-income cities.

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