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Article

The Coordinated Development and Regulation Research on Public Health, Ecological Environment and Economic Development: Evidence from the Yellow River Basin of China

1
Center for Energy Environment & Economy Research, School of Management, Zhengzhou University, Zhengzhou 450001, China
2
Research Center for Economic Development and Environment of the Yellow River Basin, Zhengzhou University, Zhengzhou 450001, China
3
Yellow River Institute for Ecological Protection & Regionally Coordinated Development, Zhengzhou University, Zhengzhou 450001, China
*
Authors to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(11), 6927; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph19116927
Submission received: 28 March 2022 / Revised: 31 May 2022 / Accepted: 2 June 2022 / Published: 6 June 2022
(This article belongs to the Special Issue New Challenges and Crucial Topics for 2030 Public Health)

Abstract

:
The dual problems of the public crisis from the global epidemic and the deterioration of the ecological environment constrain the economic development in the Yellow River Basin. To promote the sustainable and balanced development in the Yellow River Basin, this paper takes public health, ecological environment, and economic development, as a whole, to study the coordinated development of the Yellow River Basin. Based on coupling coordinated theory, we use the SMI-P method to evaluate the coordinated development index of public health, the ecological environment, and economic development in the Yellow River Basin. Moreover, we use the coordinated regulation and obstacle factor diagnosis to identify the main influencing factors and design regulation methods to optimize the coordinated development index. The results found that (1), during the research period, there is spatiotemporal heterogeneity in the coordinated development level in the Yellow River Basin. From 2009 to 2019, the overall development index increased steadily, while the regional disparity in the coordinated development level was obvious. (2) The ecological environment indicators contribute more to the relevance and obstacle factors, such as the average concentration of fine particulate matter, per capita arable land area, afforestation area, etc. (3) After regulating the overall development level of the Yellow River Basin, we prove that Path 4, which comprehensively considers the relevance and obstacle factors, performs better.

1. Introduction

Since the outbreak of the global epidemic, COVID-19, there has been an increasing concern about public health issues [1,2,3]. Meanwhile, the deterioration of the ecological environment, caused by economic development, also has a great impact on public health, which restricts social development [4]. The Yellow River Basin is rich in grain, coal, and oil, which make it an important economic zone in China. To be specific, the regional GDP of Yellow River Basin accounts for more than 1/4 of the national total output value. Moreover, the Yellow River Basin is an important ecological barrier in northern China. However, the ecological environment of the Yellow River Basin is getting worse because of intensified human destruction and tremendous resource consumption [5,6]. It’s necessary to take a series of effective measures to improve the ecological conservation capacity and the restoration of ecological barrier of the Yellow River Basin. Furthermore, the Yellow River Basin flows through nine provinces, whose population accounts for about 1/3 of China. The public health in the Yellow River Basin is facing challenges due to environmental degradation and other issues. Therefore, increasing investment in public health and improving the level of public health can narrow the gap in people’s livelihood, maintain sufficient healthy labor, and guarantee food production and national security in the Yellow River Basin. In summary, the ecological environment, public health, and economic development of the Yellow River Basin are interconnected. Comprehensive treatment for the ecological environment can safeguard public health and propel the economic development of the Yellow River Basin. In turn, the safeguard of citizens’ health provides labor security for economic development, and economic development will also facilitate the infrastructure improvement to further enhance the level of public health, as well as the restoration and protection of the ecological environment.
Under the background of ecological protection and high-quality development of the Yellow River in China, we explore the synergistic relationship among public health, the ecological environment, and economic development, which aims to provide effective suggestions for the high-quality development of the Yellow River Basin. Existing studies have shown that there is a close and complex causal relationship among the economic development system, public health system, and the ecological environment system [7]. Relatively speaking, studies on the relationship of the three subsystems are more complex than mere dyads.
For the relationship between public health and economic development, the US Special Administrative Committee on Occupational and Environmental Medicine Health emphasized the impact of health on the economy from the perspective of health productivity and health care crisis [8]. Nichol et al., designed a retrospective cohort study and used multivariate models to analyze the experimental data, to assess the socioeconomic burden of the disease, from the perspective of an invasive disease [9]. Some scholars used the Granger-type causality test to empirically demonstrate the impact of public health on economic development from both macro and micro perspectives [10]. On the other hand, high-quality social and economic development promotes people’s income growth and improves public health indirectly. First, economic growth promotes adequate social health care facilities, which will improve the public health [11]. Second, economic growth brought by technological progress can improve the medical level and further promote public health [12]. Stenberg et al. used simulation modelling to assess the socioeconomic returns of health investments, and they demonstrated that investments in public health can significantly improve both public health and social returns [13]. On the contrary, economic recession will have an adverse impact on the public health level [14,15]. For the sake of long-term development, scholars have reviewed previous research findings, on public health and economics, to make recommendations for the coordinated development of the two subsystems [16,17].
In terms of the relationship between public health and the ecological environment, about 1.6 million deaths each year can be attributed to the unhealthy air, which accounts for about 17% of all deaths in China [18]. Grossman pioneered a healthy production model to describe the relationship between healthy input and output [19]. Cropper, Gerking, and Stanley improved the healthy production model and proposed a simple model of preventive health care and a health-oriented choice model, respectively, revealing that the key factors affecting public health are health care, genetics, the environment, lifestyle, etc. [20,21]. Based on empirical data, Wells and Evans explained the relationship between public health and the ecological living environment of citizens [22]. Given the existing research results, Koehler et al. proposed a conceptual framework to consider the impact of environmental decision-making on public health, further emphasizing that public health is not only related to the living environment but also to local transportation and energy [23]. Various resources in the ecological environment are closely related to the survival of human beings, and they also have a significant impact on the public health level. The important ecological resources, such as water resources [24], forest resources, [25], and air resources [26] are destroyed and polluted seriously, and the resulting public health problems have triggered extensive research in the field. In addition, some scholars have innovatively discussed public health from the perspective of food pesticide residues [27].
For the relationship between the ecological environment and economic development, existing studies verified that the inverted U-shaped relationship between economic growth and environmental degradation is based on the empirical framework of the Environmental Kuznets Curve (EKC) [28,29]. In recent studies, Hao et al. draw the similar conclusions of the inverted U-shaped relationship, when they studied the relationship between China’s ecological environment and economic development, by using the spatial lag model SLM and spatial panel data model, respectively [30,31]. On the other hand, the defects of the ecological environment will also restrict the economy development. For example, Saidi and Hammami found that energy consumption has a positive impact on economic growth, while carbon dioxide has a negative impact on economic growth based on synchronous equations [32]. In addition, some scholars use various models to study the impact of the ecological environment on the economy, such as the coupling coordination model. Shi T et al. measured the coupling coordination and spatial heterogeneity of economic development and the ecological environment in parts of China through Geographically and Temporally Weighted Regression (GTWR) [33]. Liu et al. used the coupling coordination model and Geographically Weighted Regression (GWR) to analyze the coupling coordination relationship between economic development and the ecological environment in the Yellow River Basin [34]. Recently, some scholars have used the coupling model to carry out research. Li et al. used an obstacle degree model, based on the coupling coordination model, to diagnose the obstacle factors affecting the coupling coordination [35]. Zhang et al. used the Tapio decoupling model and the STIR PAT model to analyze the economic output and water environmental pressure in the Yangtze River Basin, and they put forward relevant suggestions [36]. Some scholars use the environmental Impact-GDP-Technology (IGT) decoupling model to study the economic growth and energy consumption of developed and developing countries, indicating that the decoupling index of developed countries is better than the index of developing countries [37]. With further research on the relationship between the two, more and more scholars propose that environmental protection should be promoted by reducing the speed of economic growth [38,39].
“Coupling coordination” originates from the field of physics and refers to the close connection between each internal and external element of two or more systems. It is mainly used in the field of climate change. As the research moves along, coupling coordination has been introduced to measure the nonlinear interactions between the ecological environment and economic development, as well as public health and economic development. Liao et al. measured the degree of coupling and coordination between economic development and the ecological environment in the Beijing-Tianjin-Hebei region of China, and they made policy recommendations for local coordinated development [40]. Wu et al. studied the coordinated development level of China’s overall economic development and the ecological environment, and they conducted an empirical analysis of the spatial and temporal distribution of coordination in 31 provincial-level regions in China [41]. In addition, Zou et al. used the coupling coordination method to evaluate the coordinated development between economic development and public health in Sichuan, but they found that the level of coupling coordination was not ideal [42]. In conclusion, as for the relationship among public health, the ecological environment, and economic development, current studies are mostly discussing the relationship between two of them, while lacking the comprehensive researches on the three-subsystem relationship and the coordinated development path of the three subsystems for regulation. However, only by considering the correlation among the three, comprehensively, can we find out the certain problems existing in the coordinated development from an overall perspective. We comprehensively evaluate the coordinated development level of public health, the ecological environment, and economic development, and we systematically consider how to promote the overall coordination level and high-quality development in the Yellow River Basin.

2. Methodology

2.1. Quantitative Evaluation Method of Coordinated Development

The evaluation method of “single index quantification-multi-index synthesis-multi-criteria integration” ( S M I P ) is usually used to evaluate the interaction and change between different systems [43]. We adopt the fuzzy analysis method to quantify the high-quality development indicators of public health in the Yellow River Basin to the [0,1]. According to the impact of indicators on the index of coordinated development, the indicators are divided into positive and negative indicators. The corresponding quantitative calculation formulas for indicators are positive Equation (1) and negative Equation (2). Given the regional characteristics and index properties, we determine each index node according to the selected quantification method. Among them: the average value of each indicator in the Yellow River Basin, over the years, is regarded as the passing value (c); the optimal value (e) represents the maximum value of the indicator increased by 10%; the worst value (a) is the minimum value of the indicator reduced by 10%; the worse value (b) represents the interpolation of a and c; the better value (d) represents the interpolation of c and e.
S H D i = { 0                                                                                         ( x i a i ) 0.3 ( x i a i b i a i )                                                     ( a i < x i b i ) 0.3 + 0.3 ( x i b i c i b i )                                   ( b i < x i c i ) 0.6 + 0.2 ( x i c i d i c i )                             ( c i < x i d i ) 0.8 + 0.2 ( x i d i e i d i )                             ( d i < x i e i ) 1                                                                                   ( e i < x i )
S H D i = { 1 ( x i e i ) 0.8 + 0.2 ( d i x i d i e i ) ( e i < x i d i ) 0.6 + 0.2 ( c i x i c i d i ) ( d i < x i c i ) 0.3 + 0.3 ( b i x i b i c i ) ( c i < x i b i ) 0.3 ( a i x i a i b i ) ( b i < x i a i ) 0 ( a i < x i )
For the three subsystems of the ecological environment, economic development, and public health, we adopt the method of multi-index integration to evaluate the coordinated development index of the three subsystems comprehensively. The calculation equations are:
E E D I ( T ) = i = 1 n 1 w i S H D ( Y i ( T ) )
H Q E D I ( T ) = i = 1 n 2 w i S H D ( Y i ( T ) )
P H D I ( T ) = i = 1 n 3 w i S H D 3 ( Y i ( T ) )
where T represents the year, i represents the evaluation indicator, and the variable S H D ( Y i ( T ) represents the result of single-index quantization; E D I ( T ) , H Q E D I ( T ) , and P H D I ( T ) represent the index of the ecological environment, economic development, and public health in the T year, respectively. n 1 , n 2 , and n 3 are the number of evaluation indicators of the ecological environment, economic development, and public health subsystem, respectively; w i is the weight of each indicator.
The Yellow River Basin Public Health High Quality Coordinated Development Index ( E H P ) is composed of three subsystem development indices, E E D I , H Q E D I , and P H D I , by the following equation:
E H P ( T ) = β 1 E E D I ( T ) + β 2 H Q E D I ( T ) + β 3 P H D I ( T )
where β 1 , β 2 , and β 3 represent the system weights of the given E E D I ( T ) , H Q E D I ( T ) , and P H D I ( T ) , respectively, and β 1 = β 2 = β 3 = 1 / 3 .
After calculating the coordinated development index of the public health, ecological environment, and economic development, the index is divided into seven levels, according to its value, as shown in Table 1.

2.2. Coordinated Identification

Coordinated identification makes quantitative analysis easier through the coordinated relationship between two or more parties, which can be used to identify the contribution of each indicator to the overall coordinated development index of the system. Modeling identification and non-modeling identification are two methods for coordinated identification. Particularly, the non-modeling identification method is used in the paper to identify the main influencing factors of the coordinated development of public health, the ecological environment, and economic development in the Yellow River Basin. The calculation process is as follows [44]:
  • Determine the reference sequence and the comparison sequence, the dependent variable constitutes the reference sequence x 0 , and the independent variable constitutes x i .
x 0 ( k ) = { x 0 ( 1 ) ,   x 0 ( 2 ) ,     ,   x 0 ( n )   ( k = 1   ,   2   ,     ,   n )
x i ( k ) = { x i ( 1 ) ,   x i ( 2 ) ,     ,   x i ( n ) }   ( k = 1   2   ,     ,   m )
b.
The data is dimensionless to obtain the sequences x 0 and x i . The common methods are the mean value method and the initial value method, with the former used at this point.
Δ 0 i ( k ) = | x 0 ( k ) x i ( k ) |
c.
Correlation degree r ( x 0 , x i ) calculation.
r ( x 0 ,   x i ) = ( Min i Min k Δ 0 i ( k ) + ξ Max i Max k Δ 0 i ( k ) ) ( Δ 0 i ( k ) + ξ Max i Max k Δ 0 i ( k ) )
In the equation, ξ is the resolution coefficient. With the value range of (0,1), ξ generally takes 0.5. Moreover, Δ 0 i ( k ) is a difference sequence.
d.
Calculate the grey correlation degree r 0 i .
r 0 i = 1 n k = 1 n r ( x 0 ( k ) ,           x i ( k ) )

2.3. Obstacle Factors Diagnosis

The obstacle degree model is used to diagnose the obstacle factors, which can identify the main influencing factors on the overall coordination. The specific calculation processes are as follows [45]:
  • Calculate the factor contribution degree F j of the jth evaluation index:
F j = w j w j *
where w j * represents the weight of the subsystem to which the j th indicator belongs.
2.
Calculate the deviation
I j = 1 x i j
3.
Calculate the obstacle degree P j of each evaluation index:
P j = F j I j j = 1 n F j I j
We can obtain the obstacle degree of each index, in all provinces and regions, by using the same method to diagnose the obstacle factors.

2.4. Coordinated Regulation

Coordinated regulation aims to ameliorate the coordinated development index of the overall system by some reconciliation steps [43]. There are two methods for coordinated regulation: (1) adopt the optimal method of coordinated behavior set; (2) determine the minimum range of coordinated balance based on the coordinated balance optimization model. The first method is used for regulation in the paper.

3. System Construction and Data Sources

According to the existing research frameworks of coordinated development and regulation research [44], we establish the modified research framework, as shown in Figure 1. The specific research steps are summarized as follows.
First of all, we need an index system to evaluate the coordinated development index of public health, the ecological environment, and economic development in the Yellow River Basin. The existing research focuses, mainly, on the provincial and municipal levels [46,47]. Given the difficulty in prefecture data acquisition and the multiple research indicators in this paper, we research the Yellow River Basin, at the provincial level, based on the “Outline of Ecological Protection and High-quality Development Planning in the Yellow River Basin”. The public health, ecological environment, and economic development system is an open but complex system, and whether the index system is scientific or systematic will affect the evaluation effect. According to existing theoretical results [44], we construct the index system from three subsystems of ecological environment, economic development, and public health system to measure the coordinated development level of the Yellow River Basin. The existing research results, which have established two index systems of economic development and ecological development, are limited [48]. First, the original index system only considered the two dimensions of economic structure and resource consumption when measuring economic development. Based on the outline of the Yellow River strategic plan, this paper evaluates the regional economic system from the three dimensions of economic foundation, scientific and technological innovation, and opening to the outside world. The important indicators, such as the number of R&D personnel among 10,000 employees, the number of people engaged in scientific and technological activities, and the number of higher education graduates are included to measure regional economic innovation. Second, the original indicator system emphasized ecological space area, total resources, etc., while it ignored regional disparity in economy, population, and area. Therefore, we incorporate the per capita park green space, afforestation area, and per capita water consumption into the index system to reflect the ecological environment in the basin. Third, the original index system did not consider public health. The public health indicators can reflect the regional economic development level. Therefore, we take public health as one of the subsystems in the evaluation index system. In conclusion, the portfolio of the evaluation index system is critical, which should follow the principles of scientificity, systematicness, operability, availability, etc. To be specific, the determined evaluation index system includes three first-level indicators of the ecological environment, economic development, and public health, as well as 10 s-level indicators of the ecological environment pressure, health service and security, and economic foundation, in addition to 39 three-level indicators, which is shown in Table 2.
To facilitate the indicators’ labeling and selection, all indicators are coded by the XABC method. The index number starts with X, and A represents the subsystem (1 represents E E D I , 2 represents H Q E D I , 3 represents P H D I ), B represents the classification layer of the subsystem, and the last C represents the index number of the corresponding indicator. For example, X1101 represents the index 01 of the first-level classification layer of the ecological environment system. The specific codes are shown in Table 2.
Secondly, we determine the node value of each indicator based on its properties, such as a, b, c, d, and e, whose specific values are shown in Table 3. The S M I P method is used to calculate the E H P by using Equations (1)–(6). Thirdly, using Equations (7)–(9) of coordinated identification, in combination with E H P , can calculate the contribution of each indicator to the overall development index of the Yellow River Basin. Fourthly, using the S H D , as well as Equations (10)–(12) can help calculate the obstacle degree of each indicator with regards to the overall coordinated development index of the Yellow River Basin. Finally, after coordinately regulating the quantitative index system of public health and high-quality development in the Yellow River Basin, the second step is repeated to obtain the regulated coordinated development index.
Figure 2 demonstrates the general situation of the Yellow River Basin. There is a close relationship between public health, the ecological environment, and economic development in the Yellow River Basin. We select the Yellow River Basin as the research object, and we analyze and evaluate the relationship between the overall public health, ecological environment, and economic development. The data for each indicator comes from “China Statistical Yearbook”, “China Health Statistical Yearbook”, “China Environmental Statistical Yearbook”, “China Rural Poverty Inspection Report”, “China’s Statistical Bulletin of Outbound Investment”, and the Statistical Yearbooks of the Yellow River Basin Provinces. Some missing data is complemented by means of adjacent years or linear interpolation.

4. Empirical Results and Discussion

4.1. Analysis and Evaluation of the Coordinated Development Index of Public Health, Ecological Environment, and Economic Development in the Yellow River Basin

According to the established evaluation index system for the coordinated development of the public health, ecological environment, and economic development in the Yellow River Basin, we use the S M I P method to process and calculate the data. The overall EEDI, HQEDI, and PHDI, from 2009 to 2019, are obtained, and we get the overall EHP through Equation (6), as shown in Table 4. In addition, we also calculate the coordinated development index of the provinces, upstream, midstream, and downstream, as shown in Table 5. Finally, according to the classification criteria in Table 1, the coordinated development index of each region is classified into different grades, and the results are shown in Table 6.

4.1.1. Analysis of the Overall Coordinated Development Index of the Yellow River Basin

Table 4 shows the overall coordinated development index of the Yellow River Basin from 2009 to 2019, which shows an upward trend. Specifically, the overall coordinated development index is from 0.352 to 0.486 in a decade, and the coordination level is from “less coordinated” in 2009 to “close to coordination” in 2011, and it remains stable in the subsequent stage. It demonstrates that the overall uncoordinated problem of high-quality public health development in the Yellow River Basin is relatively prominent, and there is much space for strengthening the connections between subsystems.
Compared to Table 4, the Figure 3 can directly demonstrate the evolutionary trend of the respective development indices of the Yellow River Basin subsystems. The ecological environment coordinated development index shows a trend of a wave-like rise [49], which can be attributed to the promotion of environmental protection awareness among people, the improvement of the environmental protection system, and the construction of large-scale basic environmental protection facilities. Taking 2012 as a key turning point, the ecological environment development index before 2012 was on a declining curve, which proves the rapid economic development in the basin led to the deterioration of the ecological environment [48,50]. While after 2012, the governance of ecological environmental protection, coordinated economic development, and the transformation and upgrading of heavily polluting enterprises were enhanced under the guidance of the “Twelfth Five-Year Plan” and the “Thirteenth Five-Year Plan”, as a result, the ecological environment system and economic development system appear with an upward trend again. The public health development index climbs steadily from 2009 to 2019, and there was a vigorous growth after the “Healthy China 2030” in 2016.

4.1.2. Analysis of the Coordinated Development Index of the Provinces in the Yellow River Basin and the Upstream, Midstream and Downstream

Using the coordinated development index of the upstream, midstream, and downstream, from 2009 to 2019 in Table 5, its trend map can be drawn, as shown in Figure 4. In combination with Table 5 and Table 6, we can have a comprehensive analysis of the coordinated development index of the provinces in the Yellow River Basin and the upstream, midstream, and downstream.
From the perspective of each province, the development index of public health, the ecological environment, and economic development in nine provinces is mainly concentrated as 0.1~0.7, involving four levels of basically uncoordinated, less uncoordinated, close to coordination, and more coordinated. Specially, the coordinated levels of Qinghai, Gansu, and Ningxia are less coordinated, and Inner Mongolia, Shaanxi, Shanxi, and Henan are close to coordination. Furthermore, Sichuan has developed from close to coordination to more coordinated, and Shandong is more coordinated, which reaches the highest level of coordination. From the perspective of upstream, midstream, and downstream, the coordinated development level of the downstream is the highest, which is close to coordination, while the level of the midstream has changed from less coordinated to close to coordination. However, the level of the upstream is less uncoordinated, which demonstrates the massive gap among upstream, midstream, and downstream. The coordinated status of each subsection of the basin is consistent with the actual situation. There are, indeed, certain gaps and barriers in the coordinated development index between provinces, as well as the upstream, midstream, and downstream [51,52].
On the whole, the coordinated development index of each province and upstream, midstream, and downstream have shown an upward trend, which indicates that the coordinated development of the three subsystems of the Yellow River Basin shows a positive rising trend in the future.

4.1.3. Spatial Evolution Analysis of the Coordinated Development Index of Public Health, Ecological Environment and Economic Development in the Yellow River Basin

We used the coordinated development index of each province in Table 5 to draw the spatial distribution of the coordinated development index of each province in the Yellow River Basin in 2009 and 2019, as shown in Figure 5. From the perspective of the overall spatial distribution, the coordinated development index of the Yellow River Basin has improved significantly from 2009 to 2019, which shows a progressively increasing distribution pattern from west to east [34]. The developed transportation and policy dividends in the downstream of the Yellow River Basin make the prior economic development level and public health index of the provinces in the downstream [53]. In addition, although desertification in the upstream has been effectively curbed, the low vegetation coverage still constrains the comprehensive development of the upstream of the Yellow River. This distribution pattern is consistent with the actual situation in the Yellow River Basin. From the perspective of provinces, the coordinated development indices of each province differ greatly. Compared with neighboring provinces, Sichuan and Shandong have relatively higher coordinated development indices. Due to the superior geographical location at the estuary of the Yellow River, Shandong performs well in economy development, the ecological environment, living conditions, and public health. Sichuan is the passage of both the Yellow River and the Yangtze River. With the unique geographical advantage, Sichuan has a higher comprehensive development level, especially with the ecological environment. The development index of Ningxia is always the bottom level, but its increment of development index has little difference with other regions. Restricted by a small population and inland locations, the comprehensive development levels of Xinjiang and Tibet are greatly affected by economic development and the ecological environment. The ideal state is to break down administrative barriers and play some leading role of high-level regions to promote the coordinated development of surrounding regions.

4.2. Coordinated Identification of Public Health, Ecological Environment and Economic Development in the Yellow River Basin

4.2.1. The Relationship between Public Health, Ecological Environment and Economic Development in the Yellow River Basin

Based on the calculation of S M I P method, we carry out the coordinated identification. Take the time series of E H P as the reference series ( x 0 (k)) and the S H D of each index as the comparison series ( x i ( k ) ) to calculate the grey correlation degree, whose results are shown in Table 7. Due to the large number of indicators, each province only lists the first eight indicators with larger values, which are recorded as key indicators. The growing grey correlation degree indicates the increasingly high level of contribution to the overall development.
The degree of contribution to the three-subsystem coordinated development, of each indicator in the nine provinces, can be seen in Table 7. On the whole, the key indicators of each province are mainly concentrated on the economic subsystem and the public health subsystem, indicating that the economic and public health subsystems play a dominant role in the overall development index of the Yellow River Basin. In terms of specific indicators, there are eight indicators that appear no less than four times in the key indicators. The ecological environment subsystem supplies three of the eight indicators: average concentration of fine particulate matter, per capita arable land, and effective utilization coefficient of farmland irrigation water, respectively. The economic subsystem supplies two of the eight indicators; they are the number of people engaged in scientific and technological activities and the number of higher education graduates. The public health subsystem also supplies three of the eight indicators: the number of beds in health care institutions, the number of travel agencies, and the number of medical institutions are the corresponding indicators. The eight indicators are, basically, even distributed, indicating that the three subsystems must be developed in a coordinated manner to continuously improve the overall coordinated development level in the Yellow River Basin, thus making the Yellow River Basin more coordinated as a whole.

4.2.2. The Yellow River Basin Obstacles of Public Health, Ecological Environment and Economic Development

We use Obstacle Factors Diagnosis to calculate the obstacle degree of each index of the nine provinces in the Yellow River Basin, in 2019, and select the eight indicators with higher obstacle degree rankings in each province as the main obstacle factors, which is shown in Table 8.
Table 8 quantitatively shows the restrictive effect of each indicator on the coordinated development of public health, the ecological environment, and economic development in the Yellow River Basin. The larger obstacle degree is the stronger restrictive function. On the whole, economic development subsystem indicators appear more frequently than public health subsystems and ecological environment subsystems. The result is in line with the fact that economic growth promotes the perfection of public facilities, which subsequently improves the public health level and the ecological environment. In terms of specific indicators, some indicators are universal, including the total sewage discharge, afforestation area, number of R&D personnel among 10,000 employees, natural population growth rate, government health spending as a percentage of health spending, and the number of days that the air quality reaches the second level and above [35]. Among them, the total amount of sewage discharge and the afforestation area belong to the ecological environment subsystem. The sewage discharge from polluting enterprises in the Yellow River Basin for economic growth has actually affected the environment. It is crucial to take measures to reduce pollution. Given the collateral effect of the coordination level, the afforestation expansion is another urgent task. The number of R&D personnel among the 10,000 employees is an economic indicator, which reflects insufficient innovation capability in economy development. The natural population growth rate, the government health spending as a percentage of health spending, and the number of days that the air quality reaches the second level and above are the indicators of the public health subsystem, The air quality reaching the second level and above means that the Air Quality Index (AQI) is no more than 100 [54]. Only when the air quality reaches the second level and above can it meet the living standard of “healthy air quality”. The indicators of the public health subsystem reflect several realistic problems: for example, the declined natural population growth in China, the inadequate obligations for public health of the government, and the harm to citizens’ health caused by the ecological environment deterioration.

4.3. Coordinated Regulation of Public Health, Ecological Environment and Economic Development in the Yellow River Basin

According to the coordinated development results calculated by the S M I P method, it’s not difficult to find that the overall coordinated development level of the Yellow River Basin is close to coordination. To obtain the optimal adjustment method, we adjust each indicator of the Yellow River Basin through the optimal set of four coordination behaviors, which are shown in Table 9:
The original data are regulated through the coordinated behavior regulation path, and then, the coordination development index of each path is calculated by the S M I P method. The calculation results are shown in Table 10, and the dynamic change chart of the development index in each province is shown in Figure 6.
On the whole, the results in Figure 6 and Table 10 imply the coordinated development index of each province in each path. Particularly, the coordinated development index growth of each path in Sichuan, Gansu, Inner Mongolia, and Shandong is relatively significant.
In terms of the specific paths, Path 4 has the best coordinated regulation effect from the holistic watershed perspective, which integrally considers the correlation and constraints. The overall coordinated development index increases by 0.42. Moreover, the adjustment effect of other paths, from high to low, is Path 3, Path 1, and Path 2. From the adjustment effect of each province, the Path 4 is still the best one, while Path 1, Path 2, and Path 3 have their own advantages in the adjustment effect when applied to different provinces. In summary, the optimal adjustment method for the optimal set of coordinated regulatory behaviors should be comprehensively considering the correlation and constraints that affect the overall development index. For the indicator’s adjustment, it is necessary to comprehensively consider its own relevance and obstacle factors, and finally, Path 4 is used as the optimal adjustment method in the paper.

5. Discussion

Existing studies have already developed several methods to quantitatively evaluate the overall coordinated development of the Yellow River Basin. Among them, the coupling coordination method is widely used. The coupling coordination method can measure the close relationship between systems and the influence of one thing on the others [55]. Table 11 lists some studies that used the coupling coordination method and did some innovations to evaluate the coordinated development level in the Yellow River Basin. As for the research systems, the evaluation of the two systems of the Yellow River Basin is the choice of more scholars. Based on the coupling coordination method, this paper uses the S M I P method to evaluate the three systems of public health, the ecological environment, and economic development in the Yellow River Basin, and it adopts coordinated identification and obstacle factor diagnosis to identify and regulate the main influencing factors. Not coincidentally, the research period in this paper is basically consistent with some existing studies. The main reason is the long period of about ten years can help to comprehensively reflect the overall development level and the long-standing problems of the Yellow River Basin. It found that most of the existing studies focus on the evaluation of coupling coordination and the identification of the main influencing factors, but there are a few explorations on the regulation of the main influencing factors. Therefore, we complement the previous research properly. Based on the evaluation results, we identify the main influencing factors and design four methods to explore the optimal method. On the whole, the overall coordinated index shows a slow upward trend with spatiotemporal heterogeneity [56], which is similar to the existing research conclusions. In addition, we also found that the overall coordinated development index of the Yellow River Basin is not only affected by the common factors, such as population size and per capita natural growth rate [35,57], but also by other specific factors, such as the number of days that air quality reaches the second standard and above, the number of medical institutions, number of higher education graduates, etc. We also reach the conclusion that the method which comprehensively considers the relevance and obstacle factors for regulation has the best overall regulation effect.
At present, the coupling coordination degree method is mainly used to evaluate the coordination development level [58]. Compared with the existing coupling coordination research method, we use the S M I P method to measure the coordination development level in the yellow river basin. The two research methods have similarities and differences. The difference is mainly reflected in the different data normalization methods. The S M I P method uses the segmentation fuzzy membership analysis method to process the data, while the coupling coordination method uses the normalization method. The same points are reflected in: ① They all use the entropy weight method to weigh the indicators. ② Both the S M I P method and the coupling coordination method have a guiding role for reality. For example, Li and Yi use the coupling coordination method to evaluate the economy, society, and the environment of nine central cities in China [59]. Zuo used the S M I P method to evaluate the relationship between humans and water in the Tarim River in China [60].
In addition, we considered the research scope. We chose the entire province of the watershed as the study area, instead of the prefecture-level cities, because it is difficult to form a relatively complete index system due to the inaccessible data in prefecture-level cities.

6. Conclusions and Policy Implications

Based on the coordinated development of the three subsystems of the ecological environment, economy, and public health, we research the nine provinces in the Yellow River Basin and construct the evaluation system for the public health, ecological environment, and economic development as a whole. In addition, the correlation degree and obstacle degree of the system indicators that affect its coordinated development index are calculated. Furthermore, the coordinated regulation method is adopted to regulate the index system. Based on the above processes, we draw some conclusions:
(1)
The coordinated development index of the public health, ecological environment, and economic development, during the study period, shows an increasing trend [34,49]. The ecological environment index (EEDI) has a higher base value but the slowest growth rate compared with the ecological environment index and economic index [48]. The base value of the public health index (PHDI) and the growth rate are in the middle level. The index of each subsystem in the Yellow River Basin tends to be consistent. However, the overall development index level is not prominent, and each subsystem still has a huge space for ameliorating the development level.
(2)
During the study period from 2009 to 2019, the overall coordinated development index kept growing steadily from 0.352 to 0.486. The level of coordinated development also has promoted from less coordinated to close to coordination. When discussing the coordinated development level of the upstream, midstream, and downstream, the upstream comes last, followed by the midstream, with the downstream topping the table [34]. As for the coordinated development level of the nine provinces, Shandong and Sichuan are at the peak levels, which are close to coordination [48]. While Ningxia and Qinghai are ranked the worst performers, which is still at a basically uncoordinated level. Other provinces are basically close to coordination. On the whole, the certain gap and barrier in the coordinated development index among the basins cannot be ignored, as well as the nine provinces. [53].
(3)
In terms of correlation, the indicators that have a general impact on the overall coordinated development index of the Yellow River Basin, including the average concentration of fine particulate matter, the per capita arable land, the effective utilization coefficient of farmland irrigation water, the number of people engaged in scientific and technological activities, the number of higher education graduates, the number of beds in health care institutions, the number of travel agencies, and the number of medical institutions [57]. In terms of the obstacle degree, the indicators that have a general restrictive effect on the overall coordinated development index of the Yellow River Basin, including the total sewage discharge, afforestation area, number of R&D personnel among 10,000 employees, natural population growth rate, government health spending as a percentage of health spending, and the number of days that the air quality reaches the second level and above [35]. According to the optimal method of coordinated behavior set, we construct the index system and found that regulation Path 4 is the optimal regulation method, which comprehensively considers the relevance and obstacle factors.
Based on the above research results and conclusions, the following policy recommendations are proposed for the high-quality development in the Yellow River Basin.
(1)
In terms of the ecological environment, strengthen the intensity of sewage treatment, increase investment in sewage treatment facilities, ameliorate sewage treatment standards to reduce pollution of ecological water, and ensure water safety for residents. In addition, treating agricultural equipment, improving the utilization rate of agricultural irrigation water, and reducing the use of agricultural fertilizers and pesticides can reduce the burden on land and make land sustainable. Moreover, promote the transformation and upgrading of heavily polluted enterprises, use clean energy, develop new technologies, and improve the efficiency of resource utilization and the recycling rate of waste, thereby reducing solid particulate matter and harmful gas emissions and improving air quality. Furthermore, strengthen afforestation, increase the coverage rate of forests and wetlands in the Yellow River Basin, and promote the restoration of the ecological environment on both sides of the Yellow River and the prevention and control of river basin pollution to enhance the environmental carrying capacity and the ability to restore the ecological environment, and the ecological barrier function of the Yellow River Basin can be stably played.
(2)
In terms of economic development, consider the actual situation of the region, optimize the industrial structure, attach importance to technological innovation, increase investment in research and development, use the actual policy to introduce talents in order to transform the local industry into technology-intensive industries and enhance the local economic creativity. Furthermore, policies guide the increase in the share of the tertiary industry structure, and they increase the disposable income of residents to stimulate economic growth to achieve the purpose of stimulating residents’ consumption and economic growth. Besides, regions should strengthen cooperation with neighbors, so provinces with better economic development can play a leading role in promoting the development of surrounding regions, accelerate economic development in poor regions, and narrow economic regional differences. At the same time of economic development, properly balancing the relationship with other industries enables the formation of a new regional economic pattern with complementary advantages and characteristic development, which realizes the sustainable development of the regional economy.
(3)
In terms of public health, raise the concept to guide population growth, improve the working welfare of medical personnel, and strengthen policy subsidies for drugs to reduce the degree of aging, improve the motivation of medical staff, and reduce the personal health consumption expenditure of residents. In addition, increase care for the elderly, strictly monitor drinking water resources, improve urban infrastructure and emergency facilities in provinces, and prevent public health crises caused by emergencies, so the lives, health, and safety of residents can be guaranteed, and the happiness and satisfaction of living can be improved. Furthermore, developing fitness and entertainment venues, travel agencies, and other venues for physical exercise and spiritual entertainment can improve the health of residents and achieve the goal of the Healthy China.
(4)
Promote the comprehensive management of the public health, ecological environment and economy subsystems. The economy can drive the improvement of ecological environment protection and public health, while the high quality of the ecological environment and public health can also promote economic development. Moreover, by breaking administrative barriers, promoting regional open cooperation, market cooperation, brand development, and benefit sharing, establish cooperative and mutual aid relationships and, ultimately, realize the overall high-quality development of the Yellow River Basin
From an application point of view, the above suggestions may be helpful for policy design. In addition, the scientific and reasonable policies can improve the level of coordinated development of public health, the ecological environment, and economy in the Yellow River Basin, and they promote the high-quality development of public health in the Yellow River Basin, which is in line with our research purposes.
Academically, the paper can effectively make up for the relative insufficiency of the current studies on the regulation method of the main factors affecting the overall coordinated development index, and it can also provide auxiliary reference for further research by other scholars. In the future, we will conduct more detailed research on the Yellow River flowing through prefecture-level cities. In addition, this study assigns one-third of the weight to each subsystem of public health, the ecological environment, and economic development, and future research will assign weight to each system in a more rational manner.

Author Contributions

Conceptualization, W.W., J.L. and T.N.; methodology, W.W., C.J., Y.H. and Z.H.; writing—original draft preparation, W.W., C.J. and Y.H.; funding acquisition, W.W. and J.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Natural Science Foundation of PR China (grant number 72001191), Henan Natural Science Foundation (grant number 202300410442), Henan Philosophy and Social Science Program (grant number 2020CZH009), Humanities and Social Science Fund of the Ministry of Education (grant number 21YJC790104), National Social Science Foundation of China (grant number 20BJL034), Major Program of National Social Science Foundation of China (grant number 21&ZD108).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

Special thanks should be given to National Natural Science Foundation of China, Henan Natural Science Foundation, Henan Philosophy and Social Science Program, Humanities and Social Science Fund of the Ministry of Education, and National Social Science Foundation of China.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Research framework.
Figure 1. Research framework.
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Figure 2. Yellow River Basin Map.
Figure 2. Yellow River Basin Map.
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Figure 3. The overall subsystem development trend change diagram.
Figure 3. The overall subsystem development trend change diagram.
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Figure 4. Coordinated development trend of upstream, midstream, and downstream.
Figure 4. Coordinated development trend of upstream, midstream, and downstream.
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Figure 5. Coordination index spatial distribution: (a) is the distribution of 2009 and (b) is the distribution of 2019.
Figure 5. Coordination index spatial distribution: (a) is the distribution of 2009 and (b) is the distribution of 2019.
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Figure 6. Dynamic changes in the development index of each province.
Figure 6. Dynamic changes in the development index of each province.
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Table 1. The grades of the coordination index of public health and high-quality development in the Yellow River Basin.
Table 1. The grades of the coordination index of public health and high-quality development in the Yellow River Basin.
Coordination LevelCoordinate GradingThe Value Range of EHP
fully coordinatedVII1
basic coordinationVI[0.8,1)
more coordinatedV[0.6,0.8)
close to collaborationIV[0.4,0.6)
less coordinatedIII[0.2,0.4)
basically uncoordinatedII(0,0.2)
totally uncoordinatedI0
Table 2. Quantitative index system for high-quality development of public health in the Yellow River Basin.
Table 2. Quantitative index system for high-quality development of public health in the Yellow River Basin.
SubsystemClassification LayerIndicator LayerExplanationUnitIndex Number
Ecological environmentEcological environment pressureFertilizer (Pesticide) Application AmountThe amount of fertilizers (pesticides) actually used in agricultural production104 tonsX1101
Per capita water consumptionTotal water supply/populationm3/capitaX1102
Total sewage dischargeThe amount of sewage discharged from the sewage outlet104 m3X1103
General industrial solid waste dischargeThe amount of solid waste discharged outside the pollution prevention and control facilities104 tonsX1104
Average concentration of fine particulate matterAverage concentration of particulate matter less than 2.5 microns in diameterμg·m−3X1105
Ecological environmentPer capita water resourcestotal water resources/total populationm3/capitaX1201
Per capita park green spaceTotal park area/total population104 m2/capitaX1202
Development and utilization of water resourcesTotal water consumption × 100%/total water resources%X1203
Per capita arable landTotal arable land area/total population104 m2/capitaX1204
Ecological environment responseInvestment in pollution control as a percentage of GDP/%Pollution treatment cost × 100%/GDP%X1301
Afforestation areaAfforestation Area108 m2X1302
Harmless treatment rate of domestic wasteAmount of garbage treated in a harmless manner × 100%/total amount of garbage%X1303
Sewage treatment ratesewage treatment volume × 100%/total sewage discharge%X1304
Effective utilization coefficient of farmland irrigation waterThe actual effective water use of farmland × 100%/total water consumption of farmland%X1305
Soil erosion control areaThe total area of soil erosion under control104 km2X1306
Economic developmentEconomic baseGDP per capitaGDP/total populationyuanX2101
Per capita disposable incomeIncome that everyone can use without limityuanX2102
Total retail sales of social consumptionThe total volume of social consumer goods transactions109 yuanX2103
The proportion of the tertiary industrytertiary industry output value × 100%/GDP%X2104
Science and education innovationNumber of R&D personnel among 10,000 employeesTotal R&D employees × 10,000/total populationpeopleX2201
Number of people engaged in scientific and technological activitiesNumber of people working in scientific and technological activitiespeopleX2202
R&D spending intensityR&D investment × 100%/total output%X2203
Number of higher education graduatesNumber of higher education graduatespeopleX2204
Opening to the outside worldForeign direct investmentAmount invested by foreign businessmen104 dollarsX2301
Import and export volumeTotal amount of goods actually imported and exported104 dollarsX2302
Degree of external dependenceTotal import and export × 100%/GDP%X2303
Public healthlevel of healthNatural population growth ratethe number of natural population increasing × 100%/average total population%X3101
Maternal mortality ratioTotal Maternal Deaths /the number of population increasing1/103X3102
Aging proportionNumber of people over 65 years old × 100%/total population%X3103
Health services and securityPersonal hygiene expenditure as a percentage of health spendingPersonal hygiene expenditure × 100%/total hygiene expenditure%X3201
Government health spending as a percentage of health spendingGovernment health expenditure × 100%/total health expenditure%X3202
Number of health techniciansNumber of people working in health technologypeopleX3203
Number of beds in health care facilitiesTotal number of beds in medical institutions × 1000/total populationPiece/103X3204
Healthy environmentThe number of days that the air quality reaches the second level and aboveNumber of days per year to achieve healthy air quality standardsdayX3301
The proportion of surface water quality reaching or better than Class III water bodyNumber of water bodies with water quality reaching or better than Class III × 100%/total number of water bodies%X3302
Health industryNumber of units of fitness, leisure and entertainment activitiesNumber of units of fitness, leisure and entertainment activities\X3401
Number of travel agenciesNumber of travel agencies\X3402
Number of Aged Care InstitutionsNumber of Aged Care Institutions\X3403
Number of medical institutionsNumber of medical institutions\X3404
Table 3. The properties of each indicator of the quantitative index system for high-quality development of public health.
Table 3. The properties of each indicator of the quantitative index system for high-quality development of public health.
Indicator LayerUnitIndex NumberabcdeIndicator Direction
Fertilizer (Pesticide) Application Amount104 tonsX1101787.71508.806229.901118.5377.173
Per capita water consumptionm3/capitaX11021278.53857.583436.636292.388148.14
Total sewage discharge104 m3X1103375,011.12242,215.677109,420.23460,124.51710,828.8
General industrial solid waste discharge104 tonsX110440,233.2727,278.75414,324.2387791.3541258.47
Average concentration of fine particulate matterμg·m−3X110571.24249.10526.96816.566.151
Per capita water resourcesm3/capitaX1201121.951302.1332482.31711,639.23820,796.16+
Per capita park green space104 m2/capitaX12027.19110.15813.12518.1423.155+
Development and utilization of water resources%X1203943.45528.591113.73158.0862.442
Per capita arable land104 m2/capitaX12040.6751.3512.0284.0946.16+
Investment in pollution control as a percentage of GDP/%%X13010.4681.1061.7453.0894.433+
Afforestation area108 m2X13020.7047.82214.94137.95260.963+
Harmless treatment rate of domestic waste%X130329.13358.45687.77998.862109.945+
Sewage treatment rate%X130438.00761.86685.72696.631107.536+
Effective utilization coefficient of farmland irrigation water%X13050.3650.4460.5260.6180.711+
Soil erosion control area104 km2X13060.0090.1470.2850.5390.794+
GDP per capitayuanX210111,521.825,104.69838,687.59658,202.94877,718.3+
Per capita disposable incomeyuanX21025627.711,049.08616,470.47225,613.58634,756.7+
Total retail sales of social consumption109 yuanX2103272.5713790.1247307.67619,741.98732,176.298+
The proportion of the tertiary industry%X21041.53820.32139.10449.86760.63+
Number of R&D personnel among 10,000 employeespeopleX220117.82928.81939.80963.82387.836+
Number of people engaged in scientific and technological activitiespeopleX22023607.239,922.54476,237.889224,451.794372,665.7+
R&D spending intensity%X22030.4320.8531.2731.9632.653+
Number of higher education graduatespeopleX220413,19499,731.475186,268.949419,504.475652,740+
Foreign direct investment104 dollarsX23013920.4231,892.715459,865.031,358,332.3152,256,799.6+
Import and export volume104 dollarsX2302108,140.42,339,995.3464,571,850.29218,581,580.3532,591,310.4+
Degree of external dependence%X23031.5015.93710.37423.6636.945+
Natural population growth rate%X31012.0793.8095.5388.73111.924+
Maternal mortality ratio1/103X310250.7134.54118.37212.0665.76
Aging proportion%X310318.43714.0229.6087.2674.926
Personal hygiene expenditure as a percentage of health spending%X320152.87843.26133.64427.44621.249
Government health spending as a percentage of health spending%X320219.6226.26532.90943.82854.747+
Number of health technicianspeopleX320321,096141,220.232261,344.465560,933.932860,523.4+
Number of beds in health care facilitiesPiece/103X320417,207.1127,639.934238,072.768602,101.384966,130+
The number of days that the air quality reaches the second level and abovedayX3301106.65182.576258.502321.201383.9+
The proportion of surface water quality reaching or better than Class III water body%X3302936.46863.93685.978108.02+
Number of units of fitness, leisure and entertainment activities\X34011.8116.456231.1111117.6562004.2+
Number of travel agencies\X340276.5452.093827.6871860.3432893+
Number of Aged Care Institutions\X340331.5550.8661070.2322410.0663749.9+
Number of medical institutions\X34041412.114,646.47427,880.84860,006.77492,132.7+
Note: c represents the average value of each indicator over the years, e represents the maximum value of the indicator increased by 10%, a represents minimum value of the indicator reduced by 10%, b represents the interpolation of a and c, and d represents the interpolation of c and e.
Table 4. The overall coordinated development index from 2009 to 2019.
Table 4. The overall coordinated development index from 2009 to 2019.
Subsystem20092010201120122013201420152016201720182019
EEDI0.4150.4380.4590.4560.4730.4650.4600.4640.4790.4790.497
HQEDI0.2750.3200.3560.3810.4040.4200.4200.4310.4470.4640.476
PHDI0.3680.3810.3970.4040.4120.4320.4440.4570.4720.4730.485
EHP0.3520.3800.4040.4140.4300.4390.4420.4510.4660.4720.486
Coordinated levelIIIIIIIVIVIVIVIVIVIVIVIV
Note: we obtain the EEDI, HQEDI, and PHDI through Equations (1)–(5), and the EHP is calculated through Equation (6).
Table 5. Coordinated development index of provinces and upstream, midstream, and downstream of the Yellow River Basin from 2009 to 2019.
Table 5. Coordinated development index of provinces and upstream, midstream, and downstream of the Yellow River Basin from 2009 to 2019.
Area20092010201120122013201420152016201720182019
Qinghai0.2270.2260.2580.2590.2870.3040.2950.3110.3200.3370.367
Sichuan0.4900.5190.5490.5670.5750.5950.6040.6260.6530.6430.650
Gansu0.2490.2660.2830.3050.3260.3290.3510.3390.3680.3810.411
Ningxia0.1800.2040.2120.2030.2320.2290.2410.2360.2510.2760.288
Inner Mongolia0.3260.3500.3860.4010.4260.4190.4230.4290.4410.4360.440
Shaanxi0.4040.4470.4680.4750.4930.5140.5150.5270.5490.5400.564
Shanxi0.3270.3830.4020.4070.4120.4220.4130.4350.4290.4440.451
Henan0.4070.4370.4690.4940.5020.5190.5130.5260.5420.5440.551
Shandong0.5600.5860.6070.6160.6160.6210.6190.6300.6420.6470.652
Upstream0.2940.3130.3380.3470.3690.3750.3830.3880.4070.4150.431
Midstream0.3660.4150.4350.4410.4520.4680.4640.4810.4890.4920.508
Downstream0.4840.5110.5380.5550.5590.5700.5660.5780.5920.5960.602
Note: the indices of each province, upstream, midstream, and downstream are obtained by Equations (1)–(6).
Table 6. Coordinated development levels of provinces and upstream, midstream, and downstream of the Yellow River Basin from 2009 to 2019.
Table 6. Coordinated development levels of provinces and upstream, midstream, and downstream of the Yellow River Basin from 2009 to 2019.
Area20092010201120122013201420152016201720182019
QinghaiIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII
SichuanIVIVIVIVIVIVVVVVV
GansuIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIV
NingxiaIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII
Inner MongoliaIIIIIIIIIIVIVIVIVIVIVIVIV
ShaanxiIVIVIVIVIVIVIVIVIVIVIV
ShanxiIIIIIIIVIVIVIVIVIVIVIVIV
HenanIVIVIVIVIVIVIVIVIVIVIV
ShandongIVIVVVVVVVVVV
UpstreamIIIIIIIIIIIIIIIIIIIIIIIIIVIVIV
MidstreamIIIIVIVIVIVIVIVIVIVIVIV
DownstreamIVIVIVIVIVIVIVIVIVIVV
Note: the result is obtained by using Table 4 and Table 5.
Table 7. Calculation results of the correlation degree.
Table 7. Calculation results of the correlation degree.
Area12345678
x r 0 i x r 0 i x r 0 i x r 0 i x r 0 i x r 0 i x r 0 i x r 0 i
QinghaiX11020.971X32010.958X32020.956X11050.951X33020.949X12040.944X12030.942X11010.942
SichuanX32040.970X32030.967X34020.943X22040.937X13030.936X22020.935X22030.913X21030.898
GansuX13050.993X12040.964X22040.957X22020.957X11020.954X11050.950X22030.946X21040.944
NingxiaX12020.977X21040.973X13010.959X34040.958X12040.949X11050.946X11010.939X11040.937
Inner MongoliaX34020.966X13030.965X13060.950X34030.949X12040.948X22040.947X21040.943X11050.915
ShaanxiX22010.945X13050.944X11050.940X22040.939X34020.931X33020.924X31020.912X22030.909
ShanxiX13050.981X34040.964X13040.957X22040.951X34020.946X13060.945X32040.943X11050.933
HenanX32030.976X32040.975X34040.968X22040.965X13040.962X22020.962X31020.955X13050.955
ShandongX22020.979X32030.971X34040.968X23010.959X13040.957X22030.949X32040.948X13050.946
Note: The results are calculated by using the EHP and SHD already obtained, as well as Equations (7)–(9).
Table 8. Index barriers of provinces in the Yellow River Basin.
Table 8. Index barriers of provinces in the Yellow River Basin.
Area 1 2 3 4 5 6 7 8
x P j x P j x P j x P j x P j x P j x P j x P j
QinghaiX210439.8X310227.9X340124.6X220323.6X320322.6X210322.0X220421.4X220120.9
SichuanX130120.8X130218.5X130518.4X110318.3X310316.2X120415.3X310113.3X320213.3
GansuX210124.8X230122.4X220120.2X320419.0X220218.7X210217.9X210316.5X230216.0
NingxiaX120338.6X110227.8X340223.9X340122.3X320322.2X210321.1X130220.6X220420.5
Inner MongoliaX110222.5X220320.7X110419.5X220117.2X230116.5X310116.5X130215.0X340414.6
ShaanxiX120217.8X330115.9X120415.4X320214.1X110113.2X230212.7X130411.8X110311.7
ShanxiX330226.6X110423.5X230118.6X120115.6X210115.5X340414.9X120214.5X310114.4
HenanX110129.5X110524.6X130219.7X130617.8X330117.4X130117.4X110316.6X330216.5
ShandongX110528.9X110324.6X110119.5X330219.3X310318.7X320218.2X130617.2X330116.7
Note: the results are calculated by using the SHD already obtained and Equations (10)–(12).
Table 9. The coordinated regulation path.
Table 9. The coordinated regulation path.
PathExplanation
Path 1The increment of all indicators adjusts to 1x the 2009–2019 increase.
Path 2The increment of key indicators adjusts to double the 2009–2019 increase, The increment of other indicators adjusts by 0.8 times.
Path 3The increment of major obstacle factors adjusts to double the 2009–2019 increase. The increment of other indicators adjusts by 0.8 times.
Path 4Comprehensively consider the relevance and major obstacle factors to determine the increase multiple.
Note: key indicators and major obstacle factors represent top 8 indicators in relevance analysis and obstacle analysis, respectively.
Table 10. The development index of each province in the set of regulatory behaviors.
Table 10. The development index of each province in the set of regulatory behaviors.
Area2019Path 1Path 2Path 3Path 4
Qinghai0.3670.4040.3900.3920.408
Sichuan0.6500.6670.6630.6990.702
Gansu0.4110.4640.4500.4650.483
Ningxia0.2880.3100.3090.3030.312
Inner Mongolia0.4400.4880.4760.4780.500
Shaanxi0.5640.5810.5740.5930.595
Shanxi0.4510.4760.4710.4780.479
Henan0.5510.5640.5630.5650.574
Shandong0.6520.6530.6620.6780.703
Table 11. Existing studies using the coupling coordination method in the Yellow River Basin.
Table 11. Existing studies using the coupling coordination method in the Yellow River Basin.
Paper AuthorsResearch PeriodNumber of SystemsMethodsMain Conclusions
Zhao Y.; Hou P et al. [48]2000–20182coupling coordination model; evaluation method; coupling degree model.The economic development index rose steadily, the ecological status index rose first and then fell;
The degree of coupling slowly increased and then decrease;
Liu K; Qiao Y et al. [34]2008–20172coupling coordination model;
geographical weighted regression.
The coupling coordination economic development and ecological environment showed regional heterogeneity;
The coupling coordination degree is affected by population si1ze, openness and advanced industrial structure, etc.
Li H; Jiang Z et al. [35]2010–20172coupling coordination model; obstacle degree modelThe coupling coordination social economic and resource environment showed an overall upward trend;
The nine obstacle factors include natural growth rate of population, per capita green area of parks and so on
Qiu M; Yang Z et al. [57]2008–20182grey relationship and decoupling modelThe urbanization level and ecological security level show an overall upward trend;
There is a strong decoupling effect between them;
The future ecological security will be more restrictive to the urbanization.
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Wei, W.; Jin, C.; Han, Y.; Huang, Z.; Niu, T.; Li, J. The Coordinated Development and Regulation Research on Public Health, Ecological Environment and Economic Development: Evidence from the Yellow River Basin of China. Int. J. Environ. Res. Public Health 2022, 19, 6927. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph19116927

AMA Style

Wei W, Jin C, Han Y, Huang Z, Niu T, Li J. The Coordinated Development and Regulation Research on Public Health, Ecological Environment and Economic Development: Evidence from the Yellow River Basin of China. International Journal of Environmental Research and Public Health. 2022; 19(11):6927. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph19116927

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Wei, Wei, Chenggong Jin, Ying Han, Zhenhui Huang, Tong Niu, and Jinkai Li. 2022. "The Coordinated Development and Regulation Research on Public Health, Ecological Environment and Economic Development: Evidence from the Yellow River Basin of China" International Journal of Environmental Research and Public Health 19, no. 11: 6927. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph19116927

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