The Way of Governance: Smart Shift in the Modernized and Innovative Urban Development

To analyze the intakes of main food among the children of 6-17 years in different regions of China from 2019 to 2021, and to provide a scientific basis for evaluation and guiding Chinese children to make reasonable diet. Multistage stratified random sampling method was used to collect data in east China, north China, central China, south China, southwest, northwest and northeast seven areas of each random two provinces, randomly selected from each province one urban survey site and one rural survey site, 28 sites of the 13th Five Year National Science and Technology Basic Resources Survey Project-Chinese children aged 0-18 investigation and application of nutrition and health system in 14 provinces of China. The study included 6413 children aged 6 to 17. Three consecutive 24-hour recalls method combined with weighing were used to collect the information of food intake. According to the food classification in the standard version of the food composition list, the food was divided into cereals, tubers, fresh vegetables, fresh fruits, meat and poultry, fish and shrimp, eggs, milk, etc. , and the intake of various foods was calculated for boys and girls aged 6-8, 9-11, 12-14 and 15-17 in different regions. Compared with the average daily food intake of children of the same sex and age in the urban and rural, The average daily intake of cereals and tubers for boys aged 9-17, cereals for girls aged 9-17, tubers for girls aged 12-17, and fish and shrimp for boys of edible population aged 15-17 were higher in rural areas than in urban areas. There were differences in the average daily food intake and consumption rate of fresh vegetables, fresh fruits, meat and poultry, eggs and milk of the same sex and age, which were higher in urban than in rural areas(P<0.05). Compared with the average daily food intake of children of the same sex and age in the south and the north, the average daily intake of cereals and eggs for boys aged 9-14, cereals for girls aged 6-8, and fresh fruits for boys and girls of edible population aged 6-17 were higher in the north than in the south. There were differences in average daily intake and consumption rates of tubers, fresh vegetables, meat and poultry, milk and fish and shrimp of the same sex and age, which were higher in the south than in the north(P<0.05). Compared with the average daily food intake of children of the same sex and age in the eastern, central and western regions, the average daily intake of cereals for boys aged 6-14, cereals for girls aged 6-17, fresh fruits for boys and girls of edible population aged 6-17, and fish and shrimp for boys and girls of edible population aged 15-17 were lower in the eastern region than in the central and western regions. The average daily intake of tubers for boys aged 9-11 and 15-17, for girls aged 9-17 were higher in the western regions than the eastern and central regions. The average daily intake of eggs for boys and girls aged 12-17 was lower in western regions than the eastern and central regions. There were differences in average daily intake and consumption rates of fresh vegetables, meat and poultry and milk of the same sex and age, which were higher in the eastern region than in the central and western regions. (P<0.05). The proportion of coarse grains to cereals was low, between 3.7% and 10.1%. The proportion of pork to meat and poultry was high, between 56.1% and 71.4%. In China, there are differences in daily intake of main food for children aged 6 to 17 years old in urban and rural areas, north and south areas, east, central and west areas.

Which Factors Affect Farmers’ Willingness for rural community remediation? A tale of three rural villages in China

Objective: To analyze the change in human resources within China's Centers for Disease Control and Prevention (CDC) from 2010 to 2020. Methods: The self-reported information from provincial, prefectural (city), and county (district) levels of China's CDC, covering employee counts, staff composition, professional qualifications, educational backgrounds, technical titles, and tenure, were extracted from the China Disease Prevention and Control Information System. The demographic context was provided by the annual population figures from the China Statistical Yearbook (2010-2020). The profile of CDC personnel was described, and the average annual percentage rate change (AAPC), average annual percentage rate change (APC), human resource agglomeration degree (HRAD) and the difference between HRAD and population agglomeration degree (PAD) were calculated. The Joinpoint regression model was used to analyze the time trend. Results: The decade under review witnessed a net increase of 17 300 active and 18 300 enrolled personnel in the CDC, surpassing the national population growth rate with AAPCs of 0.93% and 1.03%, respectively. This upward trajectory was statistically significant (P<0.05). The ratio of disease control personnel per 10 000 population escalated from 1.14 to 1.21. An initial decline in active CDC workforce density (from 1.31 to 1.27 per 10 000 population between 2010 and 2017) was followed by an increase (from 1.28 to 1.37 between 2018 and 2020), with APCs of -0.40% and 3.73%, respectively. The proportion of professional and technical staff in 2019 was highest in the eastern region (86.01%), followed by the western (83.75%) and central regions (79.54%). The period also saw an enhancement in the average academic degree (from 1.91 to 2.43 points) and professional title scores (from 1.39 to 1.53 points) of CDC personnel. While the average tenure in the eastern and western regions showed a slight decline, the central region experienced an increase, with HRAD values indicating a higher concentration in the eastern and central regions compared to the western region. The HRAD-PAD discrepancy revealed a negative value in the eastern region, nearing zero in the central and western regions. Conclusion: Between 2010 and 2020, China's CDC experienced notable growth in human resources and underwent structural optimization, albeit with significant regional disparities in concentration.

Based on a comprehensive review of previous studies about the threshold effects of financial development on the process of foreign direct investment (FDI) spillovers, the present work roundly measures the financial development from the aspects of scale, structure, and efficiency and applies a multiple threshold regression model to estimate the threshold effects of financial development on FDI spillovers, and then examines the inherent relationship between FDI spillovers effects and the financial development from the three aspects, respectively, in different regions of China, based on regional panel data from 2000 to 2014. The results revealed that there are two thresholds of financial development scale, structure and efficiency, existing in the FDI spillover processes in different regions. The FDI spillovers effects are greatest in the eastern region and are generally smallest in the western region. There is a negative correlation between FDI spillovers effects and the financial development scale or efficiency in eastern and central region. Moreover, there is positive correlation between FDI spillovers effects and the financial development structure in eastern and central region. Additionally, there is a positive correlation between FDI spillovers effects and the financial development scale, structure, or efficiency in western region. The capital, labor, and regional technology progress have positive effects on economic growth in different regions and the effects of financial development on economic growth are not unanimous in each region. Based on the empirical results, some policies on how to develop regional finances and how to introduce FDI to promote economic growth are recommended.

This research investigates the disparities and convergence in higher education fiscal expenditures across different regions in China. The study utilises Gini coefficient analysis and σ-convergence/β-convergence tests to quantify the extent of disparities and explore convergence trends over a twelve-year investigation period (2007–2018). The results shed light on the imbalances in resource allocation and provide valuable insights into the efforts required to achieve a more equitable distribution of fiscal resources for higher education. The findings reveal significant disparities in higher education fiscal expenditures between the Eastern, Central, Western, and Northeastern regions, with the Eastern region exhibiting the largest gap compared to others. Remarkably, the disparity between the Eastern and Central regions is even greater than that between the Eastern and Western regions, emphasising the need for targeted interventions to address regional imbalances. Over the study period, the gap between the Eastern and Central regions remained consistently higher than other regional disparities. Moreover, the research shows a general trend towards narrowing regional fiscal expenditure disparities, with the most pronounced convergence observed between the Central and Northeastern regions. The Western region exhibits slightly larger disparities than the Central and Northeastern regions, possibly attributed to greater fiscal policy support and lower student enrollments. Nevertheless, the fiscal expenditure gap between the Western and Central regions has shown a trend towards reduction. The study also explores absolute and conditional β-convergence, revealing notable convergence patterns in the Eastern and Central regions. However, the Western and Northeastern regions exhibit varying degrees of convergence, indicating the necessity for region-specific convergence mechanisms. To achieve a balanced allocation of financial resources for higher education across regions, the study recommends targeted fiscal policies, additional funding, and improved transparency and accountability. Policymakers should focus on enhancing convergence mechanisms to ensure a more equitable distribution of resources and foster the sustainable development of higher education throughout the country. While this research provides valuable insights, it is essential to consider other potential factors influencing fiscal expenditure disparities, such as policy orientation, economic disparities, and demographic structures, for a more comprehensive understanding. Future research may benefit from qualitative investigations to further explore the complexities of higher education fiscal expenditure imbalances and identify effective policy interventions.

Based on the social physics theory, this paper analyzes the economic disparities between different regions in China, and contributes a conceptual model of population migration among eastern, central, western and north-eastern regions. The national 1% population sample investigation data is adopted to build a network of inter-provincial population migration, and the population migration network is analyzed with social network analysis. The results are shown that there is a very strong correlation between migrant population and economy disparity in China, and the migration with obviously geographical characteristics. The eastern region is the main areas for migration-inflow; the central region is the main areas of migration-outflow; the western region is relatively “locked-up”, with a little of population flow; and the migration of the northeast is mainly within its own regional territory.

In recent years, the proportion of added value of China's cultural industry to GDP has been increasing year by year. However, due to different levels of economic development and cultural resources, there are significant differences in the development of cultural industries in different regions. This study considers a sustainable positive externality by setting the patent as a new output and employs the non‐radial directional distance function in the framework of meta‐frontier to investigate the innovative performance of China's cultural industry because of regional disparities. Our main findings are that there is a major technological gap among the eastern region, the central region and the western region, in which the technical and management capabilities of the eastern region are far greater than those of the central and western regions; Cultural industries have greater room for improvement in the eastern, central and western regions, especially the western region; The efficiency level of the cultural industry is likely to be related to the local economic strength. This article explores the factors that constrain the competitiveness of cultural industries in different regions of China. Then based on its influencing factors, corresponding development measures are proposed.

During the “14th Five-Year Plan” period, a question worth exploring in depth would be how China promotes green development through green finance to realize the goal of financially supporting the construction of ecological civilization. This paper builds a super-efficiency SBM window model to evaluate the comparable eco-efficiency of 30 provincial administrative regions in Mainland China (except Tibet) as a measurement of green development, and constructs an evaluation system for the green finance index, as a measurement of regional green finance development levels in China from 2007 to 2019. This paper also constructs spatial econometric models to study the effects of green finance on green development, and the influence of green finance on green development through supporting green technological innovation. Moreover, this paper analyzes the mechanisms of the spatial spillover effects and the heterogeneity in eastern, central, and western regions of China. The results of the study show that green finance only has a positive effect on green development in eastern regions, while in central and western regions, it fails to effectively support green development. The positive effect of green finance on green development by supporting green technological innovation is only in eastern regions, but it is not significant in the central region, while negative effect in the western region. Finally, according to the research conclusions, it is proposed to implement differentiated policies of green finance and the integration policies of green finance and green technological innovation policies in different regions of China.

With limited resources, growing environment constraints and downward pressure on the economy, increasing agricultural environmental total factor productivity (AETFP) and its contribution to agricultural growth is significant for transforming agricultural development to make it more resource efficient and environment-friendly. This paper considered technological heterogeneity in different regions of China and measured AETFP in 30 provinces from 1997 to 2015 using the Metafrontier Malmquist-Luenberger (MML) productivity index. Multi-dimensional analysis was made on temporal and spatial characteristics, evolution patterns, and influencing factors of AETFP in China. The results showed that: (1) AETFP increased in the Ninth, Tenth, Eleventh, and Twelfth Five-Year Plan periods, with average annual growth rates of 0.76%, 0.88%, 1.17%, and 0.87%, respectively. (2) The average annual growth rate of AETFP in the eastern, central, and western regions decreased successively. The eastern region generally had played a leading role. The central region had a catch-up effect on environmental production technologies from the eastern region, while the western region lacked the catch-up effect. (3) The dynamic evolution of AETFP had prominent features. For the whole nation, the kernel density curve of AETFP continuously moved to the right. The main peak value continuously decreased and the width of the main peak continuously increased. The internal differences of AETFP in the eastern and western regions exhibited an increasing trend, while the internal differences of AETFP in the central region showed little change. (4) There was an inverted U-shaped relationship between agricultural economic growth and AETFP. Both the disaster rate and planting structure had a negative impact on AETFP with varying degrees of significance. Income gaps between urban and rural areas can partially offset the role of urbanization in promoting the growth of AETFP. The greater the income differences between urban and rural areas, the weaker the role of urbanization in promoting the growth of AETFP. These findings can help the government determine policies to change the agricultural development mode and formulate effective measures to improve AETFP.

Spatial differences, dynamic evolution and influencing factors of China's construction industry carbon emission efficiency

&lt;p style="text-align:justify"&gt;&lt;br /&gt; &lt;span style="font-size:10.5pt"&gt;&lt;span style="font-family:等线"&gt;&lt;span dir="ltr" lang="EN-US" style="font-family:&amp;quot;Cambria&amp;quot;,serif"&gt;This paper examines impacts of China&amp;rsquo;s financial liberalization policy on income inequality, through three channels: financial scale, financial structure and financial efficiency, an empirical analysis based on panel data of 30 provinces in China from 1996 to 2013 is conducted. The results confirm the Kuznets effect between financial scale, financial structure and income inequality. As the size of the financial sector expands, the financial structure is tilted toward direct financing, and the income gap among residents will experience a &amp;quot;reverse U-shaped&amp;quot; trend that rises first and then falls. Most of China has not yet passed the turning point, and is still in the upper bound of the &amp;quot;inverted U-shaped&amp;quot; curve. Financial liberalization policies will continue to exacerbate income inequality. The impact of financial efficiency on income distribution is quite different in different regions of China. After dividing the whole China into three regions according to the degree of economic development, it is found that the financial efficiency of the eastern and western regions has a Kuznets effect on the income gap, but compared with the eastern region, more provinces and cities in the western region have entered the stage of reducing the income inequality, and the financial development has a great impact on the western region. The effects of financial development on central China are weak, and income inequality increases with financial efficiency.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;

With growing global attention on sustainable environmental development, green investment has become an important tool to drive the green transformation of the economy. Financial agglomeration areas, as capital-intensive regions, provide strong support for green technological innovation and eco-environmental projects. Additionally, the policy inclinations and investment preferences of financial agglomeration areas directly influence the flow and efficiency of green funds, further shaping the path of economic green transformation. Based on this, this paper selects panel data from 31 provinces in China (except Hong Kong, Macau, and Taiwan) over 15 years from 2007 to 2021. Using the fixed effects model, the study examines the impact of financial agglomeration on the scale of green investment and conducts a heterogeneous analysis of the effects in different regions of China, as well as proposing related policy suggestions. The results show that an increase in the level of financial agglomeration can significantly enhance the scale of green investment in a region, especially in the central regions. Compared to the eastern and western regions, the promotion effect of financial agglomeration is more pronounced in the central region.

BackgroundIdiopathic epiretinal membranes (ERMs) often cause metamorphopsia and the progressive loss of central visual function, which seriously affect quality of life. We aimed to map the distribution pattern of idiopathic ERMs in China and to examine the factors affecting the surgical choices of multicenter surgeons.MethodsA national ophthalmologist-oriented questionnaire was administered, applied with a multistage probability sampling method. Data of essential characteristics, including age, professional title, residence, and perioperative and postoperative care, were gathered. All the data are expressed as odds ratios (ORs) and 95% confidence intervals (CIs). The histogram and choropleth map were generated by Excel 2016.ResultsIn total, 1,137 (85.2%) valid responses were returned with maximized response and completion rates. The study showed that monthly admission numbers, and preoperative and postoperative care varied significantly across different regions in China. Generally, the monthly patient admission numbers were lower in the Western region than the Eastern region. However, patients in the Eastern region had longer preoperative waiting periods and shorter hospital stays.ConclusionsThe epidemiology of idiopathic ERMs varied significantly across different regions in China. The distribution pattern of ERM in China and the overview of the factors affecting the surgery approaches of multicenter surgeons were shown. The findings of this study will contribute to the formulation of medical policies, and provide insights into the healthcare environments across China.

Objective: To investigate the occurrence pattern of abnormal bone density in male long-distance runners from several different regions of China, and provide a basis for elucidating the influences of geo-environmental differences on bone density. Methods: We employed a set of well-designed exclusion-inclusion criteria to recruit study subjects, in which compounding factors were managed and regional environmental traits were fully incorporated. WHO (World Health Organization) criteria for the diagnosis of osteoporosis were then used to examine the subjects to determine occurrence of abnormal bone density. The resulting data were analyzed using methods of spatial statistics, which included several approaches, such as spatial autocorrelation, hot spot analysis, and Geodetector Software analysis, to depict and analyze the spatial distribution of abnormal bone density in male athletes from different regions in China, thereby investigating the influences of geo-environmental factors (e.g., temperature, humidity, and altitude) on bone density. Results: A total of 685 subjects were effectively examined in this study, including 486 with normal bone density, 185 with osteopenia, and 14 with osteoporosis. Spatial distribution analysis revealed that the distribution of subjects with abnormal bone density overall exhibited a pattern indicating that the level of abnormal bone density in the eastern regions was higher than that in the western regions and that the levels of abnormal bone density in the southern and northern regions were higher than that in the middle regions. Spatial autocorrelation analysis revealed a Moran’s I = 0.136, Z-score = 1.114, and P value = 0.265 and indicated that the athletes with abnormal bone density were randomly distributed in each region. Hot spot analysis revealed that Tibet and Qinghai displayed distributions of cold spots. Geodetector Software analysis yielded a Q value for annual average temperature of 1.000 and a corresponding P value of 0.000, and the results revealed that temperature significantly affected bone density and that altitude, relative humidity, sunlight hours, and temperature variations displayed synergistic effects on bone density and could diminish the influences of temperature on bone density. Conclusion: Our data revealed that different regions displayed different distribution patterns of abnormal bone density such that the level in the eastern regions was higher than that in the western ones and that the levels in the southern and northern regions were higher than that in the middle regions; specifically, the provinces of Yunnan, Heilongjiang, Hainan, and Inner Mongolia had high rates of abnormal bone density, whereas Tibet and Qinghai had relatively good conditions of bone density. Our data suggested that suitable temperature changes and appropriate levels of temperature variations can decrease the occurrence rates of osteopenia and osteoporosis.

Using the panel data of 30 provinces in China from 2008 to 2018, this paper compares the impact of clean energy on carbon emissions in different regions of China on the basis of extending the STIRPAT model. The results show that the impacts of clean energy on carbon emissions are different in different regions. The eastern region is not significant due to its developed economy and many influencing factors. The carbon emissions in the central and western regions are significantly affected by the energy structure, which reflects the relatively low scale of clean energy development in China and the huge dependence on fossil energy. In the future, one is to continue to strengthen the construction of clean energy; the other is to improve the technological level of the central and western regions and reduce their dependence on fossil energy.