Interregional Differences Research Articles

Level measurement, regional variations, and the dynamic evolution of active aging in China-analysis based on CHARLS tracking data.

Given the world's largest and increasingly serious aging population, China has elevated "positively responding to aging of population" to a national strategy. Exploring the current state and evolutionary trends of active aging over the past decade is a fundamental prerequisite and the primary task for implementing this strategy. Based on data from the China Health and Retirement Longitudinal Study (2011-2018), this study primarily employs methods such as the entropy method, Gini coefficient, Moran index, and Kernel density estimation to analyze the development level, regional differences, and dynamic evolution of active aging in China. (1) From a general point of view, the overall level of active aging in China has not been high in the past decade, but has shown a rising trend year by year. Older Chinese people exhibit high levels of physical and mental health, but social participation and economic status remain areas of weakness in active aging. (2) Inter-regional differences are the main source of the overall differences in the level of active aging in China. (3) There is a spatial clustering of the active aging level in China, along with a neighborhood effect. (4) The bifurcation phenomenon of active aging in China has intensified over time. While the eastern region exhibits uneven development, the central and western regions have generally had more balanced growth. To improve the level of active aging among older adult individuals in China, policymakers should continuously optimize policies and pay more attention to the economic status and social participation of the older adult. Local governments should not only fully leverage their regional advantages but also interact with other regions to achieve cross-regional joint development.

Carbon information disclosure and corporate financial performance-Empirical evidence based on heavily polluting industries in China.

Global climate change has become one of the most large-scale, widespread, and far-reaching challenges facing mankind. Against this background, China has proposed a "dual-carbon" target in 2020, which greatly demonstrates China's determination and commitment to carbon emission reduction, and the burden of realizing the "dual-carbon" target is mainly borne by heavy polluters. The burden of achieving the "dual-carbon" goal is mainly borne by the heavily polluting firms. Although this has increased the economic burden of the firms to a certain extent, carbon information disclosure reduces the degree of information asymmetry and also obtains the support of the government, which improves the financial performance of the firms. Based on the data of A-share listed companies in Shanghai and Shenzhen in the heavy pollution industry in 2013-2023, this paper analyzes the relationship between carbon information disclosure, and corporate financial performance according to signaling theory, rent-seeking theory, and sustainable development theory. It is found that enhanced corporate carbon disclosure can significantly improve corporate financial performance, and the main effect is realized through reducing debt financing costs and increasing the proportion of institutional investors' shareholding. In the heterogeneity analysis, this paper finds that the main effect is more significant in the samples of firms located in the western region and the central region. Based on existing research, this paper deepens the study of the relationship between carbon disclosure and corporate financial performance. By integrating the multiple perspectives of signaling theory, rent-seeking theory and sustainable development theory, this paper systematically analyzes how creditors, institutional investors and other stakeholders play a role in the dynamic interaction between carbon disclosure and corporate financial performance, and reveals the motives and mechanisms behind the behaviors of these stakeholders. In order to further refine the analysis path, this paper constructs an intermediary model in order to deconstruct the deep logic of the path and mechanism through which carbon disclosure indirectly affects corporate financial performance. This model not only enhances the theoretical explanatory power, but also provides a more refined analytical framework for empirical testing, which helps to reveal the "black box" mechanism of carbon disclosure's impact on corporate financial performance. In addition, in view of China's vast territory and the uneven level of economic development between regions, this paper adopts a differentiated analysis strategy, based on the economic characteristics of the regions where the heavy polluters are located, and divides the whole sample into three sub-samples for independent regression analysis. This heterogeneity test incorporates inter-regional development differences into the scope of analysis, making the research conclusions more geographically specific and policy-guiding significance. By comparing and analyzing the differences in the impact of carbon disclosure on the financial performance of enterprises in different regions, this paper provides a reference for the government to formulate differentiated carbon disclosure policies in the future, accurately promote the construction of the carbon trading market, and efficiently achieve the carbon emission reduction targets at the national level.

Spatio-temporal evolution characteristics and influencing factors of carbon emission reduction potential of the transportation industry in China

AbstractScientific estimation of China's transport carbon reduction potential (CERP) and exploration of its temporal and spatial characteristics and influencing factors are important bases for formulating emission reduction policies. Based on the dual perspective of equity and efficiency, we assess the CERP of the transportation industry in 30 provinces in China from 2010 to 2019 and analyze its spatio-temporal evolution characteristics using the Kernel density estimation method. Then, the Dagum Gini coefficient is used to measure the regional differences and sources of the CERP, and its influencing factors are analyzed with the help of the random effects panel Tobit regression model. The results show that: (1) from 2000 to 2019, the CERP of the transportation industry in China and the three regions show an oscillating upward trend, with a spatial pattern of "high in the west and low in the east". (2) The overall difference in the CERP of the transportation industry shows a fluctuating downward trend, and the difference in hypervariable density has the highest contribution rate. The inter-regional differences between the West and other regions are the largest, and the intra-regional difference pattern shows the pattern of western > central > east. (3) The technological improvement, industrial structure, and scale of transportation industry development have a significant positive impact on the CERP of the transportation industry. The influence of urbanization influence and environmental regulation have a significant negative influence.

Spatiotemporal dynamic and regional differences of public attention to vaccination: An empirical study in China

Background Internet searches offer an indicator of public attention and possible demand for certain things. Studying the spatiotemporal characteristics of the public’s concern for vaccination can determine the spatiotemporal distribution of demand for vaccines in China, and capture the changes in the health awareness of the Chinese population, thus informing future vaccination strategies. Methods Based on the collection of Baidu search indices for vaccination-related keywords in 363 cities in China, This paper seeks to explore the spatiotemporal changes and regional differences in public attention toward vaccination in China by using the seasonal index, seasonal concentration index, Herfindahl index, Moran index, and Dagum Gini coefficient. Results The following findings are presented. First, there are significant seasonal fluctuations and unbalanced monthly distributions of vaccination-related public attention in China. Second, the public attention in Chinese cities shows the spatial characteristics of "leading in the east, followed by the central, western and northeastern regions". The spatial correlation of attention has been strengthened, and the high-high clusters are mainly distributed in the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Greater Bay Area (GBA) urban agglomerations. Third, regional differences in overall public attention narrowed in China, with intra-regional differences narrowing in seven regions (Northwest China, Central China, and so on), and intra-regional differences increasing in East China. The dominant role in the Gini coefficient changes from transvariation intensity to inter-regional differences. Conclusion Major public health emergencies stimulate the public’s attention to health topics. Although the short-term increase in vaccination-related public attention was not observed to translate into a long-term increase in public vaccine literacy, the seasonal and regional differences in vaccination-related public attention in China have significantly narrowed before and after COVID-19, suggesting that the imbalance between public health literacy levels has improved.

Intra- and inter-session reliability and repeatability of 1H magnetic resonance spectroscopy for determining total creatine concentrations in multiple brain regions.

Using proton magnetic resonance spectroscopy (1H MRS) to determine total creatine (tCr) concentrations will become increasingly prevalent, as the role of creatine (Cr) in supporting brain health gains interest. Methodological limitations and margins of error in repeated 1H MRS, which often surpass reported effects of supplementation, permeate existing literature. We examined the intra- and inter-session reliability and repeatability of 1H MRS for determining tCr concentrations across multiple brain regions (midbrain, visual cortex and frontal cortex). Eighteen healthy adults aged 20-32 years were recruited (50% female; n=14 intra-session; n=15 inter-session). 1H Magnetic resonance imaging and spectroscopy were completed at 3T. Intra-session analyses involved repeated 1H MRS of the midbrain, visual cortex and frontal cortex without participant or voxel repositioning, whereas inter-session analyses involved measurements of the same regions, but with participant and voxel repositioning between repeated measurements. The 1H MRS data (174 spectra) were analysed using TARQUIN and OSPREY, and voxel fractions (grey/white matter and CSF) were determined using segmentation. Our findings show that tCr concentrations can be determined reliably and repeatably using 1H MRS, within an error of <2%, and that large inter-regional differences in tCr concentration are present in the human brain. We provide new minimum detectable change data for tCr concentrations, a detailed discussion of the inherent error sources in repeated 1H MRS, including the substantial effect of the analysis package on tCr quantification, and suggestions for how these should be managed to improve the interpretability and clinical value of future research. More studies are needed to determine whether our findings can be replicated in other centres and different populations.

Equity of intensive care unit bed resource allocation in ethnic minority areas of China—an empirical analysis based on geographical and population dimensions

ObjectiveThe purpose of this study is to analyse the changes in the equity of intensive care unit (ICU) bed allocation in 14 cities in China’s Guangxi Zhuang Autonomous Region from...

Spatiotemporal Evolution and Obstacle Factor Analysis of Coupling Coordination Between Economic Resilience and Green, Low-Carbon Development in China

To achieve economic resilience and green, low-carbon development are two goals of China’s high-quality economic development. This paper uses the entropy weight method and coupling coordination degree model to estimate the coupling coordination level of economic resilience and green, low-carbon development. Kernel density estimation, Moran index, Dagum Gini coefficient, Markov chain, and obstacle degree model are used to explore the spatiotemporal evolution characteristics and obstacle factors. The results are as follows. (1) The coupling coordination degree between China’s economic resilience and green, low-carbon development has increased overall. However, the eastern region has the highest, and the central region has the fastest growth. (2) The coupling coordination degree shows positive spatial autocorrelation, with most provinces exhibiting high–high or low–low aggregation characteristics. (3) The contribution of imbalance mainly comes from inter-regional differences, but the contribution of intra-regional differences to imbalance is increasing. (4) The spatio-temporal evolution pattern is generally better, and the probability of the coupling coordination degree maintaining the initial state is the largest. The neighborhood’s state affects the transition probability but does not affect that of high-level provinces. (5) Innovation capacity is the main obstacle to improving economic resilience, and per capita water resources are the main obstacle to green and low-carbon development. Finally, this paper puts forward suggestions for creating a good innovation environment, increasing R&amp;D investment, promoting green technology progress, optimizing regional cooperation and resource allocation, and promoting industrial green transformation.

Challenging (mis)understandings of labour productivity for levelling-up: a broader research agenda for regional development

ABSTRACT Policy work typically conflates measures of real and nominal labour productivity, using them interchangeably, often leading to misdiagnoses of the causes of regional disparities, with potentially flawed policy as a response. The Levelling Up White Paper is no exception, reflecting a fundamental misunderstanding of what is being measured and why it matters. This article makes two contributions to the literature on this point. First, it shows theoretically and empirically that there is no necessary correlation between real and nominal labour productivity for either sectors or regions. Secondly, it builds and extends an industry-sector typology to argue that interregional nominal labour productivity differences are best understood within an augmented post-classical power-over-rents framework, where the ability to capture value is critical. We trace the consequences of this for understanding the industrial mix in high nominal productivity regions and the effect on local prices and real wages. While we suggest some potential measures for rebalancing economic activities across regions, we argue that levelling up of living standards is a problem of distribution as much as efficiency. It requires moving beyond the obsession with attempting to directly target misdiagnosed differences in regional labour productivity, and rather engaging with regional development holistically and sustainably.

Exploring Sustainable Innovation Level, Spatial Inequities, and Convergence Trends in China’s Wood Industry

The importance of sustainable innovation in the wood industry is growing, but there is a lack of comprehensive analysis of its evolution, regional differences, and patterns of convergence in China. Based on the panel data of 31 provinces in China from 2011 to 2021, the sustainable innovation index of the wood industry is measured by the projection pursuit method. On this basis, the kernel density estimation method and Dagum Gini coefficient are used to study the dynamic evolution trend, regional differences, and sources of the index, and the convergence characteristics are examined using the coefficient of variation method. The study shows that (1) China’s overall wood industry sustainable innovation index shows a decreasing trend from 2011 to 2021. (2) The differences in the four regions mainly come from inter-regional differences. (3) The index shows significant nonequilibrium characteristics and progressive evolution patterns, and the spatial agglomeration is significant. The magnitude of the index deviation from the average did not decrease over time for the northern and southwestern forest regions. (4) The wood industry sustainable innovation index of the four major forest regions has obviously converged to the same level; under the condition of considering multifactors differentiation, the growth rate of the index of the lower regions is significantly higher than that of the higher regions. The study concludes that current regional imbalances in sustainable innovation in China impede progress and equitable distribution of benefits in the wood industry, and that the impact of regional differences on the β-convergence of sustainable innovation varies according to specific regional characteristics and conditions. These findings provide important theoretical contributions and practical guidance for the development of targeted innovation strategies for the sustainable development of the wood industry, as well as for the promotion of balanced regional development.

Spatial-Temporal Evolution of Carbon Sequestration and Emission Reduction Capacity of Agricultural Cultivation in Different Functional Grain Areas

The capacity of agricultural cultivation for carbon sequestration and emission reduction plays a key role in advancing the green and sustainable development of agriculture and achieving both emission reduction and carbon sink objectives. This study constructs an index for agricultural carbon sequestration and emission reduction capacity using spatial autocorrelation analysis, Theil index, and kernel density estimation, to thoroughly explore spatiotemporal changes and regional differences in carbon sequestration and emission reduction capacity across China and its different grain functional areas. Major findings include: (1) From 2000 to 2020, China’s agricultural carbon sequestration and emission reduction capacity exhibited a fluctuating upward trend, consistent in grain main production areas, while production–consumption and main marketing areas showed a fluctuating decline. (2) From 2000 to 2020, positive spatial correlation in carbon sequestration and emission reduction capacity increased at both national and regional levels, particularly in the main production and production–consumption areas, while the main consumption areas demonstrated a trend toward negative correlation. (3) The Theil index of China’s agricultural carbon sequestration and emission reduction capacity showed an overall fluctuating increase, with interregional differences contributing over 54%, significantly surpassing intra-regional contributions. Moreover, the main producing regions are the main source of the overall national variance. (4) Kernel density analysis highlights that there are significant differences in the distribution and evolution of carbon sequestration and emission reduction capacity among different grain functional areas, and the overall development is unbalanced. Therefore, each region needs to formulate tailored measures to improve agricultural carbon sequestration efficiency, promote regional sustainable development, and achieve carbon reduction goals.

Distinguishing West Florida gag (Mycteroperca microlepis) nurseries with otolith stable isotopes

Numerous reef fishes utilize estuarine nurseries following spawning in marine habitats. Nursery origin affects their life cycle space use, and otolith chemistry can be an effective tool for tracking movement over this lifetime scale. Gag Mycteroperca microlepis occupy West Florida (WF), USA, estuaries as juveniles and have a spatially complex life cycle with ontogenetic habitat shifts and offshore spawning. We tested whether age-0 gag otolith stable isotope values distinguished WF nurseries and assessed isotopic variability at multiple temporal and spatial scales. Northern and southern juveniles had distinct otolith carbon (δ13C) and oxygen (δ18O) stable isotope values despite evidence of interannual variability, and both year-specific and combined year models had high (&gt;80%) classification accuracies. We investigated long-term stability of otolith δ13C and δ18O by comparing age-0 gag collected during 2009-2012 and 2020-2021. The δ18O values of southern age-0 otoliths decreased over time, thus decreasing inter-regional differences and the classification accuracy of the combined year model (79%). Concomitantly, age-0 otoliths became depleted in 13C across regions, which may result from increased limestone dissolution (i.e. dekarstification) in the Floridan aquifer. We identified greater decadal variability in region-specific stable isotope values than has been documented in previous studies, indicating that a cohort-specific approach will likely be required to estimate gag lifetime movement.

The spatio-temporal characteristics and dynamic evolution of coupling and coordinated development of innovation factor allocation and green economy in China

IntroductionMeasuring the coupling coordination degree between the innovation factor allocation system and the green economy development system, and deeply exploring the changing trends in the coupling coordination between innovation factors allocation, including their subsystems, and green economy development, are essential prerequisites for achieving a high degree of coupling coordination between the two systems.MethodsThis paper, based on panel data from 30 provincial regions in China from 2013 to 2022, measures the coupling coordination degree between innovation factor allocation and green economy development, including their subsystems, and explores the spatial differentiation characteristics of this coupling coordination across the provinces in China and its three major regions. First, an evaluation index system for the innovation factor allocation system and the green economy development system is constructed from both input and output perspectives. The entropy weighted TOPSIS method and the coupling coordination degree model are then employed to explore the temporal characteristics of the coupling coordination between innovation factor allocation and green economy development. Second, Dagum's Gini coefficient is used to reveal the directional distribution of coupling coordination and the sources of spatial disparities. Third, kernel density estimation and spatial Markov chain methods are applied to uncover the dynamic evolution of this coupling coordination.Results and discussionThe study finds that the overall coupling coordination degree between innovation factor allocation and green economy development in China is relatively low, but it exhibits a continuous upward trend. From the perspective of regional disparities, the coupling level between innovation factor allocation and green economy development across Chinese provinces shows an imbalanced spatial distribution, characterized by higher levels in the east and lower levels in the west, with spatial disparities tending to widen. Inter-regional differences are the primary source of these spatial disparities, followed by intra-regional differences. While internal disparities within Eastern China are narrowing, they are expanding within the Central and Western China. The development processes in these regions are often influenced by neighboring spatial spillover effects. Finally, recommendations are proposed to enhance the coupling coordination degree between innovation factor allocation and green economy development in China.

Heterogeneity of population exposure to particulate matter pollution and its socioeconomic driving mechanism in Shaanxi Province, China

The rapid pace of economic and social development has led to a surge of particulate matter (PM) pollution incidents, which is detrimental to human health. Air quality in China has improved in recent years, but differences in PM exposure remain due to spatial heterogeneity in pollution and population. The identification of socioeconomic factors associated with PM pollution has attracted widespread attention. Current research predominantly targets cities, overlooking regional and county scale disparities. An analytical framework is established to evaluate the spatial heterogeneity in PM exposure and to identify the socioeconomic factors contributing to its pollution. The results revealed that: (1) the Theil index increased from 0.06 to 0.12, indicating a gradual increase in the inequality of PM exposure in Shaanxi Province. The differences within the Guanzhong Plain are obvious and the interregional differences substantially outweigh the intraregional variations. (2) Energy transition is pivotal in curbing air pollution in a region and economic growth consistently fuels particulate emissions. (3) For effective pollution mitigation, further emphasis on vegetation preservation and environmental inputs is imperative. The findings of this research provide decision support for optimizing air pollution control measures at the county scale.

Analysis of Regional Differences and Convergence of Equalization Level of Marine Public Services in China’s Coastal Areas

The equalization of marine public services is an effective way to achieve harmonious coexistence of the sea. In this paper, a variable fuzzy recognition model is used to measure the equalization level of marine public services in 11 provinces and cities in China’s coastal areas from 2006 to 2019. The Dagum Gini coefficient, kernel density estimation model, and convergence model are used to study their regional differences, distribution dynamics, and convergence characteristics. The results show that the equalization level of marine public services in China’s coastal areas increased year by year from 2006 to 2019. In terms of spatial distribution, the equalization level of marine public services in coastal areas presents an unbalanced distribution pattern. The overall regional differences in the equalization level of marine public services in China’s coastal areas have narrowed, and the inter-regional differences are the main reasons for the overall differences. The absolute difference in the equalization level of marine public services in China’s coastal areas shows an expanding trend. The equalization level of marine public services in China’s coastal areas has α convergence and β convergence.

Factors influencing regional disparities in online shopping

Online shopping has grown exponentially in the Russian Federation (hereinafter referred to as RF, Russia) in recent years. This growth has significantly accelerated during the COVID-19 pandemic. However, data shows that there are inter-regional disparities in the use of online shopping. This includes intergenerational and rural-urban disparities. This study investigates the factors responsible for inter-regional differences in the development of online shopping in Russia. The author has identified 5 main factors that can influence the development: internet infrastructure (measured by regional expenses for the introduction of digital technologies and the number of connected mobile subscribers), economic wealth (measured by gross regional product), standard of living (measured by the population income), rate of poverty, and the region’s population. The research uses data of the Federal State Statistics Service and Association of Internet Trade Companies to analyse 85 regions in the RF. A multi-level regression analysis has enabled examination of the 5 factors and the contextual influence of 8 federal districts of Russia in level 2. The results show that internet infrastructure, economic wealth, population size, and the 8 federal districts has influenced the development of online shopping in the RF, but standard of living is not statistically significant. The author recommends that policymakers pay attention to these underlying factors.

Debatable issues of coding chronic forms of ischemic heart disease as the primary cause of death

Aim: to examine the opinions of healthcare professionals on using codes from the ICD-10 group chronic ischemic heart disease (CIHD) (I25.0, I25.1, I25.8, I25.9) as the primary cause of death and discuss the results in the context of comparing with regional variability of standardized mortality ratio (SMR) from different forms of CIHD.Materials and methods. A one-stage study was conducted. This article describes the results of a survey of 366 medical workers (cardiologists, internists/general practitioners/family doctors, pathologists, public health and healthcare specialists, paramedics) from 47 subjects of the Russian Federation who fill out a medical death certificate (MDS) more often than 2–3 times a month. In addition, SMR from coronary heart disease were determined based on a brief nomenclature of causes of death of Rosstat in 82 regions of the Russian Federation for 2022.Results. 80.1 % of respondents expressed the opinion that I25.0, I25.1, I25.8, I25.9 are necessary for coding causes of death, but half of those surveyed do not see any differences in them. At the same time, respondents admit the possibility of using these CIHD codes as the primary cause of death without ante-mortem and pathological verification. The relatively small coefficient of variation of SMR overall from CIHD (34.19 per 100,000 population) is associated with high values from its individual forms: the coefficient of variation of average regional SMRs ranged from 62 % for code I25.1 to 174 % for code I25.0.Conclusions. The results of this study indicate a variable attitude of specialists filling out MSD towards choosing ICD-10 codes from the CIHD group, leading to significant interregional differences in CIHD mortality rates. It is necessary to develop unified recommendations describing situations in which codes from the CIHD group can be considered the primary (main) cause of death.

Path to sustainable development: The effect of China's innovative industrial clusters pilot policy on prefecture-level cities' green total factor productivity

To enhance industrial production efficiency and promote sustainable social development, the Chinese Ministry of Science and Technology announced the innovative industrial clusters pilot (IICP) policy and named three batches of pilot cities in 2013, 2014, and 2017. Whether this significant industrial policy has promoted green total factor productivity (GTFP) is a meaningful but under investigated question in the literature. This study thus explores the above question using a multiperiod spatial difference-in-differences approach and panel data from 273 prefecture-level cities covering 2007–2021. The super slacks based measure and Dagum Gini coefficient are first utilized to assess city-level GTFP and evaluate its spatiotemporal evolutionary features. The intraregional and interregional differences of GTFP reveal expanding trends, with contribution rates to the overall difference above 30%. Benchmark and robustness tests demonstrate promotional direct and spatial spillover effects of the IICP on GTFP. We also employ several additional tests for deeper exploration, determining that a) the direct effect of IICP gradually increases over time, with an evident a time-lag effect, and the positive spatial spillover effect has fluctuated since the policy was enforced; b) the heterogeneity effects of the IICP on GTFP was detected; c) green scientific and technological innovation is an important mechanism of how IICP implementation affects cities' GTFP; and d) the promotional effect of the IICP on GTFP significantly increases when industrial structure upgrading exceeds certain threshold values. The empirical findings of this study not only provide theoretical and practical recommendations for Chinese policymakers to enhance the IICP's policy effect, but also offer suggestions for other emerging markets to develop similar policies for sustainable social development.

Forecasting Carbon Dioxide Emission Regional Difference in China by Damping Fractional Grey Model

The emission of carbon dioxide is the main reason for many global warming problems. Although China has made tremendous efforts to reduce carbon emission, the space–time dynamics of the carbon emission trend is still imbalanced. To forecast CDED in China, the Dagum Gini coefficient was applied to measure regional CDED. Then, a grey correlation model was used to select potential influence factors and a wrapping method for selecting the optimal subset. DGMC is proposed to forecast CDED. The research results showed that the DGMC generalization performance is significantly superior to other models. The MAPE of DGMC in six cases are 1.18%, 1.11%, 0.66%, 1.13%, 1.27% and 0.51%, respectively. The RMSPEPR of DGMC in six cases are 1.08%, 1.21%, 0.97%, 1.36%, 1.41% and 0.57%, respectively. The RMSPEPO of DGMC in six cases are 1.29%, 0.69%, 0.02%, 0.58%, 0.78% and 0.32%, respectively. In future trends, the eastern carbon dioxide emission intraregional differences will decrease. Additionally, the intraregional differences in western and middle-region carbon dioxide emissions will expand. Interregional carbon emission difference will display a narrowing trend. Compared with the traditional grey model and ANN model, integrating the influence factor information significantly improved forecasting accuracy. The proposed model will present better balanced historical information and accurately forecast future trends. Finally, policy recommendations are proposed based on the research results.

Evolving trends, regional differences, determinants, and disease sources of provincial-level health inequalities in china 1990–2019: a temporal convergence and novel triple decomposition analysis

BackgroundPromoting health equity has been a worldwide goal, but serious challenges remain globally and within China. Multiple decomposition of the sources and determinants of health inequalities has significant implications for narrowing health inequalities and improve health equity.MethodsLife expectancy (LE), healthy life expectancy (HALE), age-standardized mortality rate (ASMR), and age-standardized disability-adjusted life-year (DALY) rates in 31 provinces of mainland China were selected as health status indicators, obtained from the Global Burden of Disease (GBD) database. Temporal convergence analysis was used to test the evolving trends of health status. Dagum’s Gini coefficient decomposition was used to decompose the overall Gini coefficient based on intraregional and interregional differences. Oaxaca-Blinder decomposition was used to calculate contributions of determinants to interregional differences. The factor-decomposed Gini coefficient was used to analyze the absolute and marginal contribution of each component to overall Gini coefficients.ResultsFrom 1990-2019, China witnessed notable improvements in health status measured by LE, HALE, ASMR and age-standardized DALY rates.Nevertheless, the three regions (East, Central and West) exhibited significant inter-regional differences in health status, with the differences between the East and West being the largest. The adjusted short-term conditional β-convergence model indicated that the inter-provincial differences in LE, HALE, ASMR, and age-standardized DALY rates significantly converged at annual rates of 0.31%, 0.35%, 0.19%, and 0.28% over 30 years. The overall Gini coefficients of LE, HALE, and age-standardized DALY rates decreased, while the ASMR exhibited an opposite trend. Inter-regional and intra-regional differences accounted for >70% and<30% of overall Gini coefficients, respectively. Attribution analysis showed that socioeconomic determinants explained 85.77% to 91.93% of the eastern-western differences between 2010-2019, followed by health system determinants explaining 7.79% to 11.61%. The source-analysis of Gini coefficients of ASMR and age-standardized DALY rates revealed that noncommunicable diseases (NCDs) made the largest and increasing absolute contribution, while communicable, maternal, neonatal, and nutritional diseases (CMNNDs) had a diminishing and lower impact. However, NCDs exerted a negative marginal effect on the Gini coefficient, whereas CMNNDs exhibited a positive marginal effect, indicating that controlling CMNNDs may be more effective in reducing health inequities.ConclusionsRegional differences are a major source of health inequities in China. Prioritizing prevention and control of CMNNDs, rather than NCDs, may yield more pronounced impacts on reducing health inequalities from the perspective of marginal effect, although NCDs remain the largest absolute contributor to health inequalities.

Spatio-temporal Situation, Regional Differences, and Dynamic Evolution of the Distribution of Ecological Compensation in the Yellow River Basin

In the context of regional coordinated development and modernization of ecological and environmental governance capacity, the spatial collaborative governance of transboundary river basins has received extensive attention, but the ecological compensation of river basins is faced with the intertwined relationship of rights and responsibilities, and the horizontal ecological compensation mechanism has not yet been perfected. Based on the emergy ecological footprint model, the ecological compensation amount of 90 cities in the Yellow River Basin in 2007-2021 was measured, and the spatiotemporal pattern, regional differences, and dynamic evolution characteristics of distribution were explored by combining exploratory spatial data analysis, Dagum Gini coefficient, kernel density estimation, and spatial Markov chain analysis. The results showed that： ① The spatiotemporal pattern of ecological compensation in the Yellow River Basin was different, the ecological compensation amount decreased slightly in the fluctuation and increased from the northwest to southeast gradient in general, and the high-value areas were concentrated in the areas with a superior ecological background or developed economy, and some upstream cities had given up many development opportunities to maintain the ecological security of the Yellow River Basin, however, failed to obtain reasonable ecological compensation. ② A significant positive spatial agglomeration phenomenon was observed in ecological compensation and the overall spatial distribution trend was "cold in the north and hot in the south." The number of low-payment areas and low-compensation areas gradually decreased, showing a gradually shrinking agglomeration layout from the periphery to the center, whereas the number of high-payment areas and high-compensation areas continued to increase and formed a spatial evolution characteristic of the coexistence of scattered distribution and group distribution. ③ The overall regional differences in ecological compensation expanded. The over-variation density was the main source of the overall differences, and the focus on alleviating the intra-regional and inter-regional differences was located in the downstream areas. ④ A slight multi-level differentiation phenomenon was present in ecological compensation. The influence of different neighbors on the horizontal transfer of ecological compensation was quite different. This spatial spillover effect easily formed a "space club convergence" phenomenon within a certain geographical spatial range, but with the expansion of time, the probability of maintaining the original level of ecological compensation in each city decreased, and mobility gradually increased. Therefore, increasing the investment in ecological compensation in different fields, strengthening the coordinated development between regions, and giving full play to the spatial spillover effect are important ways to solve the current spatial imbalance of ecological compensation in the Yellow River Basin.