Indicators In China Research Articles

Research on the development relationship between safety production indicators and economic and social indicators in China

In order to study the relationship between China's safety production indicators and economic and social indicators, the development trend of indicator data in the past 20 years was statistically analyzed, and qualitative and quantitative research was conducted using grey relational analysis and multiple linear regression analysis methods. In the past two decades, there has been a significant improvement in the number of deaths, work-related injuries, and occupational patients in China's safety production, and the country's three categories of 14 economic and social indicators have achieved rapid development. Using the grey relation analysis method, the grey correlation degree between the number of deaths, work-related injuries, and occupational patients in China over the past twenty years and 14 economic and social indicators was obtained. The ranking of economic and social indicators that affect the number of deaths, work-related injuries, and occupational patients varies greatly. A multiple linear regression model was established for the number of deaths, work-related injuries, occupational diseases, and 14 economic and social indicators. The rationality of the model was verified from four aspects: R2, F-value, P-value, and deviation between actual and fitted values. Provide guidance for the development of safety production indicators and economic and social indicators in China through research.

Challenges in Chinese Path to Modernization of Agriculture and Rural Areas: A Comparison With the U.S.

This study establishes, for the first time, an index system for comparing agricultural and rural modernization in China and the United States, which aims to identify key challenges in China’s agricultural and rural development by contrasting indicators from both countries. Overall, China’s current level of agriculture and rural modernization is akin to that of the United States in the 1960s and 1970s, with an approximate time lag of 60 years. China exhibits the largest gap with the U.S. in agricultural modernization and the smallest gap in rural modernization. Three key indicators in China that require improvement compared to the United States are the disposable income of rural residents, the population size supported by each agricultural laborer, and the share of agricultural employment. This research lays down a theoretical foundation and practical strategies for advancing the Chinese path to agriculture and modernization in rural areas.

A Randomized Controlled Trial Comparing Automated Peritoneal Dialysis and Hemodialysis for Urgent-Start Dialysis in ESRD

Peritoneal dialysis (PD) shows promise for urgent-start dialysis in end-stage renal disease (ESRD), with automated PD (APD) having advantages. However, there is limited multicenter randomized controlled trial (RCT) evidence comparing APD with temporary hemodialysis (HD) for this indication in China. This multicenter RCT enrolled 116 patients with ESRD requiring urgent dialysis from 11 hospitals, randomized to APD or HD. Patients underwent a 2-week treatment with APD or HD via a temporary central venous catheter (CVC), followed by a maintenance PD. Outcomes were assessed over 12 months during 8 visits. The primary outcome was dialysis-related complications. The 1-year incidence of dialysis-related complications was significantly lower in the APD group than in the HD group (25.9% vs. 56.9%, P= 0.001). No significant differences were found between the groups in terms of PD catheter survival rates (P= 0.388), peritonitis-free survival rates (P= 0.335), and patient survival rates (P= 0.329). In terms of health economics, the total direct medical cost of the initial hospitalization for patients with ESRD was significantly lower in the APD group (27,008.39 CNY) than in the HD group (42,597.54 CNY) (P= 0.001), whereas the duration of the first hospital stay showed no significant difference (P= 0.424). For patients with ESRD needing urgent initiation of dialysis, APD was associated with a lower incidence of dialysis-related complications and lower initial hospitalization costs compared with HD, with no significant differences in PD catheter survival rate, peritonitis-free survival rates, or patient survival rates. These findings can guide clinical decision-making for the optimal dialysis modality for patients requiring urgent dialysis initiation.

Research on Quantile Regression Method for Longitudinal Interval-Censored Data Based on Bayesian Double Penalty

The increasing prominence of the problem of censored data in various fields has made studying how to perform parameter estimation and variable selection in censored mixed-effects models one of the hotspots of current research. In this paper, considering the situation that the response variable is restricted by the bilateral limit, a double-penalty Bayesian Tobit quantile regression model was constructed to carry out parameter estimation and variable selection in the interval-censored mixed-effects model, and at the same time, the fixed-effects and random effects coefficients are compressed in Tobit’s mixed-effects model, so as to reduce the estimation error of the model at the same time as the variable selection of the model is carried out. The posterior distribution of each unknown parameter was derived using the conditional Laplace prior and the mixed truncated normal distribution of interval-censored data, and then the Gibbs sampling algorithm for unknown parameter estimation was constructed. Through Monte Carlo simulation, it was found that the new method is more advantageous than the classical method in terms of variable selection and parameter estimation accuracy in various situations, such as different model sparsity, different data censoring ratios and different random error distributions, and the model is able to realize automatic variable selection. Finally, the new method is used to analyze the correlation between the crime rate and various economic indicators in China.

Influence Path Analysis of Coordination between Material and Spiritual Civilization Based on the VAR Model

This paper quantitatively analyzes the degree of coordination between China's material civilization and spiritual civilization by establishing an entropy method-coupled coordination degree model. Based on the quantitative results, indicators of China's 1987-2021 tax policy, monetary policy, and open economy policy are introduced to construct a vector autoregressive model to deeply analyze the dynamic relationship between the level of coordination and these influencing factors from multiple perspectives. It is found that maintaining a robust monetary policy, optimizing the structure of foreign trade and exports, and optimizing the structure of taxation are conducive to further enhancing the level of the degree of harmonization between China's material and spiritual civilization, and promoting the high-quality development of China's modernization.

Cancer drug indication approvals in China and the United States: a comparison of approval times and clinical benefit, 2001–2020

Perceived delays in cancer drug approvals have been a major concern for policymakers in China. Policies have been implemented to accelerate the launch of new cancer drugs and indications. This study aimed to assess similarities and differences between China and the United States in the approvals, timing, and clinical benefit evidence of cancer drug indications between 2001 and2020. This study retrospectively identified all cancer drugs and indications approved in both China and the United States from January 1st, 2001 to December 31, 2020, and described differences in approval times as well as in submission and review times. Information on the availability of overall survival benefit evidence by December 31, 2020, was collected. Univariate and multiple logistic regression analyses were used to assess whether evidence of benefit and other factors affected the propensity and timing of approvals of cancer drug indications in China. Between 2001 and 2020, 229 indications corresponding to 145 cancer drugs approved in the United States were identified. Of those, 80 indications (34.9%) were also approved in China by the end of 2020. Cancer drug indications were approved in China at a median of 1273.5 days after approval in the United States. The median submission and review time differences for cancer drug indications in China were 1198.0 days and 180.0 days respectively. Submission time differences accounted for most of the approval time differences (p<0.001). Indications supported by overall survival benefit evidence had shorter median review time differences (145.0 days) than those without such evidence (235.0 days, p=0.008). Indications with overall survival benefit evidence were 3.94 times more likely to be approved in China compared to those without such evidence (p=0.001), controlling for approval year, cancer type, and the prevalence of cancer by site. FDA-approved cancer drug indications demonstrating a survival benefit were more likely to receive approvals in China with shorter regulatory review times compared to indications without such evidence. Given that manufacturer submission times were the main driver of cancer drug approval times in China, factors influencing submission timing should be explored. No funding.

Analysis on Housing Price Using Macroeconomic Indicators in China

In China, one of the most important stimulations in economic development has belonged to real estate market after the reform and opening, and it also contributes a lot to the financial market. However, there are many arguments nowadays, believing that Chinese real estate market is on the process of bubbles, almost about to burst. This study aims at discussing the influences of some macroeconomic indicators on price of commercial housing in China between 2013 and 2022. GDP, interest rate, inflation rate and money supply are chosen to be the independent variables. Using correlation and regression models, the results show that the indicators are correlated with each other. The analysis shows that there is a strong positive correlation between China’s GDP and commercial housing price which is the key for future economic development. Inflation positively correlates with the commercial housing price and a strong negative correlation is found between commercial housing price and interest rate and money supply. This research suggests that government should regulate and control macroeconomic indicators to protect the development in real estate market.

Perceiving progress and imbalance of environmental SDG indicators in China using big data

ABSTRACT In the past decades, the environment has changed drastically in China with rapid economic development. Lack of data, especially data with spatiotemporal information, has however hindered evaluating progress of environmental indicators in the global Sustainable Development Goal (SDG) framework. Here, we evaluate and explore geospatial information of 20 environmental SDG indicators from six SDGs in China from 2010 to 2020 using big data. We show China has improved rapidly in most of the 20 indicators, except for indicator 13.2.2 (CO2 emission). 63.5% of China’s land mass showed improved states for the SDG indicators. By 2020, four of the indicators were found to have achieved their 2030 targets. It is predicted from the existing data that 10 of the 20 indicators can achieve their targets smoothly by 2030, but two indicators will lag behind. We quantitatively show China’s progress towards the environmental SDG indicators, and put forward timelines and suggestions for policy makers.

Reflections on the Legal Protection System of Geographical Indications in China

Reflections on the Legal Protection System of Geographical Indications in China

A Multisample Path Analysis Including a Novel Psychological Indicator, Attitude Toward Life, After the First Wave of COVID-19.

During the COVID-19 outbreak, China applied a unique volunteerism system in which nurses and physicians traveled to the epicenter to care for patients. During the same period, another group, nurse and physician nonvolunteers, stayed at their home hospitals outside of the epicenter and cared for patients without COVID-19. Yet only one Chinese study examined psychological responses comparing these groups. To explore whether relationships among compassion satisfaction, general health, attitude toward life, satisfaction with life, perceived stress, and posttraumatic stress disorder (PTSD) symptomatology differ between volunteers and nonvolunteers. Attitude toward life is examined for the first time in COVID-19 research. A cross-sectional study was conducted (259 nurse and physician volunteers, 330 nurse and physician nonvolunteers). Online survey data were analyzed using multisample path analysis. There was no significant difference between volunteer and nonvolunteer models. In the volunteer model, paths significantly related to PTSD symptomatology included compassion satisfaction (total effect, β = -0.12), general health (total effect, β = -0.09), attitude toward life (direct effect, β = -0.30; total effect, β = -0.30), and perceived stress (direct effect, β = 0.30; total effect, β = 0.30), and in nonvolunteers included general health (direct effect, β = -0.11; total effect, β = -0.11) and attitude toward life (direct effect, β = -0.47; total effect, β = -0.47). No significant difference between models means both groups could benefit from psychological intervention. Within each model, significant paths were identified. For volunteers, counselors might focus on compassion satisfaction and perceived stress and, for both volunteers and nonvolunteers, on health and attitude toward life. Delivering counseling based on key indicators in China may help prevent or mitigate PTSD. Globally, researchers could identify factors to target and determine to whom long-term counseling might be directed. Findings about attitude toward life lay the groundwork for future research.

Evaluation and Discussion on the Sustainable Development of Higher Education

Though the higher education system has great significance to a nation, compelling model to evaluate the higher education system is currently lacking. Due to changes in the social environment, such as the epidemic, countries’ requirements for the health and sustainability of the higher education system are gradually increasing. To assess this system, a thorough evaluation model is established by k-means cluster analysis and TOPSIS analysis. 15 indicators in 8 countries from the Global Competitiveness Report (2009-2019) are selected. In addition, we choose China to do the further analysis. Calculation results of factor analysis show that there are 5 indicators with greater influence among 15 indicators. It makes sense to increase the weights of these five indicators in China for more sustainable development.

The Impact of Population Aging on China's Macroeconomy

China's aging population is a growing concern and the country will become a super-aged society by 2050. Aging has a number of important implications for various macroeconomic indicators in China. From a labor market perspective, aging will have a negative impact on real labor supply and labor productivity in the Chinese market. And the impact on human capital will depend on the relative magnitude of its shrinking effect on educational human capital and its boosting effect on healthy human capital. From an investment demand perspective, an aging population will dampen investment demand in the Chinese market by affecting investment returns and social investment preferences. From a balance of payments perspective, aging may have a negative impact on both China's current account and international capital account, leading to a double deficit in the balance of payments. From a fiscal balance perspective, aging will increase the Chinese government's fiscal burden while decreasing its fiscal revenue, thus increasing the fiscal pressure on the Chinese government.

The Impact of the COVID-19 Pandemic on Major Air Quality Indicators in China and the United States

After the COVID-19 pandemic, some countries have restricted and blocked economic activities, which affects industrial production to a certain extent. This may lead to improved air quality. Different countries worldwide adopt different restrictions during the pandemic, which may also affect air quality at different levels. To verify the degree of environmental impact, the article selects the two representative economies in the world China and the United States. These two countries choose policies with varying degrees of strictness, which may cause different impacts on production and air quality. This article uses regression methods to analyze the leading environmental and industrial production indicators before and after the pandemic and determine the impact of changes in industrial production during the epidemic on the air quality during the epidemic, according to the regression analysis, the quality of the environment has improved due to the control measures on economic activities. Moreover, after the main control measures have ended, economic activities and environmental quality have quickly returned to their original levels.

Do the effects of aggregate and disaggregate energy consumption on different environmental quality indicators change in the transition to sustainable development? Evidence from wavelet coherence analysis.

In the 2030 Agenda for Sustainable Development, adopted by the United Nations (UN) member states in 2015, half of the target period has been exceeded. However, China, whose energy consumption relies heavily on fossil resources, remains at the top of the list of global polluters. Therefore, investigating the environmental impacts of energy types is essential to China's path towards Sustainable Development Goals (SDG)-7 and SDG-13. Based on this motivation, the paper offers new insights into the energy-environment literature for China with wavelet coherence analysis (WCA). This approach can investigate the relationship between variables in a periodic manner based on the frequency behavior of the models. The paper separately analyzes the effects of primary energy consumption (PEC), fossil energy consumption (FEC), renewable energy consumption (REC), nuclear energy consumption (NEC), GDP, and population (POP) on three different environmental indicators in China. Using two environmental pollution indicators (carbon emission (CO2) and ecological footprint (EF)) and one environmental quality indicator (load capacity factor (LCF)), the paper allows for comparison and robustness checks on the environmental impacts of energy indicators. Empirical findings reveal the following: (i) Except for REC and POP in the CO2 model, the variables in all three models largely move together during the period under observation; (ii) variables other than POP have consistent coefficient signs; (iii) PEC, FEC, NEC, and GDP increase CO2 and EF while decreasing LCF; (iv) the effect of NEC on LCF is more obvious until 2000; (v) unlike the others, REC affects CO2 and EF negatively and LCF positively; (vi) there is bidirectional causality between PEC and environmental indicators but not for REC; (vii) the causality relations of other variables with environmental indicators differ in terms of model, time, and direction of causality. In light of the findings, the paper highlights that only the REC improves environmental quality in China. Other energy indicators contribute to environmental degradation. China, whose ecological deficit has increased dramatically in recent years, urgently needs to reduce its dependence on fossil energy sources by accelerating investments in REC. Governments should also review nuclear energy policies, which are expected to help achieve carbon neutrality.

Developing indicators for promoting provincial-level ecological economics in China

The development of the eco-economy has become an important way to promote sustainable development and address climate change worldwide. Implementing eco-economic developmental policy globally or locally requires establishing precise indicators. Currently, there are many studies on eco-economy indicators at the academic level, but the eco-economy indicators researched at the academic level are difficult to be implemented and applied by local governments in China, and there is a knowledge gap between the political sector and the academic sector in the process of cooperation. This mainly stems from the lack of whole-process research and analysis that combines government practice and academic research. We attempt to analyze the differences in the understanding of eco-economic indicators between academics and government decision-makers through the study of the establishment process of China's local eco-economic indicator system. We try to find out the reasons for the knowledge gap between academics and government decision-makers, and to build a knowledge bridge between government practice and academic research. At the same time, China, as the largest developing country and an emerging country in the construction of ecological civilization, is worth studying and learning from its experience in the construction of eco-economic indicators. Therefore, we systematically study the connotation of China's eco-economy and the development process of the indicators. And we combine with the practical experience, describe the method and specific process of constructing eco-economy indicators at the provincial scale of the Chinese government. Meanwhile, we put forward the limitations of the construction of the eco-economy indicator system in Liaoning Province. In addition, we analyze in detail the characteristics and attributes of the ecological economy indicators in Liaoning Province, as well as the relationship of these indicators to the implementation of national strategies and to the SDGs. The discipline contributions and scientific and technological concerns of the indicator system's creation are reviewed, and additional improvement ideas are presented. It is expected that the practice of eco-economic indicators in China will further promote eco-economy development and provide methodological reference for countries to measure the level of eco-economic development.

Does environmental regulation improve energy transition performance in China?

This study examines the relationship between environmental regulation and energy transition performance in China. With the pressing need to mitigate climate change and reduce environmental impact, understanding the effectiveness of environmental regulations in facilitating the transition to cleaner energy sources is of paramount importance. Using comprehensive data on environmental regulations and energy transition indicators in China, this research investigates whether stringent environmental regulations positively influence the country's energy transition performance. The study employs statistical analysis techniques to analyze the correlation between environmental regulation stringency and various energy transition metrics, including renewable energy capacity, carbon intensity, and energy efficiency. The findings provide valuable insights into the role of environmental regulation in shaping China's energy transition landscape. Understanding this relationship can guide policymakers and stakeholders in formulating effective strategies and policies to accelerate the transition towards a sustainable and low-carbon energy system in China and beyond.

Risk analysis of cruise ship supply chain based on the set pair analysis-Markov chain model

The cruise industry, which serves as a prominent exemplar of globalized business, is characterized by unique features that render its supply chain operations highly susceptible to various risk factors, thereby giving rise to significant consequences. Evaluating the risks associated with major disruptive events and enhancing the robustness of the cruise supply chain have become crucial issues of concern for various stakeholders. This study first develops an indicator evaluation system for assessing the risks of China's cruise supply chain, drawing upon relevant literature and expert interview opinions. Secondly, set pair analysis is utilized to identify the scores and trends of risk indicators in China's cruise supply chain. Thirdly, the Set pair analysis-Markov chain model is employed to forecast the future risk status of China's cruise supply chain system, and the influence of different weights on the prediction results is discussed. Finally, the risk evolution network of China's cruise supply chain is constructed to identify common risk consequences and visualize the evolution path of risk events, with the aim of providing reference for the formulation of prevention and control measures. The findings of this article have important consequences for improving risk mitigation strategies and enhancing the resilience of the cruise supply chain.

Immediate and long-term outcomes after treat-all among people living with HIV in China: an interrupted time series analysis

BackgroundIn 2003, China implemented free antiretroviral therapy (ART) for people living with HIV (PLHIV), establishing an eligibility threshold of CD4 < 200 cells/μl. Subsequently, the entry criteria were revised in 2012 (eligibility threshold: CD4 ≤ 350 cells/μl), 2014 (CD4 ≤ 500 cells/μl), and 2016 (treat-all). However, the impact of treat-all policy on HIV care and treatment indicators in China is unknown. We aimed to elucidate the immediate and long-term impact of the implementation of treat-all policy in China.MethodsAnonymized programmatic data on ART initiation and collection in PLHIV who newly started ART were retrieved between 1 January 2015 and 31 December 2019, from two provincial and municipal Centers for Disease Control and Prevention and ten major infectious disease hospitals specialized in HIV care in China. We used Poisson and quasi-Poisson segmented regression models to estimate the immediate and long-term impact of treat-all on three key indicators: monthly proportion of 30-day ART initiation, mean CD4 counts (cells/μl) at ART initiation, and mean estimated time from infection to diagnosis (year). We built separate models according to gender, age, route of transmission and region.ResultsMonthly data on ART initiation and collection were available for 75,516 individuals [gender: 83.8% males; age: median 39 years, interquartile range (IQR): 28–53; region: 18.5% Northern China, 10.9% Northeastern China, 17.5% Southern China, 49.2% Southwestern China]. In the first month of treat-all, compared with the contemporaneous counterfactual, there was a significant increase in proportion of 30-day ART initiation [+ 12.6%, incidence rate ratio (IRR) = 1.126, 95% CI: 1.033–1.229; P = 0.007] and mean estimated time from infection to diagnosis (+ 7.0%, IRR = 1.070, 95% CI: 1.021–1.120; P = 0.004), while there was no significant change in mean CD4 at ART initiation (IRR = 0.990, 95% CI: 0.956–1.026; P = 0.585). By December 2019, the three outcomes were not significantly different from expected levels. In the stratified analysis, compared with the contemporaneous counterfactual, mean CD4 at ART initiation showed significant increases in Northern China (+ 3.3%, IRR = 1.033, 95% CI: 1.001–1.065; P = 0.041) and Northeastern China (+ 8.0%, IRR = 1.080, 95% CI: 1.003–1.164; P = 0.042) in the first month of treat-all; mean estimated time from infection to diagnosis showed significant increases in male (+ 5.6%, IRR = 1.056, 95% CI: 1.010–1.104; P = 0.016), female (+ 14.8%, IRR = 1.148, 95% CI: 1.062–1.240; P < 0.001), aged 26–35 (+ 5.3%, IRR = 1.053, 95% CI: 1.001–1.109; P = 0.048) and > 50 (+ 7.8%, IRR = 1.078, 95% CI: 1.000–1.161; P = 0.046), heterosexual transmission (+ 12.4%, IRR = 1.124, 95% CI: 1.042–1.213; P = 0.002) and Southwestern China (+ 12.9%, IRR = 1.129, 95% CI: 1.055–1.208; P < 0.001) in the first month of treat-all.ConclusionsThe implementation of treat-all policy in China was associated with a positive effect on HIV care and treatment outcomes. To advance the work of rapid ART, efforts should be made to streamline the testing and ART initiation process, provide comprehensive support services, and address the issue of uneven distribution of medical resources.

Developing online medical service quality indicators in China from the perspective of online-offline integration: a modified Delphi-AHP study.

Online medical services are developing rapidly worldwide, and policies encourage the integrated development of online and offline services in China. However, there is a lack of comprehensive and systematic quality indicators for online medical services to ensure patients' safety. This study aimed to construct a set of quality indicators from the perspective of online-offline integration, to provide a basis for the evaluation and management of online medical service quality. Based on the literature review, we included 53 potential indicators. In two rounds of consultations, we invited 21 and 19 experts, respectively, to rate the importance and feasibility of each indicator via email. We used the modified Delphi method and analytic hierarchy process to determine the final indicators and their weights. We used experts' positive coefficient, authority coefficient, and opinion coordination degree to test the reliability and validity of experts. After two rounds of Delphi consultation, the experts' positive coefficients were 90.48% and 89.47%, and the authoritative coefficients were both over 0.7. An online medical service quality index system for public hospitals in China was developed with 4 primary indicators, 13 secondary indicators, and 34 tertiary indicators. Among the primary indicators, the weights of structure, process, outcome, and integration quality were 0.22, 0.26, 0.34, and 0.18, respectively. We constructed the first set of online medical service quality indicators for public hospitals in China from the perspective of online-offline integration. It could be applied as a standardized and meaningful guide for online medical service evaluation and quality development.

Predictive value of atherogenic index of plasma and atherogenic index of plasma combined with low-density lipoprotein cholesterol for the risk of acute myocardial infarction.

Acute myocardial infarction (AMI) is a prevalent medical condition associated with significant morbidity and mortality rates. The principal underlying factor leading to myocardial infarction is atherosclerosis, with dyslipidemia being a key risk factor. Nonetheless, relying solely on a single lipid level is insufficient for accurately predicting the onset and progression of AMI. The present investigation aims to assess established clinical indicators in China, to identify practical, precise, and effective tools for predicting AMI. The study enrolled 267 patients diagnosed with acute myocardial infarction as the experimental group, while the control group consisted of 73 hospitalized patients with normal coronary angiography. The investigators collected general clinical data and relevant laboratory test results and computed the Atherogenic Index of Plasma (AIP) for each participant. Using acute myocardial infarction status as the dependent variable and controlling for confounding factors such as smoking history, fasting plasma glucose (FPG), low-density lipoprotein cholesterol (LDL-C), blood pressure at admission, and diabetes history, the researchers conducted multivariate logistic regression analysis with AIP as an independent variable. Receiver operating characteristic (ROC) curves were employed to determine the predictive value of AIP and AIP combined with LDL-C for acute myocardial infarction. The results of the multivariate logistic regression analysis indicated that the AIP was an independent predictor of acute myocardial infarction. The optimal cut-off value for AIP to predict AMI was -0.06142, with a sensitivity of 81.3%, a specificity of 65.8%, and an area under the curve (AUC) of 0.801 (95% confidence interval [CI]: 0.743-0.859, P < 0.001). When AIP was combined with LDL-C, the best cut-off value for predicting acute myocardial infarction was 0.756107, with a sensitivity of 79%, a specificity of 74%, and an AUC of 0.819 (95% CI: 0.759-0.879, P < 0.001). The AIP is considered an autonomous determinant of risk for AMI. Utilizing the AIP index alone, as well as in conjunction with LDL-C, can serve as effective predictors of AMI.