Influencing Factors In China Research Articles

Understanding regional talent attraction and its influencing factors in China: From the perspective of spatiotemporal pattern evolution.

Talents are not only an important strategic resource for promoting regional development but also a core element for maintaining competitiveness. We organize the evaluation index system of regional talent attraction into the following four aspects: regional development, industry development, income and regional environment. Combined with the talent possession of 31 provinces (cities) from 2010 to 2018, we establish a regression equation of the relationship between the evaluation index and talent possession by using a stepwise regression and the Bayesian prior function. Simultaneously, we apply the spatial autocorrelation analysis method to measure the correlation and agglomeration degree of the talent attraction level of provinces and municipalities in China. The results reveal the following. (1) From 2010 to 2018, the talent attractiveness level of China's provinces shows a steady upward trend with an average annual growth rate of 5.804%. The regional environment has the highest score, and the income level has the lowest score. (2) The level of talent attraction in China shows a decreasing trend from east to west, and the ranking in 2018 was "East Coast > North Coast > Southern Coast > Middle Yangtze River > Middle Yellow River > Southwest > Northeast > Greater Northwest". The trend of spatial agglomeration is apparent and gradually increases over the years. The numbers of hot and cold spots are relatively large and concentrated in the eastern coast and western region, respectively. (3) The level of economic development, quality of people's life, and level of the development of the tertiary industry have a great impact on the attractiveness of talents. Talents also pay more attention to regional medical, education and transportation indicators. These research results can provide some guidance and references for the formulation of talent introduction policies in various provinces and municipalities.

Green economic efficiency and its influencing factors in China from 2008 to 2017: Based on the super-SBM model with undesirable outputs and spatial Dubin model

Due to the pressure of global ecological degradation, the coordination of economic increase and ecological protection has drawn attention from policymakers and practitioners. Green economic efficiency (GEE) is a comprehensive index to measure economic, social, and environmental development. As China is the second-biggest economy in the world with high-energy consumption, it is necessary to investigate its green economy efficiency. In this paper, we innovatively adopt a super-SBM (slacks-based measure) model with undesirable outputs to calculate the GEE in 30 provinces of China between 2008 and 2017, and then comprehensively apply a spatial Dubin model (SDM) to investigated its influencing factors. The results showed that the overall GEE in China during the study period was at a low level with significant regional differences. The inter-regional GEE generally showed a gradient decreasing pattern of “East-Middle-West”, which demonstrates a gradual decline from the East to the West in China. The trend of the national GEE initially dropped and then gradually stabilized over the study period. Foreign trade dependence and direct investment had significant positive effects on the GEE, while the secondary industry and urbanization level had a significant negative effect.

Synergy effects and it’s influencing factors of China’s high technological innovation and regional economy

The Chinese government adheres to the innovation driven strategy and emphasizes that technological innovation is the strategic support for improving social productivity and comprehensive national strength. This paper discusses the mechanism of technological innovation and regional economic co-evolution, and constructs an index system to assess them based on the principles of synergy and systematics. The authors use a dynamic coupling model to study the law of the cooperative evolution of composite systems and geo-detector methods to reveal the main factors controlling the degree of coordination among them. The results show that the total factor productivity of China’s high-tech industry showed a "W"-type trend of change from 2006 to 2016, and the other indices exhibited a volatile trend. The total factor productivity, technical efficiency, scale efficiency, pure technical efficiency, and technological progress increased by 37%, 13.3%, 3.9%, 9%, and 20.8%, respectively. There was a significant spatial difference in changes in total factor productivity, forming a core-edge spatial pattern with the middle and upper reaches of the Yangtze River as the center of concentration. Most of China’s technological innovation and regional economic complex systems were in a state of interactive development from 2007 to 2016, except in the three northeastern provinces of Zhejiang, Shanghai, and the western part of the country. The degree of coupling of the other provinces showed an increasing trend, and the overall degree of coupling exhibited the spatial pattern of Central > Eastern > Western > Northeastern. The three most influential factors for the degree of coupling of China’s provincial complex system were the gross domestic product, efficiency of technological innovation, and expenditure on research and development, whereas the three most important factors affecting the degree of coupling of complex systems were the efficiency of technological innovation, gross domestic product, and number of high-tech enterprises as well as research and development personnel, respectively, in the eastern, central, western, and northeastern regions. Finally, the paper puts forward the suggestions of regional innovation driven coordinated development, technology innovation and regional economic coordinated development, in order to provide reference for the high-quality economic development of developing countries.

Spatial proximity, localized assets, and the changing geography of domestic mergers and acquisitions in transitional China

AbstractMergers and acquisitions (M&As) are the main force of spatial restructuring in the location of economic decision making. This paper analyzes the changing geography of M&As and its influencing factors in China during the period of 2002–2016. It shows a significant “core‐periphery” spatial pattern or network structure, in which a core group of major metropolises and developed provinces, led by Beijing, Shanghai, Guangdong, Zhejiang and Jiangsu, dominates China's M&As market and inter‐regional networks, marginalizing the other regions. The descriptive and modelling results indicate that spatial proximity and corporate preferences for localized assets can shape this geography of China's domestic M&As. The findings confirm that the “home bias” does exist in China's M&As partnering. Meanwhile, the key drivers of China's domestic acquirers are their desire to access and internalize localized assets, especially in the emerging market, new technology, and policy advantages. This study enriches the existing knowledge about the determinants of inter‐regional M&As in emerging economies (e.g., China), where the influences of regional disparities in the institutional setting, industrial structure, as well as economic marketization and financialization are more significant.

Estimation of eco‐efficiency and identification of its influencing factors in China's Yangtze River Delta urban agglomerations

AbstractEco‐efficiency is an important indicator which serves as a helpful instrument for the studies of sustainable development. This paper estimated the eco‐efficiency of 26 cities in China's Yangtze River Delta urban agglomerations. Based on different matrixes, Moran's I was applied to analyze the spatial correlation. The spatial Durbin model was applied to analyze the direct and indirect effect of influencing factors. Some conclusions were drawn. (a) The average eco‐efficiency showed an increasing trend. The regional difference of eco‐efficiency decreased and then increased. Shanghai's eco‐efficiency had been the highest. (b) The eco‐efficiency showed positive spatial autocorrelation and it also exhibited significant characteristic of local spatial autocorrelation. (c) Economic development, fixed assets investment, and technological level of one city had a significant positive impact on the eco‐efficiency of the city itself. Industrial structure, fiscal decentralization, and foreign direct investment of a city had a significant negative impact on the eco‐efficiency of the city itself. Changes in the economic development and technological levels in a city had positive impacts on the eco‐efficiency of its neighboring cities. Foreign direct investment had a negative spatial spillover effect. (d) This paper suggested that it is necessary to pay attention to the interaction of influencing factors among cities.

Spatial econometric analysis of environmental total factor productivity of ranimal husbandry and its influencing factors in China during 2001–2017

Pollution discharge from animal husbandry deteriorates the environment and is of global concern. In this study, data envelopment analysis (DEA) was used to indirectly estimate the pollution discharge of livestock and poultry breeding in terms of sustainable development in China. Land, biogas, and grassland were included as input indexes, and the inverted values of indexes of organic matter, nitrogen, and phosphorus produced by pigs, dairy cattle, beef cattle, poultry, and sheep were included as output indexes. Based on the DEA model with variable returns to scale, the “pollution intensity index of livestock and poultry breeding” was estimated using the principle of output maximization. This study focused on livestock and poultry farming pollution emissions, and the slack-based measure directional distance and metafrontier efficiency functions were used to measure the environmental total factor productivity (ETFP) of animal husbandry in each province and six major animal husbandry production regions of China during 2001–2017. Additionally, a spatial econometric model was employed to analyze the factors affecting animal husbandry ETFP. The results show that the mean value of animal husbandry ETFP was higher than that of conventional total factor productivity. The driver of increased animal husbandry ETFP was technological progress. Overall, China's animal husbandry was developing sustainably, and there was little scope for group technology to catch up. According to an empirical analysis of influencing factors, farmers' improved per capita income level and environmental governance helped to increase animal husbandry ETFP. Furthermore, various measures to improve animal husbandry ETFP in China according to local conditions are needed. Finally, animal husbandry should continue to develop sustainably, using environmental regulations that continuously exert the “Porter Effect.”

Analysis of the Status and Influencing Factors of Rural Waste Classification and Treatment—Based on the Empirical Study of Bengbu City

Realizing the classification and treatment of rural garbage not only has the practical significance of improving the quality of life of rural residents, improving the rural ecological environment, increasing the reuse rate of resources, but also the need to build beautiful countryside. Based on field survey data from Dougou Village and Xinbei Village, Bengbu City, the rural waste classification and treatment work is not well implemented by residents; the rural waste treatment methods are deficient; the infrastructure for waste treatment is insufficient; and the sources of funds for waste treatment are limited difficult. In order to analyze the influencing factors of China’s rural garbage classification and treatment at this stage, this paper selects nine factors from five aspects: residents, government, society, economy, and family, and uses the analytic hierarchy process to compare the factors to find the main factors affecting rural garbage classification. Combined with the current status of rural waste classification and treatment, we provide effective suggestions for the development of waste classification and treatment in rural areas in China, in order to improve the current status of rural garbage treatment.

Research on the Fluctuation and Factors of China TFP of IT Industry

The production capacity of the industry itself is booming in the development of the information technology (IT) industry in China. At the same time, we should clearly understand that in the process of industrial development and aggregation, there are very significant features, such as differences in investment in output between software and hardware development, regional differences, and even IT industries in different levels of cities. The development also has a clear division of labor and constraints. Furthermore, it is necessary to study the fluctuations of the total factor productivity (TFP) of the IT industry and the analysis of the influencing factors in China. This is not only a review of the past development of the IT industry of China, but also the IT in the new era and the new situation. The industry gives correspondingly targeted and feasible recommendations for China. This paper attempts to calculate the TFP of the IT industry of the 23 provinces in China from 2007 to 2016, describes the fluctuations of the TFP of IT industry in China, using the decomposition indicators to analyze the constituent factors and make recommendations. After the argumentation, this paper chose the DEA-Malquist index method and uses the Deap2.1 system. The empirical analysis found that the TFP of China’s IT industry fluctuated less, with an average annual growth rate of 10.7%. Its pure technical efficiency continues to be improving, and its scale efficiency is significant, but its regional differences are large. The differences are not only reflected in the relative value of inputs, but also in the progress of the productivity breakdown.

Energy consumption and the influencing factors in China: A nonlinear perspective

Different from many studies on Energy Kuznets Curve, this paper does not directly consider income factor but conducts a nonlinear study on per capita primary energy consumption and electricity consumption in China, whose economic development is considered investment-driven, in which government macroeconomic policies, especially government expenditure plays a very important role. In particular, this paper attempts to compare the different impacts of government expenditures and the other influencing factors on energy consumption. Based on the results of the threshold regression, in the future, with the further development of the economy, the driving force of labor population growth will slow down. Comparing with primary energy, the relationship between electricity consumption and its influencing factors will change later, and the difference in the effects of the influencing factors is mainly reflected in the formation of capital stock (investment) and the development of urbanization. Government expenditure on private goods may not be always as inefficient in energy consumption and cleaner production as previously thought in the literature. Meanwhile, the growth of government expenditure on public goods will become a powerful driving factor which indicates that the government needs to assess its overall impact on energy consumption and energy efficiency when participating in the provision of public goods. The paper also found that when studying the issue of energy consumption and regional differences in China, the geographic classification of eastern, central and western regions may not be appropriate. Grouping according to energy consumption levels may be one of the better options. And the distribution of energy consumption levels in China’s provinces is consistent with the distribution of government expenditure levels. The estimation results also provide us with important policy implications: the government expenditure in education is of great importance, and it can produce a strong energy-saving effect through technological progress.

Knowledge and attitudes toward end-of-life care among community health care providers and its influencing factors in China: A cross-sectional study.

A majority of nurses struggled with a negative emotion of anger, doubt, fear, or anxious, uncomfortable in the face of death and dying. However, little was known about community health care providers’ in China. Therefore, we conducted a study to investigate their knowledge and attitudes toward end-of-life care and analyze its influencing factors. To provide reference for developing effective strategies to promote end-of-life care in China.A total of 132 community health care providers of 10 community health care centers in Changzhi city were investigated by a Questionnaire of Knowledge and Attitudes toward Caring for the Dying from May, 2017 to December, 2017, and data was analyzed by SPSS 22.0 software.Of the 132 community health care providers who were under investigation, 70 knew about hospice care, but they rated their overall content on end-of-life care as inadequacy, especially in communication skills and knowledge of pain management. The average score of attitudes was 3.47 (SD = 0.44), the lowest score was in the subscale of nurse−patient communication, which was 2.91 (SD = 0.65). Health care providers who had worked for more than 11 years, who had experiences of the death of relatives or friends, and who had previous experiences of caring for terminal patients had more positive attitudes toward caring for the dying (P < .05 for all). There was a significant relationship between community health care providers’ attitudes toward death and their attitudes toward end-of-life care (r = −0.282, P < .01). The significant predictors of attitudes toward end-of-life care were attitudes toward death (β = −0.342), experiences of the death of relatives (β=−0.207), experiences of caring for the dying (β = 0.185), and working experience (β = 0.171).Community health care providers had positive attitudes toward end-of-life care, but they lacked systematic and professional knowledge and skills of caring for the terminal patients. Education is the top priority. It is imperative to set up palliative care courses and life-death education courses, establish an indigenous end-of-life care model, and improve policies, systems, and laws to promote end-of-life care.

Inter-regional innovation correlation effects and influencing factors in China

Purpose The purpose of this paper is to find out the characteristics and evolutionary trends of China’s inter-regional innovation correlation network, the status and roles of each province in China’s inter-regional innovation correlation network and the influencing factors of China’s inter-regional innovation correlation effect. Design/methodology/approach Based on the patent data of 30 provinces (autonomous regions and municipalities) in China from 1991 to 2017, social network analysis was used to find out the characteristics and evolutionary trends of China’s inter-regional innovation correlation network and the status and roles of each province in China’s inter-regional innovation correlation network. Furthermore, the QAP method was used to find out the influencing factors of China’s inter-regional innovation correlation effect. Findings China’s inter-regional innovation correlation is becoming increasingly close and inter-regional innovation correlation network is becoming increasingly stable. Jiangsu, Zhejiang, Beijing, Shanghai, Guangdong and other eastern coastal provinces are at the core in the inter-regional innovation correlation network, while the western regions are marginal actors. China’s regional innovation development territory can be divided into four blocks, namely, “bidirectional spillover block,” “net spillover block,” “main beneficial block” and “net beneficial block,” and gradient transfer mechanism is obvious between the blocks. The geographical adjacency and similarity in regional industrial structure, urbanization level and government attention degree have significant positive effect on China’s inter-regional innovation correlation effects. Research limitations/implications This paper only uses patent application as a measure of regional innovation level to analyze inter-regional innovation correlation effect. Meanwhile, this paper carries out an empirical study only from the provincial level and not from the city level. Practical implications This paper provides the practical basis for further promoting the coordinated development of regional innovation and promoting the construction of regional innovation systems with different characteristics. Originality/value This paper contributes to understand the status and role of each province in inter-regional innovation correlation network. Meanwhile, this paper also helps to understand the influence of the proximity and external environmental factors on inter-regional innovation correlation effect.

Study on Environmental Impact Factors of Carbon Emissions and Air Pollution Control in Transportation Industry

Since the industrial revolution, global warming has become more and more serious. Existing research shows that the significant increase in greenhouse gas emissions such as CO2 is the most important cause of global warming. Therefore, all countries have begun to formulate practical and feasible carbon emission reduction policies and measures. China is the largest developing country in the world and the largest energy consumer, facing many pressures to reduce emissions. This paper takes the carbon emissions of China’s transportation industry as the research object, based on the carbon emissions of China’s transportation industry from 2003 to 2017. Through the analysis of data, transportation industry added value, transportation intensity, transportation energy intensity and transportation energy structure were introduced to study the environmental impact factors and air pollution control of China’s transportation industry carbon emissions. Through the expanded STIRPAT model, the order of influence of various factors is ranked from the largest to the smallest: population size, transportation energy structure, transportation intensity, transportation energy intensity, transportation industry added value. This paper conducts a comprehensive and in-depth study on the influencing factors of China’s transportation industry carbon emissions, identifies the main influencing factors, and lays an important theoretical foundation for China to develop emission reduction targets and measures that meet environmental requirements and self-development.

The sedation practices of paediatric intensive care unit nurses and the influencing factors in China.

Nurses play a key role in administering sedation to mechanically ventilated children, which impacts children's psychological, physiological and cognitive changes in the paediatric intensive care unit. This study aimed to survey the sedation practices of paediatric intensive care unit nurses on mechanically ventilated children in China and explored the influencing factors. A cross-sectional survey was conducted based on electronic questionnaires comprised of the Nurse Sedation Practices Scale (Chinese version) in 14 different types of paediatric intensive care units of 11 academic hospitals in China from 15 February to 15 April 2017. A convenience sample of 495 nurses [73·4% response rate, (674)] completed the survey. Seven units applied Ramsay Sedation Scale as a sedative assessment tool. The majority of the nurses used observed behaviours and physiological changes of the ventilated children as indicators to assess the sedation level, and they had a positive attitude and intention, which may influence practice positively, whereas high clinical workload and the lack of communication between the nurses and families might hinder practice. The practice of sedation varied greatly in different regions, and the respondents of the northwest region scored lower. Paediatric nurses in China rarely used a validated paediatric instrument to assess sedation, and most nurses relied on physiological and behavioural cues. The quality of sedation training, nursing workload and regional economic disparity affected the sedation practice. The restricted visiting policy and lack of clearly defined nursing responsibilities around sedation may hinder effective sedation assessment and management. This study found that there was no paediatric-validated tool popularized in paediatric intensive care units in China and explored influencing factors. We suggest that a validated tool, high-quality training and hospital's policy, such as visiting regulation, should be promoted to improve the sedation practice.

Incomplete Vaccination Among Children With Special Health Care Needs in Zhejiang, China: Analysis of Retrospective Data.

Objective: There is a lack of data relating to vaccination of children with special health care needs (CSHCN) and its influencing factors in China. We investigated the disease spectrum of CSHCN at the Vaccination Consultation Clinic in Zhejiang province as well as the underlying factors of vaccination recommendations of these children.Methods: In this study, we retrospectively analyzed the data of 4,525 CSHCN, who visited to our clinic for a vaccination consultation from January 1, 2016 to May 30, 2018. Descriptive data were presented as mean ± standard deviation (SD) and percentages. Multivariate analysis was performed with non-conditional bivariate logistic regression to identify the underlying factors of vaccination recommendations. Subsequent information regarding the following vaccination and the occurrence of AEFI were also collected and analyzed.Results: The main diseases consulted were those relating to the circulatory and nervous systems as well as neonatal diseases. The distribution of diseases varied by age: 53.6% infants under 12 months were counseled for circulatory system diseases, while 44.6% children aged 12~24 months and 54.7% children over 25 months were counseled for nervous system diseases. According to the evaluation reports issued by the consultation clinic, 75.0% of CSHCN were recommended to be vaccinated normally, 21.2% were recommended to defer specific vaccination, while only 3.8% were recommended to defer all vaccinations. In logistic regression analysis, age, history of adverse events following immunization (AEFI) and the number of diseases combined were all strong correlative factors for vaccination recommendations. Children who were aged over 25-month-old (OR = 1.34, 95%CI: 1.11–1.61) or had a history of AEFI (OR = 3.77, 95%CI: 2.83~5.01) or those who had numerous diseases combined (OR = 2.00, 95%CI: 1.46~2.75) tended to have a higher rate of deferred vaccination recommendation. Among those CSHCN who received nationally-recommended vaccines, the estimated AEFI rate was 24.29/100 000. No uncommon or rare serious adverse reactions were detected.Conclusion: Age, history of AEFI, and the number of diseases combined were important factors that affected the vaccination recommendations of CSHCN. Most CSHCN can be safely vaccinated according to the nationally-recommended schedule.

Provincial Carbon Emissions Efficiency and Its Influencing Factors in China

We calculated provincial carbon emissions efficiency and related influencing factors in China with the purpose of providing a reference for other developing countries to develop a green economy. Using panel data covering the period from 2004–2016 from 30 provinces in China, we calculated the carbon emission performance (CEP) and the technology gap ratio of carbon emission (TGR) with the data envelopment analysis (DEA) method and the meta-frontier model separately to analyze provincial carbon emissions efficiency in China. No matter which indicator was employed, we found that distinct differences exist in the eastern, the central, and the western regions of China, and the eastern region has the highest carbon emission performance, followed by the central and the western regions. Then, the panel data Tobit regression model was employed to analyze the influencing factors of carbon emissions efficiency, and we found that scale economy, industrial structure, degree of opening up, foreign direct investment (FDI), energy intensity, government interference, ownership structure, and capital-labor ratio have different impacts on the carbon emission efficiency in different regions of China, which indicates different policies should be implemented in different regions.

Total-factor industrial eco-efficiency and its influencing factors in China: A spatial panel data approach

China's rapid economic growth and industrialization process has inevitably led to severe resource depletion and environmental degradation. Therefore, establishing total-factor industrial eco-efficiency (TFIEE) and probing into its influencing factors has great significance for improving overall eco-efficiency and the level of sustainable development. In this study, we evaluated the total-factor industrial eco-efficiency of 30 Chinese provinces grouped into eight regions in the period of 2006–2015 using a modified super-efficiency SBM-DEA model in which capital, labor, energy and water are adopted as inputs; and industrial value-added and industrial waste (soot & dust, solid wastes, waste water, waste gas) are treated as a desirable output and an undesirable output, respectively. Global and local Moran's indexes were used to analyze the spatial autocorrelation of TFIEE at both the national and regional levels. A panel spatial autoregressive (SAR) model was also proposed to study how technology and government interference affect TFIEE. We find that the ranking of TFIEE shows a descending order from the coast to the inland of China, which is consistent with the development levels of the regions in China. The Moran's index reveals that TFIEE shows a spatially positive autocorrelation from a national perspective. However, there exists no spatial autocorrelation for central China from a regional perspective, reflecting the cutting-off effect on the linkage of TFIEE between the eastern and western areas of China. We also find that TFIEE is positively correlated with technological progress and negatively correlated with government interference. Finally, policy implications were summarized to guide the green transition of the industrial sector in China.

Efficiency evaluation of urban wastewater governance and its influencing factors in China

Efficiency evaluation of urban wastewater governance and its influencing factors in China

Spatiotemporal variations of photosynthetically active radiation and the influencing factors in China from 1961 to 2016

Daily measurements of photosynthetically active radiation (PAR) and other meteorological parameters at 16 stations in China during 2005–2015 were used to develop the all-weather Adaptive-Network-based Fuzzy Inference System (ANFIS) PAR models. The ANFIS models were compared with other semi-empirical and semi-physical methods, and the results showed that ANFIS models using global solar radiation (G) as input parameter provided more accurate estimates than other models. Daily PAR values during 1961–2016 were reconstructed using meteorological parameters at 908 meteorological stations, and the spatiotemporal characteristics of PAR in China were analyzed. The daily PAR ranged from 20.03 to 36.29 mol m−2 day−1 with annual mean value being about 29.03 mol m−2 day−1 in China during 1961–2016. The PAR values were generally higher in Qinghai-Tibet Plateau (QTP) and Inner Mongolian Plateau (IMP) and lower in Northeast and Southeast China, especially in the Sichuan Basin. PAR decreased in most part of China, especially in Northeast China, with the minimum value being about − 0.11 mol m−2 day−1 year−1 during 1961–2016. The increasing trend only appeared in Southwest China with the maximum value being about 0.02 mol m−2 day−1 year−1. Annual mean daily G, PAR fraction (Fp, the ratio of PAR and G), sunshine duration (SSD), relative humidity (RH), and water pressure (MP) were further analyzed to find the influencing parameters for PAR. The results showed that G, Fp, and SSD were the major factors for influencing PAR in most part of China, but in some areas, RH and MP influenced the PAR more effectively. Finally, the monthly variations of aerosol optical depth (AOD) in the Yangtze River Basin gathered from the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 Atmosphere Product during 2002–2016 were analyzed, which was one important factors influencing the PAR values in summer and winter months.

Environmental regulatory efficiency and its influencing factors in China

The effectiveness of environmental regulations (ERs) has been examined carefully in the past time; however, the inputs of ERs have been neglected so far. In order to track the relationship between inputs and outputs of ERs, this paper first constructs an environmental regulatory efficiency (ERE) index system and develops an entropic slack-based model suitable for measuring China’s ERE during 2004–2014, which considers the entropic allocation of multiple inputs and desirable and undesirable outputs. The influencing factors of ERE were then explored by the panel Tobit model. Results have illustrated that in China, ERE is relatively low in general, with significant and narrowing geographical discrepancies, and ERs are becoming more and efficient from 2004 to 2014. From the regional view, the east has the highest ERE values, followed by the west, then northeast, and lastly the central regions with the lowest values. Furthermore, it has been discovered that the economic development level and population density both affected ERE positively, while technological innovation and industrialization level exerted a reverse effect. From the perspectives of the level of opening-up and urbanization, environmental pursuits, all three displayed no correlation with ERE. The conclusions may be helpful for the Chinese government to improve ERE.

Current status of national free antiretroviral therapy in interprovincial migrating people living with HIV/AIDS and influencing factors, China, 2011-2015

Objective: To understand the current status of national free antiretroviral therapy in interprovincial migrating people living with HIV/AIDS (PLWHA) and influencing factors in China. Methods: Descriptive and trend test analyses were performed to evaluate the historical characteristics and trends of main descriptive indicators on national free antiretroviral therapy for the interprovincial migrating PLWHA by using the data collected from National Comprehensive HIV/AIDS Information System from 2011 to 2015. Logistic regression model was used to explore the main factors that influencing the coverage of national free antiretroviral therapy among the interprovincial migrating PLWHA in China. Results: The proportion of interprovincial migrating PLWHA gradually increased in last 5 years from 7.1% (17 784/250 645) in 2011 to 10.3% (54 596/528 226) in 2015 (Z=51.38, P<0.000 1) in China. The coverage rate of free antiretroviral therapy in interprovincial migrating PLWHA increased from 37.3% (6 641/17 784) in 2011 to 71.0% (38 783/54 596) in 2015, showing a significant rising tendency (Z=96.23, P<0.000 1), but it was slightly lower than that in non-interprovincial migrating PLWHA in 2015 (71.5%, 338 654/473 630). Multivariate logistic regression analysis showed that the PLWHA who were females, aged ≥50 years, of Han ethnic group, married or had spouse, had the educational level of high school or above, infected through homosexual intercourse, with CD(4)(+)T cells counts ≤500 cells/μl at the first visit, identified to be infected with HIV in medical setting, living in urban areas et al, were more likely to receive free antiretroviral therapy. Conclusions: The coverage rate of free antiretroviral therapy varied among the interprovincial migrating PLWHA with different characteristics. It is still necessary to take effective measures to further increase the coverage of free antiretroviral therapy in interprovincial migrating PLWHA and to include the free antiretroviral therapy in interprovincial migrating PLWHA into standardized management system as soon as possible.