Central China Region Research Articles

Seasonal prediction of the distribution of three major malaria vectors in China: Based on an ecological niche model.

Against the backdrop of a global malaria epidemic that remains severe, China has eradicated indigenous malaria but still has to be alert to the risk of external importation. Understanding the distribution of vectors can provide an adequate and reliable basis for the development and implementation of vector control strategies. However, with the decline of malaria prevalence in recent years, the capacity of vector monitoring and identification has been greatly weakened. Here we have used new sampling records, climatic data, and topographic data to establish ecological niche models of the three main malaria vectors in China. The model results accurately identified the current habitat suitability areas for the three species of Anopheles and revealed that in addition to precipitation and temperature as important variables affecting the distribution of Anopheles mosquitoes, topographic variables also influenced the distribution of Anopheles mosquitoes. Anopheles sinensis is the most widespread malaria vector in China, with a wide region from the northeast (Heilongjiang Province) to the southwest (Yunnan Province) suitable for its survival. Suitable habitat areas for Anopheles lesteri are concentrated in the central, eastern, and southern regions of China. The suitable habitat areas of Anopheles minimus are the smallest and are only distributed in the border provinces of southern China. On this basis, we further assessed the seasonal variation in habitat suitability areas for these three major malaria vectors in China. The results of this study provide new and more detailed evidence for vector monitoring. In this new era of imported malaria prevention in China, regular reassessment of the risk of vector transmission is recommended.

Identification of potential source regions and long-range transport routes/channels of marine PM2.5 at remote sites in East Asia

Long-range transport (LRT) of air masses in East Asia and their impacts on marine PM2.5 were explored. Situated in the leeward region of East Asia, Taiwan Island marked by its elevated Central Mountain Range (CMR) separates air masses into two distinct air currents. This study aims to investigate the transport of PM2.5 from the north to the leeward region. Six transport routes (A-F) were identified and further classified them into three main channels (i.e. East, West, and South Channels) based on their transport routes and potential sources. Green Island (Site GR) and Hengchun Peninsula (Site HC) exhibited similarities in their transport routes, with Central China, North China, and Korean Peninsula being the major source regions of PM2.5, particularly during the Asian Northeastern Monsoons (ANMs). Dongsha Island (Site DS) was influenced by both Central China and coastal regions of East China, indicating Asian continental outflow (ACO) as the major source of PM2.5. The positive matrix factorization (PMF) analysis of PM2.5 resolved that soil dust, sea salts, biomass burning, ship emissions, and secondary aerosols were the major sources. Northerly Channels (i.e. East and West Channels) were primarily influenced by ship emissions and secondary aerosols, while South Channel was dominated by oceanic spray and soil dust. The results of W-PSCF and W-CWT analysis indicated that three remote sites experienced significant contributions from Central China in the highest PM2.5 concentration range (75–100%). In contrast, PM2.5 in the 0–25% and 25–50% ranges primarily originated from the open seas, with ship emissions being the prominent source. It suggested that northern regions with heavy industrialization and urbanization have impacts on high PM2.5 concentrations, while open seas are the main sources of low PM2.5 concentrations.

Mindfulness and impulsive behavior: exploring the mediating roles of self-reflection and coping effectiveness among high-level athletes in Central China.

In the highly competitive field of sports, impulsive behavior by athletes not only threatens personal and team harmony but also poses significant risks to their careers and public image. Despite these behaviors often becoming the focus of public attention, their underlying causes and prevention strategies remain relatively unknown. This study delves deep into the impact of mindfulness on athletes' impulsive behavior, revealing the mediating roles of self-reflection and coping effectiveness. Using a combination of snowball and convenience sampling, a sample of 403 athletes from high-level sports teams in the Central China region participated in a questionnaire survey. The data were analyzed using Amos v.23 software. The findings indicate a positive correlation between mindfulness and coping effectiveness (standardized coefficient = 0.336, p < 0.001), as well as between self-reflection and coping effectiveness (standardized coefficient = 0.406, p < 0.001). There is a negative correlation between coping effectiveness and impulsive behavior (standardized coefficient = -0.476, p < 0.001). The positive impact of mindfulness on impulsive behavior (standardized coefficient = -0.371, p < 0.01) is mediated by self-reflection and coping effectiveness. The explanatory power of this study is R2 = 0.35. Mindfulness reduces impulsive behavior by enhancing self-reflection capabilities and improving coping effectiveness. Based on these substantive research results, to mitigate impulsive behavior in athletes, it is recommended that the National Sports Administration and coaches actively implement mindfulness training. Additionally, targeted psychological intervention strategies should be developed to enhance athletes' mental health levels and optimize their sports performance.

The impact of robots on informal employment: evidence from China

ABSTRACT Informal employment, which has grown rapidly in recent years, is closely related to individual welfare, and is inevitably influenced by the rise of robots. Against this backdrop, this study aims to explore the impact of robots on informal employment. Applying a probit model and using data from the China Family Panel Studies in 2014, 2016, and 2018 and the International Federation of Robotics, this study reveals that robots do not have a significant impact on unemployment or labour force participation, but significantly increase the probability of informal employment. Further heterogeneity analysis indicates that robots have a greater positive impact on informal employment in the central and western regions of China. Moreover, individuals working in non-routine task-oriented industries, with higher general or specialized skills, exhibit a lower probability of being informally employed under the influence of robots. This study provides empirical evidence to maintain job market stability in the era of automation in China, which can also be used by policymakers in other countries.

The spatial mobility network and influencing factors of the higher education population in China

Abstract The scale and frequency of talent mobility in the world have increased sharply, and the competition for talent has intensified in various regions. This paper mainly studies the spatial mobility characteristics and influencing factors of China’s highly educated talents. It found that China’s higher education population mobility network has prominent uneven characteristics, the central and eastern regions of China, especially the eastern coastal regions, are the hotspots of the network. The higher education population flows frequently in large cities and regional central areas. The hierarchical structure follows a “north-south division,” which is dominated by Beijing and Shanghai, respectively. Geographical distance has a specific hindering effect in this context. Furthermore, the similarity of culture, institutions, customs, and dialect facilitates the mobility of the higher education population. Cities with high economic levels, centralized educational resources, sound infrastructure, and aesthetically appealing environments are also likely to attract more talents.

Spatial-temporal pattern and spatial convergence of carbon emission intensity of rural energy consumption in China.

Based on the panel data of 30 provinces (municipalities and autonomous regions) in China from 2005 to 2019, this paper uses Gini coefficient decomposition and kernel density estimation to investigate the regional differences and dynamic evolution trend of rural energy carbon emission intensity in China. Then, the convergence model is used to analyze the convergence characteristics and influencing factors of carbon emission intensity. The study found the following: (1) During the observation period, the carbon emissions of coal energy and oil energy were much higher than those of gas energy. The carbon emissions of rural energy consumption experienced three stages of development, and the carbon emission intensity showed a downward trend as a whole. The spatial distribution pattern of total carbon emissions present an "adder" distribution, and the spatial agglomeration phenomenon gradually strengthens with the passage of time. (2) The Gini coefficient of China's rural energy consumption carbon emission intensity shows a trend of "Inverted N-shaped." The Gini coefficient of carbon emission intensity in the eastern and northeastern regions shows an increasing trend, while the Gini coefficient of carbon emission intensity in the western and central regions shows a downward trend. The super variable density is the main source of carbon emission intensity difference. The peak value of the main peak of the nuclear density curve of the carbon emission intensity increased significantly, the bimodal form evolved into a single peak form, and the density center moved to the left. (3) The carbon emission intensity of rural energy consumption in the whole, central, and western regions of China has the characteristic of σ convergence, while the carbon emission intensity in the eastern and northeastern regions does not have the characteristic of σ convergence. There is a significant spatial positive correlation in the carbon emission intensity, there is also a significant β convergence characteristic, the speed of conditional β convergence is significantly higher than that of absolute β convergence, and the spatial interaction will further improve the convergence speed. Industrial structure, industrial agglomeration, and energy efficiency will increase the convergence speed. In terms of sub-regions, the conditional convergence rate of carbon emission intensity in the four regions shows a decreasing trend in the northeast, central, eastern, and western regions.

Assessment of methane emissions from pressure regulation stations in China

Pressure regulation stations are responsible for transporting natural gas downstream and are an indispensable part of the gas supply chain. In recent years, countries and enterprises have attached increasing importance to methane emission accounting. However, methane emissions from pressure regulation stations are still not comprehensively understood and accounted for. In this study, methane emissions from 21 pressure regulation stations under normal conditions were quantified using the Environmental Protection Agency's (EPA's) “Other Test Method 33 A” (OTM 33 A) in three regions of China: the eastern, northern, and central regions of China. The results showed that the emission rate from pressure regulation stations generally lied in the order of 10−1-10−3 kg/h, whereas the measured methane emission rate (MMER) with 95% confidence interval (95%CI) was 0.671 (0.066, 3.040) (kg/h), which was determined from the bootstrapping measurements from all pressure regulation stations. The MMER (95%CI) values were 0.051 (0.026, 0.102) for East China, 2.263 (0.095, 8.317) for North China, and 0.004 (0.003, 0.005) (kg/h) for Central China, showing a relatively obvious skewed distribution. Overall, MMER had a diminutive correlation with gas throughput and pipeline pressure. In contrast, the degree of correlation of pipeline pressure was higher than that of gas throughput.

Novel use of structural equation modeling to examine the development of a framework of patient-centered two-way referral systems for building digital subjective well-being healthcare: A cross-sectional survey in Central China.

Digital health technologies are progressively assuming significant roles in aspects encompassing in-hospital management, patient-centered design, and tiered referral systems. Nevertheless, current studies do not involve exploration into the potential value and mechanisms of digital health in a patient-centered context. This study aimed to explore the development of a framework of comprehensive, evidence-based digital health technologies for the construction of welfare-oriented healthcare. From March to June 2023, a cross-sectional online study was performed, involving 335 respondents with prior referral experiences hailing from the Central China region. Data on welfare-oriented healthcare factors (clinical pathway management, medical structure configuration, healthcare service accessibility, two-way referrals) underwent factor analysis in advance, and correlation between these factors and their association with two-way referrals was evaluated by testing for direct and indirect (mediating) effects. Firstly, there existed a significant positive correlation between integrative medical indicators and welfare-centered healthcare (β = 0.02-0.16, p < 0.05). Furthermore, two-way referral had an direct association with integrative medical parameters and the welfare healthcare service system (β = 0.15-0.31, p < 0.05), but exerted a partial mediatory function in the welfare healthcare service system (β = 0.005-0.021, α < 0.05). Two-way referrals partially mediate the integrated medical indicators, mainly through direct effects, while also providing complementary support. Clinical pathways, medical structure, and accessibility are closely linked to welfare healthcare and significantly influence healthcare quality. Thus, improving these factors should be prioritized. This study proposes a method combining integrated evaluation indicators with pathway mechanism design. This pathway mechanism design includes key steps such as patient registration, information extraction, hospital allocation or referral, diagnosis and treatment, rehabilitation plan monitoring, service feedback, and demand resolution. This design aims to change patients' intentions in seeking healthcare, thereby increasing their acceptance of bidirectional referrals, and ultimately enhancing the effectiveness and realization of welfare healthcare.

A115: Revision of the Chinese Version of Physical Self-Description Questionnaire-Short for Middle School Students

Purpose: The Physical Self-Description Questionnaire -Short (PSDQ-S) is one of the world's recognized effective tools for measuring Physical Self-Concept (PSC). However, Latent profile analysis of the physical self-description among Chinese adolescents only supported the 3-dimensional model of PSDQ-S, that is, it could only distinguish the Physical Activity (PA), Appearance, and Body Fat of Chinese children and adolescents, but could not effectively distinguish the 8 dimensions of Coordination, Flexibility, Strength, Endurance, Sport, Global Physical, Health, and Global Esteem. It cannot meet the needs of PSC measurement in the field of sports psychology in China. The purpose of this study was to revise the PSDQ-S for Chinese middle school students, and to test its reliability, validity, and gender measurement equivalence in Chinese middle school students. Methods: A stratified random cluster sampling method was used to conduct a questionnaire survey on the Chinese version of PSDQ-S. 2505 middle school students in grades 7-12 (12-18 years old) were selected from seven administrative geographic regions of North China, Northeast China, East China, Central China, South China, Southwest and Northwest China, among which 1239 were male subjects, with an average age of (15.07±1.93) years, Female subjects were 1266, with an average age of (15.02±2.04) years. SPSS 24.0 and Mplus 8.3 were used for data analysis. Results: Eight common factors were extracted by exploratory factor analysis, and the cumulative variance interpretation rate was 79.45%. Confirmatory factor analysis support 8 factor model hypothesis (χ2 / df = 1.846, CFI = 0.939, TLI = 0.929, SRMR = 0.050, RMSEA = 0.061). The 8 dimensions were Physical Activity, Appearance, Body Fat, Flexibility &amp; Coordination, Endurance, Sport, Global Physical and Health. The average variance extraction of each factor of the Chinese version PSDQ-S convergence validity index was greater than 0.50, and the combination reliability was greater than 0.60. The gender equivalence hypothesis was established. Conclusions: The revised Chinese version of PSDQ-S has good reliability, validity, and gender equivalence. It can be used as a measurement tool of PSC of Chinese middle school students.

Research on the Evaluation of Innovation Capability of Manufacturing Enterprises in Central and Western Regions of China

Research on the Evaluation of Innovation Capability of Manufacturing Enterprises in Central and Western Regions of China

Study on the impact of digital economy on industrial collaborative agglomeration: Evidence from manufacturing and productive service industries.

In the digital era, digital economy has a far-reaching impact on the collaborative agglomeration of manufacturing and service industries. This research aims to examine the economic relationship between digital economy and industrial collaborative agglomeration. Based on a panel data set of 286 Chinese cities, this research employs Tobit model, moderating effect model, and mediating effect model to conduct data analysis. It is found that digital economy has a nonlinear relationship with industrial collaborative agglomeration, and this relationship is a U-shape. Moderating effect analysis reveals that government intervention significantly regulates the role of digital economy in industrial collaborative agglomeration. Mediating effect analysis indicates that digital economy promotes industrial collaborative agglomeration through entrepreneurial activity. Heterogeneity analysis shows that the facilitating effect of digital economy on collaborative agglomeration in high-end industries comes earlier than in middle- and low-end industries. Moreover, this research finds that digital economy plays a significant role in industrial collaborative agglomeration in central and western regions of China but not in the eastern region. To enhance the impact of digital economy on industrial collaborative agglomeration, it is crucial to strengthen the engagement of the government and ensure the availability of digital technology.

New record of Miniopterusmagnater (Chiroptera, Miniopteridae) from south-western China and a comparative study of three species of Miniopterus in China.

This research documents a new record of Miniopterusmagnater in the south-western region of China, a significant discovery given the limited diversity of the Miniopterus genus within the country. Only three species of Miniopterus occur in China: Miniopterusmagnater, Miniopterusfuliginosus and Miniopteruspusillus. These species share a high degree of morphological similarity, particularly in their external characteristics. This underscores the necessity for the identification of additional distinguishing traits that can aid in the taxonomic differentiation of these closely-related species. During the 2023 field expedition to various nature reserves in Yunnan Province, China, we encountered specimens of the genus Miniopterus. Utilising a combination of morphological assessments and phylogenetic analyses, we identified six individuals as Miniopterusmagnater. A review of the existing geographical distribution data revealed that this species is primarily found in central and southern regions of China, with no previous records from the south-western part of the country. Based on our findings, we present a novel record of Miniopterusmagnater's distribution in the south-western region of China.

Research on the impact and mechanism of digital capabilities and digital finance on household wealth in the context of aging

China has entered a period of synchronous development between digitalization and aging. Based on the data from the China Household Finance Survey (CHFS), the partial least squares structural equation model (PLS-SEM) and multi-group analysis were used to analyze the impact mechanism of digital capabilities and digital finance on the wealth of elderly households. The results indicate that digital capabilities and digital finance can improve the wealth level of households headed by the elderly through direct and indirect paths. The indirect effects of digital capabilities and digital finance on elderly household wealth are all exerted through the node of business and property income, and entrepreneurship/investment are mediating variables. Moreover, digital capabilities have a greater impact on the wealth of elderly households in the central and western China regions, while digital finance has a greater impact in the eastern China regions. In addition, there is no significant difference in the effect of digital capabilities on business and property income across regions, while digital finance has a larger effect in the eastern region. The above conclusions can provide theoretical and practical support for realizing active aging and common prosperity in different countries and regions.

Exploring the Nexus between Moderate-to-Vigorous Physical Activity, Self-Disclosure, Social Anxiety, and Adolescent Social Avoidance: Insights from a Cross-Sectional Study in Central China.

Objectives: Psychological issues among adolescents represent a prevalent challenge in today's society. The purpose of this study is to explore the associations among moderate-to-vigorous physical activity, self-disclosure, social anxiety, and social avoidance in adolescents. Methods: This study collected cross-sectional data from 427 students in eight provincial key junior and senior high schools in the central China region of three provinces using snowball sampling and convenience sampling from July to August 2023. A structural equation model was employed to investigate the relationship between moderate-to-vigorous physical activity and social avoidance among adolescents. Results: The findings indicate that moderate-to-vigorous physical activity is negatively correlated with social anxiety (standardized coefficient = -0.219, p < 0.001) and positively correlated with self-disclosure (standardized coefficient = 0.454, p < 0.001). Social anxiety is negatively correlated with self-disclosure (standardized coefficient = -0.220, p < 0.001). Social avoidance is positively correlated with social anxiety (standardized coefficient = 0.461, p < 0.001) and negatively correlated with self-disclosure (standardized coefficient = -0.331, p < 0.001). Conclusions: The chain-mediated dual-path model between moderate-to-vigorous physical activity and social avoidance is facilitated by social anxiety and self-disclosure. In other words, adolescents who engage in more moderate to high-intensity physical activities exhibit lower levels of social anxiety, and those who have a stronger inclination for self-disclosure tend to demonstrate lower levels of social avoidance. In light of these findings, it is recommended that the government, society, schools, and families collaborate synergistically to promote the holistic well-being of adolescents and advance the development of a healthier China.

CAN FINTECH CURB INCOME INEQUALITY IN CHINA?

The effect of FinTech on income inequality in China and the characteristics of the existing thresholds are examined in this study based on China provincial panel data from 2011 to 2020 by combining dynamic panel differential GMM with panel threshold models. As revealed by this study, (1) FinTech can significantly curb income inequality. (2) FinTech can mitigate income inequality in all regions, and the degree of mitigation is more significant in the central and western regions of China. (3) The improvement of FinTech development can reduce income inequality in all quantiles. The regions with high-income inequality and low-income inequality are compared. The comparison results reveal that FinTech can reduce income inequality to a greater extent in regions with lowincome inequality. (4) FinTech can restrain income inequality under different threshold variables, and the restraining effect of economic growth is the most significant. The policy significance of this study is to fully exploit the empowerment and income-generating role played by FinTech, build a more inclusive financial system, create a good financial environment, cultivate residents’ financial knowledge level, enhance the ability of low-income groups to obtain income from financial services and reduce income inequality, to fulfill the development goal of common prosperity.

How to reach new technological specialisation: The role of related technological capabilities and complementary technological linkages

Technological specialisation is critical for regional development. One region can specialise in new technologies at a lower cost and faster speed by relating to specialised local technologies. Therefore, combined with the theory of path branching, we propose the research hypotheses that related technological capabilities and complementary technological linkages play important roles in the new technological specialisation. Moreover, we perform empirical analysis and test our hypotheses using patent text data on listed firms in China from 2000 to 2020. The results show that the impact of related technological capabilities on new technological specialisation is significantly positive. There is an optimal number of interregional technological linkages that promote new technological specialisation. Too many or too few are detrimental to the specialisation of new technologies. These results remain robust. Further investigation reveals that related technological capabilities and complementary technological linkages can work together to push for new technological specialisation throughout the sample period. However, this is weak in the short term or even insignificant in the central and western regions of China. These findings provide new insights and policy implications for emerging markets regarding reaching new technological specialisation by strengthening regional technological capabilities and collaboration.

The impact of digital financial inclusion on China's regional disparities in the quality of economic development: Based on the relational data paradigm

This study constructs a multi-dimensional evaluation system for the quality of economic development (QED) and measures the QED in 30 provinces of China from 2012 to 2021. The results show that both QED and digital financial inclusion (DFI) exhibit significant differences across space and time. Specifically, QED and the development level of DFI are higher in eastern regions compared to central and western regions of China. Additionally, while regional disparities in DFI show an upward tendency, they are trending downward in QED. Based on the analytical paradigm of relational data, this research investigates the influence of DFI on regional disparities in QED using econometric models of relational data and the quadratic assignment procedure. This research finds that: (1) Regional differences in DFI, including breadth of coverage and depth of usage, positively impact regional disparities in QED when looking at the full sample. (2) Analyzed by region, DFI's regional disparities positively influence QED's regional disparities in the eastern and western regions of China. (3) Compared across years, the impact intensity of DFI on regional disparities in QED exhibits an overall rising trend, with depth of usage rising the most, while the impacts of coverage breadth and digitization degree weaken. This study not only promotes the understanding of the relationship between DFI and QED, but also provides a policy reference for narrowing regional development disparities, promoting coordinated development, and improving the quality of economic development.

The impact of economic uncertainty on carbon emission: Evidence from China

Economic uncertainty (EU) has received greater attention in recent years Based on media data, this research applies the Latent Dirichlet Allocation method to create a new provincial EU index and from panel data of provinces in China examines how EU impacts carbon emissions. The calculations illustrate that province-level EU in the country exerts a significantly positive influence on province-level carbon emissions. A mechanism test indicates that EU raises carbon emissions by harming green technology innovation, enterprise profits, and carbon emission efficiency. Companies hesitantly make decisions, put off innovations, and use cheaper, environmentally-unfriendly materials, and so a moderating test shows that a province's economic level suppresses the impact of EU on carbon emissions whereas foreign direct investment enhances it. Developed areas are more capable of bearing the negative effect from high EU, while foreign companies tend to focus on short-term profit instead of environment protection. Central and northeast regions of China suffer a significant impact from EU on carbon emissions, but the east and west regions incur no obvious change when undergoing EU. The west region is too backwards to see any impact from EU, while the east region is the opposite. Carbon emissions from transportation and industrial production incur a significant impact from EU, but not from daily life activities. Spatial analysis describes that carbon emissions see a significant impact of EU from other provinces. Governments and decision makers should thus give carbon emissions a higher priority, and the case of China is rather applicable to other regions and countries.

Spatiotemporal variations and spillover effects of regional water resources metabolism efficiency with heterogeneous resource endowments

Abstract Scientific evaluation of water resources metabolism efficiency (WME) has essential theoretical and practical value for regional water resources security and sustainable utilization. Based on the framework of the water resources metabolism process and construction of the indicator system of WME, the spatiotemporal variations of WME were analyzed using the weighted summation method in the Eastern, Central, and Western regions of China during the period from 1990 to 2020 with heterogeneous resource endowments. The exploratory spatial data analysis (ESDA) and spatial Durbin model were applied to analyze the spatial autocorrelation patterns and reveal spillovers of the WME. The results show that (1) The WME increased at different speeds in the Eastern, Central, and Western regions from 1990 to 2020 with heterogeneous resource endowment, and the spatial variation of WME in the Eastern and Central regions was significantly higher than in the Western regions. (2) The WME had significant spatial autocorrelation except in 2015, indicating obvious spatial agglomeration characteristics and spatial heterogeneity simultaneously. (3) The spatial spillover effects analysis indicated that the waste virtual recycling use ratio, the ratio of output virtual water and input virtual water, and industrial water ratio were the primary factors influencing WME.

Genomic analysis of lineage-specific transmission of multidrug resistance tuberculosis in China

ABSTRACT Objectives We investigated the genetic diversities and lineage-specific transmission dynamics of multidrug-resistant tuberculosis (MDR-TB), with the goal of determining the potential factors driving the MDR epidemics in China. Methods We curated a large nationwide Mycobacterium tuberculosis (M. tuberculosis) whole genome sequence data set, including 1313 MDR strains. We reconstructed the phylogeny and mapped the transmission networks of MDR-TB across China using Bayesian inference. To identify drug-resistance variants linked to enhanced transmissibility, we employed ordinary least-squares (OLS) regression analysis. Result The majority of MDR-TB strains in China belong to lineage 2.2.1. Transmission chain analysis has indicated that the repeated and frequent transmission of L2.2.1 plays a central role in the establishment of MDR epidemic in China, but no occurrence of a large predominant MDR outbreak was detected. Using OLS regression, the most common single nucleotide polymorphisms (SNPs) associated with resistance to isoniazid (katG_p.Ser315Thr and katG_p.Ser315Asn) and rifampicin (rpoB_p.Ser450Leu, rpoB_p.His445Tyr, rpoB_p.His445Arg, rpoB_p.His445Asp, and rpoB_p.His445Asn) were more likely to be found in L2 clustered strains. Several putative compensatory mutations in rpoA, rpoC, and katG were significantly associated with clustering. The eastern, central, and southern regions of China had a high level of connectivity for the migration of L2 MDR strains throughout the country. The skyline plot showed distinct population size expansion dynamics for MDR-TB lineages in China. Conclusion MDR-TB epidemic in China is predominantly driven by the spread of highly transmissible Beijing strains. A range of drug-resistance mutations of L2 MDR-TB strains displayed minimal fitness costs and may facilitate their transmission.