Disparities In China Research Articles

Socio–Economic Disparities in Dental Health and Dental Care Utilisation Among Older Chinese

IntroductionDental care is mostly excluded from healthcare coverage in China. This study examines disparities in dental care and in the costs of such care, according to insurance type and socio–economic status, among Chinese older adults. MethodsThe data were obtained from the 2015 China Health and Retirement Longitudinal Study (CHARLS). A final sample of 5,230 respondents was included, with a mean age of 72 years. Edentulousness, any dental visit and per-patient dental care expenditure were used as outcome variables. Both unweighted and weighted logistic regression analyses were used to examine the association of socio–economic status (education, insurance type and income) associated with edentulousness and use of dental care. ResultsWe found that 28% of Chinese older adults have no remaining teeth and that only 19% had used dental care in the past year. The uninsured and those with rural resident insurance had edentulousness rates of 31%, while the edentulousness rate in those with urban employee insurance was 19%. About 13% of the uninsured study respondents and 15% of those with rural resident insurance had used dental care compared with 30% of those with urban employee insurance. Those in the highest income and education groups and those enrolled in a plan with a lower coinsurance rate had a higher likelihood of using dental care services and spending more on dental care than did those in the lowest socio–economic groups. ConclusionsDental care disparities in China may be reduced through increasing the proportion of the population with insurance and expanding the range of dental treatments covered by all three major insurance schemes.

What Drove Housing Wealth Inequality in China?

AbstractAlthough China is experiencing a deterioration in wealth distribution where housing is playing a dominant role, this issue has received scant research attention despite its importance. Combining four rounds of the China Household Finance Survey (CHFS) data, this paper measures and discusses wealth inequality in China, with a special emphasis on the contribution of housing. Our analysis reveals that housing is the largest contributor to wealth inequality, responsible for around 70 percent of total wealth inequality, and its contribution has been increasing over time. Our research efforts have focused on the housing wealth disparity, exploring its composition from alternative perspectives. The results show that housing wealth inequality has also been rising over time and an absolute majority of housing wealth inequality is due to within‐group gaps. Finally, we employ Wan's (2004) regression‐based decomposition methodology to quantify the contributions of different determinants to housing wealth disparity in China, and to demonstrate serious biases in the conventional approach that is often used to analyze housing wealth inequality.

Urban-Rural Mental Health Disparities in China: The Neighborhood Effects

This paper intended to explore the neighborhood effects on mental health disparities of urban and rural residents in Mainland China. Data were drawn from the CHARLS baseline (2011). The sample included 450 neighborhoods, with 3907 urban residents and 13,391 rural residents older than 45 years old. Multilevel model was used to determine the neighborhoods’ effects and individual effects on depressive symptom scores (CES-D). Independent variables included social activities, health status, and demographic characteristics. The result reveals three context effects of urban-rural neighborhoods: first, people living in urban communities reported better physical health, higher educational levels, and lower depressive symptoms than their rural counterparts. Second, people living in urban communities are more engaged in social activities than people living in rural villages. Third, the urban neighborhoods present more variations in depressive symptoms and social activities than the rural neighborhoods.

Do socioeconomic factors modify the effects of PM1 and SO2 on lung cancer incidence in China?

BackgroundIt remains uncertain whether socioeconomic factors modify the effect of air pollution on human health. Moreover, studies investigating socioeconomic modifying roles on the effect of PM1 are quite limited, especially in developing countries. ObjectivesThe present study aims to investigate socioeconomic modification effects on the associations of the incidence rate of male lung cancer with ambient PM1 and SO2 in China. MethodsWe conducted a nationwide analysis in 345 Chinese counties (districts) between 2014 and 2015. In terms of multivariable linear regression models, we examined the modification effects of urban-rural division, education level and proportion of construction workers in the stratified and combined datasets according to the tertile and binary divisions of the three factors. Moreover, we performed three sensitivity analyses to test the robustness of socioeconomic modification effects. ResultsWe found a larger effect of PM1 on the incidence rate of male lung cancer in urban areas than in rural areas. The association between PM1 (or SO2) and the incidence rate of male lung cancer was stronger in counties with low education levels than in those with high education levels. The findings of the significant modification effects of urban-rural division and education level were robust in the three sensitivity analyses. No significant modification effect was observed for the proportion of construction workers. ConclusionsMale residents in urban areas have a high risk of lung cancer incidence associated with ambient PM1. Male residents with low education levels suffer from larger effects of PM1 and SO2 on the incidence rate of lung cancer. Area- and population-specific strategies should be developed to reduce the urban-rural and educational disparities in air pollution effects, which thereby alleviates air pollution-associated health disparities in China.

Regional distribution and clinicopathological characteristics of Epstein-Barr virus associated gastric cancer

Objective: To investigate regional distribution and clinicopathological features of Epstein-Barr virus associated gastric cancer (EBVaGC). Methods: Epstein-Barr virus encoded RNA (EBER)was detected in 4 081 cases of gastric adenocarcinoma in Cancer Hospital, Chinese Academy of Medical Sciences by using in situ hybridization. EBVaGCs were identified and their proportions in different provinces, autonomous regions and municipalities were compared. The correlation between EBVaGC and clinicopathological features was also analyzed. Results: A total of 3.0% (123/4 081) patients with gastric adenocarcinoma are EBVaGCs. Among the areas with cases more than 90, the highest proportion of EBVaGC was found in Jilin province, accounting for 7.6%, and then followed by 5.4% in Liaoning province, 4.1% in Anhui province, 3.9% in Beijing, 3.7% in Inner Mongolia Autonomous Region, 3.4% in Shanxi province, 3.0% in Heilongjiang province, 2.1% in Shandong province, 1.6% in Hebei province, and no EBVaGC was found in Henan province. EBVaGC proportions are significantly different in these provinces, autonomous regions and municipalities (P<0.05). Multivariate analysis of logistic regression revealed that gender (OR=2.231, 95%CI: 1.290~3.858), WHO classification (OR=2.338, 95%CI: 2.051~2.664) and N stage (OR=0.420, 95%CI: 0.284~0.621) were independent impact factors for EBVaGC. The proportion of EBVaGC was higher in males, gastric carcinomas accompanied with lymphoid stroma and patients without lymph node metastasis. Conclusions: The proportion of EBVaGC in gastric adenocarcinoma displays area distribution disparity in China. The gender, WHO classification and N stage are closely associated with EBVaGC.

China's Economic Growth and Financial Development after Reform and Opening-up

In this paper, I analyze China's economic growth and financial development after 1978's reform and opening-up, and verify whether convergence hypothesis and financial deepening hypothesis exist by using the provincial data from 1978 to 2014. The main contribution is that I examine regional disparities in China's economic growth and financial development by period, consider the effects of Deng Xiaoping's Southern Tour Talks in 1992 and China's accession to the WTO in 2001 on regional economic growth and financial development. The empirical analyses clarify that the convergence hypothesis is valid for the whole sample period of 1978–2014 and the sub-period 2002–2014. Analyses of economic convergence reveal that the poorer provinces have tended to show higher rates of economic growth than the richer provinces during the period 1978–2014, particularly after China's accession to the WTO in 2001. On the other hand, the financial deepening hypothesis only appears to be valid to the whole period of 1978–2014, which means that the provinces with larger financial sectors have tended to show higher rates of economic growth than the provinces with smaller financial sectors over the long term, but this was not valid for any of the sub-periods considered (1978–1991, 1992–2001, and 2002–2014) due to reforms of SOEs, diversification of corporate financing methods, and changes in China's economic and financial situation, which prevented bank loans from making a positive impact on economic growth during any one of the sub-periods.

China's agricultural GHG emission efficiency: regional disparity and spatial dynamic evolution.

Improving China's agricultural greenhouse gases (GHG) emission efficiency has become an important way to cope with climate change in an ecologically-and ethically responsible manner. In this paper, we use a global slacks-based inefficiency model to evaluate the agricultural greenhouse gases (GHG) emission efficiency levels in China during 2000-2015. The regional disparity of China's GHG emission efficiency is examined by using a Dagum Gini coefficient. A spatial Markov chain technique is also employed to investigate the spatial dynamic evolution of agricultural GHG emission efficiency. The results show that: (1) China's agricultural GHG emission efficiency increased steadily during the study period; a certain gap in efficiency among provinces and regions also exists. (2) Between-group disparity is the main source of the overall regional disparities in China's agricultural GHG emission efficiency. The disparities between regions are on the rise, while the disparities within regions are relatively stable. (3) China's agricultural GHG emission efficiency demonstrates significant spatial dependence. This study provides policy implications for the sustainable development of China's agricultural sector.

Estimating dynamic interactive linkages among urban agglomeration, economic performance, carbon emissions, and health expenditures across developmental disparities

This work analyzed the dynamic interactive causal links among urban agglomeration, economic performance, carbon emissions, and health expenditures across developmental disparities in China. To this end, this work developed a health expenditures-augmented growth model to introduce health expenditures and carbon emissions as a shift factor of total factor productivity. A block of simultaneous equations is developed based on the health expenditures-augmented growth modeling framework. The System-variant/Difference-variant Generalized Method of Moments is employed to estimate the block of simultaneous equations in order to deal with the potential endogeneity of the variables used. Based on empirical results, the core findings are as follows: first, a Pendroni cointegration-based long-run stable association is verified. Second, the urban agglomeration exhibited a bidirectional positive causal linkage with the gross domestic product (GDP) growth and health expenditures growth. Third, the health expenditures growth demonstrated a bidirectional positive causal linkage with carbon emissions growth and GDP growth. Fourth, a unidirectional mixed causal linkage—positive (negative) for linear form (squared form) of urban agglomeration—existed from urban agglomeration to carbon emissions growth. Fifth, there is a negative causal linkage operating from carbon emissions growth to GDP growth. However, there is mixed causal linkage—positive for a linear form of GDP growth, and negative for the squared form of GDP—operating from GDP growth to carbon emissions growth. These findings exhibited consistency in the type of causal linkages across the developmental disparities and hence showed robustness. Nevertheless, the findings showed disparities in the degree of impact across the developmental disparities. In this regard, the strength of causal linkage is the largest (moderate/lowest) for highly (moderately/least) developed regions of China. Based on empirical results, inferences are extracted and discussed.

Impacts of high-speed railways on economic growth and disparity in China

China's high-speed railways (HSRs) networks have dramatically expanded since 2008, which is widely believed to have promoted economic growth. This study empirically tests this hypothesis and analyses the impact of HSRs on economic disparity between 2002 and 2016 in China using a spatial econometric model. The results confirm the role of HSRs as a driving force in promoting local economic growth, although the spill-over effect is found to be insignificant. However, the cross-city analysis suggests there are heterogeneous effects of HSRs on economic growth. By dividing the sample into small-medium cities and large-mega cities, as well as least-developed, developing, and developed cities, this study finds that HSRs make a significant positive contribution to economic growth in large-mega cities and developed cities but has insignificant effects in other cities. The results indicate that HSRs can widen economic disparity in China. Our findings not only advance the understanding of the role of HSRs in promoting China’s economic growth but also provide insights for planning future HSR networks. This study concludes that each city should reasonably plan its HSR network to promote economic growth and reduce economic disparity by accounting for different resource endowments, especially geographic and population factors.

Regional economic development, household income, gender and hypertension: evidence from half a million Chinese

BackgroundHypertension may be influenced by multiple factors, including social and individual determinants. Regional and individual economic disparity in China is closely associated with such factors that may give rise to diverse health outcomes. This study examines the relationship between regional economic development, household income, gender and hypertension prevalence in China.MethodsThis study utilized data from the China Kadoorie Biobank (CKB), a population-based study on half a million Chinese adults from 10 geographically distinct regions. Hypertension was identified by a measured systolic blood pressure/diastolic blood pressure ≥ 140/90 mmHg or receiving treatment. Regional economic development was inferred from GDP per capita at the time of the study. A logistic regression based method was used in calculating the prevalence of hypertension in different household income, regional economic development, and gender groups, adjusting for demographic, social-economic and lifestyle factors.ResultsThe prevalence of hypertension was the lowest in the medium GDP per capita areas in both male (31.62, 95% CI: 31.26–31.98%) and female (22.85, 95% CI: 22.50–23.19%) as compared to that in the low GDP per capita regions (male: 32.75, 95% CI 32.41–33.08%; female: 32.12, 95% CI: 31.78–32.47%) and high GDP per capita areas (male: 39.74, 95% CI: 39.33–40.16%; female: 35.19, 95% CI: 34.74–35.65%). There was an inverse relationship between hypertension and household income in the low and high GDP areas and an U-shaped association in the medium GDP per capita areas. Higher hypertension prevalence was observed in males across all GDP per capita areas. The negative correlation between hypertension and household income (across all GDP per captia areas) was stronger in females than in males.ConclusionsThe present study underlined the important influence of regional economic development, household income and gender on hypertension. Interventions for hypertension prevention and management should take into consideration the influence of sex difference and socioeconomic disparities at both micro- and macro- levels, in addition to a person-centered approach.

Distribution dynamics of China’s regional housing price disparity

ABSTRACT Based on the methods of distribution dynamics analysis, this study estimates the regional housing price disparity across China’s eastern, central and western regions. Analysis from decomposition of housing price growth rate by subgroup indicates that the disparity is largely due to intra-regional rather than inter-regional differences. Eastern region contributes the most to the disparity of housing prices, followed by the Central region and the Western region. Ergodic distributions reveal that Eastern region with housing price growth rates from 4% to 7% tend to move upwards in the coming period, while in the Central and Western regions housing prices tend to converge to no change of housing prices. Mobility probability plot result further suggests that medium sized housing may have higher probability for price growth. The findings help better understand the regional disparity of housing price in China, an issue that has largely been neglected. Long-standing inequality across regions can exert adverse impact on poverty reduction, economic development, and even social stability. The research implications will enable scholars and policymakers to rethink the impact of homeownership financialization when discussing and designing housing policies. Highlights This paper uses distribution dynamics analysis to study the housing price disparity in China. Ergodic distributions reveal that Eastern region has upward housing price trend. Ergodic distributions reveal that Central and Western regions have converged housing prices. Mobility probability plots reveal that medium sized housing tends to have more price growth.

Regional carbon imbalance within China: An application of the Kaya-Zenga index

Considering the enlarging inter-provincial disparities in China as regards carbon emissions and carbon intensity (carbon emissions per unit gross domestic product), this paper is the first study to investigate the inter-provincial carbon imbalance by constructing and employing the Kaya-Zenga index. We use China's panel data of provincial-level carbon emissions over 1995–2016 to quantitatively measure the levels of inter-provincial imbalance and polarization in carbon emissions and carbon intensity. Further, we decompose the Kaya-Zenga index into different contributing factors both regionally and structurally and perform a scenario analysis to identify the corresponding regionally differentiated countermeasures regarding carbon emission reduction. The results show that the imbalance in carbon emissions is mainly caused by imbalances in population scale and income level, while the imbalance in carbon intensity predominantly results from imbalances in energy efficiency and energy mix. In addition, for heavy manufacturing provinces, the respective emission-reduction strategy should aim at lowering energy intensity through local technology improvement and inter-regional technology transfer. For light manufacturing and high technology provinces, carbon emission reduction is harder to be achieved; however, a mix of policies of improving energy efficiency, optimizing energy mix, and industrial upgrading should be implemented. The results of the scenario analysis indicate that reducing imbalance in carbon intensity under different scenarios can lead to a substantial reduction in carbon emissions (up to 10%).

Associations of Dietary Sodium, Potassium, and Sodium to Potassium Ratio with Blood Pressure- Regional Disparities in China.

High dietary sodium and low potassium intake increase blood pressure and risk of hypertension, but whether the relationship between dietary sodium and potassium and risk of hypertension is different in North China and South China remains unclear. We used data from the longitudinal China Health and Nutrition Survey (CHNS) and selected 6705 adults who participated in at least two waves in 2009, 2011, and 2015 and had no hypertension in baseline. We performed multiple linear regression analysis and multiple logistic regressions stratified by area for the present study design. Sodium and potassium intake were higher in North China (4343.4 and 1624.8 mg/day, respectively) than in South China (4107.8 and 1516.1 mg/d, respectively) (p < 0.05). Multiple linear regression revealed that a positive correlation of sodium intake (β = 0.026, p < 0.05) and ratio of sodium to potassium (Na-K) intake (β = 0.041, p < 0.01) with diastolic blood pressure (DBP) was found in North China, and the association of sodium, potassium, and Na-K intake ratio with blood pressure was different in South China. Multiple logistic regressions documented a similar significant inverse association between dietary potassium intake and risk of hypertension in both North China and South China (risk ratio (RR): 0.63, 95%CI: 0.50–0.79; RR: 0.80, 95%CI: 0.66–0.98, respectively). The risk of hypertension increased in the fourth quartile of dietary sodium and Na-K intake ratio (RR: 1.20, 95%CI: 1.00–1.44; RR: 1.35, 95%CI: 1.13–1.62, respectively) in North China but no association was observed in South China. The current study indicates a different association of dietary sodium and Na-K intake ratio with systolic blood pressure (SBP), DBP, and risk of hypertension in North China and South China.

Provincial cultivated land use efficiency in China: Empirical analysis based on the SBM-DEA model with carbon emissions considered

Rapid urbanization and industrialization has worsened the situation of the scarce cultivated land resources of China. It's therefore of great importance for sustainable development based on the systematic evaluation on cultivated land use efficiency (CLUE). This study took carbon emissions resulting from cultivated land use into the measurement framework of CLUE, and a slack-based measure (SBM) model with undesirable outputs, boxplot, kernel density estimation and Tobit regression model are adopted for the analysis of 31 provinces in China from 2000 to 2017. The results showed that there was an increasing trend in CLUE in China from 0.5236 in 2000 to 0.8501 in 2017, with the growth rate of 38.40%. Most of provinces in China have much lower levels of CLUE with significantly spatial disparities. In particular, Hainan, Chongqing, Sichuan and Guizhou are always most efficient with the highest value of 1. At the regional level, the average value of CLUE in the northeastern region is the highest, followed by the western, eastern and central regions, and the CLUE in the eastern region is more unstable than the other three regions. The results of Tobit regression show that natural conditions, cultivated land resource endowments, agricultural production conditions, regional economic development and regional science and technology development are important factors resulting in the disparity of China's CLUE.

Analysis of environment influencing factors in China based on STIRPAT model

Since the reformation and the opening-up policy in 1978, China has achieved a high economic growth for about 30 years. However, the problem of economic disparity in China has been worsened than ever before, and the environment inequality is beginning to be more noticeable. China faces the challenge this environmental inequality. In this paper, we first calculated the Green Contribution Coefficient in the 31 provinces in 2000 and 2014, and then clarified the fact that there existed regional environmental inequality in China. Based on the STIRPAT model, various factors affecting environmental in China from 2000 to 2014 were analyzed by the regression analysis, using the panel data on industrial air pollution published by each ministry. We examined the hypothesis that the increase in GDP, secondary industry ratio, the energy industry investment has a negative influence on Chinese environment. The environmental inequality is to be balanced by the progress of industrial structures in the various regions of China.

Regional efficiency disparities in China’s construction sector: A combination of multiregional input–output and data envelopment analyses

As a major contributor to the increasing adverse environmental impact worldwide, China’s construction industry faces major challenges in energy conservation. Improving energy utilization efficiency is an effective method for mitigating energy-intensive problems induced by this industry. Accordingly, this study combined a multiregional input–output model with data envelopment analysis to assess the energy efficiency of China’s construction industry at the provincial level. Results show that the majority of the provincial construction sectors in China are energy inefficient and the performance of energy efficiency is highly related to the level of regional economic development. Scale efficiency is comparatively high in the regional construction sectors, but technical aspects are lagging behind. Moreover, cross-regional energy allocation demonstrates higher efficiency than that of the energy structure. The inefficient utilization of unclean and clean energy can be attributed to the lack of required instruments that can facilitate clean production processes in the construction field. To solve these problems, this study presents corresponding governmental measures and market-driven strategies from the institutional, technical and management aspects. The findings of this study can provide a holistic understanding of the current efficiency status of the construction industry and help decision makers stratify regional energy conservation targets at the industrial level.

The Psychometric Properties of the Chinese eHealth Literacy Scale (C-eHEALS) in a Chinese Rural Population: Cross-Sectional Validation Study.

BackgroundThe eHealth Literacy Scale (eHEALS) is the most widely used instrument in health studies to measure individual’s electronic health literacy. Nonetheless, despite the rapid development of the online medical industry and increased rural-urban disparities in China, very few studies have examined the characteristics of the eHEALS among Chinese rural people by using modern psychometric methods. This study evaluated the psychometric properties of eHEALS in a Chinese rural population by using both the classical test theory and item response theory methods.ObjectiveThis study aimed to develop a simplified Chinese version of the eHEALS (C-eHEALS) and evaluate its psychometric properties in a rural population.MethodsA cross-sectional survey was conducted with 543 rural internet users in West China. The internal reliability was assessed using the Cronbach alpha coefficient. A one-factor structure of the C-eHEALS was obtained via principal component analysis, and fit indices for this structure were calculated using confirmatory factory analysis. Subsequently, the item discrimination, difficulty, and test information were estimated via the graded response model. Additionally, the criterion validity was confirmed through hypothesis testing.ResultsThe C-eHEALS has good reliability. Both principal component analysis and confirmatory factory analysis showed that the scale has a one-factor structure. The graded response model revealed that all items of the C-eHEALS have response options that allow for differentiation between latent trait levels and the capture of substantial information regarding participants’ ability.ConclusionsThe findings indicate the high reliability and validity of the C-eHEALS and thus recommend its use for measuring eHealth literacy among the Chinese rural population.

Regional disparity and dynamic evolution of carbon emission reduction maturity in China’s service industry

Abstract As a vital source of carbon emissions, the carbon emission reduction in service industry and its spatial and temporal distribution are of great significance to promote the green development of the service industry, however, there is a lack of research on carbon emission reduction maturity (CERM) and the spatial mechanism of the regional disparity in China’s service industry. To address this problem, we select the basic index of service industry CERM based on the Kaya identity, measure the CERM in China’s service industry from 2006 to 2015 by using a grey relational model, and analyse the spatial pattern of its evolution by applying the spatial auto-correlation method. The results show that: the average level of CERM in China’s service industry is between 0.379 and 0.766, which shows a spatial imbalance. Provinces with high maturity are found in eastern coastal areas, and on the contrary, those with low maturity are found in the western district where the economy is less developed, which shows a decreasing tendency from coastal regions to inland and from eastern areas to the middle and western areas. From the spatial auto-correlation perspective, service industry CERM in China shows spatial aggregation. Neighbouring regions with similar maturity influence each other and produce obvious spatial spillover effects and the spatial disparity tends to decrease.

Heterogeneous health classes for older adults and their regional disparities in China: based on multidimensional health

ObjectivesChina is currently facing an unprecedented complex health demand from a rapidly aging population. Based on multidimensional health, this study aimed to identify heterogeneous latent health classes for older Chinese people, and assess regional disparities and associated sociodemographic factors. Study designChinese Longitudinal Healthy Longevity Survey in 2014 was adopted. MethodsFor 2886 participants aged 65 years and more without missing health indicators in physical, psychological, and social dimensions, latent class analysis was used to identify heterogeneous health. For 2128 participants with complete information, logistic regressions were used to examine how regional divisions and sociodemographic factors impact each identified class. ResultsFour classes were identified and labeled as ‘Lacking Socialization’ (17.4%), ‘High Comorbidity’ (13.7%), ‘Functional Impairment’ (7.1%), and ‘Relative Health’ (61.8%). When the Relative Health class was the reference, the likelihoods of the High Comorbidity and Functional Impairment classes were higher for older adults in eastern and central regions than in western regions. Those in eastern regions also tended to be in the Lacking Socialization class than in western regions. The effects of regional divisions on the different classes were significantly impacted by sociodemographic characteristics. ConclusionsFour health classes identified by multidimensional health have enhanced our understanding of heterogeneity among older Chinese people. By examining regional disparities in China, our study provided evidence for health policies addressing the issue of aging with respect to regional disparities.

Is polycentricity a promising tool to reduce regional economic disparities? Evidence from China’s prefectural regions

Although polycentrism is widely regarded by city planners and policymakers as a potential solution for reducing regional disparities, there is currently little empirical basis for accepting or rejecting this claim. Our study aims to fill this empirical gap by providing reliable evidence as to whether or not a polycentric urban structure can reduce regional economic disparities. However, we reach a counter-intuitive result: monocentricity, from the morphological perspective, is robustly associated with less territorial economic disparity in China’s prefectural regions. Further analyses illustrate that the core cities in monocentric regions can share the benefits of agglomeration through labor mobility, and monocentricity does not introduce an extra agglomeration shadow. Meanwhile, cities within polycentric regions may not “borrow” as much function or performance from each other as expected. These results suggest that polycentric-oriented spatial strategy, at least in terms of morphology, may not be an appropriate policy to enhance cohesion in China.