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We adapted the chord diagram plot to visualize China’s recent inter-provincial migration during 2010–2015. The arrowheads were added to present the direction of the flows. This method allows us to show the complete migration flows between 31 provinces in China including the direction and volume of the flows. The spatial component was also clearly d...
Citations
... Moreover, internal migration after retirement across provinces may also contribute to geospatial disparity in dementia prevalence. Previous studies suggested that the predominant internal migration patterns stem from the Central or Western provinces towards the Eastern China, 50 and as migrants tended to have better health status compared to nonmigrants, 51 this may potentially contribute to decreased dementia prevalence of inflow provinces and increased prevalence of outflow provinces. We didn't identify any inter-provincial migrants among our study sample, while excluding these rural-to-urban migrants within province (13%) did not change the geospatial pattern of dementia identified in our main analysis. ...
Background
Dementia poses great health and social challenges in China. Dementia prevalence may vary across geographic areas, while comparable estimations on provincial level is lacking. This study aims to estimate dementia prevalence by provinces across China, taking into account risk factors of individual level and potential spatial correlation of provinces.
Methods
In this study, 17,176 adults aged 50 years or older were included from the fourth wave of the China Health and Retirement Longitudinal Study (CHARLS 2018), covering 28 provinces, autonomous regions and municipalities. To improve provincial representativeness, we constructed provincial survey weights based on China 7th census (2020). The prevalence of dementia and 95% Bayesian credible intervals (BCIs) were estimated using a Bayesian conditional autoregressive (CAR) model with spatially varying coefficients of covariates.
Findings
The weighted prevalence of dementia at provincial level in China in 2018 ranged from 2.62% (95%BCI: 1.70%, 3.91%) to 13.53% (95%BCI: 8.82%, 20.93%). High dementia prevalence was concentrated in North China, with a prominent high–high cluster, while provinces of low prevalence were concentrated on East and South China, characterized by a low–low cluster. Ordered by the median estimation of prevalence, the top 10% of provinces, include Xinjiang, Jilin, and Beijing. Meanwhile, Fujian, Zhejiang, and Guangdong rank among the last. The association between dementia prevalence and drinking, smoking, social isolation, physical inactivity, hearing impairment, hypertension, and diabetes exhibits provincial variation.
Interpretation
Our study identifies a geospatial disparity in dementia prevalence and risk factor effects across China’s provinces, with high–high and low–low clusters in some northern and southern provinces, respectively. The findings emphasize the need for targeted strategies, such as addressing hypertension and hearing impairment, in specific regions for more effective dementia prevention and treatment.
Funding
10.13039/501100001809National Science Foundation of China/the 10.13039/501100000269Economic and Social Research Council, UK Research and Innovation joint call: Understanding and Addressing Health and Social Challenges for Ageing in the UK and China. UK-China Health And Social Challenges Ageing Project (UKCHASCAP): present and future burden of dementia, and policy responses (grant number 72061137003, ES/T014377/1).
... We used chord diagrams to visualise more detailed flows of patient treatment seeking. Chord diagrams are a visualisation method used in migration studies [40][41][42][43][44] and population health research [45,46] that represents connections between several nodes as curved arcs within a circle. Each node in the chord diagram is a treatment attempt with a certain type of provider (that is, government clinic, private clinic, drug shops/pharmacies, self-treatment) and accounts for whether antibiotics were taken. ...
Background
There is still little empirical evidence on how the outbreak of coronavirus disease 2019 (COVID-19) and associated regulations may have disrupted care-seeking for non-COVID-19 conditions or affected antibiotic behaviours in low- and middle-income countries (LMICs). We aimed to investigate the differences in treatment-seeking behaviours and antibiotic use for urinary tract infection (UTI)-like symptoms before and during the pandemic at recruitment sites in two East African countries with different COVID-19 control policies: Mbarara, Uganda and Mwanza, Tanzania.
Methods
In this repeated cross-sectional study, we used data from outpatients (pregnant adolescents aged >14 and adults aged >18) with UTI-like symptoms who visited health facilities in Mwanza, Tanzania and Mbarara, Uganda. We assessed the prevalence of self-reported behaviours (delays in care-seeking, providers visited, antibiotics taken) at three different time points, labelled as ‘pre-COVID-19 phase’ (February 2019 to February 2020), ‘COVID-19 phase 1’ (March 2020 to April 2020), and ‘COVID-19 phase 2’ (July 2021 to February 2022).
Results
In both study sites, delays in care-seeking were less common during the pandemic than they were in the pre-COVID phase. Patients in Mwanza, Tanzania had shorter care-seeking pathways during the pandemic compared to before it, but this difference was not observed in Mbarara, Uganda. Health centres were the dominant sources of antibiotics in both settings. Over time, reported antibiotic use for UTI-like symptoms became more common in both settings. During the COVID-19 phases, there was a significant increase in self-reported use of antibiotics like metronidazole (<30% in the pre-COVID-19 phase to 40% in COVID phase 2) and doxycycline (30% in the pre-COVID-19 phase to 55% in COVID phase 2) that were not recommended for treating UTI-like symptoms in the National Treatment Guidelines in Mbarara, Uganda.
Conclusions
There was no clear evidence that patients with UTI-like symptoms attending health care facilities had longer or more complex treatment pathways despite strict government-led interventions related to COVID-19. However, antibiotic use increased over time, including some antibiotics not recommended for treating UTI, which has implications for future antimicrobial resistance.
... Hunan Province, where the county is located, has the second-largest domestic floating population in China. Since the reform and opening of China, restrictions on population mobility have been relaxed, and leaving hometowns to work in more prosperous provinces has become a trend among Hunan residents (Qi et al., 2017). The rural resident population of Shuangfeng County has declined from 77% in 2001 to 41% in 2020 (The People's Government of Shuangfeng County, 2021), reflecting the trend of rural depopulation and outflow, which makes it a representative area for studying rural out-migration. ...
In the mobile era, place attachment among rural migrants and returnees has become dynamic and diversified. However, research on place attachment to native place among rural migrants and returnees is limited. The focus of previous research has primarily been on the destination place attachment of rural migrants, which makes it difficult to gain a comprehensive understanding of the place attachment among both rural migrants and returnees. This study aims to investigate the state of place attachment to both native and destination places among rural migrants and returnees originating from the same birthplace. It explores their place attachment after migrating from rural areas to cities. A quantitative research approach was adopted, garnering questionnaire responses from 274 rural migrants and returnees, all born in Shuangfeng County, Hunan Province. The questionnaire encompassed a Likert scale for measuring place attachment, as well as sociodemographic statistical information. Exploratory factor analysis and confirmatory factor analysis were conducted to ascertain the reliability and validity of the questionnaire. Based on the factor scores of place attachment to both places from migrants and returnees, a two-step cluster analysis identified three types of migrants and two types of returnees. Chi-square tests revealed significant differences among migrants in terms of property ownership, educational level, marital status, presence of children, age at departure, and time away from hometown. The study discovered that, regardless of being a migrant or returnee, the overall attachment to hometown was stronger than that to the current or previously inhabited city. In the context of existing literature primarily concerned with the integration of rural migrants into urban areas, this paper offers a fresh research perspective, highlighting the significance of emotional ties to one’s hometown for rural migrants. The findings of this paper provide direction and a theoretical basis for rural areas to attract return migration and for urban regions to facilitate the integration of migrants.
... Chordal graphs have gained significant attention in the study of network topology in recent years [50][51][52]. However, these graphs do not provide a comprehensive representation of the directional and multilevel linkages inherent in complex network connections. ...
The United Nations Sustainable Development Goals (SDGs) and the rise of global sustainability science have led to the increasing recognition of basins as the key natural geographical units for human–land system coupling and spatial coordinated development. The effective measurement of spatiotemporal patterns of urban connectivity within a basin has become a key issue in achieving basin-related SDGs. Meanwhile, China has been actively working toward co-ordinated regional development through in-depth implementation of the Yellow River Basin’s ecological protection and high-quality development. Urban connectivity has been trending in urban planning, and significant progress has been made on different scales according to the flow space theory. Nevertheless, few studies have been conducted on the multiscale spatiotemporal patterns of urban agglomeration connectivity. In this study, the urban network in the Yellow River Basin was constructed using Tencent population migration data from 2015 and 2019. It was then divided into seven distinct communities to enable analysis at both the basin and community scales. Centrality, symmetry, and polycentricity indices were employed, and the multiscale spatiotemporal patterns of urban agglomerations in the Yellow River Basin were identified using community detection, complex networks, and the migration kaleidoscope method. Community connectivity was notably concentrated at the basin scale with a centripetal pattern and spatial heterogeneity. Additionally, there was a symmetrical and co-ordinated relationship in population migration between the eastern and western regions of the basin, as well as between the internal and external parts of the basin. At the community scale, there was significant variation in the extent of central agglomeration among different communities, with few instances of similar-level, long-distance, and interregional bilateral links. The utilization of multiscale spatiotemporal patterns has the potential to enhance the comprehension of economic cooperation between various cities and urban agglomerations. This understanding can aid decision-makers in formulating sustainable development policies that foster the spatial integration of the basin.
... The discussion of migration started with analyze the spatial pattern and direction of population flow [8,[12][13][14]. In China, since the reform and opening up (1978), large numbers of people were pouring into megacities such as Beijing and Shanghai [2]. ...
The purpose of this paper is to explore the spatial heterogeneity of internal migration in China and to discuss the influence of economic, social and environmental characteristics on this demographic process. The overall results suggest that migration in China occurred from inland to coastal areas and from rural areas to urban areas. By stepwise regression, we identified that 9 out of 15 factors with potential influence on internal migration were retained, and the multicollinearity among them was reduced. In addition, we used the OLS and GWR regression analysis to discuss the global and local effects of relevant factors on internal migration. Economic scale (GDP), population concentration (population density) and demographic dividend (labour force proportion) were the three main driving forces of internal migration. In turn, internal migration further widened the gap of economic scale, population agglomeration and demographic dividend between counties and cities. Internal migration in southern coastal areas of China was most affected by economic aspects and demographic dividend. In the central China, the population was more concentrated in high-density cities, while in the eastern regions, areas with high level of education were conducive to immigration, thus forming talent reserve highlands. In the west, areas with highly educated level faced out-migration, which might cause brain drain and widen further the gap in talent reserves between the east and the west in China. From the perspective of location, the net immigration of the provincial capital was accompanied by the net immigration of the surrounding area, which was conducive to the formation of city clusters or urban sprawl. On the other side, the net immigration in prefecture-level cities often meant the net out-migration in surrounding areas. The correlation is particularly strong in eastern coastal provinces.
... In populous China, internal migration serves as a binding thread between provinces that weaves the fabric of regional development and urbanisation (Gu et al., 2019). While current geographical visualisation techniques regarding migration feature the use of the chord diagram to illustrate migration flows between different pairs of origin and destination sites (e.g., Gu et al., 2022;Qi et al., 2017;Abel and Sander, 2014), they are (i) often tricky to render migration with hierarchies, even harder to peruse when regional migration flows run parallel to flows of a higher hierarchy; (ii) sufficient to visualise migration flows but inadequate for inflows and outflows, hindering further recognition of the status of space in migration network; and (iii) typically unapt for the perception of larger numbers of migration bodies. The article proposes a novel migration Kaleidoscope by applying the Voronoi-based Kaleidoscope diagram introduced by the German Federal Statistical Office (2022), combining it with the sunburst treemap (Michael et al., 2022) to deliver visualisation of interprovincial migration patterns. ...
... With data derived from China's latest population censuses and the intercensal 1% national population sample surveys during 1985-2020 (National Bureau of Statistics of China, 2017, 2021), seven migration Kaleidoscope diagrams are generated where each bears the volume of 5 years' in-(deep colour) and out-(light colour) migration of every province, categorised into four economicgeographical regions (Qi et al., 2017). Overall, the interprovincial migration scale of China has been climbing quickly, reaching the climax during 2005-2010 and then taking a gradual return. ...
In migration networks, the origin-destination (OD) bilateral flows and each site's in-and outflow volumes are like two sides of the same coin; though popular visualisation approaches such as the chord diagram excel in describing the former, the latter mostly remains less depicted aspect. By applying the Voronoi-based migration Kaleidoscope diagram and integrating it with the sunburst treemap, the article visualises China's interprovincial migration from 1985 to 2020 with the latest data and focalises on the relative status of each migration body as origin or destination. By attributing different colours to China's four economic-geographical regions and differentiating in-and outflows with deep and light shades, information about each province's weight in the migration network is gained from their size in the diagrams, and variable as well as invariable patterns are observed from the trends. Possible social and economic causes in shaping the diagrams are discussed , and the potential for the migration Kaleidoscope pertaining to other migration data is examined.
... China's unique socioeconomic pathway might also complicate the ecological prediction of cultural change, such as the sizeable internal migrant flow due to rural to urban movement (Qi et al., 2017). In macroeconomics, rural to urban migration is a socioeconomic phenomenon and termed labour migration-people tend to flock to commercial centres for better livelihood (Barbosa et al., 2018;Carling & Collins, 2018). ...
The ecological theory of cultural change suggests that socioeconomic development enhances individualism and weakens collectivism. Yet, collectivism in terms of childcare arrangements seems to persist in rapidly transforming China. It is possible that Confucian ideals and rural to urban migration promoted kin-based cooperation and enhanced collectivism. To explore such possibilities, forty-five caregivers of two generations from an ethnic village located in the Southwest of China were invited to share their childcare arrangements, priorities, and histories. Iterative thematic analyses revealed that improved life quality allowed caregivers the time and resources to attend to children’s personal well-being, whilst socioeconomic potentials and limitations pressured caregivers to cooperate for children’s developments. Emphases on psychological autonomy and relatedness, and material relatedness all increased. Further, regardless of migrant status, grandparents ( n = 24) and parents ( n = 21) readily agreed on childcare cooperation for supporting their children’s education and future mobility. Traditional virtues, such as filial piety, endurance, and sacrifice, fostered caregivers’ reciprocal and kin altruism, proposing the involvement of morality in explaining cultural orientations and changes.
... The chord diagram helps to facilitate comparisons of migration flows amongst different areas and during a serial of periods, providing the size and direction of each unit's flow (Abel and Cohen, 2019;Abel and Sander, 2014;Qi et al., 2017). Applying the updated migest package in R (Abel, 2013), we arrange the 20-year ISM flows into four diagrams by a five-year interval with the top 30 regions and propose a seminal framework by attributing conclusive names to In phase A (1999-2003), almost all ISM flows terminated at the US, UK, France, Australia and Canada (62.69%), as if they were the main "arteries" of the body, with other European countries like Spain, Belgium, Austria, Switzerland and Italy acting as smaller "branches" (9.96%). ...
The flows of international students are like the currents of the oceans, not only affecting the individuals adrift in them but the global circulation of policy, economics and academics as a whole, bearing pros and cons for each country or region along the way. To date, there has not been a detailed and elaborate description of the fluxes of international students over decades. In light of the research gap, the article utilises the chord diagram to draw threads between each pair of origin and destination of international students in the last 20 years and divides the periods into four main phases. With each phase exhibiting its specific features, we have tentatively concluded that the global student mobility structure has evolved from Arterial (1999–2003), Breakthrough (2004–2008) to Catch-Up (2009–2013), and lastly, Diversification (2014–2018). Corresponding reasons underpinning each change of the migration flows are also discussed briefly in the article.
... Importantly, color should ref lect an attribute that is thought to correlate with the ordering attribute; otherwise, they are difficult to read. Chord diagrams have been frequently used to visualize population movements ( Qi, Abel, Muttarak, & Liu, 2017 ). ...
Disaster survivors and scholars alike argue that the presence, dearth, and type of social ties in a community can enable or limit disaster adaptation, response, evacuation, and recovery. After Hurricane Katrina struck New Orleans in 2005, the Vietnamese American community returned and rebuilt more quickly than other damaged areas in the city, relying on the strength of their local co-ethnic and religious neighborhood ties, rather than limited finances or education ( Aldrich, 2012 ). Likewise, after Japan’s 2011 earthquake, tsunami, and nuclear disaster, prefectures with greater bridging ties aid and governmental organizations recovered faster ( Bisri, 2016 a, 2016b; Aldrich, 2019 ). Increasingly, scholars and policymakers see social networks as playing a key role in disaster evacuation, recovery, and resilience. But what kinds of networks can we examine in disaster studies? What kinds of data do we need, what kinds of questions can we answer about these networks, and what tools might students and scholars of disaster studies use to answer these questions?
This chapter seeks to make social network analysis methods accessible to students and scholars of disaster policy. Using a network of disaster reconstruction committee members from our own research, we demonstrate different techniques for network visualization, analysis, and statistics. First, we introduce readers to the logic and types of networks they may encounter, drawing from recent examples. Second, we lay out a process for analyzing networks, describing centrality measures, visualization, and statistical models. These techniques predominantly use R. These accessible techniques allow us to identify what kinds of social ties affect recovery and how we can leverage these to improve disaster outcomes.
... Based on gross flow data instead of net rates, multi-regional population forecast can improve the accuracy of population prediction (Rogers 2015), and its prediction results aggregated to geographical regions are probably more compatible with GIS software. Recent years have witnessed some improvements in the field of multi-regional population forecast, such as a new type of multi-regional forecast model using place of birth data (Abel 2013) and the visualization of population prediction results by the method of chord diagram plot (Abel and Sander 2014;Qi et al. 2017). ➂ Population and environment. ...
Demographic research involves the study of demographic processes and outcomes that take place in space. As space is an important element of demographic research, a number of scholars have begun studying demographic issues from the spatial perspective since last century and achieved progress to some extent, while the concept of Spatial Demography hasn’t emerged until 2007. With the continuous improvement of computer and spatial analysis technology based on GIS, Spatial Demography has gained booming development to sophistication and systematism. After elucidating the origin and development of Spatial Demography, this study systematically reviews recent research progress on Spatial Demography from the perspectives of differentiation and isolation, birth and death, migration and urbanization, regional population forecast, population and the environment, as well as spatial analysis technique and its application, thus providing an outlook of the future of Spatial Demography, which will present some enlightenment for the development of Spatial Demography.
