Dataset Information

Measuring directional urban spatial interaction in China: A migration perspective.

ABSTRACT: The study of urban spatial interaction is closely linked to that of economic geography, urban planning, regional development, and so on. Currently, this topic is generating a great deal of interest among researchers who are striving to find accurate ways to measure urban spatial interaction. Classical spatial interaction models lack theoretical guidance and require complicated parameter-adjusting processes. The radiation model, however, as proposed by Simini et al. with rigorous formula derivation, can simulate directional urban spatial interaction. We applied the radiation model in China to simulate the directional migration number among 337 nationwide research units, comprising 4 municipalities and 333 prefecture-level cities. We then analyzed the overall situation in Chinese cities, the interaction intensity hierarchy, and the prime urban agglomerations from the perspective of migration. This was done to ascertain China's urban spatial interaction and regional development from 2000 to 2010 to reveal ground realities.

SUBMITTER: Li F

PROVIDER: S-EPMC5283794 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Measuring directional urban spatial interaction in China: A migration perspective.

Li Fangzhou F Feng Zhiming Z Li Peng P You Zhen Z

PloS one 20170131 1

The study of urban spatial interaction is closely linked to that of economic geography, urban planning, regional development, and so on. Currently, this topic is generating a great deal of interest among researchers who are striving to find accurate ways to measure urban spatial interaction. Classical spatial interaction models lack theoretical guidance and require complicated parameter-adjusting processes. The radiation model, however, as proposed by Simini et al. with rigorous formula derivati ...[more]

PMID: 28141853

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Project description:Atmospheric fine particulate matter (PM2.5) causes severe haze in China and is regarded as a threat to human health. The health effects of PM2.5 vary location by location due to the variation in size distribution, chemical com position, and sources. In this study, the cytotoxicity effect, oxidative stress, and gene expression regulation of PM2.5 in Chengdu and Chongqing, two typical urban areas in southern China, were evaluated. Urban PM2.5 in summer and winter significantly inhibited cell viability and increased reactive oxygen species (ROS) levels in A549 cells. Notably, PM2.5 in winter exhibited higher cytotoxicity and ROS level than summer. Moreover, in this study, PM2.5 commonly induced cancer-related gene expression such as cell adhesion molecule 1(PECAM1), interleukin 24 (IL24), and cytochrome P450 (CYP1A1); meanwhile, PM2.5 commonly acted on cancer-related biological functions such as cell-substrate junction, cell-cell junction, and focal adhesion. In partic ular, PM2.5 in Chengdu in summer had the highest carcinogenic potential among PM2.5 at the two sites in summer and winter. Importantly, cancer-related genes were uniquely targeted by PM2.5, such as epithelial splicing regu latory protein 1 (ESRP1) and membrane-associated ring-CH-type finger 1 (1-Mar) by Chengdu summer PM2.5; collagen type IX alpha 3 chain (COL9A3) by Chengdu winter PM2.5; SH2 domain-containing 1B (SH2D1B) by Chongqing summer PM2.5; and interleukin 1 receptor-like 1 (IL1RL1) and zinc finger protein 42 (ZNF423) by Chongqing winter PM2.5. Meanwhile, important cancer-related biological functions were specially induced by PM2.5, such as cell cycle checkpoint by Chengdu summer PM2.5; macromolecule methylation by Chengdu win ter PM2.5; endoplasmic reticulum-Golgi intermediate compartment membrane by Chongqing summer PM2.5;and cellular lipid catabolic process by Chongqing winter PM2.5. Conclusively, in the typical urban areas of southern China, both summer and winter PM2.5 illustrated significant gene regulation effects. This study contrib utes to evaluating the adverse health effects of PM2.5 in southern China and providing public health suggestions for policymakers.

Project description:BackgroundHuman migration facilitate the spread of tuberculosis (TB). Migrants face an increased risk of TB infection. In this study, we aim to explore the spatial inequity of sputum smear-positive pulmonary TB (SS + PTB) in China; and the spatial heterogeneity between SS + PTB and internal migration.MethodsNotified SS + PTB cases in 31 provinces in mainland China were obtained from the national web-based PTB surveillance system database. Internal migrant data were extracted from the report on China's migrant population development. Spatial autocorrelations were explored using the global Moran's statistic and local indicators of spatial association. The spatial variation in temporal trends was performed using Kulldorff's scan statistic. Fixed effect and spatial autoregressive models were used to explore the spatial inequity between SS + PTB and internal migration.ResultsA total of 2 380 233 SS + PTB cases were reported in China between 2011 and 2017, of which, 1 716 382 (72.11%) were male and 663 851 (27.89%) were female. Over 70% of internal migrants were from rural households and had lower income and less education. The spatial variation in temporal trend results showed that there was an 9.9% average annual decrease in the notification rate of SS + PTB from 2011 to 2017; and spatial clustering of SS + PTB cases was mainly located in western and southern China. The spatial autocorrelation results revealed spatial clustering of internal migration each year (2011-2017), and the clusters were stable within most provinces. Internal emigration, urban-to-rural migration and GDP per capita were significantly associated with SS + PTB, further, internal emigration could explain more variation in SS + PTB in the eastern region in mainland. However, internal immigration and rural-to-urban migration were not significantly associated with SS + PTB across China.ConclusionsOur study found the spatial inequity between SS + PTB and internal migration. Internal emigration, urban-to-rural migration and GDP per capita were statistically associated with SS + PTB; the negative association was identified between internal emigration, urban-to-rural migration and SS + PTB. Further, we found those migrants with lower income and less education, and most of them were from rural households. These findings can help stakeholders to implement effective PTB control strategies for areas at high risk of PTB and those with high rates of internal migration.

Dataset Information

Measuring directional urban spatial interaction in China: A migration perspective.

Publications

Measuring directional urban spatial interaction in China: A migration perspective.

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