The objective of this study was to characterise the injury epidemic and injury prevention needs of migrant workers in Shanghai. Cluster random sampling was applied in selecting subjects in migrant gathering areas, and face-to-face interview survey was conducted in this study. In this survey, 1256 migrant workers were included, among which the injury incidence in last one year was 38.3%. The first four injuries were incised and penetrating injury (9.5%), falls (7.2%), traffic injury (6.3%) and burns (5.3%). The injury incidence of male workers was significantly higher than that of female workers (χ(2) = 22.7, P < 0.01). Electricians, safeguards and construction workers were at the highest risk of getting injured. About 60.7% of injury episodes happened at a residence. The longest period of absence from work was up to 3 months due to falls, while the highest medical expense was near 9999 CNY ($1464.2) caused by traffic injury. About 62.9% of migrant workers need services on injury prevention. It is concluded that compared with urban registered residents, migrant workers have significantly higher incidence of injury in Shanghai. Injury prevention services are in urgent demand among the migrant workers.

Injury among migrant workers in Changning district, Shanghai, China.

This paper analyzes and interprets statistical data documenting
changes in China’s urbanization process in term of three elements:
population, economy and society. The results show that the comprehensive
level of urbanization in China reflects the interplay between the continuously
increasing internal migration pattern, from rural to urban, and the accelerated
economic and social urbanization. The ensuing challenges flowing from the
mismatch between residential policy and practices, imbalance between social
and economic development, and population pressures, are discussed in terms
of their longitudinal impact.

Urbanization and Impact of Rural-Urban Migration on Chinese Cities

It is a major aspect of social network analysis to apply data mining techniques to analyze relationship pattern and reveal social phenomena. And the analysis of attack-resistance of national economy is critical to a country and her people's livelihood. Previous studies of attack resistance of social network mainly focus on analyzing the attack effect on the network's connectivity, when a few nodes and edges are removed, for instance the internet attack research. However, the method is not applicable to the social network that is full-connected, such as a population flow network. Therefore, the paper proposes a novel attack evaluation method that considers the changes of nodes' importance before and after the attack. The method is applicable to the more general network. First, we get the number of floating population between all provinces of China based on the 1% national population sample survey in 2005, and the population flow data is used to construct the social network that reflect economical connection between all provinces; Second, the PageRank algorithm is adopted to compute the importance of each regional economy; Third, we analyze the attack resistance of nation economy when random and deliberate attacks at some regional economies and the links of them occur. The experimental results show that the deliberate attack at important province and link is more virtual to national economy.

Study of the attack-resistance of national economy based on data mining analysis of the population flow social network

The economic development of a region is closely related with its population flow from/to other regions. And the regions, which have close relationship of the population flow, usually have a high economic relationship. Therefore, the analysis of the regional population flow can find the potential economic circles. Different from previous methods which are only rely on the analysis of experts to find economic circles, the paper proposes a method based on the weighted complex network clustering algorithm. The method analyzes the economic relationship based on the data of regional population flow. First, we construct the population flow social network according to the 1% national population sample survey in 2005; Second, we analyze the population flow social network using three clustering algorithms that are designed to analyze the weighted complex network; Third, we detect the regional economic circle and compare the result with prior knowledge.

Clustering analysis of regional economy relationship based on the population flow social network

Using the data of 1% national population sample survey 2005 the paper studies and describes geographical distribution and demographic characteristics of the nationwide floating population,together with its employment,right protection.The results are shown as follows: the major of the population is from the less-developed central provinces,floating to the developed eastern and southern coastal provinces;The sex structure of the population is quietly changing with an increase of women proportion;The flow time becomes longer,and some people in fact no longer flow;The vast majority of mobile workers engaged in production,transportation,trade and service,with an average income of about thousand yuan a month.Besides,the population's rate of job contract is low,working hours long,level of social insurance participation low.As the result,the protection of their rights and interests need to be considerably further strengthened.

On China's Floating Population:Based On the Analysis of 1% National Population Sample Survey 2005

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On China's Floating Population:Based On the Analysis of 1% National Population Sample Survey 2005