Suchergebnisse

The rapid urbanisation of China has increased public awareness of rising housing prices, particularly in large and medium-sized cities. The popularisation of the Internet in China has driven a shift in the public's attention to housing prices, moving from geographic space to cyberspace. Based on web search engine data using geotag, this paper attempts to create a better visualisation of the shift in the public's attention to housing prices from the perspectives of geographic space and cyberspace. Intercity interaction is also analysed in the context of cyberspace-based urban networks, through hybrid featured graphics. Specifically, data regarding public attention to housing prices are gathered (via queries data through Baidu Index) in 363 Chinese cities. The data are divided into a local city housing price attention index and an offsite city housing price attention index. Second, public attention flows are presented using origin-destination flows maps, chord diagrams and violin diagrams. These hybrid feature graphics show the interrelationship between cities and the complexity of public attention flows. This information will help us to reveal intercity interaction and the cyberspace-based urban network structure in China.

AbstractWith the development and popularity of mobile Internet technology, data sources of human activity in urban centers are rapidly updated and play an important role in supporting urban planning and management. Therefore, it is critical to integrate different data sources and detect spatially implicit information in the spatial pattern of relationships between urban human activity and related geographical factors. A new analytical framework is first proposed to integrate multisource location‐based big data and use these data to analyze dynamic real‐time human activity density (HAD). Taking Wuhan, the largest city in central China as an example, using the Baidu's thermal data, this paper analyzes spatiotemporal characteristics of HAD distributions at different points on weekends and weekdays, and further combines the relevant cities' points of interest data to analyze the correlations between different spatial elements and HAD distributions. The results show that: (a) Using a new indicator and data processing method can simply achieve effective utilization of Baidu's thermal data; (b) Combined with standardized grids, spatial density estimation can match the two different data sources in this study; (c) The greater the HAD, the greater is the elasticity of change, and in the active population area, the densities of human activity on weekends and weekdays at different times have significant differences; and (d) Different geographically weighted regression models effectively distinguish the influence of different urban elements on weekdays and weekends. In particular, the impact patterns of the workplace, education, and cityscape reflect the unique spatial patterns of research cases. These findings, as well as visual analytics, help in the understanding of the potential value of Baidu heatmaps in urban study and provide support for more scientific and accurate urban planning and space management for the better consideration of real‐time changes in human activity.

AbstractThe relationship between labor migration and the medical benefits of migrant children (MC) has long been a focus of empirical research. Based on the dynamic monitoring data of the migrant population in Hubei Province by the National Health and Family Planning Commission of China in 2014 and the characteristic data of prefecture‐level cities, this paper studies the impact of labor migration on the medical benefits of MC. The major findings of this paper are that in China, due to the huge spatial differences in medical services, the migration of labor to urban areas with better public services helps to improve the medical benefits of women during pregnancy and lying‐in period, and at the same time significantly enhances the medical benefits of the MC. In contrast, due to the relative lag of the reform in social security system such as household registration and medical care, in the long run, labor migration is not conducive to the improvement of the medical benefits of MC. Based on the above findings, this paper suggests that in the short‐term, more public resources should be allocated to the urban medical supply, especially at the primary level, and in the long‐term, the adjustment of public policies should be aimed at eliminating urban‐rural differences.

The development of comprehensive measures for tobacco exposure is crucial to specify effects on disease and inform public health policy. In this population-based case-control study, we evaluated the associations between cumulative lifetime cigarette tar exposure and cancers of the lung and upper aerodigestive tract (UADT). The study included 611 incident cases of lung cancer; 601 cases of UADT cancers (oropharyngeal, laryngeal and esophageal cancers); and 1,040 cancer-free controls. We estimated lifetime exposure to cigarette tar based on tar concentrations abstracted from government cigarette records and self-reported smoking histories derived from a standardized questionnaire. We analyzed the associations for cumulative tar exposure with lung and UADT cancer, overall and according to histological subtype. Cumulative tar exposure was highly correlated with pack-years among ever smoking controls (Pearson coefficient = 0.90). The adjusted odds ratio (95% confidence limits) for the estimated effect of about 1 kg increase in tar exposure (approximately the interquartile range in all controls) was 1.61 (1.50, 1.73) for lung cancer and 1.21 (1.13, 1.29) for UADT cancers. In general, tar exposure was more highly associated with small, squamous and large cell lung cancer than adenocarcinoma. With additional adjustment for pack-years, positive associations between tar and lung cancer were evident, particularly for small cell and large cell subtypes. Therefore, incorporating the composition of tobacco carcinogens in lifetime smoking exposure may improve lung cancer risk estimation. This study does not support the claim of a null or inverse association between "low exposure" to tobacco smoke and risk of these cancer types.

Abstract

Aims
To examine the association between alcohol consumption and mental health during the COVID-19 pandemic.


Methods
An anonymous online survey was distributed among US adults during May–August 2020 through social networks and ResearchMatch. We collected information on demographic, lifestyles and mental health symptoms including anxiety, depression, stress and post-traumatic stress disorder. Logistic regression models were used to examine the cross-sectional association between alcohol consumption and mental health symptoms. We also examined effect modification by race, age, gender, social support, financial insecurity and quarantine status.


Results
The analytical sample consists of 3623 adults. Stable drinking habits and regular drinking behaviors were found to co-exist with better mental health status. Participants who increased their alcohol use had higher odds of developing mental health disorders than those who maintained their pre-pandemic drinking habits. Additionally, participants who engaged in binge drinking during the pandemic had higher odds of depression and stress than those who did not. The associations regarding increased drinking and binge drinking in relation to adverse mental health outcomes were stronger among females, racial minorities, and individuals with financial concerns, poor social support and restricted quarantine status than their counterparts.


Conclusions
During the early stage of the COVID-19 pandemic, increased alcohol use and binge drinking are cross-sectionally associated with higher odds of mental health disorders, which highlighted the need for targeted intervention to address the mental health needs of individuals who have engaged in these behaviors, especially among females, minorities, those with insecurities or with restricted quarantine status.