Investigation of multi-scale spatio-temporal pattern of oldest-old clusters in China on the basis of spatial scan statistics

Spatial-temporal evolution of population aging in the yangtze river delta urban agglomeration of China

The Yangtze River Delta urban agglomeration (YRDUA) is China's most representative region with remarkable economic development vitality. The purpose of this study is to provide valuable data analysis to actively respond to the population aging in China. We mainly focus on the spatial and temporal evolution of population aging in YRDUA from 2000 to 2020 using city-level population data. This study constructs a multi-dimensional index system to measure population aging including population aging degree, speed, and density. It finds out: (1) the elderly population rate (EPR), the elder-child ratio (ECR), and the elderly dependency ratio (EDR) in the YRDUA area are gradually increasing from 2000 to 2020. In addition, the trends of these indicators in various cities and regions are relatively consistent. All 27 cities in YRDUA entered an aging society, from the primary to the moderate aging stage from 2000 to 2010 and from the moderate to the hyper aging stage from 2010 to 2020. (2) the absolute and relative growth rate of EPR is increasing from 2000 to 2020. However, the absolute and relative growth rate of ECR is increasing from 2000 to 2010 and then decreasing from 2010 to 2020. These results indicate that the two-child policy adopted by the Chinese government plays a positive role. (3) the density level of the elderly population in the YRDUA evolved from low in 2000 to middle in 2010 and then to high in 2020. (4) There are remarkable differences in the process of population aging among three provinces and one city. The contribution of this study is mainly reflected in two aspects: firstly, it constructs a multi-dimensional index system to measure population aging; secondly, using this multi-dimensional index system, it systematically observes the spatial and temporal evolution of population aging from 2000 to 2020 in the Yangtze River Delta Urban Agglomeration.

Spatial autocorrelation and stratified heterogeneity in the evaluation of breast cancer risk inequity and socioeconomic factors analysis in China: Evidence from Nanchang, Jiangxi Province

Study of socioeconomic factors can play an important role in the spatial distribution of breast cancer by leading to a better understanding of its spatial pattern and assist breast cancer screening and early diagnosis. Taking Nanchang, a major city in central China, as an example, spatial autocorrelation and stratified heterogeneity were applied using a 10 10 km grid division to analyse breast cancer risk and socioeconomic factors. The research results showed that the median incidence rate of female breast cancer in Nanchang from 2016 to 2018 was 6.6/100,000 with a standard deviation of 12.3/100,000. Areas with higher incidence rates were mainly located in the central urban area and the major county towns. Spatial regression analysis showed that there was a statistically significant correlation between the spatial patterns of breast cancer incidence on the one hand, and on the other socioeconomic factors, such as total gross domestic product (GDP), per capita GDP and density of places of social and economic activities, i.e. points of interest. In addition, the normalized difference vegetation index also played a part in this respect. This research could serve as a reference for regional public health policy formulation and breast cancer screening.

Multi-Dimensional Urbanization Coordinated Evolution Process and Ecological Risk Response in the Yangtze River Delta

The dislocated development of population, land, and economy will disturb the urban system, cause ecological risk problems, and ultimately affect regional habitat and quality development. Based on social statistics and nighttime lighting data from 2000 to 2018, we used mathematical statistics and spatial analysis methods to analyze the change process of urbanization’s coupling coordination degree and ecological risk response pattern in the Yangtze River Delta. Results show that: ① From 2000 to 2018, the coupling coordination degree of urbanization in the Yangtze River Delta increased, with high values in Suzhou-Wuxi-Changzhou, Shanghai, Nanjing and Hangzhou regions. ② The ecological risk in the Yangtze River Delta weakened, and the vulnerability and disturbance of landscape components together constitute the spatial differentiation pattern of regional ecological risk, which presented homogeneous aggregation and heterogeneous isolation. ③ The overall ecological stress of urbanization in the Yangtze River Delta decreased. ④ The population aggregation degree, socio-economic development level and built-up area expansion trend contributed to the spatiotemporal differentiation of urbanization’s ecological risks through the synergistic effects of factor concentration and diffusion, population quality cultivation and improvement, technological progress and dispersion, industrial structure adjustment and upgrading. This study can provide a reference for regional urbanization to deal with ecological risks reasonably and achieve high-quality development.

Application of GIS Spatial Analysis and Scanning Statistics in the Gynecological Cancer Clustering Pattern and Risk Screening: A Case Study in Northern Jiangxi Province, China

OBJECTIVE

The incidence of gynecological cancer is high in China, and the effects of related treatments and preventive measures need to be improved.

METHODS

This study uses GIS spatial analysis methods and a scanning statistical analysis to study the major gynecological cancers in northern Jiangxi Province from 2016 to 2018.

RESULTS

The incidence and spatial pattern of cervical cancer, ovarian cancer, and uterine cancer had agglomeration characteristics and changes during the study period. The gynecological cancer had a spatial autocorrelation and agglomeration in its spatial pattern. The Moran's Index of the overall gynecological cancer incidence rate was 0.289 (p = 0.005). Ripley's L(d) function showed that the agglomeration radius was between 51.40 and 52.82 km. The results of the kernel density estimation showed that the cases of gynecological cancer were concentrated in the central and northeastern areas of the study area. The overall county-level incidence of gynecological cancer varied from 0.26 to 11.14 per 100,000. The results of the gravity center analysis showed that the spatial distribution of the gravity center point of gynecological cancer had moved toward the east during the past three years. The results of a hotspot analysis showed that there were five hotspot areas that had gynecological cancers. The most likely clusters of gynecological cancer at the county level in northern Jiangxi Province were distributed in the adjacent areas of Jiujiang, Yichun, and Nanchang, with a relative risk of 1.85.

CONCLUSION

The research shows that GIS can display the distribution of cancer cases and can use spatial analysis methods and scanning statistical techniques to obtain key areas of cancer incidence. These results can provide data and key areas for the formulation of regional public health policies and provide recommendations for cancer screening and the rational allocation of health resources.

Epidemiological Characteristics and Spatiotemporal Analysis of Acute Hemorrhagic Conjunctivitis from 2004 to 2018 in Chongqing, China

Chongqing is one of the five provinces in China that has the highest incidence of acute hemorrhagic conjunctivitis (AHC). Data of AHC cases from 2004 to 2018 were obtained from National Notifiable Diseases Reporting Information System (NNDRIS). Descriptive statistical methods were used to analyze the epidemiological characteristics; incidence maps were used to reflect incidence trends in each district; spatial autocorrelation was used to identify hotspot regions and spatiotemporal patterns of AHC outbreaks; spatiotemporal scan were conducted to identify AHC clusters. A total of 30,686 cases were reported with an annual incidence of 7.04 per 100,000. The incidence rates were high in 2007 and 2014, and large epidemics were observed in 2010 with the seasonal peak in September. Individuals aged 10–19 years, males, students and farmers were the prime high-risk groups. Except for 2012 and 2013, the spatial distribution of AHC did not exhibit significant global spatial autocorrelation. Local indicators of spatial association showed that the high-risk regions are Chengkou and Wuxi. The spatiotemporal scan indicated that all clusters occurred in September 2010, and the high-incidence clusters were mainly distributed in the northeast of Chongqing. The results could assist public health agencies to consider effective preventive measures based on epidemiological factors and spatiotemporal clusters in different regions.