AUTHOR=Shi Xiujing , Gao Zhaorong , Leng Lin , Guo Zhen 

TITLE=Temporal and spatial characterization of myopia in China

JOURNAL=Frontiers in Public Health

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.896926

DOI=10.3389/fpubh.2022.896926

ISSN=2296-2565

ABSTRACT=Purpose: The aim of the current study was to characterise the temporal and spatial distribution of myopia among students aged 7–18 years old. We analyse the aggregation area and provide the basis for the prevention and control of myopia in China.
Methods: A database for the spatial analysis of myopia in China in the 1995–2014 period was established using ArcGIS10.0 software as a platform for data management and presentation. A spatial autocorrelation analysis of myopia was undertaken, and a temporal and spatial scan analysis was performed using SaTScan9.5 software.
Results: The prevalence of myopia in various provinces (municipalities and autonomous regions) was the highest in Jiangsu Province, with an average Moran’s I index of 0.244295 in China (P ≤ 0.05). According to the local Moran’s I autocorrelation analysis, there was a spatial aggregation of myopia prevalence among students in the entire country, with Shandong, Jiangsu, Anhui and Shanghai being classified as high-high aggregation areas, while Hainan and Guangxi were classified as low-low aggregation areas. In addition, the Getis-Ord General G results of the global hotspot analysis showed a countrywide myopia prevalence index of 0.035020 and a Z of 1.7959, (P = 0.07251). Because the myopia prevalence correlation difference was not statistically significant, there were no “positive hotspots” or “negative hotspots.” The local hotspot analysis shows that Shandong and Jiangsu belong to high-value aggregation areas, while Hainan and Guizhou belong to low-value aggregation areas. Further analysis using time-space scanning showed fifteen aggregation regions in five stages, with four aggregation regions having statistically significant differences (P ≤ 0.05). However, the aggregation range has changed over time. Overall, from 1995 to 2014, the aggregation areas for the myopia prevalence in Chinese students have shifted from the northwest, north and northeast regions to the southeast regions.
Conclusion: Our data demonstrate that, from 1995 to 2014, the prevalence of myopia increased in students aged 7–18 years old in China.And the gathering area is gradually shifting to the southeast, with the existence of high-risk areas. It is necessary to focus on this area and undertake targeted prevention and control measures.