Space-time analysis of poor vision among primary and secondary school students in Chengdu from 2021 to 2023
10.16835/j.cnki.1000-9817.2025028
- VernacularTitle:成都市2021—2023年中小学生视力不良的时空分析
- Author:
XIE Yuhuan, WANG Zitong, CHEN Xi, YUE Lin, PAN Jie
1
Author Information
1. West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu (610041) , Sichuan Province, China
- Publication Type:Journal Article
- Keywords:
Vision,low;
Space time clustering;
Students
- From:
Chinese Journal of School Health
2025;46(1):29-33
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the space time characteristics of poor vision among primary and secondary school students in Chengdu, in order to provide the reference for formulating myopia prevention and control policies for students.
Methods:The data relating to poor vision among primary and secondary school students in Chengdu from 2021 to 2023 were sourced from the Sichuan Students Physical Health Big Data Center. The districts and counties of Chengdu were divided into three circles, including the main urban area, suburban districts and counties, and suburban districts and counties. The Chi square test was used for inter group comparison, and the Cochran-Armitage test was used to analyze the trend of changes. Global and local Moran s I were used to analyze spatial clustering.
Results:The detection rates of poor vision among primary and secondary school students in Chengdu from 2021 to 2023 were 62.47%, 61.61% and 60.78%, respectively, showing a decreasing trend ( Z=-32.01, P <0.01). For each year, the higher detection rate of poor vision among students was detected in the higher level of education, and differences were statistically significant ( χ 2=161 549.47, 173 471.87, 233 459.09, P <0.01). The rate of poor vision among primary and secondary school students gradually decreased from the central districts and counties of Chengdu to the surrounding districts and counties for each year, and the differences were statistically significant ( χ 2=299.20, 776.22, 633.16, P <0.01). The spatial autocorrelation analysis showed that the first circle of Chengdu City was mainly characterized by high-high agglomeration ( P <0.01), with the rate of poor vision among primary school students in Wuhou District in 2023 exhibiting a low-high anomaly. The third circle was mainly characterized by low-low aggregation ( P <0.01), while the spatial clusterings of the second circle was not significant ( P >0.05).
Conclusions:The myopia prevention and control work in Chengdu has achieved preliminary results. It should continue to consolidate existing achievements and implement targeted myopia prevention and control measures based on regional characteristics.
