Study population
A retrospective study was conducted from 2013 to 2018 in Liuyang, which is a county-level city located in the Northeast of Hunan province, China. Liuyang has jurisdiction of 4 city districts and 33 towns, including 1.49 million populations. Liuyang was ranked as 19th among the ‘top 100 national strong counties’ in China in 201612. From 2006, Liuyang Health Bureau has appointed the Liuyang Center for Disease Control and Prevention (CDC) to conduct annual physical examination among school students from grades 1 to 12. As a health policy aimed to improve the health of school children, the annual physical examination is requested to cover all the students in primary, junior and senior high schools under Liuyang jurisdiction. As part of the yearly compulsory routine physical examination that all students are requested to undergo, the eye examination records of all students were routinely collected each year by Jili hospital (also named as Liuyang Eye Hospital) in Liuyang City. The facility mandated for the physical examination for the students in the district. In this study, data related to the eye examination from 2013 to 2018 were retrieved for analysis.
All students’ records were electronically registered by file numbers, name, gender, age, ethnicity, school, and address. All the data were submitted to the Liuyang CDC, the institution that was in charge of the physical examination. The Liuyang CDC is the custodian of the database and data retrieval was conducted with de-identification of all students in May 2019, with the official permission from the Liuyang CDC.
Ethical approval
Since this study was based on routing data with all the subjects being de-identified. Ethical approval was waved from the Xiangya School of public health, Central South University and Liuyang CDC. The study followed the guidelines of the Declaration of Helsinki13.
Data collection
The following data were retrieved from the dataset: age, sex, residency type (rural/urban), education level, height, weight and results of eye examination. Details about height and weight measurements were presented in Appendix 1. Any record with missing data regarding the above listed variables, logic errors or had an age lower than 6 or larger than 18 was excluded from the final data analysis.
Eye examination
The Eye examination was conducted by an experienced group of ophthalmologists optometrists and nurses according to the Chinese National standard for students’ physical examination (GB11533). All were staffs from the department of ophthalmology in Jili Hospital. Each student’s uncorrected visual acuity (UCVA) was measured monocularly at a distance of 5 meters using the Standard Logarithmic Visual Acuity (LogMAR) Chart with tumbling-E optotypes under room lighting. The acuity of the LogMAR Chart that can be measured ranges from 4.0 to 5.3. If a score lower than 5.0 UCVA and a slit lamp examination as well excluded opacity of optical media and other eye conditions, then it was recorded abnormal vision (myopia). Students who have UCVA lower than 5.0, were further classified as slight myopia (4.9≤UCVA<5.0), moderate myopia (4.6≤UCVA≤4.8) and sever myopia (UCVA≤4.5).
Body mass index (BMI) calculation
BMI for age was calculated by the formula weight (kg)/height (m^2). BMI was further categorized using the World Health Organization’s Z score chart for children 5-19 years (appendix 2)14.
Statistical analysis
Mean with standard deviations (SD), and frequencies with percentages were reported in the descriptive statistical analyses for the continuous variables and the categorical variables, respectively. The data from the left eye was used for the estimation of myopia prevalence as a highly significant correlation of 0.89 (p>0.001) (Appendix 3) between the left and right eyes was reported 15.
Myopia prevalence was calculated one-time for each year and by age group from 2013 to 2018. Line graphs were used to describe and compare the annual prevalence trends of myopia, within each sex and one-year time age interval (6 to 18years) from 2013 to 2018. Linear-by-Linear association test was used to test the trends of myopia prevalence at each age group with the increase of age (from 6 years to 18 years) and year going on (from 2013 to 2018). Differences in myopia prevalence among different groups were compared with Chi-squared test. Multivariable logistic regression analysis was used to identify the association between demographic variables and myopia within each year from 2013 to 2018, and the total population. Among each logistic regression analysis, myopia status was used as the dependent variables; sex, BMI status, grade and residency type were used as the independent variables. Sensitivity analyses on multivariable logistic regressions were conducted by excluding students from senior high schools as enrollment rates decreased from over 99% in primary school and junior high school to around 88% in senior high school 16, and a relative low eye examination rate was observed in senior high school. Age was not included in the logistic regression for its collinearity with grade group. The model fitting was checked with Hosmer and Lemeshow (HL) test, with P-value greater than 0.1 being considered as adequate model fit. Adjusted Odds Ratio (OR) with 95% confidence interval (CI) was calculated. A P-value of less than 0.05 (two-tailed) was accepted as statistically significant (except for HL test). All data analyses were performed using SPSS statistics version 21.0 (SPSS Inc., Chicago, Illinois, USA) and Graphical presentations by Microsoft Excel version 10.