中小学生高度近视发生风险预测模型：基于巢式病例对照研究
Risk Prediction Model for High Myopia in Primary and Secondary School Students：Based on Nested Case-control Study
杜持新 胡旺成 倪作为 叶春梅 陈晓丹 夏冰 郑永韬 陈胜蓝
作者信息
摘要
背景 中小学生由于学习压力、电子产品普及以及不良用眼习惯，视力健康问题日益严重，成为近视的高发群体，高度近视作为近视的严重阶段，已成为全球范围内的公共卫生问题。尽管现有诸多研究对近视的危险因素进行了探讨，但鲜有研究针对性阐明风险因素与高度近视发生的复杂非线性关系，本研究结合巢式病例对照研究和限制性立方样条，开发一个中小学生高度近视风险预测模型，通过早期识别高风险个体，延缓或阻止高度近视的发展，实现近视的三级预防，对中小学生的学业和生活质量有积极意义。目的 探究中小学生高度近视的流行现状及危险因素，构建风险预测模型，为中小学生高度近视防控提供科学依据。方法 采用巢式病例对照研究，于2023年选取杭州市12所学校中度近视的学生作为研究对象建立队列，按照全国学生常见病和健康影响因素监测与干预工作方案，对纳入研究的中小学生开展近视状况监测，研究期间进展为高度近视的中小学生作为高度近视发生组，其余未进展为高度近视的中小学生作为对照组，对两组研究对象开展视力保健行为进行调查。采用Lasso回归筛选特征变量后进行多因素Logistic回归分析中小学生高度近视发生的影响因素，并采用列线图对风险预测模型可视化，同时采用Hosmer-Lemeshow检验、受试者工作特征（ROC）曲线、Calibration曲线、决策曲线分析（DCA）对模型性能进行评估，最后采用限制性立方样条进一步明确年龄与高度近视发生风险的关系。结果 12所中小学校共纳入2 468名学生，未进展为高度近视的学生1 293名，中度近视进展为高度近视的学生1 175名，高度近视发生率为47.61%（1 175/2 468）。两组学生年龄、年级、BMI、每日入睡时间、地区、户外活动时间、电子产品使用时间、课后作业时间、家用台灯比较，差异有统计学意义（P<0.05）。Lasso回归筛选出8个特征变量：年级、BMI、每日入睡时间、地区、户外活动时间、电子产品使用时间、课后作业时间、家用台灯。多因素Logistic回归分析结果显示，初中年级（OR=2.612，95%CI=2.185~3.127），BMI超重或肥胖（OR=2.140，95%CI=1.458~3.169）、偏瘦（OR=1.807，95%CI=1.430~2.290），每日入睡时间在22：00之后（OR=1.408，95%CI=1.188~1.670），户外活动时间1~2 h/d（OR=1.371，95%CI=1.122~1.675）、<1 h/d（OR=1.648，95%CI=1.342~2.027），电子产品使用时间>2 h/d（OR=1.440，95%CI=1.119~1.856），课后作业时间1~2 h/d（OR=1.461，95%CI=1.126~1.899）、>2 h/d（OR=1.534，95%CI=1.218~1.935）为中小学生高度近视发生的危险因素（P<0.05）；而高中年级（OR=0.560，95%CI=0.419~0.743）为中小学生高度近视发生的保护因素（P<0.05）。基于年级、BMI、每日入睡时间、户外活动时间、电子产品使用时间、课后作业时间等6个变量构建的预测模型AUC为0.840（95%CI=0.825~0.855），具有良好的拟合优度、一致性、应用性，限制性立方样条分析显示13~15岁为高度近视的高发年龄段。结论 中小学生高度近视发生率较高，风险预测模型为高度近视的预防和控制提供了科学依据，同时在初中年级加强近视防控措施，改善学生的视力保健行为，降低高度近视的发生。
Abstract
BackgroundThe vision health of primary and secondary school students has become a growing concern due to increasing academic pressurethe widespread use of electronic devicesand poor eye care habits. High myopiaas an advanced stage of myopiaemerging as a global public health issue. While many existing studies have explored the risk factors for myopiafew have specifically addressed the complex non-linear relationships between these factors and the development of high myopia. This study combines a nested case-control study with restricted cubic splines to develop a risk prediction model for high myopia in primary and secondary school students. By identifying high-risk individuals earlythis model aims to delay or prevent the progression of high myopiacontributing to tertiary prevention of myopiaand positively impacting the academic and life quality of students. ObjectiveTo investigate the prevalence and risk factors of high myopia in primary and secondary school studentsand conduct a risk prediction model to provide a scientific basis for myopia prevention. MethodsA nested case-control study was conducted in 2023involving students with moderate myopia from 12 schools in Hangzhou to establish a cohort. Myopia status among the students was monitored in accordance with the National Monitoring and Intervention Program for Common Diseases and Health-Related Factors in Students. Students who progressed to high myopia were classified as the case groupwhile the others formed the control groupvision care behaviors were surveyed for both groups. Lasso regression was used to select feature variablesfollowed by multivariate logistic regression analysis to identify factors influencing the development of high myopia among primary and secondary school students. A Nomogram was employed to visualize the risk prediction model. The model's performance was evaluated using the Hosmer-Lemeshow testreceiver operating characteristicROCcurve calibration curveand decision curve analysisDCA. Additionallyrestricted cubic splines were used to further clarify the relationship between age and the risk of high myopia. ResultsA total of 2468 students from 12 primary and secondary schools were enrolled. Among them1 293 students did not progress to high myopiawhile 1 175 students with moderate myopia progressed to high myopiaresulting in a high myopia incidence rate of 47.61%1 175/2 468. Significant differences were observed between the two groups in terms of agegrade levelBMIdaily sleep timegeographic regionoutdoor activity timeelectronic device usage timeafter-school homework timeand household lamp usageP<0.05. Lasso regression identified eight feature variablesgrade levelBMIdaily sleep timegeographic regionoutdoor activity timeelectronic device usage timeafter-school homework timeand household lamp usage. Multivariate Logistic regression analysis revealed that the risk factors for high myopia in primary and secondary school students included being in middle schoolOR=2.612 95%CI=2.185-3.127being overweight or obeseOR=2.14095%CI=1.458-3.169being underweightOR=1.807 95%CI=1.430-2.290sleeping after 2200 dailyOR=1.40895%CI=1.188-1.670engaging in outdoor activities for 1-2 h/dOR=1.37195%CI=1.122-1.675or <1 h/dOR=1.64895%CI=1.342-2.027using electronic devices >2 h/dOR=1.440 95%CI=1.1191.856and spending 1-2 h/dOR=1.46195%CI=1.126-1.899or >2 h/dOR=1.53495%CI=1.218- 1.935on after-school homeworkP<0.05. In contrastbeing in high school was identified as a protective factor against high myopiaOR=0.56095%CI=0.419-0.743P<0.05. A risk prediction model was constructed based on six variables grade levelBMIdaily sleep timeoutdoor activity timeelectronic device usage timeand after-school homework time. The model achieved an area under the curveAUCof 0.84095%CI=0.825-0.855demonstrating good fitconsistency and applicability. Additionallyrestricted cubic spline analysis indicated that the age group of 13~15 years was the high-risk period for developing high myopia. ConclusionThe incidence of high myopia among primary and secondary school students was notably high. The risk prediction model could provide a scientific basis for the prevention and control of high myopia. Strengthening myopia prevention and control measures in middle schoolalong with improving students' vision care behaviorswas essential for reducing the occurrence of high myopia.关键词
近视/学生/高度近视/巢式病例对照研究/限制性立方样条/预测模型引用本文复制引用
杜持新,胡旺成,倪作为,叶春梅,陈晓丹,夏冰,郑永韬,陈胜蓝.中小学生高度近视发生风险预测模型：基于巢式病例对照研究[EB/OL].(2024-10-10)[2026-04-03].https://chinaxiv.org/abs/202410.00086.学科分类
预防医学/眼科学/医学研究方法
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