目的：分析中学生近视与抑郁症状共患现状，识别关键影响因素，构建预测模型，为近视与抑郁的综合干预提供依据。

方法：抽取2022至2024年肥东县3所中学的学生，依据裸眼视力≤5.0且等效球镜度数<-0.50 D和流调中心用抑郁量表(CES-D)评分≥16分判定近视及抑郁症状。采用EpiData建立数据库录入数据，使用R统计软件版本4.5.2进行Pearson卡方检验和多因素Logistic回归分析影响因素并筛选变量，最后使用Python3.13软件构建Stacking集成预测模型。

结果：本研究抽取2 476名学生，男1 380人，女1 096人。肥东县近视与抑郁共患检出率为14.54%。单因素分析显示：家庭结构、年级、饮用含糖饮料频率、运动频率、校园欺凌、家长打骂等变量差异显著(均P<0.05)。多因素Logistic回归显示危险因素为高年级(八年级：OR=1.9143，95%CI：1.1096-3.3024； 九年级：OR=1.7884，95%CI：1.0506-3.0444； 高二年级：OR=2.1847，95%CI：1.1980-3.9840； 高三年级：OR=3.4606，95%CI：1.8250-6.5621)、饮用含糖饮料每天1次以上(OR=3.1383，95%CI：1.7112-5.7560)、周末节假日运动中高强度频率较低(多数能做到：OR=3.3115，95%CI：1.009-10.8685)、饮酒(OR=4.4021，95%CI：2.7383-7.0766)、久坐>10 h(OR=1.8594，95%CI：1.2141-2.8476)、未经历青春期教育(OR=3.0098，95%CI：2.0659-4.3848)、遭受家长打骂(OR=2.4050，95%CI：1.1484-5.0364)； 保护因素为未经历校园欺凌(OR=0.0055，95%CI：0.0002-0.1602)、未遭受严重伤害(OR=0.3118，95%CI：0.1823-0.5332)、课间户外活动(OR=0.1672，95%CI：0.0752-0.3719)、课后作业时长适中(2-3 h：OR=0.4802，95%CI：0.2620-0.8801)。预测模型：AUC=0.855，灵敏度81.5%，特异度74.0%； 关键预测因子包括饮酒情况、课间休息场所、不健康习惯综合指数(久坐时长和饮用含糖饮料频率的交互特征)、学业压力指数(久坐时长与课后作业时长的交互特征)、课后作业时长。

结论：中学生近视与抑郁共患受生活方式、学业压力及家庭/校园环境等因素多重影响，提倡进行限购含糖饮料、久坐学生心理筛查、“家校医”联合管理饮酒行为的三级干预体系。本模型可用于学校卫生筛查、社区青少年健康管理中高风险人群早期识别，适用于类似经济水平地区中学生，不适用于特殊教育学生或有严重器质性疾病的学生。

METHODS: Students from 3 middle schools in Feidong county were recruited between 2022 and 2024. Myopia was defined as uncorrected visual acuity ≤5.0 with spherical equivalent refraction <-0.50 diopters(D). Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale(CES-D), with a score ≥16 indicating the presence of depressive symptoms. A database was established and data were entered using EpiData software. Pearson's Chi-square test and multivariate Logistic regression analysis were performed to identify influencing factors and screen variables with R statistical software(version 4.5.2). Finally, a Stacking ensemble prediction model was constructed using Python3.13 software.

RESULTS: The study included 2 476 students, consisting of 1 380 males and 1 096 females. The overall detection rate of myopia-depressive symptom comorbidity among the studied students was 14.54%. Univariate analysis showed that variables were significantly associated with the comorbidity, including family structure, grade level, sugar-sweetened beverage intake, exercise frequency, school bullying, and parental physical or verbal abuse(all P<0.05). Multivariate Logistic regression analysis identified the following risk factors: higher grade levels(8^th grade: OR=1.9143, 95%CI: 1.1096-3.3024; 9^th grade: OR=1.7884, 95%CI: 1.0506-3.0444; 11^th grade: OR=2.1847, 95%CI: 1.1980-3.9840; 12^th grade: OR=3.4606, 95%CI: 1.8250-6.5621), daily consumption of sugar-sweetened beverages more than once(OR=3.1383, 95%CI: 1.7112-5.7560), low frequency of moderate-to-vigorous exercise on weekends and holidays(mostly achievable: OR=3.3115, 95%CI: 1.009-10.8685), alcohol consumption(OR=4.4021, 95%CI: 2.7383-7.0766), daily sedentary time exceeding 10 h(OR=1.8594, 95%CI: 1.2141-2.8476), lack of puberty education(OR=3.0098, 95%CI: 2.0659-4.3848), and exposure to parental physical or verbal abuse(OR=2.4050, 95%CI: 1.1484-5.0364). Protective factors included no experience of school bullying(OR=0.0055, 95%CI: 0.0002-0.1602), no history of severe injury(OR=0.3118, 95%CI: 0.1823-0.5332), outdoor activities during class breaks(OR=0.1672, 95%CI: 0.0752-0.3719), and moderate after-school homework duration(2-3 h per day: OR=0.4802, 95%CI: 0.2620-0.8801). The constructed Stacking prediction model demonstrated good discriminative ability, with an area under the receiver operating characteristic curve(AUC)of 0.855, a sensitivity of 81.5%, and a specificity of 74.0%. Key predictive factors included alcohol consumption status, location of recess activities, unhealthy lifestyle composite index(interaction term between sedentary duration and sugar-sweetened beverage intake frequency), academic stress index(interaction term between sedentary duration and homework duration), and after-school homework duration.

CONCLUSION: The comorbidity of myopia and depression among middle school students is jointly influenced by multiple factors such as lifestyle, academic pressure, and family/campus environment. It is advocated to implement a three-level intervention system that includes restricting the sale of sugar-sweetened beverages, conducting psychological screening for sedentary students, and carrying out family-school-medical collaborative management of drinking behaviors. This model can be applied to school health screening and the early identification of high-risk groups in community adolescent health management. It is suitable for middle school students in regions with similar economic levels, but not applicable to students receiving special education or those with severe organic diseases.