留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

天津某高校新生计算机视觉综合征现状及影响因素

李炳钦 张红梅 王志洋 魏瑞华

李炳钦, 张红梅, 王志洋, 魏瑞华. 天津某高校新生计算机视觉综合征现状及影响因素[J]. 中国学校卫生, 2023, 44(6): 850-853, 858. doi: 10.16835/j.cnki.1000-9817.2023.06.012
引用本文: 李炳钦, 张红梅, 王志洋, 魏瑞华. 天津某高校新生计算机视觉综合征现状及影响因素[J]. 中国学校卫生, 2023, 44(6): 850-853, 858. doi: 10.16835/j.cnki.1000-9817.2023.06.012
LI Bingqin, ZHANG Hongmei, WANG Zhiyang, WEI Ruihua. Status quo and influencing factors of computer vision syndrome among college freshmen in Tianjin[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2023, 44(6): 850-853, 858. doi: 10.16835/j.cnki.1000-9817.2023.06.012
Citation: LI Bingqin, ZHANG Hongmei, WANG Zhiyang, WEI Ruihua. Status quo and influencing factors of computer vision syndrome among college freshmen in Tianjin[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2023, 44(6): 850-853, 858. doi: 10.16835/j.cnki.1000-9817.2023.06.012

天津某高校新生计算机视觉综合征现状及影响因素

doi: 10.16835/j.cnki.1000-9817.2023.06.012
基金项目: 

天津市卫生健康科技项目 TJWJ2022MS014

天津市医学重点学科(专科)建设项目资助 TJYXZDXK-037A

详细信息
    作者简介:

    李炳钦(1999-),男,山西临汾人,在读硕士,主要研究方向为眼视光学

    通讯作者:

    魏瑞华,E-mail:rwei@tmu.edu.cn

  • 利益冲突声明  所有作者声明无利益冲突。
  • 中图分类号: B844.2  G478  R179

Status quo and influencing factors of computer vision syndrome among college freshmen in Tianjin

  • 摘要:   目的  调查新冠肺炎疫情期间天津某高校学生计算机视觉综合征(CVS)的现状及其影响因素,为改善大学生的视觉舒适度提供参考。  方法  2021年10—12月,以天津某高校2021级868名新生为研究对象,采用CVS定性分析问卷、眼健康情况调查问卷与眼健康检查相结合的方式进行研究。采用χ2检验和多因素Logistic回归进行数据分析。  结果  学生的CVS检出率为68.5%(595名),女生检出率(72.2%)高于男生(61.7%)。女生、非低度近视、入睡需要>30 min、睡前习惯使用手机>1 h、夜间睡眠时长≤8 h的学生CVS检出率(72.2%,70.4%,81.1%,72.7%,71.2%)比男生、低度近视、入睡需要≤30 min、睡前习惯使用手机≤1 h、夜间睡眠时长>8 h高(61.7%,63.3%,67.4%,65.9%,61.1%),差异均有统计学意义(χ2值分别为10.08,3.94,5.89,4.40,7.94,P值均<0.05);每日使用电子设备时间和学业压力不同的学生CVS检出率差异均有统计学意义(χ2值分别为22.03,21.24,P值均<0.05)。多因素Logistic回归显示,每日使用电子设备的时间4~6,7~9,≥10 h,入睡需要>30 min,平时的学业压力适中、很大与CVS呈正相关(OR值分别为1.95,2.94,2.30,2.39,3.51,4.41,P值均<0.05);男生、低度近视、夜间睡眠时长>8 h与CVS呈负相关(OR值分别为0.65,0.70,0.65,P值均<0.05)。  结论  天津某高校新生CVS检出率较高,应关注线上学习时学生CVS情况,对广大学生进行宣教,减少不必要电子产品使用时间,保证夜间睡眠,降低CVS的发生。
    1)  利益冲突声明  所有作者声明无利益冲突。
  • 表  1  天津高校大学生CVS相关因素的单因素分析

    Table  1.   Univariate Logistic regression analysis of CVS-related risk factors among the college sutdents in Tianjin

    组别 选项 人数 CVS人数 χ2 P
    性别 303 187(61.7) 10.08 <0.01
    565 408(72.2)
    BMI分级 过轻 156 104(66.7) 2.46 0.48
    正常 543 382(70.3)
    过重 104 68(65.4)
    肥胖 65 41(63.1)
    屈光状态 高度近视 251 183(72.9) 9.15 0.06
    中度近视 343 241(70.3)
    低度近视 226 143(63.3)
    正视 35 22(62.9)
    远视 13 6(46.2)
    是否高度近视 251 183(72.9) 3.11 0.08
    617 412(66.8)
    是否中度近视 343 241(70.3) 0.77 0.38
    525 354(67.4)
    是否低度近视 226 143(63.3) 3.94 < 0.05
    642 452(70.4)
    是否正视 35 22(62.9) 0.55 0.46
    833 573(68.8)
    是否远视 13 6(46.2) 2.11 0.15
    855 589(68.9)
    每日使用电子设备 1~3 62 29(46.8) 22.03 <0.01
    时间/h 4~6 376 247(65.7)
    7~9 345 259(75.1)
    ≥10 85 60(70.6)
    入睡需要>30 min 74 60(81.1) 5.89 0.02
    794 535(67.4)
    睡前习惯使用手机>1 h 337 245(72.7) 4.40 0.04
    531 350(65.9)
    夜间使用手机时开灯 437 293(67.0) 0.92 0.34
    431 302(70.1)
    夜间睡眠时长>8 h 226 138(61.1) 7.94 <0.01
    642 457(71.2)
    平时的学业压力 很大 133 87(65.4) 21.24 <0.01
    适中 702 497(70.8)
    轻松 33 11(33.3)
    是否佩戴眼镜 706 482(68.3) 0.13 0.71
    162 113(69.8)
    :()内数字为检出率/%。
    下载: 导出CSV

    表  2  天津市高校大学生CVS相关因素的多因素Logistic回归分析(n=868)

    Table  2.   Multivariate Logistic regression analysis of CVS-related risk factors among the college students in Tianjin(n=868)

    自变量 选项 OR值(95%CI)
    性别 0.65(0.47~0.88)**
    1.00
    低度近视 0.70(0.50~0.97)*
    1.00
    每日使用电子设备的时长/h 1~3 1.00
    4~6 1.95(1.11~3.43)*
    7~9 2.94(1.64~5.30)**
    ≥10 2.30(1.10~4.79)*
    入睡需要>30 min 2.39(1.27~4.51)**
    1.00
    睡前习惯使用手机>1 h 1.18(0.85~1.64)
    1.00
    夜间睡眠时长>8 h 0.65(0.46~0.91)*
    1.00
    平时的学业压力 很大 4.41(2.05~9.48)**
    适中 3.51(1.53~8.07)**
    轻松 1.00
    :*P < 0.05,**P < 0.01。
    下载: 导出CSV
  • [1] RANDOLPH S A. Computer vision syndrome[J]. Workplace Health Saf, 2017, 65(7): 328. doi: 10.1177/2165079917712727
    [2] BLEHM C, VISHNU S, KHATTAK A, et al. Computer vision syndrome: a review[J]. Surv Ophthalmol, 2005, 50(3): 253-262. doi: 10.1016/j.survophthal.2005.02.008
    [3] LOGARAJ M, MADHUPRIYA V, HEGDE S. Computer vision syndrome and associated factors among medical and engineering students in Chennai[J]. Ann Med Health Sci Res, 2014, 4(2): 179-185. doi: 10.4103/2141-9248.129028
    [4] ROSENFIELD M. Computer vision syndrome: a review of ocular causes and potential treatments[J]. Ophthalmic Physiol Opt, 2011, 31(5): 502-515. doi: 10.1111/j.1475-1313.2011.00834.x
    [5] RANASINGHE P, WATHURAPATHA W S, PERERA Y S, et al. Computer vision syndrome among computer office workers in a developing country: an evaluation of prevalence and risk factors[J]. BMC Res Notes, 2016, 9: 150. doi: 10.1186/s13104-016-1962-1
    [6] BALI J, NEERAJ N, BALI R. Computer vision syndrome: a review[J]. J Clinic Ophthalmol Res, 2014, 2(1): 61-68. doi: 10.4103/2320-3897.122661
    [7] AGARWAL S, GOEL D, SHARMA A. Evaluation of the factors which contribute to the ocular complaints in computer users[J]. J Clin Diagn Res, 2013, 7(2): 331-335.
    [8] GALINSKY T L, SWANSON N G, SAUTER S L, et al. A field study of supplementary rest breaks for data-entry operators[J]. Ergonomics, 2000, 43(5): 622-638. doi: 10.1080/001401300184297
    [9] ASSEFA N L, WELDEMICHAEL D Z, ALEMU H W, et al. Prevalence and associated factors of computer vision syndrome among bank workers in Gondar City, Northwest Ethiopia, 2015[J]. Clin Optom, 2017, 9: 67-76. doi: 10.2147/OPTO.S126366
    [10] MOWATT L, GORDON C, SANTOSH A B R, et al. Computer vision syndrome and ergonomic practices among undergraduate university students[J]. Int J Clin Prac, 2018, 72(1): e13035. doi: 10.1111/ijcp.13035
    [11] ALTALHI A, KHAYYAT W, KHOJAH O, et al. Computer vision syndrome among health sciences students in Saudi Arabia: prevalence and risk factors[J]. Cureus, 2020, 12(2): e7060.
    [12] ZENBABA D, SAHILEDENGLE B, BONSA M, et al. Prevalence of computer vision syndrome and associated factors among instructors in Ethiopian universities: a web-based cross-sectional study[J]. Sci World J, 2021, 2021: 3384332.
    [13] AL TAWIL L, ALDOKHAYEL S, ZEITOUNI L, et al. Prevalence of self-reported computer vision syndrome symptoms and its associated factors among university students[J]. Eur J Ophthalmol, 2020, 30(1): 189-195. doi: 10.1177/1120672118815110
    [14] SEGUI MDEL M, CABRERO-GARCIA J, CRESPO A, et al. A reliable and valid questionnaire was developed to measure computer vision syndrome at the workplace[J]. J Clin Epidemiol, 2015, 68(6): 662-673. doi: 10.1016/j.jclinepi.2015.01.015
    [15] CANTÓ-SANCHO N, SÁNCHEZ-BRAU M, IVORRA-SOLER B, et al. Computer vision syndrome prevalence according to individual and video display terminal exposure characteristics in Spanish university students[J]. Int J Clin Pract, 2021, 75(3): e13681.
    [16] 徐素华, 孙贵龙, 武鹏, 等. 土家族聚居区儿童青少年视力不良状况[J]. 中国学校卫生, 2022, 43(6): 930-933. doi: 10.16835/j.cnki.1000-9817.2022.06.031

    XU S H, SUN G L, WU P, et al. Low vision among children and adolescents in Tujia inhabited areas[J]. Chin J Sch Health, 2022, 43(6): 930-933. (in Chinese) doi: 10.16835/j.cnki.1000-9817.2022.06.031
    [17] 魏瑞华, 鹿大千, 金楠, 等. 国际近视研究学会(IMI)近视防控研究白皮书解读[J]. 眼科新进展, 2019, 39(8): 701-713. doi: 10.13389/j.cnki.rao.2019.0162

    WEI R H, LU D Q, JIN N, et al. Interpretation of the International myopia Institute white papers focusing on myopia prevention and control[J]. Recent Adv Ophthalmol, 2019, 39(8): 701-713. (in Chinese) doi: 10.13389/j.cnki.rao.2019.0162
    [18] 仝昕炜, 潘同斌, 张宝山, 等. 江苏高校教师超重肥胖与体质的相关性[J]. 四川体育科学, 2023, 42(3): 34-35, 44. https://www.cnki.com.cn/Article/CJFDTOTAL-SCTK202303007.htm

    TONG X W, PAN T B, ZHANG B S, et al. The correlation analysis of overweight obesity and physical fitness among teachers in universities in Jiangsu Province[J]. Sichuan Sports Sci, 2023, 42(3): 34-35, 44. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SCTK202303007.htm
    [19] SULLIVAN D A, ROCHA E M, ARAGONA P, et al. TFOS DEWS Ⅱ sex, gender, and hormones report[J]. Ocul Surf, 2017, 15(3): 284-333. doi: 10.1016/j.jtos.2017.04.001
    [20] SCHRÖDER A, ABRAR D B, HAMPEL U, et al. In vitro effects of sex hormones in human meibomian gland epithelial cells[J]. Exp Eye Res, 2016, 151: 190-202. doi: 10.1016/j.exer.2016.08.009
    [21] BALI J, NEERAJ N, BALI R. Computer vision syndrome: a review[J]. J Clin Ophthalmol Res, 2014, 2(1): 61-68. doi: 10.4103/2320-3897.122661
    [22] KIM D J, LIM C Y, GU N, et al. Visual fatigue induced by viewing a tablet computer with a high-resolution display[J]. Korean J Ophthalmol, 2017, 31(5): 388-393. doi: 10.3341/kjo.2016.0095
    [23] PRABHASAWAT P, PINITPUWADOL W, ANGSRIPRASERT D, et al. Tear film change and ocular symptoms after reading printed book and electronic book: a crossover study[J]. Jpn J Ophthalmol, 2019, 63(2): 137-144. doi: 10.1007/s10384-018-00648-1
    [24] ACOSTA M C, GALLAR J, BELMONTE C. The influence of eye solutions on blinking and ocular comfort at rest and during work at video display terminals[J]. Exp Eye Res, 1999, 68(6): 663-669. doi: 10.1006/exer.1998.0656
    [25] WANG M T, MUNTZ A, WOLFFSOHN J S, et al. Association between dry eye disease, self-perceived health status, and self-reported psychological stress burden[J]. Clin Exp Optom, 2021, 104(8): 835-840. doi: 10.1080/08164622.2021.1887580
    [26] SOLER F, SÁNCHEZ-GARCÍA A, MOLINA-MARTÍN A, 等. 普通用户电子设备使用距离的特征分析[J]. 国际眼科杂志, 2021, 21(9): 1508-1514. https://www.cnki.com.cn/Article/CJFDTOTAL-GJYK202109004.htm

    SOLER F, SÁNCHEZ-GARCÍA A, MOLINA-MARTÍN A, et al. Analysis of the characteristics of electronic equipment usage distance for common users[J]. Int Eye Sci, 2021, 21(9): 1508-1514. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GJYK202109004.htm
    [27] GOLBERSTEIN E, WEN H, MILLER B F. Coronavirus disease 2019 (COVID-19) and mental health for children and adolescents[J]. JAMA Pediatr, 2020, 174(9): 819-820. doi: 10.1001/jamapediatrics.2020.1456
    [28] BAHKIR F A, GRANDEE S S. Impact of the COVID-19 lockdown on digital device-related ocular health[J]. Ind J Ophthalmol, 2020, 68(11): 2378-2383. doi: 10.4103/ijo.IJO_2306_20
    [29] EXELMANS L, Van DEN BULCK J. Bedtime mobile phone use and sleep in adults[J]. Soc Sci Med, 2016, 148: 93-101. doi: 10.1016/j.socscimed.2015.11.037
    [30] DEMIRCI K, AKGÖNVL M, AKPINAR A. Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students[J]. J Behav Addict, 2015, 4(2): 85-92. doi: 10.1556/2006.4.2015.010
    [31] 曹文婷, 嵇红, 杜娜, 等. 青少年视疲劳现况调查及影响因素分析[J]. 吉林医学, 2021, 42(7): 1682-1685. doi: 10.3969/j.issn.1004-0412.2021.07.055

    CAO W T, JI H, DU N, et al. The prevalence and influencing factors of visual fatigue in adolescent[J]. Jilin Med J, 2021, 42(7): 1682-1685. (in Chinese) doi: 10.3969/j.issn.1004-0412.2021.07.055
  • 加载中
表(2)
计量
  • 文章访问数:  344
  • HTML全文浏览量:  153
  • PDF下载量:  29
  • 被引次数: 0
出版历程
  • 收稿日期:  2023-01-11
  • 修回日期:  2023-03-20
  • 网络出版日期:  2023-06-28
  • 刊出日期:  2023-06-25

目录

    /

    返回文章
    返回