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Clinical and Epidemiologic Research  |   July 2015
Time Outdoors and Myopia Progression Over 2 Years in Chinese Children: The Anyang Childhood Eye Study
Author Affiliations & Notes
  • Shi-Ming Li
    Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Science Key Lab, Beijing, China
    Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China
  • He Li
    Anyang Eye Hospital, Anyang, Henan Province, China
  • Si-Yuan Li
    Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Science Key Lab, Beijing, China
  • Luo-Ru Liu
    Anyang Eye Hospital, Anyang, Henan Province, China
  • Meng-Tian Kang
    Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Science Key Lab, Beijing, China
    Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China
  • Yi-Peng Wang
    Anyang Eye Hospital, Anyang, Henan Province, China
  • Fengju Zhang
    Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Science Key Lab, Beijing, China
  • Si-Yan Zhan
    Department of Epidemiology and Health Statistics, Peking University School of Public Health, Beijing, China
  • Bamini Gopinath
    Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute, University of Sydney, Sydney, Australia
  • Paul Mitchell
    Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute, University of Sydney, Sydney, Australia
  • Ningli Wang
    Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Science Key Lab, Beijing, China
    Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China
  • Correspondence: Ningli Wang, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Science Key Lab, Beijing, China; Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China, 100730; wningli@vip.163.com
  • Footnotes
     See the appendix for the members of the Anyang Childhood Eye Study Group.
Investigative Ophthalmology & Visual Science July 2015, Vol.56, 4734-4740. doi:10.1167/iovs.14-15474
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      Shi-Ming Li, He Li, Si-Yuan Li, Luo-Ru Liu, Meng-Tian Kang, Yi-Peng Wang, Fengju Zhang, Si-Yan Zhan, Bamini Gopinath, Paul Mitchell, Ningli Wang, ; Time Outdoors and Myopia Progression Over 2 Years in Chinese Children: The Anyang Childhood Eye Study. Invest. Ophthalmol. Vis. Sci. 2015;56(8):4734-4740. doi: 10.1167/iovs.14-15474.

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Abstract

Purpose: To investigate whether time outdoors and a range of other activities are associated with change in spherical equivalent (SE) and axial length in Chinese children over a period of 2 years.

Methods: A total of 1997 children aged 12.7 ± 0.5 (10.9–15.6) years in the Anyang Childhood Eye Study (ACES) were examined annually (baseline and two follow-up visits). Myopia was defined as cycloplegic SE < −0.50 diopters (D). Questionnaires were administered to the students and parents at baseline to gauge time spent outdoors and on other tasks. We ran mixed linear models including age, sex, and years of follow-up.

Results: In the full cohort of children there was a suggestive association between time spent outdoors and change in axial length; however, the effect size was very small (high versus low tertile: −0.016 mm/y, P = 0.053). The association was observed in children not myopic at baseline (high versus low tertile, −0.036 mm/y; P = 0.009) but not in those already myopic at baseline (high versus low tertile: −0.005 mm/y; P = 0.595). Time outdoors and change in SE showed similar, but nonsignificant, relationships (P > 0.05), perhaps due to insufficient statistical power. The other activities examined and parental myopia were not associated with changes in SE and axial length (P > 0.11).

Conclusions: Within the normal range of variation encountered in these Chinese children, a wide range of activities were largely unrelated to myopia progression at this age. However, there was suggestive evidence that greater time outdoors was associated with slower axial elongation in nonmyopic teenagers, but not in existing myopes.

Myopia is one of the most prevalent ocular disorders among adults and children.1 In adult white populations, myopia affects approximately 30% of the population,2 and myopic retinopathy is already ranked the second to third cause of blindness in Caucasians.3 
In mainland China,4 Taiwan,5 and Japan,6 myopic retinopathy has been ranked the second cause of blindness among adults. In general, myopia has become an important cause of vision loss worldwide, and pathologic myopia affects up to 3% of the whole population in the world.7 
Myopia prevalence in children was shown to vary significantly across different regions, ethnicities, and ages.811 Myopia incidence and myopic shift in children also varied significantly. In Hong Kong, annual myopia incidence and myopic shift were 14% and −0.6 diopters (D) in children aged 5 to 16 years12 and were 8% and −0.2 D in children aged 2 to 6 years.13 In Singapore, these outcomes were 16% and −0.8 D in children aged 7 to 9 years.14 To date, however, few studies have addressed the incidence and progression of myopia among children in mainland China.15,16 
Most previous studies have reported that more time outdoors is associated with decreased myopia prevalence1721 and myopia incidence22,23 in children, although two studies in children of Chinese ethnicity have failed to find such an association.24,25 Progression of myopia has also been reported to be faster in winter than in summer,26,27 indicative of a possible effect of time outdoors on slowing myopia progression. However, Jones-Jordan et al.28 found no association between time outdoors and myopia progression in myopic children. An intervention trial also found a protective effect of outdoor activities in nonmyopic but not myopic subjects.29 Therefore, it is still uncertain whether time outdoors inhibits myopia progression in children with existing myopia.30 Changes in refractive error in school-age children are primarily dependent on axial elongation, which has not always been evaluated in previous studies. 
Here, we sought to evaluate whether time spent outdoors was predictive of future change in refractive error and axial length in a large sample of grade 7 Chinese children over a 2-year period of follow-up. Given that more than half of the children were already myopic at baseline, we also sought to provide a test of whether time outdoors was associated with slower myopia progression in existing myopes. 
Materials and Methods
Study Population
The ACES was a school-based cohort study aiming to annually observe the prevalence, incidence, and progression of myopia among Chinese children in urban areas of Anyang, Henan Province, Central China. Details of the methodology have been previously reported.11 The ACES was approved by the Ethics Committee of Beijing Tongren Hospital, Capital Medical University, and adhered to the tenets of the Declaration of Helsinki. Informed written consent was obtained from at least one parent of each child, as well as verbal assent from all children. During the period from October 2011 to December 2011, 2267 grade 7 students were examined, with a baseline response rate of 95.9%.11 At the first and second follow-up, 93.5% and 83.3% of these students were reexamined, respectively. 
Procedures
Cycloplegia was performed with one drop of topical anesthetic agent (Alcaine; Alcon, Fort Worth, TX, USA), followed by two drops of 1% cyclopentolate (Alcon) and one drop of tropicamide (Mydrin P; Santen, Osaka, Japan) at a 5-minute interval. Thirty minutes after the last drop, autorefraction was performed three times (HRK-7000A; Huvitz, Gunpo, Korea) and the average was used for analyses. The Lenstar LS900 (Haag-Streit, Koeniz, Switzerland) was used to measure axial length. 
An interviewer-administered questionnaire was used for parents to identify the number of myopic parents.31 Time outdoors and near work (h/d) were estimated by an interviewer-administered questionnaire from the students.17,32 The time outdoors question included time engaged in the following outdoor activities: running; swimming; dancing; bicycle riding; playing football, table tennis, badminton, and basketball; exercise between classes; throwing sandbags; skipping rope; rubber band skipping; and kicking shuttlecocks. The near work question included time spent doing school homework, reading extracurricular books, handheld games, drawing, painting, writing, cooking, playing music, playing with pets, and playing chess and cards. The students were asked to identify whether the places for these activities were outdoor or indoor, and to fill out these activities separately for during the school year, the summer vacation, and the winter vacation. The average time performing the activity was calculated as time spent during school year × 9/12 + time spent in vacations × 3/12 according to the school term arrangement of Chinese children. Hours spent doing indoor and outdoor activities during the school day were assumed to be approximately constant for the whole cohort, and so were not individually calculated. 
In the present study, the questionnaire on time outdoors had an overall intraclass correlation coefficient of 0.63 between two repeated surveys (with an interval of 3 weeks), a Cronbach's α coefficient for each item of 0.61, and load values of 12 items on common factors all greater than 0.4.11 Time levels were divided into low, moderate, and high using population tertiles of the average daily hours spent in near work (0.29–2.50 h/d; 2.51–3.71 h/d; 3.72+ h/d) and outdoors (0–1.23 h/d; 1.24–2.27 h/d; 2.27+ h/d). To examine the association between environmental exposures and the development of myopia and high myopia, baseline measures for time outdoors and near work were used.33 
Definitions
Refraction was calculated as the spherical equivalent (SE) averaged between the right and left eyes. We defined myopia as SE < −0.50 D. The number of myopic parents was determined from a questionnaire used in a previous study.31 Myopia progression was considered to be any increase in the myopic SE in myopic children, while in the full cohort such a shift toward a more negative or less positive refractive error was termed a myopic shift. Change in axial length was calculated as the difference in axial length between sequential visits. Age from baseline was defined as the number of years from the first visit with values of 0 (i.e., baseline), 1, or 2. 
Statistical Analysis
General statistical analysis was performed using SAS (v9.3; SAS Institute, Inc., Cary, NC, USA). Measures are presented as mean ± standard deviations (SD) for continuous variables and percentages for categorical variables. Association between exposure variables, changes in SE, and axial length during the follow-up period of 2 years were investigated using linear mixed models (nlme package for R, http://www.r-project.org/, in the public domain), in order to take account of the repeated measurements for individuals in the sample. A full description of this approach has been reported previously.34 Briefly, individual-level random effects were used to explore how each child's change in SE and axial length differed based on time outdoors, near work, or number of myopic parents. Sex, age at baseline, and age from baseline (i.e., number of years from baseline) were included as fixed effects in each model. Exposure variables were coded as categorical variables (low, middle, and high tertiles). Each exposure variable was tested in a separate model to maximize statistical power. Because previous studies have reported an association between time outdoors and incident myopia but not between time outdoors and myopia progression, a model incorporating an interaction term between time outdoors and the presence/absence of myopia at baseline was also tested, that is, whether the effect of time outdoors differed depending on the child's myopia status at baseline. P ≤ 0.05 was considered to be statistically significant. Similarly, we also ran a model that tested for an interaction between time spent outdoors (low, middle, or high tertile) and the number of myopic parents (0, 1, or 2). 
Results
Of 2267 grade 7 students aged 10 to 15 years at baseline, 2140 (94.4%) were reexamined 1 year later, and 1890 (83.4%) were reexamined 2 years later. Mean age at baseline was 12.68 ± 0.48 years, and girls constituted 52.2% of the sample. There were no statistical differences in age, baseline refraction, number of myopic parents, or time spent outdoors, reading, doing homework, computer use, and video games between the 1890 participants who attended both follow-up assessments and the 377 who missed one or both follow-up visits. Among 1890 participants, 1724 had information available for at least one exposure variable. 
Table 1 shows the baseline characteristics of the children. Boys spent significantly more time outdoors (2.35 vs. 1.82 h/d, P < 0.01) and on computer use (0.76 vs. 0.51 h/d, P < 0.01) than girls yet reported a similar time performing reading (0.79 vs. 0.74 h/d, P = 0.20). Boys spent less time on homework (1.67 vs. 1.74 h/d, P = 0.06) and more time on video games (0.76 vs. 0.51 h/d, P = 0.07) with a borderline significance. 
Table 1
 
Baseline Characteristics of the Study Cohort
Table 1
 
Baseline Characteristics of the Study Cohort
In the model that included the full cohort of participants, the mean change in SE per year in the sample was −0.48 (95% confidence interval [CI], −0.54 to −0.42) D, and the mean change in axial length per year was 0.24 (95% CI, 0.23–0.26) mm. Both age at baseline (P < 0.01) and age from baseline (P < 0.01) were positively associated with change in SE and negatively associated with change in axial length (Table 2), indicating that, on average, the older the child and the longer the period of follow-up, the slower the progression toward myopia (or the reduction in hyperopia) and the slower the rate of axial elongation. These age-related nonexposure variables were adjusted for in all subsequent the models, along with sex. 
Table 2
 
Association Between Change in Spherical Equivalent (D/y) or Axial Length (mm/y) and Nonexposure Variables for the Model in the Full Cohort of Children
Table 2
 
Association Between Change in Spherical Equivalent (D/y) or Axial Length (mm/y) and Nonexposure Variables for the Model in the Full Cohort of Children
Although time outdoors was not associated with change in SE in the full cohort of children (P > 0.19; Table 3), or in those children who were or were not myopic at baseline (P > 0.24; Table 4; Fig. 1A), time outdoors had a borderline significant association with change in axial length in the full cohort of children (high versus low time outdoors tertile, P = 0.054; Table 3; Fig. 1B). This association was also observed in children who were not myopic at baseline (high versus middle tertile, P = 0.024; high versus low tertile, P = 0.009; Table 4) but not in children who were already myopic at baseline (P = 0.996 and P = 0.595, respectively; Table 4). Indeed, for the analysis of change in axial length there was a significant interaction between time outdoors and myopia status at baseline (P = 0.015 and P = 0.010, respectively; Table 5; Fig. 1B). There was no comparable interaction between time outdoors and number of myopic parents (P > 0.26; Table 5; Fig. 2B). Furthermore, no association with change in SE or with change in axial length was observed for any of the other exposure variables that were assessed. 
Table 3
 
Association Between Change in Spherical Equivalent (D/y) or Change in Axial Length (mm/y) and Each Exposure Variable for the Full Cohort of Children
Table 3
 
Association Between Change in Spherical Equivalent (D/y) or Change in Axial Length (mm/y) and Each Exposure Variable for the Full Cohort of Children
Table 4
 
Association of Time Outdoors With Change in Spherical Equivalent (D/y) or Change in Axial Elongation (mm/y) in Children Classified as Myopic and Nonmyopic at Baseline
Table 4
 
Association of Time Outdoors With Change in Spherical Equivalent (D/y) or Change in Axial Elongation (mm/y) in Children Classified as Myopic and Nonmyopic at Baseline
Figure 1
 
Association between time outdoors and annual change in spherical equivalent (A) and between time outdoors and annual change in axial length (B) among myopic and nonmyopic children, respectively. The points and lines show predictions from the best-fit linear mixed model that included sex, age at baseline, and age from baseline.
Figure 1
 
Association between time outdoors and annual change in spherical equivalent (A) and between time outdoors and annual change in axial length (B) among myopic and nonmyopic children, respectively. The points and lines show predictions from the best-fit linear mixed model that included sex, age at baseline, and age from baseline.
Table 5
 
Tests for Interaction Between Time Outdoors, and Either the Presence/Absence of Myopia at Baseline or the Number of Myopic Parents
Table 5
 
Tests for Interaction Between Time Outdoors, and Either the Presence/Absence of Myopia at Baseline or the Number of Myopic Parents
Figure 2
 
The interaction between time outdoors and number of myopic parents for association with annual change in spherical equivalent (A) and annual change in axial length (B). The points and lines show predictions from the best-fit linear mixed model that included sex, age at baseline, age from baseline, and myopia status at baseline.
Figure 2
 
The interaction between time outdoors and number of myopic parents for association with annual change in spherical equivalent (A) and annual change in axial length (B). The points and lines show predictions from the best-fit linear mixed model that included sex, age at baseline, age from baseline, and myopia status at baseline.
Discussion
Our findings showed that in a school-based population of Chinese children aged 10 to 15 years in Central China, a wide range of indoor and outdoor activities showed little or no relationship with the changes in refractive error and axial length that occurred in the next 2 years. In fact, the only activity variable with evidence of an association with refractive error development was the time children spent outdoors, which had a borderline significant association with the rate of axial elongation over the 2-year follow-up period. Interestingly, the association with time outdoors appeared to be restricted to children who were not myopic at baseline (Table 4; Fig. 1B) and occurred in the direction that greater time outdoors was associated with a slower rate of axial elongation. Children already myopic at baseline showed a rate of axial elongation that did not vary significantly with the time they spent outdoors and that was faster than in those not myopic at baseline (Table 5; Fig. 1B). The relationship between time outdoors and change in SE showed the same trends as that between time outdoors and change in axial length (Table 4; Fig. 1A); however, there was no significant association between time outdoors and change in refractive error either in the full cohort (Table 3) or in children who were or were not myopic at baseline (Table 5). The most parsimonious explanation for the disparate results between the axial and refractive changes is that the models analyzing change in SE were less powerful than those for change in axial length—perhaps reflecting the greater accuracy and repeatability with which the latter can be measured35—and thus it seems likely that a lack of statistical power led to the results for change in SE failing to reach statistical significance. While the lack of consistency between our axial and refractive findings do not allow us to draw definitive conclusions, they suggest that time spent outdoors is not predictive of myopia progression in existing myopes (unlike the reproducibly observed role of time outdoors in predicting incident myopia22,23). 
In the present study, a range of near tasks—including reading, using a computer, playing video games, and doing homework—also were not associated with future changes in SE or axial length. Therefore, either these behaviors are not causally involved in the refractive shift toward myopia that occurred in the study cohort, on average, or the levels of variation in these behaviors within the study sample were too narrow for us to detect any associations; for example, potentially too few children spent a short enough time reading to reduce their incidence or progression of myopia relative to their peers. Recent work by Jones-Jordan et al.36 demonstrated that child-specific environmental factors including near work and outdoor activity reduced the between-sibling correlation for refractive error by only 0.5%, suggesting that environmental factors such as outdoor activities have a limited impact on the degree of myopia, or that they have an impact only at specific time(s) during childhood that are not well captured by current measurement instruments. In a longitudinal study of 835 myopic children by the same research group,28 there was no association between time outdoors and either myopia progression or axial elongation. Our findings were consistent with those of the latter study.28 In contrast, Guo et al.37 reported that axial elongation was significantly associated with less time spent outdoors (P = 0.02, standardized coefficient β −0.12) in 643 Beijing primary school children; however, there was no separate analysis in children who were or were not myopic at baseline.37 The children in the study by Guo et al.37 were mostly younger (range, 5–13, mean, 7.7 years) than those studied here, which may account for the difference in results. 
French et al.30 have argued that the failure of the time outdoors to show an association with myopia progression, as opposed to myopia incidence, is likely to be a statistical problem, given that myopic children tend to be derived from a segment of the population who tend to do more near work and spend less time outdoors. This would limit the amount of variation within the population of those with existing myopia, making statistical significance more difficult to achieve. In our study cohort, myopic and nonmyopic children spent similar amounts of time outdoors (2.04 vs. 2.17 h/d, P = 0.08), and the variance in time outdoors was also similar in myopes and nonmyopes (Table 1). This makes it unlikely that differences in time spent outdoors—at least at the age at which the information was collected here—could explain the faster myopic shift we observed in myopic versus nonmyopic children. A threshold effect of time outdoors on myopia progression has also been suggested to explain the difference in effect observed previously between myopic and nonmyopic children.30 
Consistent with some previous studies,23,38 we found a weak positive correlation between near tasks and outdoor activities. Such results support the idea18 that any protective effect of time outdoors against myopia is not simply due to a reduction in near work. Seasonal differences in progression rates26,27 and the small number of intervention trials published to date29,39 (Morgan IG, et al. IOVS 2012;53:E-Abstract 2753) support the theory that spending more time outdoors can slow the incidence—and possibly the progression—of myopia in children. Future research in this area will be important in providing an evidence base for the use of increased time outdoors, or increased exposure to bright lighting, as a potential therapy. 
Strengths of our study were that it included a large number of children in a setting in which a high proportion typically develop myopia; it had a high response to follow-up; and it included data on both cycloplegic autorefraction and axial length. Although ACES is a school-based, not a population-based cohort study, the attendance of students in Anyang was greater than 99% due to the compulsory education system. However, a potential limitation should be mentioned: Time spent outdoors and time performing near tasks were self-reported. This could have been a source of recall bias, although this type of questionnaire-based assessment has been adopted widely, including in studies that found strong associations between time outdoors and myopia.17,30,32 
In summary, this prospective cohort study revealed that time outdoors was not significantly associated with change in refractive error or change in axial length over a 2-year period in a population of Chinese children aged 10 to 15 years. In children who were not myopic at baseline, the rate of axial elongation was lower (by ∼0.03 D/y; P < 0.05) in children who spent more time outdoors, yet this was not matched by a slower shift toward a more myopic refractive error—possibly due to insufficient statistical power to detect such a small effect. The rate of axial elongation was not associated with time spent outdoors in the children who were already myopic at baseline. 
Acknowledgments
The authors thank the Anyang city government for its support in helping to organize the survey. 
Supported by the Major State Basic Research Development Program of China (973 Program, 2011CB504601) of the Ministry of Science and Technology, the Major International (Regional) Joint Research Project of the National Natural Science Foundation of China (81120108007), Beijing Nova Program (Z121107002512055), and the National Natural Science Foundation of China (81300797). The authors alone are responsible for the content and writing of the paper. 
Disclosure: S.-M. Li, None; H. Li, None; S.-Y. Li, None; L.-R. Liu, None; M.-T. Kang, None; Y.-P. Wang, None; F. Zhang, None; S.-Y. Zhan, None; B. Gopinath, None; P. Mitchell, None; N. Wang, None 
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Appendix
The Anyang Childhood Eye Study Group
STUDY CHAIR'S OFFICE: Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China: Ningli Wang (Principal Investigator), Shi-Ming Li (Project Manager and Executive Principal Investigator), Luo-Ru Liu (Co-principal Investigator, Anyang Eye Hospital, Henan Province, Anyang, China), Paul Mitchell (Co-principal Investigator, Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute, University of Sydney, Sydney, Australia). 
COORDINATING CENTER: Anyang Education Bureau, Henan Province, Anyang, China: Xiuzi Zhou (Coordinator). Anyang Health Bureau, Henan Province, Anyang, China: Weixin He (Coordinator). Anyang Eye Hospital, Henan Province, Anyang, China: Wenjie Li, Yazhou Ji, Fangrong Shi, Jiyuan Guo (Coordinators). 
MAIN INVESTIGATORS: Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China: Fengju Zhang, Si-Yuan Li, Meng-Tian Kang, Jin Fu, Lei Li, Shiqiang Zhao, Yang Wang, Yan Xu, Zhou Yang. Department of Ophthalmology, Tongzhou Maternal and Child Health Hospital of Beijing, Beijing China: Bi-Dan Zhu. Anyang Eye Hospital, Henan Province, Anyang, China: Yazhou Ji, Hailin Meng, He Li, Fangrong Shi, Yongfang Tu, Yipeng Wang, Hongliang Zhang, Donghai Yang, Wenfang Niu, Jinling Li, Jiyuan Guo, Baohong Han, Lin Jia, Zuowei Qi, Zhenhuai Kang, Bing Cao, Xianfang Du, Yicao Zhang, Chuanqi Xie, Bingqi Zhang, Songtao Li. Department of Ophthalmology, Zhengzhou Second Hospital, Zhengzhou, China: Xiaoyuan Yang. Institute of Biophysics, Chinese Academy of Sciences, Beijing, China: Bo Wang. 
COMMITTEES: Data and Safety Monitoring: Si-Yan Zhang (Epidemiologist), Hongyuan Wang (Statistician), Department of Epidemiology and Health Statistics, Peking University School of Public Health, Beijing, China; Xiaoxia Peng (Statistician), School of Public Health, Capital Medical University, Beijing, China; Lei Li (Data Analyst), Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China. 
Figure 1
 
Association between time outdoors and annual change in spherical equivalent (A) and between time outdoors and annual change in axial length (B) among myopic and nonmyopic children, respectively. The points and lines show predictions from the best-fit linear mixed model that included sex, age at baseline, and age from baseline.
Figure 1
 
Association between time outdoors and annual change in spherical equivalent (A) and between time outdoors and annual change in axial length (B) among myopic and nonmyopic children, respectively. The points and lines show predictions from the best-fit linear mixed model that included sex, age at baseline, and age from baseline.
Figure 2
 
The interaction between time outdoors and number of myopic parents for association with annual change in spherical equivalent (A) and annual change in axial length (B). The points and lines show predictions from the best-fit linear mixed model that included sex, age at baseline, age from baseline, and myopia status at baseline.
Figure 2
 
The interaction between time outdoors and number of myopic parents for association with annual change in spherical equivalent (A) and annual change in axial length (B). The points and lines show predictions from the best-fit linear mixed model that included sex, age at baseline, age from baseline, and myopia status at baseline.
Table 1
 
Baseline Characteristics of the Study Cohort
Table 1
 
Baseline Characteristics of the Study Cohort
Table 2
 
Association Between Change in Spherical Equivalent (D/y) or Axial Length (mm/y) and Nonexposure Variables for the Model in the Full Cohort of Children
Table 2
 
Association Between Change in Spherical Equivalent (D/y) or Axial Length (mm/y) and Nonexposure Variables for the Model in the Full Cohort of Children
Table 3
 
Association Between Change in Spherical Equivalent (D/y) or Change in Axial Length (mm/y) and Each Exposure Variable for the Full Cohort of Children
Table 3
 
Association Between Change in Spherical Equivalent (D/y) or Change in Axial Length (mm/y) and Each Exposure Variable for the Full Cohort of Children
Table 4
 
Association of Time Outdoors With Change in Spherical Equivalent (D/y) or Change in Axial Elongation (mm/y) in Children Classified as Myopic and Nonmyopic at Baseline
Table 4
 
Association of Time Outdoors With Change in Spherical Equivalent (D/y) or Change in Axial Elongation (mm/y) in Children Classified as Myopic and Nonmyopic at Baseline
Table 5
 
Tests for Interaction Between Time Outdoors, and Either the Presence/Absence of Myopia at Baseline or the Number of Myopic Parents
Table 5
 
Tests for Interaction Between Time Outdoors, and Either the Presence/Absence of Myopia at Baseline or the Number of Myopic Parents
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