Abstract
Previous studies used the Normalized Difference Vegetation Index (NDVI) to assess green space and showed its potential protective effect on myopia. However, this top-down measurement of green space cannot fully reflect the eye-level greenness perception. This study used the Vision Greenness Index (VGI) to assess visual greenness from street-view images and compare its effect on myopia with NDVI. This multicenter, cross-sectional study investigated 69,051 children from 146 schools in five cities in Hubei, ranging from kindergarten to high school. Visual greenness was calculated from street-view images with DeepLab v3 and NDVI was calculated from Landsat 8 satellite observations. Regression models were used to analyze the relationship between school myopia and environmental factors. The partial correlation coefficient between VGI within a 5,000-m buffer zone and myopia was − 0.343 (P = 0.038) and − 0.326 (P < 0.001) in Models 1 (all schools) and 2 (schools except high schools), respectively, whereas NDVI showed no significant results. In Model 3 (kindergartens), the partial correlation coefficients between VGI and NDVI within a 5,000-m buffer zone were − 0.675 (P = 0.029) and − 0.380 (P = 0.032), respectively. In Model 4 (elementary schools), the partial correlation coefficients between VGI and NVDI within a 5,000-m buffer zone were − 0.310 (P = 0.027) and − 0.088 (P = 0.043), respectively. Model 5 (high schools) did not demonstrate any correlations between the identified factors and the prevalence of myopia during high school. VGI demonstrated a more significant relation to the myopia than NVDI. Visual greenness was found to be related to myopia in kindergartens and elementary schools rather than in high school, indicating its more significant association with a lower prevalence of myopia in early school ages than in high school.
Data availability
The data that has been used is commonly confidential. The parameters in our model (text, tables, figures, models, and appendices) are only available on reasonable request from the author Dihao Hua (Email: [dihaohuaphd@163.com](mailto: dihaohuaphd@163.com) ) under certain conditions, with the consent of all participating centers and with a signed data access agreement.
Abbreviations
- NDVI:
-
Normalized Difference Vegetation Index
- VGI:
-
Vision Greenness Index
- VIF:
-
Variance inflation factor
- AIC:
-
Akaike Information Criterion
References
Morgan, I. G., Ohno-Matsui, K. & Saw, S. M. Myopia. Lancet 379 (9827), 1739–1748. https://doi.org/10.1016/s0140-6736(12)60272-4 (2012).
Holden, B. A. et al. Global prevalence of myopia and high myopia and Temporal trends from 2000 through 2050. Ophthalmology 123 (5), 1036–1042. https://doi.org/10.1016/j.ophtha.2016.01.006 (2016).
Hu, Y. et al. Association of age at myopia onset with risk of high myopia in adulthood in a 12-year follow-up of a Chinese cohort. JAMA Ophthalmol. 138 (11), 1129–1134. https://doi.org/10.1001/jamaophthalmol.2020.3451 (2020).
Jonas, J. B., Wang, Y. X., Dong, L. & Panda-Jonas, S. High myopia and glaucoma-like optic neuropathy. Asia-Pacific J. Ophthalmol. (Philadelphia Pa). 9 (3), 234–238. https://doi.org/10.1097/apo.0000000000000288 (2020).
Haarman, A. E. G. et al. The complications of myopia: a review and meta-analysis. Investig. Ophthalmol. Vis. Sci. 61 (4), 49. https://doi.org/10.1167/iovs.61.4.49 (2020).
Ma, Y. et al. Healthcare utilization and economic burden of myopia in urban china: a nationwide cost-of-illness study. J. Global Health. 12, 11003. https://doi.org/10.7189/jogh.12.11003 (2022).
Naidoo, K. S. et al. Potential lost productivity resulting from the global burden of myopia: systematic review, meta-analysis, and modeling. Ophthalmology 126 (3), 338–346. https://doi.org/10.1016/j.ophtha.2018.10.029 (2019).
Li, R. et al. Implementing a digital comprehensive myopia prevention and control strategy for children and adolescents in china: a cost-effectiveness analysis. Lancet Reg. Health Western Pac. 38, 100837. https://doi.org/10.1016/j.lanwpc.2023.100837 (2023).
Morgan, I. G. et al. Imi risk factors for myopia. Investig. Ophthalmol. Vis. Sci. 62 (5), 3. https://doi.org/10.1167/iovs.62.5.3 (2021).
Choi, K. Y., Chan, S. S. & Chan, H. H. The effect of spatially-related environmental risk factors in visual scenes on myopia. Clin. Exp. Optometry. 105 (4), 353–361. https://doi.org/10.1080/08164622.2021.1983400 (2022).
Eppenberger, L. S. & Sturm, V. The role of time exposed to outdoor light for myopia prevalence and progression: a literature review. Clin. Ophthalmol. (Auckland NZ). 14, 1875–1890. https://doi.org/10.2147/opth.S245192 (2020).
Yuan, T. & Zou, H. Effects of air pollution on myopia: an update on clinical evidence and biological mechanisms. Environ. Sci. Pollut. Res. Int. 29 (47), 70674–70685. https://doi.org/10.1007/s11356-022-22764-9 (2022).
Cui, Q. et al. Impacts of environments on school myopia by Spatial analysis techniques in Wuhan. Sci. Rep. 14 (1), 29941. https://doi.org/10.1038/s41598-024-81270-9 (2024).
Zhang, C. et al. Effects of greenness on myopia risk and school-level myopia prevalence among high school-aged adolescents: cross-sectional study. JMIR public. Health Surveill. 9, e42694. https://doi.org/10.2196/42694 (2023).
Lu, C. et al. Socioeconomic disparities and green space associated with myopia among Chinese school-aged students: a population-based cohort study. J. Global Health. 14, 04140. https://doi.org/10.7189/jogh.14.04140 (2024).
Zhao, L. et al. Prevalence and risk factors of myopia among children and adolescents in Hangzhou. Sci. Rep. 14, 24615. https://doi.org/10.1038/s41598-024-73388-7 (2024).
Clark, R. et al. Time spent outdoors partly accounts for the effect of education on myopia. Investig. Ophthalmol. Vis. Sci. 64, 2563. https://doi.org/10.1167/iovs.64.14.38 (2023).
Nguyen, P. Y., Astell-Burt, T., Rahimi-Ardabili, H. & Feng, X. Green space quality and health: a systematic review. Int. J. Environ. Res. Public Health. 18, 21. https://doi.org/10.3390/ijerph182111028 (2021).
Rahimi-Ardabili, H. et al. Green space and health in Mainland china: a systematic review. Int. J. Environ. Res. Public Health. 18, 18. https://doi.org/10.3390/ijerph18189937 (2021).
Yang, Y. et al. Green space morphology and school myopia in China. JAMA Ophthalmol. 142 (2), 115–122. https://doi.org/10.1001/jamaophthalmol.2023.6015 (2024).
Yang, B. Y. et al. Greenness surrounding schools and visual impairment in Chinese children and adolescents. Environ. Health Perspect. 129 (10), 107006. https://doi.org/10.1289/ehp8429 (2021).
Yang, Y. et al. Spatial technology assessment of green space exposure and myopia. Ophthalmology 129 (1), 113–117. https://doi.org/10.1016/j.ophtha.2021.07.031 (2022).
Martinez, A. I. & Labib, S. M. Demystifying normalized difference vegetation index (Ndvi) for greenness exposure assessments and policy interventions in urban greening. Environ. Res. 220, 115155. https://doi.org/10.1016/j.envres.2022.115155 (2023).
Larkin, A. & Hystad, P. Evaluating street view exposure measures of visible green space for health research. J. Expo. Sci. Environ. Epidemiol. 29 (4), 447–456. https://doi.org/10.1038/s41370-018-0017-1 (2019).
Labib, S. M., Huck, J. J. & Lindley, S. Modelling and mapping eye-level greenness visibility exposure using multi-source data at high Spatial resolutions. Sci. Total Environ. 2021, 755. https://doi.org/10.1016/j.scitotenv.2020.143050 (2021).
Shi, X. et al. Measuring greenspace in rural areas for studies of birth outcomes: a comparison of street view data and satellite data. GeoHealth 8 (4), e2024GH001012 (2024).
Helbich, M. et al. Using deep learning to examine street view green and blue spaces and their associations with geriatric depression in Beijing, China. Environ. Int. 126, 107–117. https://doi.org/10.1016/j.envint.2019.02.013 (2019).
Wang, R. et al. Exploring the impacts of street-level greenspace on stroke and cardiovascular diseases in Chinese adults. Ecotoxicol. Environ. Saf. 243, 562. https://doi.org/10.1016/j.ecoenv.2022.113974 (2022).
Flitcroft, D. I. et al. Imi - Defining and classifying myopia: a proposed set of standards for clinical and epidemiologic studies. Investig. Ophthalmol. Vis. Sci. 60 (3), M20–m30. https://doi.org/10.1167/iovs.18-25957 (2019).
Martinez-Sanchez, L. et al. Semantic segmentation dataset of land use/cover area frame survey (lucas) rural landscape street view images. Data brief. 54, 110394. https://doi.org/10.1016/j.dib.2024.110394 (2024).
Pan, W. Akaike’s information criterion in generalized estimating equations. Biometrics 57 (1), 120–125. https://doi.org/10.1111/j.0006-341x.2001.00120.x (2001).
Labib, S. M., Lindley, S. & Huck, J. J. Spatial dimensions of the influence of urban green-blue spaces on human health: a systematic review. Environ. Res. 180, 108869. https://doi.org/10.1016/j.envres.2019.108869 (2020).
Wang, R., Feng, Z., Pearce, J., Liu, Y. & Dong, G. Are greenspace quantity and quality associated with mental health through different mechanisms in Guangzhou, china: a comparison study using street view data. Environ. Pollution (Barking Essex: 1987). 290, 117976. https://doi.org/10.1016/j.envpol.2021.117976 (2021).
Yi, L. et al. Satellite-based and street-view green space and adiposity in Us children. JAMA Netw. open. 7 (12), e2449113. https://doi.org/10.1001/jamanetworkopen.2024.49113 (2024).
Yi, L. et al. Assessing greenspace and cardiovascular health through deep-learning analysis of street-view imagery in a cohort of Us children. Environ. Res. 265, 120459. https://doi.org/10.1016/j.envres.2024.120459 (2025).
Kumakoshi, Y., Chan, S. Y., Koizumi, H., Li, X. & Yoshimura, Y. Standardized green view index and quantification of different metrics of urban green vegetation. Sustainability 12 (18), 7434 (2020).
Peng, B. A., Naduvilath, T. J., Flitcroft, D. I. & Jong, M. Is myopia prevalence related to outdoor green space? Ophthalmic Physiol. Opt. 41 (6), 1371–1381. https://doi.org/10.1111/opo.12896 (2021).
Morgan, I. G., He, M. & Rose, K. A. Epidemic of pathologic myopia: what can laboratory studies and epidemiology tell us? Retina (Philadelphia Pa). 37 (5), 989–997. https://doi.org/10.1097/iae.0000000000001272 (2017).
Rose, K. A., French, A. N. & Morgan, I. G. Environmental factors and myopia: paradoxes and prospects for prevention. Asia-Pacific J. Ophthalmol. (Philadelphia Pa). 5 (6), 403–410. https://doi.org/10.1097/apo.0000000000000233 (2016).
Wang, J. et al. Outdoor time could regulate the effects of green environment on myopia in Chinese children and adolescents. Ophthalmic Epidemiol. 2025, 1–10. https://doi.org/10.1080/09286586.2025.2475207 (2025).
Fernandes, A. et al. Availability, accessibility, and use of green spaces and cognitive development in primary school children. Environ. Pollut. 334, 122143. https://doi.org/10.1016/j.envpol.2023.122143 (2023).
Wang, J. et al. Association of built environment attributes with screening myopia among children and adolescents: large-sample, cross-sectional, observational evidence from Shanghai, China. SSRN Electron. J. https://doi.org/10.2139/ssrn.4124055 (2022).
Huang, L. et al. Association between greater residential greenness and decreased risk of preschool myopia and astigmatism. Environ. Res. 196, 110976. https://doi.org/10.1016/j.envres.2021.110976 (2021).
Flitcroft, D. I., Harb, E. N. & Wildsoet, C. F. The Spatial frequency content of urban and indoor environments as a potential risk factor for myopia development. Investig. Ophthalmol. Vis. Sci. 61 (11), 42. https://doi.org/10.1167/iovs.61.11.42 (2020).
Li, D. L. et al. Lower indoor Spatial frequency increases the risk of myopia in children. Br. J. Ophthalmol. https://doi.org/10.1136/bjo-2024-325888 (2024).
Wu, P-C. et al. Myopia prevention and outdoor light intensity in a school-based cluster randomized trial. Ophthalmology 125 (8), 1239–1250. https://doi.org/10.1016/j.ophtha.2017.12.011 (2018).
Wei, C. C. et al. Pm2.5 and nox exposure promote myopia: clinical evidence and experimental proof. Environ. Pollut. 254, 113031. https://doi.org/10.1016/j.envpol.2019.113031 (2019).
Cho, P. & Tan, Q. Myopia and orthokeratology for myopia control. Clin. Exp. Optometry. 102 (4), 364–377. https://doi.org/10.1111/cxo.12839 (2019).
Jiang, D. D., Zhao, C. P., Ding, W. Z. & Leng, L. The role of peripheral retinal defocus in myopia progression. Chin. J. Ophthalmol. 60 (6), 541–546. https://doi.org/10.3760/cma.j.cn112142-20231024-00173 (2024).
Jiang, Y. et al. Effect of repeated low-level red-light therapy for myopia control in children: a multicenter randomized controlled trial. Ophthalmology 129 (5), 509–519. https://doi.org/10.1016/j.ophtha.2021.11.023 (2022).
Morgan, I. G. & Jan, C. L. China turns to school reform to control the myopia epidemic: a narrative review. Asia-Pac. J. Ophthalmol. (Philadelphia, Pa). 11 (1), 27–35. https://doi.org/10.1097/apo.0000000000000489 (2022).
Morgan, I. G. & Lan, W. New clinical and public health perspectives on myopia prevention and control in China. Eye (Lond. Engl.) 38 (1), 8–9. https://doi.org/10.1038/s41433-023-02625-6 (2024).
Zhu, Z. et al. Interventions recommended for myopia prevention and control among children and adolescents in china: a systematic review. Br. J. Ophthalmol. 107 (2), 160–166. https://doi.org/10.1136/bjophthalmol-2021-319306 (2023).
Wang, R. et al. Dynamic greenspace exposure and residents’ mental health in Guangzhou, china: from over-head to eye-level perspective, from quantity to quality. Landsc. Urban Plann. 215, 104230. https://doi.org/10.1016/j.landurbplan.2021.104230 (2021).
Zhang, W. & Zeng, H. Spatial differentiation characteristics and influencing factors of the green view index in urban areas based on street view images: a case study of Futian District, Shenzhen, China. Urban Forestry Urban Green. 93, 128219. https://doi.org/10.1016/j.ufug.2024.128219 (2024).
Gibaldi, A., Harb, E. N., Wildsoet, C. F. & Banks, M. S. A child-friendly wearable device for quantifying environmental risk factors for myopia. Transl. Vis. Sci. Technol. 13, 28. https://doi.org/10.1167/tvst.13.10.28 (2024).
Wen, L. et al. The Clouclip, a wearable device for measuring near-work and outdoor time: validation and comparison of objective measures with questionnaire estimates. Acta Ophthalmol. 99, e1222–e1235. https://doi.org/10.1111/aos.14785 (2021).
Funding
National Natural Science Foundation of China (NO. 42201457).
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Conceptualization, D.H.; Writing–original draft preparation, D.H., T.Y., C.Q., J.Z.; Writing—review and editing, Z.Y., Y.X., C.C, and Z.C.; Funding acquisition, D.H.; Visualization, D.H., T.Y., C.Q.; Resources, D.H., J.Z., G.L., A.S., W.S., M.M.; Investigation, F.Z., R.Z. All the authors have read and agreed to the published version of the manuscript.
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The study was approved by the Ethics Committee of Renmin Hospital of Wuhan University (WDRY2020-K234) and followed the tenets of the Declaration of Helsinki. Informed consent was obtained from all the subjects in this study.
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Hua, D., Yang, T., Cui, Q. et al. Using deep learning to explore the impacts of street-view green space on school myopia prevalence: a multicenter, cross-sectional study. Sci Rep (2026). https://doi.org/10.1038/s41598-026-40477-8
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DOI: https://doi.org/10.1038/s41598-026-40477-8
