A higher shadow ratio of the living environment on the remote sensing digital image is possibly protective for adolescent myopia

doi:10.21203/rs.3.rs-4702497/v1

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A higher shadow ratio of the living environment on the remote sensing digital image is possibly protective for adolescent myopia

https://doi.org/10.21203/rs.3.rs-4702497/v1

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This study aims to assess how the construction patterns within residential communities influence the adolescent myopia using cluster sampling. In a private high school from a megacity in mid-west China, a questionnaire gathered data on the 10th-grade students' level of myopia, home address, and some potential confounding factors. Additionally, satellite digital images were utilized to calculate the proportion of shadow area (PSA) and the proportion of greenness area (PGA) within a 500m×500m area centered on each student's home address. Correlations between myopia levels and PSA, along with other variables, were analyzed. The prevalence of mild, moderate, and high myopia were 39.2%, 32.5%, and 8.3%, respectively. A negative correlation was observed between myopia levels and PSA, albeit marginally significant (r=-0.189*, P = 0.05). Upon dividing the sample into higher and lower PSA groups using a cut-off point of 20%, a significant difference in myopia levels was evident (χ2 = 8.361, P = 0.038), while other confounding factors remained comparable. In conclusion, high-rise apartment constructions, which often cast more shadows on digital satellite maps, may not exacerbate myopia progression. Instead, they could potentially serve as a protective factor against adolescent myopia in densely populated megacities, as they allow for more ground space allocation.

Health sciences/Diseases

Health sciences/Risk factors

adolescent myopia

megacity

remote sensing digital image

shadow

living environment

Uncorrected refractive error, especially myopia, is the most common cause of vision impairment worldwide and the second most common cause of reversible blindness (1). Therefore, myopia has attracted increasing attention. However, myopia is an increasingly widespread condition around the world, particularly in east Asia (2). And east Asia shows by far the greatest productivity loss resulting from myopia in total dollar terms in the world (3). In China, the prevalence of myopia among teenagers has shown a concerning trend, escalating from 48.4% prior to 2008 to 84.8% post-2013 in individuals aged 16 to 18 (4). Expected increases in myopia prevalence are likely to cause greatly increased public health and economic problems in the future (3). Hence, strategies are warranted to reduce the prevalence and the progression of myopia. A comprehensive understanding of the factors contributing to myopia development is imperative for devising effective prevention strategies. Numerous factors have been proposed to play a role in myopia onset, ranging from non-modifiable genetic predispositions (5) and physical characteristics (6), to modifiable environmental influences (7), educational attainment (8), outdoor exposure (9), and digital device usage (10), among others. A review by the International Myopia Institute highlighted the significant associations of time spent outdoors, educational attainment, and parental myopia with myopia development (11). In recent years, attention has increasingly turned towards housing and living environments as potential contributors to the myopia epidemic. Reduced exposure to green spaces has been identified as a potential risk factor for myopia (12, 13). Disparities in myopia prevalence have been observed between urban and suburban regions and across different housing types, as evidenced by a study conducted in Sydney (14). In another study in Hong Kong (15), small home size was supposed to be an environmental threat for myopia development.

Over the past three decades, China has undergone rapid urbanization on an unprecedented scale. It is projected that by 2030, China's urbanization rate will reach 70%, reflecting the migration of nearly 300 million individuals from rural to urban areas (16). Accompanying this urbanization, there has been a notable shift in housing types, transitioning predominantly from low-rise multistory flats to high-rise apartment complexes. However, the potential impact of these changes in residential environments on myopia development remains largely unexplored.

In this study, we aimed to investigate the influence of residential transformations on myopia development by collecting questionnaires from a homogeneous sample in a major city in mid-west China. Additionally, we utilized a commercial digital satellite mapping tool to quantify the extent of building shadows within the relevant communities, serving as a proxy measure for residential changes. Through this investigation, we endeavor to contribute to the understanding of how urbanization and housing alterations may shape the prevalence of myopia in urban environments.

Study design and population

We conducted a clustered sampling of 10th-grade students enrolled in the International Course Center at Xi’an Gao Xin No. 1 High School, situated in Xi’an, a major city characterized by a blend of tradition and modernization in mid-west China. In May 2023, following a popular science lecture on myopia delivered by an ophthalmologist and optometrist (Z.L.), we administered a questionnaire, as detailed in Table 1, to each student anonymously. Non-myopic eyes were defined as those with an equivalent spherical lens (ESL) greater than -0.5D, while other categories included mild myopia (ESL between -3.0D to -0.5D), moderate myopia (ESL between -6.0D to -3.0D), and high myopia (ESL ≤ -6.0D).

Of primary interest was the residential address where each survey participant predominantly resided within the past six years. Based on the review of risk factors for myopia from the International Myopia Institute (11), the confounding factors we assessed in the questionnaire included parental myopia status, time spent outdoors, time dedicated to near-work activities, and the utilization of orthokeratology lenses which have been widely used in China to control the progress of adolescent myopia. Notably, the inquiry into the use of low-dose atropine was omitted from the questionnaire as it has yet to receive official approval from the Chinese Food and Drug Administration (CFDA). To ensure the accuracy of responses, the questionnaires were not distributed and collected on the same day, allowing students to engage in thorough discussions with their parents.

The studies involving human participants followed the tenets of Declaration of Helsinki and were reviewed and approved by the Ethics Committee and Institutional Review Board of The First Affiliated Hospital of Xi’an Jiaotong University. We confirmed that all experiments were performed in accordance with relevant guidelines and regulations. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.

Image processing and measurements

A commercially available digital satellite map (Gao De software, (2023) No.4047, Beijing, China. Image source: DigitalGlobe&spaceview) was utilized to geolocate the residential addresses, and a 500m×500m area of the image centered on each automatic label was extracted from the map (as depicted in Figure 1). Subsequently, the full-color image was converted into a histogram image using the “Color Inspector 3D” plugin within the ImageJ software (version 1.53t, developed by Wayne Rasband and contributors at the National Institutes of Health, USA). Adjustments to brightness and contrast were made to optimize the delineation of shadows, typically composed of one to three RGB values. We developed a novel metric, the proportion of shadow area (PSA), to approximate the residential environment of a community by quantifying the shadows cast by buildings in remote sensing digital images, given that the sun-synchronous orbit satellite passes a location on earth at the same time of a day, thus the angle of sunlight should be approximately the same within a certain district and a period of season. PSA was determined by summing the frequencies of RGB values within the shadowed regions (refer to Figure 2). Similarly, the proportion of greenness area (PGA) was calculated using the same methodology.

In addition to residential areas, consideration was given to schools attended during grades 4 through 9. PSA within school was not assessed due to regulations stipulated by the Chinese government, which mandate that school buildings for the nine-year compulsory education program should not exceed five floors in height. The PGA within the official boundaries of each school, as delineated on the satellite map, was determined using the aforementioned methodology.

Statistics

The univariate correlation between the degree of myopia and each candidate factor was assessed using Spearman’s rho in SPSS 20.0 (SPSS Inc., Chicago, IL). A graphical representation illustrating the relationship between PSA and the odds ratio of myopia was generated using the open-source R program (version 4.3.1) and RStudio (version 2023.09.1+494). Identification of a cut-off point for PSA from the graph allowed for the stratification of the sample into two groups. Subsequently, a comparison of the degree of myopia, along with confounding factors, between these two groups was conducted using either the chi-square test or independent samples T-test in SPSS 20.0 (SPSS Inc., Chicago, IL). A significance level of P≤0.05 was employed to determine statistical significance.

Among the 150 students enrolled in the 10th-grade International Course Class at Xi’an Gao Xin No.1 High School, 120 students (73 females and 47 males, all of Asian descent) participated in the questionnaire. The mean age was 15.9 ± 0.6 (14–18) years. All students were residents of Xi’an city, except one who hails from Bao Ji city, which lies at approximately the same latitude as Xi’an.

Among the 120 students surveyed, the prevalence of myopia in at least one eye was 80.0%, with 8.3% exhibiting high myopia. Mild and moderate myopia accounted for 39.2% and 32.5% of the sample, respectively. Over 90% of students reported spending more than 6 hours per day engaged in near-work activities, while less than 20% reported rare use of electronic devices. Additionally, more than half of the students reported spending less than 3 hours engaged in outdoor activities per week. Orthokeratology lens usage for over one year was documented in 29.2% of the students.

Out of the 120 participants, 109 were successfully geolocated to their living addresses (from 93 distinct communities) on the satellite map. The mean PSA and PGA within a 500 square meter radius of the addresses were (20.24 ± 8.59)(2.7–43.6)% and (20.53 ± 8.78)(7.1–39.6)%, respectively. Furthermore, the 120 participants originated from 38 elementary schools (grades 4 to 6) and 29 middle schools (grades 7 to 9), with mean PGA values of (10.78 ± 7.16)(2.0-34.5)% and (12.26 ± 5.59)(3.8–35.0)%, respectively.

Correlations between the level of myopia and each factor are summarized in Table 2. Notably, residential PSA exhibited a negative correlation with the level of myopia, albeit with marginal significance (r=-0.189, P = 0.05). The restricted cubic spline analysis (Fig. 3) revealed a cut-off point of 20% for PSA in terms of the odds ratio for moderate and high myopia. Beyond this threshold, PSA appeared to confer a protective effect against myopia, and vice versa. Subsequently, the sample was stratified into two groups based on the PSA cut-off point (20%). A chi-square test demonstrated a significant difference in the level of myopia between the two groups (P = 0.012), while all other confounding factors exhibited no statistically significant differences (refer to Table 3). The scatter plot of the relationship between myopia level and residential PSA was shown in Fig. 4.

In this cross-sectional study, we aimed to investigate the relationship between varied urban living environments and the prevalence of myopia among adolescents. And PSA was developed to approximate the residential environment of a community. Surprisingly, our findings revealed a negative correlation between shadow proportion and myopia development, with shadow proportions below 20% posing a risk, while proportions beyond 20% potentially exhibiting a protective effect (illustrated in Fig. 3).

Through a comprehensive review of the satellite images, we observed that communities primarily comprised of high-rise apartments tended to have higher shadow area ratios. These areas typically featured larger inter-architectural distances compared to those dominated by multistory flats or houses in our study city. Examples showcasing high and low proportions of shadows are depicted in Fig. 5. We postulate that taller floors and greater inter-architectural spacing may contribute to reduced myopia progression. However, it's noteworthy that our analysis only considered community-wide environments. Future research should explore the effects of specific living floor levels on myopia development. In addition, there are studies linking violet and blue light to less progression of myopia (17, 18). It is also intriguing to explore the impact of color distribution within a living environment on the progress of myopia in future studies.

Prior research has suggested conflicting findings regarding the influence of living conditions on myopia. A large-scale survey in China suggested that lower living floors may be protective against myopia (19), and a recent study in South India indicated a higher prevalence of myopia among children living in apartments compared to other types of housing (20). However, these studies did not account for rural-urban or socioeconomic disparities, which may influence housing type differences and the development of myopia. Future investigations should adjust for these disparities or adopt a more uniform survey population to elucidate the physical impact of city constructions on myopia.

Our study sample is notably homogenous, comprising solely 10th-grade students with an average age of approximately 16 years. These students predominantly hail from middle-class or affluent families, as they are enrolled in the international course class of a private high school, aiming to pursue higher education abroad. Additionally, the vast majority of participants originate from Xi’an city, providing a microcosmic representation of China's urbanization trends over the past two decades. Consequently, participants share similar educational and socioeconomic backgrounds, which are known to influence myopic development (21, 22). By sampling within these environmental conditions, we were able to minimize possible confounding effects from factors such as education and study.

The prevalence of myopia and high myopia of the sample was 80% and 8.3% each, which is comparable to the large-sample studies in China (4, 23). Some factor such as near work, parental myopia and time outdoors were not significantly correlated with myopia in this study, probably due to the limited sample and small variations of the factors. We also calculated the green space within both the residentials and the schools using the green color coding from the histograms of satellite maps, which was not associated with myopia either. One disadvantage of this method is that the green space within the shadows could not be calculated. In previous studies suggesting a protective effect of green space (12, 13), the normalized difference vegetation index was used as an indicator, although it could also be affected by the shadows (24).

Still, there were several limitations of this study. Firstly, our study population is limited in scope and the limited scope may increase the likelihood of selection bias. However, the homogeneity of the sample may mitigate bias. Moreover, despite the small sample size, a significant difference in myopia levels was observed between higher and lower shadow area groups, with adjustments made for other confounding factors. Secondly, our study relies primarily on questionnaire data rather than performing rigorous measurements, which may introduce inaccuracies. One study have pointed out the tendency of questionnaire to overestimate the outdoor time while underestimate near-work time (25). To enhance reliability, a lecture was conducted by an optometrist prior to questionnaire distribution. Thirdly, our metric for evaluating building height and density may not be universally applicable, particularly in communities with significant geographical disparities, necessitating measurements within the same season. Fourthly, the green space could be underestimated due to the overlap of the shadows and the shadow area could also be miscalculated resulting from its projections on the neighbor structures which composed of only a very small fraction. And we consider them as the systematic errors in this study.

In summary, our findings demonstrate a negative correlation between myopia levels and shadow areas within living communities among a sample of 10th-grade students in a megacity. These results alleviate concerns that high-rise constructions accompanying urban modernization may adversely affect adolescent eye health. On the contrary, high-rise apartments may offer a solution for megacities by maximizing ground space while potentially exerting a protective effect against myopia progression.

Funding

This study was supported by the Key Research and Development program of Shaanxi Province (Grant Number 2024SF-YBXM-328), the Key Research and Development Program of Shaanxi, China (Grant Number 2023-YBSF-568), and the Integration Innovation Program of Xi’an Jiaotong University Health Science Center (Grant Number YXJLRH2022037).

Author Contribution

LC: conception and design of the study. N-yZ, Z-yL, J-yY, Y-cZ: data collection. H-zZ: illustrations, statistical analysis, and interpretation of data. ZL: administrative, technical, or material support. H-zZ and N-yZ: drafting of the manuscript. LC: critical revision of the manuscript. ZL and LC: study supervision. All authors read and approved the final manuscript.

Acknowledgments

Generative AI technology (ChatGPT 3.5, Open AI) was used for language editing only, with the prompt “Correct all the grammar mistakes in the following essay, improve the language and make it more academic.” All the references were searched and cited by the authors using PubMed. All the written contents produced by AI were checked to ensure they accurately reflected the data presented in the manuscript.

Data Availability

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. Please contact the corresponding author if needed.

Ethics statement

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Table 1. Myopia questionnaire in the international course center from Xi’an Gao Xin No. 1 high school.

Question	Answer (Answer on the horizontal line or Tick the corresponding option)
Gender	□Male □Female
Age(Y)
Elementary school
Middle school
The residential area that you most frequently dwelled in within the past six years.
Is the myopia present (in one or both eyes)? And what’s the equivalent spherical lens (ESL) of the worse eye? (ESL= sphere+0.5×cylinder)	□No myopia (ESL>-0.5D) □Mild myopia (ESL between -3.0D to -0.5D) □Moderate myopia (ESL between -6.0D to -3.0D) □High myopia (ESL≤-6.0D)
Since what age(Y) do you become myopic? (If no myopia，ignore it.)
Does the father or mother have high myopia (ESL≤-6.0D)?	□Yes □No
The average hours with near-work everyday in middle school. Suah as drawing, homework, reading, and handheld computer use.	□<6 □between 6 to 9 □between 9 to 12 □≥12
Among them, the proportion of electronic products used.	□<10% □between 10% to 30% □between 30% to 50% □≥50%
The average hours with outdoor activities every week. Suah as playing outdoors, family picnics, bicycle riding, and outdoor sport.	□<3 □between 3 to 5 □between 5 to 7 □≥7
Have you been using orthokeratology lens for more than 1 year？	□Yes □No

Table 2. Correlations between the level of myopia and each factor

Variables	n	r	P
Gender	120	-0.013	0.888
Age	120	-0.147	0.108
Parental myopia	120	0.08	0.387
Years with myopia	93	-0.085	0.418
Time with near-work	120	-0.123	0.181
Proportion of electronic products	120	0.162	0.077
Time outdoors	120	0.127	0.165
Orthokeratology lens use	120	0.175	0.056
PGA in elementary school	112	0.037	0.7
PGA in middle school	110	0.051	0.595
Residential PGA	112	0.054	0.575
Residential PSA	109	-0.189*	0.05

* Correlation is significant at the 0.05 level (2-tailed).

PGA, proportion of greenness area. PSA, proportion of shadow area.

Table 3. Comparison between two groups exploiting the cut point (20%) of PSA.

Variables	c²	t	P
Myopia	8.361		0.038
Gender	0.443		0.506
Age		-0.796	0.428
Parental myopia	0.443		0.506
Years with myopia		-0.566	0.573
Time with near-work	1.132		0.798
Proportion of electronic products	3.005		0.391
Time outdoors	3.511		0.327
Orthokeratology lens use	0.516		0.531
PGA in elementary school		-0.023	0.981
PGA in middle school		-0.192	0.848
Residential PGA		0.517	0.606

PGA, proportion of greenness area. PSA, proportion of shadow area.

No competing interests reported.

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You are reading this latest preprint version

A higher shadow ratio of the living environment on the remote sensing digital image is possibly protective for adolescent myopia

Status:

Version 1

Abstract

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Introduction

Materials and Methods

Results

Discussions

Declarations

Funding

Author Contribution

Acknowledgments

Data Availability

Ethics statement

References

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Status:

Version 1