Ethnic Disparities in Risk Factors for Myopia among Han and Minority Schoolchildren in Shawan, Xinjiang, China : Optometry and Vision Science

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Ethnic Disparities in Risk Factors for Myopia among Han and Minority Schoolchildren in Shawan, Xinjiang, China

Shi, Yumeng PhD, MD1,2,3; Ma, Dongmei PhD, MD1,2,3; Li, Xuemei MD4; He, Xiaolan MD5; Cui, Hanwen MD5; Li, Guoqing MD5; Wang, Jingjing MD5; Luo, Jianfeng PhD6,7,8∗; Yang, Jin PhD, MD1,2,3∗

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Optometry and Vision Science 100(1):p 82-90, January 2023. | DOI: 10.1097/OPX.0000000000001949
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Myopia has become a serious public health concern because of its remarkably increasing prevalence, especially in East Asia, and the ethnic differences in its prevalence have long been observed in previous studies. China is a multinational country, with a population comprising 56 distinct ethnic groups. According to the 2010 census, the Han majority constitutes approximately 91.51% of the total population, whereas the remaining 55 ethnic minority groups comprise a relatively small population.1 Occupying the northwestern corner of China, Xinjiang borders Mongolia, Russia, Kazakhstan, Kyrgyzstan, Tajikistan, Afghanistan, Pakistan, and India, making it a centralized multiethnic region. Xinjiang Minority Eye Studies (XMES) aim to establish a comprehensive comparison of children's individual eye development and describe geographical and ethnic variations in the distribution of myopia among schoolchildren in this region.

Considerable data from recent epidemiological research have established that myopia generally develops during early to middle childhood years.2 Consequently, myopia may start at the age of 5 to 6 years and progress to −5 to −6 D at the age of 11 to 13 years.3 Furthermore, the earlier the onset, the more myopic an individual could become, with all the increased risks, leading to the development of high myopia.3,4 Thus, major priorities lie in postponing myopia onset and retarding myopic progression among school-aged children, who were thus chosen as the participants of the present study.

In a previous report of XMES phase I,5 the prevalence of refractive errors and ocular dimensions were described individually for students aged 6 to 23 years (N = 67,102) in five areas of Xinjiang. The study indicated significant ethnic disparities in myopia and axial length, with Han and Hui presenting a higher prevalence of myopia, high myopia, longer axial lengths, and a larger axial length-to-corneal radius ratio compared with the Uyghur, Kyrgyz, and Kazakh minorities. However, data regarding meaningful lifestyle or educational differences among the five ethnic groups remain extremely scarce. Thus, the results of the observed ethnic differences in myopia through this large epidemiological survey need to be further verified. The present study, with a considerably designed questionnaire, explores the risk factors of myopia among multiethnic schoolchildren in Xinjiang, with the goal of identifying the intrinsic role that ethnicity plays in myopia and its related ocular biometry.


Study Population

The XMES are population-based studies conducted among different ethnic groups, including Han, Hui, and Uygur et al. (Uygur and other Altaic Language Families including Kazak, Saltar, and Tujia) in the Xinjiang Autonomous Region, using the same study protocols for data collection. The XMES were conducted from 2019 to July 2020. In a previous report, the detailed methodology of XMES and some major findings of ethnic refractive disparities in five major cities, that is, two southern cities, two northern cities, and one caption city, were presented. In the present study, one representative multiethnic school in the city of Shawan, Xinjiang, comprising grades 1 to 9 students, was chosen as the study region. This study was approved by the Chinese Teenager Eye Screening Institute Board and was conducted in accordance with the Declaration of Helsinki. The local administration of the Education and School Board of Xinjiang supported the study, and informed written consent was obtained from the parents or guardians of all the students.

Clinical Examinations

Ophthalmic examination, which consisted of measurement of uncorrected visual acuity, sphere, cylinder, and axis, was performed using one of two autorefractors (ARK-1, AR-1; NIDEK), and the average refractive error readings were recorded. Cycloplegia was induced with three drops of 1% cyclopentolate instilled 5 minutes apart, and pupillary dilation of at least 6 mm in the absence of a light reflex was considered complete cycloplegia. The spherical equivalent was defined as a sphere plus a half-cylinder. Myopia was defined as ≤−0.5 D spherical equivalent in either eye. Ocular biometric parameters, including axial length and corneal radius in the horizontal and vertical meridians, were measured using an AL-Scan Optical Biometer (AL-scan; NIDEK). Students' eye examination results and recommendations on strategies for myopia control are available online through a mobile phone application at for the convenience of checking and recording their own testing results.

Parents and their children were interviewed using an online questionnaire. The questionnaire included the following questions concerning the students: birth date, height, weight, sex, ethnicity, eye exercises, eye habits, time spent sleeping/using mobile phone or computer/watching TV/playing outdoor sports/doing homework/taking school and extracurricular remedial classes per day and per week, and children's birth history, including maternal age, children's birth season, pre-term birth or full-term birth, type of delivery, whether blue-light phototherapy was supplied after birth, and any history of cord around the neck. Meanwhile, the questions concerning parents include the following: educational level (primary education/junior school/high school or polytechnic/university), smoking or not, myopic status and age of myopia onset, household foods containing vitamin A or anthocyanin intake level, and ethnic background of both parents. Eye exercise, that is, periorbital self-massage around the acupoints of traditional Chinese medicine, has been promoted by the Chinese government since 1963 to prevent myopia in children. In our questionnaire, bad reading habits refer to reading while lying down or in vehicles, with eyes less than 20 cm away from the book, and other poor reading postures. The frequency of consuming foods containing anthocyanins (blueberries/mulberries/purple potatoes/purple cabbage/black wolfberries) and vitamin A (carrot/egg/milk/fish/cabbage/bean sprout/tofu/animal liver/lean meat/jujube/orange/mango) was categorized into the following: once a day (sometimes), once a week (occasionally), and in between (often). The standardized questionnaire was completed by both parents and children under the guidance of a trained research assistant.

Data Analysis

Statistical analysis was conducted using SAS 9.4 (SAS Institute, Cary, NC). Because the Spearman correlation coefficients for ocular parameters in the two eyes were high, only the data for the right eye were presented. Descriptive analyses were performed, and the results are presented as proportions (in percent) or mean ± standard deviation. The confidence interval (CI) for each effect variable was expressed as the 95% CI. Comparisons of lifestyle differences and refractive errors between the three ethnic groups were performed using the χ2 test and one-way analysis of variance based on the types of variables. Univariate and multivariate logistic regression analyses were performed to investigate the association between myopia and the demographic and environmental variables. A P value of .05 or less was considered statistically significant.


Overall, 876 students (97.9% response) from grades 1 to 9 of the Anjihai Multi-Ethnic School in Shawan, Xinjiang, participated in this study. The mean age of the participants was 11.3 years, of whom 51.9% are boys. Among the participants, most were Han (37.8%) and Hui (44.7%), followed by Uygur et al. (Uygur, Kazak, Saltar, and Tujia), accounting for 17.5% of the total.

Participants Characteristics

Table 1 compares the demographic, systematic, household, and birth history parameters of the three ethnic groups. No significant differences were found in age, sex, height, weight, eye exercises, eye habits, birth season, and average mobile phone or TV usage time between the groups. Children from the Hui and Uygur et al. consumed more vitamin A food (P < .01), spent more time sleeping (P = .02), engaged in weekend outdoor sports (P = .02), and spent less time doing homework (P = .04) than the Han nationality. Hui's maternal age (P < .01) and the proportion of premature babies (P = .02) were relatively low. The proportion of history of blue-light phototherapy (P < .01) or umbilical cord around the neck (P = .04) of Han students was higher than that of Hui and Uygur et al. In addition, the Han group was most likely to choose cesarean delivery (P < .01). With respect to parents, the proportion of parents of Hui and Uygur et al. students who smoked (P < .01) and had received education higher than middle and high school (P < .01) was lower than that of Han parents (Table 1).

TABLE 1 - Demographic and environmental variables by ethnicity in the Xinjiang Minority Eye Study
Han (n = 331) Hui (n = 392) Uygur/Kazak/Saltar/Tujia (n = 153) P
Age, mean ± SD (y) 11.31 ± 2.57 10.83 ± 2.51 11.42 ± 2.69 .01
Sex, n (%)
 M 174 (52.6) 207 (52.8) 74 (48.4) .62
 F 157 (47.4) 185 (47.2) 79 (51.6)
Height, median (cm) 155.00 150.00 153.00 .10
Weight, median (kg) 47.00 41.50 45.00 .49
Eye exercises, n (%)
 Seriously 289 (87.3) 351 (89.5) 142 (92.8) .19
 Not seriously 33 (10.0) 38 (9.7) 7 (4.6)
 Not arranged 9 (2.7) 3 (0.8) 4 (2.6)
Bad reading habits, n (%)
 Yes 123 (37.2) 138 (35.2) 43 (28.1) .15
Spectacle wear, n (%)
 Yes 60 (18.1) 60 (15.3) 18 (11.8) .07
School, mean ± SD (h/d) 6.85 ± 1.95 6.60 ± 1.95 6.86 ± 2.09 .19
Homework, mean ± SD (h/d) 2.28 ± 1.60 2.05 ± 1.60 1.94 ± 1.27 .04
Mobile phone usage time per day, n (%)
 <0.5 h 216 (65.3%) 282 (71.9%) 96 (62.7%) .94
 1–2 h 99 (29.9%) 96 (24.5%) 50 (32.7%)
 ≥3 h 16 (4.8%) 14 (3.6%) 7 (4.6%)
TV watching time per day, n (%)
 <0.5 h 222 (67.1%) 260 (66.3%) 98 (64.1%) .61
 1–2 h 104 (31.4%) 123 (31.4%) 51 (33.3%)
 ≥3 h 5 (1.5%) 9 (2.3%) 4 (2.6%)
Weekday outdoor time, mean ± SD (h/d) 2.03 ± 1.30 2.24 ± 1.28 2.23 ± 1.25 .07
Weekend outdoor time, mean ± SD (h/d) 3.28 ± 1.92 3.63 ± 1.96 3.73 ± 2.05 .02
Sleep time, mean ± SD (h/d) 8.62 ± 1.13 8.84 ± 1.19 8.88 ± 1.11 .02
Spectacle wear (parents), n (%)
 None 283 (85.5) 348 (88.8) 134 (87.6) .48
 Mother 25 (7.6) 22 (5.6) 8 (5.2)
 Father 16 (4.8) 20 (5.1) 9 (5.9)
 Both 7 (2.1) 2 (0.5) 2 (1.3)
Education (parents), n (%)
 None 6 (1.8) 18 (4.6) 3 (2.0) <.001
 Elementary school 35 (10.6) 143 (36.5) 30 (19.6)
 Junior high 217 (65.6) 193 (49.2) 99 (64.7)
 Senior high or polytechnic 69 (20.8) 36 (9.2) 19 (12.4)
 College or more 4 (1.2) 2 (0.5) 2 (1.3)
Smoke (parents), n (%)
 Yes 146 (44.1) 71 (18.1) 45 (29.4) <.001
Premature birth, n (%)
 Yes 21 (6.3) 9 (2.3) 9 (5.9) .02
Maternal age, mean ± SD (y) 28.35 ± 6.62 26.76 ± 6.04 28.00 ± 5.72 <.01
Birth season, n (%)
 Spring 90 (27.2) 91 (23.2) 31 (20.3) .21
 Summer 70 (21.1) 79 (20.2) 39 (25.5)
 Autumn 62 (18.7) 101 (25.8) 38 (24.8)
 Winter 109 (32.9) 121 (30.9) 45 (29.4)
Vaginal or cesarean delivery, n (%)
 Vaginal 204 (61.6) 315 (80.4) 107 (69.9) <.001
Blue-light phototherapy, n (%)
 Yes 36 (10.9) 23 (5.9) 5 (3.3) <.01
Cord around neck, n (%)
 Yes 41 (12.4) 36 (9.2) 8 (5.2) .04
Anthocyanin intake, n (%)
 Sometimes 72 (21.8) 76 (19.4) 41 (26.8) .22
 Occasionally 242 (73.1) 298 (76.0) 101 (66.0)
 Often 17 (5.1) 18 (4.6) 11 (7.2)
Vitamin A intake, n (%)
 Sometimes 95 (28.7) 118 (30.1) 39 (25.5) <.01
 Occasionally 29 (8.8) 70 (17.9) 21 (13.7)
 Often 207 (62.5) 204 (52.0) 93 (60.8)
Data presented are means (SDs) or n (%), as appropriate for variable. P value, comparing the differences between the two ethnic groups, based on χ2 test or t test, as appropriate. SD = standard deviation.

Refractive Error and Biometric Parameters

Measures of refractive error and ocular dimensions, including uncorrected visual acuity, sphere, cylinder, axis, axial length, corneal radius, and axial length-to-corneal radius ratio, are summarized and compared between the groups (Table 2). Overall, the prevalence rates of myopia in Han, Hui, and Uygur et al. were 50.5, 41.3, and 32.0%, respectively (all P < .001). The mean refractive errors were −0.90 ± 1.49 D in ethnic Han, −0.71 ± 1.51 D in ethnic Hui, and −0.33 ± 0.83 D in the Uygur et al. minorities (P < .001). The three groups presented similar levels of negative astigmatism (all: mean, −0.5 D; P = .37). The axial length of Han students was the longest (mean, 23.67 ± 1.54 mm), followed by Hui (mean, 23.44 ± 1.55 mm) and Uygur et al. (mean, 23.25 ± 1.36 mm; P = .01). The Han (mean, 7.86 ± 0.26 mm) and Hui (mean, 7.84 ± 0.28 mm) students had 0.02 mm steeper corneal radius and 0.02 mm thicker corneas than the Uygur et al. (mean, 7.86 ± 0.25 mm), with a less marked variation (P = .47). However, significant variability was observed among the ethnic groups in the axial length-to-corneal radius ratio (P = .03).

TABLE 2 - Refractive parameters and myopia prevalence by ethnicity in the Xinjiang Minority Eye Study
Han (n = 331) Hui (n = 392) Uygur/Kazak/Saltar/Tujia (n = 153) P
Sphere (D) −0.54 ± 1.46 −0.37 ± 1.47 −0.01 ± 0.88 <.001
Cylinder (D) −0.73 ± 0.66 −0.67 ± 0.64 −0.64 ± 0.72 .37
SE (D) −0.90 ± 1.49 −0.71 ± 1.51 −0.33 ± 0.83 <.001
Myopia, n (%)
 Yes 167 (50.5) 162 (41.3) 49 (32.0) <.001
 No 164 (49.5) 230 (58.7) 104 (68.0)
AL (mm) 23.67 ± 1.54 23.44 ± 1.55 23.25 ± 1.36 .01
CR (mm) 7.86 ± 0.26 7.84 ± 0.28 7.86 ± 0.25 .47
AL/CR 3.01 ± 0.19 2.99 ± 0.19 2.96 ± 0.16 .03
Data presented are means (standard deviations) or n (%), as appropriate for variable. P value, comparing the differences between the two ethnic groups, based on χ2 test or t test, as appropriate. AL = axial length; AL/CR = axial length-to-corneal radius ratio; CR = corneal radius; SE = spherical equivalent.

Risk Factor Assessment

The univariate regression analysis of the factors associated with myopia is shown in Table 3. Han ethnicity, older age, performing eye exercises without good quality, poor reading habits, longer school time per day, longer duration of time spent on mobile phones per day, myopic mothers, household smokers, longer sleep duration, born in winter, and lower anthocyanin intake were all significantly associated with myopia (all P < .05; Table 3).

TABLE 3 - Associations of potential contributing factors and myopia evaluated by univariate logistic regression analysis
Model Effect OR (95% CI) P
Ethnicity Han: Hui 0.69 (0.52–0.93) .01
Han: Uygur/Kazak/Saltar/Tujia 0.46 (0.31–0.69) <.001
Age Age 1.35 (1.27–1.43) <.001
Eye exercises Not seriously: seriously 2.54 (1.56–4.12) <.001
Not seriously: not arranged 0.65 (0.22–1.88) .42
Bad reading habits Bad reading habits 1.66 (1.26–2.20) <.001
School School 1.13 (1.05–1.21) <.001
Homework Homework 1.01 (0.92–1.10) .91
Phone usage time <0.5 h: 1–2 h 2.09 (1.54–2.82) <.001
<0.5 h: ≥3 h 2.79 (1.41–5.54) <.01
TV watching time <0.5 h: 1–2 h 0.91 (0.68–1.22) .53
<0.5 h: ≥3 h 1.62 (0.63–4.15) .32
Weekday outdoor time Weekday outdoor time 0.97 (0.88–1.08) .58
Weekend outdoor time Weekend outdoor time 0.98 (0.91–1.05) .49
Sleep time Sleep time 0.83 (0.73–0.93) <.01
Spectacle wear (parents) None: mother 2.17 (1.24–3.79) .01
None: father 1.81 (0.99–3.31) .06
None: both 2.53 (0.73–8.71) .14
Education (parents) None: elementary school 1.03 (0.46–2.31) .94
None: junior high 0.85 (0.39–1.85) .68
None: senior high or polytechnic 1.25 (0.54–2.89) .60
None: college or more 1.25 (0.26–6.07) .78
Smoke (parents) Smoke (parents) 1.49 (1.11–1.99) <.01
Premature birth Premature birth 1.75 (0.92–3.34) .09
Maternal age Maternal age 1.01 (0.99–1.03) .35
Birth season Winter: spring 0.96 (0.67–1.37) .82
Winter: summer 0.65 (0.44–0.95) .02
Winter: autumn 0.75 (0.52–1.09) .13
Vaginal or cesarean delivery Vaginal: cesarean 0.76 (0.56–1.03) .07
Blue-light phototherapy Blue-light phototherapy 0.96 (0.57–1.60) .87
Cord around neck Cord around neck 1.55 (0.99–2.42) .06
Anthocyanin intake Sometimes: occasionally 1.07 (0.77–1.49) .67
Sometimes: often 0.42 (0.20–0.88) .02
Vitamin A intake Sometimes: occasionally 0.91 (0.58–1.41) .66
Sometimes: often 1.02 (0.75–1.38) .92
CI = confidence interval; OR = odds ratio.

Risk factors for myopia were also analyzed using various multivariate logistic regression models, as shown in Table 4. The variation in myopia prevalence between Han and Uygur et al. minorities in all models (models 1 to 7) remained significant, whereas it changed to not significant between Han and Hui ethnicities. Models 2 to 7 were further controlled for environmental risk factors. Notably, the prevalence variation was largely attenuated once the family-related factors were controlled in model 6 (P = .22 in Han vs. Hui; P = .02 in Han vs. Uygur et al.). Moreover, the percentage reduction in excess prevalence was estimated by adjusting for the potential contributing factors. Additional adjustment for environmental influences, such as time spent on near work, outdoor activities, and sleeping, or birth-related factors did not result in a marked reduction in the odds of myopia. Conversely, adjustment for parental factors reduced the excess prevalence of myopia by 17.4% in Hui and 14.5% in Uygur et al. (Table 4). Han ethnicity, higher grades, performing eye exercises without high quality, and myopic mothers were associated with increased odds of being myopic after adjusting for all covariates (all P < .05; data not presented). Kaplan-Meier survival analysis was used to compare myopia-free rates among Han, Hui, and Uygur et al. (Fig. 1). Myopia in Han and Hui ethnicities showed a faster progression than that reported by Uygur et al. In addition, interaction was assessed between ethnic groups (Han vs. Uygur et al.) and representative variables using logistic regression models; significant interaction was found only in birth seasons (P = .049; Fig. 2).

TABLE 4 - Factors associated with myopia identified by multilevel multivariate logistic regression models in Han ethnicity compared with minorities
Model Effect aOR (95% CI) P % Reduction excess prevalence
M1 Hui 0.77 (0.56–1.06) .11 Reference
Uygur/Kazak/Saltar/Tujia 0.38 (0.24–0.58) <.001 Reference
M2 Hui 0.76 (0.55–1.06) .11 4.35
Uygur/Kazak/Saltar/Tujia 0.39 (0.25–0.61) <.001 −1.61
M3 Hui 0.76 (0.55–1.04) 0.09 4.35
Uygur/Kazak/Saltar/Tujia 0.38 (0.25–0.59) <.001 0
M4 Hui 0.78 (0.57–1.08) .13 −4.35
Uygur/Kazak/Saltar/Tujia 0.37 (0.23–0.57) <.001 1.61
M5 Hui 0.77 (0.56–1.06) .11 0
Uygur/Kazak/Saltar/Tujia 0.38 (0.24–0.59) <.001 0
M6 Hui 0.73 (0.43–1.21) .22 17.39
Uygur/Kazak/Saltar/Tujia 0.29 (0.11–0.78) .02 14.52
M7 Hui 0.78 (0.57–1.08) .13 −4.35
Uygur/Kazak/Saltar/Tujia 0.39 (0.25–0.60) <.001 −1.61
Percentage reduction in excess prevalence is defined by the formula: (Ra − Rb)/(1 − Ra), where Ra is the OR of myopia in Han ethnicity versus the Hui or other ethnicity groups adjusted for age, sex, height, and weight only (model 1, reference), and Rb is the OR after additional adjustment for the variables in models 2 to 7. Model 1 is a baseline model with demographic factors (age, sex, height, and weight) adjusted. Model 2 is adjusted for demographic factors and birth factors (premature birth, maternal age, birth season, vaginal or cesarean delivery, blue-light phototherapy, cord around neck). Model 3 is adjusted for demographic factors and diet factors (Anthocyanin and Vitamin A intake). Model 4 is adjusted for demographic factors and near work (bad reading habits, eye exercises, school, homework, phone usage time, TV watching time). Model 5 is adjusted for demographic factors and outdoor activities (weekday outdoor time, weekend outdoor time). Model 6 is adjusted for demographic factors and family factors (spectacle wear [parents], education [parents], smoke [parents]). Model 7 is adjusted for demographic factors and sleep time. aOR = adjusted odds ratio; CI = confidence interval; M1-7 = models 1 to 7.

Survival plot of myopia-free rates of three ethnicity groups.
Interaction between ethnicity (Han, Uygur/Kazak/Saltar/Tujia) and variables in logistic regression analysis.


This multiethnic study, based on a questionnaire survey and clinical examination among students from grades 1 to 9 of the same school in Shawan, Xinjiang Autonomous Region, provided novel data for a comprehensive comparison of ethnic variations in myopia prevalence, biometry dimensions, meaningful lifestyle, and personal and family variables in Northwest China.

One of the most important findings in this study is that Han children had the longest axial lengths and most myopic average spherical equivalent (same patterns observed in the prevalence of myopia). This finding is consistent with the results of our previous large-scale population-based study in accordance with the National Juvenile Myopia Screening Program from 2019 to 2020.5 The important risk factors of myopia include a history of parental myopia, time spent performing outdoor activities, and near work.6,7 Height was also associated with axial length.8 However, these important covariables were not captured and included in the multivariate models in our previous study, thus failing to identify the factors that could explain ethnic differences in myopia. Consequently, based on the preliminary results, the present study aimed to describe and compare the lifestyle and educational differences between ethnic groups residing in Xinjiang to examine factors accounting for these ethnic variations and explore feasible methods to prevent juvenile myopia.

With myopia identified as a major public health issue worldwide, several studies have reported myopia rates of greater than 50% among school students, especially in the Southeast Asia region.9 Up to 90% of Chinese teenagers and young adults have been reported to be shortsighted.10 However, because of the paucity of prevalence data and screening practices at schools in Western China, a broad public misconception about myopia and myopia prevention, including a lack of parental and teacher awareness and even resistance to wearing spectacles, continues to exist, particularly among ethnic minorities. In the present study, spectacle use was reported in 35.9, 37.0, and 36.7% of myopic students of Han, Hui, and Uygur et al. minorities, respectively, which were considerably lower than those of students residing in urban cities in eastern and southern China.11,12 Through screening program, public awareness and understanding of myopia prevention and control could be raised with the government and nongovernment cooperation.

Although the participants of this study were from the same school in Xinjiang, large variations in lifestyle, including dietary and reading habits, parental education level, maternal age, and even the chosen birthing method (vaginal or cesarean delivery), have been commonly observed among different ethnic groups. For instance, maternal age and proportion of premature births in Hui were the lowest in this study. Moreover, ethnicities originating from Altaic and Eurasia were more prone to a normative life, that is, devoting more time to outdoor activities and less time to homework than the Han majority, and their sleep duration was longer than that of Han students. Regarding the parents, low education level and nonsmoking status were more common in the non-Han groups. As for dairy and vegetable consumption, the non-Han groups consumed more vitamin A containing foods, such as carrots, eggs, milk, fish, and Chinese cabbage.

Among the numerous influences pertaining to myopia, the three most common are genes, extended periods of near work, and limited outdoor activities,6,13 some of which were also identified by logistic regression analysis in the present study. School hours, average time spent on cell phones per day, and bad reading habits, including lying down, abnormal reading distance, and other improper reading postures (all P < .001), were environmental factors linked with an increased prevalence of myopia in the univariate logistic models. These can be attributed to spending more time on fixation with fewer breaks at a closer distance, thereby eventually causing the elongation of the eyeball. Time spent on television per day was not associated with the occurrence of myopia, which is consistent with the results reported by Kinge et al.14 and Czepita et al.,15 both indicating that watching television exerts nearly negligible influence on myopia progression.

Regarding protective factors, this study showed that performing eye exercises seriously led to a lower risk of myopia development (odds ratio [OR], 2.54; 95% CI, 1.56 to 4.12; P < .001). A 3-year cohort study in Beijing found that children performing eye exercises more frequently daily had significantly less myopic progression16; however, a case-control study with a 2-year follow-up suggested no association between eye exercises and the risk of myopia onset (OR, 0.73; 95% CI, 0.24 to 2.21) or myopia development (OR, 0.79; 95% CI, 0.41 to 1.53). The students who performed high-quality exercises presented only a slightly lower myopia progression of 0.15 D than those who did not perform eye exercises over a period of 2 years.17 Differences in methodology, including follow-up periods and lack of a control group and measurement of ocular blood flow, made comparisons across findings more difficult and evidence less convincing. Although these exercises, featuring massage on traditional Chinese medicine acupoints, have been widely performed on a national scale for decades, the possible mechanisms for relieving ocular fatigue and retarding myopia remain poorly understood.

An association between longer sleep duration and reduced risk of myopia was also found (OR, 0.83; 95% CI, 0.73 to 0.93; P < .001). Such inverse relationship was observed among Korean adolescents in 2016, with a dose-response pattern.18 In particular, the adjusted OR for myopia was decreased in those with more than 9 hours of sleep compared with those with less than 5 hours of sleep (OR, 0.59; 95% CI, 0.38 to 0.93), whereas the adjusted OR for refractive error was increased per 1 hour in sleep duration (OR, 0.9; 95% CI, 0.83 to 0.97).18

Anthocyanin intake may also affect myopia occurrence. This study found a reduction in the odds of myopia in children who consumed anthocyanins more often (OR, 0.42; P = .02). Blueberry, Lycium ruthenicum, red cabbage, mulberry, purple sweet potato, black soybean, and blackcurrant contain various anthocyanins19 that are abundant in Xinjiang. The inhibitory effects of anthocyanins on myopia, mainly due to the relaxation of the ciliary smooth muscle, have been reported in several previous studies. Its mitigative effects on eye fatigue are supported by not only molecular-based evidence from animal experiments, with a concentration of 10−8 to 10−7 M,20 but also by human crossover designed trials with additional anthocyanin intake.21

Recent research has increasingly examined the season of birth in relation to the risk of myopia. In the present study, being born in summer was associated with decreased odds of myopia compared with being born in winter (P = .02; OR, 0.65). In contrast, a retrospective study in the United Kingdom in 2009 indicated that individuals born in summer or autumn were more likely to be highly myopic than those born in winter.22 Seasonal variation in myopia risk was not observed in a recent case-control study focusing on neonatal 25-hyrdroxyvitamin D3 levels.23 Given that interstudy comparisons are difficult, many potential confounders, including parental education and uneven distribution of birth season, must be considered when accounting for the results.

Intriguingly, an unusual inverse relationship between juvenile myopia and parental smoking was observed, similar to the results of another multiethnic study using the U.S. National Health and Nutrition Examination Survey with 6571 participants, suggesting that increased exposure to tobacco smoke seems to have a protective effect against the development of myopia (OR, 0.79).24 The STrabismus, Amblyopia, and Refractive errors in Singaporean children (STARS) study25 also associated maternal history of smoking, smoking during a child's life, and smoking during pregnancy with a reduced risk of myopia occurrence (OR, 0.05, 0.39, and 0.30, respectively). Nevertheless, no correlation between household smoking and myopia has been observed in some research.26

Comparison of myopia prevalence among the three ethnic groups, with the adjustment of demographic and environmental variables in different multivariate logistic models, showed that prevalence disparity became unremarkable between Han and Hui ethnicities but remained significant between Han and Uygur et al. This finding indicated that the ethnic variability in myopia prevalence between Han and Hui could be largely explained by environmental factors rather than ethnicity itself, whereas the intrinsic role that ethnicity plays in the variability between Han and Uygur et al. may be more vital. These diametrically opposed results suggest that the enabling factors of myopia vary by race or ethnicity. Therefore, we speculate that compared with Uygur, Kazak, Saltar, and Tujia (Altaic language family ethnicity), the Han and Hui people (Sino-Tibetan language family ethnicity) may have a genetic predisposition to myopia, but no evidence to date could support this. Conversely, the discrepancies in cultural backgrounds may explain the ethnic disparities observed between the Han and Hui students because traditional Han culture highlights early academic achievements and passing examinations, which is also consistent with the findings of our questionnaire survey. We believe that large-scale prevalence investigations among adults of different ethnicities in Xinjiang are required to draw more distinct conclusions.

The strengths of our study include the homogeneity of the participants, high response rate, and the use of standardized questionnaires that sought multiple perspectives for risk factor assessment. Limitations include the cross-sectional nature of the study, which makes it infeasible to infer the temporal relationship between the factors under study. In addition, the participants with relatively modest sample sizes were from a single institution; thus, a selection bias may have occurred. In conclusion, large variations in myopia prevalence, biometric parameters, lifestyle, and household factors linked to myopia were observed among the different ethnic groups in Shawan, Xinjiang. Certain features of indoor and outdoor behavior, birth status, and familial tendency that account for such variance are important for the development and/or progression of myopia. More evidence, particularly from random clinical trials and cohort studies, is warranted in the future to further understand the potential environmental risk factors driving myopia development.


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