June 2023
Volume 64, Issue 7
Open Access
Glaucoma  |   June 2023
Racial and Ethnic Differences in the Roles of Myopia and Ocular Biometrics as Risk Factors for Primary Open-Angle Glaucoma
Author Affiliations & Notes
  • Sarah Zhou
    Keck School of Medicine at the University of Southern California, Los Angeles, California, United States
  • Bruce Burkemper
    Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine at the University of Southern California, Los Angeles, California, United States
  • Anmol A. Pardeshi
    Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine at the University of Southern California, Los Angeles, California, United States
  • Galo Apolo
    Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine at the University of Southern California, Los Angeles, California, United States
  • Grace Richter
    Southern California Permanente Medical Group, Los Angeles, California, United States
  • Xuejuan Jiang
    Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine at the University of Southern California, Los Angeles, California, United States
    Department of Population and Public Health Sciences, Keck School of Medicine at the University of Southern California, Los Angeles, California, United States
  • Mina Torres
    Southern California Eye Institute, CHA Hollywood Presbyterian Medical Center, Los Angeles, California, United States
  • Roberta McKean-Cowdin
    Keck School of Medicine at the University of Southern California, Los Angeles, California, United States
    Department of Population and Public Health Sciences, Keck School of Medicine at the University of Southern California, Los Angeles, California, United States
  • Rohit Varma
    Southern California Eye Institute, CHA Hollywood Presbyterian Medical Center, Los Angeles, California, United States
  • Benjamin Y. Xu
    Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine at the University of Southern California, Los Angeles, California, United States
  • Correspondence: Benjamin Xu, Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine at the University of Southern California, 1450 San Pablo Street, 4th Floor, Suite 4700, Los Angeles, CA 90033, USA; benjamin.xu@med.usc.edu
Investigative Ophthalmology & Visual Science June 2023, Vol.64, 4. doi:https://doi.org/10.1167/iovs.64.7.4
  • Views
  • PDF
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Sarah Zhou, Bruce Burkemper, Anmol A. Pardeshi, Galo Apolo, Grace Richter, Xuejuan Jiang, Mina Torres, Roberta McKean-Cowdin, Rohit Varma, Benjamin Y. Xu; Racial and Ethnic Differences in the Roles of Myopia and Ocular Biometrics as Risk Factors for Primary Open-Angle Glaucoma. Invest. Ophthalmol. Vis. Sci. 2023;64(7):4. https://doi.org/10.1167/iovs.64.7.4.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose: Assess how the roles of refractive error (RE) and ocular biometrics as risk factors for primary open-angle glaucoma (POAG) differ by race and ethnicity.

Methods: Data from the Los Angeles Latino Eye Study (LALES) and the Chinese American Eye Study (CHES), two population-based epidemiological studies, were retrospectively analyzed. Multivariable logistic regression and interaction term analyses were performed to assess relationships between POAG and its risk factors, including RE and axial length (AL), and to assess effect modification by race/ethnicity.

Results: Analysis included 7601 phakic participants of LALES (47.3%) and CHES (52.7%) with age ≥ 50 years. Mean age was 60.6 ± 8.3 years; 60.9% were female. The prevalence and unadjusted risk of POAG were higher in LALES than CHES (6.0% and 4.0%, respectively; odds ratio [OR] = 1.55; P < 0.001). In the multivariable analysis, significant risk factors for POAG included Latino ethnicity (OR = 2.25; P < 0.001), refractive myopia (OR = 1.54 for mild, OR = 2.47 for moderate, OR = 3.94 for high compared to non-myopes; P ≤ 0.003), and longer AL (OR = 1.37 per mm; P < 0.001). AL (standardized regression coefficient [SRC] = 0.3) was 2.7-fold more strongly associated with POAG than high myopia status (SRC = 0.11). There was no modifying effect by race/ethnicity on the association between RE (per diopter) or AL (per millimeter) and POAG (P = 0.49).

Conclusions: Although the POAG risk conferred by myopic RE and longer AL is similar between Latino and Chinese Americans, the difference in POAG prevalence between the two groups is narrowed by higher myopia prevalence among Chinese Americans. Racial/ethnic populations with higher myopia incidence may become disproportionately affected by POAG in the context of the global myopia epidemic.

Primary open-angle glaucoma (POAG) is a leading cause of irreversible vision loss worldwide.1 POAG has a number of well-established risk factors, including older age, higher intraocular pressure (IOP), positive family history of glaucoma, African ancestry and Latino ethnicity, myopic refractive error (RE), longer axial length (AL), and thinner cornea.113 Recent projections estimate that the global prevalence of POAG will increase from 44 million in 2013 to nearly 80 million by 2040, largely due to aging of the world's population.1 However, these projected changes in POAG prevalence do not consider the effects of other global trends, including the concurrent rise in myopia prevalence. Myopia, especially moderate to high myopia above 3 diopters (D), is a strong risk factor for POAG, increasing the odds of POAG by 1.8 to 3.3 times compared to emmetropia.7,8,12,14,15 Therefore, there is a need to better understand the contributions of myopia and ocular biometrics to POAG risk and how effects of these risk factors differ by race and ethnicity.5 
The ongoing myopia epidemic is well publicized; myopia prevalence is estimated to double from 22.9% to 49.8% of the global population between 2000 and 2050.15,16 Significant increases in refractive and axial myopia prevalence have been reported in the United States, East Asia, and Europe.1719 Although research elucidating factors underlying this rapid rise in myopia is ongoing, findings from human and animal studies support the role of axial elongation as a primary anatomical mechanism.20 For example, longitudinal studies in Asian youth demonstrated that faster myopic progression is associated with greater increases in AL, particularly in vitreous chamber depth (VCD), and exposure to risk factors associated with myopia, such as decreased time outdoors, is associated with greater axial elongation and myopic progression.21,22 
The prevalence of POAG varies by race, but there is limited knowledge about racial and ethnic differences in the roles of specific risk factors, including RE and ocular biometrics.13,23 In this study, we compared the roles of myopia and AL as risk factors for POAG in Latino and Asian Americans using combined data from the Los Angeles Latino Eye Study (LALES) and the Chinese American Eye Study (CHES), two population-based epidemiological studies on eye disease among the two fastest growing minority populations in the United States.24 Although previous epidemiological studies suggest that Latinos have a higher POAG risk compared to Asians, an explanation for this difference remains elusive.2527 As patient populations become increasingly diverse and myopia prevalence rises around the world, physiological differences between racial and ethnic populations will be important to consider when risk-stratifying patients for POAG and forecasting changes in POAG prevalence. 
Methods
Ethics committee approval was previously obtained from the University of Southern California Medical Center Institutional Review Board. All study procedures adhered to the tenets of the Declaration of Helsinki. All study participants provided informed consent at the time of enrollment. 
Clinical Assessment
Eligible study participants were identified from LALES and CHES.28,29 The LALES was a population-based, cross-sectional study of 6357 Latino participants of primarily Mexican descent age 40 years and older living in La Puente, California. The CHES was a population-based, cross-sectional study of 4582 Chinese participants age 50 years and older living in Monterey Park, California.28,29 Complete ophthalmic examinations in both studies were performed using similar equipment, including automated refraction (Humphrey Autorefractor; Carl Zeiss Meditec, Dublin, CA, USA) if uncorrected visual acuity was less than 20/20 in either eye; ultrasound A-scan biometry (DGH 4000B A-Scan; DGH Technology, Exton, PA, USA); three IOP measurements by Goldman applanation tonometry; visual field (VF) testing with standard automated perimetry (Humphrey Field Analyzer in LALES and Humphrey Field Analyzer II 750 in CHES; Carl Zeiss Meditec); fundus photography (TRC 50EX in LALES and TRC Digital 50DX in CHES; Topcon, Paramus, NJ, USA); and stereoscopic disc photography (Nidek 3Dx; Nidek, Fremont, CA, USA). Participants with a history of lens extraction were excluded due to the effects of surgery on RE and ocular biometry. Participants with inconclusive glaucoma grading or primary angle-closure glaucoma (PACG) were also excluded. 
Glaucoma Definitions and Grading
In both studies, glaucomatous optic neuropathy (GON) was defined as (1) characteristic or compatible glaucomatous visual field abnormality and/or evidence of characteristic or compatible glaucomatous optic disc damage in at least one eye after ophthalmologic exclusion of other possible causes; and (2) end-stage disease with VA of ≤20/200 and a cup-to-disc ratio of 1.0.28,29 POAG was defined as GON in the absence of angle closure, defined as three or more quadrants of non-visible trabecular meshwork on gonioscopy. Gonioscopy was performed by trained ophthalmologists masked to other exam findings using a Posner-type four-mirror lens (ODPSG; Ocular Instruments, Bellevue, WA, USA) under dark ambient lighting (0.1 cd/m2). In LALES, only participants with narrow angles on slit-lamp examination received gonioscopy; in CHES, all participants received gonioscopy. Definitions of GON did not include IOP. 
Glaucoma grading in both studies was performed by three glaucoma specialists. Two glaucoma specialists independently reviewed demographic and clinical data, including optic disc photographs and VFs, to make the diagnosis of glaucoma. If the two specialists agreed, the diagnosis was assigned. If there was disagreement between the specialists, a third glaucoma specialist adjudicated the diagnosis using the same demographic and clinical data; the diagnosis was assigned based on agreement between two of the three specialists. 
Statistical Analysis
Phakic right eyes were selected for analysis. If the right eye was pseudophakic or aphakic, the phakic left eye was used. RE was categorized as no myopia (>−0.5 D), mild myopia (≤−0.5 to >−3 D), moderate myopia (≤−3 to >−6 D) and high myopia (≤−6 D).20,30 Log odds plots were generated to assess linearity of data. Univariable and multivariable logistic regression models were developed to assess the relationship between risk of POAG and: RE (Model A); AL (Model B); both RE and AL (Model C); AL components (Model D), comprised of central corneal thickness (CCT), anterior chamber depth (ACD), lens thickness (LT), and VCD (calculated as AL – CCT – ACD – LT); and RE and VCD (Model E). Variables with P < 0.15 on univariable analysis were included in the multivariable analysis. Models C, D, and E were included to assess relative contributions of RE, AL, and AL components to POAG risk based on direct comparison of standardized regression coefficients (SRCs). Kendall's τ < 0.7, correlation coefficients of < |0.7|, variable inflation factor (VIF) < 3, and squared generalized VIF (GVIF2) < 3 were confirmed prior to inclusion of RE and AL or VCD in the same multivariable model (Models C and E) to rule out strong multicollinearity. Three additional multivariable models were developed to assess interactions between race/ethnicity and RE, AL, or IOP. All models were adjusted for sex, age, race/ethnicity, self-reported family history of glaucoma, and IOP. Locally weighted scatterplot smoothing (LOWESS) curves were plotted to visualize the predicted relationship between AL or VCD and probability of POAG. Points with sample size < 30 participants were omitted from the LOWESS plots to avoid reporting unreliable probability estimates. All statistical analyses were performed using R (R Foundation for Statistical Computing, Vienna, Austria) using a significance level of 0.05. 
Results
In total, 10,927 participants were recruited across LALES and CHES. In LALES, 6142 of 6357 participants received complete in-clinic eye exams; 3596 participants remained after excluding 2341 with age < 50 years and 205 (46 with POAG, 159 without POAG) due to pseudophakia or aphakia status. Among the remaining 3596 LALES participants, 217 (6.0%) had POAG and 3379 (94.0%) did not. In CHES, 4582 participants were recruited and received complete in-clinic eye exams. Of these, 4310 participants remained after excluding 272 participants with missing or inconclusive glaucoma grades. Among these participants, 259 (48 with POAG, 211 without POAG) were excluded due to pseudophakia or aphakia status. In addition, 46 participants with PACG were also excluded. Among the remaining 4005 CHES participants, 159 (4.0%) had POAG and 3846 (96.0%) did not (Table 1). After combining eligible LALES and CHES participants, the dataset contained 7601 participants overall. 
Table 1.
 
Baseline Demographic and Clinical Characteristics of the Study Population
Table 1.
 
Baseline Demographic and Clinical Characteristics of the Study Population
The mean age of participants was 60.6 ± 8.3 years; 2974 (39.1%) participants were male and 4627 (60.9%) were female (Table 1); and 376 (4.9%) participants had POAG and 7225 (95.1%) did not. Family history of glaucoma was present in 617 (8.7%) participants. Mean RE was –0.08 ± 2.6 D, and mean AL was 23.6 ± 1.2 mm. Mean IOP was 15.0 ± 3.3 mmHg overall, 14.7 ± 3.5 mmHg in LALES, and 15.3 ± 3.1 mmHg in CHES (P < 0.001). Mean IOP among participants with POAG was 17.3 ± 5.1 mmHg overall, 17.5 ± 5.4 mmHg in LALES, and 17.1 ± 4.6 mmHg in CHES (P = 0.56). Also, 1.6% of LALES participants and 2.4% of CHES participants were on IOP-lowering medications at the time of examination. 
In the univariable analysis, male sex, older age, Latino ethnicity, family history of glaucoma, higher IOP, refractive myopia (mild, moderate, or high), and longer AL were associated with higher POAG risk (P < 0.05) (Table 2). In Model A (RE only), mild myopia (odds ratio [OR] = 1.54; 95% confidence interval [CI], 1.15–2.04), moderate myopia (OR = 2.47; 95% CI, 1.60–3.71), and high myopia (OR = 3.94; 95% CI, 2.39–6.25) all conferred higher risk of POAG (P ≤ 0.003). In Model B (AL only), longer AL (OR = 1.37 per mm; 95% CI, 1.26–1.48; P < 0.001) conferred higher risk of POAG. In Model C (RE and AL together), mild myopia (OR = 1.35; 95% CI, 1.00–1.81; P = 0.04) and high myopia (OR = 1.81; 95% CI, 0.97–3.27; P = 0.06) were no longer significantly associated with POAG and moderate myopia was borderline (OR = 1.64; 95% CI, 1.02–2.58; P = 0.04). Latino ethnicity (OR = 2.25; 95% CI, 1.75–2.90; P < 0.001) was also significantly associated with higher POAG risk. SRC analysis for Model C showed that age (SRC = 0.50), IOP (SRC = 0.50), and race/ethnicity (SRC = 0.41) were the strongest determinants of POAG risk, followed by AL (SRC = 0.30). AL was 2.7-fold more strongly associated with POAG compared to high myopia status (SRC = 0.11) per standard deviation. 
Table 2.
 
Univariable and Multivariable Models of the Association Between RE and/or AL and POAG
Table 2.
 
Univariable and Multivariable Models of the Association Between RE and/or AL and POAG
In univariable analysis with AL divided into its components, longer VCD and ACD were associated with higher POAG risk (P ≤ 0.02), but LT and CCT were not (Table 3). In Model D, longer VCD (OR = 1.37 per mm; 95% CI, 1.24–1.50; P < 0.001) remained significantly associated with higher POAG risk, whereas ACD (OR = 1.43; 95% CI, 1.00–2.04; P = 0.05) did not. Latino ethnicity (OR = 2.00; 95% CI, 1.48–2.72; P < 0.001) was also significantly associated with higher POAG risk. SRC analysis for Model D showed that VCD (SRC = 0.39) was 2.8-fold and 3.3-fold more strongly associated with higher POAG risk than ACD (SRC = 0.14) and LT (SRC = 0.12) per standard deviation, respectively. In multivariable Model E, longer VCD (OR = 1.24 per mm; 95% CI, 1.11–1.39), moderate myopia (OR = 1.69; 95% CI, 1.04–2.65), and high myopia (OR = 2.12; 95% CI, 1.14–3.82) were significantly associated with POAG risk (P ≤ 0.03), whereas mild myopia was not. SRC analysis for Model E showed that the association was 2.3-fold and 2.1-fold stronger for VCD (SRC = 0.28) compared to moderate myopia status (SRC = 0.12) and high myopia status (SRC = 0.13), respectively, per standard deviation. 
Table 3.
 
Univariable and Multivariable Models of the Association Between AL Components and RE and POAG
Table 3.
 
Univariable and Multivariable Models of the Association Between AL Components and RE and POAG
Multivariable logistic regression models with sex, age, race/ethnicity, family history of glaucoma, IOP, AL, or RE and an interaction term (race/ethnicity × IOP, AL, or myopic RE) were developed to assess effect modifications. These interaction terms were not significant between race/ethnicity and IOP, AL, or any severity of myopia (P ≥ 0.38). 
LOWESS curves fit to predict POAG risk adjusted for sex, age, family history of glaucoma, IOP, and AL or VCD were generated using separate multivariable logistic regression models for LALES and CHES. Results showed a similar effect of AL (Fig. 1) and VCD (Fig. 2) for both cohorts with a trend toward consistently higher POAG risk among LALES participants. 
Figure 1.
 
LOWESS plot showing predicted probability of POAG per 0.5 mm AL among LALES (gray) and CHES (black) participants. Points represent the mean probability of POAG within each 0.5-mm AL category; lines represent regression fitting to the probability points. Points with small sample size (<30 participants) are omitted.
Figure 1.
 
LOWESS plot showing predicted probability of POAG per 0.5 mm AL among LALES (gray) and CHES (black) participants. Points represent the mean probability of POAG within each 0.5-mm AL category; lines represent regression fitting to the probability points. Points with small sample size (<30 participants) are omitted.
Figure 2.
 
LOWESS plot showing predicted probability of POAG per 0.5 mm VCD among LALES (gray) and CHES (black) participants. Points represent the mean probability of POAG within each 0.5-mm VCD category; lines represent regression fitting to the probability points. Points with small sample size (<30 participants) are omitted.
Figure 2.
 
LOWESS plot showing predicted probability of POAG per 0.5 mm VCD among LALES (gray) and CHES (black) participants. Points represent the mean probability of POAG within each 0.5-mm VCD category; lines represent regression fitting to the probability points. Points with small sample size (<30 participants) are omitted.
Discussion
In this cross-sectional study, we investigated racial and ethnic differences in the roles of myopia and ocular biometrics as risk factors for POAG among phakic Latino and Chinese Americans from LALES and CHES. Unadjusted POAG risk was 1.6 times higher among LALES participants, which increased to 2.3 times higher risk after adjusting for associated factors, including RE and/or ocular biometrics. In addition, there was no modifying effect by race/ethnicity on the relationships between POAG risk and RE, AL, or IOP. Finally, we found that AL is 2.7-fold more strongly associated with higher POAG risk than high myopia status. These findings highlight the importance of ocular biometrics in the pathogenesis of POAG and the potential impact of racial and ethnic differences in myopia incidence on POAG prevalence worldwide. 
The burden of POAG varies significantly by race and ethnicity, with Latinos generally having higher prevalence of POAG compared to Asians; however, a strong explanatory factor for these observed differences has not been established.2527 This motivated us to assess how RE and AL contribute to racial and ethnic differences in POAG prevalence and risk between Latino and Chinese Americans. We initially observed a 1.6-fold higher unadjusted risk of POAG in LALES compared to CHES participants. However, we also observed a higher burden of refractive and axial myopia in CHES participants; 15.0% were moderate or severe myopes and 7.4% had AL > 26.0 mm compared to 3.4% and 1.1% in LALES, respectively.20,31 After adjusting for associated factors, including RE and AL, Latinos had 2.3-fold higher risk of POAG. These findings demonstrate that the difference in POAG prevalence between Latino and Chinese Americans is narrowed by the higher prevalence of refractive and axial myopia among Chinese Americans; however, they do not explain why the adjusted risk of POAG is also higher in LALES.7 
We hypothesized that the risk of POAG conferred by more myopic RE or longer AL may be greater among Latinos than Asians, even if these risk factors are less common. However, our interaction term analyses showed no effect modification between RE or AL and POAG risk by race/ethnicity, and LOWESS plots showed a constant difference in POAG risk between Latino and Chinese Americans. Our results are consistent with findings from Shen et al.,30 who found no significant difference in the per-diopter decrease in RE on POAG risk between Asian and Latino subjects, while providing novel insight into the interaction between race, AL, and POAG risk. These findings together suggest that higher POAG risk among Latino Americans is not related to a stronger effect of myopic RE or longer AL and instead implicates other genetic, physiological, or environmental factors.13 By extension, the similar effects of RE (per diopter) and AL (per millimeter) on POAG risk across race and ethnicity suggest that racial populations that currently have higher incidence of myopia, such as Asians, may become disproportionately affected by POAG in the future, thereby further narrowing racial differences in POAG prevalence.7 
Our findings on the contributions of myopic RE and longer AL to POAG risk are consistent with their well-established roles as risk factors for POAG. We found that high, moderate, and mild myopes have 3.9-, 2.5-, and 1.5-times higher risks of POAG, respectively, compared to non-myopes. These estimates are comparable to those reported by a meta-analysis of seven cross-sectional studies on the association between RE and POAG, which reported an OR of 2.46 for moderate to high myopia and 1.65 for mild myopia.7 We also found that that each millimeter longer in AL conferred 1.4-times higher odds of POAG. This estimate is comparable to previous studies that reported 1.3-times higher odds per millimeter longer in AL.11,12 
Our SRC analysis provides novel insight into the relative contributions of RE and ocular biometrics to POAG risk. AL and VCD were 2.7- and 2.1-times more strongly associated with POAG risk, respectively, than high myopia status. In addition, mild and high myopia status were no longer significantly associated with POAG risk when AL was included in the same multivariable model (Model C), and mild myopia was no longer significantly associated with POAG when VCD was included in the same multivariable model (Model E).16 These findings suggest that myopic RE contributes to POAG risk primarily through axial elongation, which increases shear strain on the lamina cribrosa and impairs structural support and peripapillary perfusion of the optic nerve.32,33 RE as a predictive factor for POAG appears weakened by corneal and lens properties that influence refractive status but not POAG risk. Our analyses of AL components further suggest that VCD contributes more to POAG risk than CCT, ACD, or LT (Model D), although not as much as AL overall (Models C and E). These findings together suggest that future studies on myopia could benefit from reporting of not only RE status but also AL and VCD, at least for forecasting changes in POAG prevalence. 
In addition to myopic RE and longer AL, we also identified higher IOP, older age, positive family history of glaucoma, and male sex as risk factors for POAG. IOP remains the primary modifiable risk factor in the treatment of glaucoma. Although mean IOP was higher in CHES, mean IOP among participants with POAG was similar between LALES and CHES. In addition, interaction term analysis showed no effect modification between IOP and POAG risk by race/ethnicity. Therefore, POAG risk conferred per mmHg of IOP appears similar between Latino and Chinese Americans. Numerous studies, including LALES, Blue Mountains Eye Study, and Baltimore Eye Study, support the significance of age and family history as risk factors for POAG.3,4,34,35 However, the role of male sex as a risk factor is less clear. Recent studies, including LALES, Beijing Eye Study, Primary Open-Angle African American Glaucoma Genetics Study, and two large meta-analyses, found significant associations between male sex and POAG.1,3,6,26,36 However, the Barbados Eye Study, Proyecto VER, and Handan Eye Study found no significant association, whereas other studies have reported a higher risk of POAG among females.4,11,3739 Therefore, further work is required to firmly establish the role of sex as a risk factor for POAG. 
Our study has some limitations. First, differentiating myopic from glaucomatous damage of the optic nerve head based on cross-sectional data can be difficult. This is especially true when AL exceeds 26.0 mm, which occurred in 1.1% of LALES and 7.4% of CHES participants.20,31,32 The higher proportion of difficult-to-evaluate cases among CHES participants could have confounded the effect modification by race/ethnicity on AL, although this effect would likely be small due to the small sample of eyes with AL > 26.0 mm. Second, although gonioscopy in CHES was performed on all participants, gonioscopy in LALES was performed at the examiner's discretion and only when participants appeared to have narrow angles on slit-lamp exam.28 The misclassification of angle-closure glaucoma as POAG would strengthen the association between hyperopia/shorter AL and POAG, as hyperopia and short AL are both risk factors for PACG.2 However, this sample of eyes and, consequently, the effect of this misclassification would be expected to be small. Finally, although LALES and CHES were both conducted in Los Angeles County, LALES participants were recruited from La Puente and CHES participants were recruited from Monterey Park. Therefore, participants of the two studies could have been exposed to different environmental and lifestyle factors that contribute to POAG risk. 
In conclusion, Latino Americans are at higher risk for POAG than Chinese Americans, but the difference in POAG prevalence is narrowed by higher prevalence of refractive and axial myopia among Chinese Americans. AL is also a stronger predictor of POAG risk than RE, although the latter remains a useful and often more convenient clinical measure for risk stratification. These findings are important in the setting of rising myopia prevalence worldwide and increasing racial/ethnic diversity in some regions. However, an explanation for why POAG risk is higher in some racial/ethnic populations, including Latinos, even after accounting for established risk factors, remains elusive. Future study of other factors that could be modulated by race and ethnicity, especially genetic, biomechanical, and sociodemographic factors, may be informative and beneficial. We hope our findings contribute to improvements in the precision of glaucoma risk stratification and prevalence forecasts in the setting of the ongoing myopia epidemic. 
Acknowledgments
Supported by grants from the National Eye Institute, National Institutes of Health (EY-017337 and K23 EY029763); a Young Clinician Scientist Research Award from the American Glaucoma Society; and an unrestricted grant to the Department of Ophthalmology from Research to Prevent Blindness. S.Z. was supported by the Dean's Research Scholars Program of the Keck School of Medicine. 
Disclosure: S. Zhou, None; B. Burkemper, None; A.A. Pardeshi, None; G. Apolo, None; G. Richter, None; X. Jiang, None; M. Torres, None; R. McKean-Cowdin, None; R. Varma, None; B.Y. Xu, None 
References
Tham YC, Li X, Wong TY, Quigley HA, Aung T, Cheng CY. Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. Ophthalmology. 2014; 121(11): 2081–2090. [CrossRef] [PubMed]
Iwase A, Suzuki Y, Araie M, et al. The prevalence of primary open-angle glaucoma in Japanese: the Tajimi Study. Ophthalmology. 2004; 111(9): 1641–1648. [PubMed]
Doshi V, Ying-Lai M, Azen SP, Varma R. Sociodemographic, family history, and lifestyle risk factors for open-angle glaucoma and ocular hypertension: the Los Angeles Latino Eye Study. Ophthalmology. 2008; 115(4): 639–647. [CrossRef] [PubMed]
Leske MC, Connell AMS, Wu SY, Hyman LG, Schachat AP. Risk factors for open-angle glaucoma: the Barbados Eye Study. Arch Ophthalmol. 1995; 113(7): 918–924. [CrossRef] [PubMed]
Holden BA, Fricke TR, Wilson DA, et al. Global prevalence of myopia and high myopia and temporal trends from 2000 through 2050. Ophthalmology. 2016; 123(5): 1036–1042. [CrossRef] [PubMed]
Kapetanakis VV, Chan MPY, Foster PJ, Cook DG, Owen CG, Rudnicka AR. Global variations and time trends in the prevalence of primary open angle glaucoma (POAG): a systematic review and meta-analysis. Br J Ophthalmol. 2016; 100(1): 86–93. [CrossRef] [PubMed]
Marcus MW, De Vries MM, Montolio FGJ, Jansonius NM. Myopia as a risk factor for open-angle glaucoma: a systematic review and meta-analysis. Ophthalmology. 2011; 118(10): 1989–1994. [CrossRef] [PubMed]
Mitchell P, Hourihan F, Sandbach J, Wang J. The relationship between glaucoma and myopia: the Blue Mountains Eye Study. Ophthalmology. 1999; 106(10): 2010–2015. [CrossRef] [PubMed]
Xu L, Wang Y, Wang S, Wang Y, Jonas JB. High myopia and glaucoma susceptibility: the Beijing Eye Study. Ophthalmology. 2007; 114(2): 216–220. [CrossRef] [PubMed]
Congdon NG, Broman AT, Bandeen-Roche K, Grover D, Quigley HA. Central corneal thickness and corneal hysteresis associated with glaucoma damage. Am J Ophthalmol. 2006; 141(5): 868–875. [CrossRef] [PubMed]
Liang YB, Friedman DS, Zhou Q, et al. Prevalence of primary open angle glaucoma in a rural adult Chinese population: the Handan Eye Study. Invest Ophthalmol Vis Sci. 2011; 52(11): 8250–8257. [CrossRef] [PubMed]
Kuzin AA, Varma R, Reddy HS, Torres M, Azen SP. Ocular biometry and open-angle glaucoma: the Los Angeles Latino Eye Study. Ophthalmology. 2010; 117(9): 1713–1719. [CrossRef] [PubMed]
Jiang X, Varma R, Wu S, et al. Baseline risk factors that predict the development of open-angle glaucoma in a population: the Los Angeles Latino Eye Study. Ophthalmology. 2012; 119(11): 2245–2253. [CrossRef] [PubMed]
Tham YC, Aung T, Fan Q, et al. Joint effects of intraocular pressure and myopia on risk of primary open-angle glaucoma: the Singapore Epidemiology of Eye Diseases Study. Sci Rep. 2016; 6: 19320. [CrossRef] [PubMed]
Baird PN, Saw SM, Lanca C, et al. Myopia. Nat Rev Dis Primer. 2020; 6(1): 1–20.
Perera SA, Wong TY, Wan-Ting T, Foster PJ, Saw SM, Aung T. Refractive error, axial dimensions, and primary open-angle glaucoma: the Singapore Malay Eye Study. Arch Ophthalmol. 2010; 128(7): 900–905. [CrossRef] [PubMed]
Williams KM, Verhoeven VJM, Cumberland P, et al. Prevalence of refractive error in Europe: the European Eye Epidemiology (E3) Consortium. Eur J Epidemiol. 2015; 30(4): 305–315. [CrossRef] [PubMed]
Vitale S, Sperduto RD, Ferris FL. Increased prevalence of myopia in the United States between 1971-1972 and 1999-2004. Arch Ophthalmol. 2009; 127(12): 1632–1639. [CrossRef] [PubMed]
Han X, Guo X, Lee PY, Morgan IG, He M. Six-year changes in refraction and related ocular biometric factors in an adult Chinese population. PLoS One. 2017; 12(8): e0183364. [CrossRef] [PubMed]
Flitcroft DI, He M, Jonas JB, et al. IMI - defining and classifying myopia: a proposed set of standards for clinical and epidemiologic studies. Invest Ophthalmol Vis Sci. 2019; 60(3): M20–M30. [CrossRef] [PubMed]
Saw S, Chua W, Gazzard G, Koh D, Tan D, Stone R. Eye growth changes in myopic children in Singapore. Br J Ophthalmol. 2005; 89(11): 1489–1494. [CrossRef] [PubMed]
Guo Y, Liu LJ, Tang P, et al. Outdoor activity and myopia progression in 4-year follow-up of Chinese primary school children: the Beijing Children Eye Study. PLoS One. 2017; 12(4): e0175921. [CrossRef] [PubMed]
Khachatryan N, Medeiros FA, Sharpsten L, et al. The African Descent and Glaucoma Evaluation Study (ADAGES): predictors of visual field damage in glaucoma suspects. Am J Ophthalmol. 2015; 159(4): 777–787. [CrossRef] [PubMed]
U.S. Census Bureau. (NP-T5-G) projections of the resident population by race, hispanic origin and nativity: middle series, 2050 to 2070. Available at: https://www2.census.gov/programs-surveys/popproj/tables/2000/2000-national-summary-tables/np-t5-f.pdf . Accessed May 18, 2023.
Varma R, Ying-Lai M, Francis BA, et al. Prevalence of open-angle glaucoma and ocular hypertension in Latinos: the Los Angeles Latino Eye Study. Ophthalmology. 2004; 111(8): 1439–1448. [CrossRef] [PubMed]
Wang YX, Xu L, Yang H, Jonas JB. Prevalence of glaucoma in North China: the Beijing Eye Study. Am J Ophthalmol. 2010; 150(6): 917–924. [CrossRef] [PubMed]
He M, Foster PJ, Ge J, et al. Prevalence and clinical characteristics of glaucoma in adult Chinese: a population-based study in Liwan District, Guangzhou. Invest Ophthalmol Vis Sci. 2006; 47(7): 2782–2788. [CrossRef] [PubMed]
Varma R, Paz SH, Azen SP, et al. The Los Angeles Latino Eye Study: design, methods, and baseline data. Ophthalmology. 2004; 111(6): 1121–1131. [CrossRef] [PubMed]
Varma R, Hsu C, Wang D, Torres M, Azen SP. The Chinese American eye study: design and methods. Ophthalmic Epidemiol. 2013; 20(6): 335–347. [CrossRef] [PubMed]
Shen L, Melles RB, Metlapally R, et al. The association of refractive error with glaucoma in a multiethnic population. Ophthalmology. 2016; 123(1): 92–101. [CrossRef] [PubMed]
Tideman JWL, Snabel MCC, Tedja MS, et al. Association of axial length with risk of uncorrectable visual impairment for Europeans with myopia. JAMA Ophthalmol. 2016; 134(12): 1355–1363. [CrossRef] [PubMed]
Wang YX, Panda-Jonas S, Jonas JB. Optic nerve head anatomy in myopia and glaucoma, including parapapillary zones alpha, beta, gamma and delta: histology and clinical features. Prog Retin Eye Res. 2021; 83: 100933. [CrossRef] [PubMed]
Wang X, Kong X, Jiang C, Li M, Yu J, Sun X. Is the peripapillary retinal perfusion related to myopia in healthy eyes? A prospective comparative study. BMJ Open. 2016; 6(3): e010791. [CrossRef] [PubMed]
Tielsch JM, Katz J, Sommer A, et al. Family history and risk of primary open angle glaucoma. The Baltimore Eye Survey. Arch Ophthalmol. 1994; 112(1): 69–73. [CrossRef] [PubMed]
Podos SM, Becker B, Morton W. High myopia and primary open-angle glaucoma. Am J Ophthalmol. 1966; 62(6): 1038–1043. [CrossRef] [PubMed]
Khachatryan N, Pistilli M, Maguire MG, et al. Primary Open-Angle African American Glaucoma Genetics (POAAGG) Study: gender and risk of POAG in African Americans. PLoS One. 2019; 14(8): e0218804. [CrossRef] [PubMed]
Quigley H, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol. 2006; 90(3): 262–267. [CrossRef] [PubMed]
Klein R, Klein BEK. The prevalence of age-related eye diseases and visual impairment in aging: current estimates. Invest Ophthalmol Vis Sci. 2013; 54(14): ORSF5–ORSF13. [CrossRef] [PubMed]
Quigley HA, West SK, Rodriguez J, Munoz B, Klein R, Snyder R. The prevalence of glaucoma in a population-based study of hispanic participants: Proyecto VER. Arch Ophthalmol. 2001; 119(12): 1819–1826. [CrossRef] [PubMed]
Figure 1.
 
LOWESS plot showing predicted probability of POAG per 0.5 mm AL among LALES (gray) and CHES (black) participants. Points represent the mean probability of POAG within each 0.5-mm AL category; lines represent regression fitting to the probability points. Points with small sample size (<30 participants) are omitted.
Figure 1.
 
LOWESS plot showing predicted probability of POAG per 0.5 mm AL among LALES (gray) and CHES (black) participants. Points represent the mean probability of POAG within each 0.5-mm AL category; lines represent regression fitting to the probability points. Points with small sample size (<30 participants) are omitted.
Figure 2.
 
LOWESS plot showing predicted probability of POAG per 0.5 mm VCD among LALES (gray) and CHES (black) participants. Points represent the mean probability of POAG within each 0.5-mm VCD category; lines represent regression fitting to the probability points. Points with small sample size (<30 participants) are omitted.
Figure 2.
 
LOWESS plot showing predicted probability of POAG per 0.5 mm VCD among LALES (gray) and CHES (black) participants. Points represent the mean probability of POAG within each 0.5-mm VCD category; lines represent regression fitting to the probability points. Points with small sample size (<30 participants) are omitted.
Table 1.
 
Baseline Demographic and Clinical Characteristics of the Study Population
Table 1.
 
Baseline Demographic and Clinical Characteristics of the Study Population
Table 2.
 
Univariable and Multivariable Models of the Association Between RE and/or AL and POAG
Table 2.
 
Univariable and Multivariable Models of the Association Between RE and/or AL and POAG
Table 3.
 
Univariable and Multivariable Models of the Association Between AL Components and RE and POAG
Table 3.
 
Univariable and Multivariable Models of the Association Between AL Components and RE and POAG
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×