Purpose
To describe racial variations in the prevalence of refractive errors among adult white, Chinese, Hispanic, and black subjects in the United States.
Design
Cross-sectional data from a prospective cohort study—the Multi-Ethnic Study of Atherosclerosis (MESA).
Methods
A total of 6000 adults aged 45 to 84 years living in the United States participated in the study. Refractive error was assessed, without cycloplegia, in both eyes of all participants using an autorefractor. After excluding eyes with cataract, cataract surgery, or previous refractive surgery, the eye with the larger absolute spherical equivalent (SE) value for each participant was used to classify refractive error. Any myopia was defined as SE of -1.0 diopters (D) or less; high myopia was defined as SE of -5.0 D or less; any hyperopia was defined as SE of +1.0 D or more; clinically significant hyperopia was defined as SE of +3.0 D or more. Astigmatism was defined as a cylinder value of +1.0 D or more.
Results
After excluding 508 participants with cataracts in both eyes, 838 participants with cataract surgery, 90 participants with laser refractive surgery, and 134 participants who refused to remove their contact lenses for the refraction measurement, 4430 adults with refractive error assessment in at least 1 eye contributed to the analysis. The prevalence of myopia among MESA participants was 25.1%, with lowest rates in Hispanic participants (14.2%), followed by black (21.5%) and white participants (31.0%), and highest rates in Chinese participants (37.2%). The overall rates of high myopia and astigmatism were 4.6% and 45.0%, respectively, with Chinese subjects also having the highest rates of high myopia (11.8%) and astigmatism (53.4%). The overall prevalence of any hyperopia was 38.2% and clinically significant hyperopia was 6.1%, with Hispanic participants having the highest rates of hyperopia (50.2%) and clinically significant hyperopia (8.8%). In multivariate analyses adjusting for age, sex, race, and study site, higher education level, being employed, and being taller were associated with a higher prevalence of myopia. In contrast, lower educational level and being shorter were associated with a higher prevalence of hyperopia.
Conclusions
Myopia and astigmatism were most prevalent in the Chinese population, with Chinese subjects having 3 times the prevalence of myopia as Hispanic subjects. Hyperopia was most common in Hispanic subjects. These findings provide further insights into variations in refractive errors among different racial groups and have important implications for the eye care services in the United States.
Refractive errors are significant public health concerns in the United States and throughout the world. Approximately 1.6 billion people worldwide are affected by myopia and the prevalence of myopia is expected to increase to 2.5 billion by the year 2020. Uncorrected refractive error is a leading cause of visual loss in the population, and high myopia is associated with higher risks of cataract, glaucoma, and retinal diseases. It is estimated that globally 153 million people over 5 years of age are visually impaired as a result of uncorrected refractive errors, of whom 8 million are blind. It is widely believed that refractive errors, especially myopia, are multi-factorial traits, involving the effect of genes as well as environmental factors. Race may be a surrogate for differences in both genetic biomarkers and environmental exposures such as the intensity of schooling, near work, outdoor activity, and lifestyle factors. Current data, largely based on studies in children, have shown significant racial difference in the prevalence of myopia. For example, in Asia, where a perceived “epidemic” of myopia has been observed, Chinese children have been reported to have higher prevalence of myopia compared with other racial groups. In the United States, the Collaborative Longitudinal Evaluation of Ethnicity and Refractive Error (CLEER) found that Asian children had the highest prevalence of myopia (18.5%), followed by Hispanic subjects (13.2%). White subjects had the lowest prevalence of myopia (4.4%), which was not significantly different from black subjects (6.6%).
However, the exact pattern of racial variations in adult populations remains unclear, and most studies have compared racial differences between disparate populations and used varying definitions. The Tanjong Pagar study on a Singapore Chinese population reported a myopia prevalence of 51.7% in female subjects and 45.2% in male subjects in the 40- to 49-year-old group, whereas the meta-analysis by Kempen and associates reported a prevalence of 46.3% for US white female subjects and 36.8% for male subjects in the same age group. Given that the analysis by Kempen and associates used a more stringent criterion of -1 diopter (D) whereas the Tanjong Pagar analysis used -0.5 D, it is unclear if there are true racial differences between Singapore Chinese and US white subjects. In the 1999-2004 National Health and Nutrition Examination Survey (NHANES) on a nationally representative sample of the US noninstitutionalized, civilian population 12 years and older, myopia was more common in non-Hispanic white subjects (35.2%) than in non-Hispanic black (28.6%) or Hispanic subjects (25.1%). However, the prevalence of myopia in Chinese American subjects was not reported in NHANES. Furthermore, racial differences in other refractive errors such as hyperopia and astigmatism are less well studied.
In this paper, we described the prevalence of refractive errors in the middle- and older-age adults of 4 racial groups in the United States: white, Chinese, black, and Hispanic.
Methods
Study Population
The Multi-Ethnic Study of Atherosclerosis (MESA) is a prospective cohort study of adults aged 45 to 84 years sampled from 6 United States communities who, at the time of study enrollment, were free from clinical cardiovascular disease. Details of the design and methodology of the study have been described elsewhere. In brief, the MESA cohort includes 6814 men and women 45 to 84 years old at baseline (July 2000 to July 2002) who were recruited from 6 field centers: Baltimore, Maryland; Chicago, Illinois; Forsyth County, North Carolina; Los Angeles, California; New York, New York; and St Paul, Minnesota. Each site planned to examine about 1100 eligible participants, equally divided between men and women, according to site-specified race/ethnicity proportions. Each field site recruited from locally available sources, which included lists of residents, lists of dwellings, and telephone exchanges. In the last few months of the recruitment period, supplemental sources (ie, lists of Medicare beneficiaries from the Centers for Medicare and Medicaid Services and referrals by participants) were used to ensure adequate numbers of minorities and elderly subjects. In general, we sought to recruit a population-based cohort from defined census tracts or an occupational cohort using a random selection process. Of the 6814 adults examined at baseline, 6233 returned for a second examination and 6099 agreed to participate in the refraction component offered to them (August 2002 to February 2004). Table 1 shows the distribution of the MESA study participants in each study site by racial group. All participants completed a study questionnaire inquiring about demographic, behavioral, and personal medical history.
| White | Chinese | Black | Hispanic | |||||
|---|---|---|---|---|---|---|---|---|
| N | % | N | % | N | % | N | % | |
| Forsyth County, North Carolina | ||||||||
| Baseline examination (n = 6814) | 573 | 53.2 | 0 | 0 | 501 | 46.5 | 3 | 0.3 |
| Second examination (n = 6233) | 536 | 54.4 | 0 | 0 | 446 | 45.3 | 3 | 0.3 |
| Agreeing to refraction (n = 6099) | 531 | 55.4 | 0 | 0 | 423 | 44.3 | 3 | 0.3 |
| Included in the analysis (n = 4430) | 359 | 52.7 | 0 | 0 | 320 | 47.0 | 2 | 0.3 |
| New York, New York | ||||||||
| Baseline examination (n = 6814) | 223 | 20.2 | 2 | 0.2 | 381 | 34.6 | 496 | 45.0 |
| Second examination (n = 6233) | 214 | 20.8 | 2 | 0.2 | 354 | 34.4 | 459 | 44.6 |
| Agreeing to refraction (n = 6099) | 212 | 21.0 | 2 | 0.2 | 347 | 34.4 | 449 | 44.5 |
| Included in the analysis (n = 4430) | 142 | 19.4 | 0 | 0 | 256 | 35.0 | 334 | 45.6 |
| Baltimore, Maryland | ||||||||
| Baseline examination (n = 6814) | 533 | 49.1 | 0 | 0 | 553 | 50.9 | 0 | 0 |
| Second examination (n = 6233) | 483 | 50.5 | 0 | 0 | 473 | 49.5 | 0 | 0 |
| Agreeing to refraction (n = 6099) | 472 | 50.8 | 0 | 0 | 458 | 49.2 | 0 | 0 |
| Included in the analysis (n = 4430) | 323 | 49.4 | 0 | 0 | 331 | 50.6 | 0 | 0 |
| St Paul, Minnesota | ||||||||
| Baseline examination (n = 6814) | 605 | 56.8 | 0 | 0 | 0 | 0 | 461 | 43.2 |
| Second examination (n = 6233) | 567 | 58.5 | 0 | 0 | 0 | 0 | 402 | 41.5 |
| Agreeing to refraction (n = 6099) | 566 | 59.0 | 0 | 0 | 0 | 0 | 394 | 41.0 |
| Included in the analysis (n = 4430) | 396 | 55.5 | 0 | 0 | 0 | 0 | 318 | 44.5 |
| Chicago, Illinois | ||||||||
| Baseline examination (n = 6814) | 557 | 47.9 | 304 | 26.1 | 303 | 26.0 | 0 | 0 |
| Second examination (n = 6233) | 531 | 49.1 | 277 | 25.6 | 273 | 25.3 | 0 | 0 |
| Agreeing to refraction (n = 6099) | 511 | 49.2 | 264 | 25.4 | 264 | 25.4 | 0 | 0 |
| Included in the analysis (n = 4430) | 350 | 46.7 | 192 | 25.6 | 208 | 27.7 | 0 | 0 |
| Los Angeles County, California | ||||||||
| Baseline examination (n = 6814) | 131 | 9.9 | 497 | 37.7 | 155 | 11.8 | 536 | 40.6 |
| Second examination (n = 6233) | 133 | 11.0 | 449 | 37.0 | 145 | 12.0 | 486 | 40.1 |
| Agreeing to refraction (n = 6099) | 128 | 10.7 | 447 | 37.2 | 143 | 11.9 | 483 | 40.2 |
| Included in the analysis (n = 4430) | 97 | 10.8 | 487 | 11.0 | 115 | 12.8 | 392 | 43.6 |
Tenets of the Declaration of Helsinki were followed, and institutional review board approval was granted at each study site. Written informed consent was obtained from each participant.
Refractive Assessment
Participants underwent an examination for refractive errors performed using a table-top autorefractor (NIDEK model ARK-760A; Nidek Co Ltd, Tokyo, Japan). In a dim room, participants had each eye refracted separately without pharmacologic cycloplegia by trained technicians certified for adherence to a standardized study protocol. Refractive error values of sphere and cylinder were measured to the closest 0.25 D using positive cylinder notation.
Exclusion Criteria
Two participants who had no light perception in both eyes and 1 participant who had a serious eye infection at the time of the examination were considered ineligible for this study. Six participants who wore an eye patch to the examination did not have refraction testing performed on the patched eye. Participants wearing contact lenses were asked to remove them before measurements were taken. Incomplete refraction data were obtained from 96 individuals who did not complete the assessment because of physical limitations, scheduling conflicts, or equipment failure.
Of the 6099 agreeing to participate in the refraction component, spherical equivalent (SE) data in at least 1 eye was available from 6000 participants. We excluded from this analysis 508 participants with cataracts in both eyes, 838 participants with cataract surgery, 90 participants with laser refractive surgery, and 134 participants who refused to remove their contact lenses for the refraction measurement. There were 4430 eligible participants with complete refraction data in at least 1 eye and 1669 participants who either were ineligible, did not have complete refractive data in either eye, or were otherwise excluded.
Classification of Refractive Errors
For all eyes contributing data to this analysis, we calculated spherical equivalent (SE) by adding the spherical diopter value to half of the cylinder diopter value. Refractive errors were also categorized into types, using values from the eye with the larger absolute SE. High myopia was defined as SE of -5.0 D or less; any myopia was defined as SE of -1.0 D or less; any hyperopia was defined as +1.0 D or more; clinically significant hyperopia was defined as +3.0 D or more. Astigmatism was defined as at least 1 D of cylinder, without reference to the axis.
Statistical Analyses
Demographics of subjects included in and excluded from analysis were compared. For those included in analysis, demographics were described and compared stratified by race and sex. The prevalence of different refractive errors was estimated within each racial group, adjusting for age, sex, and height. We adjusted for height since it was significantly associated with the prevalence of refractive errors in our study. Variables of interest significant in univariate analysis were included in multivariate logistic regression models to determine whether a variable of interest was associated with a specific type of refractive error. Odds ratio (OR) and 95% confidence interval (CI) were presented. Statistical analyses were performed using SAS software (SAS Institute Inc, Cary, North Carolina, USA).
Results
The distribution of demographic characteristics of these included and excluded groups is shown in Table 2 . Demographic characteristics of participants by sex are presented separately for white, Chinese, black, and Hispanic subjects in Table 3 .
| Excluded (N = 1669) | Included (N = 4430) | P | |
|---|---|---|---|
| Sex | |||
| Male | 676 (40.5%) | 2215 (50.0%) | <.001 |
| Female | 993 (59.5%) | 2215 (50.0%) | |
| Race | |||
| White | 754 (45.2%) | 1667 (37.6%) | <.001 |
| Chinese | 227 (13.6%) | 487 (11.0%) | |
| Black | 406 (24.3%) | 1230 (27.8%) | |
| Hispanic | 282 (16.9%) | 1046 (23.6%) | |
| Age | |||
| Mean ± SD (y) | 69.7 ± 9.23 | 61.3 ± 9.4 | <.001 |
| 45-54 y | 147 (8.8%) | 1280 (28.9%) | |
| 55-64 y | 262 (15.7%) | 1506 (34.0%) | |
| 65-74 y | 689 (41.3%) | 1196 (27.0%) | |
| 75+ y | 571 (34.3%) | 448 (10.1%) | |
| Education | |||
| <12 y | 294 (17.6%) | 728 (16.4%) | .339 |
| Completed HS/GED | 324 (19.4%) | 785 (17.7%) | |
| Some college | 464 (27.8%) | 1281 (28.9%) | |
| Bachelor’s degree | 292 (17.5%) | 798 (18.0%) | |
| Graduate/professional degree | 295 (17.6%) | 838 (18.9%) | |
| Marital status | |||
| Single | 139 (8.3%) | 377 (8.5%) | <.001 |
| Married | 956 (57.3%) | 2780 (63.2%) | |
| Divorced | 249 (14.9%) | 806 (18.2%) | |
| Widowed | 325 (19.5%) | 443 (10.0%) | |
| Occupation | |||
| Homemaker | 219 (13.1%) | 443 (10.0%) | <.001 |
| Employed | 584 (35.0%) | 2640 (59.6%) | |
| Unemployed | 23 (1.4%) | 137 (3.1%) | |
| Retired | 843 (50.5%) | 1210 (27.3%) | |
| Income | |||
| <20K | 487 (29.2%) | 935 (21.1%) | <.001 |
| 20K-<40K | 464 (27.8%) | 1205 (27.2%) | |
| 40K-<75K | 382 (22.9%) | 1214 (27.4%) | |
| >75K | 336 (20.1%) | 1076 (24.3%) | |
| Medical insurance available | 1632 (97.8%) | 4049 (91.4%) | <.001 |
| Hypertension | 920 (55.1%) | 1869 (42.2%) | <.001 |
| Diabetes | 551 (33.0%) | 1373 (31.0%) | .144 |
| Current smoker | 129 (7.7%) | 576 (13.0%) | <.001 |
| Wear glasses for distance vision | 1237 (74.1%) | 2848 (64.3%) | <.001 |
| Height in cm | 164.5 ± 9.8 | 166.7 ± 9.4 | <.001 |
| Study site | |||
| Forsyth County, NC | 279 (16.7%) | 682 (15.4%) | .139 |
| New York, NY | 279 (16.7%) | 733 (16.5%) | |
| Baltimore, MD | 275 (16.5%) | 652 (14.7%) | |
| St Paul, MN | 245 (14.7%) | 714 (16.1%) | |
| Chicago, IL | 290 (17.4%) | 754 (17.0%) | |
| Los Angeles, CA | 301 (18.0%) | 895 (20.2%) |
| White Subjects N = 1667 | Chinese Subjects N = 487 | Black Subjects N = 1230 | Hispanic Subjects N = 1046 | |||||
|---|---|---|---|---|---|---|---|---|
| Men n = 860 | Women n = 807 | Men n = 251 | Women n = 236 | Men n = 641 | Women n = 589 | Men n = 530 | Women n = 516 | |
| Mean age (SD) | 62.37 (9.59) | 60.86 (9.17) | 61.15 (9.35) | 59.35 (8.70) | 62.04 (9.50) | 61.20 (9.20) | 60.84 (9.55) | 60.64 (9.49) |
| Mean height in cm (SD) | 175.86 (6.91) | 162.30 (6.46) | 168.25 (6.20) | 156.28 (5.46) | 175.95 (6.87) | 162.33 (6.83) | 168.99 (6.37) | 155.44 (6.32) |
| Education | ||||||||
| <12 y | 33 (3.9%) | 28 (3.5%) | 38 (14.8%) | 63 (26.7%) | 68 (10.7%) | 54 (9.1%) | 206 (39.0%) | 236 (45.8%) |
| Completed HS/GED | 107 (12.4%) | 149 (18.5%) | 30 (12.0%) | 55 (23.3%) | 124 (19.3%) | 107 (18.2%) | 103 (19.4%) | 112 (21.7%) |
| Some college | 212 (24.6%) | 269 (33.3%) | 40 (16.0%) | 50 (21.2%) | 219 (34.2%) | 214 (36.3%) | 155 (29.3%) | 122 (23.6%) |
| Bachelor’s degree | 212 (24.6%) | 181 (22.4%) | 71 (28.4%) | 42 (17.8%) | 124 (19.3%) | 108 (18.4%) | 32 (6.0%) | 30 (5.8%) |
| Graduate/professional degree | 296 (34.5%) | 180 (22.3%) | 72 (28.8%) | 26 (11.0%) | 106 (16.5%) | 106 (18.1%) | 34 (6.4%) | 16 (3.0%) |
| Income | ||||||||
| <20K | 48 (5.6%) | 95 (11.8%) | 83 (32.9%) | 101 (42.7%) | 105 (16.4%) | 109 (18.5%) | 159 (30.0%) | 229 (44.4%) |
| 20K-<40K | 157 (18.2%) | 180 (22.3%) | 60 (24.1%) | 59 (24.8%) | 181 (28.2%) | 200 (33.9%) | 191 (36.0%) | 177 (34.4%) |
| 40K-<75K | 282 (32.8%) | 254 (31.5%) | 44 (17.7%) | 37 (15.8%) | 204 (31.9%) | 188 (31.9%) | 120 (22.7%) | 86 (16.6%) |
| >75K | 373 (43.4%) | 278 (34.5%) | 64 (25.3%) | 39 (16.7%) | 151 (23.5%) | 93 (15.8%) | 60 (11.3%) | 24 (4.6%) |
| Current smoker | 111 (12.9%) | 98 (12.1%) | 26 (10.4%) | 6 (2.5%) | 132 (20.6%) | 89 (15.1%) | 74 (14.0%) | 45 (8.7%) |
Refractive error, defined as mean SE of both eyes, differs by age and sex and is depicted graphically for each ethnic group in the Figure . Across ethnic groups, negative SE values were more common at the younger ages, whereas positive SE values predominated at the older ages. Women tended to have more extreme SE values as compared with men of comparable age, except among Chinese subjects. Chinese men had lower SE values compared with Chinese women. In contrast to the other racial groups, Chinese subjects had the most variation in SE values across the age range of MESA participants.
Age-, sex-, and height-adjusted rates of specific types of refractive errors are presented by racial group and overall in Table 4 . The prevalence of myopia among all MESA participants was 25.1% (1111/4430), although the rates varied from 14.2% (149/1046) in Hispanic subjects to 37.2% (181/487) in Chinese subjects. The overall rates of high myopia and astigmatism were 4.6% (204/4430) and 45.0% (1993/4430), respectively. Again, contrasting the racial groups, Chinese subjects also had the highest rates of high myopia (11.8%, 57/487) and astigmatism (53.4% 260/487). The overall prevalence of any hyperopia was 38.2% (1694/4430) and clinically significant hyperopia was 6.1% (271/4430). Hispanic subjects had the highest rates of hyperopia (50.2%, 525/1046) and clinically significant hyperopia (8.8%, 92/1046).
| White | Chinese | Black | Hispanic | P Value | Overall | |
|---|---|---|---|---|---|---|
| High myopia | 90 (5.4%) | 57 (11.8%) | 38 (3.1%) | 19 (1.8%) | <.001 | 204 (4.6%) |
| Any myopia | 517 (31.0%) | 181 (37.2%) | 264 (21.5%) | 149 (14.2%) | <.001 | 1111 (25.1%) |
| Any hyperopia | 585 (35.1%) | 120 (24.7%) | 464 (37.7%) | 525 (50.2%) | <.001 | 1694 (38.2%) |
| Clinically significant hyperopia | 102 (6.1%) | 17 (3.4%) | 60 (4.9%) | 92 (8.8%) | <.001 | 271 (6.1%) |
| Astigmatism | 760 (45.6%) | 260 (53.4%) | 529 (43.0%) | 444 (42.4%) | <.001 | 1993 (45.0%) |
| Emmetropia | 565 (33.9%) | 186 (38.1%) | 502 (40.8%) | 372 (35.6%) | <.001 | 1625 (36.7%) |
Various refractive types adjusted for major demographic factors are presented in Table 5 . Controlling for all other factors in the model, the risk of myopia was significantly higher in the younger ages compared with older ages, whereas the opposite was true for hyperopia and astigmatism. Compared with white participants, Chinese subjects were more likely to have myopia, whereas black and Hispanic subjects were less likely. For hyperopia, Chinese subjects were less likely, Hispanic subjects more likely, and black subjects just as likely to have rates comparable to white subjects. For astigmatism, Hispanic subjects were less likely, Chinese subjects more likely, and black subjects just as likely to have astigmatism compared with white subjects. Female subjects were somewhat more likely than male subjects to have myopia or hyperopia; male subjects were more likely than female subjects to have astigmatism. There was no association between income and any type of refractive error; however, those who were currently or formerly employed were more likely to have myopia compared with homemakers. Employment history was not associated with hyperopia or astigmatism. Increasing educational level was associated with increasing risk of myopia in a dose-response manner, whereas those at the highest education levels were least likely to have hyperopia. There was no association between educational level and astigmatism. Height was positively associated with myopia, whereas it was negatively associated with hyperopia. There was no association of height with high myopia, clinically significant hyperopia, or astigmatism.
