Purpose
To estimate the prevalence of near vision impairment and use of corrective spectacles among middle-aged and older adults in different settings and ethnic groups.
Design
Population-based, cross-sectional study.
Methods
People aged ≥35 years were randomly selected with cluster sampling in 4 rural settings in Shunyi (China), Kaski (Nepal), Madurai (India), and Dosso (Niger); 1 semi-urban area in Durban (South Africa); and 2 urban settings in Guangzhou (China) and Los Angeles (USA). Near visual acuity (VA), with and without presenting near correction, was measured at 40 cm using a logMAR near vision tumbling E chart. Subjects with uncorrected binocular near VA ≤20/40 were tested with plus spheres to obtain the best-corrected binocular VA.
Results
A total of 17 734 persons aged ≥35 years were enumerated and 14 805 (83.5%) were examined. The age- and sex-standardized prevalence of uncorrected near vision impairment (VA ≤20/40) ranged from 49% in Dosso to 60% in Shunyi and Guangzhou, 65% in Kaski and Los Angeles, and 83% in Madurai and Durban. The prevalence of near vision impairment based on best-corrected visual acuity was less than 10% in Guangzhou, Kaski, Durban, and Los Angeles, but as high as 23% in Madurai. In multiple logistic regression models, uncorrected near vision impairment was associated with older age (odds ratio [OR] = 1.14, P < .001) and female sex (OR = 1.12, P = .027), but not with educational level (OR = 1.01, P = .812). Over 90% of people in need of near refractive correction in rural settings did not have the necessary spectacles. These rates were 40% in urban settings.
Conclusions
By 50 years of age, the majority of people suffer from near vision impairment, most of which can be corrected optically. Over 90% of those in need of near refractive correction in rural settings do not have the necessary spectacles.
Uncorrected refractive error is increasingly recognized as an important cause of avoidable visual disability worldwide, and has been included as one of the priority conditions in Vision 2020. The World Health Organization (WHO) has also acknowledged that near vision impairment is an important ocular condition affecting quality of life, but it has yet to be included in WHO estimates of diseases burden, in part because of an almost complete lack of scientifically valid, population-based data.
A major cause of loss of near vision in older people is the development of presbyopia, the progressive loss of accommodative amplitude. It has been stated that in human subjects, two-thirds of the accommodation amplitude is lost by the age of 35, and it reaches almost complete loss of accommodation by the age of 50 to 55. This loss of accommodative amplitude with age leads to optically correctable near vision impairment, independent of effects on distance vision, but the impact of loss of accommodation has different effects depending on refractive status. Hyperopic individuals tend to lose near visual acuity earlier, while those with myopia can be protected from near vision impairment. Our interest is in the overall prevalence of near vision impairment, irrespective of whether it is caused by presbyopic changes or has other causes.
The prevalence of near vision impairment, sometimes labeled as presbyopia, has been reported in Tanzania, China, India, and Timor-Leste. Widely varying prevalence rates and spectacle coverage among persons with near vision impairment have been reported, partly attributable to differences in definitions, protocols, measurement conditions, and age groups between studies. These problems hinder a valid comparison of data between areas.
The purpose of the current study was to evaluate the prevalence of near vision impairment (from all causes) among people aged ≥35 years in different settings and ethnic groups using a standardized protocol. Surveys were conducted in China, Nepal, India, South Africa, Niger, and the United States. By enrolling subjects from the age of 35 years, during the early stages of loss of accommodation, the study results will reflect the age-related rise in the prevalence of near vision impairment caused by presbyopia, along with other changes.
Methods
Study Sites and Sampling
The 2 study sites selected in China were representative of very different levels of socioeconomic development in the east coast region. Shunyi district, in the northeast near Beijing, is representative of a rural/semi-rural area with increasing accessibility and affordability of eye care services. Shunyi district had a population of nearly 732 000 in 2009, covering 1019 square kilometers. The sample was drawn from the rural parts of the district. The Yuexiu District of Guangzhou in the south covers an upper-middle-income population within a large urban area, with a population of 416 407 living in 9.16 square kilometers.
The Nepal study was conducted in a rural area 200 kilometers west of Kathmandu in the Kaski district. The study area in Kaski district consists of rural valleys, hills, and mountains with altitudes ranging from 1000 to 8000 meters. Subsistence agriculture is the occupation of the population residing in this area, which is also partially supported by tourism in the city and villages along trekking routes. The total population of the district is 380 527, with an average density of 189 per square kilometer.
The India study was conducted in 2 subdivisions, namely Thirumangalam and Alanganallur in Madurai district, Tamil Nadu. The study sites are 20 to 25 kilometers from Madurai, the nearest large city. The 2 blocks, with a total population of nearly 250 000 (2001 census) had a rural population of 73%, with the remainder in small towns classified as urban in the census. The sample clusters were drawn from both rural and urban populations. The population is predominantly agriculture-based (86% report agriculture as the main work). Population density is around 350 per square kilometer.
The South Africa study was conducted in a semi-urban area, situated 20 km northwest of Durban. The area is predominantly residential and comprises an estimated population of 580 000 in an area that covers 70.1 square kilometers. The population is primarily isiZulu speaking and of African ancestry, accounting for 99% of the total population, with 1% of Indian origin (2001 census). Low income, unemployment, and poverty are characteristic of the area.
The Niger study was conducted in semi-urban wards and rural villages/hamlets within the Dosso Commune of the Dosso Sanitary District. Dosso is located 140 km from Niamey City, the capital of Niger. Based on the 2001 census updated in 2008, the total population of the Dosso Commune is 79 657. The depressed economy is agriculture-based, with limited access to healthcare services.
The study in Los Angeles was conducted in the population-based Los Angeles Latino Eye Study (LALES) cohort. The LALES population was primarily Latinos of Mexican descent residing in six low- to moderate-income census tracts in the urban La Puente area of Los Angeles County, California.
The surveys were carried out on a randomly selected sample of individuals within each study site—except for Los Angeles, where the study was conducted in a sample of previously examined LALES participants. Sampling frames were constructed using geographically defined clusters based on census data. Cluster boundaries were defined such that each cluster would have approximately 100 study participants. A sample size on the order of 2000 for each site was based on estimating the prevalence of near vision impairment within age subgroups, with adjustment for nonparticipation and cluster design effects.
In door-to-door household visits, eligible persons were enumerated by name, sex, age, education (highest level completed), and spectacle usage. Those ≥65 years of age were interviewed in all households, those 50 to 64 were interviewed in every other household (half of households), and those 35 to 49 were interviewed in every fourth household (one-quarter of households). The interviews covered questions on visual functioning and work productivity and an assessment of the burden of their visual disability. The age-based sampling for interviews was used to ensure a reasonably balanced distribution of study subjects across the 3 age categories.
Examinations took place in local clinics and other community facilities, according to prescheduled dates established at the time of enumeration. Those who did not appear at the examination site were revisited by a member of the enumeration team to encourage participation. Written informed consent was obtained at the time of the examination, if not already obtained during the enumeration visit.
Examination
Binocular near visual acuity (VA), both with and without correction for those presenting with bifocals or near vision spectacles, was measured at 40 cm using a logMAR near vision tumbling E chart (Precision Vision, La Salle, Illinois, USA) under ambient lighting. In Dosso, VA was measured outdoors in sunlight, because of unreliable power supply. VA was recorded as the smallest line read with 1 or no errors. Subjects with uncorrected binocular near VA ≤20/40 were progressively tested with increasing plus spheres to obtain best-corrected VA. Those presenting with binocular near VA ≤20/63 that could be improved by 2 or more lines were provided with near vision glasses free of charge.
Data Management and Analysis
Computerized data entry was carried out at each study site using standardized programs. Measurement data ranges, frequency distributions, and consistency among related measurements were checked with data-cleaning programs.
Crude and standardized prevalence rates of near visual acuity 20/40 to 20/63 and <20/63 were calculated using uncorrected and best-corrected binocular VA. In adjusting for the age and sex differences across the 7 sites, the standardization procedure calculated the prevalence rates that would result if each site had an age and sex distribution similar to that of the aggregated sample across all 7 sites. The association of age, sex, and educational level with near vision impairment (uncorrected binocular near VA ≤20/40) was investigated with multiple logistic regression.
The proportion of participants with uncorrected, presenting, and best-corrected near VA ≤20/40 was graphed as a function of age for each site using LOWESS smoothing. The LOWESS procedure imputes smoothed values for age-specific rates using a locally weighted regression of the prevalence of visual impairment on age.
Statistical analyses were performed using Stata/SE Statistical Software: Release 9.0 (Stata Corporation, College Station, Texas, USA). Confidence intervals (CI) and P values (significant at the P ≤ .05 level) were calculated with adjustment for clustering effects associated with the sampling design.
Results
A total of 17 734 persons aged >35 years were enumerated and 14 805 (83.5%) examined, with distributions across age, sex, and education by study site as shown in Table 1 . Not included among the examined are 44 enumerated individuals (0.25%) who came to the examination site but were unable to cooperate with visual acuity testing.
| Sex | Age (y) | Education | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Male | Female | 35–49 | 50–64 | ≥65 | None | <Primary | Primary | Secondary | ≥ High School | No Info. | All | |
| Shunyi | ||||||||||||
| Enumerated, n (%) | 1865 (46.9) | 2112 (53.1) | 1402 (35.3) | 1651 (41.5) | 924 (23.2) | 619 (15.6) | 263 (6.6) | 679 (17.1) | 1928 (48.5) | 377 (9.5) | 111 (2.8) | 3977 (100.0) |
| Examined, n (%) | 1613 (45.4) | 1941 (54.6) | 1200 (33.8) | 1543 (43.4) | 811 (22.8) | 551 (15.5) | 246 (6.9) | 619 (17.4) | 1791 (50.4) | 345 (9.7) | 2 (0.06) | 3554 (100.0) |
| % Examined | 86.5 | 91.9 | 85.6 | 93.5 | 87.8 | 89.0 | 93.5 | 91.2 | 92.9 | 91.5 | 1.8 | 89.4 |
| Guangzhou | ||||||||||||
| Enumerated, n (%) | 1110 (48.6) | 1174 (51.4) | 1095 (47.9) | 747 (32.7) | 442 (19.4) | 33 (1.4) | 77 (3.4) | 155 (6.8) | 426 (18.7) | 1434 (62.8) | 159 (7.0) | 2284 (100.0) |
| Examined, n (%) | 836 (46.0) | 981 (54.0) | 803 (44.2) | 645 (35.5) | 369 (20.3) | 30 (1.7) | 64 (3.5) | 134 (7.4) | 388 (21.4) | 1113 (61.3) | 88 (4.8) | 1817 (100.0) |
| % Examined | 75.3 | 83.6 | 73.3 | 86.4 | 83.5 | 90.9 | 83.1 | 86.5 | 91.1 | 77.6 | 55.4 | 79.6 |
| Kaski | ||||||||||||
| Enumerated, n (%) | 897 (38.0) | 1463 (62.0) | 973 (41.2) | 825 (35.0) | 562 (23.8) | 1524 (64.6) | 203 (8.6) | 290 (12.3) | 85 (3.6) | 232 (9.8) | 26 (1.1) | 2360 (100.0) |
| Examined, n (%) | 814 (37.8) | 1342 (62.2) | 861 (39.9) | 764 (35.4) | 531 (24.6) | 1395 (64.7) | 179 (8.3) | 262 (12.2) | 79 (3.7) | 217 (10.1) | 24 (1.1) | 2156 (100.0) |
| % Examined | 90.8 | 91.7 | 88.5 | 92.6 | 94.5 | 91.5 | 88.2 | 90.3 | 92.9 | 93.5 | 92.3 | 91.4 |
| Madurai | ||||||||||||
| Enumerated, n (%) | 1246 (42.6) | 1676 (57.4) | 1469 (50.3) | 920 (31.5) | 533 (18.2) | 1399 (47.9) | 521 (17.8) | 522 (17.9) | 310 (10.6) | 168 (5.8) | 2 (0.07) | 2922 (100.0) |
| Examined, n (%) | 1068 (40.6) | 1563 (59.4) | 1330 (50.6) | 812 (30.9) | 489 (18.6) | 1263 (48.0) | 478 (18.2) | 467 (17.8) | 278 (10.6) | 143 (5.4) | 2 (0.08) | 2631 (100.0) |
| % Examined | 85.7 | 93.3 | 90.5 | 88.3 | 91.7 | 90.3 | 91.8 | 89.5 | 89.7 | 85.1 | 100.0 | 90.0 |
| Durban | ||||||||||||
| Enumerated, n (%) | 784 (28.4) | 1980 (71.6) | 1380 (49.9) | 985 (35.6) | 399 (14.4) | 151 (5.5) | 872 (31.6) | 750 (27.1) | 389 (14.1) | 251 (9.1) | 351 (12.7) | 2764 (100.0) |
| Examined, n (%) | 482 (24.9) | 1457 (75.1) | 839 (43.3) | 779 (40.2) | 321 (16.6) | 111 (5.7) | 645 (33.3) | 513 (26.5) | 251 (12.9) | 144 (7.4) | 275 (14.2) | 1939 (100.0) |
| % Examined | 61.5 | 73.6 | 60.8 | 79.1 | 80.5 | 73.5 | 74.0 | 68.4 | 64.5 | 57.4 | 78.4 | 70.2 |
| Dosso | ||||||||||||
| Enumerated, n (%) | 1166 (42.2) | 1598 (57.8) | 1524 (55.1) | 796 (28.8) | 444 (16.1) | 1801 (65.2) | 337 (12.2) | 273 (9.9) | 242 (8.8) | 104 (3.8) | 7 (0.25) | 2764 (100.0) |
| Examined, n (%) | 771 (37.7) | 1274 (62.3) | 1141 (55.8) | 596 (29.1) | 308 (15.1) | 1352 (66.1) | 231 (11.3) | 210 (10.3) | 171 (8.4) | 74 (3.6) | 7 (0.34) | 2045 (100.0) |
| % Examined | 66.1 | 79.7 | 74.9 | 74.9 | 69.4 | 75.1 | 66.6 | 76.9 | 70.7 | 71.2 | 100.0 | 74.0 |
| Los Angeles | ||||||||||||
| Enumerated, n (%) a | — | — | — | — | — | — | — | — | — | — | — | |
| Examined, n (%) | 236 (35.6) | 427 (64.4) | 192 (29.0) | 273 (41.2) | 198 (29.9) | 22 (3.3) | 111 (16.7) | 152 (22.9) | 109 (16.4) | 250 (37.7) | 19 (2.9) | 663 (100.0) |
| % Examined | — | — | — | — | — | — | — | — | — | — | — | |
a Participants were obtained from a list of previously examined individuals.
In multiple logistic regression modeling for each site, participation in the examination was associated with older age in Kaski and Durban, female sex at all 7 sites, and higher educational level in Shunyi and Kaski.
Across the 7 sites, the examined population was 39.3% male, ranging from 24.9% in Durban to 46.0% in Guangzhou. The mean age was 53.3 ± 12.6 years, ranging from 49.8 years in Dosso to 57.4 years in Los Angeles. Educational background varied considerably between sites. Overall, nearly one-third of those examined were without formal education, but the site prevalence ranged from 66.1% and 64.7% in Dosso and Kaski to 1.7% and 3.4% in Guangzhou and Los Angeles, respectively. Education at the high school level or higher was reported by 15.9% of subjects, ranging from 64.4% and 38.8% in Guangzhou and Los Angeles to 3.63% and 5.44% in Dosso and Madurai, respectively.
Sex- and age-specific prevalence of uncorrected and best-corrected binocular near visual acuity >20/40, 20/40 to 20/63, and <20/63 is shown for each study site in Table 2 . Generally, half of the population at each site will experience near vision impairment (VA ≤20/40) by the 40- to 49-year age interval, earlier in Madurai and Durban, and approximately half will have near VA <20/63 by their seventies.
| Sex a | Age (y) a | All b | ||||||
|---|---|---|---|---|---|---|---|---|
| Male | Female | 35–39 | 40–49 | 50–59 | 60–69 | 70+ | ||
| Shunyi | ||||||||
| >20/40 | 33.0; 82.8 | 30.2; 78.0 | 97.4; 98.3 | 71.6; 97.8 | 14.1; 91.6 | 4.7; 67.2 | 1.1; 31.0 | 39.8 (38.5,41.0); 81.7 (80.4, 82.9) |
| 20/40-20/63 | 39.1; 13.3 | 38.9; 15.9 | 1.7; 0.86 | 24.5; 1.7 | 57.4; 7.4 | 46.2; 26.6 | 32.3; 46.2 | 34.2 (32.6,35.8); 13.3 (12.1, 14.5) |
| <20/63 | 28.0; 3.9 | 30.9; 6.1 | 0.86; 0.86 | 3.9; 0.52 | 28.5; 0.96 | 49.0; 6.2 | 66.6; 22.9 | 25.8 (24.7,27.0); 4.5 (3.8, 5.1) |
| Guangzhou | ||||||||
| >20/40 | 38.5; 94.0 | 40.2; 89.5 | 84.7; 100. | 58.4; 99.8 | 23.3; 98.5 | 16.1; 89.6 | 6.4; 54.7 | 38.8 (36.9, 40.7); 92.1 (91.0, 93.3) |
| 20/40-20/63 | 45.1; 5.3 | 41.1; 9.0 | 5.5; 0.0 | 35.0; 0.19 | 59.2; 1.4 | 55.2; 9.1 | 55.1; 38.9 | 43.3 (41.2, 45.7); 6.6 (5.5, 7.7) |
| <20/63 | 16.4; 0.72 | 18.8; 1.5 | 9.9; 0.0 | 6.6; 0.0 | 17.5; 0.19 | 28.7; 1.3 | 38.5; 6.4 | 17.4 (15.6, 19.2); 0.9 (0.4, 1.5) |
| Kaski | ||||||||
| >20/40 | 25.1; 90.3 | 37.6; 93.1 | 94.4; 100. | 50.2; 98.6 | 11.4; 98.2 | 8.2; 91.7 | 13.1; 68.0 | 33.9 (32.3, 35.4); 93.6 (92.7, 94.4) |
| 20/40-20/63 | 42.4; 6.9 | 36.9; 3.7 | 5.3; 0.0 | 35.3; 0.54 | 49.7; 0.99 | 50.1; 5.6 | 45.1; 19.7 | 39.1 (37.1, 41.1); 3.7 (3.0, 4.3) |
| <20/63 | 32.6; 2.8 | 25.6; 3.2 | 0.33; 0.0 | 14.6; 0.90 | 38.9; 0.79 | 41.7; 2.7 | 41.9; 12.3 | 26.8 (25.1, 28.6); 2.5 (1.9, 3.1) |
| Madurai | ||||||||
| >20/40 | 16.2; 79.6 | 18.5; 76.2 | 49.0; 95.7 | 11.6; 89.8 | 10.4; 73.5 | 8.9; 54.9 | 5.1; 53.3 | 14.6 (13.3, 15.9); 74.9 (73.1, 76.6) |
| 20/40-20/63 | 67.3; 15.4 | 63.5; 19.3 | 46.1; 3.1 | 78.3; 8.6 | 69.1; 21.7 | 63.2; 35.6 | 54.9; 34.5 | 66.3 (64.5, 68.1); 18.1 (16.5, 19.6) |
| <20/63 | 16.5; 5.0 | 18.0; 4.4 | 4.9; 1.2 | 10.1; 1.6 | 20.5; 4.9 | 28.0; 9.5 | 40.1; 12.2 | 17.4 (15.9, 18.9); 4.8 (3.8, 5.7) |
| Durban | ||||||||
| >20/40 | 15.2; 92.7 | 12.3; 91.4 | 46.7; 93.3 | 16.4; 96.5 | 5.2; 96.0 | 1.5; 87.7 | 3.7; 68.6 | 15.4 (13.7, 17.0); 90.1 (89.0, 91.3) |
| 20/40-20/63 | 55.0; 4.2 | 46.5; 5.7 | 39.6; 4.2 | 52.1; 2.7 | 52.3; 2.8 | 48.1; 8.1 | 39.2; 17.6 | 47.8 (45.4, 50.1); 4.9 (4.0, 5.8) |
| <20/63 | 29.9; 3.1 | 41.2; 3.0 | 13.8; 2.5 | 31.6; 0.84 | 42.5; 1.2 | 50.5; 4.2 | 57.1; 13.8 | 35.4 (33.3, 37.4); 3.1 (2.4, 3.8) |
| Dosso | ||||||||
| >20/40 | 54.5; 90.9 | 59.3; 90.1 | 91.7; 98.8 | 57.5; 97.4 | 46.9; 94.2 | 41.0; 82.0 | 19.3; 51.7 | 49.6 (47.4, 51.8); 87.1 (85.6, 88.5) |
| 20/40-20/63 | 38.3; 5.5 | 34.1; 6.1 | 7.7; 1.2 | 39.6; 2.0 | 48.0; 4.2 | 47.0; 12.0 | 50.2; 24.6 | 41.1 (38.9, 43.3); 7.4 (6.1, 8.7) |
| <20/63 | 7.3; 3.6 | 6.5; 3.8 | 0.61; 0.0 | 2.9; 0.62 | 5.1; 1.6 | 12.0; 6.0 | 30.4; 23.7 | 7.6 (6.3, 8.9); 4.0 (3.0, 4.9) |
| Los Angeles | ||||||||
| >20/40 | 32.2; 95.7 | 26.0; 95.8 | 92.9; 98.6 | 50.8; 99.2 | 13.3; 98.3 | 14.1; 98.1 | 10.5; 85.1 | 35.3 (32.5, 38.0); 96.4 (95.2, 97.6) |
| 20/40-20/63 | 39.0; 3.8 | 34.4; 3.5 | 2.9; 1.4 | 37.7; 0.82 | 44.8; 1.7 | 37.8; 1.3 | 38.1; 12.7 | 35.2 (31.9, 38.6); 2.4 (1.4, 3.4) |
| <20/63 | 28.8; 0.43 | 39.6; 0.70 | 4.3; 0.0 | 11.5; 0.0 | 42.0; 0.0 | 48.1; 0.64 | 51.5; 2.2 | 29.0 (25.9, 32.1); 0.3 (0.0, 0.8) |
a Data given as % uncorrected visual acuity; best-corrected visual acuity. Best-corrected visual acuity was not available for 16 participants in Shunyi, 15 in Madurai, 8 in Durban, and 1 in Los Angeles.
b Standardized age- and sex-adjusted prevalence (95% confidence interval): uncorrected visual acuity; best-corrected visual acuity.
The standardized age- and sex-adjusted prevalence of uncorrected and best-corrected VA is also shown in Table 2 .
In multiple logistic regression modeling, uncorrected near VA ≤20/40 was associated with older age in all study sites ( Table 3 ). Female sex was significantly associated with near vision impairment in Los Angeles, while in Kaski female subjects had significantly less impairment. Lower educational level was associated with near vision impairment in Kaski, Durban, and Los Angeles; in Dosso, those with less education had less impairment.
| Study Site | Uncorrected Visual Acuity ≤20/40 | ||
|---|---|---|---|
| Older Age | Female Sex | Lower Education Level | |
| Shunyi | 1.30 (1.22–1.39) | 1.26 (0.97–1.63) | 1.08 (0.95–1.23) |
| P < .001 | P = .078 | P = .225 | |
| Guangzhou | 1.13 (1.10–1.16) | 0.93 (0.78–1.10) | 1.09 (0.92–1.30) |
| P < .001 | P = .341 | P = .288 | |
| Kaski | 1.13 (1.10–1.16) | 0.72 (0.53–0.98) | 1.11 (1.05–1.18) |
| P < .001 | P = .038 | P = .001 | |
| Madurai | 1.09 (1.07–1.11) | 1.11 (0.88–1.39) | 0.96 (0.87–1.07) |
| P < .001 | P = .375 | P = .451 | |
| Durban | 1.16 (1.12–1.20) | 1.52 (0.92–2.51) | 1.16 (1.01–1.33) |
| P < .001 | P = .096 | P = .039 | |
| Dosso | 1.09 (1.08–1.10) | 1.24 (0.98–1.57) | 0.72 (0.64–0.81) |
| P < .001 | P = .069 | P < .001 | |
| Los Angeles | 1.12 (1.06–1.19) | 2.07 (1.19–3.61) | 1.20 (1.04–1.38) |
| P = .004 | P = .022 | P = .023 | |
| All sites | 1.14 (1.13–1.15) | 1.12 (1.01–1.23) | 1.01 (0.96–1.06) |
| P < .001 | P = .027 | P = .812 | |
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