Purpose
To evaluate disparities in access to vision care among US-born and foreign-born adults and children in the United States, with particular attention to duration of US residence and language spoken with healthcare providers.
Design
Retrospective cohort study.
Subjects
US-born and foreign-born adults and children participating in the 2023 National Health Interview Survey.
Methods
Data from the 2023 National Health Interview Survey were analyzed using survey-weighted methods. Outcomes included delayed medical care due to cost or transportation, receipt of an eye examination, vision testing history among children, and self- or parent-reported vision difficulty. Multivariable logistic regression models estimated adjusted odds ratios (aORs) and 95% confidence intervals (CIs), adjusting for sociodemographic characteristics and insurance status. Among foreign-born adults, analyses were further stratified by years lived in the United States and language spoken with healthcare providers.
Main Outcome Measures
Delayed medical care due to cost or transportation, receipt of an eye examination in the past 12 months, lifetime vision testing among children, and vision-related functional outcomes.
Results
Among 27,822 adults, foreign-born individuals had lower adjusted odds of receiving an eye examination in the past 12 months compared with US-born adults (aOR 0.91; 95% CI 0.84-0.98). Among foreign-born adults, use of a non-English language with healthcare providers was associated with lower odds of recent eye examination (aOR 0.66; 95% CI 0.53-0.83). Cost-related delays to care were more common in unadjusted analyses among foreign-born adults but attenuated after adjustment. Among 6615 children, those from foreign-born households had significantly lower odds of ever having undergone vision testing (aOR 0.50; 95% CI 0.36-0.69) and lower odds of receiving an eye examination in the past year (aOR 0.74; 95% CI 0.57-0.96).
Conclusions
The 2023 NHIS data identified possible disparities in access to preventive vision care for both immigrant adults and children. Language barriers and insurance-related factors primarily affected adults, whereas reduced exposure to preventive screening appeared to contribute to disparities among children. Targeted, age-specific strategies could potentially promote equitable access to vision care in immigrant populations.
INTRODUCTION
Visual impairment remains a significant public health concern in the United States, with substantial implications for quality of life, educational attainment, and long-term health outcomes. ,,, Access to timely preventive vision screening and eye care is critical for early detection and intervention, yet disparities in utilization persist across sociodemographic groups. These inequities disproportionately affect individuals from lower socioeconomic backgrounds, racial and ethnic minority populations, and immigrant communities, where structural barriers may limit engagement with routine eye care.
Among adults, gaps in vision care utilization have been consistently documented, particularly among those at elevated risk for vision loss. Despite clinical guidelines recommending periodic eye examinations, many adults do not receive preventive care, often due to lack of insurance, interruptions in coverage, or financial constraints. Variation in state-level Medicaid coverage for routine vision services further contributes to unequal access across regions. Language barriers represent an additional and independent obstacle: adults with limited English proficiency (LEP) experience greater difficulty navigating the health system and lower utilization of preventive services, including eye care. ,
For children, early identification of visual disorders is especially important, as many causes of visual impairment are amenable to treatment when detected during critical developmental periods. ,, However, pediatric vision care access remains uneven. ,, Children from low-income households and those experiencing insurance instability have higher odds of unmet vision care needs, and access to preventive services is strongly influenced by the availability and effectiveness of school-based vision screening programs. ,, Disruptions to these programs, particularly during the COVID-19 pandemic, have been associated with declines in pediatric vision screening and follow-up, potentially exacerbating existing disparities.
Immigrant families may face overlapping barriers that affect both adult and pediatric access to vision care. Prior national analyses suggest that immigrant adults are less likely to utilize optometry services and that children in immigrant households are less likely to receive recommended vision screening. , However, limited contemporary evidence has examined how these disparities differ between adults and children, or how duration of US residence and language use with healthcare providers shape access to preventive eye care. Using data from the 2023 National Health Interview Survey, this study evaluates nativity-based disparities in vision care access among US-born and foreign-born adults and children, with the goal of clarifying age-specific mechanisms underlying immigrant vision care disparities.
METHODS
Data were obtained from the 2023 National Health Interview Survey (NHIS), an annual, nationally representative survey of the civilian, noninstitutionalized US population conducted by the National Center for Health Statistics. NHIS employs a multistage probability sampling design incorporating clustering, stratification, and unequal selection probabilities. Public-use files contain no personally identifiable information; therefore, this study was considered exempt from institutional review board review as determined by the Florida State University Office for Human Subjects Protection. The study was adherent to the tenets in the Declaration of Helsinki.
The analytic sample included 29,522 adults and 7692 children. Adults missing nativity or required survey design variables were excluded. Children missing nativity were excluded, and the “ever had a vision test” outcome was restricted to those aged ≥5 years because younger children were not asked this item. Because NHIS collects outcomes and covariates on different subsamples with varying item-level completeness, analytic sample sizes differed across models. Exact denominators for each outcome are reported in Tables 1 to 6 . Figures 1 and 2 demonstrate the inclusion process used for the analytic sample.
TABLE 1
Adult Participant Characteristics by Nativity
| Characteristics | Category | Total Adults ( n ) | US-Born ( n ) | Foreign-Born ( n ) | US-Born (%) | Foreign-Born (%) | P Value | |
|---|---|---|---|---|---|---|---|---|
| Demographics | Sex | Male | 12,923 | 10,801 | 2122 | 49.3 | 47.4 | .13 |
| Female | 15,360 | 12,781 | 2579 | 50.7 | 52.6 | |||
| Missing | 5 | 4 | 1 | 0 | 0 | |||
| Race/ethnicity | Non-Hispanic White | 18,851 | 17,881 | 970 | 73 | 17.4 | – | |
| Non-Hispanic Black | 2979 | 2585 | 394 | 12 | 9.2 | |||
| Hispanic | 4199 | 2124 | 2075 | 10.4 | 47.4 | |||
| Non-Hispanic Asian | 187 | 183 | 4 | 0.7 | 0.1 | |||
| Non-Hispanic Other/Multiple | 2072 | 813 | 1259 | 3.9 | 25.9 | |||
| Socioeconomic characteristics | Education | Less than HS | 2395 | 1498 | 897 | 7.4 | 23.1 | – |
| HS/GED | 7132 | 6130 | 1002 | 27.5 | 23.1 | |||
| Some college/AA | 7842 | 7016 | 826 | 31.8 | 18.7 | |||
| Bachelor’s degree | 6561 | 5472 | 1089 | 20.7 | 19.9 | |||
| >Bachelor’s degree | 4234 | 3380 | 854 | 12.2 | 14.3 | |||
| Missing | 124 | 90 | 34 | 0.5 | 1 | |||
| Poverty ratio | <0.50 | 811 | 619 | 192 | 2.6 | 4.1 | <.001 | |
| 0.50-<1.00 | 875 | 667 | 208 | 2.7 | 4 | |||
| 1.00-<1.25 | 1239 | 940 | 299 | 3.5 | 6.4 | |||
| 1.25-<1.50 | 1092 | 834 | 258 | 3.3 | 5.9 | |||
| 1.50-<2.00 | 1465 | 1152 | 313 | 4.7 | 7.4 | |||
| 2.00-<3.00 | 1229 | 997 | 232 | 4.2 | 5.8 | |||
| 3.00-<4.00 | 1365 | 1121 | 244 | 4.3 | 5.5 | |||
| 4.00-<5.00 | 2359 | 1971 | 388 | 8.2 | 9.1 | |||
| >5.00 | 2451 | 2082 | 369 | 8.9 | 8 | |||
| Not reported | 1924 | 1655 | 269 | 7.4 | 6 | |||
| Missing | 13,478 | 11,548 | 1930 | 50.2 | 37.7 | |||
| Region | Northeast | 4334 | 3535 | 799 | 16.5 | 19.5 | – | |
| Midwest | 6250 | 5731 | 519 | 23.2 | 10.3 | |||
| South | 10,516 | 8847 | 1669 | 39 | 36.4 | |||
| West | 7188 | 5473 | 1715 | 21.4 | 33.7 | |||
| Insurance status | Insured | 26,299 | 22,368 | 3931 | 93.8 | 80.9 | <.001 | |
| Uninsured | 1918 | 1161 | 757 | 5.9 | 18.7 | |||
| Missing | 71 | 57 | 14 | 0.4 | 0.3 | |||
| Private insurance | Yes | 17,371 | 14,783 | 2588 | 65.2 | 53.7 | <.001 | |
| No | 10,812 | 8715 | 2097 | 34.3 | 45.9 | |||
| Missing | 105 | 88 | 17 | 0.5 | 0.4 | |||
| Medicaid | Yes | 3631 | 2877 | 754 | 13.9 | 17.1 | <.001 | |
| No | 24,588 | 20,648 | 3940 | 85.8 | 82.7 | |||
| Missing | 69 | 61 | 8 | 0.3 | 0.2 | |||
| Medicare | Yes | 9688 | 8650 | 1038 | 25.9 | 17.4 | <.001 | |
| No | 18,518 | 14,870 | 3648 | 73.7 | 82.2 | |||
| Missing | 82 | 66 | 16 | 0.4 | 0.4 | |||
| Vision-only SSP | Yes | 7802 | 6693 | 1109 | 30 | 21.7 | <.001 | |
| No | 20,181 | 16,622 | 3559 | 68.6 | 77.5 | |||
| Missing | 305 | 271 | 34 | 1.4 | 0.8 | |||
| Barriers to care | Language at doctor | English | 2926 | 1249 | 1677 | 6.7 | 34.3 | – |
| Non-English | 1105 | 81 | 1024 | 0.4 | 25 | |||
| Missing | 24,257 | 22,256 | 2001 | 92.9 | 40.7 | |||
| Delay care due to no reliable transportation (<12 mo) | Yes | 1934 | 1603 | 331 | 6.6 | 7 | .031 | |
| No | 26,160 | 21,842 | 4318 | 92.6 | 91.8 | |||
| Missing | 194 | 141 | 53 | 0.7 | 1.2 | |||
| Delay medical care due to cost (<12 mo) | Yes | 1864 | 1507 | 357 | 6.9 | 8.3 | .023 | |
| No | 26,409 | 22,067 | 4342 | 93 | 91.6 | |||
| Missing | 15 | 12 | 3 | 0.1 | 0.1 | |||
| Unmet medical need due to cost (<12 mo) | Yes | 1658 | 1300 | 358 | 5.9 | 8.4 | <.001 | |
| No | 26,614 | 22,276 | 4338 | 94.1 | 91.5 | |||
| Missing | 16 | 10 | 6 | 0 | 0.1 | |||
| Vision outcomes | Eye exam (<12 mo) | Yes | 15,944 | 13,570 | 2374 | 54.1 | 48 | <.001 |
| No | 12,316 | 9991 | 2325 | 45.8 | 52 | |||
| Missing | 28 | 25 | 3 | 0.1 | 0.1 | |||
| Vision difficulty | No difficulty | 22,735 | 18,753 | 3982 | 80.4 | 84 | <.001 | |
| Any difficulty | 5546 | 4827 | 719 | 19.6 | 16 | |||
| Missing | 7 | 6 | 1 | 0 | 0 | |||
| Wears glasses/contact lenses | Yes | 19,098 | 16,382 | 2716 | 65.5 | 53.6 | <.001 | |
| No | 9189 | 7203 | 1986 | 34.5 | 46.4 | |||
| Missing | 1 | 1 | 0 | 0 | 0 | |||
| Nativity | Nativity | US-born | 23,586 | 23,586 | 0 | – | – | – |
| Foreign-born | 4702 | 0 | 4702 | – | – | |||
| Years in the US (foreign-born) | <1 | – | – | 49 | – | 1.1 | – | |
| 1-<5 | – | – | 348 | – | 8.3 | |||
| 5-<10 | – | – | 499 | – | 11.2 | |||
| 10-<15 | – | – | 373 | – | 8.4 | |||
| >15 | – | – | 3305 | – | 68.1 | |||
| Unknown | – | – | 128 | – | 2.8 | |||
| Weighted mean age (y): All adults: 48.2 (SD 18.6); US-born: 48.1 (SD 19.2); foreign-born: 48.7 (SD 16.3); P value =.10 | ||||||||
Percentages represent survey-weighted column percentages unless otherwise specified. P values were calculated using survey-weighted chi-square tests for categorical variables and survey-weighted t tests for continuous variables. Language spoken with a healthcare provider was assessed only among respondents who reported seeing a healthcare provider in the past 12 months. Missing values are shown where applicable and were excluded from percentage calculations. Years in the United States are reported for foreign-born participants only. All analyses account for the complex sampling design of the NHIS.
GED = General Educational Development; HS = high school; NHIS = National Health Interview Survey; SD = standard deviation; SSP = supplemental security plan.
STROBE flow diagram for adult analytic sample.
