Life Stage Differences in Vision Difficulty and Receipt of a Past-Year Eye Examination Among Midlife and Older Adults: Analysis of a National Sample

Abstract

Objectives:

We examined the association between self-reported vision difficulty and receipt of an annual eye examination among US adults aged ≥45 years and assessed differences by age.

Methods:

We used 2022 and 2023 National Health Interview Survey data for 34 350 adults aged ≥45 years. The outcome was self-reported eye examination in the past year, and the key independent variable was self-reported vision difficulty. We used multivariable logistic regression with an interaction term to assess whether associations varied by age group (45-64 vs ≥65 y). We estimated predicted probabilities from fully adjusted models.

Results:

Adults with vision difficulty (vs adults without vision difficulty) were more likely to be female, have lower educational attainment, have lower income, and report more chronic conditions (P < .001). Among adults aged 45 to 64 years, vision difficulty was associated with a lower probability of receiving a past-year eye examination (50.3% vs 57.7%; 7.4 percentage points; P < .001). Among adults aged ≥65 years, the gap was smaller (68.8% vs 70.1%; 1.3 percentage points; P < .001). Gaps in a past-year eye examination were greater among midlife adults than among older adults (P < .001).

Conclusions:

Self-reported vision difficulty is not consistently linked to receiving routine eye examinations, especially during midlife, when structural, financial, and behavioral barriers converge. Public health strategies should address the factors underlying the age differences, reduce barriers to care, and integrate vision care into routine preventive health services to improve vision health and reduce the risk of vision loss.

Keywords

self-reported vision difficulty eye examination aging midlife adults older adults preventive care services

With the aging population, the absolute number of adults affected by vision impairment is expected to rise, increasing the population-level burden and public health relevance of vision loss.¹ Vision impairment contributes to diminished quality of life, reduced independence, and increased risk of injury.^2-9 Vision impairment is associated with a wide range of adverse outcomes, including an increased risk of falls, cognitive decline, and disability.^10-12 Early detection through regular eye examinations is one of the most effective strategies for preventing avoidable vision loss, especially as the US population ages and the prevalence of vision impairment is expected to increase.^13,14 However, substantial gaps in the receipt of an eye care examination remain, highlighting ongoing missed opportunities for preventing vision loss.¹

Clinical guidelines from national organizations recommend regular eye examinations, particularly for adults with chronic health conditions, diabetes, or vision concerns.^15,16 However, population-level data show that a substantial proportion of adults, including those at elevated risk for vision loss, do not adhere to the recommended guidelines.^1,17 Prior research has focused on structural barriers such as cost, health insurance coverage, and health care provider accessibility.^1,17 Less attention has been given to behavioral drivers related to seeking care, particularly how individuals’ assessment of their own vision is associated with the likelihood of receiving routine eye examinations, and whether this perception differs by age group.

Self-reported vision difficulty may be a key indicator of unmet vision needs. Vision difficulty reflects perceived functional impairment and may imply where public health systems are missing chances to connect individuals to timely care and prevention. Self-reported vision difficulty is already widely used in public health surveillance as a practical, scalable proxy for functional vision impairment.¹⁸ Therefore, understanding how it relates to receiving routine eye care examinations could inform strategies for patient education, health care provider communication, and clinical care coordination. Insights into these patterns may also guide public health messaging and improve the integration of patient-reported vision concerns into clinical workflows.

Differences examined across the life course further underscore the need to consider age when examining these associations. Middle-aged adults begin to experience early signs of visual decline but may underuse preventive care because of competing work and caregiving demands, limited vision coverage, and low perceived urgency.^17,19 Identifying unmet needs in this group is especially important because midlife represents a window for prevention before impairments progress. In contrast, older adults may have more frequent interactions with health care providers, better access to vision care through Medicare, and increased awareness of the importance of regular eye examinations. Such age differences may be reflected in how vision difficulty is associated with care-seeking behavior. Although prior studies have examined the predictors of having an eye examination,^1,20 few studies have directly examined whether the association between perceived vision difficulty and having an eye examination differs by age group after adjusting for sociodemographic and health factors.

To address these gaps, this study used nationally representative data from the National Health Interview Survey (NHIS) to (1) examine the association between self-reported vision difficulty and receipt of a past-year eye examination among adults aged ≥45 years and (2) examine whether this association differed between middle-aged (45-64 y) and older (≥65 y) adults. By identifying age-specific patterns in perceived vision difficulty and receipt of routine eye examinations, this study sought to inform clinical and policy strategies designed to identify groups vulnerable to vision loss, improve access to preventive vision services, and reduce avoidable vision loss among adults.

Methods

Study Design and Data Source

This cross-sectional study used data from the 2022 and 2023 NHIS, a nationally representative survey of the noninstitutionalized US civilian population. NHIS collects detailed information on health status, health behaviors, access to care, and sociodemographic characteristics through in-person and telephone interviews.²¹ The NHIS uses a complex multistage area probability sampling design to allow for nationally representative estimates. Response rates were 47.7% in 2022 and 47.0% in 2023. The University of Georgia Institutional Review Board (IRB ID: PROJECT00012391) reviewed this study and considered it exempt from IRB review because the study analyzed deidentified, publicly available NHIS data.

Study Population

The analytic sample included adults aged ≥45 years (n = 36 364) who had complete information on self-reported vision difficulty and whether they had received an eye examination in the past 12 months (n = 35 698). Individuals were excluded if they had missing responses on covariates, including age, sex, race and ethnicity, health insurance status, education, annual household income, and indicators of chronic conditions (n = 34 350). After applying the NHIS survey weights, the final analytic sample was estimated to represent approximately 131 million US adults aged ≥45 years.

Variables

The primary outcome was self-reported receipt of an eye examination in the past 12 months. We assessed this outcome using the question: “During the past 12 months, have you had an eye exam from an eye specialist such as an optometrist, ophthalmologist, or eye doctor?” We dichotomized responses as yes or no. The main independent variable was self-reported vision difficulty, measured by using the question, “Do you have difficulty seeing, even when wearing glasses or contact lenses?” Responses were grouped into 2 categories: yes (any difficulty: some difficulty, a lot of difficulty, cannot at all) and no (no difficulty). We included age group as a modifier and categorized it into 2 groups: midlife adults (aged 45-64 y) and older adults (aged ≥65 y).

We selected covariates based on Andersen’s Behavioral Model of Health Services Use,²² which conceptualizes health care use as a function of predisposing, enabling, and need-based factors. Predisposing factors included sex (male or female), race and ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, or non-Hispanic other), marital status (single vs married/partnered), and educational attainment (<high school diploma, high school diploma or equivalent, or >high school diploma). Enabling factors were type of health insurance (private, public, other, or uninsured), annual household income as a percentage of the federal poverty level (FPL) (<200%, 200%-399%, or ≥400% FPL), and having a usual source of general health care (yes/no). Additional enabling variables included region of residence (Northeast, Midwest, South, West), urbanicity (large central metropolitan, large fringe metropolitan, medium/small metropolitan, nonmetropolitan), and whether the individual reported delaying needed medical care because of cost in the past 12 months. Need-based factors included self-reported functional limitation and the presence of chronic conditions, including arthritis, asthma, cancer, chronic obstructive pulmonary disease, dementia, diabetes, heart disease, high cholesterol, hypertension, and stroke. We also included survey year as a control variable to account for temporal variation.

Statistical Analysis

To explore age-specific differences, we stratified descriptive statistics by age group and examined the distribution of baseline characteristics by vision difficulty and receipt of an eye examination in the past 12 months. To assess the association between self-reported vision health and receipt of an eye examination in the past year, we used multivariable logistic regression models adjusting for covariates guided by Andersen’s Behavioral Model.²³ To evaluate whether this association varied by age group, we included an interaction term between age group and vision difficulty. Based on the fully adjusted model, we also estimated the predicted probabilities of receipt of an annual eye examination by vision difficulty and age group. To assess the robustness of our findings, we conducted 2 sensitivity analyses. First, we reestimated the multivariable logistic regression models using the unweighted analytic sample to examine whether the results were sensitive to the application of survey weights. Second, we performed a restricted subgroup analysis that focused on adults who reported no vision difficulty or only some vision difficulty, thereby excluding those with more severe self-reported vision problems, because individuals reporting more severe self-reported vision problems comprised a small proportion of the sample and may not reflect the typical challenges faced by the general population. All analyses accounted for the complex sampling design of NHIS, applying survey weights, strata, and primary sampling units to produce nationally representative estimates. We performed statistical analyses using R version 4.4.3 (R Core Team).

Results

Vision difficulty was reported by 16.7% of midlife adults and 23.2% of older adults. In both age groups, those who did not receive an eye examination in the past year tended to have lower educational attainment, were more likely to be uninsured or have public health insurance, and were less likely to report a usual source of care (Tables 1 and 2).

Table 1.

Characteristics of the weighted sample of adults aged 45 to 64 years, by vision difficulty and receipt of a past-year eye examination, National Health Interview Survey, 2022-2023^a

Characteristic	Overall	Vision difficulty				P value^b
		No		Yes
		Received past-year eye examination		Received past-year eye examination
		No	Yes	No	Yes
Weighted no.	72 785 256	23 699 789	32 370 117	8 309 835	8 405 515
Biological sex, %						<.001
Female	50.8	43.6	54.3	49.2	59.0
Male	49.2	56.4	45.7	50.8	41.0
Race and ethnicity, %						<.001
Non-Hispanic White	63.6	60.5	65.8	65.6	62.1
Non-Hispanic Black	11.4	11.0	11.4	11.7	12.4
Hispanic or Latino	16.7	20.1	14.0	17.5	17.0
Non-Hispanic Other^c	8.2	8.4	8.8	5.2	8.5
Marital status, %						<.001
Single	28.4	30.0	24.8	34.4	31.6
Married/partnered	71.6	70.0	65.2	65.6	68.4
Education level, %						<.001
<High school diploma	11.2	14.3	7.1	16.3	13.3
High school diploma or equivalent	25.5	28.5	21.8	31.0	25.4
>High school diploma	63.3	57.2	71.1	52.7	61.3
Health insurance, %						<.001
Private	73.0	69.1	80.9	59.5	66.5
Public	12.2	12.0	9.0	17.7	19.2
Other^d	6.1	4.9	5.6	9.0	8.2
None	8.8	14.0	4.4	13.7	6.1
Family income, % FPL						<.001
<200	23.1	26.6	15.7	35.6	29.4
200-399	25.6	27.3	22.9	29.0	27.8
≥400	51.3	46.0	61.4	35.4	42.7
Usual source of care, %						<.001
No	7.3	11.7	3.6	12.1	4.3
Yes	92.7	88.3	96.4	87.9	95.7
Region of residence, %						<.001
Northeast	17.3	17.1	19.4	12.3	14.3
Midwest	20.7	19.9	20.9	20.5	22.2
South	38.9	38.4	37.6	44.3	40.3
West	23.1	24.6	22.1	22.9	23.2
Urbanicity, %						<.001
Large central metropolitan	29.6	30.3	30.2	25.7	29.4
Large fringe metropolitan	26.4	25.1	28.0	25.2	25.0
Medium/small metropolitan	29.2	29.6	28.6	30.0	29.4
Nonmetropolitan	14.8	14.9	13.2	19.2	16.1
Delayed medical care due to cost, %						<.001
Yes	7.9	7.8	4.6	6.3	11.4
No	92.1	92.2	95.4	82.7	88.6
Functional limitation, %						<.001
Yes	20.0	14.1	15.6	35.3	38.9
No	80.0	85.9	84.4	64.7	61.1
Chronic conditions, %
Arthritis	24.9	19.8	23.3	34.0	36.0	<.001
Asthma	13.7	11.2	13.4	16.7	18.9	<.001
Cancer	9.2	6.9	10.2	10.4	11.0	<.001
COPD	5.1	4.2	3.5	10.7	7.8	<.001
Dementia	0.3	0.3	0.2	0.5	1.0	<.001
Diabetes	12.2	6.9	13.3	12.1	23.2	<.001
Heart disease	4.0	3.1	3.6	5.7	6.6	<.001
High cholesterol	35.3	28.5	36.2	38.8	47.7	<.001
Hypertension	39.1	35.6	38.0	42.8	49.7	<.001
Stroke	2.8	2.2	2.1	5.0	5.3	<.001
Year, %						.09
2022	49.8	48.7	50.4	48.1	51.9
2023	50.2	51.3	49.6	51.9	48.1

Abbreviations: COPD, chronic obstructive pulmonary disease; FPL, federal poverty level.

Data source: National Health Interview Survey.³³

Survey-weighted Rao-Scott χ² tests were used to assess differences across groups, with 2-sided P < .05 considered statistically significant.

Includes non-Hispanic Asian only, non-Hispanic American Indian or Alaska Native (AI/AN) only, non-Hispanic AI/AN and any other group, other single, and multiple races.

Other coverage includes military, other government, or public insurance not classified in the primary health insurance categories.

Table 2.

Characteristics of the weighted sample of adults aged ≥65 years, by vision difficulty and receipt of a past-year eye examination, National Health Interview Survey, 2022-2023^a

Characteristic	Overall	Vision difficulty				P value^b
		No		Yes
		Received past-year eye examination		Received past-year eye examination
		No	Yes	No	Yes
Weighted no.	57 751 247	13 288 319	31 108 690	4 165 926	9 188 311
Biological sex, %						<.001
Female	54.3	49.7	55.3	51.4	58.8
Male	45.7	50.3	44.7	48.5	41.2
Race and ethnicity, %						<.001
Non-Hispanic White	75.2	71.4	77.6	72.5	74.0
Non-Hispanic Black	9.1	10.2	8.3	10.3	10.0
Hispanic or Latino	9.4	10.5	8.3	11.8	10.4
Non-Hispanic Other^c	6.2	7.9	5.8	5.4	5.5
Marital status, %						<.001
Single	39.3	41.3	35.5	50.9	43.7
Married/partnered	60.7	58.7	64.5	49.1	56.3
Education level, %						<.001
<High school diploma	12.8	15.4	9.4	23.8	15.5
High school diploma or equivalent	28.3	31.0	26.7	30.3	29.0
>High school diploma	58.9	53.6	63.9	45.9	55.5
Health insurance, %						<.001
Private	37.7	36.0	40.3	29.6	34.9
Public	52.5	53.0	50.7	57.6	55.7
Other^d	8.7	8.6	8.6	9.8	9.0
None	1.1	2.3	0.5	3.0	0.3
Family income, % FPL						<.001
<200	28.5	35.0	22.7	44.1	31.4
200-399	32.8	32.0	33.0	31.9	33.6
≥400	38.8	33.0	44.3	24.0	35.0
Usual source of care, %						<.001
No	2.8	5.9	1.5	6.0	1.5
Yes	97.2	94.1	98.5	94.0	98.5
Region of residence, %						<.001
Northeast	18.3	17.8	19.3	11.9	18.2
Midwest	21.8	20.8	22.7	20.1	20.7
South	37.5	37.1	36.3	44.8	38.5
West	22.5	24.2	21.6	23.2	22.5
Urbanicity, %						.02
Large central metropolitan	26.2	27.2	25.6	25.0	27.1
Large fringe metropolitan	24.3	23.8	25.4	21.6	22.8
Medium/small metropolitan	32.5	31.7	32.7	32.8	32.8
Nonmetropolitan	17.0	17.3	16.4	20.6	17.2
Delayed medical care due to cost, %						<.001
Yes	2.8	3.4	1.4	8.1	4.2
No	97.2	96.6	98.6	91.9	95.8
Functional limitation, %						<.001
Yes	40.2	35.5	34.0	61.7	58.0
No	59.8	64.5	66.0	38.3	42.0
Chronic conditions, %
Arthritis	47.1	40.3	46.2	52.1	57.5	<.001
Asthma	12.1	10.0	11.8	14.7	15.0	<.001
Cancer	25.3	20.9	26.3	23.0	29.3	<.001
COPD	9.5	8.9	7.5	17.1	13.4	<.001
Dementia	3.6	3.6	2.3	6.9	6.5	<.001
Diabetes	20.0	13.2	20.7	21.9	26.4	<.001
Heart disease	14.5	12.1	13.4	19.0	19.5	<.001
High cholesterol	53.2	45.8	54.4	54.6	58.9	<.001
Hypertension	61.2	56.2	60.6	65.6	68.7	<.001
Stroke	7.4	6.6	6.2	12.5	10.2	<.001
Year, %						.01
2022	50.6	49.2	51.4	46.8	51.7
2023	49.4	50.8	48.6	53.2	48.3

Abbreviations: COPD, chronic obstructive pulmonary disease; FPL, federal poverty level.

Data source: National Health Interview Survey.³³

Survey-weighted Rao-Scott χ² tests were used to assess differences across groups, with 2-sided P < .05 considered statistically significant.

Includes non-Hispanic Asian only, non-Hispanic American Indian or Alaska Native (AI/AN) only, non-Hispanic AI/AN and any other group, other single, and multiple races.

Other coverage includes military, other government, or public insurance not classified in the primary health insurance categories.

In addition, among adults aged 45 to 64 years with vision difficulty (Table 1), those who did not receive an eye examination in the past year had higher rates of delayed care because of cost (17.3% vs 11.4%) and lower rates of private health insurance (59.5% vs 66.5%) than those who did receive an eye examination in the past year. Chronic conditions such as diabetes (12.1% vs 23.2%), hypertension (42.8% vs 49.7%), and arthritis (34.0% vs 36.0%) were also more common among those who received an eye examination in the past year than among those who did not. We observed a similar pattern among adults aged ≥65 years (Table 2), particularly among those with vision difficulty. Those who did not receive an eye examination in the past year were more likely to have lower income (<200% FPL: 44.1% vs 31.4%), lower educational attainment (<high school diploma: 23.8% vs 15.5%), no usual source of care (6.0% vs 1.5%), and greater functional limitations (61.7% vs 58.0%) than those who received an eye examination in the past year. Chronic conditions such as diabetes (21.9% vs 26.4%), hypertension (65.6% vs 68.7%), and arthritis (52.1% vs 57.5%) were more prevalent among those who received an eye examination in the past year than among those who did not.

In model 1, which adjusted for predisposing, enabling, and need factors, both vision difficulty and age group were independently associated with receipt of an eye examination in the past year (eTable 1 in the Supplement). Adults with vision difficulty had significantly lower odds of having an eye examination in the past year than those without vision difficulty (odds ratio [OR] = 0.87; 95% CI, 0.82-0.92; P < .001). Similarly, adults aged 45 to 64 years had significantly lower odds of receiving an eye examination in the past year than adults aged ≥65 years (OR = 0.62; 95% CI, 0.58-0.65; P < .001). Model 2 added an interaction term between vision difficulty and age group. In this model, the age group difference remained significant (OR for age 45-64 y = 0.65; 95% CI, 0.62-0.70; P < .001), and vision difficulty was no longer significant (OR = 0.99; 95% CI, 0.91-1.07; P = .72), indicating no difference in the odds of receiving an eye examination in the past year by vision status among adults aged ≥65 years. However, the interaction term (OR = 0.77; 95% CI, 0.69-0.86; P < .001) suggests that the odds of receiving an eye examination in the past year were 22% lower among adults aged 45 to 64 years with vision difficulty than among adults aged ≥65 years with vision difficulty.

Among adults aged 45 to 64 years, those with vision difficulty had a significantly lower predicted probability of receiving an eye examination in the past year than those without vision difficulty (50.3% vs 57.7%; Figure), an absolute difference of 7.4 percentage points (P < .001). Among adults aged ≥65 years, the difference was smaller (68.8% vs 70.1%), an absolute difference of 1.3 percentage points (P < .001). The difference in predicted probability of receiving an eye examination in the past year between those with and without vision difficulty was significantly greater among adults aged 45 to 64 years than among adults aged ≥65 years (difference-in-differences = −6.2 percentage points; P < .001). Results of the sensitivity analyses were similar to those in the main analyses (eTable 2 in the Supplement, eFigure 1 and eFigure 2 in the Supplement).

Figure.

Predicted probability of receipt of a past-year eye examination among adults aged ≥45 years, by vision difficulty and age group, National Health Interview Survey, 2022-2023. Predicted probabilities were calculated based on the logistic regression model adjusted for sex, race and ethnicity, marital status, education level, health insurance type, household income-to-poverty ratio, usual source of care, region, urbanicity, delayed care due to cost, functional limitations, chronic conditions, and year. The difference in receipt of a past-year eye examination between those with and without vision difficulty was significantly larger among adults aged 45 to 64 years (50.3% vs 57.7%; P < .001) than among adults aged ≥65 years (68.8% vs 70.1%; P < .001); difference-in-differences = −6.2 percentage points (95% CI, −7.0 percentage points to −5.3 percentage points); P < .001. Error bars are 95% CIs. Data source: National Health Interview Survey.³³

Discussion

This study used nationally representative data to examine the association between self-reported vision difficulty and receipt of an annual eye examination among midlife and older adults. The prevalence of self-reported vision difficulty observed in this study is consistent with prior US population-based estimates using NHIS.²⁰ We also found that adults who reported vision difficulty were less likely to have received an eye examination in the past year than those who reported no vision difficulty, particularly among middle-aged adults, while the differences in the predicted probability of receiving an eye examination in the past year by vision difficulty was lower among older adults. These findings highlight a public health concern: self-perceived vision difficulty does not uniformly prompt care-seeking behavior across the life course, and midlife adults with vision difficulty may represent a group vulnerable to facing missed opportunities for preventing vision loss.

Older adults in our study had substantially higher rates of having an eye examination, regardless of whether they had self-reported vision problems. This finding may be partially explained by improved access to eye care through increased contact with the health care system and greater health awareness among older adults.^21,24-27 Furthermore, older adults are more likely than middle-aged adults to have established care routines and regular interactions with health care providers who may facilitate vision screening and referrals.^20,28 These routines and interactions could lead to reductions in differences in receiving routine eye examinations by perceived vision health in this age group. However, it is important to note that despite the higher likelihood of receiving a routine eye examination, nearly 30% of older adults in our study did not report having an eye examination in the past year, underscoring the need for continued efforts to improve access to vision care across all age groups. Vision coverage and benefits vary by Medicare programs and Medicare Advantage plans,^23,28 which may in part explain why a substantial proportion of older adults do not receive recommended eye care, highlighting the importance of expanding the vision benefits in public health insurance programs. Further research examining how the characteristics of Medicare programs and vision coverage affect the receipt of routine eye care among older adults could provide valuable insights to guide policy and improve access to preventive vision services.

Extending previous work documenting the underuse of eye care services in the United States,^14,20 our findings suggest that self-reported vision difficulty is not always a sufficient driver of receiving routine eye care, even after adjusting for key enabling and need factors, especially among middle-aged adults, for whom early detection can be especially beneficial.²⁹ This finding may reflect both individual barriers (competing life demands) and structural barriers to preventive care, including cost-related delays and gaps in health insurance that do not adequately cover eye care services.^16,18,30 This finding underscores midlife as a critical but often overlooked prevention window where strengthening access and awareness could have a meaningful long-term impact on potential vision loss among those with self-reported vision difficulty.

Moreover, our findings highlight how self-reported vision difficulty should be interpreted and applied within the broader public health context. While it is a practical proxy for functional vision impairment,¹⁷ self-reported vision difficulty does not uniformly translate to receipt of an annual eye care examination. Self-reported vision difficulty should be interpreted as an indicator of potential unmet needs in eye care, identifying populations that may benefit from targeted outreach, education, and systems-level efforts to improve access and encourage the use of preventive eye care services.

Individuals who report vision difficulty but do not receive eye examinations represent a group at risk of vision loss that may benefit from targeted interventions.^3,31 This finding emphasizes the need to complement surveillance efforts with strategies that proactively address the complex barriers that prevent people from accessing eye care. Integrating targeted outreach, health education, and vision screening into primary care, workplace wellness initiatives, and community-based programs may help bridge this gap.³² Embedding vision care within broader preventive care frameworks, akin to blood pressure or cholesterol screening, may further improve adherence to receiving regular eye examinations as part of routine health maintenance. Recognizing self-reported vision difficulty as an early warning sign can also help improve timely access to care and support efforts to prevent avoidable vision loss during the life course.

Beyond structural barriers, underlying age-related behavioral patterns can offer important insights for effective, tailored public health strategies. Middle-aged adults often deprioritize their own preventive health needs, including eye care, because of work, family, or caregiving responsibilities.^17,19 In addition, awareness of the importance of eye examinations may be lower among midlife adults than among older adults, who may have more frequent health-related messaging and opportunities for screening. Understanding how life stage, health literacy, and care navigation skills influence the link between self-perceived vision difficulty and receipt of an annual eye examination will be beneficial to develop targeted and effective public health strategies for middle-aged adults.

Limitations

This study had several limitations. First, the cross-sectional design precluded causal inferences; thus, associations should be interpreted within a correlational framework. Second, both vision difficulty and receipt of a past-year eye examination were self-reported and may have been subject to recall or reporting bias. Third, residual confounding by unmeasured factors such as transportation barriers or provider availability may remain.

Conclusion

Using self-reported nationally representative data, this study found that middle-aged adults were significantly less likely to receive a past-year eye examination than older adults. While this finding may partly reflect age-related differences in the prevalence of vision problems, it could also indicate a critical gap in preventive vision care during a period in which early intervention can be especially important. In addition, the relationship between self-reported vision difficulty and receipt of a past-year eye examination differed by age. Among midlife adults, having self-reported vision difficulty was associated with lower odds of receiving an eye care examination in the past year, whereas this pattern was attenuated among older adults. These findings suggest that self-reported vision difficulty is not consistently linked to care-seeking behavior, particularly in midlife when structural, financial, and behavioral barriers may intersect. It is essential to enhance public health strategies to address factors that drive differences between middle-aged and older adults, reduce barriers to care, and integrate vision care into routine preventive health services for improving vision health and preventing vision loss.

Supplemental Material

sj-docx-1-phr-10.1177_00333549261442145 – Supplemental material for Life Stage Differences in Vision Difficulty and Receipt of a Past-Year Eye Examination Among Midlife and Older Adults: Analysis of a National Sample

Supplemental material, sj-docx-1-phr-10.1177_00333549261442145 for Life Stage Differences in Vision Difficulty and Receipt of a Past-Year Eye Examination Among Midlife and Older Adults: Analysis of a National Sample by Daniel Jung and Eunhae Shin in Public Health Reports®

Footnotes

ORCID iD

Daniel Jung, PhD

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the University of Georgia Research Foundation and Owens Institute for Behavioral Research, University of Georgia.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data used in this study are publicly available through the National Health Interview Survey (NHIS), conducted by the National Center for Health Statistics. These data can be accessed at .

Disclaimer

The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the article; and decision to submit the article for publication.

Supplemental Material

Supplemental material for this article is available online. The authors have provided these supplemental materials to give readers additional information about their work. These materials have not been edited or formatted by Public Health Reports’s scientific editors and, thus, may not conform to the guidelines of the AMA Manual of Style, 11th Edition.

References

Saydah

Gerzoff

Saaddine

Zhang

Cotch

MF.

Eye care among US adults at high risk for vision loss in the United States in 2002 and 2017. JAMA Ophthalmol. 2020;138(5):479-489. doi:10.1001/jamaophthalmol.2020.0273

Varadaraj

Muñoz

Simonsick

Swenor

BK.

Vision impairment and participation in cognitively stimulating activities: the Health ABC Study. J Gerontol A Biol Sci Med Sci. 2021;76(5):835-841. doi:10.1093/Gerona/glaa184

Jin

Trope

Buys

, et al. Reduced social participation among seniors with self-reported visual impairment and glaucoma. PLoS One. 2019;14(7):e0218540. doi:10.1371/journal.pone.0218540

Coyle

Steinman

Chen

Visual acuity and self-reported vision status. J Aging Health. 2017;29(1):128-148. doi:10.1177/0898264315624909

Dinarvand

Panthakey

Hassan

Ahmed

MH.

Frailty and visual impairment in elderly individuals: improving outcomes and modulating cognitive decline through collaborative care between geriatricians and ophthalmologists. Diseases. 2024;12(11):273. doi:10.3390/diseases12110273

Balakrishnan

McGwin

Jr Owsley

Timed instrumental activities of daily living tasks in adults with irreversible vision impairment: validation to visual function and self-report. BMC Ophthalmol. 2024;24(1):417. doi:10.1186/S12886-024-03683-4

Thompson

Miller

Webb

Williamson

Kritchevsky

SB.

Visual impairment predicts greater declines in physical performance over time: the Health, Aging and Body Composition Study. BMC Geriatr. 2025;25(1):176. doi:10.1186/s12877-025-05747-6

Swenor

Muñoz

West

SK.

Does visual impairment affect mobility over time? The Salisbury Eye Evaluation Study. Invest Ophthalmol Vis Sci. 2013;54(12):7683-7690. doi:10.1167/iovs.13-12869

Harada

Nishiwaki

Michikawa

, et al. Gender difference in the relationships between vision and hearing impairments and negative well-being. Prev Med. 2008;47(4):433-437. doi:10.1016/j.ypmed.2008.06.011

10.

Whitson

Whitaker

Potter

, et al. A low-vision rehabilitation program for patients with mild cognitive deficits. JAMA Ophthalmol. 2013;131(7):912-919. doi:10.1001/jamaopthalmol.2013.1700

11.

Zheng

Swenor

Christ

West

Lam

Lee

DJ.

Longitudinal associations between visual impairment and cognitive functioning: the Salisbury Eye Evaluation Study. JAMA Ophthalmol. 2018;136(9):989-995. doi:10.1001/jamaophthalmol.2018.2493

12.

Crews

Chou

Zack

, et al. The association of health-related quality of life with severity of visual impairment among people aged 40-64 years: findings from the 2006-2010 Behavioral Risk Factor Surveillance System. Ophthalmic Epidemiol. 2016;23(3):145-153. doi:10.3109/09286586.2016.1168851

13.

Administration for Community Living. 2020 Profile of Older Americans. Administration on Aging, US Department of Health and Human Services; 2021. Accessed June 4, 2025. https://acl.gov/sites/default/files/aging%20and%20Disability%20In%20America/2020Profileolderamericans.final_.pdf

14.

Centers for Disease Control and Prevention. Why eye exams are important. May 15, 2024. Accessed June 24, 2025. https://www.cdc.gov/vision-health/about-eye-disorders/why-eye-exams-are-important

15.

American Academy of Ophthalmology. Comprehensive adult medical eye evaluation PPP 2020. 2020. Accessed June 4, 2025. https://www.aao.org/education/preferred-practice-pattern/comprehensive-adult-medical-eye-evaluation-ppp

16.

American Optometric Association. Clinical practice guidelines. 2025. Accessed June 24, 2025. https://www.aoa.org/practice/clinical-guidelines/clinical-practice-guidelines

17.

Chou

Sherrod

Zhang

, et al. Barriers to eye care among people aged 40 years and older with diagnosed diabetes, 2006-2010. Diabetes Care. 2014;37(1):180-188. doi:10.2337/dc13-1507

18.

Centers for Disease Control and Prevention. VEHSS modeled estimates: prevalence of vision loss and blindness. May 15, 2024. Accessed June 23, 2025. https://www.cdc.gov/vision-health-data/prevalence-estimates/vision-loss-prevalence.html

19.

Centers for Disease Control and Prevention. Reasons for not seeking eye care among adults aged ≥40 years with moderate-to-severe visual impairment—21 states, 2006-2009. MMWR Morb Mortal Wkly Rep. 2011;60(19):610-613.

20.

Moayad

Zajner

Popovic

, et al. Association between sociodemographic factors and vision difficulty in the National Health Interview Survey: a population-based analysis. Am J Ophthalmol. 2023;255:30-42. doi:10.1016/j.ajo.2023.06.015

21.

Ehrlich

Ndukwe

Solway

, et al. Self-reported eye care use among US adults aged 50 to 80 years. JAMA Ophthalmol. 2019;137(9):1061-1066. doi:10.1001/jamaophthalmol.2019.1927

22.

Centers for Disease Control and Prevention. 2023 National Health Interview Survey description. 2024. Accessed June 25, 2025. https://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/NHIS/2023/srvydesc-508.pdf

23.

Andersen

RM.

Revisiting the behavioral model and access to medical care: does it matter?

J Health Soc Behav. 1995;36(1):1-10.

24.

Assi

Varadaraj

Shakarchi

, et al. Association of vision impairment with preventive care use among older adults in the United States. JAMA Ophthalmol. 2020;138(12):1298-1306. doi:10.1001/jamaophthalmol.2020.4524

25.

Freed

Cubanski

Sroczynski

Ochieng

Neuman

Dental, Hearing, and Vision Costs and Coverage Among Medicare Beneficiaries in Traditional Medicare and Medicare Advantage. Kaiser Family Foundation; 2021. Accessed June 23, 2025. https://www.kff.org/health-costs/issue-brief/dental-hearing-and-vision-costs-and-coverage-among-medicare-beneficiaries-in-traditional-medicare-and-medicare-advantage

26.

Freed

Biniek

Damico

Neuman

Medicare Advantage 2023 spotlight: first look. November 10, 2022. Accessed June 23, 2025. https://www.kff.org/medicare/issue-brief/medicare-advantage-2023-spotlight-first-look

27.

Zhang

Saaddine

Lee

, et al. Eye care in the United States: do we deliver to high-risk people who can benefit most from it? Arch Ophthalmol. 2007;125(3):411-418. doi:10.1001/archopht.125.3.411

28.

Pope

Supplemental benefits under Medicare Advantage. Health Aff Forefront. Published online January 21, 2016. doi:10.1377/forefront.20160121.052787. Accessed February 16, 2026. https://www.healthaffairs.org/content/forefront/supplemental-benefits-under-medicare-advantage

29.

Turbert D. Eye health information for adults 40 to 65. July 14, 2025. Accessed June 23, 2025. https://www.aao.org/eye-health/tips-prevention/midlife-adults

30.

Lipton

Garcia

Boudreaux

Azatyan

McInerney

MP.

Most state Medicaid programs cover routine eye exams for adults, but coverage of other routine vision services varies. Health Aff (Millwood). 2024;43(8):1073-1081. doi:10.1377/hlthaff.2023.00873

31.

Alfaro Hudak

Wittenborn

Lamuda

Lundeen

Saaddine

Rein

DB.

Association between social determinants of health and examination-based vision loss vs self-reported vision measures. JAMA Ophthalmol. 2023;141(5):468-476. doi:10.1001/jamaophthalmol.2023.0723

32.

Zhang

Beckles

Chou

, et al. Socioeconomic disparity in use of eye care services among US adults with age-related eye diseases: National Health Interview Survey, 2002 and 2008. JAMA Ophthalmol. 2013;131(9):1198-1206. doi:10.1001/jamaophthalmol.2013.4694

33.

Centers for Disease Control and Prevention. NHIS questionnaires, datasets, and documentation. No date. Accessed March 17, 2026. https://www.cdc.gov/nchs/nhis/documentation/index.html

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