Discordance between measured and perceived vision in older adults: the need for objective screening despite health consciousness

Abstract

Perceived visual problems in older adults do not always align with measured vision, potentially delaying diagnosis and timely intervention. In this cross-sectional analysis of baseline data from the Proactive Ophthalmic Examination Cohort (Guangzhou, 2023–2024), we evaluated the prevalence and correlates of discordance between objective vision impairment (OVI, presenting visual acuity <20/40) and subjective visual disturbance (SVD, self-reported visual symptoms) among 829 health-conscious adults aged ≥65 years without prior intraocular interventions. Discordance was defined as two conditions: OVI without SVD or non-OVI with SVD. Associated factors were examined at the eye level using generalized linear mixed-effects models. Within this cohort, the prevalences of OVI and SVD were 42.8% and 44.6%, respectively (53.1% and 47.9% at the participant level). Discordance was substantial: 47.2% of OVI eyes did not report SVD, whereas 38.5% of non-OVI eyes reported SVD. SVD demonstrated limited accuracy for identifying OVI (sensitivity, 0.53; specificity, 0.64). The proportion of OVI eyes attributable to uncorrected refractive error was higher in OVI without SVD than in OVI with SVD (83.0% vs. 66.8%, p < 0.001). Higher income and lower Self-Rating Anxiety Scale (SAS) scores were associated with OVI without SVD, while lower income and higher SAS scores were linked to non-OVI with SVD; unilateral OVI was also associated with OVI without SVD. These findings indicate that SVD incompletely reflects OVI and underscore the need for routine objective vision screening in older populations, irrespective of perceived symptoms.

Introduction

The global aging trend is substantially increasing the burden of vision impairment. In 2020, an estimated 295 million people had moderate-to-severe vision impairment (MSVI), over 70% of whom were aged 50 years or older¹. In China alone, approximately 59 million individuals live with vision impairment, of whom 80% are aged 50 or above and 40% are aged 70 or older². Vision impairment in older adults extends beyond functional loss, as it restricts participation in outdoor and social activities³, limits access to health care⁴, and is associated with elevated risks of depression⁵, anxiety⁶, and cognitive decline⁷. Although many causes, such as refractive error and cataract, are treatable with existing interventions⁸, significant barriers, including inequitable access to eye care and limited health literacy, often delay diagnosis and treatment, leading to irreversible vision loss⁹.

In practice, subjective visual disturbance (SVD), which refers to symptoms such as blurred vision, floaters, or visual distortion (International Classification of Diseases, 10th Revision, code H53.1)¹⁰, remains the primary trigger for older adults in China to seek ophthalmic evaluation. However, the reliability of SVD as an indicator of clinically significant ocular disease remains unclear. Objective vision impairment (OVI)¹¹, defined by standardized visual acuity testing, typically reflects underlying eye conditions requiring clinical attention. Notably, some older adults exhibit OVI without reporting SVD, which may delay diagnosis, while others report SVD in the absence of measured OVI, potentially reflecting early ocular changes or non-ophthalmic conditions. This discordance highlights a critical gap in understanding real-world visual health perception and clinical need.

Elucidating the status and associated factors of OVI–SVD discordance is therefore essential to optimize vision care strategies for aging populations. Using baseline data from the Proactive Ophthalmic Examination Cohort (POEC) in Guangzhou, China, this study aims to investigate the prevalence and associated factors underlying OVI–SVD discordance within a population characterized by relatively high medical accessibility and health consciousness. This setting provides a unique opportunity to assess the persistence of such discordance when structural barriers to care and general health neglect are minimized. By evaluating both individual- and eye-level factors, this study aims to inform targeted screening approaches and health policy initiatives to improve early detection and management of vision impairment in older adults.

Results

Characteristics of study population

A total of 1658 eyes from 829 participants were included in the final analysis, and key baseline characteristics are summarized in Supplementary Table S1. The mean age of participants was 70.5 ± 4.5 years, and 63.2% were female. The most prevalent systemic comorbidities were hypertension (54.9%), diabetes (21.4%), cognitive impairment (25.0%), and anxiety (5.3%). At the participant level, the prevalence of OVI was 53.1% (440/829), with 38.9% (171/440) of cases being unilateral. In terms of severity, 25.1% (208/829) of participants had mild vision impairment (MVI), 26.1% (216/829) had MSVI, and 1.9% (16/829) met the criteria for blindness. SVD was reported by 47.9% (397/829) of participants. At the eye level, the prevalence of OVI was 42.8% (709/1658), and SVD was reported by 44.6% (739/1658) of eyes.

Discordance between OVI and SVD

Discordance was defined as two conditions: OVI without SVD or non-OVI with SVD. Specifically, OVI without SVD was defined as an eye with presenting visual acuity (PVA) < 20/40 that did not report SVD, whereas non-OVI with SVD referred to an eye reporting SVD despite having PVA ≥ 20/40. Considerable discordance between OVI and SVD was observed. Overall, 47.2% (335/709) of OVI eyes did not report SVD, while 38.5% (365/949) of non-OVI eyes reported SVD. The estimated sensitivity of SVD in identifying OVI was 0.53 (95% confidence interval [CI]: 0.47–0.59), with a specificity of 0.64 (95% CI: 0.59–0.69), a positive predictive value of 0.51 (95% CI: 0.46–0.56), and a negative predictive value of 0.65 (95% CI: 0.61–0.70). Blind eyes were more likely to report SVD compared to eyes with MVI (p < 0.001; Fig. 1A and Supplementary Table S2) or MSVI (p < 0.001), whereas no significant difference was found between MVI and MSVI eyes. Of note, the proportion of OVI eyes attributable to uncorrected refractive error (URE) was higher in OVI without SVD than in OVI with SVD (83.0% vs. 66.8%; odds ratio [OR]: 2.436, 95% CI: 1.577–3.765, p < 0.001). The proportion of OVI eyes without SVD did not differ between unilateral and bilateral cases (47.9% vs. 47.0%; OR: 0.949, 95% CI: 0.595–1.513, p = 0.826).

Fig. 1. Distribution of subjective visual disturbance (SVD) under different definitions of objective vision impairment (OVI).

A Distribution of SVD across OVI severity levels (mild vision impairment [MVI], moderate-to-severe vision impairment [MSVI], and blindness) defined by presenting visual acuity (PVA). B Distribution of SVD across OVI severity levels (MVI, MSVI, and blindness) defined by best-corrected visual acuity (BCVA). C Distribution of SVD symptom types among eyes with and without OVI as defined by PVA. D Distribution of SVD symptom types among eyes with and without OVI as defined by BCVA. Between-group comparisons in all panels were performed using generalized linear mixed-effects models with participant-level random intercepts to account for inter-eye correlation. For A, B, post hoc pairwise comparisons were further conducted with Bonferroni correction for multiple testing. No significant between-group differences in symptom distribution were observed in (C, D) (all p > 0.05; see Supplementary Table S7). *p < 0.05; ***p < 0.001.

Comparison of ocular parameters across study groups

Eyes were categorized into four groups based on the presence or absence of OVI and SVD: non-OVI/non-SVD, non-OVI/SVD, OVI/non-SVD, and OVI/SVD. The distribution of ocular parameters across these groups is presented in Supplementary Table S3, with post hoc pairwise comparisons shown in Fig. 2 and Supplementary Table S4. Among OVI eyes, those with SVD had significantly worse best-corrected visual acuity (BCVA) than those without SVD (p < 0.001). Notably, OVI eyes without SVD exhibited a higher proportion of URE than those with SVD (p < 0.05). Among non-OVI eyes, those with SVD demonstrated significantly lower nasal and inferior macular vessel density compared to eyes without SVD (both p < 0.05).

Fig. 2. Comparison of ocular parameters across study groups defined by objective vision impairment and subjective visual disturbance.

Ocular parameters were compared across four study groups stratified by the presence or absence of objective vision impairment (OVI) and subjective visual disturbance (SVD). A logMAR best-corrected visual acuity (BCVA) and VA decrement due to uncorrected refractive error (URE). B Spherical equivalent and astigmatism. C Axial length and anterior chamber depth. D Superior retinal nerve fiber layer (RNFL) thickness and inferior RNFL thickness. E Superior macular vessel density (MVD), inferior MVD, nasal MVD, and temporal MVD. F Cataract. G URE. URE was defined as a difference of ≥0.2 logMAR between logMAR PVA and logMAR BCVA. VA decrement due to URE was calculated as the difference between logMAR PVA and logMAR BCVA. Between-group comparisons were performed using mixed-effects models with participant-level random intercepts to account for inter-eye correlation; linear mixed-effects models were used for continuous outcomes and logistic mixed-effects models for binary outcomes. Post hoc pairwise comparisons were Bonferroni-corrected. *p < 0.05; **p < 0.01; ***p < 0.001.

Factors associated with discordance: OVI without SVD

Multivariable analysis identified several factors associated with the absence of SVD in OVI eyes (Table 1 and Supplementary Table S5), including better BCVA (OR: 0.213, 95% CI: 0.079–0.575, p = 0.002), higher annual household income (≥100,000 Chinese yuan [CNY], OR: 2.609, 95% CI: 1.461–4.657, p = 0.001), heart disease (OR: 0.395, 95% CI: 0.180–0.867, p = 0.021), and lower Self-Rating Anxiety Scale (SAS) scores (OR: 0.958, 95% CI: 0.930–0.987, p = 0.005).

Table 1.

Multivariable analysis of factors associated with discordance: OVI (PVA-defined) without SVD (n = 709)

Variable	OR (95% CI)	p-value
Annual household income (CNY)
<50,000	1.000 (reference)
50,000–100,000	1.220 (0.728, 2.045)	0.450
≥100,000	2.609 (1.461, 4.657)	0.001
Heart disease
No	1.000 (reference)
Yes	0.395 (0.180, 0.867)	0.021
Self-Rating Anxiety Scale score	0.958 (0.930, 0.987)	0.005
logMAR BCVA	0.213 (0.079, 0.575)	0.002

Multivariable generalized linear mixed-effects models (GLMMs) were performed at the eye level with participant ID as a random intercept to account for inter-eye correlation. Candidate variables with p < 0.20 in univariable analyses were assessed for multicollinearity using variance inflation factors (VIFs). Backward elimination based on likelihood ratio tests (LRTs) was applied to derive the final model (removal criterion p > 0.10). Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were obtained from the final model.

OVI objective vision impairment, PVA presenting visual acuity, SVD subjective visual disturbance, OR odds ratio, CI confidence interval, CNY Chinese yuan, BCVA best-corrected visual acuity.

Bold values indicate statistically significant results (p < 0.05).

Factors associated with discordance: non-OVI with SVD

Among non-OVI eyes, multivariable analysis identified several factors associated with reporting SVD (Table 2 and Supplementary Table S6), including lower nasal macular vessel density (OR: 0.943, 95% CI:0.903–0.986, p = 0.010), diabetes (OR: 1.884, 95% CI: 1.120–3.170, p = 0.017), joint pain (OR: 1.931, 95% CI: 1.205–3.093, p = 0.006), higher serum cholesterol levels (OR: 1.233, 95% CI: 1.015–1.499, p = 0.035), inadequate physical activity (OR: 1.768, 95% CI: 1.136–2.752, p = 0.012), and shorter weekly outdoor time (OR: 0.974, 95% CI: 0.951–0.997, p = 0.029).

Table 2.

Multivariable analysis of factors associated with discordance: non-OVI (PVA-defined) with SVD (n = 949)

Variable	OR (95% CI)	p-value
Weekly physical activity
≥600 MET-min/week	1.000 (reference)
<600 MET-min/week	1.768 (1.136, 2.752)	0.012
Weekly outdoor time	0.974 (0.951, 0.997)	0.029
Diabetes
No	1.000 (reference)
Yes	1.884 (1.120, 3.170)	0.017
Joint pain
No	1.000 (reference)
Yes	1.931 (1.205, 3.093)	0.006
Cholesterol	1.233 (1.015, 1.499)	0.035
Nasal macular vessel density	0.943 (0.903, 0.986)	0.010

Multivariable generalized linear mixed-effects models (GLMMs) were performed at the eye level with participant ID as a random intercept to account for inter-eye correlation. Candidate variables with p < 0.20 in univariable analyses were assessed for multicollinearity using variance inflation factors (VIFs). Backward elimination based on likelihood ratio tests (LRTs) was applied to derive the final model (removal criterion p > 0.10). Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were obtained from the final model.

OVI objective vision impairment, PVA presenting visual acuity, SVD subjective visual disturbance, OR odds ratio, CI confidence interval, MET-min/week metabolic equivalent task minutes per week.

Bold values indicate statistically significant results (p < 0.05).

Sensitivity analyses using BCVA-based OVI definition

A sensitivity analysis was conducted by redefining OVI based on BCVA (<20/40). At the participant level, OVI prevalence decreased substantially to 15.6% (129/829), with 59.7% (77/129) of cases unilateral. MSVI prevalence was 3.9% (32/829) and blindness 1.4% (12/829). At the eye level, OVI prevalence was 10.9% (181/1658). Overall, 31.5% (57/181) of OVI eyes did not report SVD, while 41.6% (615/1477) of non-OVI eyes reported SVD. The estimated sensitivity of SVD in identifying OVI was 0.70 (95% CI: 0.59–0.79), with a specificity of 0.60 (95% CI: 0.56–0.64), a positive predictive value of 0.15 (95% CI: 0.12–0.18), and a negative predictive value of 0.95 (95% CI: 0.93–0.96).

Blind eyes showed a significantly higher proportion of reporting SVD than MVI eyes (p = 0.004; Fig. 1B and Supplementary Table S2). The most common SVD symptoms across both definitions were blurred vision, floaters, and photophobia. However, no significant differences in symptoms were observed between groups (all p > 0.05; Fig. 1C, D and Supplementary Table S7). OVI eyes from unilateral cases were more likely not to report SVD than those from bilateral cases (41.6% vs. 24.0%; OR: 2.463, 95% CI: 1.119–5.420, p = 0.025), a pattern not observed under the PVA definition. Bilateral OVI eyes exhibited a significantly higher rate of SVD absence under the PVA definition compared to the BCVA definition (47.0% vs. 24.0%; OR: 2.174, 95% CI: 1.022–4.630, p = 0.044).

Factors associated with discordance under the BCVA definition are detailed in Supplementary Tables S8–S11. For OVI eyes without SVD, the associations with lower SAS scores and better BCVA remained consistent with the primary analysis. Newly identified factors included older age (OR: 1.125, 95% CI: 1.038–1.219, p = 0.004), unilateral OVI (OR: 2.924, 95% CI: 1.176–7.268, p = 0.021), and rare dairy intake (OR: 0.313, 95% CI: 0.111–0.880, p = 0.028). For non-OVI eyes with SVD, the associations with higher SAS scores and lower annual household income remained significant. Poorer PVA was also associated with SVD reporting. Additionally, poorer self-rated memory was associated with a higher likelihood of SVD reporting (OR: 1.853, 95% CI: 1.111–3.092, p = 0.018).

Discussion

This study systematically assessed the discordance between OVI and SVD in a health-conscious older population in Southern China. We observed a substantial level of discordance: 47.2% of OVI eyes did not report SVD, while 38.5% of non-OVI eyes reported SVD. Multivariable analyses revealed that discordance was associated with visual acuity, retinal microvascular characteristics, psychological and cognitive factors, household income, physical activity levels, and several chronic systemic conditions. Importantly, the extent and associated factors of discordance differed when OVI was defined using PVA versus BCVA, highlighting the key role of URE in this phenomenon.

In this cohort, the prevalence of PVA-defined OVI was 53.1%, whereas BCVA-defined OVI was 15.6%; 47.9% of participants reported SVD. Compared to the nationwide systematic review by Zou et al. (2021) of adults aged ≥50 years in China¹², our cohort exhibited higher rates of MSVI (26.1% vs. 10.9%) and comparable rates of blindness (1.9% vs. 2.2%) under the PVA definition. Under the BCVA definition, however, rates of MSVI (3.9% vs. 5.4%) and blindness (1.4% vs. 2.2%) were lower. These patterns suggest that a significant proportion of vision impairment in our participants was attributable to URE. Notably, our participants were community-dwelling residents of Guangzhou, a metropolitan area with high ophthalmic care availability and relatively high health consciousness. Despite these advantages, a significant burden of OVI remained, underscoring the persistent need for routine objective vision screening even among health-conscious older adults.

The observed discordance between measured and perceived vision has important clinical implications. OVI without SVD may delay diagnosis and treatment, whereas non-OVI with SVD may indicate early ocular changes or non-ophthalmic conditions. Similar discordance has been reported in other aging populations, with studies indicating that 74.9–85.9% of older adults with OVI do not report visual symptoms^13,14. In our study, among PVA-defined OVI eyes, those without SVD showed a significantly higher proportion of URE than those with SVD, suggesting that gradual refractive changes may lead to perceptual adaptation and reduced symptom awareness¹⁵. Consistent with this, bilateral OVI eyes exhibited a significantly higher rate of SVD absence under the PVA definition compared to the BCVA definition. The World Health Organization (WHO) identifies uncorrected refractive error and cataract as two of the leading causes of vision impairment and blindness worldwide, underscoring the public health importance of timely refraction assessment and optical correction⁸. These measures are also crucial for maintaining daily visual function in older adults. Furthermore, under the BCVA definition, participants with unilateral OVI were more likely to lack SVD than those with bilateral OVI, which may reflect compensatory binocular mechanisms that mask monocular visual deficits in daily life¹⁶. As unilateral OVI can be insidious, many patients may not recognize it until the affected eye has already developed irreversible impairment, further underscoring the necessity of regular objective ophthalmic examinations.

Our findings align with prior evidence linking systemic health, socioeconomic status, lifestyle, and psychological factors to OVI–SVD discordance^13,14,17. Across both OVI definitions, poorer visual acuity, higher SAS scores, and lower income were associated with non-OVI with SVD, whereas better visual acuity, lower SAS scores, and higher income were associated with OVI without SVD. Anxiety may heighten perceptual sensitivity to minor visual changes¹⁸, while income is likely to influence both access to care and timely refractive correction¹⁹. Additionally, relatively preserved visual acuity within the impaired range may reduce symptom reporting, whereas visual acuity near the impairment threshold may provoke subjective complaints.

Other factors were also associated with discordance. Among those with OVI but without SVD, older age and unilateral OVI were significant correlates, possibly reflecting diminished self-awareness of gradual vision loss²⁰ and binocular compensatory mechanisms, respectively. Among those without OVI but with SVD, lower nasal macular vessel density, diabetes, joint pain, higher serum cholesterol levels, lower physical activity, and shorter outdoor time were associated factors. Altered retinal microcirculation may impair visual quality despite preserved acuity^21,22, while systemic comorbidities^23,24 and sedentary lifestyles^25,26 may exacerbate perceptual visual complaints.

As our cohort was recruited from an urban, high-resource setting with relatively high health consciousness, the observed patterns of OVI–SVD discordance may differ from those in rural or underserved populations. In underserved settings, limited access to eye care and lower health consciousness may increase the proportion of OVI without SVD. This possibility is supported by observations from our unpublished internal field investigation conducted in Mangxin Town, Kashgar, Xinjiang, a remote and less-developed region of China. Among 2356 eyes from 1178 older adults, 1367 eyes (58.0%) met the criteria for PVA-defined OVI, whereas only 223 eyes (9.5%) reported SVD. Of the 1367 OVI eyes, 87.9% did not report SVD, while among 989 non-OVI eyes, 5.9% reported SVD. These findings underscore the importance of objective visual acuity screening across both high- and low-resource settings, rather than relying on symptom-based identification alone. Annual vision assessment is commonly recommended for adults aged ≥65 years, with adaptation to local resource availability^27,28. Given the simplicity and convenience of measuring PVA, it may serve as a first-line screening measure, with pinhole testing or BCVA assessment used for further confirmation when feasible. Considering the accessibility and the minimal equipment required for visual acuity examinations, community-based and primary care settings may serve as practical platforms for primary vision screening. In addition, the rapid development of smartphone-based vision screening tools provides promising opportunities to further expand access to screening services²⁹. Longitudinal follow-up of the POEC cohort will provide further evidence to guide screening strategies tailored to individual risk and local resources.

While previous studies have documented OVI–SVD discordance, most have relied on limited symptom definitions and omitted detailed ocular parameters. Our study expands this evidence by employing a broader SVD definition, incorporating both PVA- and BCVA-based OVI criteria, and integrating comprehensive ocular structural and functional metrics. Furthermore, by focusing on a health-conscious urban Chinese cohort with high medical accessibility, this study uniquely examines whether discordance persists when structural barriers to care are minimized. Despite methodological and population differences, our results corroborate key findings from Western cohorts. Specifically, we found that higher income and fewer comorbidities were associated with OVI without SVD, while anxiety and lower income were associated with non-OVI with SVD. These findings underscore that discordance is shaped not only by ocular pathology but also by psychosocial and socioeconomic contexts, which should inform vision screening and individualized eye care strategies.

This study has several limitations. First, its cross-sectional design precludes causal inferences. The observed associations were correlational only and may reflect bidirectional or confounding relationships. Future longitudinal follow-up within the POEC cohort will be important to further clarify these temporal relationships. Second, although we implemented structured interviews and eye-specific reporting to minimize potential misclassification, recall bias in SVD remains difficult to completely avoid. Future studies using more detailed and objective assessment tools, such as standardized questionnaires or clinical visual function evaluations, may help more comprehensively characterize participants’ SVD status. Third, the sample consisted of urban-dwelling, health-conscious older adults from a high-resource setting, which may limit generalizability to rural or underserved populations.

In summary, this study demonstrates a substantial discordance between OVI and SVD among older adults, even in a health-conscious population with good access to eye care. Both OVI without SVD and non-OVI with SVD were common and were associated with a range of visual, systemic, psychological, and lifestyle factors. These findings caution against reliance on self-reported symptoms alone for vision screening and underscore the importance of regular, objective ophthalmic assessment in older adults.

Methods

Study design and participants

This cross-sectional analysis utilized baseline data from POEC, an ongoing prospective, community-based study established at the Zhongshan Ophthalmic Center in Guangzhou, China, in 2023. The POEC conducts annual follow-ups to monitor ocular and systemic health trajectories in older adults. Community-dwelling residents aged ≥65 years were recruited through public announcements. All participants provided written informed consent and underwent comprehensive annual ophthalmic and general health evaluations. The study protocol was approved by the Institutional Review Board of the Zhongshan Ophthalmic Center, Sun Yat-sen University (Approval No. 2023KYPJ003-3) and adhered to the tenets of the Declaration of Helsinki.

Between February 20, 2023, and May 11, 2024, 1037 participants were enrolled. After excluding individuals with (1) a history of intraocular interventions (surgery, laser photocoagulation, or intravitreal injections) or (2) incomplete assessments preventing classification of OVI or SVD, a final analytical sample of 829 individuals was analyzed. The participant selection process is summarized in Fig. 3.

Fig. 3.

Flowchart of enrolled participants.

Data collection and assessments

Based on clinical experience and prior literature, we identified variables potentially associated with visual abnormalities in older adults and prospectively collected these data for subsequent analysis. The collected data included ocular parameters, such as visual acuity, refractive status, intraocular pressure, ocular biometric parameters, and fundus-related parameters, as well as systemic variables, including demographic characteristics, lifestyle factors, medical history, physical examination data, and laboratory test results. Data collection was performed by trained personnel following standardized operating procedures. To minimize bias, different technicians administered questionnaires, performed visual acuity measurements, and conducted ocular and systemic examinations; all assessors were blinded to participants’ other clinical information. Questionnaires were administered through face-to-face interviews to ensure comprehension and minimize missing data. All examination results were independently reviewed by two ophthalmologists (W.X., 10 years of experience; T.X.E., 3 years of experience). Discrepancies were resolved through adjudication by a senior expert (L.H.T., >20 years of experience).

Measurement of OVI and SVD

Visual acuity was assessed using a 4-m Early Treatment Diabetic Retinopathy Study (ETDRS) chart. PVA was measured under habitual viewing conditions. Participants who regularly wore corrective lenses were tested with their habitual spectacles, whereas those without correction were measured unaided³⁰. BCVA was obtained after subjective refraction, with spherical and cylindrical components recorded. Following WHO guidelines, OVI was primarily defined as PVA < 20/40 in either eye¹¹. For sensitivity analyses, OVI was redefined as BCVA < 20/40. MSVI was defined as visual acuity <20/63 but ≥20/400; blindness was defined as <20/400.

SVD was evaluated using a structured, face-to-face questionnaire administered by trained interviewers. For each eye, participants were asked: “In the past month, have you experienced any of the following visual symptoms in your right/left eye?”³¹ Symptoms included blurred vision, floaters, metamorphopsia, photophobia, and halos¹⁰, each accompanied by a brief description. To improve laterality accuracy, participants were instructed to occlude one eye at a time and report symptoms based on monocular perception. Frequency and daily-life impact were recorded for each reported symptom. An eye was classified as having SVD if at least one symptom occurred weekly and interfered with daily activities. Both OVI and SVD were analyzed at the eye level, with data recorded separately for each eye.

Ophthalmic and systemic examinations

Comprehensive ophthalmic examinations were performed for all participants. Specifically, slit-lamp biomicroscopy and anterior segment photography were performed to evaluate anterior segment structures, including cataract grading via the Lens Opacities Classification System III (LOCS III)³². Intraocular pressure was measured initially via non-contact tonometry, with abnormal readings confirmed by Goldmann applanation tonometry. Ocular biometry was performed using IOLMaster 700 (Carl Zeiss Meditec AG, Jena, Germany) and Pentacam AXL (Oculus Optikgeräte GmbH, Wetzlar, Germany). Widefield true-color fundus imaging was conducted with the CLARUS 500 digital fundus camera (Carl Zeiss Meditec, Dublin, CA, USA). Macular and optic disc evaluation was performed via optical coherence tomography (OCT) and OCT angiography using DRI OCT Triton (Topcon Corp., Tokyo, Japan), yielding parameters including macular thickness, retinal nerve fiber layer (RNFL) thickness, and macular vessel density (MVD). Ocular history was obtained via a structured questionnaire. PVA and BCVA were converted to logarithm of the minimum angle of resolution (logMAR) values for analysis. URE was defined as a difference of ≥0.2 logMAR between logMAR PVA and logMAR BCVA³³. VA decrement due to URE was calculated as the difference between logMAR PVA and logMAR BCVA³⁴. Definitions and classifications of ocular variables are summarized in Supplementary Table S12.

Systemic assessment included structured questionnaires, physical examinations, laboratory tests, and psychological scales. Physical activity was quantified in metabolic equivalent task minutes (MET-min) per week, with <600 MET-min classified as insufficient according to WHO guidelines³⁵. Cognitive function was assessed using the Mini-Mental State Examination, and anxiety was evaluated via the SAS. Physical measurements included height, weight, waist, and hip circumference for calculation of body mass index and waist-to-hip ratio. Fasting blood and urine samples were analyzed for complete blood count, biochemistry, liver and renal function, glycated hemoglobin (HbA1c), and urinalysis. Definitions and classifications of systemic variables are summarized in Supplementary Table S13.

Statistical analysis

Analyses were conducted using IBM SPSS Statistics version 29.0 (IBM Corp., Armonk, NY, USA) and R version 4.2.1 (R Foundation for Statistical Computing, Vienna, Austria). A two-sided p < 0.05 was considered statistically significant. Missing data (<10% for any variable) were imputed via K-nearest neighbors (k = 5) using the Visualization and Imputation of Missing Values (VIM) package in R. Sensitivity analyses based on the complete-case dataset yielded materially similar results and are presented in Supplementary Tables S14–S17. Descriptive statistics are presented as mean ± standard deviation or median (interquartile range) for continuous variables and as number (%) for categorical variables.

All analyses conducted at the eye level were performed using generalized linear mixed-effects models to account for inter-eye correlation, with participant ID specified as a random intercept. For between-group comparisons, linear mixed-effects models were applied for continuous outcomes, and logistic mixed-effects models were used for binary outcomes. When comparisons involved more than two groups, model-based post hoc pairwise comparisons were performed with Bonferroni correction for multiple testing. For analyses of factors associated with discordant vision status, binary logistic mixed-effects models were fitted. Candidate variables identified in univariable analyses (p < 0.20) were first evaluated for multicollinearity using variance inflation factors (Supplementary Table S18). Backward elimination using likelihood ratio tests was then applied to derive the final model, with a removal criterion of p > 0.10. Adjusted ORs with 95% CIs were derived from the final model.

Author contributions

HL, XT, and XW contributed to the concept of the study. HL, XT, XW, and LZ contributed to the methodology of the study. XT, XW, WH, JF, and QZ collected data. XT and LZ performed the analysis. XT contributed to the original draft preparation. HL, XW, DL, and ZL contributed to the review and editing of the manuscript. HL, XW, and DL provided research funding. WH, JF, MD, and DW provided administrative, technical, or material support. All authors read and approved the final manuscript.

Data availability

Due to patient privacy and ethical restrictions, the raw clinical data cannot be shared publicly. De-identified representative data can be requested for nonprofit academic research to the corresponding author HL (linht5@mail.sysu.edu.cn) following review by the data access committee at the State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center.

Competing interests

The authors declare no competing interests.

Supplementary information

The online version contains supplementary material available at 10.1038/s41514-026-00403-8.