The prevalence of amblyopia and associated factors in older adults in The Malta Eye Study

Abstract

To assess amblyopia-related visual impairment in older Maltese adults and describe age-related trends in prevalence. The Malta Eye Study, a population-based, cross-sectional study, assessed a random stratified sample of adults aged 50–80 years. The examination involved a visual acuity test, autorefraction, slit-lamp examination, and a questionnaire related to demographics, ocular history, and the national eye institute visual function questionnaire. Statistical analysis of the visually impaired and amblyopic participants was performed, and associations with demographic and clinical variables were explored using stepwise multivariate logistic regression. Among 1794 participants aged 50 to 80 years, the prevalence of amblyopia-related visual impairment was 5.0% (95% CI 4.1–6.1%). The highest rates were observed in males, individuals aged 60–69 years, those with primary-level education, residents of the South-Eastern district, and individuals engaged in domestic work. When compared to individuals without visual impairment, only age 60–69 remained significantly associated in the final regression model (OR 2.2; 95% CI 1.2–4.1; p = 0.014). Anisometropia was the presumed cause of amblyopia in 50.6% of cases. Vision-related quality of life was mildly reduced in amblyopic individuals compared to non-visually impaired individuals. Amblyopia remains a cause of visual impairment among older adults in Malta, particularly those aged 60 + years, highlighting the irreversible visual and functional life-long impact of undetected childhood amblyopia and the need for early vision screening.

Introduction

Amblyopia is a neurodevelopmental visual processing disorder defined by reduced best-corrected visual acuity in one or both eyes that cannot be attributed solely to structural ocular anomalies. It is the result of either ocular disuse, as in anisometropia and visual deprivation, or improper binocular function, as can occur in strabismus, during the critical period of visual development, that is, the first seven years of life^1,2. It typically results in unilateral visual impairment and is usually diagnosed during childhood, when early detection and treatment can substantially improve outcomes, while becoming irreversible in adulthood. Amblyopia affects 2–4% of children³.

Paediatric amblyopia diagnostic criteria typically require an interocular best corrected visual acuity difference of at least two lines⁴, accounting for normal visual maturation in children². No established criteria exist for adults, where coexisting ocular diseases such as cataracts or macular degeneration can obscure or mimic amblyopic vision loss. Adult diagnosis often relies on modified criteria that combine historical visual and refractive data with unexplained asymmetry in visual function and/or reduced best corrected visual acuity⁵.

The functional impact of amblyopia extends beyond reduced acuity and stereopsis. Recent studies highlight additional deficits in oculomotor control, motion perception, visuospatial processing, eye–hand coordination, and fine motor skills, suggesting that amblyopia reflects a broader disruption of visual neurodevelopment than previously recognised^{6, 7–8}. These deficits can contribute to poorer academic performance, limitations in occupational opportunities, and reduced quality of life^9,10.

The prevalence of amblyopia among individuals aged 49 + in the Blue Mountains Eye Study using a 20/40 best corrected visual acuity definition was 2.9% (95%CI 2.4%-3.5%) and was caused by anisometropia (49%), strabismus (18%), mixed anisometropia and strabismus (27%), and visual deprivation (4%)¹¹. Most adult studies prioritise bilateral vision loss as a public health concern^12,13 and since amblyopia causes unilateral visual impairment, it has rarely been highlighted. Amblyopia affects visual function, quality of life^14,15, and educational levels⁵ in adulthood through monocularity and reduced stereopsis¹². In adults, amblyopia also increases the risk of a 5-year incident visual impairment from the better eye by 2.7 (95%CI 1.6–4.6)⁵.

The Malta Eye Study (TMES) is a cross-sectional population-based study that estimates the prevalence of common eye diseases and visual impairment in Maltese adults aged 50–80 years. This paper presents real-world prevalence data from TMES for amblyopia in older individuals and investigates for any differences across age groups.

Materials and methods

The TMES methodology, has been described in detail elsewhere¹⁶. This study adhered to the STROBE Checklist¹⁷.

Ethical clearance and permissions

Ethical approval was granted by the University of Malta Faculty Research Ethics Committee (FRECMDS_1819_94) prior to data collection in 2019. The study followed the Declaration of Helsinki¹⁸ and GDPR¹⁹ guidelines, with hospital and Data Protection Officer approvals. Written informed consent was obtained, and the data were pseudonymised.

Sample size justification

TMES recruited 1,794 participants to assess the prevalence of ocular conditions. Using Piface, for an expected amblyopia prevalence of 2.9%¹¹, this sample size yields a margin of error of ± 0.78% with 95% confidence²⁰. This corresponds to about 0.25 of the expected prevalence, fulfilling the recommended criterion for prevalence studies described by Naing et al.²¹.

Study population

To reach the desired response rate, a random sample of 4006 individuals aged 50–80 years, out of an available nationwide random sample of 5000 individuals, stratified by age, sex, and locality, obtained from the Malta Electoral Register, were invited for an ophthalmic assessment between September 2021 and July 2024.

Ophthalmic assessment

The individuals were examined at Mater Dei Hospital between September 2021 and May 2024 and at Gozo General Hospital between June 2024 and July 2024.

Monocular presenting visual acuity testing was performed with distance vision glasses, when available, using an electronic ETDRS chart with a logMAR scale²². Pinhole testing was performed if monocular presenting visual acuity was > 0.3 logMAR and the best corrected visual acuity was taken following Visionix^®23 autorefraction and subjective refraction. The assessment also involved anthropometric measurements, Goldmann tonometry, slit lamp-based anterior segment and dilated posterior segment indirect (90D) examination, fundus photography, and swept-source optical coherence tomography scanning of the macula and disc.

The questionnaire included themes related to sociodemographic status, ocular history, and the National Eye Institute Visual Function Questionnaire (NEIVFQ)²⁴. The collected sociodemographic variables were used to assign the individuals into mutually exclusive groups.

Definitions used

Visual impairment was defined using ICD-11 criteria²⁵ based on distance monocular presenting visual acuity. Severity, based on the better eye or affected eye in unilateral visual impairment, was classified as mild (monocular presenting visual acuity > 0.3–0.5 logMAR), moderate-to-severe (moderate-severe visual impairment; monocular presenting visual acuity > 0.5–1.3 logMAR), and blindness (monocular presenting visual acuity > 1.3 logMAR).

Amblyopia was defined as best corrected visual acuity > 0.3 logMAR in one eye, where such reduction could not be attributed to identifiable structural ocular pathology (e.g., media opacity, retinal or optic nerve disease) alone. Cases with coexisting ocular pathology were included in the amblyopia group if the visual acuity reduction could not be fully explained by that pathology. Supportive features included a history of visual loss since childhood or evidence of amblyogenic factors, such as anisometropia or childhood-onset strabismus. When historical data were limited, amblyopia was inferred from the pattern of findings consistent with longstanding monocular vision loss, without an identifiable organic cause.

Amblyopia cases were classified into four presumed causes based on clinical and historical data: anisometropia, strabismus, mixed anisometropia and strabismus, and “other” causes. Presumed visual deprivation, including bilateral amblyopia or history of vision loss since birth, corrected squint, and pseudophakia-related changes were classified as “other”. In pseudophakic cases with anisometropia but no strabismus, the cause was classified as “other” to avoid misattribution. History of squint surgery without current squint also led to the classification as “other”. Cases in which cause could not be confidently assigned were labelled “unknown”. The spherical equivalent (SE) was defined as the sphere + ½ astigmatism requirement in dioptres (D). Emmetropia was defined as SE ≥-0.50D and ≤ + 0.50D, with myopia being <-0.50D and hyperopia being > + 0.50D. Anisometropia was defined as ≥ 1.00D difference between right and left SEs of phakic surgically untouched eyes. Strabismus was defined as the presence of an asymmetric corneal reflex in the Hirschberg test.

Statistical analysis

Statistical analyses were performed using the IBM SPSS Statistics v23²⁶. Demographic variables (age, sex, and district) were compared with the national census data²⁷ for representativeness. Descriptive statistics were used to provide prevalence estimates with 95% confidence intervals. Chi-square tests assessed age-gender subgroup representativity, and weights (population proportion/sample proportion) standardised the sample to census data for ages 50–80. These weights were applied in all prevalence and confidence interval calculations to ensure that the results were representative of the Maltese population aged 50–80. No propensity weighting was used. Categorical predictors of visual impairment were tested using Chi-square or Fisher’s exact tests. Significant univariate predictors (p < 0.05) were included in the backward stepwise binary logistic regression models based on the Wald test, with the absence of visual impairment as a reference. The final steps were presented. Differences in NEIVFQ composite and subscale scores between individuals with and without amblyopia were assessed using the Mann–Whitney U test. Effect sizes (Cohen’s r) were calculated as , where Z is the standardised test statistic and N is the total sample size for the comparison. Subscale analyses were exploratory; p-values were not adjusted for multiple comparisons. Missing data, being minimal and unrelated to visual impairment, were handled by listwise deletion, assumed to be completely missing at random, with no imputation.

Results

A total of 1,794 individuals were assessed between September 2021 and July 2024, yielding a turnout of 44.8%. Sample representativeness was evaluated against the national census²⁷, showing good alignment for age, sex, and district when considered separately. However, there was an underrepresentation of males (p < 0.001) and females (p = 0.009) aged 50–59 in Northern Harbour, and of females aged 50–59 in Gozo (p = 0.004). To correct for this, weighting based on national census²⁷ data was applied. Missing data were minimal: 0.4% for most questionnaire items, 0.2% for visual impairment classification, 8.1% for education (post-assessment), and 4.8% for autorefraction.

Prevalence of amblyopia as a cause of visual impairment

Amblyopia visual impairment was observed in 90 individuals with a prevalence of 5.0% (95% CI 4.1%-6.1%) and it was the second commonest distance visual impairment in either eye, explaining 21.0% (95% CI 17.3%-25.2%) of cases, following uncorrected/undercorrected refractive error. Unilateral amblyopia occurred in 88 cases. It contributed more to unilateral visual impairment (25.3%; 95% CI 20.6%-30.4%) than to bilateral visual impairment (8.4%, 95% CI 3.9%-15.4%). Amblyopia was the leading cause, contributing the most in unilateral moderate-severe visual impairment (34.8%; 95% CI 25.0%-45.7%) and unilateral blindness (45.7%; 95% CI 30.9%-61.0%). Amblyopia was the only cause of visual impairment in 78.9% (95% CI 69. %-86.8%) of its cases. Amblyopia’s contribution to unilateral visual impairment was exclusive in 84.0% (95% CI 74.1%-91.2%) of unilateral amblyopia, while for bilateral visual impairment, its exclusivity was smaller (2.8%; 95% CI 0.6%-8.0% out of bilateral visual impairment, limited numbers of amblyopia cases in bilateral visual impairment). In the amblyopia group, the other visually impairing conditions included uncorrected/undercorrected refractive error (n = 7; 7.8%), pathological myopia (n = 7; 7.8%), cataract (n = 3; 3.3%), corneal conditions (n = 2; 2.2%).

The prevalence of amblyopia visual impairment was noted to increase with age, and males in the 70–80 age group had the highest rate (7.1%; 95%CI 4.3%-11.1%) (Fig. 1).

Fig. 1 [Images not available. See PDF.]

Prevalence of amblyopia visual impairment with 95%CI bars by age group and sex in census-adjusted the malta eye study population (n = 1794).

Characteristics of the amblyopic individuals and amblyopic eyes

The sociodemographic characteristics of the individuals with and without amblyopia are shown in (Table 1). Notably, the highest rates of amblyopia were observed in males, individuals aged 60–69 years, residents of the South-Eastern district, those with only primary education, and individuals engaged in domestic work. However, in a stepwise multivariate logistic regression comparing individuals with amblyopic visual impairment to those without visual impairment, these variables were excluded, except for age. The 60–69-year age group retained statistical significance, with an odds ratio (OR) of 2.2 (95%CI 1.2–4.1; p = 0.014). Among the 73 phakic amblyopic eyes, 32 (43.8%; 95% CI 32.2%-55.9%) were myopic, 2 (2.7%; 95% CI 0.3%-9.5%) were emmetropic, and 39 (53.4%; 95% CI 41.4%-65.2%) were hyperopic.

Table 1. Distribution of sociodemographic characteristics among individuals with and without amblyopia, including the prevalence of amblyopia and odds ratios with corresponding 95% confidence intervals for each group.

Variable	Category	Frequency, n (%)		Amblyopia prevalence, % (95% CI %)	Odds ratio
		No amblyopia	Amblyopia
Total		1704 (100.0%)	90 (100.0%)	5.0% (4.1%-6.1%)	N/A
Age group	50–59	601 (35.4%)	24 (26.7%)	3.8% (2.5–5.7%)	Reference
	60–69	593 (34.9%)	39 (43.3%)	6.2% (4.4–8.3%)	1.6 (1.0–2.8)
	70–80	503 (29.6%)	27 (30.0%)	5.1% (3.4–7.3%)	1.3 (0.8–2.4)
Sex	Male	841 (49.6%)	51 (56.7%)	5.7% (4.3–7.4%)	Reference
	Female	855 (50.4%)	39 (43.3%)	4.4% (3.1–5.9%)	0.8 (0.5–1.2)
District	Southern Harbour	304 (17.9%)	15 (16.9%)	4.7% (2.7–7.6%)	Reference
	Northern Harbour	489 (31.7%)	22 (26.2%)	4.3% (2.7–6.4%)	0.9 (0.5–1.8)
	South Eastern	240 (14.1%)	22 (24.7%)	8.4% (5.3–12.4%)	1.9 (0.9–3.7)
	Western	226 (13.3%)	13 (14.6%)	5.4% (2.9–9.1%)	1.2 (0.5–2.5)
	Northern	284 (16.7%)	12 (13.5%)	4.1% (2.1–7.0%)	0.9 (0.4–1.9)
	Gozo and Comino	154 (9.1%)	5 (5.6%)	3.1% (1.0–7.2%)	0.7 (0.2–1.8)
Education level	Primary	478 (30.5%)	30 (36.6%)	5.9% (4.0–8.3%)	Reference
	Secondary	568 (36.2%)	32 (39.0%)	5.3% (3.7–7.4%)	0.9 (0.5–1.5)
	Tertiary	522 (33.3%)	20 (24.4%)	3.7% (2.3–5.6%)	0.6 (0.3–1.1)
Employment status	Employed	705 (41.6%)	32 (35.6%)	4.3% (3.0–6.1%)	Reference
	Retired	776 (45.8%)	44 (48.9%)	5.4% (3.9–7.1%)	1.2 (0.8–2.0)
	Domestic Work	215 (12.7%)	14 (15.6%)	6.1% (3.4–10.0%)	1.4 (0.8–2.7)
Maltese citizens/foreigners	Foreigner	61 (3.6%)	0 (0.0%)	0.0% (0.0–5.9%)	N/A
	Maltese Citizen	1643 (96.4%)	90 (100.0%)	5.2% (4.2–6.3%)
Nationality of parents/grandparents	Maltese	1525 (90.3%)	86 (96.6%)	5.3% (4.3–6.6%)	Reference
	Foreign	164 (9.7%)	3 (3.4%)	1.8% (0.4–5.2%)	0.3 (0.1–1.0)
Either parent foreign	Maltese	1573 (92.7%)	89 (98.9%)	5.4% (4.3–6.5%)	Reference
	Foreign	123 (7.3%)	1 (1.1%)	0.8% (0.0–4.4%)	0.1 (0.0–1.0)

Causes of amblyopia

The overall prevalence rate of anisometropia among the phakic surgically untouched eyes was 22.1% (95%CI 20.0%-24.4%) and the prevalence of strabismus among the TMES population was 1.1% (95%CI 0.6%-1.6%). The prevalence rates of anisometropic, strabismic, and mixed amblyopia were 2.6% (95%CI 1.9%-3.4%), 0.2% (95%CI 0.0%-0.5%), and 0.2% (95%CI 0.1%-0.6%), respectively. The remaining 2.0% of amblyopia cases were either from other or unknown causes. Out of the amblyopia cases, at least 50.6% of the amblyopia cases were likely to be caused by anisometropia (Table 2).

Table 2. The distribution and proportion of presumed amblyopia visual impairment causes by sex and age groups in the adjusted The Malta Eye Study population (n = 1794).

Sex	Age group	Presumed amblyopia cause
		Anisometropia	Strabismus	Mixed	Other	Unknown
Male	50–59	13 (81.3%)	1 (6.3%)	1 (6.3%)	0 (0%)	1 (6.3%)
	60–69	7 (38.9%)	1 (5.6%)	1 (5.6%)	3 (16.7%)	6 (33.3%)
	70–80	8 (47.1%)	0 (0.0%)	2 (11.8%)	0 (0.0%)	7 (41.2%)
	Total	28 (54.9%)	2 (3.9%)	4 (7.8%)	3 (5.9%)	14 (27.5%)
Female	50–59	6 (75.0%)	1 (12.5%)	0 (0.0%)	0 (0.0%)	1 (12.5%)
	60–69	7 (33.3%)	0 (0.0%)	0 (0.0%)	8 (38.1%)	6 (28.6%)
	70–80	4 (44.4%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	5 (55.6%)
	Total	17 (44.7%)	1 (2.6%)	0 (0.0%)	8 (21.1%)	12 (31.6%)
Total	50–59	19 (79.2%)	2 (8.3%)	1 (4.2%)	0 (0.0%)	2 (8.3%)
	60–69	14 (35.9%)	1 (2.6%)	1 (2.6%)	11 (28.2%)	12 (30.8%)
	70–80	12 (46.2%)	0 (0.0%)	2 (7.7%)	0 (0.0%)	12 (46.2%)
	Total	45 (50.6%)	3 (3.4%)	4 (4.5%)	11 (12.4%)	26 (29.2%)

“Mixed” causes include anisometropia and strabismus in the same individual.

“Other” causes included presumed visual deprivation, corrected squint, or pseudophakia-related with anisometropia.

Visual function in amblyopia vs. no visual impairment

Individuals with amblyopia-related visual impairment had slightly lower NEI VFQ composite scores (median 95.9; IQR 91.8–97.7) compared to those without visual impairment (median 96.6; IQR 93.9–98.0). While these differences were statistically significant (p = 0.022), the correlation coefficients were very small (r = 0.061), indicating minimal variance explained. Small, statistically significant differences were also observed in the general vision (r = 0.057; p = 0.031), distance activities (r = 0.062; p = 0.018), mental health (r = 0.053; p = 0.042), colour vision (r = 0.070; p = 0.008), and peripheral vision (r = 0.091; p = 0.001) subscales. Other subscales showed non-significant differences (all r < 0.05).

Discussion

The contribution of amblyopia visual impairment is not usually considered in meta-analysis data, especially since most of its contribution is unilateral visual impairment. In TMES, amblyopia visual impairment was a unilateral condition in 97.8% of times and its contribution to unilateral visual impairment (when defined as > 0.5 logMAR) at 38.8% (95%CI 30.5%-47.6%) seems higher to that of similar studies in populations aged 40+, using > 0.5 logMAR best corrected visual acuity threshold, reporting 18.9% (95%CI 10.7%-29.7%)²⁸ and 15.8% (95%CI 7.5%-27.9%)²⁹. When compared to The Casteldaccia Eye Study, which also used the ICD-11 criteria for visual impairment severity, the amblyopia contribution to unilateral moderate severe visual impairment was similar in both studies (TMES: 34.8%; 95%CI 25.0%-45.7%; Casteldaccia: 29.5%; 95%CI 16.8%-45.2%), but its contribution towards unilateral blindness was higher in TMES (TMES: 45.7%; 95% CI 30.9%-6.0%; Casteldaccia: 3.3%; 95%CI 0.1%-17.25)²⁸. Amblyopia as a cause of unilateral blindness (> 1.0 logMAR) was also lower in studies such as the Blue Mountains Eye Study (13.3%; 95% CI 7.8%-20.7%)³⁰. The higher rates observed in TMES may potentially relate to historically lower availability of vision screening and amblyopia treatment in Malta compared to countries such as Australia, as well as a possible higher prevalence of anisometropia in the same age group in Malta (22.1%) than in Australia (14.1%)³¹. Moreover, unassessed parental factors, such as socioeconomic and educational status, smoking, diet, genetic factors and foetal development in utero could possibly account for such differences in amblyopia rates. Conversely, the similarity with the Casteldaccia Eye Study may reflect comparable healthcare contexts and methodologies.

The 60–69-year age group had double the odds of amblyopia visual impairment vs. no visual impairment compared to the 50–59-year age group. This finding likely reflects differences in childhood eye care provision across age groups, although causality cannot be established. Amblyopia treatment is most effective before the age of 7^{32, 33–34}, and individuals aged 60 years and older during TMES’s data collection period (2021–2024) would generally have passed this critical window before structured paediatric eye care was widely available in Malta.

In the early 1970s, national orthoptic services were introduced and, at the time, refraction in children was performed primarily by orthoptists, with only a small number of ophthalmologists and optometrists providing this service. While strabismus was not the major cause of amblyopia in this population, the shared role of orthoptists in detecting and correcting refractive errors, including anisometropia, suggests that these services may have contributed to a reduction in amblyopia-related visual impairment in younger age groups. However, it is important to note that other explanations are equally plausible, including broader improvements in health literacy, healthcare access, increased accuracy of refractive assessment, and greater availability of corrective lenses.

Similar age-related differences in amblyopia prevalence across age groups have been observed in other populations³⁵, highlighting the complexity of separating the effects of specific healthcare services from broader improvements in paediatric eye care. The decline noted in the 70–79-year group may additionally reflect diagnostic challenges in older adults, survivorship bias, or opportunistic screening during trachoma eradication efforts in the 1940s and 1950s^36–38. These multiple factors highlight the difficulty of attributing age groups differences to any single intervention.

Since there are no management options for amblyopia visual impairment in adulthood, and amblyopia in adulthood reflects previous childhood eye care, TMES’s amblyopia findings can suggest further investigation of amblyopia prevalence in childhood in Malta. Apart from the orthoptic department setup in the early 1970s, Malta has also seen the introduction of childhood screening³⁹ and paediatric ophthalmology services over the past 30 years. As a result, lower amblyopia prevalence rates are expected in both the current younger population and the future older generations. The absence of prevalence data in current younger age groups in Malta limits direct comparison, and further research on current amblyopia and visual impairment rates in children and young adults would help quantify the impact of improved paediatric eye care services.

The causes of amblyopia in the TMES population were similar to those reported in other populations^30,40], with anisometropia as the predominant factor. However, its true prevalence may be underestimated because of limitations in accurately identifying past paediatric anisometropia in this older population.

Although individuals with amblyopia-related visual impairment reported statistically significant reductions in several NEI VFQ domains, the magnitude of these differences was very small (all r² values < 0.01) and below the threshold generally considered clinically meaningful (≈ 3 points on the NEI VFQ scale)⁴¹. This suggests that while subtle quality-of-life differences may be detectable in large samples, amblyopia has only a limited impact on vision-related quality of life in adulthood. These findings should be interpreted cautiously given the exploratory nature of multiple comparisons and the minimal variance explained by the observed effects. A smaller Munich study found no differences⁴², our larger sample size likely enabled detection of these small effects, though their clinical importance remains limited.

Strengths and limitations

The strengths of this study include its large, population-based design, evaluation of functional outcomes such as vision-related quality of life, and its focus on amblyopia in older adults, a group often underrepresented in research. The study was also clinician-led, with all examinations conducted by the same specialist, minimising inter- and intra-observer variability¹⁶, and enhancing the robustness of the findings.

In some cases, coexisting ocular conditions (e.g., cataracts) may have contributed to visual loss, confounding the role of amblyopia. To minimise misclassification, a stricter threshold of > 0.3 logMAR was used, rather than the > 0.2 logMAR typically applied in paediatric settings^3,43], to enhance specificity in adults.

Classifying amblyopia causes in older adults is challenging because age-related ocular changes obscure the original aetiology. Cataract surgery and lens changes can mask or induce anisometropia, whereas lifetime refractive shifts further complicate the identification of anisometropic amblyopia. Strabismus classification is limited by changes in alignment, surgical history, and natural evolution over time. Strabismus assessment relied on the Hirschberg test, which may have underestimated small-angle deviations. Additionally, degenerative changes in amblyopic eyes, particularly in those with high myopia, can mimic or mask amblyopia-related vision loss. The lack of pre-and postoperative cataract refractive data, availability of binary childhood vision loss history, and absence of detailed squint records limited precise causal attribution. As a result, anisometropic amblyopia may have been underreported, particularly in pseudophakic individuals. Future prospective studies with longitudinal data and comprehensive ocular histories are needed to improve classification accuracy, as the retrospective design limits causal inference owing to potential bias, confounding, and unclear temporal relationships.

A limitation of TMES is the lack of comparative prevalence data in younger age groups, such as those aged 20–30, who have had the benefit of modern paediatric eye care services. Future studies assessing visual impairment and amblyopia prevalence in these younger generations are required to contextualise the improvements achieved in childhood eye health.

This study used participants’ employment status and educational level as proxy measures for socioeconomic circumstances. However, parental socioeconomic status would have been a more accurate indicator for amblyopia, as current status may not reflect childhood healthcare access.

Conclusion

Amblyopia remains an important cause of visual impairment in older adults, though rates appear lower in individuals aged 50–59 compared to older age groups. Further research in younger populations, including children, is needed to determine whether prevalence continues to decline and to explore the potential impact of improved early detection and paediatric eye care.

Acknowledgements

We thank the management at the Mater Dei and Gozo General Hospitals for their study support and Mr. Martin Francalanza and Ms. Alexandra Fsadni for their insights on orthoptic services. We also acknowledge the support of Mr. Nicolai Schembri and Mr. Christian Attard for IT services, Mr. Stefan Attard for the invitation design, and Dr. George Farrugia for translation services. We thank Dr. John Cachia for sharing his past research experience and to all staff, volunteers, and assistants involved in data collection. Special thanks to Mrs. Marilyn Grech for her vital logistical support throughout this study.

Author contributions

Conceptualisation: Prof Francis Carbonaro, Dr David Agius, Methodology: Dr David Agius, Formal analysis and investigation: Dr David Agius, Data curation: Dr David Agius, Ms Maria Elena Pace, Ocular assessments and imaging: Dr David Agius, Anthropometric assessments and questionnaire administration: Dr Daniel Cassar, Dr Maria Christina Nappa, Dr Michaela Zammit, Participant recruitment: Dr Xeniya Marku, Resources: Prof Francis Carbonaro, Writing—original draft preparation: Dr David Agius, Writing—review and editing: Prof Julian Mamo, Prof Neville Calleja, Prof Francis Carbonaro, Funding acquisition: Prof Francis Carbonaro, Supervision: Prof Francis Carbonaro, Prof Julian Mamo, Prof Neville Calleja.

Funding

Funding for Dr David Agius: (1) The Malta Community Chest Fund (MCCF), coordinated by the University of Malta’s Research, Innovation and Development Trust (RIDT), provided funding amounting to EUR 132,000. This covered equipment, publication and conference costs, and a stipend to Dr. David Agius under a University of Malta Scholarship agreement (30/01/2019, agreement 20190304). (2) Tertiary Education Scholarship Scheme (TESS) funded Dr. Agius’s tuition. (3) Prohealth Ltd^® Malta provided stationery and postage. (4) Class Optical^® supplied participant gifts. None of the funders were involved in the study’s design, data, or manuscript decisions. The other authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability

Dr. David Agius has full data access and is responsible for data integrity and analysis. Data are not publicly available but may be shared with approved bodies upon ethical clearance.

Declarations

Competing interests

The authors declare no competing interests.

Consent to participate

Written informed consent was obtained, and the data were pseudonymised.

Consent to publish

The manuscript does not have any distinguishable individual persons’ details, images or video. All data is pseudonymised and presented as a population-based cohort, and written consent has been obtained from every participant for publication.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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