Prevalence and risk factors of keratoconus among school children in Oman: a population-based study

Abstract

Background

To investigate the prevalence and risk factors of keratoconus (KC) among Omani school children.

Methods

The cross-sectional, population-based, descriptive design study assessed a cohort of school students, aged 9 to 18 years from the Al Buraimi Governorate of Sultanate of Oman. They underwent comprehensive ocular examination, including auto-kerato-refractometry (ARK), retinoscopy, and corneal topography. Firth’s penalized (bias-reduced) logistic regression was used to identify independent predictors of KC and keratoconus suspect (KCS) status.

Results

A total of 733 students participated (mean age 13.95 ± 2.19 years) and 67.4% were males. The prevalence of KC was 1.6% (95% CI: 0.85% – 2.84%), and 5.0% (95% CI: 3.58% – 6.89%) were classified as keratoconus suspect (KCS). Frequent eye rubbing (OR = 12.89, 95% CI: 3.45–70.12; p < 0.001) and parental consanguinity (OR = 14.74, 95% CI: 3.36–138.98; p < 0.001) were significant independent predictors of KC (model AUC = 0.91). No covariate was independently associated with KCS status after adjustment (model AUC = 0.60).

Conclusion

Keratoconus prevalence in this Omani school-age cohort is consistent with reports from the Middle East and, confirms a higher burden than in Western populations. Consanguinity and frequent eye rubbing as significant predictors of KC emphasize the value of genetic counselling and risk-factor awareness.

Background

Keratoconus (KC) is an ectatic corneal disorder with multifaceted etiology and pathogenesis [1]. The resulting progressive corneal changes range from irregular myopic astigmatism to corneal scarring and may potentially lead to severe visual impairment [1, 2]. Pediatric KC has more severe presentation, rapid progression and higher odds of developing corneal hydrops and corneal opacity. This increases the risk of severe visual disability and the need for early clinical intervention.

The prevalence of pediatric KC varies widely across ethnic populations and geographical regions [3, 4]. The prevalence rate varies from a very low rate in the western populations to significantly higher rates in regions with greater genetic and environmental susceptibility such as Middle East, South Asia and Africa [4–7]. Recent reports indicate that the prevalence of KC in pediatric / school-aged population ranges from 0.02 to 0.52% in some Russian and New Zealand cohorts [8–10], to 0.7–1.7% in Brazil [11] and Kenya [12] and up to 2.0–5.5% in the Middle-Eastern region [7, 13–16]. Despite growing recognition of KC as a major pediatric eye health concern, epidemiological data is limited from the parts of the Arabian Peninsula.

Across populations, the most prevalent predisposing factors for KC are vigorous eye rubbing [17, 18], genetic susceptibility (family history/consanguinity) [19–21] and atopic/allergic diseases [17, 18, 20] and a strong contributing evidence of dry climates [19, 22, 23]. Such environmental factors trigger or accelerate KC in genetically susceptible corneas. These predisposing factors like genetic susceptibility, and dry and dusty environmental conditions are actively prevalent in Oman. The current best estimate of KC prevalence (among young adults) in Oman is 3.5%, and it is observed that a significant proportion of cases are detected at advanced stages, with variations noted across geographic regions in the country [24, 25]. These patterns highlight the need for targeted screening strategies and early detection. Therefore, the present study aims to determine the prevalence of KC among pediatric population in a governorate in Oman to contribute epidemiological evidence to guide early screening and management.

Methods

Study design

This study employed a cross-sectional, population-based descriptive design conducted in the Sultanate of Oman between January 2025 and January 2026.

Geographical area description

The Sultanate of Oman is located in the southeastern corner of the Arabian Peninsula, bordered by the United Arab Emirates, Yemen, and Saudi Arabia with extensive coastal lines, desert and mountain ranges in the interiors. It influences community settlement patterns and environmental exposures [26]. Culturally, the Sultanate is characterized by a blend of Arab, Islamic and maritime traditions. Social structures are community-oriented, with strong family ties. Oman experiences mostly arid and semi-arid conditions, with high temperatures, low humidity in interior regions, and seasonal dust and sand exposure [27]. Ultraviolet radiation levels are high year-round. This study was conducted in the Al-Buraimi governorate located in the northwestern part of Oman, bordering the United Arab Emirates.

Study setting and sample

The study consists of school children attending 12 government schools from grades 4 to 12 within the three wilayat of Al-Buraimi Governorate. A stratified cluster and random sampling method was adopted to identify the required number of samples from each school as subgroups. Sample size was calculated using the formula for estimating a population proportion (n = Z²p(1 − p)/d²), based on a 95% confidence level, an expected KC prevalence of 3.5% [7, 13–15], and a precision of ± 1.75%, bringing in a base sample size of 424. This was inflated by a design effect of 1.5 to account for cluster sampling and further adjusted for an anticipated 10% nonresponse rate, giving a minimum required sample of approximately 700 participants. Consent forms were distributed to parents and those who were agreed upon were only included in the study. In instances where a child was absent from school during the screening process, the next eligible child was recruited for the study. No financial or material compensation was provided for the participants.

Study procedure

Enrolled students first completed a structured questionnaire including family history of KC, history of eye rubbing, allergy and parental consanguinity. Participants then underwent a comprehensive ocular assessment in a standardized screening setting within the school by trained optometrists. The examination included uncorrected, presenting and pinhole visual acuity (VA) using logMAR charts at 4 m. The objective refraction was conducted using an Autorefracto-Keratometry (Auto Ref/Keratometer ARK-F). The ocular media was then scanned using a retinoscope (HEINE BETA 200) primarily to identify the presence of scissor reflex suggestive of irregular astigmatism. All the participants underwent corneal topography using OS1000 Corneal Topographer (SBM Sistemi, Italy) and three consecutive measurements were obtained for each eye. Scans of suboptimal quality or with evident artifacts were repeated. Only high-quality and reliable scans as identified by the topographer were included in the final analysis. All topographic image analysis were conducted by a single trained optometrist to eliminate inter-examiner variability.

Criteria for classifying KC types

Participants were classified as having keratoconus (KC) or keratoconus suspect (KCS) using predefined screening (clinical and topographic) criteria (Table 1) [3, 28–31]. A diagnosis of KC was made when participants met at least two of the four clinical assessment criteria (topography, autorefractor-keratometry, retinoscopy, and refractive profile). To satisfy the topography criterion, all four targeted topographic parameters had to be present (Table 1).

Table 1.

Criteria utilized to classify KC and KCS

Screening tests	Targeted Parameters	KC Cutt-off Value	KCS Cutt-off Value
Topography	Mean K	≥ 47.2 D	At least two out of three topographic parameters [1. Presence of asymmetric bow-tie pattern, 2. I-S index ≥ 1, 3. SAI ≥ 0.7]
	I-S value	≥ 1.4 D
	SAI value	1.25
	Asymmetrical bow tie pattern	Present
Auto-Refractokeratometry	Mean K	≥ 47 D	≥ 45 D
Retinoscopy	Scissor Reflex	Present	Present
Refractive profile	Refractive error	≥ -5.0 D and or astigmatism	Astigmatism > 1.5 D
	Irregular Astigmatism	> 1.5 D

Participants were classified as KCS if they demonstrated a scissor reflex on retinoscopy. In addition, individuals were classified as KCS if they simultaneously met all three of the following criteria: (1) astigmatism > 1.00 Dioptre (D), (2) mean keratometry > 45.00 D, and (3) at least two of the following topographic features: asymmetric bow-tie pattern, inferior–superior (I–S) index ≥ 1, or surface asymmetry index (SAI) ≥ 0.7. These criteria were adapted collectively from published screening and validity studies, most closely Chaurasia et al. [30]. This school-based paediatric cohort (aged 9–17) closely matched with our population, setting and instrumentation. The cut-off values were cross-checked against the Youden-Index-optimised values reported by Rashid et al. [28] and the topographic-asymmetry framework described by Klyce [29] and Masiwa and Moodley [31]. Where source studies reported slightly different optimal cut-offs (e.g., irregular astigmatism > 1.5 D versus > 2.50 D), we adopted the more conservative, higher-sensitivity value given the suspect-inclusive, school-screening context of the present study.

Statistical analysis

Data was analyzed using SPSS version 31 (IBM Cor., Armonk, NY, USA). Participant demographics were summarized using descriptive statistics (mean ± SD or frequencies). Ocular parameters between KC, non-keratoconus (non-KC) and KCS were assessed using Kruskal-Wallis test along with Mann-Whitney U test for post-hoc pairwise comparisons with appropriate adjustments for multiple testing. Given the low number of KC events relative to the number of predictors (events-per-variable = 1.5 for the KC model), the Firth’s penalized (bias-reduced) logistic regression analysis was performed to identify independent predictors of KC. Results were reported as odds ratios (OR) and 95% confidence intervals (CI). The statistical significance was kept at p<0.05. Since the participants were sampled from schools selected by cluster sampling, we additionally evaluated the impact of the clustered design on both the regression analysis (Table 4) and the Kruskal-Wallis comparisons (Table 3).

Table 4.

Firth penalized logistic regression predicting KCS/KC and risk factors

Predictor variables	KCS				KC
	p	df	OR Exp[B]	95% CI for OR	p	df	OR Exp[B]	95% CI for OR
Eye rubbing – occasional	0.09	1	1.87	(0.91–3.92)	0.77	1	0.74	(0.07–5.69)
Eye rubbing – frequent	0.41	1	1.51	(0.54–3.83)	< 0.001*	1	12.89	(3.45–70.12)
Consanguinity	0.54	1	1.24	(0.62–2.40)	< 0.001*	1	14.74	(3.36–138.98)
Age	0.14	1	1.13	(0.96–1.33)	0.12	1	1.24	(0.95–1.71)
Gender	0.38	1	1.38	(0.66–2.80)	0.45	1	0.60	(0.14–2.18)
Goodness-of-fit statistics (Firth penalized log-likelihood based)
Statistic	Value				Value
AUC (C-statistic)	0.602				0.905
McFadden R2	0.064				0.394

p<0.05* 

A cluster-robust sensitivity analysis confirmed all group differences reported as statistically significant above

Table 3.

Ocular parameter comparisons among KC, non-keratoconus (NKC) and KCS groups (Median and IQR)

Parameters	Eye	NKC (n = 684) Median (IQR)	KCS (n = 37) Median (IQR)	KC (n = 12) Median (IQR)	p-value (KCS/NKC)	p-value (KC/NKC)
Unaided VA (log MAR)	OD	0.00 (0.00–0.20)	0.24 (0.00–0.40)	0.30 (0.10–0.60)	0.000	0.001
	OS	0.00 (0.00–0.16)	0.30 (0.00–0.50)	0.20 (0.10–0.32)	0.000	0.005
SER (D)	OD	0.00 (-0.40–0.00)	-0.25 (-1.25–0.00)	-1.50 (-1.75 – -0.10)	0.012	0.006
	OS	-0.25 (-0.25–0.00)	-0.25 (-1.13 – -0.13)	-1.50 (-2.00 – -0.06)	0.004	0.023
Astigmatism (D)	OD	-0.50 (-0.50 – -0.25)	-0.75 (-1.50 – -0.25)	-1.00 (-2.25 – -0.31)	0.001	0.023
	OS	-0.50 (-0.50 – -0.25)	-0.50 (-1.50 – -0.38)	-1.75 (-2.69 – -0.56)	0.001	0.001
Auto-Refractokeratometry (D)	OD	43.71 (42.53–44.76)	44.32 (43.43–45.32)	47.51 (45.57–48.13)	0.024	0.000
	OS	43.55 (42.43–44.78)	44.29 (43.12–45.24)	46.87 (45.75–47.12)	0.282	0.000
Topography mean K (D)	OD	45.13 (43.95–46.46)	46.33 (44.78–48.32)	48.80 (47.12–53.65)	0.002	0.000
	OS	45.23 (43.99–46.46)	46.00 (44.48–47.82)	49.31 (48.23–51.25)	0.087	0.000
SAI	OD	0.66 (0.43–0.88)	0.86 (0.48–1.10)	0.81 (0.41–3.22)	0.126	0.263
	OS	0.58 (0.35–0.84)	0.51 (0.35–0.79)	0.64 (0.38–2.25)	0.761	0.133
I-S value	OD	0.19 (-0.09–0.45)	-0.03 (-0.29–0.48)	0.59 (-0.28–1.43)	0.420	0.594
	OS	0.19 (-0.12–0.46)	0.12 (-0.23–0.40)	0.17 (0.10–0.91)	0.669	0.148

NKC = Non-keratoconus, KC=keratoconus, KCS=keratoconus suspect, IQR = Interquartile range, VA=visual acuity, SER=spherical equivalent refraction, D=diopter, SAI=surface asymmetry index, I-S value: Superior inferior power difference, OD=Right eye, OS=Left eye

A cluster-robust sensitivity analysis confirmed all group differences reported as statistically significant above

Results

Data from 733 schoolchildren from the Al Buraimi Governorate including its three Wilayats (Al Buraimi, Mahdha, and Al Sunaina) were analysed to identify and clinically characterize participants into normal, KC and KCS. The demographic characteristics of the study participants are presented in Table 2. The mean age of participants was 13.95 ± 2.19 years, and students were grouped into 9–12 and 13–18 years categories. Most participants were male (67.4%) and Omani nationals (87.4%).

Table 2.

Participant demographics and prevalence of KC and KCS (n = 733)

Demographics		Number n (%)	KC prevalence n (%)	KCS prevalence n (%)	p value
Nationality	Omani	641 (87.4)	11 (1.7)	34 (5.3)	0.54
	Non-Omani	92 (12.6)	1 (1.1)	3 (3.3)
Wilayats	Al Buraimi	477 (65.1)	7 (1.5)	17 (3.6)	0.00
	Mahdha	224 (30.6)	5 (2.2)	20 (8.9)
	Al Sunaina	32 (4.4)	0	0
Gender	Male	494 (67.4)	9 (1.8)	24 (4.9)	0.43
	Female	239 (32.6)	3 (1.3)	13 (5.4)
Age groups (years)	9–12	187	0	5 (2.7)	0.02
	13–18	546	12 (2.2)	32 (5.9)
Total		733	12 (1.6)	37 (5.0)

Twelve participants (1.6%) failed two or more screening tests (as specified in Table 1) and were classified as KC (prevalence = 1.6%; 95% CI: 0.85%–2.84%). KC prevalence was higher among males (9 cases) and in the 13–18 age group (all 12 cases). Based on the KCS criteria outlined in Tables 1 and 37 participants (5.0%) were classified as KCS. Prevalence was higher among females (13 cases; 5.4%) and in the 13–18 years age group (32 cases; 5.9%). Additional information is available in Table 2.

Comparisons among NKC, KCS, KC were performed using the Kruskal–Wallis test due to non-normal data distribution. When a significant omnibus effect was detected, post hoc pairwise comparisons were conducted using the Mann–Whitney U test. Results are presented as median values with interquartile ranges for right (OD) and left (OS) eyes (Table 3).

A significant difference between groups were observed for unaided visual acuity (logMAR) in both eyes (p < 0.001), spherical equivalent refraction (p < 0.05) and astigmatism (p < 0.01). The post hoc analyses showed poorer visual acuity, increasing myopia and higher astigmatism in the KCS and KC groups compared to NKC group. Average keratometry also differed significantly (p < 0.05); in the OD, both KCS (p = 0.024) and KC (p < 0.001) had steeper corneas than NKC, while in the left eye only KC remained significantly steeper (p < 0.001). There were no significant differences observed for surface asymmetrical or irregularity indices (p > 0.05), though greater variability was seen in the KC group. The OD and OS values reported for SER, astigmatism and auto-keratometry represent independent group means for each eye rather than paired within-patient inter-ocular comparisons. Therefore, it did not capture the inter-ocular asymmetry for the compared groups. The asymmetry is reflected in the topography-derived indices (SAI and I–S value), which were numerically higher in the KC group though not statistically significant. It reflects the limited power of the small KC sample in this study.

The Firth penalized logistic regression was used to identify independent predictors of keratoconus. The model included gender, age, consanguinity, and eye rubbing (occasional and frequent) as covariates (Table 4). The regression analysis identified parental consanguinity (OR = 14.74, 95% CI: 3.36-138.98.; p<0.001) and frequent eye rubbing (OR = 12.89, 95% CI: 3.45–70.12.; p<0.001) as the strongest predictors of KC. No predictor reached significance in the KCS model. Age and gender were not significant in either model (p > 0.05) too. A cluster-robust sensitivity analysis confirmed the significance of consanguinity and frequent eye rubbing for KC. For the ocular parameters in Table 3, design effects ranged from 1.28 to 5.22, and all group differences reported as significant remained significant (p < 0.0001) under the cluster-robust sensitivity test. Therefore, it confirms that these findings are not artifacts of the clustered sampling design.

Discussion

This study represents the first population-based investigation of school children in the Sultanate of Oman aimed at estimating the prevalence of KC. It revealed a comparable prevalence rate reported from the region. Consanguinity emerged as a significant predictor for KC, in addition to frequent eye rubbing.

Although the overall reported prevalence of KC in this study was 1.6% (95% CI: 0.85%–2.84%), it is important to note that no cases were identified among children aged 9–12 years, and all cases occurred in the 13-18-year age group. It is consistent with an age-related increase in KC prevalence during adolescences. However, the cross-sectional design does not establish disease progression over time. When analysis is restricted to 13–18 years subgroup, the effective prevalence becomes 2.2% (12/546), closely aligning with reports from comparable age groups in Saudi Arabia (2.75%) and the United Arab Emirates (2.7%). These findings reinforce evidence that KC prevalence in Middle Eastern adolescents is higher than that reported in western populations. Population- and school-based studies from outside the middle east show substantial variation in keratoconus prevalence. They range from 0.09% in Russia [9] to 1.7%in Kenya [12], with estimates of 0.52% in New Zealand [10], 0.5% in Trinidad [32], and 1.2% in Australia [33]. The present 2.2% among 13–18-year-olds is therefore toward the higher end of estimates reported outside the Middle East. However, such comparisons require caution, as prevalence estimates can vary according to diagnostic criteria and thresholds. A recent population-based cohort revealed a prevalence estimate ranging from 0.19% to 9.29% when ten published KC definitions were applied on the same studied cohort. It highlights the substantial influence of case definitions and diagnostic thresholds on the reported prevalence [34].

This age-specific pattern is consistent with prevalence estimates reported among young adults in the region. Studies have documented rates of 2.34% among young volunteers in Israel [35], 3.3% among medical students in Lebanon [36], 2.5% in a population-based study from Iran [37], 3.18% among Israeli college students [38], 1.5% among Palestinian youth [39], 2.4% among university students in Turkey [40], and 1.43% among Syrian university populations [41]. Taken together, these findings could reiterate KC as an important ocular health burden affecting adolescents and young adults across the Middle East, underscoring the need for proactive school and clinic-based screening in the region.

Consanguinity and frequent eye rubbing were associated with KC. While the association with eye rubbing aligns with global evidence [20, 42], the prominence of consanguinity reflects patterns more commonly reported in Middle Eastern populations [19, 43, 44]. These findings suggest that consanguinity may be associated with KC risk in this population, consistent with a potential genetic contribution. However, the cross-sectional design precludes causal inference. Across the Middle East and North Africa, an estimated 20–56% of marriages are consanguineous, significantly higher than the global average of 1–9% [45, 46]. Rates of approximately 50% or higher have been reported in several countries, including Saudi Arabia, Qatar, the United Arab Emirates, Oman, Jordan, and parts of Egypt, signifying a potential role of genetic susceptibility in KC within this region [47]. Although consanguinity and eye rubbing were treated as independent predictors, residual confounding cannot be excluded. For instance, unmeasured degree of genetic relatedness, shared environmental exposures among consanguineous families, or an underlying allergic condition, etc. may independently affect both eye-rubbing behaviour and corneal biomechanics.

This study has some limitations to report. First, since this study is cross-sectional, temporal relationships between the identified risk factors (e.g., consanguinity and eye rubbing) and KC cannot be established. Therefore, the observed associations should not be interpreted as causal. Second, the topographer utilized for screening did not provide posterior corneal profile; thus, children exhibiting only posterior corneal steepening may have missed, potentially causing an underestimation of prevalence. Third, the relatively smaller number of KC cases limited the statistical power of regression analyses and reduced the precision of confidence interval estimates. Fourth, the information on eye rubbing and allergy was obtained through self- or parent reports. This might have resulted in recall bias. Fifth, the numeric thresholds used to classify KC and KCS were adapted from published paediatric and adolescent screening cohorts. The combined multi-parameter approach applied here has not itself been independently validated against a gold-standard tomography-confirmed diagnosis in an exclusively paediatric sample. Sixth, although absent children were replaced with the next eligible participant, non-participation due to parental non-consent may have introduced selection bias.

Conclusion

The prevalence rate of keratoconus reported in this study is consistent with the reports from the Middle Eastern region and confirms a higher burden compared to the west. The significant association between consanguinity and KC is matching with regional patterns and highlights the need for greater attention to genetic counselling and risk awareness. These findings support further evaluation of targeted screening strategies in high-risk pediatric populations.

Author contributions

MZ conceived and designed the study. All authors collected the clinical data. MZ, GV, and BN analyzed and interpreted the patient data. MZ and BN prepared the manuscript draft, while JA and GV critically revised the manuscript for significant intellectual content. All authors reviewed and approved the final manuscript. Z.M & B.N wrote the main manuscript text and prepared tables and data analysis. Z.M, G.V, J.A and A.A participated in data collection and entering. Z.M & B.N. guided the article; All authors reviewed and approved the final manuscript.

Funding statement

This research project was funded by the Ministry of Education, Sultanate of Oman through the Block Funding Program under No. BFP/RGP/HSS/24/287.

Data availability

The authors affirm that all pertinent data is incorporated within the article. The data supporting the study’s findings can be obtained upon request from the corresponding author.

Declarations

Ethical approval

Ethical approval was granted by the College Research Committee of the College of Health Sciences, University of Buraimi under No. AY24-25COHS-083 which adhered to the tenets of the Declaration of Helsinki. Authorization to conduct the study in schools was obtained from the Directorate General of Education in Al Buraimi Governorate. Written informed consent was collected from parents or guardians before including students, and the study procedures were explained to the children before assessment.

Consent for publication

Not applicable.

Declaration of generative AI and AI-assisted technologies in the manuscript preparation

During the preparation of this work the author(s) used PAPERPAL to improve language clarity and readability. After using this tool, the author(s) reviewed and edited the content as needed and took full responsibility for the content of the published article.

Competing interests

The authors declare no competing interests.