Hostname: page-component-7b7567c8c-fvjsw Total loading time: 0 Render date: 2026-11-14T04:32:59.915Z Has data issue: false hasContentIssue false
  • English
  • Français

Dry Eye Symptoms Among Adults Aged 40 Years and Older in Gaza During Humanitarian Crisis: Prevalence and Associated Factors

Published online by Cambridge University Press:  02 October 2026

Mohammed Aljarousha,
Mohd Zulfaezal Che AzeminOpen the ORCID record for Mohd Zulfaezal Che Azemin[Opens in a new window],
Ithar M. Beshtawi,
Noor Ezailina Badarudin,
Bilal Irfan,
Mustafa Abdu,
Emad I. H. Shaqoura,
Nur Azalina Suzianti Feisal,
Asmaa Y. Abuhamad and
Baqiatu’l Sabiqi ’Assfi Rahmat
...Show all authors
Mohammed Aljarousha
Affiliation:
Department of Optometry, Rehabilitation & Well-Being, Faculty of Health and Life Sciences, Management and Science University , Shah Alam, Selangor, Malaysia
Mohd Zulfaezal Che Azemin*
Affiliation:
Integrated Omics Research Group, Kulliyyah of Allied Health Sciences, International Islamic University Malaysia , Kuantan, Pahang, Malaysia
Ithar M. Beshtawi
Affiliation:
Optometry Department, Faculty of Medicine and Medical Allied Sciences, An-Najah National University , Nablus, West Bank, Palestine
Noor Ezailina Badarudin
Affiliation:
Department of Optometry, Rehabilitation & Well-Being, Faculty of Health and Life Sciences, Management and Science University , Shah Alam, Selangor, Malaysia
Bilal Irfan
Affiliation:
University of Michigan , Ann Arbor, MI, USA
Mustafa Abdu
Affiliation:
Department of Optometry, College of Applied Medical Sciences, University of Jeddah , Jeddah, Saudi Arabia
Emad I. H. Shaqoura
Affiliation:
Department of Biomedical Sciences, College of Medicine and Health, University of Birmingham , Birmingham, UK
Nur Azalina Suzianti Feisal
Affiliation:
MSU Centre for Climate Resilience and Strategy (M-CREST), Management and Science University , Shah Alam, Selangor, Malaysia
Asmaa Y. Abuhamad
Affiliation:
Department of Diagnostic and Allied Health Science, Faculty of Health Sciences, Management and Science University , Shah Alam, Selangor, Malaysia
Baqiatu’l Sabiqi ’Assfi Rahmat
Affiliation:
Department of Optometry, Rehabilitation & Well-Being, Faculty of Health and Life Sciences, Management and Science University , Shah Alam, Selangor, Malaysia
Mohd Arifin Kaderi
Affiliation:
Department of Biomedical Science, Kulliyyah of Allied Health Sciences, International Islamic University Malaysia , Kuantan, Pahang
Mohamed Tawfik
Affiliation:
Memorial Institute of Ophthalmic Research, Cairo, Egypt
Omair Muhammad Qazi
Affiliation:
Department of Optometry and Vision Sciences, The University of Lahore , Lahore, Pakistan
Sara Attaallah
Affiliation:
School of Graduate Studies, Postgraduate Centre, Management and Science University , Shah Alam, Selangor, Malaysia
*
Corresponding author: Mohd Zulfaezal Che Azemin; Email: zulfaezal@iium.edu.my
Rights & Permissions [Opens in a new window]

Abstract

Background

Dry eye disease (DED) affects visual function and quality of life. In Gaza, conflict, displacement, environmental exposure, and psychological distress may increase risk, but evidence is limited. This study estimated DED symptom prevalence among adults aged ≥40 years and examined associated factors.

Methods

A community-based cross-sectional convenience sample of 296 adults aged ≥40 years living in houses, shelters, or tents in Gaza was surveyed face-to-face. Arabic OSDI assessed symptoms (≥13) and severe symptoms (≥33). Psychological distress was measured using the Arabic DASS-8. Exploratory analyses examined continuous OSDI scores, housing type, geographic/displacement context, and the OSDI environmental-trigger domain. Adjusted associations were evaluated using regression models with robust standard errors.

Results

Overall, 97.3% of participants had DED symptoms. Living in tents (PR 1.05, 95% CI 1.01-1.10; P = 0.024) and age ≥70 years (PR 1.05, 95% CI 1.00-1.09; P = 0.028) were associated with slightly higher prevalence. Higher DASS-8 scores were associated with greater continuous OSDI scores and more severe symptoms. Participants in the South/displaced group had greater symptom burden than those surveyed in the North.

Conclusion

DED symptoms were nearly universal in this convenience sample. Greater symptom burden was associated with psychological distress and displacement context, although specific environmental exposures were not measured directly.

Keywords

dry eye diseaseaged ≥ 40 yearsOSDIDASS-8tentsshelters

Information

Type
Original Research
Information
Disaster Medicine and Public Health Preparedness , Volume 20 , 2026, e176
Copyright
© The Author(s), 2026. Published by Cambridge University Press on behalf of Society for Disaster Medicine and Public Health, Inc

Background

Dry eye disease (DED) is one of the most common ocular conditions encountered in ophthalmic practice and represents a growing global public health concern due to its detrimental effects on vision-related quality of life.Reference Marculino, Hazarbassanov and Hazarbassanov1–Reference Noor, Rahayu and Gondhowiardjo3 It is a multifactorial disorder of the tear film and ocular surface, characterized by symptoms such as dryness, irritation, burning, photophobia, ocular fatigue, and fluctuating vision.Reference Cai, Wei and Zhou4–Reference Bartlett, Keith and Sudharshan6 DED is generally classified into aqueous-deficient and evaporative subtypes.Reference Vidal-Rohr, Craig and Davies7

A range of risk factors has been associated with DED, including older age, female sex, hormonal therapy, smoking, prolonged digital screen use, contact lens wear, systemic comorbidities, and medications that disrupt tear film stability.Reference Deo and Nagrale8–Reference Stapleton, Alves and Bunya15 Studies from the Middle East, including Palestine, also indicate a substantial burden of DED symptoms in the region.Reference Mohamed, Alrasheed and Abdu16

The Gaza Strip presents a unique context in which biological, psychological, and environmental contributors to DED coexist at extreme levels. Years of protracted conflict have resulted in high rates of anxiety, depression, and trauma-related stress.Reference Clayton17–Reference Lazreg, Hosny and Ahad18 Psychological distress is increasingly recognized as a contributor to ocular surface dysfunction through mechanisms involving autonomic dysregulation, inflammatory activation, altered blinking patterns, and sleep disturbance—all of which can worsen DED.Reference Aljarousha, Alghamdi and Che Azemin19

Since the escalation of violence on October 7, environmental conditions in Gaza have sharply deteriorated. Persistent bombardment has generated dense smoke, ash, particulate debris, and widespread structural destruction producing fine dust. Overcrowded shelters with poor ventilation, low humidity, and limited access to clean water further contribute to tear film instability and ocular surface irritation.Reference Hassoun, Parra-López and Ben Hassen20–Reference Dardona, Amane and Dardona21

Despite the convergence of severe psychological and environmental stressors, population-based data on DED in Gaza remain extremely limited. This knowledge gap is especially critical among adults aged ≥40 years, who may be more vulnerable to ocular morbidity under such conditions. Adults aged ≥40 years were selected because dry eye symptoms and ocular surface dysfunction are known to increase with age, and a previous regional population-based study specifically assessed dry eye disease among adults aged 40 years and older.Reference Yasir, Chauhan and Khandekar24, Reference Wang, Muntz and Lim29

Therefore, this study aimed to estimate the prevalence of DED symptoms in a community-based convenience sample of adults aged 40 years and older living in the Gaza Strip, identify associated risk factors—including psychological distress and environmental exposures—and examine their relationship with visual impairment within the context of the ongoing humanitarian crisis.

Methods

Study Design

The study was undertaken and reported in accordance with the STROBE guidelines (Appendix 1). It was a cross-sectional study using a convenience sampling method, conducted in houses, shelters, and tents across 20 communities in the Northern Gaza Strip, as well as among participants who were forcibly evacuated to the Southern Gaza Strip, Palestine. Data were collected using a hardcopy survey distributed face-to-face due to limited internet access and electricity. Participants were approached in person by the research team/data collectors at accessible community locations, including houses, shelters, and tents. Eligibility was assessed before enrolment based on age, residence during the study period, ability to complete the demographic, dry eye symptom, and psychological distress assessments, and willingness to provide written informed consent. Convenience sampling was used because probability-based sampling was not feasible under the prevailing humanitarian conditions, including restricted movement, security concerns, displacement, and limited communication infrastructure. The survey included demographic information and other potentially associated factors, such as sex, age, medical conditions, and current use of medications. Additional questions assessed the severity of dry eye symptoms and psychological distress. Written informed consent was obtained from all participants. Written informed consent was obtained from all participants.

Because participants were recruited using convenience sampling under conflict-related constraints, the findings should be interpreted as describing the study sample rather than as population-representative estimates for all adults aged ≥40 years in Gaza.

The sample size was calculated using the prevalence of dry eye symptoms based on the OSDI among Gazan adults (87.9%).Reference Aljarousha, Azemin and Ariffin22 The minimum required sample size was determined to be 130 participants using the formula

$$ n=\frac{Z^2\cdotp p\cdotp \left(1-p\right)}{d^2} $$ n equals numerator Z-squared dot p dot (1 minus p) all over denominator d-squared

with a precision/absolute error (d) of 5% and a type I error of 5% (p < 0.05). However, the actual sample size was increased to 296 participants, ensuring more robust and reliable estimates.

Categorical variables included sex and geographic group, defined according to current residence and displacement status. Participants were categorized as: (1) residents currently living in the Northern Gaza Strip, and (2) residents originally from the North who had been forcibly evacuated to the Southern Gaza Strip during the 2023 conflict. Within these groups, participants were also classified by housing type: tents, shelters (including public buildings or United Nations facilities), or houses. The final distribution of participants was 200 residents currently living in the Northern Gaza Strip and 96 forcibly evacuated to the Southern Gaza Strip. This approach allows the analysis to consider both current geographic location and displacement status while avoiding confusion between place of origin, current residence, and evacuation status.

Previous literature has reported that certain medical conditions and medications may contribute to dry eye.Reference Aljarousha, Azemin and Ariffin22–Reference Yasir, Chauhan and Khandekar24 Therefore, additional questions were included regarding a history of chronic disorders and current use of medications, where applicable. Participants provided a self-reported history of systemic medical diagnoses and prescribed medications, which was confirmed by a qualified specialist whenever possible to ensure accuracy.

Ethical Approval

Ethical approval for this study was granted by the Palestinian Health Research Council Helsinki Committee (approval no. 883/21). All participants provided written informed consent before data collection began. For individuals unable to sign their own names, consent was confirmed through the signature of an independent witness.

Inclusion and Exclusion Criteria

Inclusion Criteria

(1) Aged 40 years or older. (2) Living in the study area at the time of data collection (January 1 to April 30 2025). (3) Able to complete demographic information, dry eye symptom, and psychological distress assessments. (4) Provided signed informed consent.

Exclusion Criteria

(1) Gazan residents younger than 40 years. (2) Participants residing outside the Gaza Strip during the 2023 Gaza War.

Outcomes and Measures

Continuous variables included the Arabic Depression Anxiety Stress Scale-8 (DASS-8) and the Arab Ocular Surface Disease Index (OSDI) score. The total DASS-8 score was calculated only if a sufficient number of items were completed. Following standard guidelines for short-form DASS scales, up to one missing item was allowed; if more items were missing, the participant’s score was not computed, as including scores with too many missing items could bias results. It should be noted that the OSDI assesses symptoms only, so the study reports the prevalence of DED symptoms rather than confirmed DED.

Techniques

Arabic Depression Anxiety Stress Scale-8 (DASS-8)

Psychological distress was assessed using the Arabic DASS-8, which comprises 3 items for depression, 3 for anxiety, and 2 for stress, each rated on a 0-3 scale, with higher scores reflecting greater symptom severity.Reference Ali, Alkhamees and Hori25

Arab Ocular Surface Disease Index (OSDI)

Dry eye symptoms were assessed using the Arabic version of the OSDI, which consists of 12 items across three subscales (symptoms, vision-related function, environmental triggers), rated on a 0-4 scale, with “N/A” responses available for items 6-12. The overall score (0-100) was computed using the established formula.Reference Schiffman, Christianson and Jacobsen26 Previous studies in Gazan samples have demonstrated good reliability and internal consistency.Reference Aljarousha, Badarudin and Che Azemin27 Dry eye symptom severity was classified as mild (13-22), moderate (23-32), or severe (33-100).

For the exploratory environmental analysis, an OSDI environmental-trigger domain score was calculated from items 10-12, which assess ocular discomfort under windy conditions, low-humidity conditions, and air-conditioned environments. The answered items were scaled from 0 to 100, with higher scores indicating greater symptom provocation under these environmental conditions. A separate combined score derived from OSDI items 1-9 was used to represent ocular symptoms and vision-related functional difficulties.

Statistical Analysis

Adults aged at least 40 years were analyzed. The primary outcome was the presence of clinically meaningful dry eye symptoms, defined using the Ocular Surface Disease Index (OSDI) with a cut-off of 13 points or higher. OSDI severity was also evaluated as an ordered outcome with four levels: none, mild, moderate, and severe. The OSDI total score (0-100) was calculated according to the standard scoring procedure: answered item scores were summed, adjusted for the number of items actually answered (items marked “not applicable” were excluded), and scaled to the 0-100 range. Psychological distress was summarized with the Arabic DASS-8 by adding the eight item scores. Pre-specified covariates were sex (male or female), age band (40-49, 50-59, 60-69, and ≥70 years), residence type (tents, shelters, or houses), and province (North Gaza Strip or South Gaza Strip). Residence labels were harmonized to these categories before analysis.

The study sample was described using counts and percentages for categorical variables and medians with interquartile ranges for continuous variables, both overall and stratified by dry eye status. Cross-sectional prevalence of dry eye symptoms during the data-collection period and corresponding 95% confidence intervals were estimated overall and within subgroups using an exact binomial method. These estimates were visualized with a forest plot that displays the point estimate and its confidence interval for each subgroup.

Associations between covariates and the presence of dry eye symptoms were examined using Poisson regression with a log link and robust (sandwich) standard errors. After model fitting, regression coefficients were converted to prevalence ratios and reported with 95% confidence intervals and 2-sided P-values. The main adjusted model included sex, age band, residence type, province, and DASS-8 total. Although chronic diseases, medication use, and previous ocular disorders were collected descriptively, they were not included in the primary adjusted model because of sparse subgroup counts, incomplete self-reported confirmation, and the near-universal outcome prevalence, which could produce unstable estimates. Results were presented in a forest plot with a vertical reference line at a prevalence ratio of one to aid interpretation.

Because the prevalence of OSDI-defined symptoms was nearly universal, additional exploratory analyses were performed to examine variation in symptom burden. Spearman’s rank correlation was used to assess the relationship between DASS-8 total and OSDI total scores. OSDI total score was analyzed using multivariable linear regression with heteroscedasticity-robust standard errors. Severe symptoms, defined as OSDI ≥33, were analyzed using modified Poisson regression with robust standard errors. Both adjusted models included sex, age band, residence type, geographic/displacement group, and DASS-8 total. OSDI scores were compared across residence types using the Kruskal–Wallis test. Spearman’s rank correlation was also used to examine the relationship between the OSDI environmental-trigger domain derived from items 10-12 and the combined score derived from items 1-9.

Missing data were handled as follows. For OSDI, the standard scoring accommodates missing or “not applicable” items by using only the items that were answered and then scaling to the full range. The DASS-8 total was calculated when at least 7 of the 8 items were available. Scores with one missing item were prorated to an 8-item score, whereas scores with more than one missing item were treated as missing. Regression models used complete-case analysis based on the variables included in each model; no multiple imputation was performed.

Because the sample was obtained through convenience sampling in a conflict setting, all estimates were unweighted and should be interpreted as describing the study sample rather than the entire population. Four figures were prepared: a forest plot of overall and subgroup prevalence, a forest plot of adjusted prevalence ratios from the primary Poisson model, a stacked bar chart of OSDI severity by residence type, and a boxplot of OSDI total scores across corrected DASS-8 quartiles. All analyses were performed in Python. Data management used pandas; regression models used statsmodels; and figures were produced with matplotlib.

Results

Table 1 shows the distribution of categorical characteristics by DED symptom status among the 296 adults aged ≥40 years included in the study sample. Within the study sample, the overall prevalence of OSDI-defined DED symptoms was 97.3% screened positive for DED symptoms, with a female majority (57.4%) and nearly half in the 40-49 age band (48.6%). Participants’ living conditions included tents (41.2%), houses (39.2%), and shelters (19.6%). Approximately two-thirds of participants were originally from the Northern Gaza Strip (67.6%), though some had been forcibly evacuated to the Southern Gaza Strip during the 2023 conflict. Patterns within the DED symptoms group mirrored the overall sample (e.g., 58.0% female). Median OSDI was substantially higher among those with DED symptoms, 52.5 (IQR 33.3-72.9), compared with non-DED symptoms participants, 8.7 (3.1-10.9). Median DASS-8 was also higher in the DED symptoms group, 17 (13-21) vs. 13 (10.3-16), while median age was similar between groups: 50 (44-58) years for DED symptoms vs. 45 (42.3-54.5) years for non-DED symptoms.

Table 1.

Participant characteristics (categorical) by OSDI-defined dry-eye symptom status among Gazan residents aged ≥40 years, January 1, 2025 to April 30, 2025

Table of sex, age band, residence, and geographic/displacement group by OSDI-defined dry-eye symptom status in 296 Gazan adults aged 40 years or older. See long description.
Table 1. Long description

Table 1 describes 296 participants: 288 had OSDI-defined dry-eye symptoms and 8 did not. Sex: female, 3 without symptoms (37.5% of the no-symptom group), 167 with symptoms (58.0% of the symptom group), 170 total (57.4%); male, 5 (62.5%), 121 (42.0%), 126 total (42.6%). Age: 40–49 years, 5 (62.5%), 139 (48.3%), 144 total (48.6%); 50–59, 1 (12.5%), 89 (30.9%), 90 (30.4%); 60–69, 2 (25.0%), 39 (13.5%), 41 (13.9%); 70 or older, 0 (0.0%), 21 (7.3%), 21 (7.1%). Residence: houses, 6 (75.0%), 110 (38.2%), 116 (39.2%); shelters, 1 (12.5%), 57 (19.8%), 58 (19.6%); tents, 1 (12.5%), 121 (42.0%), 122 (41.2%). Geographic/displacement group: North Gaza, 7 (87.5%), 193 (67.0%), 200 (67.6%); South/displaced, 1 (12.5%), 95 (33.0%), 96 (32.4%). DED symptoms were defined as OSDI ≥13.

The overall prevalence of DED symptoms was 97.3% (288/296; 95% CI 94.7-98.8). Prevalence was similarly high in both women and men: 98.2% (167/170; 95% CI 94.9-99.6) among women and 96.0% (121/126; 95% CI 91.0-98.7) among men, with overlapping confidence intervals. Across age bands, prevalence remained consistently high: 96.5% (139/144; 95% CI 92.1-98.9) in those aged 40-49 years, 98.9% (89/90; 95% CI 94.0-100.0) in those aged 50-59 years, 95.1% (39/41; 95% CI 83.5-99.4) in those aged 60-69 years, and 100.0% (21/21; 95% CI 83.9-100.0) in those aged ≥70 years. When stratified by housing type, prevalence was 94.8% (110/116; 95% CI 89.1-98.1) among those living in houses, 98.3% (57/58; 95% CI 90.8-100.0) among those in shelters, and 99.2% (121/122; 95% CI 95.5-100.0) among those living in tents. By province, prevalence was 96.5% (193/200; 95% CI 92.9-98.6) in the North Gaza Strip and 99.0% (95/96; 95% CI 94.3-100.0) in the South Gaza Strip.

In the adjusted primary model, living in tents was associated with a slightly higher prevalence of OSDI-defined dry-eye symptoms than living in houses (PR 1.05, 95% CI 1.01-1.10; P = 0.024). Adults aged ≥70 years also had slightly higher prevalence than those aged 40-49 years (PR 1.05, 95% CI 1.00-1.09; P = 0.028). Other covariates, including DASS-8 total, were not associated with the presence of any OSDI-defined symptoms in this binary model (Table 2). Given the near-universal prevalence of the outcome, these effect sizes should be interpreted cautiously.

Table 2.

Adjusted prevalence ratios (PRs) from Poisson regression with robust standard errors for OSDI-defined DED symptom status (OSDI ≥ 13). Model includes sex, age band, residence, province, and DASS-8 total

Table of adjusted prevalence ratios from the primary Poisson model for OSDI-defined dry-eye symptoms, including sex, age, residence, geographic/displacement group, and DASS-8. See long description.
Table 2. Long description

Table 2 reports adjusted prevalence ratios (PRs) with 95% confidence intervals and p-values. Male versus female: PR 0.98 (0.94–1.02), p=0.226. Age 50–59 versus 40–49: 1.03 (0.99–1.07), p=0.162. Age 60–69 versus 40–49: 1.00 (0.93–1.08), p=0.999. Age 70 or older versus 40–49: 1.05 (1.00–1.09), p=0.028. Shelters versus houses: 1.04 (0.98–1.09), p=0.205. Tents versus houses: 1.05 (1.01–1.10), p=0.024. South/displaced versus North: 0.99 (0.97–1.02), p=0.554. DASS-8 total per one-point increase: 1.002 (0.998–1.006), p=0.269. Reference categories were female sex, age 40–49 years, houses, and North Gaza.

Forest plots highlight uniformly high prevalence across all strata, with participants living in tents at the upper end (Figure 1). Adjusted associations were small in magnitude; tents and age ≥70 showed slightly elevated prevalence ratios (PRs), while other factors clustered around PR ≈ 1 (Figure 2). The distribution of OSDI severity differed across residence types, with a greater proportion of severe symptoms among participants living in shelters and tents than among those living in houses (Figure 3). OSDI total scores also differed across houses, shelters, and tents (Kruskal–Wallis H = 8.82; P = 0.012).

Figure 1.

Forest plot of OSDI-defined dry-eye symptom prevalence with exact 95% confidence intervals, overall and by subgroup.

Forest plot of OSDI-defined dry-eye symptom prevalence in 296 Gazan adults aged 40 years or older. Prevalence is high across all subgroups, overall 97.3%, with the highest values among tent residents and adults aged 70+. See long description.
Figure 1 Long description

The forest plot shows the prevalence of OSDI-defined dry-eye symptoms (OSDI ≥13) with exact 95% confidence intervals. Overall prevalence was 97.3% (288/296; 95% CI 94.7–98.8). By sex, prevalence was 98.2% in women (167/170; 94.9–99.6) and 96.0% in men (121/126; 91.0–98.7). By age, prevalence was 96.5% at 40–49 years (139/144; 92.1–98.9), 98.9% at 50–59 years (89/90; 94.0–100.0), 95.1% at 60–69 years (39/41; 83.5–99.4), and 100.0% at 70 years or older (21/21; 83.9–100.0). By residence, prevalence was 94.8% in houses (110/116; 89.1–98.1), 98.3% in shelters (57/58; 90.8–100.0), and 99.2% in tents (121/122; 95.5–100.0). By geographic/displacement group, prevalence was 96.5% in North Gaza (193/200; 92.9–98.6) and 99.0% in the South/displaced group (95/96; 94.3–100.0).

Figure 2.

Adjusted prevalence ratios for OSDI-defined dry-eye symptoms with 95% confidence intervals.

Forest plot of adjusted prevalence ratios for OSDI-defined dry-eye symptoms. Most estimates cluster around 1.0; tent residence and age 70+ each had an adjusted PR of 1.05 and were statistically significant. See long description.
Figure 2 Long description

The forest plot presents adjusted prevalence ratios (PRs) and 95% confidence intervals from the Poisson regression model, with a vertical reference line at PR=1. Compared with women, men had PR 0.98 (95% CI 0.94–1.02; p=0.226). Relative to age 40–49 years, PRs were 1.03 for age 50–59 (0.99–1.07; p=0.162), 1.00 for age 60–69 (0.93–1.08; p=0.999), and 1.05 for age 70 or older (1.00–1.09; p=0.028). Relative to houses, shelters had PR 1.04 (0.98–1.09; p=0.205) and tents PR 1.05 (1.01–1.10; p=0.024). The South/displaced group versus North had PR 0.99 (0.97–1.02; p=0.554). Each one-point increase in DASS-8 had PR 1.002 (0.998–1.006; p=0.269). Only tent residence and age 70 or older reached statistical significance.

Figure 3.

Distribution of OSDI severity categories by residence type.

Stacked bar chart of OSDI severity by residence type. Severe symptoms predominate in all groups and are more common among participants living in shelters and tents than in houses. See long description.
Figure 3 Long description

The stacked bar chart compares four OSDI severity categories—none, mild, moderate, and severe—across participants living in houses, shelters, and tents. Severe symptoms form the largest segment for every residence type. The severe-symptom segment is visibly larger for shelters and tents than for houses, while houses show relatively larger mild and moderate segments. Overall OSDI scores differed across residence types (Kruskal–Wallis H=8.82; p=0.012).

Because 97.3% of participants met the OSDI ≥13 threshold, additional exploratory analyses were performed using continuous OSDI score and severe symptoms to reduce the effect of outcome ceiling. DASS-8 total was positively correlated with OSDI total score (Spearman ρ = 0.614; P < 0.001). After adjustment, each one-point increase in DASS-8 score was associated with a 2.71-point increase in OSDI total score (95% CI 2.33-3.10; P < 0.001) and a higher prevalence of severe symptoms (PR 1.053, 95% CI 1.036-1.070; P < 0.001). Participants in the South/displaced group had an adjusted OSDI score 24.25 points higher than participants in the North group (95% CI 18.68-29.81; P < 0.001) and a higher prevalence of severe symptoms (PR 1.415, 95% CI 1.143-1.753; P = 0.001). The OSDI environmental-trigger domain was positively correlated with the combined OSDI items 1-9 (Spearman ρ = 0.731; P < 0.001). These exploratory results are presented in Table 3, and the distribution of OSDI scores across corrected DASS-8 quartiles is shown in Figure 4.

Table 3.

Exploratory analyses of psychological and environmental/contextual factors associated with dry-eye symptom burden

Table of exploratory analyses relating psychological distress, displacement context, residence, and environmental-trigger symptoms to dry-eye symptom burden. See long description.
Table 3. Long description

Table 3 summarizes exploratory analyses. DASS-8 versus OSDI total: Spearman rho=0.614, p<0.001. DASS-8 per point in the adjusted continuous OSDI model: estimate 2.71 (95% CI 2.33–3.10), p<0.001. DASS-8 per point in the adjusted severe-symptom model: PR 1.053 (1.036–1.070), p<0.001. South/displaced versus North in the adjusted continuous OSDI model: estimate 24.25 (18.68–29.81), p<0.001. South/displaced versus North in the adjusted severe-symptom model: PR 1.415 (1.143–1.753), p=0.001. OSDI environmental-trigger domain versus OSDI items 1–9: Spearman rho=0.731, p<0.001. OSDI total across houses, shelters, and tents: Kruskal–Wallis H=8.82, p=0.012. Severe symptoms were defined as OSDI ≥33; adjusted models included sex, age band, residence type, geographic/displacement group, and DASS-8 total.

Figure 4.

OSDI total scores across quartiles of the corrected DASS-8 total score; outliers are not displayed.

Boxplots of OSDI total scores across corrected DASS-8 quartiles. OSDI scores rise across increasing psychological-distress quartiles, consistent with a positive Spearman correlation of 0.614. See long description.
Figure 4 Long description

Four boxplots show OSDI total scores across increasing quartiles of the corrected DASS-8 psychological-distress score; outliers are not displayed. The boxes shift upward as DASS-8 quartile increases, indicating greater dry-eye symptom burden with greater psychological distress. Across the full sample, DASS-8 and OSDI total scores were positively correlated (Spearman rho=0.614; p<0.001). In the adjusted continuous model, each one-point increase in DASS-8 was associated with a 2.71-point increase in OSDI total score (95% CI 2.33–3.10; p<0.001).

Discussion

This study identified a high prevalence of OSDI-defined dry eye symptoms in a convenience sample of adults aged 40 years and above in Gaza, with 97.3% of participants screening positive. This symptom prevalence was higher than estimates reported among younger Gazan populations and in regional and international studies involving comparable age groups.Reference Aljarousha, Alghamdi and Che Azemin19, Reference Aljarousha, Azemin and Ariffin22, Reference Aljarousha, Badarudin and Che Azemin28 However, because the study used convenience sampling under conflict-related constraints, these findings should be interpreted as reflecting the surveyed sample rather than the broader Gaza population.

For contextual comparison, a pre-crisis Gaza study reported OSDI-defined dry-eye symptoms in 58.2% of 426 participants, compared with 97.3% in the present sample.Reference Aljarousha, Badarudin and Che Azemin28 This substantial difference may be compatible with increased psychological, displacement-related, and environmental burden during the humanitarian crisis. However, it should not be interpreted as a formal before-and-after comparison because the previous study included adults aged ≥18 years, used a different sampling design, and incorporated objective ocular-surface assessments.

The high symptom burden is consistent with evidence that dry eye symptoms and ocular surface dysfunction increase with age.Reference Aljarousha, Badarudin and Che Azemin28, Reference Wang, Muntz and Lim29 Age-related changes, including tear film instability, meibomian gland dysfunction, and reduced tear production, may partly explain the high prevalence among adults aged ≥40 years.Reference Aljarousha, Badarudin and Che Azemin27–Reference Wang, Muntz and Lim29 Nevertheless, the consistently high prevalence across all age groups suggests that age alone is unlikely to account for the findings.Reference Wang, Muntz and Lim29–Reference Al-Dossary33 Systemic illnesses and medications that reduce tear secretion may also contribute to symptom severity in older adults.Reference Wang, Muntz and Lim29, Reference Shanti, Shehada and Bakkar30

Approximately three-quarters of participants reported severe symptoms. OSDI scores differed across housing types, with greater unadjusted symptom burden among participants living in shelters and tents than among those living in houses. Participants in the South/displaced group also had substantially higher adjusted OSDI scores and a higher prevalence of severe symptoms than participants surveyed in the North. These findings may reflect the combined effects of forced displacement, crowding, housing conditions, disrupted access to clean water and health care, and other environmental or structural exposures.Reference Ayer, Venkatesh and Stewart34, Reference Firdaus and Ahmad39–Reference Chaturvedi, Kaushik and Mathur42 However, particulate matter, smoke, dust, humidity, ventilation, and water access were not measured directly. Housing type and geographic/displacement group should therefore be interpreted as contextual proxies rather than direct environmental-exposure measurements.

Psychological distress was not associated with the presence of any OSDI-defined symptoms in the primary binary model. However, this outcome had limited discriminatory ability because 97.3% of participants met the OSDI ≥13 threshold. When symptom burden was analyzed using continuous OSDI scores and severe symptoms, higher DASS-8 scores were consistently associated with greater dry-eye symptom burden. This discrepancy is compatible with a ceiling effect in the binary outcome. The findings support an association between psychological distress and dry-eye symptoms, although the cross-sectional design does not establish the direction or causality of the relationship. Previous evidence supports a biologically plausible relationship between psychological distress and dry eye symptoms through inflammatory, autonomic, sleep-related, and behavioral pathways.Reference Aljarousha, Azemin and Ariffin22, Reference Ayer, Venkatesh and Stewart34–Reference Gorimanipalli, Khamar and Sethu38

Symptom prevalence was slightly higher among females than males, but the difference was small and not statistically significant after adjustment. This finding differs from much of the broader dry eye literature, where female sex is often associated with higher risk.Reference Aljarousha, Badarudin and Che Azemin28, Reference Shanti, Shehada and Bakkar30, Reference Firdaus and Ahmad39 In the current setting, the severity of environmental and displacement-related exposures may have reduced observable sex-related differences.

Within the study sample, symptom prevalence was also slightly higher among participants surveyed in the southern Gaza Strip than among those in the north. This difference should be interpreted cautiously because the study was not designed to estimate population-level geographic differences. It may reflect the concentration of displaced residents in the south, overcrowded living conditions, reduced hygiene access, poor air quality, and limited availability of health care services.Reference Irfan, Lulu and Hamawy43–Reference Hawwa, Azizi and MSallam45 Similar associations between displacement, environmental burden, air pollution, limited preventive care, and ocular surface disease have been reported in conflict-affected or resource-limited settings.Reference Irfan, Lulu and Hamawy43, Reference Hao, Zhang and Zhao46–Reference Salem, Rosen and Alharazi49

Overall, the findings suggest a substantial dry eye symptom burden among surveyed adults aged ≥40 years in Gaza. The results highlight the need for symptom screening, access to basic ocular care, environmental risk reduction where feasible, and integrated support that considers both ocular and psychosocial needs in conflict-affected settings.

Limitations

This study has several limitations that should be considered when interpreting the findings. First, the use of convenience sampling may limit the generalizability of the results to the broader population of Gaza, as individuals who were more accessible or more concerned about their ocular health may have been overrepresented. Second, the data on dry eye symptoms and systemic medical history were self-reported, which introduces the possibility of recall bias and misclassification. Because no objective ophthalmic examinations, such as tear break-up time, Schirmer testing, corneal staining, or meibomian gland assessment, were performed, the findings represent dry eye symptom burden rather than clinically confirmed DED. Third, psychological distress was assessed using DASS-8, a brief screening tool with a simplified scoring method. Although validated, it may not capture the full spectrum or severity of psychological symptoms, and this could have affected the observed associations with dry eye symptoms. Finally, the extremely high prevalence of dry eye symptoms observed in this study limits the ability of regression analyses to discriminate between individuals with and without symptoms and may have contributed to wide confidence intervals or unstable estimates. These factors should be taken into account when interpreting the findings, and future studies employing probability sampling, objective clinical assessments, and more comprehensive psychological evaluation tools are recommended.

Conclusion

This study found an extremely high prevalence of dry-eye symptoms among surveyed adults aged ≥40 years in Gaza. Although the primary binary outcome showed limited variation, greater continuous and severe symptom burden was associated with higher psychological distress and with the South/displaced geographic context. Housing type and environmentally triggered symptoms also showed relevant patterns, although specific environmental exposures were not measured directly. These findings support integrated ocular and psychosocial care in conflict-affected settings and highlight the need for future studies incorporating objective ocular examinations and direct environmental measurements.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/dmp.2026.10450.

Data availability statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Acknowledgments

The author(s) would like to thank Management and Science University for the technical support provided to publish the present manuscript.

Author contribution

Mohd Zulfaezal Che Azemin, Mohammed Aljarousha, and Mohd Arifin Kaderi: Data analysis, writing—Result section. Mustafa Abdu, Emad I H Shaqoura, and Mohammed Aljarousha: Introduction section and hypothesis analysis. Mohammed Aljarousha, Noor Ezailina Badarudin, and Baqiatu’l Sabiqi’ Assfi Rahmat: Methodology, writing—review. Ithar M. Beshtawi and Mohammed Aljarousha: Writing—Discussion section. All authors contributed to the article and approved the submitted version. All authors have read and approved the final manuscript.

Funding statement

No financial support.

Competing interests

None.

Ethics approval and consent to participate

Ethical guidelines for conducting research in conflict zones were strictly observed, including measures to protect participant confidentiality. Written informed consent was obtained from all participants.

Consent for publication

Not applicable.

Declaration of generative AI use

The authors used ChatGPT (OpenAI, GPT-5.4) on April 1, 2026, to refine sentence structure, grammar, clarity, and readability in the manuscript. All ideas, study design, results, interpretations, and final wording were reviewed and approved by the authors, who take full responsibility for the accuracy and integrity of the manuscript. This use is disclosed in accordance with the journal’s policy on transparency in the use of AI tools.

References

Marculino, LGC, Hazarbassanov, RM, Hazarbassanov, NGTQ, et al. Prevalence and risk factors for dry eye disease: the Sao Paulo dry eye study. Arq Bras Oftalmol. 2022;85(6):549–557. doi:10.5935/0004-2749.202200100CrossRefGoogle Scholar
Tovar, AA, Frankel, ST, Galor, A, et al. Living with dry eye disease and its effects on quality of life: patient, optometrist, and ophthalmologist perspectives. Ophthalmol Ther. 2023;12(5):2219–2226. doi:10.1007/s40123-023-00736-7CrossRefGoogle ScholarPubMed
Noor, NA, Rahayu, T, Gondhowiardjo, TD. Prevalence of dry eye and its subtypes in an elderly population with cataracts in Indonesia. Clin Ophthalmol. 2020;14:2143–2150. doi:10.2147/OPTH.S240057CrossRefGoogle Scholar
Cai, Y, Wei, J, Zhou, J, et al. Prevalence and incidence of dry eye disease in Asia: a systematic review and meta-analysis. Ophthalmic Res. 2022;65(6):647–658. doi:10.1159/000525696CrossRefGoogle Scholar
Guo OD, LW, Akpek, E. The negative effects of dry eye disease on quality of life and visual function. Turk J Med Sci. 2020;50(SI-2):1611–1615. doi:10.3906/sag-2002-143Google ScholarPubMed
Bartlett, JD, Keith, MS, Sudharshan, L, et al. Associations between signs and symptoms of dry eye disease: a systematic review. Clin Ophthalmol. 2015;9:1719–1730. doi:10.2147/OPTH.S89700CrossRefGoogle ScholarPubMed
Vidal-Rohr, M, Craig, JP, Davies, LN, et al. Classification of dry eye disease subtypes. Cont Lens Anterior Eye. 2024;47(5):102257. doi:10.1016/j.clae.2024.102257CrossRefGoogle ScholarPubMed
Deo, N, Nagrale, P. Dry eye disease: an overview of its risk factors, diagnosis, and prevalence by age, sex, and race. Cureus. 2024;16(2):e54028. doi:10.7759/cureus.54028Google ScholarPubMed
AlAwlaqi, A, Hammadeh, M. Examining the relationship between hormone therapy and dry-eye syndrome in postmenopausal women: a cross-sectional comparison study. Menopause. 2016;23(5):550–555. doi:10.1097/GME.0000000000000570CrossRefGoogle ScholarPubMed
Titiyal, JS, Falera, RC, Kaur, M, et al. Prevalence and risk factors of dry eye disease in North India: ocular surface disease index-based cross-sectional hospital study. Indian J Ophthalmol. 2018;66(2):207–211. doi:10.4103/ijo.IJO_698_17CrossRefGoogle ScholarPubMed
Markoulli, M, Kolanu, S. Contact lens wear and dry eyes: challenges and solutions. Clin Optom (Auckl). 2017;9:41–48. doi:10.2147/OPTO.S111130CrossRefGoogle ScholarPubMed
Ward, MF 2nd, Le P, Donaldson, JC, et al. Racial and ethnic differences in the association between diabetes mellitus and dry eye disease. Ophthalmic Epidemiol. 2019;26(5):295–300. doi:10.1080/09286586.2019.1607882CrossRefGoogle ScholarPubMed
Britten-Jones, AC, Wang, MTM, Samuels, I, et al. Epidemiology and risk factors of dry eye disease: considerations for clinical management. Medicina (Kaunas). 2024;60(9):1458. doi:10.3390/medicina60091458CrossRefGoogle ScholarPubMed
Papas, EB. The global prevalence of dry eye disease: a Bayesian view. Ophthalmic Physiol Opt. 2021;41(6):1254–1266. doi:10.1111/opo.12888CrossRefGoogle ScholarPubMed
Stapleton, F, Alves, M, Bunya, VY, et al. TFOS DEWS II Epidemiology Report. Ocul Surf. 2017;15(3):334–365. doi:10.1016/j.jtos.2017.05.003CrossRefGoogle ScholarPubMed
Mohamed, Z, Alrasheed, S, Abdu, M, et al. Dry eye disease prevalence and associated risk factors among the Middle East population: a systematic review and meta-analysis. Cureus. 2024;16(9):e70522. doi:10.7759/cureus.70522Google ScholarPubMed
Clayton, JA. Dry eye. N Engl J Med. 2018;378(23):2212–2223. doi:10.1056/NEJMra1407936CrossRefGoogle ScholarPubMed
Lazreg, S, Hosny, M, Ahad, MA, et al. Dry eye disease in the Middle East and Northern Africa: a position paper on the current state and unmet needs. Clin Ophthalmol. 2024;18:679–698. doi:10.2147/OPTH.S436027CrossRefGoogle ScholarPubMed
Aljarousha, M, Alghamdi, WM, Che Azemin, MZ, et al. Epidemiology of ocular surface symptoms and their association with stress levels among the Gazan population in crowded shelters during the 2023 Israel war. Cont Lens Anterior Eye. 2025;48(4):102403. doi:10.1016/j.clae.2025.102403CrossRefGoogle Scholar
Hassoun, A, Parra-López, C, Ben Hassen, T, et al. The Gaza conflict and its implications for the sustainable development goals: a comprehensive analysis. Environ Dev Sustain. 2025. doi:10.1007/s10668-025-06763-7CrossRefGoogle Scholar
Dardona, Z, Amane, M, Dardona, A, et al. Health and environmental impacts of Gaza conflict (2023-2024): a review. One Health Bull. 2025;5(1):1–12. doi:10.4103/ohbl.ohbl_42_24CrossRefGoogle Scholar
Aljarousha, M, Azemin, MZC, Ariffin, IA, et al. Depression, anxiety, stress, and dry eye disease among Gazan undergraduate health sciences and nursing students: a structural equation modeling study. Cont Lens Anterior Eye. 2026;49(1):102504. doi:10.1016/j.clae.2025.102504CrossRefGoogle ScholarPubMed
Elagamy, A, Bawazir, S. Dry eye evaluation in Saudi patients with vitamin D deficiency. Int Ophthalmol Eye Care. 2019;2(1):1–7.Google Scholar
Yasir, ZH, Chauhan, D, Khandekar, R, et al. Prevalence and determinants of dry eye disease among 40 years and older population of Riyadh (Except Capital), Saudi Arabia. Middle East Afr J Ophthalmol. 2019;26(1):27–32. doi:10.4103/meajo.MEAJO_194_18CrossRefGoogle ScholarPubMed
Ali, AM, Alkhamees, AA, Hori, H, et al. The depression anxiety stress scale-21: development and validation of the depression anxiety stress scale 8-item in psychiatric patients and the general public. Int J Environ Res Public Health. 2021;18(19):10142. doi:10.3390/ijerph181910142CrossRefGoogle ScholarPubMed
Schiffman, RM, Christianson, MD, Jacobsen, G, et al. Reliability and validity of the ocular surface disease index. Arch Ophthalmol. 2000;118(5):615–621. doi:10.1001/archopht.118.5.615CrossRefGoogle ScholarPubMed
Aljarousha, M, Badarudin, NE, Che Azemin, MZ, et al. The validity and reliability of the Arabic version of the Ocular Surface Disease Index (OSDI) questionnaire in a sample of the Gazan population: a study from Palestine. Int Ophthalmol. 2023;43(4):1303–1316. doi:10.1007/s10792-022-02528-7CrossRefGoogle Scholar
Aljarousha, M, Badarudin, NE, Che Azemin, MZ, et al. Prevalence and risk factors of dry eye disease in the South of Palestine. Malays J Med Sci. 2024;31(2):72–97. doi:10.21315/mjms2024.31.2.8CrossRefGoogle ScholarPubMed
Wang, MT, Muntz, A, Lim, J, et al. Ageing and the natural history of dry eye disease: a prospective registry-based cross-sectional study. Ocul Surf. 2020;18(4):736–741. doi:10.1016/j.jtos.2020.07.003CrossRefGoogle ScholarPubMed
Shanti, Y, Shehada, R, Bakkar, MM, et al. Prevalence and associated risk factors of dry eye disease in 16 Northern West Bank towns in Palestine: a cross-sectional study. BMC Ophthalmol. 2020;20(1):26. doi:10.1186/s12886-019-1290-zCrossRefGoogle ScholarPubMed
Sherry, A, Aridi, M, Ghach, W. Prevalence and risk factors of symptomatic dry eye disease in Lebanon. Cont Lens Anterior Eye. 2020;43(4):355–358. doi:10.1016/j.clae.2019.08.001CrossRefGoogle ScholarPubMed
Aldawsari, SA, Alzaidi, N, Abdalla Elsayed, ME, et al. Prevalence and determinants of symptomatic dry eye disease among adult urban residents of high-altitude areas of southwest Saudi Arabia—a survey. Clin Ophthalmol. 2021;15:2687–2695. doi:10.2147/OPTH.S427101Google Scholar
Al-Dossary, SK. Environmental and occupational triggers of dry eye symptoms in the Ahsa Region of Saudi Arabia: a cross-sectional study. Clin Ophthalmol. 2024;18:2427–2438. Published 2024 Aug 29. doi:10.2147/OPTH.S474832CrossRefGoogle ScholarPubMed
Ayer, L, Venkatesh, B, Stewart, R, et al. Psychological aspects of the Israeli–Palestinian conflict: a systematic review. Trauma Violence Abuse. 2017;18(3):322–338. doi:10.1177/1524838015613774CrossRefGoogle ScholarPubMed
Basilious, A, Xu, CY, Malvankar-Mehta, MS. Dry eye disease and psychiatric disorders: a systematic review and meta-analysis. Eur J Ophthalmol. 2022;32(4):1872–1889. doi:10.1177/11206721211060963CrossRefGoogle ScholarPubMed
He, Q, Chen, Z, Xie, C, et al. The association between dry eye disease with depression, anxiety and sleep disturbance during COVID-19. Front Psychiatry. 2022;12:802302. doi:10.3389/fpsyt.2021.802302CrossRefGoogle ScholarPubMed
Tananuvat, N, Tansanguan, S, Wongpakaran, N, et al. Role of neuroticism and perceived stress on quality of life among patients with dry eye disease. Sci Rep. 2022;12(1):7079. doi:10.1038/s41598-022-11271-zCrossRefGoogle ScholarPubMed
Gorimanipalli, B, Khamar, P, Sethu, S, et al. Hormones and dry eye disease. Indian J Ophthalmol. 2023;71(4):1276–1284. doi:10.4103/IJO.IJO_2887_22CrossRefGoogle ScholarPubMed
Firdaus, G, Ahmad, A. Relationship between housing and health: a cross-sectional study of an urban centre of India. Indoor Built Environ. 2013;22(3):498–507. doi:10.1177/1420326X1244384CrossRefGoogle Scholar
Bron, AJ, de Paiva, CS, Chauhan, SK, et al. TFOS DEWS II pathophysiology report. Ocul Surf. 2017;15(3):438–510. doi:10.1016/j.jtos.2017.05.011CrossRefGoogle ScholarPubMed
Alghamdi, WM. Alghamdi, WM. Impact of environmental exposure on ocular surface balance: a comparative study. Clin Ophthalmol. 2025;19:747–752. Published 2025 Mar 3. doi:10.2147/OPTH.S504021CrossRefGoogle ScholarPubMed
Chaturvedi, PK, Kaushik, J, Mathur, V, et al. Determining the effect of climate and profession on dry eye disease: a prevalence study among young males in North, north-west and central India. Med J Armed Forces India. 2023;79:S75–S83. doi:10.1016/j.mjafi.2021.12.005CrossRefGoogle ScholarPubMed
Irfan, B, Lulu, I, Hamawy, A, et al. Combating infections under siege: healthcare challenges amidst the military assault in Gaza. World Med Health Policy. 2025;17(1):188–213. doi:10.1002/wmh3.642CrossRefGoogle Scholar
Irfan, B, Ali, E, Abu Alamrain, A, et al. Ophthalmic care in Gaza is collapsing. Eur J Ophthalmol. 2025;35(6):NP57–NP58. doi:10.1177/11206721251367565CrossRefGoogle ScholarPubMed
Hawwa, O, Azizi, S, MSallam, M, et al. Ophthalmology during conflict: a vitreoretinal surgeon’s journey in Gaza. Eye (Lond). 2025;39(9):1657–1658. doi:10.1038/s41433-025-03802-5CrossRefGoogle ScholarPubMed
Hao, R, Zhang, M, Zhao, L, et al. Impact of air pollution on the ocular surface and tear cytokine levels: a multicenter prospective cohort study. Front Med (Lausanne). 2022;9:909330. Published 2022 Jul 6. doi:10.3389/fmed.2022.909330CrossRefGoogle Scholar
Dafallah, A, Elmahi, OK, Ibrahim, ME, et al. Destruction, disruption and disaster: Sudan’s health system amidst armed conflict. Confl Health. 2023;17(1):43. doi:10.1186/s13031-023-00542-9CrossRefGoogle ScholarPubMed
Barten, DG, Tin, D, Granholm, F, et al. Attacks on Ukrainian healthcare facilities during the first year of the full-scale Russian invasion of Ukraine. Confl Health. 2023;17(1):57. Published 2023 Dec 8. doi:10.1186/s13031-023-00557-2CrossRefGoogle ScholarPubMed
Salem, A, Rosen, A, Alharazi, I, et al. Healthcare accessibility in Yemen’s conflict zones: comprehensive review focused on strategies and solutions. Confl Health. 2025;19(1):42. Published 2025 Jul 14. doi:10.1186/s13031-025-00685-xCrossRefGoogle ScholarPubMed
Figure 0

Table 1.Participant characteristics (categorical) by OSDI-defined dry-eye symptom status among Gazan residents aged ≥40 years, January 1, 2025 to April 30, 2025Table 1. long description.

Figure 1

Table 2.Adjusted prevalence ratios (PRs) from Poisson regression with robust standard errors for OSDI-defined DED symptom status (OSDI ≥ 13). Model includes sex, age band, residence, province, and DASS-8 totalTable 2. long description.

Figure 2

Figure 1.Forest plot of OSDI-defined dry-eye symptom prevalence with exact 95% confidence intervals, overall and by subgroup.Figure 1 long description.

Figure 3

Figure 2.Adjusted prevalence ratios for OSDI-defined dry-eye symptoms with 95% confidence intervals.Figure 2 long description.

Figure 4

Figure 3.Distribution of OSDI severity categories by residence type.Figure 3 long description.

Figure 5

Table 3.Exploratory analyses of psychological and environmental/contextual factors associated with dry-eye symptom burdenTable 3. long description.

Figure 6

Figure 4.OSDI total scores across quartiles of the corrected DASS-8 total score; outliers are not displayed.Figure 4 long description.

Supplementary material: File

Aljarousha et al. supplementary material

Aljarousha et al. supplementary material
Download Aljarousha et al. supplementary material(File)
File 36.9 KB