Prevalence of Dry Eye Disease among Indoor and Outdoor Workers and The Impact on Work Productivity in the West Bank of Palestine in 2024: A Cross-Sectional Study

Prevalence of Dry Eye Disease among Indoor and Outdoor Workers and The Impact on Work Productivity in the West Bank of Palestine in 2024: A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence of Dry Eye Disease among Indoor and Outdoor Workers and The Impact on Work Productivity in the West Bank of Palestine in 2024: A Cross-Sectional Study Hamza Abu Alhasan Abu Alhasan, Jamal Qaddumi, Shahd Samaana, Sana Abu Baker, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5868558/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 May, 2025 Read the published version in BMC Public Health → Version 1 posted 26 You are reading this latest preprint version Abstract Background Dry Eye Disease (DED) is a multifactorial ocular condition characterized by the disturbance of the tear film and interpalpebral ocular surface. It is characterized by ocular itchiness, grittiness, burning, and visual disturbances. Many risk factors were linked to DED, including occupational-related risk factors. This study aimed to investigate the prevalence and impact of DED on work productivity among outdoor and indoor occupational workers in the West Bank of Palestine and the impact of DED on daily activities performance Methods A population-based descriptive cross-sectional study was conducted on male and female Palestinian workers aged 18 years or older, carried out between June and October 2024. A total of 464 participants were included and completed a structured interview questionnaires using the Arabic version of the Ocular Surface Disease Index questionnaire (Arab-OSDI) and the Work Productivity and Activity Impairment questionnaire (WPAI) for participants who scored 13 or higher on OSDI. Results The prevalence of DED in Palestinian workers was 61.4%, which was higher among outdoor workers (64.7%) than indoor workers (58.2%), but this difference was not statistically significant (p = 0.153). The impact of DED on work performance was reported in all severity levels (p < 0.001); participants with severe DED had a mean of 5.93 hours, which is higher than the mean for moderate and mild DED patients (4.71 and 3.42 hours), respectively. Similarly, the impact on the ability to perform daily activities was significant (p < 0.001), greatest among respondents with severe disease (5.86 hours). Conclusions Dry eye disease is more likely to develop in outdoor workers than in office workers. Meanwhile, workers with DED report lower productivity and struggle with everyday tasks regardless of the severity level. This underlines the detrimental effects of the workplace on the ocular surface, which present a significant risk for the onset and exacerbation of dry eye symptoms. Dry eye disease Outdoor workers Indoor workers Work productivity Figures Figure 1 Background Dry Eye Disease (DED), or keratoconjunctivitis sicca, is a multifactorial ocular condition characterized by the disturbance of the tear film and interpalpebral ocular surface ( 1 ). It is associated with tear film hyperosmolarity and neurosensory abnormalities, accompanied by inflammation and damage to the ocular surface, which further exacerbate its impact on patients’ quality of life ( 2 , 3 ). The etiology of DED is complex, encompassing both environmental and physiological factors. Common causes include reduced tear production and excessive evaporation ( 4 ). The nature of DED symptoms and their intensity vary widely among patients and often manifest as ocular itchiness, grittiness, burning, soreness, increased watery discharge, foreign body sensation, and visual disturbances, which can significantly impact daily activities and work productivity ( 5 ). Diagnostic evaluation typically combines subjective symptom assessment with objective clinical tests. Tools such as the Ocular Surface Disease Index (OSDI) questionnaire are widely used to quantify symptom severity and impact on quality of life ( 6 ). There are a wide spectrum of risk factors for DED, including female gender, increasing age, certain comorbid conditions (e.g., hypertension, diabetes, thyroid disease), sun exposure, smoking, wearing contact lenses, previous eye surgery, and dry environments or workplaces ( 7 , 8 ). Occupational settings play a pivotal role in DED risk, with outdoor workers demonstrating higher susceptibility due to prolonged exposure to dust and wind ( 9 , 10 ). These occupational differences underscore the need to consider workplace conditions in understanding and mitigating DED. The prevalence of DED varies widely across geographic regions, largely due to differences in environmental factors, diagnostic criteria, and population demographics ( 11 ). Universally, DED prevalence ranges from 5% to over 50%, with higher rates observed in Asian and arid regions due to harsher environmental conditions ( 12 ). In Palestine, was 64% in a previous study. ( 13 ). DED imposes a significant burden on individuals by reducing their quality of life and work productivity. The economic implications are profound, with direct costs associated with treatment and indirect costs such as reduced employment, work absences, and decreased productivity, and a decline in the quality of life ( 14 ). Also, DED’s impact on mental health, including associations with anxiety and depression, further compounds its societal burden ( 15 ). Therefore, in this study, the aim is to fill the research gap by exploring how DED affects the productivity of both outdoor and indoor workers in the West Bank, the influence in their daily activities, and find the prevalence of DED for them. Methods In this cross-sectional study which was conducted between July to October 2024, 464 participants were involved ages 18 years old or older from different locations in the West Bank included taxi stations for transportation drivers situated in the cities centers in West Bank, the downtown areas of these cities where mobile vendors suited, and various companies such as Paltel and bank branches. These participants were divided randomly to 232 outdoor workers and 232 indoor office workers. Also, they had to comply with the following criteria: currently workers either full- or part-time, and had been working in their current job for at least 6 months. While, the exclusion criteria included contact lens wearers, who had active ocular allergy, ongoing uveitis, or anterior segment infection, who undergone ocular surgery in the preceding 6 months, and those who used any of the following in the previous month: topical ocular medications, such as antibiotics, antivirals, corticosteroids, NSAIDs, decongestants, mydriatics, cycloplegics, IOP-lowering drops, anti-glaucoma medications, or allergy drops, or systemic medications, such as antihistamines, decongestants, acne medications, hormone replacement therapy (HRT), or oral contraceptives. For the registered participants, written informed consent was signed by all subjects and complete description of the study and ample opportunity to ask questions through face to face interview. Then, they were asked about their demographic data, including age, gender, education level, and smoking status, information about each participant’s health history (previous ocular surgeries and ocular and non-ocular comorbid diseases), information about medication use (lubricant eye drops use, and systemic medicitions), and employment history (employment type, work regions, work experience, time spent at work, use of electronic devices, and time spent on them). After that, The Arabic version of the Ocular Surface Disease Index (OSDI) were used to assess the dry eye which is a well-established, validated, and reliable tool for DED contains 12 questions subdivided into three sections: 5 questions on ocular symptoms, 4 on vision-related function, and 3 on environmental triggers ( 16 ). The Arabic-language version of the OSDI questionnaire was administered to all participants ( 17 ). After that, those who got a score of 13 or above were able to complete the Work Productivity and Activity Impairment Questionnaire: Specific Health Problem, version 2.0 (WPAI-SHP) which assesses the impact of DED on work productivity and performance of daily activities outside work. The WPAI has demonstrated good validity and reliability since it has been significantly related to general health perceptions and global measures of interference with regular activity ( 18 ). A pilot study was done on 25 participants to ensure the validity and reliability after translated it to Arabic language. It includes 6 questions about the current employment status, the number of work hours missed because of DED during last week, the number of work hours missed for other reasons during last week, the number of hours actually worked during last week, the degree of DED that affected productivity while working during the last week, and the degree of DED that affected regular activities. After that, work productivity indices of absenteeism, presenteeism (on-the-job effectiveness), and productivity impairment (combined absenteeism plus presenteeism) (for employed patients) and the non-work-related productivity index of activity impairment (for all patients) were generated from WPAI questionnaire responses as follows (Q represents the question number): - Absenteeism (percent of work time missed due to dry eye) = [Q2/(Q2 + Q4)]*100 - Presenteeism (percent impairment of work performance due to dry eye) = (Q5/10)*100 - Productivity impairment (percent of overall work productivity lost due to dry eye) = {[Q2/(Q2 + Q4)] + [1-([Q2/(Q2 + Q4)] * (Q5/10)]} * 100 - Activity impairment (percent impairment of non-work-related activities due to dry eye) = (Q6/10)*100 Then, the data were analyzed by SPSS v 22. Results Table 1 summarizes the baseline demographic and clinical characteristics data of the 464 participants. 232 (50%) were outdoor workers, whom 231 (99.6%) were males and 1 (0.4%) was female, while the remaining 232 (50%) were indoor office workers, 146 (63%) of them were males and 86 (37%) were females. The study sample covered several age groups, with the highest percentage of outdoor workers (n = 111, 47.8%) being aged 36 to 55 and nearly half of indoor workers (n = 119, 51.3%) aged 26 to 35 years. Most of the outdoor respondents were smokers (n = 147, 63.4%) compared with indoor respondents, (n = 99, 42.7%) were smokers. Table 1 : Patients’ Demographic and Clinical Characteristics. Outdoor Workers (n=232) (%) Indoor Workers (n=232) (%) Total (N=464) (%) Age groups : 18-25 26-35 36-55 >55 27 (11.6%) 47 (20.3%) 111 (47.8%) 47 (20.3%) 21 (9.0%) 119 (51.3%) 81 (35.0%) 11 (4.7%) 48 (10.3%) 166 (35.8%) 192 (41.4%) 58 (12.5%) Gender : Male Female 231 (99.6%) 1 (0.4%) 146 (63.0%) 86 (37.0%) 377 (81.3%) 87 (18.7%) Education level : Primary School Middle School Secondary School College and Higher 29 (12.5%) 81 (35.0%) 93 (40.0%) 29 (12.5%) 7 (3.0%) 0 (0%) 1 (0.4%) 224 (96.6%) 36 (7.7%) 81 (17.5%) 94 (20.3%) 253 (54.5%) Smoking/Shisha : No Yes 85 (36.6 %) 147 (63.4%) 133 (57.3%) 99 (42.7%) 218 (47.0%) 246 (57.0%) Non-ocular comorbidities : No Yes 175 (75.4%) 57 (24.6%) 200 (86.2%) 32 (13.8%) 375 (80.8%) 89 (19.2%) Medication use : No Yes 177 (76.3%) 55 (23.7%) 201 (86.6%) 31 (13.4%) 378 (81.5%) 86 (18.5%) Ocular comorbidities : No comorbidity Myopia Hyperopia Astigmatism Myopia and Astigmatism Cataract 224 (96.5%) 2 (0.9%) 5 (2.2%) 0 (0%) 0 (0%) 1 (0.4%) 208 (89.7%) 10 (4.3%) 4 (1.7%) 5 (2.2%) 4 (1.7%) 1 (0.4%) 432 (93.1%) 12 (2.6%) 9 (1.9%) 5 (1.1%) 4 (0.9%) 2 (0.4%) Lubricant eye drops use : No Yes 224 (96.6%) 8 (3.4%) 161 (69.4%) 71 (30.6%) 385 (83.0%) 79 (17.0%) Previous diagnosis of DED : No Yes 220 (95.0%) 12 (5.0%) 153 (66.0%) 79 (34.0%) 373 (80.4%) 91 (19.6%) Also, the majority of indoor workers being university graduates (96.6%) whereas (12.5%) for outdoor workers. Of the study sample, secondary, middle, and primary school graduates documented 20.3%, 17.5%, and 7.7%, respectively. For non-ocular conditions, of all workers, 19.2% reported comorbid conditions, with 13.8% of indoor workers and 24.6% of outdoor workers having comorbid diseases. While regarding medication use, 18.5% of all participants reported medication use. For the use of lubricant eye drops, most of the participants (83.0%) reported no use, while 17.0% indicated their use. In addition, for indoor workers regarding ocular comorbidities, the most frequent ocular disease was myopia, followed by astigmatism (4.3% and 2.2%, respectively). Compared with hyperopia (2.2%) for the outdoor workers s ee Table 1 (page 25) . Moreover, the prevalence of DED was higher in older individuals, who were aged above 35 years, compared to the younger age groups who were aged less than 35 years; this difference was significant (p < 0.001). While the gender had no significant difference (p = 0.531), with females being more likely to experience DED (64.4%) compared to males (60.7%). In terms of education level, there was also a significant association (p = 0.008), with individuals with lower educational attainment, such as primary school (72.2%) or middle school (75.3%), having a higher prevalence of DED compared to those with secondary school (53.2%) and college or higher education (58.5%). Smoking had no significant association with DED (p = 0.187); it was associated with a slightly higher proportion of DED cases (64.2%) compared to non-smokers (58.3%). Participants with non-ocular comorbidities showed a notably higher prevalence of DED (78.7%) compared to those without comorbidities (57.3%); this difference was significantly associated with DED (p < 0.001). Similarly, individuals using medications also had a significant association with DED (p < 0.001), which reported more DED (80.2%) compared to non-users (57.1%). While among ocular comorbidities, participants without any ocular issues reported a lower prevalence of DED than those with ocular comorbidities such as myopia, hyperopia, cataract, and astigmatism, while these comorbidities were also not significantly associated with DED (p = 0.603). Also, Lubricant eye drop use was significantly associated with DED (p < 0.001), with 79.7% of users reporting DED. Additionally, a previous diagnosis of DED was significantly linked to current DED (p < 0.001), with 81.3% of previously diagnosed individuals reporting DED compared to 56.6% of those without prior diagnoses see Table 2 (page26). Table 2 : Association of Dry Eye (diagnosed by OSDI) with study groups. DED present DED absent P-value n (%) n (%) Age groups: 18-25 26-35 36-55 >55 16 98 132 39 33.3% 59.0% 68.8% 67.2% 32 68 60 19 66.7% 41.0% 31.3% 32.8% <0.001 Gender: Male Female 229 56 60.7% 64.4% 148 31 39.3% 35.6% .531 Education level: Primary School Middle School Secondary School College and Higher 26 61 50 148 72.2% 75.3% 53.2% 58.5% 10 20 44 105 27.8% 24.7% 46.8% 41.5% .008 Smoking/Shisha: No Yes 127 158 58.3 % 64.2% 91 88 41.7% 35.8% .187 Non-ocular comorbidities: No Yes 215 70 57.3% 78.7% 160 19 42.7% 21.3% <0.001 Medication use: No Yes 216 69 57.1% 80.2% 162 17 42.9% 19.8% <0.001 Ocular comorbidities: No ocular comorbidity Myopia Hyperopia Astigmatism Myopia and Astigmatism Cataract 261 8 7 4 3 2 60.4% 66.7% 77.8% 80.0% 75.0% 100.0% 171 4 2 1 1 0 39.6% 33.3% 22.2% 20.0% 25.0% 0.0% .603 Lubricant eye drops use: No Yes 222 63 57.7% 79.7% 163 16 42.3% 20.3% <0.001 Previous diagnosis of DED : No Yes 211 74 56.6% 81.3% 162 17 43.4% 18.7% <0.001 The prevalence of DED in Palestinian workers was 61.4%, which was higher among outdoor workers (64.7%) compared to indoor workers (58.2%) (p = 0.153). Among work regions, Nablus had the highest percentage of DED cases (66.2%), followed by Tulkarm (60.8%), while Jenin (51.5%) and Ramallah (55.6%) reported comparatively lower percentages (p = 0.172). Work experience showed a significant relation with DED prevalence (p = 0.053); individuals with more than 10 years of experience had a higher prevalence of DED compared to those with less than 10 years. However, the number of days spent at work weekly did not show marked differences, with those working 5 days or fewer reporting 60.7% DED prevalence and those working more than 5 days reporting 62.1% (p = 0.759). Furthermore, time spent at work daily showed slight variations, with those working more than 10 hours daily reporting a higher prevalence of DED (65.9%) compared to those working fewer than 8 hours (61.0%) (p = 0.658). Similarly, the prevalence of DED increased with daily electronic device usage, with 68.3% of those using devices for 2 hours or less reporting DED, compared to 60.0% of those using devices for more than 6 hours (p = 0.165). Among electronic devices, although the highest prevalence of DED was observed in individuals who did not use any electronic devices during the day (90.9%), the prevalence was lower among those who primarily used any electronic devices, such as smartphones, laptops, desktop computers, iPads, and televisions, during the day. While the strongest association with DED presence was noted among workers who don’t use electronic devices and TV users (p = 0.042) and (p < 0.001), respectively see Table 3 (page 27) Table 3 : Employment Factors and Presence of DED. DED Present DED Absent P-value n (%) n (%) Work type: Outdoor Workers Indoor Workers 150 135 64.7% 58.2% 82 97 35.3% 41.8% .153 Work region: Nublus Jenin Tulkarm Ramallah 129 34 107 15 66.2% 51.5% 60.8% 55.6% 66 32 69 12 33.8% 48.5% 39.2% 44.4% .172 Work experience (years): 15 49 71 41 124 55.7% 54.6% 63.1% 68.5% 39 59 24 57 44.3% 45.4% 36.9% 31.5% .053 Days spent at work weekly: 5 or less >5 128 157 60.7% 62.1% 83 96 39.3% 37.9% .759 Time spent at work daily (hours): 10 50 181 54 61.0% 60.3% 65.9% 32 119 28 39.0% 39.7% 34.1% .658 Time spent on electronic devices daily (hours): 2 or less 3-6 >6 84 72 129 68.3% 57.1% 60.0% 39 54 86 31.7% 42.9% 40.0% .165 The electronic device used the most during the day: None Smartphone Laptop Desktop computer iPad Television 10 221 32 104 10 64 90.9% 61.7% 58.2% 60.1% 76.9% 79.0% 1 137 23 69 3 17 9.1% 38.3% 41.8% 39.9% 23.1% 21.0% .042 .801 .599 .656 .244 <0.001 A multivariate logistic regression model was conducted to identify the significant risk factors that are associated with symptomatic DED. The study noted that a worker’s age was found to be correlated with their risk of developing dry eye illness; the older the worker, the higher the risk (OR = 1.88; 95% CI: 0.971, 1.54; P = 0.193), even though this was not significant by multivariate analysis. Also, there was no significant association noted with non-ocular comorbidities (OR = 1.392; 95% CI: 0.2, 9.66; P = 0.738), medication use (OR = 1.587; 95% CI: 0.223, 11.291; P = 0.645), and lubricant eye drops use (OR = 1.821; 95% CI: 0.905, 3.667; P = 0.093). On the other hand, workers who had a previous diagnosis of DED were noted to be 2.8 times more likely to develop DED compared to workers with no history of previous DED (OR = 2.815; 95% CI: 1.456, 5.442; P = 0.002) see Table 4 . Table 4 : Logistic regression analysis of risk factors associated with symptomatic DED. Risk factors P-value OR (95% CI ) Age groups 18-25 26-35 36-55 >55 0.193 1.188 (0.917-1.54) Education level: Primary School Middle School Secondary School College and Higher 0.217 0.838 (0.633-1.109) Non-ocular comorbidities: No Yes 0.738 1.392 (0.2-9.66) Medication use: No Yes 0.645 1.587 (0.223-11.291) Lubricant eye drops use: No Yes 0.093 1.821 (0.905-3.667) Previous diagnosis of DED : No Yes 0.002 2.815 (1.456-5.442) DED severity was assessed by the OSDI questionnaire as follows: mild in 96 participants (33.7%), moderate in 63 participants (22.1%), and severe in 126 participants (44.2%). All these participants were either in full- or part-time employment at the time of the study. The mean number of work hours missed per patient due to DED during the last week was significantly greater in severe DED patients (4.36 hours) than those with moderate (1.69 hours) or mild (0.58 hours) disease (p < 0.001). In comparison, the mean of work hours missed for other reasons during the same period was 2.981 hours, with the highest mean for mild DED patients (3.394 hours), however, this was not statistically significant (p = 0.616). Meanwhile, the mean hours worked during the past week was 48.334 hours, which was lower in moderate and severe DED patients (44.112 and 44.857 hours, respectively). This was not statistically significant (p = 0.063). Additionally, the association regarding the impact of DED on work performance during the past week was significant (p < 0.001), having a mean score of 3.97, with the highest impact on severe DED patients (5.93). Similarly, the mean impact of DED on non-work-related daily activities during the same period was 3.44, with the highest impact on severe DED patients (5.86), yielding a significant association (p < 0.001) see Table 5 . Table 5 Work Productivity and Activity Impairment Questionnaire Item Outcomes, Categorized by OSDI. WPAI Questionnaire Items OSDI Dry Eye Severity P-value Mild , n = 96 Moderate , n = 63 Severe , n = 126 Overall , N = 285 Q1. Currently employed, n (%) 96 (100) 63 (100) 126 (100) 285 (100) Q2. Work hours missed due to dry eye during past week, mean (SD) .58 (1.941) 1.69 (4.174) 4.36 (6.834) 1.17 (3.401) < 0.001 Q3. Work hours missed for other reasons during past week, mean (SD) 3.394 (6.7075) 2.061 (4.4973) 2.714 (4.4795) 2.981 (6.0361) .616 Q4. Hours worked during past week, mean (SD) 50.50 (17.8254) 44.112 (16.3714) 44.857 (19.6776) 48.334 (17.7437) .063 Q5. Impact of dry eye on work performance during past week, mean (SD) score on a scale of 0 to 10 3.42 (2.412) 4.71 (2.776) 5.93 (1.979) 3.97 (2.601) < 0.001 Q6. Impact of dry eye on non–work-related daily activities during past week, mean (SD) score on a scale of 0 to 10 2.97 (2.498) 3.90 (2.568) 5.86 (.949) 3.44 (2.557) < 0.001 Absenteeism due to DED was uncommon, but patients with severe DED reported missing more work time (2.09%) than patients with mild or moderate DED (0.89% and 0.28%), respectively. Similarly, impairment of work performance due to DED was interestingly higher among workers with severe disease (7.99%). In addition, productivity impairment while at work was reported by all three severity groups, and patients with moderate (15.93%) and severe (20.4%) disease had greater reductions in productivity than (13.66%) with mild disease. However, impairment in the ability to perform regular daily activities was observed among all three severity groups, which was significantly greater among patients with severe DED (14.56%) than those with moderate (9.84%) and mild (7.48%) disease. see Fig. 1 . Discussion In this study, the prevalence of DED was 61.4%, which aligns closely with findings from a study conducted across 16 towns in the Northern West Bank in 2017, which reported a prevalence of 64.0% ( 13 ). On the other hand, the prevalence varies considerably from a study done in Gaza in 2022 where the prevalence was 31.5% ( 19 ). This discrepancy may be ascribed to differences in the populations studied. This study also revealed a higher prevalence of DED among outdoor workers compared to indoor workers (64.7% and 58.2%, respectively). This can be explained by the increased exposure of outdoor workers to environmental irritants like dust, smoke, and sunlight. These findings are aligned with a Nigerian study, which reported a prevalence of 35.7% for outdoor street sweepers and 20.0% for indoor office sweepers, which was also measured by the OSDI questionnaire ( 9 ). However, a UK study provided opposing results, suggesting that outdoor workers have a lower risk of symptomatic dry eyes, while occupations involving high screen use showed the highest prevalence. This was largely credited to the frequent use of contact lenses among these workers ( 20 ). Numerous studies have investigated the relationship between DED and aging, revealing inconsistent findings. While some research has indicated a higher prevalence of DED among older individuals ( 13 , 21 ), other studies have not shown this association ( 22 ). In this study, a significant correlation (p < 0.001) was reported between age and DED, with older adults being at a notably higher risk compared to younger individuals. This corresponds with findings from earlier research, which suggest that the elderly have a 75% higher risk of DED compared to young individuals ( 23 ). Regarding gender, the evidence remains conflicting. Some studies have reported no significant association between DED and gender ( 22 ), while others have found a link ( 13 , 19 , 24 ). Nevertheless, a strong link between feminine gender and DED was documented through previous studies, which could be attributed to the different hormone levels throughout female life that affect the lacrimal gland and ocular surface, potentially explaining the higher prevalence of DED in women in particular studies ( 13 , 25 ). However, in this study, no independent correlation between DED and gender was identified (p = 0.531). DED prevalence was higher in smokers, but the difference was not statistically significant (p = 0.187), in agreement with other studies ( 13 , 26 ), while other reports showed an association ( 24 , 27 – 29 ). This may be explained by exposure to tobacco smoke, which can impair ocular surface defense and retinal nerve fiber layer, along with impacting tear film secretion and stability ( 29 ). Artificial tears are used to lubricate dry eyes and keep the outer surface of the eyes hydrated. Traditionally, they have been utilized as a first-line therapy to alleviate symptoms at every stage of DED treatment. Nevertheless, its primary purpose is to prevent the accumulation of symptoms rather than to alleviate them, as a recent study mentioned ( 30 ). In the presented study, the use of lubricant eye drops was more among those having DED (p < 0.001) than those who did not have DED. That agreed with previous studies ( 19 , 31 ). In this study, no association with ocular diseases and DED (p = 0.603), but a significant correlation was observed between systemic diseases and DED (p 35 years) and more likely to have systemic comorbidities. Paulsen et al. conducted comprehensive research on the link between DES and systemic disorders and found that dry eyes can be caused by systemic disorders like allergies, arthritis, and thyroid disease ( 32 ). While other meta-analysis studies found that hypertension and DM were associated with an increased risk of DED ( 25 ). DED onset and progression has been linked to several systemic drugs, such as anxiolytics, antidepressants, antihistamines, and antihypertensive medications ( 25 , 33 ). In support of this, the present study confirmed that intake of systemic medication was independently associated with DED (p < 0.001). The present study also found a significant association between participants who had a previous diagnosis of DED and active DED (p < 0.001). For employment factors, the frequency of DED was higher (68.5%) among participants who had worked for more than 15 years. Despite this, the difference was marginally significant (p = 0.053). However, another study finds no connection between DED severity and work experience ( 34 ). Although not statistically significant (p = 0.658), the prevalence of DED was highest among participants who spent more than 10 hours at work daily (65.9%). Digital screen time is strongly linked to DED, as indicated by numerous studies ( 35 , 36 ). An increase in digital screen time of one hour per day was linked to 1.14 higher odds of developing dry eye illness ( 37 ). The reason for this correlation may be that while performing tasks requiring a lot of visual processing, specifically activities with higher cognitive demands, the spontaneous blink reflex is suppressed. Consequently, low blink rate and partial blinking lead to unstable tear films and poor tear lipid layer integrity ( 38 ). According to Wang et al., DED was independently linked to more hours spent in front of a digital screen each day ( 37 ). Nevertheless, the current study found no correlation between DED and screen time on electronic devices (p = 0.165). Moreover increasing use of smartphones, laptops, desktop computers, iPads, and televisions has led to an increase in the prevalence of DED. Interestingly, the current study has only found an independent relationship between using a television and not using any kind of device. Although not being sight-threatening symptoms, as the dryness progresses or worsens, they become more troubling and burdensome for the sufferers ( 39 ), consistent with this study that found a considerable impact of DED on work productivity and non-job-related daily activities, Productivity loss was evident in all groups of dry eye severity, but it increased sharply as severity increased. Work productivity decreased by 13.66% for patients with mild DED, 15.93% for those with moderate DED, and 20.4% for those with severe DED. For non-work-related activities, impairment was increased similarly as severity increased. It has been demonstrated that DED affects job attendance more than absenteeism; only a small percentage of responders missed work because of their DED; patients with severe DED missed an average of 4 work hours each week. The outcomes of this study are in alignment with previously published data regarding the effect of DED on work productivity and performance of non–work-related activities using the WAPI questionnaire in 158 patients attending clinics for relief of dry eye symptoms, indicating that dry eye resulted in a loss of 0.36% of work time and ~ 30% impairment of workplace performance (presenteeism), work productivity, and non–job-related activities. Presenteeism and productivity impairment scores showed significant correlation with OSDI total (r = 0.55); the activity impairment score showed a stronger correlation with OSDI total (r = 0.61) ( 40 ). The impairment to both employment and daily activities imposed by DED, as indicated in this study, contributes to the burden for patients who have been proven to have decreased quality of life and psychological stress due to their condition ( 12 , 39 , 41 ). Conclusion To sum up, the prevalence of DED among worker categories in a previously unexamined Palestinian population was found to be 61.4%, which is quite significant. Moreover, considering the diverse environmental working conditions, outdoor workers are more prone to experience dry eye symptoms compared to indoor workers. Additionally, employees with DED report reduced productivity and face difficulties with daily activities, regardless of the severity level. These results highlight the critical need for implementing effective protective strategies in the workplace, such as utilizing eye shields that would be protective against environmental irritants and pollutants, as well as enhancing indoor working conditions, which could substantially lower the risk and progression of DED. Efforts should be directed towards enhancing societal awareness about DED to reduce its modifiable risk factors. Abbreviations DED: Dry Eye Disease, OSDI: The Ocular Surface Disease Index questionnaire, WPAI: The Work Productivity and Activity Impairment questionnaire. Declarations Ethics approval and consent to participate Before collecting data, institutional review board approval was obtained from An-Najah National University (Ref: Med. Dec. 2023/91), and permissions were granted by companies’ managers before we started this study. We obtained informed consent from the participants, ensuring their privacy and confidentiality, by choosing a quiet and secluded area away from others. We needed to ensure sufficient physical distance to prevent easy overhearing, speak softly, and avoid sensitive questions in public. We used a cover sheet to help shield responses, and we were mindful of participants' comfort through attentive body language during the interview. And participants’ data was to be only accessible by researchers. Participation in our study was entirely voluntary, and participants had the right to withdraw from the study at any time. Consent for publication Not applicable in this section Availability of data and materials The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Competing interests There is no conflict of interest declared by all authors. Funding No financial support Authors' contributions SA, SS, QS, JQ, HA, SA Conceptualization, Data Collection, and writing. JQ, SA, SS, QS analysis and interpretation of data HA. SA, SS, QS, JQ, SA drafted the work and revised it All Authors approved the submitted version, agreed both to be personally accountable for the contributions and integrity of any part of the work Acknowledgements The author(s) would like to thank An-Najah National University (www.najah.edu) for the technical support provided to publish the present manuscript References Courtin R, Pereira B, Naughton G, Chamoux A, Chiambaretta F, Lanhers C et al. Prevalence of dry eye disease in visual display terminal workers: A systematic review and meta-analysis. 6, BMJ Open. 2016. Lollett IV, Galor A. Dry eye syndrome: Developments and lifitegrast in perspective. Clin Ophthalmol. 2018;12. Craig JP, Nichols KK, Akpek EK, Caffery B, Dua HS, Joo CK et al. 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Identified risk factors for dry eye syndrome: A systematic review and meta-analysis. PLoS ONE. 2022;17(8 August):1–18. Hernandez-Llamas S, Paz-Ramos AK, Marcos-Gonzalez P, Amparo F, Garza-Leon M. Symptoms of ocular surface disease in construction workers: Comparative study with office workers. BMC Ophthalmol. 2020;20(1). Hashmani N, Mustafa FG, Tariq MA, Ali SF, Bukhari F, Memon AS et al. Distribution and Correlation of Ocular Surface Disease Index Scores in a Non-Clinical Population: The Karachi Ocular Surface Disease Study. Cureus. 2020. Alshamrani AA, Almousa AS, Almulhim AA, Alafaleq AA, Alosaimi MB, Alqahtani AM et al. Prevalence and risk factors of dry eye symptoms in a Saudi Arabian population. Middle East Afr J Ophthalmol. 2017;24(2). Ghach W, Bakkar MM, Aridi M, Beshtawi I, Doughaily R, Al-Fayoumi N. Prevalence and Behavioral-Based Risk Factors (Eye Cosmetic and Tobacco Use) of Symptomatic Dry Eye Disease in Four Middle Eastern Countries: Lebanon, Syria, Jordan, and Palestine. Clin Ophthalmol. 2022;16(October):3851–60. Mohamed HB, Abd El-Hamid BN, Fathalla D, Fouad EA. Current trends in pharmaceutical treatment of dry eye disease: A review. 175, Eur J Pharm Sci. 2022. Han SH, Kim EY. Prevalence of Dry Eye Disease Its Affecting Factors by Using OSDI Questionnaire. J Korea Academia-Industrial cooperation Soc. 2016;17(10). Paulsen AJ, Cruickshanks KJ, Fischer ME, Huang GH, Klein BEK, Klein R, et al. Dry eye in the beaver dam offspring study: Prevalence, risk factors, and health-related quality of life. Am J Ophthalmol. 2014;157(4):799–806. Britten-Jones AC, Wang MTM, Samuels I, Jennings C, Stapleton F, Craig JP. Epidemiology and Risk Factors of Dry Eye Disease: Considerations for Clinical Management. Medicina. 2024;60(9):1458. Binyousef FH, Alruwaili SA, Altammami AF, Alharbi AA, Alrakaf FA, Almazrou AA. Impact of dry eye disease on work productivity among Saudi workers in Saudi Arabia. Clin Ophthalmol. 2021;15:2675–81. Uchino M, Schaumberg DA, Dogru M, Uchino Y, Fukagawa K, Shimmura S, et al. Prevalence of Dry Eye Disease among Japanese Visual Display Terminal Users. Ophthalmology. 2008;115(11):1982–8. Titiyal JS, Falera RC, Kaur M, Sharma V, Sharma N. 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):207–11. Wang MTM, Muntz A, Mamidi B, Wolffsohn JS, Craig JP. Modifiable lifestyle risk factors for dry eye disease. Contact Lens Anterior Eye. 2021;44(6). Schwartz SG, Ceecee Britten-Jones A, Wang MTM, Samuels I, Jennings C, Stapleton F, et al. Epidemiology and Risk Factors of Dry Eye Disease: Considerations for Clinical Management. Medicina 2024. Page 1458. 2024;60(9):1458. Mertzanis P, Abetz L, Rajagopalan K, Espindle D, Chalmers R, Snyder C et al. The relative burden of dry eye in patients’ lives: Comparisons to a U.S. normative sample. Invest Ophthalmol Visual Sci. 2005;46(1). Nichols KK, Bacharach J, Holland E, Kislan T, Shettle L, Lunacsek O et al. Impact of dry eye disease on work productivity, and patients’ Satisfaction with Over-The-Counter dry eye treatments. Invest Ophthalmol Visual Sci. 2016;57(7). Dana R, Meunier J, Markowitz JT, Joseph C, Siffel C. Patient-Reported Burden of Dry Eye Disease in the United States: Results of an Online Cross-Sectional Survey. Am J Ophthalmol. 2020;216. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5868558","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":421462816,"identity":"944d2363-82c8-44af-a85e-4f0739eea14c","order_by":0,"name":"Hamza Abu Alhasan Abu Alhasan","email":"","orcid":"","institution":"An-Najah National University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hamza","middleName":"Abu Alhasan Abu","lastName":"Alhasan","suffix":""},{"id":421462817,"identity":"b168962a-efd7-4f42-87b2-92f96f343b51","order_by":1,"name":"Jamal Qaddumi","email":"","orcid":"","institution":"An-Najah National University","correspondingAuthor":false,"prefix":"","firstName":"Jamal","middleName":"","lastName":"Qaddumi","suffix":""},{"id":421462818,"identity":"7a7c84f5-1205-4870-a1ec-4b8975db41a5","order_by":2,"name":"Shahd Samaana","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIie2PMUvDQBTH3xFIlyddUxT6Fe4mK0byVSJCXA7H4nhnIF0CWVP0S/gNIjdksnNFh5SCXTJkzGDBC3YqXFo3wfsNB/d4P/7vD2Cx/EHGMZFV0/oYzMTPhAjUr2tWaOnEbJ5GZxQLIo5ThoPkFF3lUy8ku5xDikMSDzHC89Fms0b4GDuz1wKaqerrEk+8iY8Xj5zFCJ9MpnchyRdmBRSRS6pT4J0Treiv4NQ5SXoV4YWuQngrV50SyKymzrZfefAKrdAldIepa5nzrqBZoYrE+vwIRyln8yeqbmRe05d0cWuun5Wr9VfrB8NBWTX1vbp6zjir2uml+bC9UAAmAIpj93e5v1u3WCyWf8A3e+VaOwk5+isAAAAASUVORK5CYII=","orcid":"","institution":"An-Najah National University","correspondingAuthor":true,"prefix":"","firstName":"Shahd","middleName":"","lastName":"Samaana","suffix":""},{"id":421462819,"identity":"2b87f067-109d-488f-b383-ee1ec02bbcf4","order_by":3,"name":"Sana Abu Baker","email":"","orcid":"","institution":"An-Najah National University","correspondingAuthor":false,"prefix":"","firstName":"Sana","middleName":"Abu","lastName":"Baker","suffix":""},{"id":421462821,"identity":"b886a771-ffd8-49ad-a4e3-d1697102f5f3","order_by":4,"name":"Qutaiba Saidi","email":"","orcid":"","institution":"An-Najah National University","correspondingAuthor":false,"prefix":"","firstName":"Qutaiba","middleName":"","lastName":"Saidi","suffix":""},{"id":421462822,"identity":"08e8c0ca-7894-40f1-8069-2b37c4cac4fe","order_by":5,"name":"Shahd Abusalha","email":"","orcid":"","institution":"An-Najah National University","correspondingAuthor":false,"prefix":"","firstName":"Shahd","middleName":"","lastName":"Abusalha","suffix":""}],"badges":[],"createdAt":"2025-01-20 20:38:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5868558/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5868558/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-025-22779-0","type":"published","date":"2025-05-03T15:57:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":78246701,"identity":"68b33cf6-f965-4fbb-b503-83686d6b45fc","added_by":"auto","created_at":"2025-03-11 09:31:14","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":159591,"visible":true,"origin":"","legend":"\u003cp\u003eWork Productivity and Activity Impairment questionnaire domain scores, categorized by OSDI ocular disability level.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5868558/v1/2fc12b3dc42449f5553bdacb.jpg"},{"id":81988163,"identity":"ff1b3e3d-5cac-472d-a6d6-6c2fe3eb9f6c","added_by":"auto","created_at":"2025-05-05 16:08:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1425973,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5868558/v1/505a8c62-6187-4fcf-8dbd-63a73b2ac897.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePrevalence of Dry Eye Disease among Indoor and Outdoor Workers and The Impact on Work Productivity in the West Bank of Palestine in 2024: A Cross-Sectional Study\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eDry Eye Disease (DED), or keratoconjunctivitis sicca, is a multifactorial ocular condition characterized by the disturbance of the tear film and interpalpebral ocular surface (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). It is associated with tear film hyperosmolarity and neurosensory abnormalities, accompanied by inflammation and damage to the ocular surface, which further exacerbate its impact on patients\u0026rsquo; quality of life (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The etiology of DED is complex, encompassing both environmental and physiological factors. Common causes include reduced tear production and excessive evaporation (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The nature of DED symptoms and their intensity vary widely among patients and often manifest as ocular itchiness, grittiness, burning, soreness, increased watery discharge, foreign body sensation, and visual disturbances, which can significantly impact daily activities and work productivity (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Diagnostic evaluation typically combines subjective symptom assessment with objective clinical tests. Tools such as the Ocular Surface Disease Index (OSDI) questionnaire are widely used to quantify symptom severity and impact on quality of life (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere are a wide spectrum of risk factors for DED, including female gender, increasing age, certain comorbid conditions (e.g., hypertension, diabetes, thyroid disease), sun exposure, smoking, wearing contact lenses, previous eye surgery, and dry environments or workplaces (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Occupational settings play a pivotal role in DED risk, with outdoor workers demonstrating higher susceptibility due to prolonged exposure to dust and wind (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). These occupational differences underscore the need to consider workplace conditions in understanding and mitigating DED.\u003c/p\u003e \u003cp\u003eThe prevalence of DED varies widely across geographic regions, largely due to differences in environmental factors, diagnostic criteria, and population demographics (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Universally, DED prevalence ranges from 5% to over 50%, with higher rates observed in Asian and arid regions due to harsher environmental conditions (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In Palestine, was 64% in a previous study. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). DED imposes a significant burden on individuals by reducing their quality of life and work productivity. The economic implications are profound, with direct costs associated with treatment and indirect costs such as reduced employment, work absences, and decreased productivity, and a decline in the quality of life (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Also, DED\u0026rsquo;s impact on mental health, including associations with anxiety and depression, further compounds its societal burden (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTherefore, in this study, the aim is to fill the research gap by exploring how DED affects the productivity of both outdoor and indoor workers in the West Bank, the influence in their daily activities, and find the prevalence of DED for them.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eIn this cross-sectional study which was conducted between July to October 2024, 464 participants were involved ages 18 years old or older from different locations in the West Bank included taxi stations for transportation drivers situated in the cities centers in West Bank, the downtown areas of these cities where mobile vendors suited, and various companies such as Paltel and bank branches. These participants were divided randomly to 232 outdoor workers and 232 indoor office workers. Also, they had to comply with the following criteria: currently workers either full- or part-time, and had been working in their current job for at least 6 months. While, the exclusion criteria included contact lens wearers, who had active ocular allergy, ongoing uveitis, or anterior segment infection, who undergone ocular surgery in the preceding 6 months, and those who used any of the following in the previous month: topical ocular medications, such as antibiotics, antivirals, corticosteroids, NSAIDs, decongestants, mydriatics, cycloplegics, IOP-lowering drops, anti-glaucoma medications, or allergy drops, or systemic medications, such as antihistamines, decongestants, acne medications, hormone replacement therapy (HRT), or oral contraceptives.\u003c/p\u003e \u003cp\u003e For the registered participants, written informed consent was signed by all subjects and complete description of the study and ample opportunity to ask questions through face to face interview. Then, they were asked about their demographic data, including age, gender, education level, and smoking status, information about each participant\u0026rsquo;s health history (previous ocular surgeries and ocular and non-ocular comorbid diseases), information about medication use (lubricant eye drops use, and systemic medicitions), and employment history (employment type, work regions, work experience, time spent at work, use of electronic devices, and time spent on them). After that, The Arabic version of the Ocular Surface Disease Index (OSDI) were used to assess the dry eye which is a well-established, validated, and reliable tool for DED contains 12 questions subdivided into three sections: 5 questions on ocular symptoms, 4 on vision-related function, and 3 on environmental triggers (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The Arabic-language version of the OSDI questionnaire was administered to all participants (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfter that, those who got a score of 13 or above were able to complete the Work Productivity and Activity Impairment Questionnaire: Specific Health Problem, version 2.0 (WPAI-SHP) which assesses the impact of DED on work productivity and performance of daily activities outside work. The WPAI has demonstrated good validity and reliability since it has been significantly related to general health perceptions and global measures of interference with regular activity (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). A pilot study was done on 25 participants to ensure the validity and reliability after translated it to Arabic language. It includes 6 questions about the current employment status, the number of work hours missed because of DED during last week, the number of work hours missed for other reasons during last week, the number of hours actually worked during last week, the degree of DED that affected productivity while working during the last week, and the degree of DED that affected regular activities.\u003c/p\u003e \u003cp\u003eAfter that, work productivity indices of absenteeism, presenteeism (on-the-job effectiveness), and productivity impairment (combined absenteeism plus presenteeism) (for employed patients) and the non-work-related productivity index of activity impairment (for all patients) were generated from WPAI questionnaire responses as follows (Q represents the question number):\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e- \u003cem\u003eAbsenteeism\u003c/em\u003e (percent of work time missed due to dry eye) = [Q2/(Q2\u0026thinsp;+\u0026thinsp;Q4)]*100\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- \u003cem\u003ePresenteeism\u003c/em\u003e (percent impairment of work performance due to dry eye) = (Q5/10)*100\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- \u003cem\u003eProductivity impairment\u003c/em\u003e (percent of overall work productivity lost due to dry eye) = {[Q2/(Q2\u0026thinsp;+\u0026thinsp;Q4)] + [1-([Q2/(Q2\u0026thinsp;+\u0026thinsp;Q4)] * (Q5/10)]} * 100\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- \u003cem\u003eActivity impairment\u003c/em\u003e (percent impairment of non-work-related activities due to dry eye) = (Q6/10)*100\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThen, the data were analyzed by SPSS v 22.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the baseline demographic and clinical characteristics data of the 464 participants. 232 (50%) were outdoor workers, whom 231 (99.6%) were males and 1 (0.4%) was female, while the remaining 232 (50%) were indoor office workers, 146 (63%) of them were males and 86 (37%) were females. The study sample covered several age groups, with the highest percentage of outdoor workers (n\u0026thinsp;=\u0026thinsp;111, 47.8%) being aged 36 to 55 and nearly half of indoor workers (n\u0026thinsp;=\u0026thinsp;119, 51.3%) aged 26 to 35 years. Most of the outdoor respondents were smokers (n\u0026thinsp;=\u0026thinsp;147, 63.4%) compared with indoor respondents, (n\u0026thinsp;=\u0026thinsp;99, 42.7%) were smokers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e: Patients\u0026rsquo; Demographic and Clinical Characteristics.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"575\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.3043%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutdoor Workers\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n=232) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4783%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndoor Workers\u003c/strong\u003e (n=232) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2174%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(N=464) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.3043%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge groups\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003e18-25\u003c/p\u003e\n \u003cp\u003e26-35\u003c/p\u003e\n \u003cp\u003e36-55\u003c/p\u003e\n \u003cp\u003e\u0026gt;55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27 (11.6%)\u003c/p\u003e\n \u003cp\u003e47 (20.3%)\u003c/p\u003e\n \u003cp\u003e111 (47.8%)\u003c/p\u003e\n \u003cp\u003e47 (20.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4783%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21 (9.0%)\u003c/p\u003e\n \u003cp\u003e119 (51.3%)\u003c/p\u003e\n \u003cp\u003e81 (35.0%)\u003c/p\u003e\n \u003cp\u003e11 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2174%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e48 (10.3%)\u003c/p\u003e\n \u003cp\u003e166 (35.8%)\u003c/p\u003e\n \u003cp\u003e192 (41.4%)\u003c/p\u003e\n \u003cp\u003e58 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.3043%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e231 (99.6%)\u003c/p\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4783%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e146 (63.0%)\u003c/p\u003e\n \u003cp\u003e86 (37.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2174%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e377 (81.3%)\u003c/p\u003e\n \u003cp\u003e87 (18.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.3043%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003ePrimary School\u003c/p\u003e\n \u003cp\u003eMiddle School\u003c/p\u003e\n \u003cp\u003eSecondary School\u003c/p\u003e\n \u003cp\u003eCollege and Higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e29 (12.5%)\u003c/p\u003e\n \u003cp\u003e81 (35.0%)\u003c/p\u003e\n \u003cp\u003e93 (40.0%)\u003c/p\u003e\n \u003cp\u003e29 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4783%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7 (3.0%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003cp\u003e224 (96.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2174%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e36 (7.7%)\u003c/p\u003e\n \u003cp\u003e81 (17.5%)\u003c/p\u003e\n \u003cp\u003e94 (20.3%)\u003c/p\u003e\n \u003cp\u003e253 (54.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.3043%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking/Shisha\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e85 (36.6 %)\u003c/p\u003e\n \u003cp\u003e147 (63.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4783%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e133 (57.3%)\u003c/p\u003e\n \u003cp\u003e99 (42.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2174%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e218 (47.0%)\u003c/p\u003e\n \u003cp\u003e246 (57.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.3043%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-ocular comorbidities\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e175 (75.4%)\u003c/p\u003e\n \u003cp\u003e57 (24.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4783%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e200 (86.2%)\u003c/p\u003e\n \u003cp\u003e32 (13.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2174%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e375 (80.8%)\u003c/p\u003e\n \u003cp\u003e89 (19.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.3043%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedication use\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e177 (76.3%)\u003c/p\u003e\n \u003cp\u003e55 (23.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4783%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e201 (86.6%)\u003c/p\u003e\n \u003cp\u003e31 (13.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2174%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e378 (81.5%)\u003c/p\u003e\n \u003cp\u003e86 (18.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.3043%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOcular comorbidities\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003eNo comorbidity\u003c/p\u003e\n \u003cp\u003eMyopia\u003c/p\u003e\n \u003cp\u003eHyperopia\u003c/p\u003e\n \u003cp\u003eAstigmatism\u003c/p\u003e\n \u003cp\u003eMyopia and Astigmatism\u003c/p\u003e\n \u003cp\u003eCataract\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e224 (96.5%)\u003c/p\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003cp\u003e5 (2.2%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4783%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e208 (89.7%)\u003c/p\u003e\n \u003cp\u003e10 (4.3%)\u003c/p\u003e\n \u003cp\u003e4 (1.7%)\u003c/p\u003e\n \u003cp\u003e5 (2.2%)\u003c/p\u003e\n \u003cp\u003e4 (1.7%)\u003c/p\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2174%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e432 (93.1%)\u003c/p\u003e\n \u003cp\u003e12 (2.6%)\u003c/p\u003e\n \u003cp\u003e9 (1.9%)\u003c/p\u003e\n \u003cp\u003e5 (1.1%)\u003c/p\u003e\n \u003cp\u003e4 (0.9%)\u003c/p\u003e\n \u003cp\u003e2 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.3043%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLubricant eye drops use\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e224 (96.6%)\u003c/p\u003e\n \u003cp\u003e8 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4783%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e161 (69.4%)\u003c/p\u003e\n \u003cp\u003e71 (30.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2174%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e385 (83.0%)\u003c/p\u003e\n \u003cp\u003e79 (17.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.3043%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious diagnosis of DED\u003c/strong\u003e:\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e220 (95.0%)\u003c/p\u003e\n \u003cp\u003e12 (5.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4783%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e153 (66.0%)\u003c/p\u003e\n \u003cp\u003e79 (34.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2174%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e373 (80.4%)\u003c/p\u003e\n \u003cp\u003e91 (19.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAlso, the majority of indoor workers being university graduates (96.6%) whereas (12.5%) for outdoor workers. Of the study sample, secondary, middle, and primary school graduates documented 20.3%, 17.5%, and 7.7%, respectively. For non-ocular conditions, of all workers, 19.2% reported comorbid conditions, with 13.8% of indoor workers and 24.6% of outdoor workers having comorbid diseases. While regarding medication use, 18.5% of all participants reported medication use. For the use of lubricant eye drops, most of the participants (83.0%) reported no use, while 17.0% indicated their use.\u003c/p\u003e\n\u003cp\u003eIn addition, for indoor workers regarding ocular comorbidities, the most frequent ocular disease was myopia, followed by astigmatism (4.3% and 2.2%, respectively). Compared with hyperopia (2.2%) for the outdoor workers s\u003cstrong\u003eee\u003c/strong\u003e Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cstrong\u003e(page 25)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eMoreover, the prevalence of DED was higher in older individuals, who were aged above 35 years, compared to the younger age groups who were aged less than 35 years; this difference was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). While the gender had no significant difference (p\u0026thinsp;=\u0026thinsp;0.531), with females being more likely to experience DED (64.4%) compared to males (60.7%). In terms of education level, there was also a significant association (p\u0026thinsp;=\u0026thinsp;0.008), with individuals with lower educational attainment, such as primary school (72.2%) or middle school (75.3%), having a higher prevalence of DED compared to those with secondary school (53.2%) and college or higher education (58.5%). Smoking had no significant association with DED (p\u0026thinsp;=\u0026thinsp;0.187); it was associated with a slightly higher proportion of DED cases (64.2%) compared to non-smokers (58.3%).\u003c/p\u003e\n\u003cp\u003eParticipants with non-ocular comorbidities showed a notably higher prevalence of DED (78.7%) compared to those without comorbidities (57.3%); this difference was significantly associated with DED (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, individuals using medications also had a significant association with DED (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), which reported more DED (80.2%) compared to non-users (57.1%). While among ocular comorbidities, participants without any ocular issues reported a lower prevalence of DED than those with ocular comorbidities such as myopia, hyperopia, cataract, and astigmatism, while these comorbidities were also not significantly associated with DED (p\u0026thinsp;=\u0026thinsp;0.603). Also, Lubricant eye drop use was significantly associated with DED (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with 79.7% of users reporting DED. Additionally, a previous diagnosis of DED was significantly linked to current DED (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with 81.3% of previously diagnosed individuals reporting DED compared to 56.6% of those without prior diagnoses \u003cstrong\u003esee\u003c/strong\u003e Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cstrong\u003e(page26).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e: Association of Dry Eye (diagnosed by OSDI) with study groups.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eDED present\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eDED absent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge groups:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e18-25\u003cbr\u003e\u0026nbsp;26-35\u003c/p\u003e\n \u003cp\u003e36-55\u003c/p\u003e\n \u003cp\u003e\u0026gt;55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e33.3%\u003c/p\u003e\n \u003cp\u003e59.0%\u003c/p\u003e\n \u003cp\u003e68.8%\u003c/p\u003e\n \u003cp\u003e67.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e66.7%\u003c/p\u003e\n \u003cp\u003e41.0%\u003c/p\u003e\n \u003cp\u003e31.3%\u003c/p\u003e\n \u003cp\u003e32.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e229\u003c/p\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e60.7%\u003c/p\u003e\n \u003cp\u003e64.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39.3%\u003c/p\u003e\n \u003cp\u003e35.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.531\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePrimary School\u003c/p\u003e\n \u003cp\u003eMiddle School\u003c/p\u003e\n \u003cp\u003eSecondary School\u003c/p\u003e\n \u003cp\u003eCollege and Higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e72.2%\u003c/p\u003e\n \u003cp\u003e75.3%\u003c/p\u003e\n \u003cp\u003e53.2%\u003c/p\u003e\n \u003cp\u003e58.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27.8%\u003c/p\u003e\n \u003cp\u003e24.7%\u003c/p\u003e\n \u003cp\u003e46.8%\u003c/p\u003e\n \u003cp\u003e41.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e.008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking/Shisha:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e127\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e158\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e58.3\u003c/span\u003e%\u003c/p\u003e\n \u003cp\u003e64.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e41.7%\u003c/p\u003e\n \u003cp\u003e35.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.187\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-ocular comorbidities:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e215\u003c/p\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e57.3%\u003c/p\u003e\n \u003cp\u003e78.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e42.7%\u003c/p\u003e\n \u003cp\u003e21.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedication use:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e216\u003c/p\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e57.1%\u003c/p\u003e\n \u003cp\u003e80.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e42.9%\u003c/p\u003e\n \u003cp\u003e19.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOcular comorbidities:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNo ocular comorbidity\u003c/p\u003e\n \u003cp\u003eMyopia\u003c/p\u003e\n \u003cp\u003eHyperopia\u003c/p\u003e\n \u003cp\u003eAstigmatism\u003c/p\u003e\n \u003cp\u003eMyopia and Astigmatism\u003c/p\u003e\n \u003cp\u003eCataract\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e60.4%\u003c/p\u003e\n \u003cp\u003e66.7%\u003c/p\u003e\n \u003cp\u003e77.8%\u003c/p\u003e\n \u003cp\u003e80.0%\u003c/p\u003e\n \u003cp\u003e75.0%\u003c/p\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39.6%\u003c/p\u003e\n \u003cp\u003e33.3%\u003c/p\u003e\n \u003cp\u003e22.2%\u003c/p\u003e\n \u003cp\u003e20.0%\u003c/p\u003e\n \u003cp\u003e25.0%\u003c/p\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.603\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLubricant eye drops use:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e222\u003c/p\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e57.7%\u003c/p\u003e\n \u003cp\u003e79.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e42.3%\u003c/p\u003e\n \u003cp\u003e20.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious diagnosis of DED\u003c/strong\u003e\u003cstrong\u003e\u003cspan dir=\"RTL\"\u003e:\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e211\u003c/p\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e56.6%\u003c/p\u003e\n \u003cp\u003e81.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43.4%\u003c/p\u003e\n \u003cp\u003e18.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe prevalence of DED in Palestinian workers was 61.4%, which was higher among outdoor workers (64.7%) compared to indoor workers (58.2%) (p\u0026thinsp;=\u0026thinsp;0.153). Among work regions, Nablus had the highest percentage of DED cases (66.2%), followed by Tulkarm (60.8%), while Jenin (51.5%) and Ramallah (55.6%) reported comparatively lower percentages (p\u0026thinsp;=\u0026thinsp;0.172).\u003c/p\u003e\n\u003cp\u003eWork experience showed a significant relation with DED prevalence (p\u0026thinsp;=\u0026thinsp;0.053); individuals with more than 10 years of experience had a higher prevalence of DED compared to those with less than 10 years. However, the number of days spent at work weekly did not show marked differences, with those working 5 days or fewer reporting 60.7% DED prevalence and those working more than 5 days reporting 62.1% (p\u0026thinsp;=\u0026thinsp;0.759). Furthermore, time spent at work daily showed slight variations, with those working more than 10 hours daily reporting a higher prevalence of DED (65.9%) compared to those working fewer than 8 hours (61.0%) (p\u0026thinsp;=\u0026thinsp;0.658).\u003c/p\u003e\n\u003cp\u003eSimilarly, the prevalence of DED increased with daily electronic device usage, with 68.3% of those using devices for 2 hours or less reporting DED, compared to 60.0% of those using devices for more than 6 hours (p\u0026thinsp;=\u0026thinsp;0.165). Among electronic devices, although the highest prevalence of DED was observed in individuals who did not use any electronic devices during the day (90.9%), the prevalence was lower among those who primarily used any electronic devices, such as smartphones, laptops, desktop computers, iPads, and televisions, during the day. While the strongest association with DED presence was noted among workers who don\u0026rsquo;t use electronic devices and TV users (p\u0026thinsp;=\u0026thinsp;0.042) and (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), respectively \u003cstrong\u003esee\u003c/strong\u003e Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cstrong\u003e(page 27)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e: Employment Factors and Presence of DED.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"584\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 259px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003eDED Present\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eDED Absent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 259px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWork type:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eOutdoor Workers\u003c/p\u003e\n \u003cp\u003eIndoor Workers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e64.7%\u003c/p\u003e\n \u003cp\u003e58.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35.3%\u003c/p\u003e\n \u003cp\u003e41.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 259px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWork region:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNublus\u003c/p\u003e\n \u003cp\u003eJenin\u003c/p\u003e\n \u003cp\u003eTulkarm\u003c/p\u003e\n \u003cp\u003eRamallah\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e66.2%\u003c/p\u003e\n \u003cp\u003e51.5%\u003c/p\u003e\n \u003cp\u003e60.8%\u003c/p\u003e\n \u003cp\u003e55.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003e33.8%\u003c/p\u003e\n \u003cp\u003e48.5%\u003c/p\u003e\n \u003cp\u003e39.2%\u003c/p\u003e\n \u003cp\u003e44.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.172\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 259px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWork experience (years):\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026lt;5\u003c/p\u003e\n \u003cp\u003e5-10\u003c/p\u003e\n \u003cp\u003e11-15\u003c/p\u003e\n \u003cp\u003e\u0026gt;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e55.7%\u003c/p\u003e\n \u003cp\u003e54.6%\u003c/p\u003e\n \u003cp\u003e63.1%\u003c/p\u003e\n \u003cp\u003e68.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;39\u003c/p\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e44.3%\u003c/p\u003e\n \u003cp\u003e45.4%\u003c/p\u003e\n \u003cp\u003e36.9%\u003c/p\u003e\n \u003cp\u003e31.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 259px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDays spent at work weekly:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e5 or less\u003c/p\u003e\n \u003cp\u003e\u0026gt;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e60.7%\u003c/p\u003e\n \u003cp\u003e62.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39.3%\u003c/p\u003e\n \u003cp\u003e37.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.759\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 259px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime spent at work daily (hours):\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026lt;8\u003c/p\u003e\n \u003cp\u003e8-10\u003c/p\u003e\n \u003cp\u003e\u0026gt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e61.0%\u003c/p\u003e\n \u003cp\u003e60.3%\u003c/p\u003e\n \u003cp\u003e65.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39.0%\u003c/p\u003e\n \u003cp\u003e39.7%\u003c/p\u003e\n \u003cp\u003e34.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.658\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 259px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime spent on electronic devices daily (hours):\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e2 or less\u003c/p\u003e\n \u003cp\u003e3-6\u003c/p\u003e\n \u003cp\u003e\u0026gt;6 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e68.3%\u003c/p\u003e\n \u003cp\u003e57.1%\u003c/p\u003e\n \u003cp\u003e60.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e31.7%\u003c/p\u003e\n \u003cp\u003e42.9%\u003c/p\u003e\n \u003cp\u003e40.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.165\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 259px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThe electronic device used the most during the day:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003cp\u003eSmartphone\u003c/p\u003e\n \u003cp\u003eLaptop\u003c/p\u003e\n \u003cp\u003eDesktop computer\u003c/p\u003e\n \u003cp\u003eiPad\u003c/p\u003e\n \u003cp\u003eTelevision\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003cp\u003e221\u003c/p\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e90.9%\u003c/p\u003e\n \u003cp\u003e61.7%\u003c/p\u003e\n \u003cp\u003e58.2%\u003c/p\u003e\n \u003cp\u003e60.1%\u003c/p\u003e\n \u003cp\u003e76.9%\u003c/p\u003e\n \u003cp\u003e79.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9.1%\u003c/p\u003e\n \u003cp\u003e38.3%\u003c/p\u003e\n \u003cp\u003e41.8%\u003c/p\u003e\n \u003cp\u003e39.9%\u003c/p\u003e\n \u003cp\u003e23.1%\u003c/p\u003e\n \u003cp\u003e21.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e.042\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e.801\u003c/p\u003e\n \u003cp\u003e.599\u003c/p\u003e\n \u003cp\u003e.656\u003c/p\u003e\n \u003cp\u003e.244\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eA multivariate logistic regression model was conducted to identify the significant risk factors that are associated with symptomatic DED. The study noted that a worker\u0026rsquo;s age was found to be correlated with their risk of developing dry eye illness; the older the worker, the higher the risk (OR\u0026thinsp;=\u0026thinsp;1.88; 95% CI: 0.971, 1.54; P\u0026thinsp;=\u0026thinsp;0.193), even though this was not significant by multivariate analysis. Also, there was no significant association noted with non-ocular comorbidities (OR\u0026thinsp;=\u0026thinsp;1.392; 95% CI: 0.2, 9.66; P\u0026thinsp;=\u0026thinsp;0.738), medication use (OR\u0026thinsp;=\u0026thinsp;1.587; 95% CI: 0.223, 11.291; P\u0026thinsp;=\u0026thinsp;0.645), and lubricant eye drops use (OR\u0026thinsp;=\u0026thinsp;1.821; 95% CI: 0.905, 3.667; P\u0026thinsp;=\u0026thinsp;0.093). On the other hand, workers who had a previous diagnosis of DED were noted to be 2.8 times more likely to develop DED compared to workers with no history of previous DED (OR\u0026thinsp;=\u0026thinsp;2.815; 95% CI: 1.456, 5.442; P\u0026thinsp;=\u0026thinsp;0.002) \u003cstrong\u003esee\u003c/strong\u003e Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e: Logistic regression analysis of risk factors associated with symptomatic DED.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk factors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI )\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge groups\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e18-25\u003cbr\u003e\u0026nbsp;26-35\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e36-55\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;55\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.188 (0.917-1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary School\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMiddle School\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSecondary School\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCollege and Higher\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.838 (0.633-1.109)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-ocular comorbidities:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.392 (0.2-9.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedication use:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.587 (0.223-11.291)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLubricant eye drops use:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.821 (0.905-3.667)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious diagnosis of DED\u003c/strong\u003e\u003cstrong\u003e\u003cspan dir=\"RTL\"\u003e:\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.815 (1.456-5.442)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eDED severity was assessed by the OSDI questionnaire as follows: mild in 96 participants (33.7%), moderate in 63 participants (22.1%), and severe in 126 participants (44.2%). All these participants were either in full- or part-time employment at the time of the study.\u003c/p\u003e\n\u003cp\u003eThe mean number of work hours missed per patient due to DED during the last week was significantly greater in severe DED patients (4.36 hours) than those with moderate (1.69 hours) or mild (0.58 hours) disease (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In comparison, the mean of work hours missed for other reasons during the same period was 2.981 hours, with the highest mean for mild DED patients (3.394 hours), however, this was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.616).\u003c/p\u003e\n\u003cp\u003eMeanwhile, the mean hours worked during the past week was 48.334 hours, which was lower in moderate and severe DED patients (44.112 and 44.857 hours, respectively). This was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.063).\u003c/p\u003e\n\u003cp\u003eAdditionally, the association regarding the impact of DED on work performance during the past week was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), having a mean score of 3.97, with the highest impact on severe DED patients (5.93). Similarly, the mean impact of DED on non-work-related daily activities during the same period was 3.44, with the highest impact on severe DED patients (5.86), yielding a significant association (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) \u003cstrong\u003esee\u003c/strong\u003e Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eWork Productivity and Activity Impairment Questionnaire Item Outcomes, Categorized by OSDI.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eWPAI Questionnaire Items\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eOSDI Dry Eye Severity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMild\u003c/strong\u003e, n\u0026thinsp;=\u0026thinsp;96\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate\u003c/strong\u003e, n\u0026thinsp;=\u0026thinsp;63\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere\u003c/strong\u003e, n\u0026thinsp;=\u0026thinsp;126\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e, N\u0026thinsp;=\u0026thinsp;285\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ1. Currently employed, \u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e285 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ2. Work hours missed due to dry eye during past week, \u003cstrong\u003emean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.58 (1.941)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.69 (4.174)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.36 (6.834)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17 (3.401)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ3. Work hours missed for other reasons during past week, \u003cstrong\u003emean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.394 (6.7075)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.061 (4.4973)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.714 (4.4795)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.981 (6.0361)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.616\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ4. Hours worked during past week, \u003cstrong\u003emean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.50 (17.8254)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.112 (16.3714)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.857 (19.6776)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.334 (17.7437)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ5. Impact of dry eye on work performance during past week, \u003cstrong\u003emean (SD)\u003c/strong\u003e score on a scale of 0 to 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.42 (2.412)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.71 (2.776)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.93 (1.979)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.97 (2.601)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ6. Impact of dry eye on non\u0026ndash;work-related daily activities during past week, \u003cstrong\u003emean (SD)\u003c/strong\u003e score on a scale of 0 to 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.97 (2.498)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.90 (2.568)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.86 (.949)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.44 (2.557)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAbsenteeism due to DED was uncommon, but patients with severe DED reported missing more work time (2.09%) than patients with mild or moderate DED (0.89% and 0.28%), respectively. Similarly, impairment of work performance due to DED was interestingly higher among workers with severe disease (7.99%).\u003c/p\u003e\n\u003cp\u003eIn addition, productivity impairment while at work was reported by all three severity groups, and patients with moderate (15.93%) and severe (20.4%) disease had greater reductions in productivity than (13.66%) with mild disease.\u003c/p\u003e\n\u003cp\u003eHowever, impairment in the ability to perform regular daily activities was observed among all three severity groups, which was significantly greater among patients with severe DED (14.56%) than those with moderate (9.84%) and mild (7.48%) disease. \u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, the prevalence of DED was 61.4%, which aligns closely with findings from a study conducted across 16 towns in the Northern West Bank in 2017, which reported a prevalence of 64.0% (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). On the other hand, the prevalence varies considerably from a study done in Gaza in 2022 where the prevalence was 31.5% (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). This discrepancy may be ascribed to differences in the populations studied.\u003c/p\u003e \u003cp\u003eThis study also revealed a higher prevalence of DED among outdoor workers compared to indoor workers (64.7% and 58.2%, respectively). This can be explained by the increased exposure of outdoor workers to environmental irritants like dust, smoke, and sunlight. These findings are aligned with a Nigerian study, which reported a prevalence of 35.7% for outdoor street sweepers and 20.0% for indoor office sweepers, which was also measured by the OSDI questionnaire (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). However, a UK study provided opposing results, suggesting that outdoor workers have a lower risk of symptomatic dry eyes, while occupations involving high screen use showed the highest prevalence. This was largely credited to the frequent use of contact lenses among these workers (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNumerous studies have investigated the relationship between DED and aging, revealing inconsistent findings. While some research has indicated a higher prevalence of DED among older individuals (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), other studies have not shown this association (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In this study, a significant correlation (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was reported between age and DED, with older adults being at a notably higher risk compared to younger individuals. This corresponds with findings from earlier research, which suggest that the elderly have a 75% higher risk of DED compared to young individuals (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding gender, the evidence remains conflicting. Some studies have reported no significant association between DED and gender (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), while others have found a link (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Nevertheless, a strong link between feminine gender and DED was documented through previous studies, which could be attributed to the different hormone levels throughout female life that affect the lacrimal gland and ocular surface, potentially explaining the higher prevalence of DED in women in particular studies (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). However, in this study, no independent correlation between DED and gender was identified (p\u0026thinsp;=\u0026thinsp;0.531).\u003c/p\u003e \u003cp\u003eDED prevalence was higher in smokers, but the difference was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.187), in agreement with other studies (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), while other reports showed an association (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). This may be explained by exposure to tobacco smoke, which can impair ocular surface defense and retinal nerve fiber layer, along with impacting tear film secretion and stability (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eArtificial tears are used to lubricate dry eyes and keep the outer surface of the eyes hydrated. Traditionally, they have been utilized as a first-line therapy to alleviate symptoms at every stage of DED treatment. Nevertheless, its primary purpose is to prevent the accumulation of symptoms rather than to alleviate them, as a recent study mentioned (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). In the presented study, the use of lubricant eye drops was more among those having DED (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than those who did not have DED. That agreed with previous studies (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, no association with ocular diseases and DED (p\u0026thinsp;=\u0026thinsp;0.603), but a significant correlation was observed between systemic diseases and DED (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This could be explained by the fact that 68.8% of the study participants who have DED are within the older age group (\u0026gt;\u0026thinsp;35 years) and more likely to have systemic comorbidities. Paulsen et al. conducted comprehensive research on the link between DES and systemic disorders and found that dry eyes can be caused by systemic disorders like allergies, arthritis, and thyroid disease (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). While other meta-analysis studies found that hypertension and DM were associated with an increased risk of DED (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDED onset and progression has been linked to several systemic drugs, such as anxiolytics, antidepressants, antihistamines, and antihypertensive medications (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). In support of this, the present study confirmed that intake of systemic medication was independently associated with DED (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The present study also found a significant association between participants who had a previous diagnosis of DED and active DED (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eFor employment factors, the frequency of DED was higher (68.5%) among participants who had worked for more than 15 years. Despite this, the difference was marginally significant (p\u0026thinsp;=\u0026thinsp;0.053). However, another study finds no connection between DED severity and work experience (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough not statistically significant (p\u0026thinsp;=\u0026thinsp;0.658), the prevalence of DED was highest among participants who spent more than 10 hours at work daily (65.9%). Digital screen time is strongly linked to DED, as indicated by numerous studies (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). An increase in digital screen time of one hour per day was linked to 1.14 higher odds of developing dry eye illness (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). The reason for this correlation may be that while performing tasks requiring a lot of visual processing, specifically activities with higher cognitive demands, the spontaneous blink reflex is suppressed. Consequently, low blink rate and partial blinking lead to unstable tear films and poor tear lipid layer integrity (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). According to Wang et al., DED was independently linked to more hours spent in front of a digital screen each day (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Nevertheless, the current study found no correlation between DED and screen time on electronic devices (p\u0026thinsp;=\u0026thinsp;0.165). Moreover increasing use of smartphones, laptops, desktop computers, iPads, and televisions has led to an increase in the prevalence of DED. Interestingly, the current study has only found an independent relationship between using a television and not using any kind of device.\u003c/p\u003e \u003cp\u003eAlthough not being sight-threatening symptoms, as the dryness progresses or worsens, they become more troubling and burdensome for the sufferers (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), consistent with this study that found a considerable impact of DED on work productivity and non-job-related daily activities, Productivity loss was evident in all groups of dry eye severity, but it increased sharply as severity increased. Work productivity decreased by 13.66% for patients with mild DED, 15.93% for those with moderate DED, and 20.4% for those with severe DED. For non-work-related activities, impairment was increased similarly as severity increased. It has been demonstrated that DED affects job attendance more than absenteeism; only a small percentage of responders missed work because of their DED; patients with severe DED missed an average of 4 work hours each week.\u003c/p\u003e \u003cp\u003eThe outcomes of this study are in alignment with previously published data regarding the effect of DED on work productivity and performance of non\u0026ndash;work-related activities using the WAPI questionnaire in 158 patients attending clinics for relief of dry eye symptoms, indicating that dry eye resulted in a loss of 0.36% of work time and ~\u0026thinsp;30% impairment of workplace performance (presenteeism), work productivity, and non\u0026ndash;job-related activities. Presenteeism and productivity impairment scores showed significant correlation with OSDI total (r\u0026thinsp;=\u0026thinsp;0.55); the activity impairment score showed a stronger correlation with OSDI total (r\u0026thinsp;=\u0026thinsp;0.61) (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe impairment to both employment and daily activities imposed by DED, as indicated in this study, contributes to the burden for patients who have been proven to have decreased quality of life and psychological stress due to their condition (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTo sum up, the prevalence of DED among worker categories in a previously unexamined Palestinian population was found to be 61.4%, which is quite significant. Moreover, considering the diverse environmental working conditions, outdoor workers are more prone to experience dry eye symptoms compared to indoor workers. Additionally, employees with DED report reduced productivity and face difficulties with daily activities, regardless of the severity level. These results highlight the critical need for implementing effective protective strategies in the workplace, such as utilizing eye shields that would be protective against environmental irritants and pollutants, as well as enhancing indoor working conditions, which could substantially lower the risk and progression of DED. Efforts should be directed towards enhancing societal awareness about DED to reduce its modifiable risk factors.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDED: Dry Eye Disease, OSDI: \u0026nbsp;The Ocular Surface Disease Index questionnaire, WPAI: The Work Productivity and Activity Impairment questionnaire.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBefore collecting data, institutional review board approval was obtained from An-Najah National University (Ref: Med. Dec. 2023/91), and permissions were granted by companies\u0026rsquo; managers before we started this study. We obtained informed consent from the participants, ensuring their privacy and confidentiality, by choosing a quiet and secluded area away from others. We needed to ensure sufficient physical distance to prevent easy overhearing, speak softly, and avoid sensitive questions in public. We used a cover sheet to help shield responses, and we were mindful of participants\u0026apos; comfort through attentive body language during the interview. And participants\u0026rsquo; data was to be only accessible by researchers. Participation in our study was entirely voluntary, and participants had the right to withdraw from the study at any time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable in this section\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no conflict of interest declared by all authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo financial support\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSA, SS, QS, JQ, HA, SA Conceptualization, Data Collection, and writing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJQ, SA, SS, QS analysis and interpretation of data\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHA. SA, SS, QS, JQ, SA drafted the work and revised it\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All Authors approved the submitted version, agreed both to be personally accountable for the contributions and integrity of any part of the work\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) would like to thank An-Najah National University (www.najah.edu) for the technical support provided to publish the present manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCourtin R, Pereira B, Naughton G, Chamoux A, Chiambaretta F, Lanhers C et al. Prevalence of dry eye disease in visual display terminal workers: A systematic review and meta-analysis. 6, BMJ Open. 2016.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLollett IV, Galor A. Dry eye syndrome: Developments and lifitegrast in perspective. 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J Korea Academia-Industrial cooperation Soc. 2016;17(10).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePaulsen AJ, Cruickshanks KJ, Fischer ME, Huang GH, Klein BEK, Klein R, et al. Dry eye in the beaver dam offspring study: Prevalence, risk factors, and health-related quality of life. Am J Ophthalmol. 2014;157(4):799\u0026ndash;806.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBritten-Jones AC, Wang MTM, Samuels I, Jennings C, Stapleton F, Craig JP. Epidemiology and Risk Factors of Dry Eye Disease: Considerations for Clinical Management. Medicina. 2024;60(9):1458.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBinyousef FH, Alruwaili SA, Altammami AF, Alharbi AA, Alrakaf FA, Almazrou AA. Impact of dry eye disease on work productivity among Saudi workers in Saudi Arabia. Clin Ophthalmol. 2021;15:2675\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUchino M, Schaumberg DA, Dogru M, Uchino Y, Fukagawa K, Shimmura S, et al. Prevalence of Dry Eye Disease among Japanese Visual Display Terminal Users. Ophthalmology. 2008;115(11):1982\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTitiyal JS, Falera RC, Kaur M, Sharma V, Sharma N. 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\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang MTM, Muntz A, Mamidi B, Wolffsohn JS, Craig JP. Modifiable lifestyle risk factors for dry eye disease. Contact Lens Anterior Eye. 2021;44(6).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwartz SG, Ceecee Britten-Jones A, Wang MTM, Samuels I, Jennings C, Stapleton F, et al. Epidemiology and Risk Factors of Dry Eye Disease: Considerations for Clinical Management. Medicina 2024. Page 1458. 2024;60(9):1458.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMertzanis P, Abetz L, Rajagopalan K, Espindle D, Chalmers R, Snyder C et al. The relative burden of dry eye in patients\u0026rsquo; lives: Comparisons to a U.S. normative sample. Invest Ophthalmol Visual Sci. 2005;46(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNichols KK, Bacharach J, Holland E, Kislan T, Shettle L, Lunacsek O et al. Impact of dry eye disease on work productivity, and patients\u0026rsquo; Satisfaction with Over-The-Counter dry eye treatments. Invest Ophthalmol Visual Sci. 2016;57(7).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDana R, Meunier J, Markowitz JT, Joseph C, Siffel C. Patient-Reported Burden of Dry Eye Disease in the United States: Results of an Online Cross-Sectional Survey. Am J Ophthalmol. 2020;216.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Dry eye disease, Outdoor workers, Indoor workers, Work productivity","lastPublishedDoi":"10.21203/rs.3.rs-5868558/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5868558/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDry Eye Disease (DED) is a multifactorial ocular condition characterized by the disturbance of the tear film and interpalpebral ocular surface. It is characterized by ocular itchiness, grittiness, burning, and visual disturbances. Many risk factors were linked to DED, including occupational-related risk factors. This study aimed to investigate the prevalence and impact of DED on work productivity among outdoor and indoor occupational workers in the West Bank of Palestine and the impact of DED on daily activities performance\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA population-based descriptive cross-sectional study was conducted on male and female Palestinian workers aged 18 years or older, carried out between June and October 2024. A total of 464 participants were included and completed a structured interview questionnaires using the Arabic version of the Ocular Surface Disease Index questionnaire (Arab-OSDI) and the Work Productivity and Activity Impairment questionnaire (WPAI) for participants who scored 13 or higher on OSDI.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe prevalence of DED in Palestinian workers was 61.4%, which was higher among outdoor workers (64.7%) than indoor workers (58.2%), but this difference was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.153). The impact of DED on work performance was reported in all severity levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); participants with severe DED had a mean of 5.93 hours, which is higher than the mean for moderate and mild DED patients (4.71 and 3.42 hours), respectively. Similarly, the impact on the ability to perform daily activities was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), greatest among respondents with severe disease (5.86 hours).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eDry eye disease is more likely to develop in outdoor workers than in office workers. Meanwhile, workers with DED report lower productivity and struggle with everyday tasks regardless of the severity level. This underlines the detrimental effects of the workplace on the ocular surface, which present a significant risk for the onset and exacerbation of dry eye symptoms.\u003c/p\u003e","manuscriptTitle":"Prevalence of Dry Eye Disease among Indoor and Outdoor Workers and The Impact on Work Productivity in the West Bank of Palestine in 2024: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-11 09:31:09","doi":"10.21203/rs.3.rs-5868558/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision 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