Prevalence and Determinants of Visual Impairment among Individuals Aged 40 Years and Above Attending Military Hospitals in Addis Ababa, 2025: A Cross-Sectional Study

Prevalence and Determinants of Visual Impairment among Individuals Aged 40 Years and Above Attending Military Hospitals in Addis Ababa, 2025: 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 Article Prevalence and Determinants of Visual Impairment among Individuals Aged 40 Years and Above Attending Military Hospitals in Addis Ababa, 2025: A Cross-Sectional Study Mr. Meles Gizachew, Teshome Habte, Zeleke Argaw, Aklil Hailu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8243267/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Visual impairment (VI) remains a significant public health concern in Ethiopia, particularly among adults aged 40 years and above, where it is often attributable to preventable or treatable causes. This study aimed to assess the prevalence and determinants of VI among this population in military hospitals in Addis Ababa. Objective To determine the prevalence and identify associated factors of visual impairment among individuals aged 40 years and above attending selected military hospitals in Addis Ababa. Methods A facility-based cross-sectional study was conducted from January 20 to February 20, 2025, involving 213 participants selected through systematic random sampling (every 8th eligible adult patient from the follow-up registry). Data were collected using structured questionnaires and standardized vision assessment tools. Descriptive statistics summarized demographic and clinical characteristics. Chi-square tests assessed associations between categorical variables and VI. Bivariate and multivariate logistic regression analyses were performed to identify significant predictors at a p-value < 0.05. Result The mean age of participants was 56 years (range 40–92), with 63% male and 46.5% retired. The prevalence of visual impairment was 51.6%. Major associated conditions included cataracts (33.8%), hypertension (29.1%), and diabetes mellitus (25.8%). Significant predictors of VI included older age, cataracts, glaucoma, refractive errors, diabetes mellitus, cigarette smoking, and difficulty watching television. Conclusion Visual impairment affects over half of the study population and is significantly associated with modifiable and age-related factors. Early detection and targeted eye care services are urgently needed for this high-risk group. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors Prevalence Determinants Visual Impairment Adults Aged 40+ Military Hospitals Addis Ababa Figures Figure 1 Brief information on the study What is already known in this topic? Visual impairment is a growing concern among adults aged 40 and above, with age-related eye conditions such as cataracts, glaucoma, and diabetic retinopathy being common causes. However, limited data exist on its prevalence and determinants among military hospital attendees in Ethiopia. What this study adds? This study provides current evidence on the high prevalence of visual impairment among adults aged 40 and above in military hospitals in Addis Ababa and identifies key associated factors, supporting the need for targeted screening, early intervention, and improved eye care services within this population. How this study might affect research practice, or policy? This study may influence research and policy by highlighting the need for routine vision screening and integrated eye care in military health services, guiding resource allocation, and informing national strategies aimed at reducing preventable visual impairment among older adults in Ethiopia. 1. Introduction 1.1. Background Information According to the World Health Organization (WHO), visual impairment is defined as a decrease in vision that cannot be fully corrected with glasses, contact lenses, medication, or surgery. WHO classifies visual impairment based on visual acuity in the better eye: mild visual impairment is worse than 6/12 but equal to or better than 6/18; moderate visual impairment is worse than 6/18 but equal to or better than 6/60; severe visual impairment is worse than 6/60 but equal to or better than 3/60; and blindness is defined as worse than 3/60. Visual impairment may manifest as difficulty seeing clearly even with corrective lenses, trouble reading or recognizing faces, issues with navigation, or partial to total loss of vision [1-3]. Globally, the prevalence of visual impairment increases significantly with age. Estimates suggest that 10–20% of individuals aged 40 years and above are affected by some degree of VI, and this figure is expected to rise due to increasing life expectancy and the growing aging population. In Ethiopia, like many low- and middle-income countries, limited access to preventive eye care services exacerbates the burden, particularly among older adults [1, 2]. Multiple factors are associated with the risk of visual impairment in this demographic group. These include socio-demographic variables (age, sex, education, occupation, and residence), medical conditions such as cataracts, glaucoma, diabetic retinopathy, hypertension, and uncorrected refractive errors, as well as behavioral and lifestyle factors like smoking and alcohol use. Low awareness and poor health-seeking behavior further hinder timely diagnosis and treatment [3, 4]. Visual impairment severely compromises quality of life, restricting daily activities, reducing independence, and increasing the risks of falls, social isolation, and mental health conditions such as depression. Its impact is not only personal but also economic, as it limits productivity and increases healthcare costs [5, 6]. In this context, understanding the prevalence and determinants of visual impairment among individuals aged 40 years and above, particularly in unique populations such as military hospital attendees in Addis Ababa, is vital. The findings can inform targeted screening initiatives, policy interventions, and the development of comprehensive, accessible, and age-appropriate eye care services. 1.2. Statement of the Problem Visual impairment (VI) refers to a significant reduction in visual function that cannot be fully corrected with conventional means such as glasses, contact lenses, medication, or surgery. It presents a major global and national health challenge, particularly among older adults, where preventable and treatable causes remain widespread and under-addressed. VI often manifests as blurred vision, night blindness, reduced peripheral vision, difficulty recognizing faces, light sensitivity, and challenges in depth or color perception symptoms that significantly impair daily functioning and quality of life [2, 4]. Globally, over 2.2 billion people are affected by some form of visual impairment, with at least 1 billion cases potentially preventable or untreated. An estimated 237 million individuals suffer from moderate to severe distance VI, and nearly 39 million are blind a figure expected to rise to 115 million by 2050. In the African region alone, approximately 26.3 million people live with VI, including 5.9 million who are blind. Ethiopia faces one of the highest burdens, with an estimated 1.18% blindness prevalence, largely attributable to cataracts, uncorrected refractive errors, diabetic retinopathy, and glaucoma. Notably, over 80% of these cases are preventable [7, 8]. Despite the growing burden, there is a paucity of data specifically addressing visual impairment among individuals aged 40 and above within military hospital settings in Ethiopia. This demographic may face unique exposures and risk factors. Therefore, this study aims to assess the prevalence and determinants of VI in military hospitals in Addis Ababa, providing critical insights to guide targeted eye care interventions, strengthen service delivery, and inform national efforts to combat avoidable blindness within this population. 1.3. Significance of the Study This study holds substantial value for multiple stakeholders. For the general public, particularly individuals aged 40 and above, the findings will support early detection and management of visual impairment, ultimately improving quality of life and reducing disability. Within military hospital settings, the results can enhance vision screening protocols, guide targeted interventions, and inform strategic allocation of resources to address preventable causes of vision loss. For healthcare professionals, the study offers evidence to support improved clinical decision-making and the development of tailored patient education and outreach programs. Policymakers will benefit from data-driven insights to design and implement age-sensitive, community-based eye care strategies. Additionally, the study serves as a foundational reference for future researchers exploring visual health among aging populations, fostering further investigation and interdisciplinary collaboration. Overall, the research aims to contribute to improved eye care services and public health planning for both military personnel and the broader civilian population in Ethiopia. Research Questions 1. What is the prevalence of visual impairment among individuals aged 40 years and above attending selected military hospitals in Addis Ababa, Ethiopia? 2. What socio-demographic, health-related, and lifestyle factors are associated with visual impairment among individuals aged 40 years and above in the study setting? 1.3. Conceptual Framework The conceptual framework of this study is informed by existing literature that identifies multiple factors influencing visual impairment among adults aged 40 years and above. Key determinants include demographic factors (such as age, sex, and education), health-related conditions (like diabetes and hypertension), lifestyle behaviors (smoking, alcohol use), and individual attitudes toward eye health and care-seeking. These independent variables are hypothesized to directly or indirectly affect the occurrence of visual impairment, the dependent variable. Understanding these interrelationships provides a foundation for identifying at-risk populations and guiding targeted interventions in military hospital settings [2, 3, 5, 7]. 2. Objectives of the study 2.1. General Objective To assess the prevalence and determinants of visual impairment among individuals aged 40 years and above attending selected military hospitals in Addis Ababa, Ethiopia, in 2025. 2.2. Specific Objectives To determine the prevalence of visual impairment among individuals aged 40 years and above in selected military hospitals in Addis Ababa, Ethiopia. To identify socio-demographic, health-related, and lifestyle factors associated with visual impairment among individuals aged 40 years and above in the study setting. 3. Methods and Materials 3.1. Study Area This study was conducted in two major military healthcare institutions (Hospital) in Addis Ababa, Ethiopia: the Armed Forces Comprehensive Specialized Hospital (AFCSH) and the Federal Police Hospital. Addis Ababa, the capital and largest urban center of Ethiopia, is a political, economic, and healthcare hub with an estimated population of 5.7 million in 2024, according to the Central Statistical Agency. AFCSH is a tertiary-level referral facility providing specialized services in ophthalmology, cardiology, oncology, and neurology, among others. It serves both military personnel and civilians, equipped with advanced diagnostic tools such as MRI, CT scan, and comprehensive laboratory services [ 9 , 10 ]. The Federal Police Hospital, located in Lideta Sub-City, primarily serves members of the federal police force and their families. It functions as a referral center, offering both emergency and routine medical services in internal medicine, surgery, orthopedics, and ophthalmology, supported by modern infrastructure and medical insurance coverage. Both hospitals were selected due to their diverse patient population aged 40 and above, access to ophthalmologic services and their strategic roles in the military health system, making them suitable for assessing the prevalence and determinants of visual impairment. 3.2. Study Design and Period An institution-based cross-sectional study design was employed to assess the prevalence and determinants of visual impairment among individuals aged 40 years and above attending military hospitals in Addis Ababa. This design was selected to capture a snapshot of the population's visual health status and associated risk factors within a defined time frame. The study was conducted over a one-month period, from January 20 to February 20, 2025. 3.3. Study Population The study population consisted of individuals aged 40 years and above attending the ophthalmology units of Armed Forces Comprehensive Specialized Hospital and Federal Police Hospital in Addis Ababa during the study period. This included active-duty members of the Ethiopian Defense Forces, military veterans residing in or around Addis Ababa, and eligible family members of military personnel. Participants were selected using a systematic random sampling method from among those seeking eye care services during the data collection period. Individuals who met the inclusion criteria and provided informed consent were considered for participation in the study. 3.4. Eligibility Criteria To ensure the appropriateness and reliability of the data, specific inclusion and exclusion criteria were applied: 3.4.1. Inclusion Criteria: Individuals aged 40 years and above who attended the ophthalmology departments of the selected military hospitals during the data collection period. Participants who were able and willing to provide informed written consent to participate in the study. 3.4.2. Exclusion Criteria: Individuals who declined to participate or withdrew consent at any stage of the study. Patients who had already participated in the study during an earlier visit and returned for follow-up care during the same data collection period, to avoid duplication of data. Individuals with severe cognitive or communication impairments that hindered effective interview or examination, as judged by the attending clinician. 3.5. Sample Size Determination, Sampling Technique, and Procedure 3.5.1. Sample Size Determination The required sample size for this study was calculated using a single population proportion formula, based on an estimated prevalence of visual impairment among adults aged 40 years and above in Ethiopia. n = 240. Since the total target population (N = 1,860) is less than 10,000, the finite population correction formula was applied: Thus, the final sample size was rounded to 213 participants (n = 213). 3.5.2. Sampling Technique and Procedure This study was conducted in two military hospitals located in Addis Ababa: the Army Forces Comprehensive Specialized Hospital (AFCSH) and the Federal Police Referral Hospital (FPRH). Both institutions were purposively selected due to their high patient volume and relevance to the military health system. To ensure equitable representation, the total sample size was proportionally allocated to each hospital based on patient flow data for individuals aged 40 years and above from outpatient departments (OPD) during October 2024 as shown in Table 1 below. According to hospital records, AFCSH reported 1,048 adult patients aged ≥ 40 years, while FPRH reported 812 patients in the same age group. Table 1 Proportional Sample Size Allocation at AFCSH and Federal Police Referral Hospitals SN Hospital Patients (≥ 40 yrs.) Proportion (%) Sample Size 1 AFCSH 1,048 56% 119 2 Federal Police Referral Hospital. 812 44% 94 Total 1,860 100% 213 A systematic random sampling technique was employed to select participants from the OPD register of each hospital. Accordingly, every 8th adult patient aged 40 years and above presenting at the OPD during the study period was selected for participation. The first participant was chosen randomly from the first 1 to 8 attendees using a lottery method. A list of eligible patients was generated using medical record numbers to ensure systematic inclusion and avoid duplication. 3.6. The study Variables 3.6.1. Dependent Variable : Visual Impairment (VI): 3.6.2. Independent Variables: The independent variables include a range of socio-demographic, clinical, behavioral, environmental, and psychosocial factors that may influence visual impairment. These are categorized as follows: A. Demographic Factors : age, Sex, occupation, educational level, marital status, and monthly income. B. Health-Related Factors : Self-reported history or clinical diagnosis of: Cataract, Glaucoma, Refractive error. (e.g., myopia, hyperopia, astigmatism) Ocular trauma Diabetic retinopathy Systemic hypertension Diabetes mellitus C. Lifestyle and Awareness-Related Factors : cigarette smoking, excessive use of alcohol, regular eye check-ups. D. Environmental and Occupational Factors : primary work environment, time spent on screen per day, access to regular eye care, and using protective eyewear. E. Social and Psychosocial Factors : living arrangement, feeling of social network, and social participation. 3.7. Operational Definitions of Key Terms Normal Vision : Best-corrected visual acuity (BCVA) of 20/20 on the Snellen chart. Visual Impairment (VI) : Defined based on standardized classifications of visual acuity as measured using a Snellen chart or equivalent method. Mild Visual Impairment (Low Vision) : BCVA between 20/30 and 20/60 in the better eye. Moderate Visual Impairment : BCVA between 20/70 and 20/150 in the better eye. Severe Visual Impairment : BCVA between 20/200 and 20/400 in the better eye; often referred to as "legal blindness." Profound Visual Impairment : BCVA worse than 20/500 in the better eye. Intraocular Pressure (IOP) : The fluid pressure inside the eye. Normal IOP ranges from 10 to 21 mmHg. Ocular Hypertension : Elevated IOP greater than 21 mmHg without detectable damage to the optic nerve or visual field defects. Glaucoma : A group of eye conditions characterized by IOP greater than 21 mmHg with progressive optic nerve damage and visual field loss [1, 2, 3, 9, 10]. 3.8. Data Collection Tools and Procedures 3.8.1. Data Collection Tools The primary data collection instrument was a structured, interviewer-administered questionnaire developed based on a synthesis of insights from four prior studies conducted in Ethiopia [11, 12]. These foundational studies provided a culturally and contextually relevant framework by incorporating locally significant socio-demographic, health, lifestyle, and environmental variables. The tool was designed to reflect the social realities, health care utilization patterns, and awareness levels of the Ethiopian adult population, particularly those attending military health facilities. The questionnaire was initially developed in English and subsequently translated into Amharic to ensure linguistic and cultural appropriateness. A back-translation into English was performed by an independent bilingual expert to verify consistency and semantic equivalence. Revisions were made to resolve any discrepancies noted during the back-translation process. The final version of the questionnaire was organized into six thematic sections: Demographic Characteristics : Seven items capturing age, sex, marital status, education level, occupation, income, and residence. Health-Related Factors : Eight items assessing self-reported and clinically confirmed conditions such as glaucoma, cataract, refractive errors, ocular trauma, diabetic retinopathy, and systemic diseases (e.g., hypertension). Lifestyle, Attitude, and Awareness : Seven items exploring behaviors like smoking, alcohol use, frequency of eye check-ups, and general awareness of eye health. Environmental Factors : Five items assessing exposure to occupational or environmental risks (e.g., screen time, use of protective eyewear, work environment). Social Factors : Six items evaluating living arrangements, social support, and community participation. Visual Impairment Symptoms and Impact : Seven items documenting participants’ subjective visual symptoms and the functional impact on daily activities. Responses were recorded on pre-coded, closed-ended formats to standardize data collection and facilitate analysis. In addition, clinical parameters—such as intraocular pressure, best-corrected visual acuity (via Snellen chart), and diagnoses from ophthalmologic examinations were extracted from medical records and entered into the questionnaire by trained data collectors. 3.8.2. Data Collection Procedures Data collection was conducted by a team of four trained ophthalmic professionals two from the Army Forces Comprehensive Specialized Hospital (AFCSH) and two from the Federal Police Referral Hospital—supported by two supervisors from each facility’s outpatient department. A one-day training session was provided to all data collectors and supervisors by the principal investigator. The training covered: Study objectives and research questions, detailed review of each item in the questionnaire, informed consent procedures, confidentiality and ethical considerations and proper interview techniques and data recording methods. Eligible participants were identified at the outpatient departments using a systematic random sampling method. Upon obtaining informed consent, participants were interviewed in a private setting before their clinical consultation. Data collectors administered the questionnaire and recorded responses directly. Following the initial interview, medical charts were reviewed to extract relevant clinical information, including documented diagnoses (e.g., glaucoma, cataract, diabetic retinopathy) and systemic conditions (e.g., hypertension and diabetes). Visual acuity testing was performed by ophthalmologists using a Snellen chart under standardized lighting conditions. Participants identified as visually impaired based on acuity criteria were invited to complete the remaining interview sections focusing on the impacts of vision loss. To ensure data accuracy and consistency: blood pressure was measured using a calibrated digital sphygmomanometer to verify hypertensive status; diagnosis of glaucoma was confirmed through chart review, incorporating IOP measurement and optic nerve assessment; ophthalmic examination findings were verified jointly by the attending ophthalmologist and the data collector. Supervisors performed routine checks and verified completeness and quality of data collected at the end of each day. 3.9. Data Quality Assurance To ensure the validity, reliability, and consistency of the data collected, multiple quality assurance strategies were employed throughout the research process: A standardized and pre-tested structured questionnaire was developed using comprehensive, relevant literature and contextualized for the Ethiopian setting and a pilot study was conducted involving 5% of the target sample size (n = 21 participants) at the Ground Army Level II health facility in Addis Ababa. The purpose of this pre-test was to assess the clarity, consistency, and cultural appropriateness of the tool, as well as to identify any logistical challenges in data collection. Feedback obtained from the pre-test was used to revise ambiguous items, rephrase unclear wording, and restructure question flow to enhance comprehensibility. Training for data collectors and supervisors were conducted. The training focused on research objectives, ethical considerations, informed consent procedures, interviewing techniques, accurate data recording, and proper handling of sensitive medical information. Furthermore, visual acuity assessments and clinical diagnoses were validated by ophthalmologists to minimize diagnostic misclassification. 3.10. Data Processing and Analysis Following data collection, all completed questionnaires were reviewed for completeness and consistency. Data were then coded, with categorical responses assigned numeric values to facilitate statistical analysis. The data coding process also involved identifying any missing values, inconsistencies, or outliers. Cleaned data were entered into EpiData version 4.6 using a double-entry system to minimize entry errors. Discrepancies between entries were cross-checked and resolved using source documents and verified dataset was exported to Statistical Package for Social Sciences (SPSS) version 28 for further analysis. The data analysis proceeded with descriptive Statistics and Multivariate Logistic Regression Analysis applied. A p-value of less than 0.05 was considered statistically significant. Results were interpreted in light of existing evidence and contextual factors. 4. Result 4.1 Demographic Characteristics of the Participants A total of 213 individuals participated in this study, yielding a 100% response rate. Participants were stratified into seven age categories, with the largest proportion, 45 participants (21.2%), falling within the 40–44 year age group. The participants’ ages ranged from 40 to 92 years, with a mean age of 56 years (± SD) and a median age of 53 years. The sample was predominantly male, comprising 136 participants (63.8%), while female participants accounted for 77 (36.2%). Regarding marital status, the majority 166 participants (77.9%) were married. In terms of military service, 61 respondents (28.6%) had served or were actively serving in the military for duration of 10 to 20 years. Educational attainment varied, with 72 participants (33.8%) having completed higher education. With respect to occupational status, 99 participants (46.5%) were retired at the time of the study as shown in Table 2 below. Lastly, the majority of the participants 193 individuals (90.6%) resided in urban areas, indicating a primarily urban-based study population. Table 2 Socio-demographic Characteristics of Participants Aged 40 Years and Above Attending Selected Military Hospitals in Addis Ababa, Ethiopia, 2025 (n = 213) Variables Category Frequency (N) Percentage(%) Age 40–44 45–49 50–54 55–59 60–64 65–69 70 and above 45 32 31 23 23 22 37 21.1 15.0 14.6 10.8 10.8 10.3 17.4 Sex Male Female 136 77 63.8 36.2 Marital status Single Married Divorced Widowed 20 166 13 14 9.4 77.9 6.1 6.6 Service in years 0–10 years 11–20 21–30 Above 30 Civil 42 61 57 41 12 19.7 28.6 26.8 19.2 5.6 Educational level write Unable to read and Able to read and write Primary school Secondary school Higher education 14 19 55 53 72 6.6 8.9 25.8 24.9 33.8 Occupation Active military Retired Civil worker Family of active military 79 99 20 15 37.1 46.5 9.4 7.0 Residence Urban Rural 193 20 90.6 9.4 4.2 Health History Characteristics of the Participants The health history of the study participants, with a focus on ocular and related systemic conditions, revealed several noteworthy findings. Among the 213 individuals assessed, 72 (33.8%) were diagnosed with cataracts, indicating a significant burden of age-related eye disease within the study population. In terms of comorbid chronic conditions, 62 participants (29.1%) reported a history of hypertension, while 55 (25.8%) were living with diabetes mellitus. These conditions are known to have potential ocular complications, including hypertensive and diabetic retinopathies. Visual acuity assessment using the Snellen chart showed that 103 participants (48.4%) had normal visual acuity (6/6) at the time of examination. Moreover, 100 participants (46.9%) reported having undergone an eye examination within the current calendar year, reflecting moderate engagement with routine eye health services. 4.3 Attitude and Lifestyle Characteristics of the Participants The lifestyle and attitudinal profiles of the study participants revealed several behaviors relevant to eye health and overall well-being. Of the 213 participants, 65 (30.5%) reported being current cigarette smokers. Among these, 23 individuals (35.4%) had a smoking history exceeding 20 years, which may pose increased risk for various ocular and systemic health issues. Excessive alcohol consumption was reported by 93 participants (43.7%), while 68 of these individuals (73.1%) indicated they consumed alcohol occasionally, suggesting varying patterns of intake within the group. Regular engagement in physical activity was limited, with only 59 participants (27.7%) reporting daily physical exercise. This may have implications for the management of chronic conditions associated with visual impairment, such as diabetes and hypertension. Regarding attitudes toward eye health, 95 participants (44.6%) expressed concern about the condition of their eyes. Notably, a substantial majority 188 participants (88.3%) acknowledged the importance of undergoing regular eye examinations, indicating a relatively high level of awareness regarding preventive eye care. 4.4. Socio-Environmental Characteristics of the Participants The socio-environmental profile of the participants revealed several contextual factors that may influence visual health and access to care. Among the 213 respondents, 83 individuals (39.0%) reported that their primary work environment was home-based. Additionally, 60 participants (28.2%) stated they spent between one to three hours daily in front of digital screens, which may have implications for visual strain and ocular health. Regarding occupational safety, 104 participants (48.8%) reported using protective eyewear while on duty, reflecting moderate adherence to eye safety practices. Access to eye care services was reported by 122 participants (57.3%), and 144 individuals (67.6%) indicated that transportation did not pose a barrier to receiving such services. In terms of living arrangements, 167 participants (78.4%) lived with their families, and 171 (80.3%) reported interacting with family members on a daily basis. When assessing perceived social support, 167 participants (78.4%) expressed feeling that they had a strong support network. Additionally, 122 participants (57.3%) reported participation in social or community-related activities during the past year. A total of 173 participants (81.2%) stated that they had someone available to assist them with daily activities when needed. Finally, 136 participants (63.8%) reported no difficulty participating in social situations due to vision-related problems, indicating that visual impairment did not significantly affect their social engagement in most cases. 4.5. Prevalence and Factors Associated with Visual Impairment The overall prevalence of visual impairment among participants aged 40 years and above was 51.6%. The condition was more common among individuals aged 70 and above (14.6%) and retired participants (31.5%). Married individuals accounted for 42.7% of cases. Cataracts were the leading ocular condition, affecting 24.9% of visually impaired participants, followed by diabetes mellitus (20.2%). Moderate visual impairment was the most prevalent severity level (25.8%). Notably, only 27.0% had undergone an eye examination in the past year. Lifestyle factors included cigarette smoking (46.3%), with 31% having smoked for over 20 years, and alcohol consumption (45.5%), with 41% drinking occasionally. One-third (33%) did not engage in physical exercise. Despite this, 46.2% expressed concern about their eye health, and 89.1% acknowledged the importance of regular eye check-ups. About 67% rated their eyesight as poor. Socio-environmentally, 29.1% worked primarily from home, and 20.2% used screens for less than one hour daily. Protective eyewear use was reported by 27.7%, and 28.2% had regular access to eye care services. Additionally, 41.8% lived with their families, 40.8% reported strong social support, and 24.9% experienced no social limitations due to visual impairment. 4.6 Bivariate and Multivariate Analysis for the Occurrence of Visual Impairment In this study, bivariate logistic regression analysis was conducted to explore the association between visual impairment and a range of independent variables. These included demographic factors (age, sex, years of service, educational level, and occupation), ocular conditions (cataract, glaucoma, and refractive errors), systemic health conditions (diabetes mellitus and hypertension), and functional limitations (difficulty in watching television, recognizing faces, and reading printed materials). Behavioral and lifestyle variables—such as cigarette smoking, excessive alcohol consumption, level of physical activity, concern about eye health, regular eye examinations, use of protective eyewear, and difficulty participating in social activities due to visual impairment—were also assessed. The results of this analysis are presented in Table 3 . Variables that were statistically significant in the bivariate analysis (p < 0.05) were entered into a multivariate logistic regression model to control for potential confounding. The multivariate analysis identified the following factors as independently and significantly associated with the occurrence of visual impairment: advanced age, presence of cataract, glaucoma, refractive errors, diabetes mellitus, cigarette smoking, and difficulty watching television. Each of these variables had a p-value less than 0.05, indicating a statistically significant relationship with visual impairment. Table 3 Bivariate and Multivariate Logistic Regression Analysis of Factors Associated with Visual Impairment among study Hospitals in Addis Ababa, Ethiopia (n = 213) Variables Category Visual impairment COR(95% CI) AOR(95% CI) P value Yes (%) No (%) Age 110(51.6) 103(48.4) 1 1.118(1.082–1.155) 1 1.073(1.035–1.113 .000* Cataract Yes No 53(24.9) 57(36.8) 19(8.5) 84(39.4) 4.11(2.205–7.663) 1 5.806(2.414–13.969) 1 .000* Glaucoma Yes No 40(18.8) 70(32.9) 18(0.9) 85(39.9) 2.698(1.423–5.117) 1 2.386(1.008–5.647) 1 .048* R.error Yes No 25(11.7) 85(39.9) 16(7.5) 87(40.8) 1.599(.798-3.205) 1 4.009(1.345–11.953) 1 .013* DM Yes No 43(20.2) 67(31.5) 12(5.6) 91(42.7) 4.867(2.385–9.933) 1 3.682(1.376–9.856) 1 .009* Difficulty watching TV Yes No 76(35.7) 34(16.0) 20(9.4) 83(39.0) 9.276(4.921–17.49) 1 3.616(1.616–8.091) 1 .002* Performing D.tasks Yes No 29(14.1) 81(44.6) 05(1.9) 98(39.4) 7017(2.598–18.95) 1 3.713(.856-16.106 1 .080 Cigarette smoking Yes No 51(19.7) 59(39,0) 14(3.3) 89(38.0) 5.495(2.793–10.812) 1 4.167(1.661–10.455) 1 .002* Note: constants are represented by the value 1, while an asterisk (*) denotes a statistically significant association. 5. Discussion This study explored the prevalence and determinants of visual impairment among individuals aged 40 years and older attending military hospitals in Addis Ababa. The overall prevalence of visual impairment was found to be 51.6%, significantly higher than rates reported in various international studies. For comparison, a population-based cross-sectional study in India reported a prevalence of 12.6% [ 13 ], while a community-based study in Sri Lanka indicated 21.3% [ 14 ]. Similarly, a study in China found a prevalence of 12.45% [ 6 ]. Within Ethiopia, previous studies have shown varying prevalence rates: Debre Birhan (16.8%), Addis Ababa (22.6%) [ 15 ], Gondar (15.3%) [ 16 ], and Northwest Ethiopia (40.8%) [ 11 ], with a community-based study in Southern Ethiopia reporting 36.95% [ 17 ].The higher prevalence observed in this study may be attributed to the unique demographic and health profiles of military personnel compared to the general population. Factors such as age, gender distribution, and physical fitness can significantly influence the prevalence of specific eye conditions. Additionally, military personnel typically undergo more frequent eye examinations and have better access to specialized care, facilitating earlier detection of vision-related issues that might go unnoticed in civilian populations. Psychological stress associated with military service, along with lifestyle factors such as diabetes mellitus and smoking, may further compromise visual health. In contrast, a retrospective chart review in South Africa reported an overall prevalence of 61.5% [ 18 ], exceeding our findings. This discrepancy may be due to differences in study design and participant age. This study highlights the prevalence of bilateral visual impairment among participants, with common symptoms including difficulties in reading and blurred vision. The significant impact of visual impairment on daily life is evident, as many participants reported challenges in everyday activities. This information is vital for healthcare professionals and policymakers, guiding the development of targeted interventions and support initiatives for those affected by visual impairment. And the finding reveals critical associations between various factors and the likelihood of visual impairment among older adults. Notably, the probability of experiencing visual impairment increases by approximately 7.3% with each additional year of age. This statistically significant relationship underscores the need for routine screenings and targeted interventions focused on visual health for older populations. The findings revealed a strong association between several modifiable and non-modifiable risk factors and the occurrence of VI, consistent with a growing body of global and regional evidence. Cataracts were the most prominent predictor of visual impairment in this population. Individuals with cataracts were found to have approximately 5.8 times higher odds of developing VI (AOR = 5.806, 95% CI: [exact interval to be inserted]), confirming cataract as a leading cause of visual disability. This aligns with the World Health Organization's (WHO) report, which continues to identify cataracts as the foremost cause of blindness globally, especially in low- and middle-income countries where access to surgical intervention may be limited [ 19 ]. Similarly, a community-based cross-sectional study conducted in Ghana reported a comparable adjusted odds ratio of 6.2 for cataract-related VI among adults over 40, reinforcing the global consistency of this association [ 20 ]. These findings highlight the necessity for routine cataract screening and timely surgical services within military health institutions. Glaucoma was another significant determinant in this study. Participants diagnosed with glaucoma had more than double the odds of visual impairment compared to those without (AOR = 2.36, p = 0.048). This is consistent with findings from a Nigerian hospital-based study where the prevalence of glaucoma-related visual impairment reached 21.4% among individuals aged 40 and above [ 21 ]. Given the irreversible nature of vision loss due to glaucoma, early detection through intraocular pressure measurement and optic nerve evaluation remains vital in reducing its impact. Refractive errors also showed a statistically significant association with visual impairment. Individuals with uncorrected or poorly corrected refractive errors were nearly four times more likely to experience VI (AOR = 4.009, p = 0.013). This is corroborated by the results of the Rapid Assessment of Avoidable Blindness (RAAB) survey in Ethiopia, which identified refractive error as the second most common cause of moderate VI [ 22 ]. This highlights the importance of improving access to affordable eye examinations and corrective lenses, particularly in military hospital settings where vision acuity is crucial for active personnel and retired servicemen alike. Diabetes mellitus (DM) emerged as a critical determinant. Diabetic participants had a 3.68-fold increased risk of VI (AOR = 3.682, p = 0.009), suggesting a strong association between diabetes and diabetic retinopathy, a well-known complication of uncontrolled blood glucose levels. A large-scale meta-analysis by Yau et al. found that nearly one-third of diabetic individuals globally exhibit signs of diabetic retinopathy, many of which result in vision loss [ 23 ]. Similarly, a study conducted in southern Ethiopia showed a significant burden of vision-threatening diabetic retinopathy among patients attending chronic disease clinics [ 24 ]. These findings reinforce the need for integrated eye care and diabetes management protocols to mitigate avoidable visual impairment. Moreover, limitations in performing routine daily activities, such as watching television, were significantly associated with VI. Participants who reported difficulty watching television had approximately 3.62 times greater odds of visual impairment (AOR = 3.616). This mirrors findings from Selangor in Peninsular Malaysia., which reported that difficulty with functional vision tasks is a sensitive indicator of both existing and developing VI among older adults [ 25 ]. These findings advocate for the inclusion of functional vision assessments in routine clinical evaluations, especially among older individuals who may underreport visual symptoms. Finally, cigarette smoking was identified as a modifiable lifestyle factor with a significant association with visual impairment. Smokers in the study exhibited more than four times the odds of VI compared to non-smokers (AOR = 4.167), consistent with previous meta-analyses that link smoking to age-related macular degeneration and cataracts [ 8 ]. This supports the role of targeted health education and smoking cessation programs as key components in preventing avoidable vision loss among older adults. 6. Strengths and Limitations 6.1. Strengths Targeted Population : Focusing on individuals aged 40 and above attending military hospitals allows for a specialized understanding of visual impairment in a specific demographic, enhancing the relevance of the findings. Military Context : The unique environment of military hospitals may provide insights into the prevalence of visual impairment influenced by occupational hazards or lifestyle factors specific to military personnel. Public Health Implications : The study has potential implications for public health policy, as understanding determinants can inform targeted interventions to improve eye health among this population. 6.2. Limitations Generalizability : Findings may not be applicable to the broader population outside military settings, limiting the external validity of the research. Sample Size and Selection Bias : If the sample size is small or not representative of all military hospital attendees, it could skew results and fail to capture the full spectrum of visual impairment. Cross-Sectional Design : A cross-sectional study design provides a snapshot in time but does not establish causality, making it difficult to determine the directionality of the relationships between determinants and visual impairment. 7. Conclusion and Recommendations 7.1. Conclusion This study revealed a prevalence of visual impairment of 51.6% among individuals aged 40 years and above in certain military hospitals, indicating a significantly high rate within this demographic. Key determinants of visual impairment identified include age, cataracts, glaucoma, refractive errors (RE), diabetes mellitus (DM), difficulties in watching television, and cigarette smoking. These findings underscore the urgent need for targeted interventions and comprehensive eye care among this population. 7.2. Recommendations Enhanced Screening Programs : Implement regular vision screening and assessment programs within military hospitals to identify individuals at risk and facilitate early intervention. Educational Outreach : Develop educational initiatives aimed at increasing awareness about eye health, risk factors for visual impairment, and the importance of regular eye examinations among military personnel and their families. Policy Development : Advocate for policies that prioritize eye health in military healthcare planning, ensuring resources are allocated for prevention, treatment, and rehabilitation of visual impairments. Further Research : Encourage longitudinal studies to explore the causal relationships between identified determinants and visual impairment, providing a deeper understanding of the underlying factors influencing eye health in this population. Abbreviations AFCSH: Army force comprehensive specialized hospital; AMA : Age-related degeneration BCVA: Best corrected macular degeneration; DM: Diabetes mellitus; DR : Diabetic retinopathy ERD : Eye related disease; FPH : Federal police hospital; HTN: Hypertension; RE : Refractive error; SPSS : Statistical Package for the Social Sciences VI: Vision impairment Declarations Acknowledgments The authors are grateful to Addis Ababa University for assigning research advisors and providing stationery items. We also appreciate the study participants for their willingness to participate and the time they dedicated during data collection. Additionally, we acknowledge the use of an AI tool for editing and grammar corrections in various parts of the manuscript. Ethics approval and consent to participate: A formal letter of ethical clearance and approval was obtained from the Institutional Review Board of Addis Ababa University (IRB-AAU) with protocol number SNM/03/2025, specifically from the School of Nursing and Midwifery's Department of Nursing Research Committee. Once ethical approval was secured, supportive letters were issued by the School of Nursing and Midwifery to the selected hospitals. Participants were informed about the study's objectives, and written permission was obtained from the hospital administrations prior to the initiation of data collection. Informed consent was secured from each participant immediately before data collection began. During the informed consent process, participants received a clear overview of the research and its objectives. They were informed that they could participate of their own free will and had the right to withdraw from data collection at any moment. To ensure the privacy of the participants' data, no personal identifiers were included in the data collection tool, thereby keeping their information confidential throughout the study. Consent for publication: Not-applicable. Availability of data and materials All essential data are included in the manuscript. For any additional data requests, please contact the corresponding author for further documentation. Competing interests This thesis is submitted as a partial achievement of the requirement for an MSc degree from the School of Postgraduate Studies at Addis Ababa University. This thesis has been deposited in the Library of Addis Ababa University and is made available to the user under the rules of the library. The authors declare that they have no conflicts of interest. Funding: Funding for this study was not provided by any institution or agency, but some stationary items, such as A4 size papers for photocopying data collection questionnaires, pencils, and research advisor assignments, were provided by the Addis Ababa University postgraduate office. Authors’ Contributions This study is the result of joint research, and the contribution of each author is comparable to the others. The roles of each author are as follows: 1. Meles Gizachew: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Project administration, Software, and Writing original draft. 2. Teshome Habte: Conceptualization, Data curation, Methodology, Project administration, Supervision, validation, visualization and Writing review and editing. 3. Zeleke Argaw: Conceptualization, Data curation, Investigation, Project administration, Supervision, validation, visualization and Writing review and editing. 4. Aklil Hailu: Data curation, Formal Analysis, Investigation, Methodology, Supervision, Writing review and editing References World Health Organization, Blindness and vision impairment & WHO. ; Aug 10 [cited 2025 Nov 14]. (2023). Available from: https://www.who.int/news-room/fact-sheets/detail/blindness-and-visual-impairment Zou, M. et al. Prevalence of visual impairment among older Chinese population: A systematic review and meta-analysis. J. global health . 11 , 08004 (2021). PMID: 33981412; PMCID: PMC8088771. Karovski, M. & Gazepov, S. PSYCHOLOGY OF LOW VISION. KNOWLEDGE-International J. 63 (4), 473–477 (2024). Moyegbone, J. et al. Visual Impairment Management and Associated Socio-demographic Factors among School Children in Delta State, Nigeria published 25 August 2024. available at:: https://researchpubjournals.org/ Ye, H. et al. Prevalence and factors associated with visual impairment in middle-aged and older Chinese population. Front. Med. 9 , 962729 (2022). Ogedengbe, T. O. Content development for a tool to assess the preparedness of employment environment to welcome people with visual impairment. (2023). Steinmetz, J. D. et al. Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study. Lancet Global Health . 9 (2), e144–e60 (2021). Flaxman, S. R. et al. Global causes of blindness and distance vision impairment 1990–2020: a systematic review and meta-analysis. Lancet Global Health . 5 (12), e1221–e34 (2017). Dalton, M. K. et al. Analysis of surgical volume in military medical treatment facilities and clinical combat readiness of US military surgeons. JAMA Surg. 157 (1), 43–50 (2022). Evans, D. D. & Hoyt, K. S. Ophthalmologic emergencies: Assessment and management. Adv. Emerg. Nurs. J. 45 (4), E9–E38 (2023). Assefa, N. L., Admas, A. W. & Adimasu, N. F. Prevalence and associated factors of visual impairment among adults at Debre Berhan town, North Shewa, Ethiopia. BMC Ophthalmol. 20 , 1–8 (2020). Killeen, O. J. et al. Population prevalence of vision impairment in US adults 71 years and older: the National Health and Aging Trends Study. JAMA Ophthalmol. 141 (2), 197–204 (2023). Tagoh, S., Kyei, S., Kwarteng, M. A. & Aboagye, E. Prevalence of refractive error and visual impairment among rural dwellers in Mashonaland Central Province, Zimbabwe. J. Curr. Ophthalmol. 32 (4), 402–407 (2020). Abeysena, C. & Bandara, H. Prevalence of visual impairment among adults aged forty years and above in a medical officer of health area in Sri Lanka: cross-sectional study. (2018). Cherinet, F. M., Tekalign, S. Y., Anbesse, D. H. & Bizuneh, Z. Y. Prevalence and associated factors of low vision and blindness among patients attending St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia. BMC Ophthalmol. 18 , 1–6 (2018). Wiafe, B. & Universal, O. E. Ghana blindness and visual impairment study (International Agency for the Prevention of Blindness, 2015). Deme, T. G., Mengistu, M. & Getahun, F. Prevalence and associated factors of visual impairment among adults aged 40 and above in Southern Ethiopia, 2022. Sci. Rep. 14 (1), 2542 (2024). Leshabane, M. M., Rampersad, N. & Mashige, K. P. Prevalence, causes and factors associated with vision impairment in Limpopo province. Afr. Vis. Eye Health . 83 (1), 1–9 (2024). World Health Organization. World Report on Vision. Geneva: WHO. (2019). available at: https://www.who.int/publications-detail-redirect/world-report-on-vision Nuertey, B. D. et al. Prevalence Causes, and Factors Associated with Visual Impairment and Blindness among Registered Pensioners in Ghana.J Ophthalmology. ; 2019 :1717464. 10.1155/2019/1717464 . (2019). PMID: 31687194; PMCID: PMC6800954. Onakoya, A. O., Mbadugha, C. A. & Aribaba, O. T. Pattern of glaucoma presentation in Lagos, Nigeria: Implications for blindness prevention. Niger J. Ophthalmol. 28 (1), 21–27 (2023). Tegegn, M. T., Assaye, A. K. & Belete, G. T. Prevalence, causes and associated factors of visual impairment and blindness among older population in outreach site, Northwest Ethiopia. A dual center cross-sectional study. Afr. Health Sci. 23 (3), 683–695 (2023). Yau, J. W. Y. et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care . 35 (3), 556–564. 10.2337/dc11-1909 (2012). Epub 2012 Feb 1. PMID: 22301125; PMCID: PMC3322721. Cherinet, F. M., Tekalign, S. Y., Anbesse, D. H. & Bizuneh, Z. Y. Prevalence and associated factors of low vision and blindness among patients attending St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia. BMC Ophthalmol. 18 , 1–6 (2018). Kee, Q. T., Abd Rahman, M. H., Mohamad Fadzil, N., Mohammed, Z. & Shahar, S. The impact of near visual impairment on instrumental activities of daily living among community-dwelling older adults in Selangor. BMC Res. Notes . 14 (1), 395. 10.1186/s13104-021-05813-3 (2021). PMID: 34689826; PMCID: PMC8543948. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8243267","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":559537829,"identity":"90ceeb9e-6c21-4194-9de4-6e9ca370e8b8","order_by":0,"name":"Mr. Meles Gizachew","email":"","orcid":"","institution":"Addis Ababa University","correspondingAuthor":false,"prefix":"Mr.","firstName":"Meles","middleName":"","lastName":"Gizachew","suffix":""},{"id":559537831,"identity":"e3f6a356-5d1d-468f-99f2-c80ba0477a12","order_by":1,"name":"Teshome Habte","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYHACNjBpwMADJCsgQhL41PMgaWFsYDiD0IJTG6oWxjYitNiztz978DHHhsGc/ezxBx/n2ckbHGA+eJuHwaYOpy08Z8wNZ25LY7DsyUtsnLkt2XDDAbZkax6GNNwOk8hhk+bddpjB4ECOYTPvNmbGDQd4zKR5GA7j1iL//BlQy38Gg/NvDJv/zqm333CA/xtQy388tjCYAbUcYDC4AbSFseFwItAWNqCWA7i1nMkxkwR6gcfgxrvEmT3HjifPPMxmbDnHIFmyAYcW9vbjzyQ+brOTMzife+DDj5pq277jzQ9vvKmw48dlC9w2BJMZRBgQ0jAKRsEoGAWjAB8AAJRqUdLeTjkLAAAAAElFTkSuQmCC","orcid":"","institution":"Addis Ababa University","correspondingAuthor":true,"prefix":"","firstName":"Teshome","middleName":"","lastName":"Habte","suffix":""},{"id":559537839,"identity":"9c2e841d-a60c-454b-b119-de6e44ea1c29","order_by":2,"name":"Zeleke Argaw","email":"","orcid":"","institution":"Addis Ababa University","correspondingAuthor":false,"prefix":"","firstName":"Zeleke","middleName":"","lastName":"Argaw","suffix":""},{"id":559537840,"identity":"65a54efb-b85d-4a8f-8915-3748d03651e9","order_by":3,"name":"Aklil Hailu","email":"","orcid":"","institution":"Addis Ababa University","correspondingAuthor":false,"prefix":"","firstName":"Aklil","middleName":"","lastName":"Hailu","suffix":""}],"badges":[],"createdAt":"2025-11-30 16:08:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8243267/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8243267/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98293942,"identity":"3c933ae1-52df-4e2f-9293-992073480315","added_by":"auto","created_at":"2025-12-16 09:04:12","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":81043,"visible":true,"origin":"","legend":"","description":"","filename":"2.Manuscriptonprevalenceofvisualimpairment1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8243267/v1/c31238d5c5b1d5713c5338ff.docx"},{"id":98293945,"identity":"b8a80ef2-1f5c-430e-8484-32061e42bf43","added_by":"auto","created_at":"2025-12-16 09:04:12","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6938,"visible":true,"origin":"","legend":"","description":"","filename":"22bdfd0b2a094b03867db2b326883f8a.json","url":"https://assets-eu.researchsquare.com/files/rs-8243267/v1/63b88a445cfcbb1553d874cf.json"},{"id":98435783,"identity":"66a20352-e46e-4950-8a6c-af7602aaf9ad","added_by":"auto","created_at":"2025-12-17 16:54:25","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":152829,"visible":true,"origin":"","legend":"","description":"","filename":"Ethicalreviewboardletter.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8243267/v1/23bf98afc92f524dd949e36f.jpg"},{"id":98435788,"identity":"989b9d9d-43d6-4893-8f53-dd161fc81d25","added_by":"auto","created_at":"2025-12-17 16:54:25","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":113240,"visible":true,"origin":"","legend":"","description":"","filename":"22bdfd0b2a094b03867db2b326883f8a1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8243267/v1/bbcf229e42ce0aa2fe3ccca1.xml"},{"id":98293948,"identity":"add8b0c8-1491-47cf-8a2c-719eab726c12","added_by":"auto","created_at":"2025-12-16 09:04:12","extension":"jpeg","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":755074,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8243267/v1/a8d6af9bdb035225aaa0a91b.jpeg"},{"id":98293944,"identity":"6d09f76a-3b21-41bc-9aae-68256972fcf2","added_by":"auto","created_at":"2025-12-16 09:04:12","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":100748,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8243267/v1/701edf5b1a3fa6376ec3b7b8.png"},{"id":98293947,"identity":"095433d8-6ab2-48e2-b026-f53cd25ea14b","added_by":"auto","created_at":"2025-12-16 09:04:12","extension":"xml","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":109841,"visible":true,"origin":"","legend":"","description":"","filename":"22bdfd0b2a094b03867db2b326883f8a1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8243267/v1/9619809ddfafa76625f0978e.xml"},{"id":98293949,"identity":"625d0ae6-b894-46c1-a96d-dcb2c6194055","added_by":"auto","created_at":"2025-12-16 09:04:12","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":127253,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8243267/v1/088e99aa3a3c6c22197b6040.html"},{"id":98293941,"identity":"f17a9d68-35af-473a-b4f0-794b69ae5865","added_by":"auto","created_at":"2025-12-16 09:04:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":171062,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual Framework for the Study on the Prevalence and Determinants of Visual Impairment among Individuals Aged 40 Years and Above Attending Military Hospitals in Addis Ababa, Ethiopia.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8243267/v1/2d9e488118f9998fd269ea94.png"},{"id":99698933,"identity":"a142faab-4f6a-4805-b2b7-5f4db64345e3","added_by":"auto","created_at":"2026-01-07 11:25:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1916159,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8243267/v1/f0f7f9e0-77b4-4096-9bee-809fbf25677e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence and Determinants of Visual Impairment among Individuals Aged 40 Years and Above Attending Military Hospitals in Addis Ababa, 2025: A Cross-Sectional Study","fulltext":[{"header":"Brief information on the study","content":"\u003cp\u003e\u003cstrong\u003eWhat is already known in this topic?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVisual impairment is a growing concern among adults aged 40 and above, with age-related eye conditions such as cataracts, glaucoma, and diabetic retinopathy being common causes. However, limited data exist on its prevalence and determinants among military hospital attendees in Ethiopia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat this study adds?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study provides current evidence on the high prevalence of visual impairment among adults aged 40 and above in military hospitals in Addis Ababa and identifies key associated factors, supporting the need for targeted screening, early intervention, and improved eye care services within this population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHow this study might affect research practice, or policy?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study may influence research and policy by highlighting the need for routine vision screening and integrated eye care in military health services, guiding resource allocation, and informing national strategies aimed at reducing preventable visual impairment among older adults in Ethiopia.\u003c/p\u003e\n"},{"header":"1. Introduction","content":"\u003ch3\u003e1.1.\u0026nbsp;Background Information\u003c/h3\u003e\n\u003cp\u003eAccording to the World Health Organization (WHO), visual impairment is defined as a decrease in vision that cannot be fully corrected with glasses, contact lenses, medication, or surgery. WHO classifies visual impairment based on visual acuity in the better eye: \u003cstrong\u003emild visual impairment\u003c/strong\u003e is worse than 6/12 but equal to or better than 6/18; \u003cstrong\u003emoderate visual impairment\u003c/strong\u003e is worse than 6/18 but equal to or better than 6/60; \u003cstrong\u003esevere visual impairment\u003c/strong\u003e is worse than 6/60 but equal to or better than 3/60; and \u003cstrong\u003eblindness\u003c/strong\u003e is defined as worse than 3/60. Visual impairment may manifest as difficulty seeing clearly even with corrective lenses, trouble reading or recognizing faces, issues with navigation, or partial to total loss of vision \u003cstrong\u003e[1-3].\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGlobally, the prevalence of visual impairment increases significantly with age. Estimates suggest that 10\u0026ndash;20% of individuals aged 40 years and above are affected by some degree of VI, and this figure is expected to rise due to increasing life expectancy and the growing aging population. In Ethiopia, like many low- and middle-income countries, limited access to preventive eye care services exacerbates the burden, particularly among older adults \u003cstrong\u003e[1, 2].\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultiple factors are associated with the risk of visual impairment in this demographic group. These include socio-demographic variables (age, sex, education, occupation, and residence), medical conditions such as cataracts, glaucoma, diabetic retinopathy, hypertension, and uncorrected refractive errors, as well as behavioral and lifestyle factors like smoking and alcohol use. Low awareness and poor health-seeking behavior further hinder timely diagnosis and treatment \u003cstrong\u003e[3, 4].\u0026nbsp;\u003c/strong\u003eVisual impairment severely compromises quality of life, restricting daily activities, reducing independence, and increasing the risks of falls, social isolation, and mental health conditions such as depression. Its impact is not only personal but also economic, as it limits productivity and increases healthcare costs \u003cstrong\u003e[5, 6].\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this context, understanding the prevalence and determinants of visual impairment among individuals aged 40 years and above, particularly in unique populations such as military hospital attendees in Addis Ababa, is vital. The findings can inform targeted screening initiatives, policy interventions, and the development of comprehensive, accessible, and age-appropriate eye care services.\u003c/p\u003e\n\u003ch3\u003e1.2. Statement of the Problem\u003c/h3\u003e\n\u003cp\u003eVisual impairment (VI) refers to a significant reduction in visual function that cannot be fully corrected with conventional means such as glasses, contact lenses, medication, or surgery. It presents a major global and national health challenge, particularly among older adults, where preventable and treatable causes remain widespread and under-addressed. VI often manifests as blurred vision, night blindness, reduced peripheral vision, difficulty recognizing faces, light sensitivity, and challenges in depth or color perception symptoms that significantly impair daily functioning and quality of life \u003cstrong\u003e[2, 4]. \u0026nbsp;\u0026nbsp;\u003c/strong\u003eGlobally, over 2.2 billion people are affected by some form of visual impairment, with at least 1 billion cases potentially preventable or untreated. An estimated 237 million individuals suffer from moderate to severe distance VI, and nearly 39 million are blind a figure expected to rise to 115 million by 2050. In the African region alone, approximately 26.3 million people live with VI, including 5.9 million who are blind. Ethiopia faces one of the highest burdens, with an estimated 1.18% blindness prevalence, largely attributable to cataracts, uncorrected refractive errors, diabetic retinopathy, and glaucoma. Notably, over 80% of these cases are preventable \u003cstrong\u003e[7, 8].\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite the growing burden, there is a paucity of data specifically addressing visual impairment among individuals aged 40 and above within military hospital settings in Ethiopia. This demographic may face unique exposures and risk factors. Therefore, this study aims to assess the prevalence and determinants of VI in military hospitals in Addis Ababa, providing critical insights to guide targeted eye care interventions, strengthen service delivery, and inform national efforts to combat avoidable blindness within this population.\u003c/p\u003e\n\u003ch3\u003e1.3. Significance of the Study\u003c/h3\u003e\n\u003cp\u003eThis study holds substantial value for multiple stakeholders. For the general public, particularly individuals aged 40 and above, the findings will support early detection and management of visual impairment, ultimately improving quality of life and reducing disability. Within military hospital settings, the results can enhance vision screening protocols, guide targeted interventions, and inform strategic allocation of resources to address preventable causes of vision loss. For healthcare professionals, the study offers evidence to support improved clinical decision-making and the development of tailored patient education and outreach programs.\u003c/p\u003e\n\u003cp\u003ePolicymakers will benefit from data-driven insights to design and implement age-sensitive, community-based eye care strategies. Additionally, the study serves as a foundational reference for future researchers exploring visual health among aging populations, fostering further investigation and interdisciplinary collaboration. Overall, the research aims to contribute to improved eye care services and public health planning for both military personnel and the broader civilian population in Ethiopia.\u003c/p\u003e\n\u003ch3\u003eResearch Questions\u003c/h3\u003e\n\u003cp\u003e1.\u0026nbsp; \u0026nbsp;What is the prevalence of visual impairment among individuals aged 40 years and above attending selected military hospitals in Addis Ababa, Ethiopia?\u003c/p\u003e\n\u003cp\u003e2. \u0026nbsp; What socio-demographic, health-related, and lifestyle factors are associated with visual impairment among individuals aged 40 years and above in the study setting?\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.3. Conceptual Framework\u003cbr\u003e\u003c/strong\u003eThe conceptual framework of this study is informed by existing literature that identifies multiple factors influencing visual impairment among adults aged 40 years and above. Key determinants include demographic factors (such as age, sex, and education), health-related conditions (like diabetes and hypertension), lifestyle behaviors (smoking, alcohol use), and individual attitudes toward eye health and care-seeking. These independent variables are hypothesized to directly or indirectly affect the occurrence of visual impairment, the dependent variable. Understanding these interrelationships provides a foundation for identifying at-risk populations and guiding targeted interventions in military hospital settings \u003cstrong\u003e[2, 3, 5, 7].\u003c/strong\u003e\u003c/p\u003e"},{"header":"2. Objectives of the study","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.1. General Objective\u003c/h2\u003e \u003cp\u003eTo assess the prevalence and determinants of visual impairment among individuals aged 40 years and above attending selected military hospitals in Addis Ababa, Ethiopia, in 2025.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.2. Specific Objectives\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eTo determine the prevalence of visual impairment among individuals aged 40 years and above in selected military hospitals in Addis Ababa, Ethiopia.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo identify socio-demographic, health-related, and lifestyle factors associated with visual impairment among individuals aged 40 years and above in the study setting.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Methods and Materials","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Study Area\u003c/h2\u003e \u003cp\u003eThis study was conducted in two major military healthcare institutions (Hospital) in Addis Ababa, Ethiopia: the Armed Forces Comprehensive Specialized Hospital (AFCSH) and the Federal Police Hospital. Addis Ababa, the capital and largest urban center of Ethiopia, is a political, economic, and healthcare hub with an estimated population of 5.7\u0026nbsp;million in 2024, according to the Central Statistical Agency. AFCSH is a tertiary-level referral facility providing specialized services in ophthalmology, cardiology, oncology, and neurology, among others. It serves both military personnel and civilians, equipped with advanced diagnostic tools such as MRI, CT scan, and comprehensive laboratory services [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Federal Police Hospital, located in Lideta Sub-City, primarily serves members of the federal police force and their families. It functions as a referral center, offering both emergency and routine medical services in internal medicine, surgery, orthopedics, and ophthalmology, supported by modern infrastructure and medical insurance coverage. Both hospitals were selected due to their diverse patient population aged 40 and above, access to ophthalmologic services and their strategic roles in the military health system, making them suitable for assessing the prevalence and determinants of visual impairment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Study Design and Period\u003c/h2\u003e \u003cp\u003eAn institution-based cross-sectional study design was employed to assess the prevalence and determinants of visual impairment among individuals aged 40 years and above attending military hospitals in Addis Ababa. This design was selected to capture a snapshot of the population's visual health status and associated risk factors within a defined time frame. The study was conducted over a one-month period, from January 20 to February 20, 2025.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Study Population\u003c/h2\u003e \u003cp\u003eThe study population consisted of individuals aged 40 years and above attending the ophthalmology units of Armed Forces Comprehensive Specialized Hospital and Federal Police Hospital in Addis Ababa during the study period. This included active-duty members of the Ethiopian Defense Forces, military veterans residing in or around Addis Ababa, and eligible family members of military personnel. Participants were selected using a systematic random sampling method from among those seeking eye care services during the data collection period. Individuals who met the inclusion criteria and provided informed consent were considered for participation in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Eligibility Criteria\u003c/h2\u003e \u003cp\u003eTo ensure the appropriateness and reliability of the data, specific inclusion and exclusion criteria were applied:\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1. Inclusion Criteria:\u003c/h2\u003e \u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eIndividuals aged 40 years and above who attended the ophthalmology departments of the selected military hospitals during the data collection period.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e Participants who were able and willing to provide informed written consent to participate in the study.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2. Exclusion Criteria:\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eIndividuals who declined to participate or withdrew consent at any stage of the study.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePatients who had already participated in the study during an earlier visit and returned for follow-up care during the same data collection period, to avoid duplication of data.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIndividuals with severe cognitive or communication impairments that hindered effective interview or examination, as judged by the attending clinician.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Sample Size Determination, Sampling Technique, and Procedure\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.5.1. Sample Size Determination\u003c/h2\u003e \u003cp\u003eThe required sample size for this study was calculated using a single population proportion formula, based on an estimated prevalence of visual impairment among adults aged 40 years and above in Ethiopia. n\u0026thinsp;=\u0026thinsp;240. Since the total target population (N\u0026thinsp;=\u0026thinsp;1,860) is less than 10,000, the finite population correction formula was applied: Thus, the final sample size was rounded to 213 participants (n\u0026thinsp;=\u0026thinsp;213).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.5.2. Sampling Technique and Procedure\u003c/h2\u003e \u003cp\u003eThis study was conducted in two military hospitals located in Addis Ababa: the Army Forces Comprehensive Specialized Hospital (AFCSH) and the Federal Police Referral Hospital (FPRH). Both institutions were purposively selected due to their high patient volume and relevance to the military health system. To ensure equitable representation, the total sample size was proportionally allocated to each hospital based on patient flow data for individuals aged 40 years and above from outpatient departments (OPD) during October 2024 as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below. According to hospital records, AFCSH reported 1,048 adult patients aged\u0026thinsp;\u0026ge;\u0026thinsp;40 years, while FPRH reported 812 patients in the same age group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProportional Sample Size Allocation at AFCSH and Federal Police Referral Hospitals\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients (\u0026ge;\u0026thinsp;40 yrs.)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProportion (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAFCSH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFederal Police Referral Hospital.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1,860\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e213\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA systematic random sampling technique was employed to select participants from the OPD register of each hospital.\u003c/p\u003e \u003cp\u003eAccordingly, every 8th adult patient aged 40 years and above presenting at the OPD during the study period was selected for participation. The first participant was chosen randomly from the first 1 to 8 attendees using a lottery method. A list of eligible patients was generated using medical record numbers to ensure systematic inclusion and avoid duplication.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6. The study Variables\u003c/h2\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e\u003cb\u003e3.6.1. Dependent Variable\u003c/b\u003e: Visual Impairment (VI):\u003c/h2\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.6.2. Independent Variables:\u003c/h2\u003e \u003cp\u003eThe independent variables include a range of socio-demographic, clinical, behavioral, environmental, and psychosocial factors that may influence visual impairment. These are categorized as follows:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eA. Demographic Factors\u003c/strong\u003e: age, Sex, occupation, educational level, marital status, and monthly income.\u003cbr\u003e\u003cstrong\u003eB. Health-Related Factors\u003c/strong\u003e:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eSelf-reported history or clinical diagnosis of: Cataract, Glaucoma, Refractive error. (e.g., myopia, hyperopia, astigmatism)\u003c/li\u003e\n \u003cli\u003eOcular trauma\u003c/li\u003e\n \u003cli\u003eDiabetic retinopathy\u003c/li\u003e\n \u003cli\u003eSystemic hypertension\u003c/li\u003e\n \u003cli\u003eDiabetes mellitus\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eC. Lifestyle and Awareness-Related Factors\u003c/strong\u003e: cigarette smoking, excessive use of alcohol, regular eye check-ups.\u003cbr\u003e\u003cstrong\u003eD. Environmental and Occupational Factors\u003c/strong\u003e: primary work environment, time spent on screen per day, access to regular eye care, and using protective eyewear.\u003cbr\u003e\u003cstrong\u003eE. Social and Psychosocial Factors\u003c/strong\u003e: living arrangement, feeling of social network, and social participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.7. Operational Definitions of Key Terms\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eNormal Vision\u003c/strong\u003e: Best-corrected visual acuity (BCVA) of 20/20 on the Snellen chart.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eVisual Impairment (VI)\u003c/strong\u003e: Defined based on standardized classifications of visual acuity as measured using a Snellen chart or equivalent method.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMild Visual Impairment (Low Vision)\u003c/strong\u003e: BCVA between 20/30 and 20/60 in the better eye.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eModerate Visual Impairment\u003c/strong\u003e: BCVA between 20/70 and 20/150 in the better eye.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eSevere Visual Impairment\u003c/strong\u003e: BCVA between 20/200 and 20/400 in the better eye; often referred to as \u0026quot;legal blindness.\u0026quot;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eProfound Visual Impairment\u003c/strong\u003e: BCVA worse than 20/500 in the better eye.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eIntraocular Pressure (IOP)\u003c/strong\u003e: The fluid pressure inside the eye. Normal IOP ranges from 10 to 21 mmHg.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eOcular Hypertension\u003c/strong\u003e: Elevated IOP greater than 21 mmHg without detectable damage to the optic nerve or visual field defects.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eGlaucoma\u003c/strong\u003e: A group of eye conditions characterized by IOP greater than 21 mmHg with progressive optic nerve damage and visual field loss [1, 2, 3, 9, 10].\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv id=\"Sec20\"\u003e\n \u003ch2\u003e3.8. Data Collection Tools and Procedures\u003c/h2\u003e\n \u003ch2\u003e3.8.1. Data Collection Tools\u003c/h2\u003e\n \u003cp\u003eThe primary data collection instrument was a structured, interviewer-administered questionnaire developed based on a synthesis of insights from four prior studies conducted in Ethiopia [11, 12]. These foundational studies provided a culturally and contextually relevant framework by incorporating locally significant socio-demographic, health, lifestyle, and environmental variables. The tool was designed to reflect the social realities, health care utilization patterns, and awareness levels of the Ethiopian adult population, particularly those attending military health facilities.\u003c/p\u003e\n \u003cp\u003eThe questionnaire was initially developed in English and subsequently translated into Amharic to ensure linguistic and cultural appropriateness. A back-translation into English was performed by an independent bilingual expert to verify consistency and semantic equivalence. Revisions were made to resolve any discrepancies noted during the back-translation process.\u003c/p\u003e\n \u003cp\u003eThe final version of the questionnaire was organized into six thematic sections:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cstrong\u003eDemographic Characteristics\u003c/strong\u003e:\u0026nbsp;\u003c/strong\u003eSeven items capturing age, sex, marital status, education level, occupation, income, and residence.\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eHealth-Related Factors\u003c/strong\u003e: Eight items assessing self-reported and clinically confirmed conditions such as glaucoma, cataract, refractive errors, ocular trauma, diabetic retinopathy, and systemic diseases (e.g., hypertension).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eLifestyle, Attitude, and Awareness\u003c/strong\u003e: Seven items exploring behaviors like smoking, alcohol use, frequency of eye check-ups, and general awareness of eye health.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eEnvironmental Factors\u003c/strong\u003e: Five items assessing exposure to occupational or environmental risks (e.g., screen time, use of protective eyewear, work environment).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eSocial Factors\u003c/strong\u003e: Six items evaluating living arrangements, social support, and community participation.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eVisual Impairment Symptoms and Impact\u003c/strong\u003e: Seven items documenting participants\u0026rsquo; subjective visual symptoms and the functional impact on daily activities.\u003c/li\u003e\n \u003c/ul\u003eResponses were recorded on pre-coded, closed-ended formats to standardize data collection and facilitate analysis. In addition, clinical parameters\u0026mdash;such as intraocular pressure, best-corrected visual acuity (via Snellen chart), and diagnoses from ophthalmologic examinations were extracted from medical records and entered into the questionnaire by trained data collectors.\u003cdiv id=\"Sec22\"\u003e\n \u003ch2\u003e3.8.2. Data Collection Procedures\u003c/h2\u003e\n \u003cp\u003eData collection was conducted by a team of four trained ophthalmic professionals two from the Army Forces Comprehensive Specialized Hospital (AFCSH) and two from the Federal Police Referral Hospital\u0026mdash;supported by two supervisors from each facility\u0026rsquo;s outpatient department. A one-day training session was provided to all data collectors and supervisors by the principal investigator. The training covered: Study objectives and research questions, detailed review of each item in the questionnaire, informed consent procedures, confidentiality and ethical considerations and proper interview techniques and data recording methods. Eligible participants were identified at the outpatient departments using a systematic random sampling method. Upon obtaining informed consent, participants were interviewed in a private setting before their clinical consultation. Data collectors administered the questionnaire and recorded responses directly. Following the initial interview, medical charts were reviewed to extract relevant clinical information, including documented diagnoses (e.g., glaucoma, cataract, diabetic retinopathy) and systemic conditions (e.g., hypertension and diabetes). Visual acuity testing was performed by ophthalmologists using a Snellen chart under standardized lighting conditions. Participants identified as visually impaired based on acuity criteria were invited to complete the remaining interview sections focusing on the impacts of vision loss.\u003c/p\u003e\n \u003cp\u003eTo ensure data accuracy and consistency: blood pressure was measured using a calibrated digital sphygmomanometer to verify hypertensive status; diagnosis of glaucoma was confirmed through chart review, incorporating IOP measurement and optic nerve assessment; ophthalmic examination findings were verified jointly by the attending ophthalmologist and the data collector. Supervisors performed routine checks and verified completeness and quality of data collected at the end of each day.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec23\"\u003e\n \u003ch2\u003e3.9. Data Quality Assurance\u003c/h2\u003e\n \u003cp\u003eTo ensure the validity, reliability, and consistency of the data collected, multiple quality assurance strategies were employed throughout the research process: A standardized and pre-tested structured questionnaire was developed using comprehensive, relevant literature and contextualized for the Ethiopian setting and a pilot study was conducted involving 5% of the target sample size (n\u0026thinsp;=\u0026thinsp;21 participants) at the Ground Army Level II health facility in Addis Ababa. The purpose of this pre-test was to assess the clarity, consistency, and cultural appropriateness of the tool, as well as to identify any logistical challenges in data collection. Feedback obtained from the pre-test was used to revise ambiguous items, rephrase unclear wording, and restructure question flow to enhance comprehensibility. Training for data collectors and supervisors were conducted. The training focused on research objectives, ethical considerations, informed consent procedures, interviewing techniques, accurate data recording, and proper handling of sensitive medical information. Furthermore, visual acuity assessments and clinical diagnoses were validated by ophthalmologists to minimize diagnostic misclassification.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec24\"\u003e\n \u003ch2\u003e3.10. Data Processing and Analysis\u003c/h2\u003e\n \u003cp\u003eFollowing data collection, all completed questionnaires were reviewed for completeness and consistency. Data were then coded, with categorical responses assigned numeric values to facilitate statistical analysis. The data coding process also involved identifying any missing values, inconsistencies, or outliers. Cleaned data were entered into EpiData version 4.6 using a double-entry system to minimize entry errors. Discrepancies between entries were cross-checked and resolved using source documents and verified dataset was exported to Statistical Package for Social Sciences (SPSS) version 28 for further analysis.\u003c/p\u003e\n \u003cp\u003eThe data analysis proceeded with descriptive Statistics and Multivariate Logistic Regression Analysis applied. A p-value of less than 0.05 was considered statistically significant. Results were interpreted in light of existing evidence and contextual factors.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Result","content":"\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Demographic Characteristics of the Participants\u003c/h2\u003e \u003cp\u003eA total of 213 individuals participated in this study, yielding a 100% response rate. Participants were stratified into seven age categories, with the largest proportion, 45 participants (21.2%), falling within the 40\u0026ndash;44 year age group. The participants\u0026rsquo; ages ranged from 40 to 92 years, with a mean age of 56 years (\u0026plusmn;\u0026thinsp;SD) and a median age of 53 years.\u003c/p\u003e \u003cp\u003eThe sample was predominantly male, comprising 136 participants (63.8%), while female participants accounted for 77 (36.2%). Regarding marital status, the majority 166 participants (77.9%) were married. In terms of military service, 61 respondents (28.6%) had served or were actively serving in the military for duration of 10 to 20 years. Educational attainment varied, with 72 participants (33.8%) having completed higher education. With respect to occupational status, 99 participants (46.5%) were retired at the time of the study as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003eLastly, the majority of the participants 193 individuals (90.6%) resided in urban areas, indicating a primarily urban-based study population.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic Characteristics of Participants Aged 40 Years and Above Attending Selected Military Hospitals in Addis Ababa, Ethiopia, 2025 (n\u0026thinsp;=\u0026thinsp;213)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003cp\u003e50\u0026ndash;54\u003c/p\u003e \u003cp\u003e55\u0026ndash;59\u003c/p\u003e \u003cp\u003e60\u0026ndash;64\u003c/p\u003e \u003cp\u003e65\u0026ndash;69\u003c/p\u003e \u003cp\u003e70 and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003cp\u003e32\u003c/p\u003e \u003cp\u003e31\u003c/p\u003e \u003cp\u003e23\u003c/p\u003e \u003cp\u003e23\u003c/p\u003e \u003cp\u003e22\u003c/p\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003cp\u003e15.0\u003c/p\u003e \u003cp\u003e14.6\u003c/p\u003e \u003cp\u003e10.8\u003c/p\u003e \u003cp\u003e10.8\u003c/p\u003e \u003cp\u003e10.3\u003c/p\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e136\u003c/p\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.8\u003c/p\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003eMarried\u003c/p\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003cp\u003e166\u003c/p\u003e \u003cp\u003e13\u003c/p\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003cp\u003e77.9\u003c/p\u003e \u003cp\u003e6.1\u003c/p\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eService in years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;10 years\u003c/p\u003e \u003cp\u003e11\u0026ndash;20\u003c/p\u003e \u003cp\u003e21\u0026ndash;30\u003c/p\u003e \u003cp\u003eAbove 30\u003c/p\u003e \u003cp\u003eCivil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003cp\u003e61\u003c/p\u003e \u003cp\u003e57\u003c/p\u003e \u003cp\u003e41\u003c/p\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003cp\u003e28.6\u003c/p\u003e \u003cp\u003e26.8\u003c/p\u003e \u003cp\u003e19.2\u003c/p\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003cp\u003ewrite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnable to read and\u003c/p\u003e \u003cp\u003eAble to read and write\u003c/p\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003cp\u003eSecondary school\u003c/p\u003e \u003cp\u003eHigher education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003cp\u003e19\u003c/p\u003e \u003cp\u003e55\u003c/p\u003e \u003cp\u003e53\u003c/p\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003cp\u003e8.9\u003c/p\u003e \u003cp\u003e25.8\u003c/p\u003e \u003cp\u003e24.9\u003c/p\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActive military\u003c/p\u003e \u003cp\u003eRetired\u003c/p\u003e \u003cp\u003eCivil worker\u003c/p\u003e \u003cp\u003eFamily of active military\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003cp\u003e99\u003c/p\u003e \u003cp\u003e20\u003c/p\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.1\u003c/p\u003e \u003cp\u003e46.5\u003c/p\u003e \u003cp\u003e9.4\u003c/p\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e193\u003c/p\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.6\u003c/p\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Health History Characteristics of the Participants\u003c/h2\u003e \u003cp\u003eThe health history of the study participants, with a focus on ocular and related systemic conditions, revealed several noteworthy findings. Among the 213 individuals assessed, 72 (33.8%) were diagnosed with cataracts, indicating a significant burden of age-related eye disease within the study population. In terms of comorbid chronic conditions, 62 participants (29.1%) reported a history of hypertension, while 55 (25.8%) were living with diabetes mellitus. These conditions are known to have potential ocular complications, including hypertensive and diabetic retinopathies. Visual acuity assessment using the Snellen chart showed that 103 participants (48.4%) had normal visual acuity (6/6) at the time of examination. Moreover, 100 participants (46.9%) reported having undergone an eye examination within the current calendar year, reflecting moderate engagement with routine eye health services.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Attitude and Lifestyle Characteristics of the Participants\u003c/h2\u003e \u003cp\u003eThe lifestyle and attitudinal profiles of the study participants revealed several behaviors relevant to eye health and overall well-being. Of the 213 participants, 65 (30.5%) reported being current cigarette smokers. Among these, 23 individuals (35.4%) had a smoking history exceeding 20 years, which may pose increased risk for various ocular and systemic health issues.\u003c/p\u003e \u003cp\u003eExcessive alcohol consumption was reported by 93 participants (43.7%), while 68 of these individuals (73.1%) indicated they consumed alcohol occasionally, suggesting varying patterns of intake within the group.\u003c/p\u003e \u003cp\u003eRegular engagement in physical activity was limited, with only 59 participants (27.7%) reporting daily physical exercise. This may have implications for the management of chronic conditions associated with visual impairment, such as diabetes and hypertension.\u003c/p\u003e \u003cp\u003eRegarding attitudes toward eye health, 95 participants (44.6%) expressed concern about the condition of their eyes. Notably, a substantial majority 188 participants (88.3%) acknowledged the importance of undergoing regular eye examinations, indicating a relatively high level of awareness regarding preventive eye care.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Socio-Environmental Characteristics of the Participants\u003c/h2\u003e \u003cp\u003eThe socio-environmental profile of the participants revealed several contextual factors that may influence visual health and access to care. Among the 213 respondents, 83 individuals (39.0%) reported that their primary work environment was home-based. Additionally, 60 participants (28.2%) stated they spent between one to three hours daily in front of digital screens, which may have implications for visual strain and ocular health.\u003c/p\u003e \u003cp\u003eRegarding occupational safety, 104 participants (48.8%) reported using protective eyewear while on duty, reflecting moderate adherence to eye safety practices. Access to eye care services was reported by 122 participants (57.3%), and 144 individuals (67.6%) indicated that transportation did not pose a barrier to receiving such services. In terms of living arrangements, 167 participants (78.4%) lived with their families, and 171 (80.3%) reported interacting with family members on a daily basis. When assessing perceived social support, 167 participants (78.4%) expressed feeling that they had a strong support network. Additionally, 122 participants (57.3%) reported participation in social or community-related activities during the past year. A total of 173 participants (81.2%) stated that they had someone available to assist them with daily activities when needed.\u003c/p\u003e \u003cp\u003eFinally, 136 participants (63.8%) reported no difficulty participating in social situations due to vision-related problems, indicating that visual impairment did not significantly affect their social engagement in most cases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Prevalence and Factors Associated with Visual Impairment\u003c/h2\u003e \u003cp\u003eThe overall prevalence of visual impairment among participants aged 40 years and above was 51.6%. The condition was more common among individuals aged 70 and above (14.6%) and retired participants (31.5%). Married individuals accounted for 42.7% of cases. Cataracts were the leading ocular condition, affecting 24.9% of visually impaired participants, followed by diabetes mellitus (20.2%). Moderate visual impairment was the most prevalent severity level (25.8%). Notably, only 27.0% had undergone an eye examination in the past year. Lifestyle factors included cigarette smoking (46.3%), with 31% having smoked for over 20 years, and alcohol consumption (45.5%), with 41% drinking occasionally. One-third (33%) did not engage in physical exercise. Despite this, 46.2% expressed concern about their eye health, and 89.1% acknowledged the importance of regular eye check-ups. About 67% rated their eyesight as poor.\u003c/p\u003e \u003cp\u003eSocio-environmentally, 29.1% worked primarily from home, and 20.2% used screens for less than one hour daily. Protective eyewear use was reported by 27.7%, and 28.2% had regular access to eye care services. Additionally, 41.8% lived with their families, 40.8% reported strong social support, and 24.9% experienced no social limitations due to visual impairment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Bivariate and Multivariate Analysis for the Occurrence of Visual Impairment\u003c/h2\u003e \u003cp\u003eIn this study, bivariate logistic regression analysis was conducted to explore the association between visual impairment and a range of independent variables. These included demographic factors (age, sex, years of service, educational level, and occupation), ocular conditions (cataract, glaucoma, and refractive errors), systemic health conditions (diabetes mellitus and hypertension), and functional limitations (difficulty in watching television, recognizing faces, and reading printed materials). Behavioral and lifestyle variables\u0026mdash;such as cigarette smoking, excessive alcohol consumption, level of physical activity, concern about eye health, regular eye examinations, use of protective eyewear, and difficulty participating in social activities due to visual impairment\u0026mdash;were also assessed. The results of this analysis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eVariables that were statistically significant in the bivariate analysis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were entered into a multivariate logistic regression model to control for potential confounding. The multivariate analysis identified the following factors as independently and significantly associated with the occurrence of visual impairment: advanced age, presence of cataract, glaucoma, refractive errors, diabetes mellitus, cigarette smoking, and difficulty watching television. Each of these variables had a p-value less than 0.05, indicating a statistically significant relationship with visual impairment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate and Multivariate Logistic Regression Analysis of Factors Associated with Visual Impairment among study Hospitals in Addis Ababa, Ethiopia (n\u0026thinsp;=\u0026thinsp;213)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eVisual impairment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCOR(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110(51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103(48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.118(1.082\u0026ndash;1.155)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.073(1.035\u0026ndash;1.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCataract\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53(24.9)\u003c/p\u003e \u003cp\u003e57(36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(8.5)\u003c/p\u003e \u003cp\u003e84(39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.11(2.205\u0026ndash;7.663)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.806(2.414\u0026ndash;13.969)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlaucoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(18.8)\u003c/p\u003e \u003cp\u003e70(32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(0.9)\u003c/p\u003e \u003cp\u003e85(39.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.698(1.423\u0026ndash;5.117)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.386(1.008\u0026ndash;5.647)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.048*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR.error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(11.7)\u003c/p\u003e \u003cp\u003e85(39.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(7.5)\u003c/p\u003e \u003cp\u003e87(40.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.599(.798-3.205)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.009(1.345\u0026ndash;11.953)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.013*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(20.2)\u003c/p\u003e \u003cp\u003e67(31.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(5.6)\u003c/p\u003e \u003cp\u003e91(42.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.867(2.385\u0026ndash;9.933)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.682(1.376\u0026ndash;9.856)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.009*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifficulty watching TV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76(35.7)\u003c/p\u003e \u003cp\u003e34(16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(9.4)\u003c/p\u003e \u003cp\u003e83(39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.276(4.921\u0026ndash;17.49)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.616(1.616\u0026ndash;8.091)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerforming D.tasks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29(14.1)\u003c/p\u003e \u003cp\u003e81(44.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e05(1.9)\u003c/p\u003e \u003cp\u003e98(39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7017(2.598\u0026ndash;18.95)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.713(.856-16.106\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCigarette smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51(19.7)\u003c/p\u003e \u003cp\u003e59(39,0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(3.3)\u003c/p\u003e \u003cp\u003e89(38.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.495(2.793\u0026ndash;10.812)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.167(1.661\u0026ndash;10.455)\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: constants are represented by the value 1, while an asterisk (*) denotes a statistically significant association.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThis study explored the prevalence and determinants of visual impairment among individuals aged 40 years and older attending military hospitals in Addis Ababa. The overall prevalence of visual impairment was found to be 51.6%, significantly higher than rates reported in various international studies. For comparison, a population-based cross-sectional study in India reported a prevalence of 12.6% [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], while a community-based study in Sri Lanka indicated 21.3% [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Similarly, a study in China found a prevalence of 12.45% [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Within Ethiopia, previous studies have shown varying prevalence rates: Debre Birhan (16.8%), Addis Ababa (22.6%) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], Gondar (15.3%) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and Northwest Ethiopia (40.8%) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], with a community-based study in Southern Ethiopia reporting 36.95% [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].The higher prevalence observed in this study may be attributed to the unique demographic and health profiles of military personnel compared to the general population. Factors such as age, gender distribution, and physical fitness can significantly influence the prevalence of specific eye conditions. Additionally, military personnel typically undergo more frequent eye examinations and have better access to specialized care, facilitating earlier detection of vision-related issues that might go unnoticed in civilian populations. Psychological stress associated with military service, along with lifestyle factors such as diabetes mellitus and smoking, may further compromise visual health. In contrast, a retrospective chart review in South Africa reported an overall prevalence of 61.5% [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], exceeding our findings. This discrepancy may be due to differences in study design and participant age.\u003c/p\u003e \u003cp\u003eThis study highlights the prevalence of bilateral visual impairment among participants, with common symptoms including difficulties in reading and blurred vision. The significant impact of visual impairment on daily life is evident, as many participants reported challenges in everyday activities. This information is vital for healthcare professionals and policymakers, guiding the development of targeted interventions and support initiatives for those affected by visual impairment. And the finding reveals critical associations between various factors and the likelihood of visual impairment among older adults. Notably, the probability of experiencing visual impairment increases by approximately 7.3% with each additional year of age. This statistically significant relationship underscores the need for routine screenings and targeted interventions focused on visual health for older populations.\u003c/p\u003e \u003cp\u003eThe findings revealed a strong association between several modifiable and non-modifiable risk factors and the occurrence of VI, consistent with a growing body of global and regional evidence. Cataracts were the most prominent predictor of visual impairment in this population. Individuals with cataracts were found to have approximately 5.8 times higher odds of developing VI (AOR\u0026thinsp;=\u0026thinsp;5.806, 95% CI: [exact interval to be inserted]), confirming cataract as a leading cause of visual disability. This aligns with the World Health Organization's (WHO) report, which continues to identify cataracts as the foremost cause of blindness globally, especially in low- and middle-income countries where access to surgical intervention may be limited [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Similarly, a community-based cross-sectional study conducted in Ghana reported a comparable adjusted odds ratio of 6.2 for cataract-related VI among adults over 40, reinforcing the global consistency of this association [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. These findings highlight the necessity for routine cataract screening and timely surgical services within military health institutions.\u003c/p\u003e \u003cp\u003eGlaucoma was another significant determinant in this study. Participants diagnosed with glaucoma had more than double the odds of visual impairment compared to those without (AOR\u0026thinsp;=\u0026thinsp;2.36, p\u0026thinsp;=\u0026thinsp;0.048). This is consistent with findings from a Nigerian hospital-based study where the prevalence of glaucoma-related visual impairment reached 21.4% among individuals aged 40 and above [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Given the irreversible nature of vision loss due to glaucoma, early detection through intraocular pressure measurement and optic nerve evaluation remains vital in reducing its impact.\u003c/p\u003e \u003cp\u003eRefractive errors also showed a statistically significant association with visual impairment. Individuals with uncorrected or poorly corrected refractive errors were nearly four times more likely to experience VI (AOR\u0026thinsp;=\u0026thinsp;4.009, p\u0026thinsp;=\u0026thinsp;0.013). This is corroborated by the results of the Rapid Assessment of Avoidable Blindness (RAAB) survey in Ethiopia, which identified refractive error as the second most common cause of moderate VI [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This highlights the importance of improving access to affordable eye examinations and corrective lenses, particularly in military hospital settings where vision acuity is crucial for active personnel and retired servicemen alike.\u003c/p\u003e \u003cp\u003eDiabetes mellitus (DM) emerged as a critical determinant. Diabetic participants had a 3.68-fold increased risk of VI (AOR\u0026thinsp;=\u0026thinsp;3.682, p\u0026thinsp;=\u0026thinsp;0.009), suggesting a strong association between diabetes and diabetic retinopathy, a well-known complication of uncontrolled blood glucose levels. A large-scale meta-analysis by Yau et al. found that nearly one-third of diabetic individuals globally exhibit signs of diabetic retinopathy, many of which result in vision loss [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Similarly, a study conducted in southern Ethiopia showed a significant burden of vision-threatening diabetic retinopathy among patients attending chronic disease clinics [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These findings reinforce the need for integrated eye care and diabetes management protocols to mitigate avoidable visual impairment.\u003c/p\u003e \u003cp\u003eMoreover, limitations in performing routine daily activities, such as watching television, were significantly associated with VI. Participants who reported difficulty watching television had approximately 3.62 times greater odds of visual impairment (AOR\u0026thinsp;=\u0026thinsp;3.616). This mirrors findings from Selangor in Peninsular Malaysia., which reported that difficulty with functional vision tasks is a sensitive indicator of both existing and developing VI among older adults [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These findings advocate for the inclusion of functional vision assessments in routine clinical evaluations, especially among older individuals who may underreport visual symptoms.\u003c/p\u003e \u003cp\u003eFinally, cigarette smoking was identified as a modifiable lifestyle factor with a significant association with visual impairment. Smokers in the study exhibited more than four times the odds of VI compared to non-smokers (AOR\u0026thinsp;=\u0026thinsp;4.167), consistent with previous meta-analyses that link smoking to age-related macular degeneration and cataracts [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This supports the role of targeted health education and smoking cessation programs as key components in preventing avoidable vision loss among older adults.\u003c/p\u003e"},{"header":"6. Strengths and Limitations","content":"\u003cp\u003e\u003cstrong\u003e6.1. Strengths\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTargeted Population\u003c/strong\u003e: Focusing on individuals aged 40 and above attending military hospitals allows for a specialized understanding of visual impairment in a specific demographic, enhancing the relevance of the findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMilitary Context\u003c/strong\u003e: The unique environment of military hospitals may provide insights into the prevalence of visual impairment influenced by occupational hazards or lifestyle factors specific to military personnel.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublic Health Implications\u003c/strong\u003e: The study has potential implications for public health policy, as understanding determinants can inform targeted interventions to improve eye health among this population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6.2. Limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeneralizability\u003c/strong\u003e: Findings may not be applicable to the broader population outside military settings, limiting the external validity of the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample Size and Selection Bias\u003c/strong\u003e: If the sample size is small or not representative of all military hospital attendees, it could skew results and fail to capture the full spectrum of visual impairment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCross-Sectional Design\u003c/strong\u003e: A cross-sectional study design provides a snapshot in time but does not establish causality, making it difficult to determine the directionality of the relationships between determinants and visual impairment.\u003c/p\u003e"},{"header":"7. Conclusion and Recommendations","content":"\u003cdiv id=\"Sec35\" class=\"Section2\"\u003e \u003ch2\u003e7.1. Conclusion\u003c/h2\u003e \u003cp\u003eThis study revealed a prevalence of visual impairment of 51.6% among individuals aged 40 years and above in certain military hospitals, indicating a significantly high rate within this demographic. Key determinants of visual impairment identified include age, cataracts, glaucoma, refractive errors (RE), diabetes mellitus (DM), difficulties in watching television, and cigarette smoking. These findings underscore the urgent need for targeted interventions and comprehensive eye care among this population.\u003c/p\u003e \u003cp\u003e \u003cb\u003e7.2. Recommendations\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eEnhanced Screening Programs\u003c/b\u003e: Implement regular vision screening and assessment programs within military hospitals to identify individuals at risk and facilitate early intervention.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eEducational Outreach\u003c/b\u003e: Develop educational initiatives aimed at increasing awareness about eye health, risk factors for visual impairment, and the importance of regular eye examinations among military personnel and their families.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePolicy Development\u003c/b\u003e: Advocate for policies that prioritize eye health in military healthcare planning, ensuring resources are allocated for prevention, treatment, and rehabilitation of visual impairments.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eFurther Research\u003c/b\u003e: Encourage longitudinal studies to explore the causal relationships between identified determinants and visual impairment, providing a deeper understanding of the underlying factors influencing eye health in this population.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eAFCSH:\u003c/strong\u003e Army force comprehensive specialized hospital; \u003cstrong\u003eAMA\u003c/strong\u003e: Age-related degeneration\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBCVA:\u003c/strong\u003e Best corrected macular degeneration; \u003cstrong\u003eDM:\u003c/strong\u003e Diabetes mellitus; \u003cstrong\u003eDR\u003c/strong\u003e: Diabetic retinopathy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eERD\u003c/strong\u003e: Eye related disease; \u003cstrong\u003eFPH\u003c/strong\u003e: Federal police hospital; \u003cstrong\u003eHTN:\u003c/strong\u003e Hypertension; \u003cstrong\u003eRE\u003c/strong\u003e: Refractive error; \u003cstrong\u003eSPSS\u003c/strong\u003e: Statistical Package for the Social Sciences \u003cstrong\u003eVI:\u003c/strong\u003e Vision impairment \u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch3\u003eAcknowledgments\u003c/h3\u003e\n\u003cp\u003eThe authors are grateful to Addis Ababa University for assigning research advisors and providing stationery items. We also appreciate the study participants for their willingness to participate and the time they dedicated during data collection. Additionally, we acknowledge the use of an AI tool for editing and grammar corrections in various parts of the manuscript.\u003c/p\u003e\n\u003cp id=\"_Toc198557695\"\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eA formal letter of ethical clearance and approval was obtained from the Institutional Review Board of Addis Ababa University (IRB-AAU) with protocol number SNM/03/2025, specifically from the School of Nursing and Midwifery\u0026apos;s Department of Nursing Research Committee. Once ethical approval was secured, supportive letters were issued by the School of Nursing and Midwifery to the selected hospitals. Participants were informed about the study\u0026apos;s objectives, and written permission was obtained from the hospital administrations prior to the initiation of data collection. \u003cstrong\u003eInformed consent\u003c/strong\u003e was secured from each participant immediately before data collection began. During the informed consent process, participants received a clear overview of the research and its objectives. They were informed that they could participate of their own free will and had the right to withdraw from data collection at any moment.\u003c/p\u003e\n\u003cp id=\"_Toc198557696\"\u003eTo ensure the privacy of the participants\u0026apos; data, no personal identifiers were included in the data collection tool, thereby keeping their information confidential throughout the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNot-applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll essential data are included in the manuscript. For any additional data requests, please contact the corresponding author for further documentation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis thesis is submitted as a partial achievement of the requirement for an MSc degree from the School of Postgraduate Studies at Addis Ababa University. This thesis has been deposited in the Library of Addis Ababa University and is made available to the user under the rules of the library. The authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding for this study was not provided by any institution or agency, but some stationary items, such as A4 size papers for photocopying data collection questionnaires, pencils, and research advisor assignments, were provided by the Addis Ababa University postgraduate office.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is the result of joint research, and the contribution of each author is comparable to the others. The roles of each author are as follows:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1. \u0026nbsp;Meles Gizachew:\u003c/strong\u003e Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Project administration, Software, and Writing original draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e \u003cstrong\u003eTeshome Habte:\u003c/strong\u003e Conceptualization, Data curation, Methodology, Project administration, Supervision, validation, visualization and Writing review and editing. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e \u003cstrong\u003eZeleke Argaw:\u0026nbsp;\u003c/strong\u003eConceptualization, Data curation, Investigation, Project administration, Supervision, validation, visualization and Writing review and editing. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Aklil Hailu:\u003c/strong\u003e Data curation, Formal Analysis, Investigation, Methodology, Supervision, Writing review and editing \u0026nbsp;\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization, Blindness and vision impairment \u0026amp; WHO. ; Aug 10 [cited 2025 Nov 14]. (2023). Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/blindness-and-visual-impairment\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/blindness-and-visual-impairment\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZou, M. et al. Prevalence of visual impairment among older Chinese population: A systematic review and meta-analysis. \u003cem\u003eJ. global health\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e, 08004 (2021). PMID: 33981412; PMCID: PMC8088771.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarovski, M. \u0026amp; Gazepov, S. PSYCHOLOGY OF LOW VISION. \u003cem\u003eKNOWLEDGE-International J.\u003c/em\u003e \u003cb\u003e63\u003c/b\u003e (4), 473\u0026ndash;477 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoyegbone, J. et al. Visual Impairment Management and Associated Socio-demographic Factors among School Children in Delta State, Nigeria published 25 August 2024. available at:: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://researchpubjournals.org/\u003c/span\u003e\u003cspan address=\"https://researchpubjournals.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYe, H. et al. Prevalence and factors associated with visual impairment in middle-aged and older Chinese population. \u003cem\u003eFront. Med.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e, 962729 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOgedengbe, T. O. Content development for a tool to assess the preparedness of employment environment to welcome people with visual impairment. (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSteinmetz, J. D. et al. Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study. \u003cem\u003eLancet Global Health\u003c/em\u003e. \u003cb\u003e9\u003c/b\u003e (2), e144\u0026ndash;e60 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFlaxman, S. R. et al. Global causes of blindness and distance vision impairment 1990\u0026ndash;2020: a systematic review and meta-analysis. \u003cem\u003eLancet Global Health\u003c/em\u003e. \u003cb\u003e5\u003c/b\u003e (12), e1221\u0026ndash;e34 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDalton, M. K. et al. Analysis of surgical volume in military medical treatment facilities and clinical combat readiness of US military surgeons. \u003cem\u003eJAMA Surg.\u003c/em\u003e \u003cb\u003e157\u003c/b\u003e (1), 43\u0026ndash;50 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvans, D. D. \u0026amp; Hoyt, K. S. Ophthalmologic emergencies: Assessment and management. \u003cem\u003eAdv. Emerg. Nurs. J.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e (4), E9\u0026ndash;E38 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAssefa, N. L., Admas, A. W. \u0026amp; Adimasu, N. F. Prevalence and associated factors of visual impairment among adults at Debre Berhan town, North Shewa, Ethiopia. \u003cem\u003eBMC Ophthalmol.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e, 1\u0026ndash;8 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKilleen, O. J. et al. Population prevalence of vision impairment in US adults 71 years and older: the National Health and Aging Trends Study. \u003cem\u003eJAMA Ophthalmol.\u003c/em\u003e \u003cb\u003e141\u003c/b\u003e (2), 197\u0026ndash;204 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTagoh, S., Kyei, S., Kwarteng, M. A. \u0026amp; Aboagye, E. Prevalence of refractive error and visual impairment among rural dwellers in Mashonaland Central Province, Zimbabwe. \u003cem\u003eJ. Curr. Ophthalmol.\u003c/em\u003e \u003cb\u003e32\u003c/b\u003e (4), 402\u0026ndash;407 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbeysena, C. \u0026amp; Bandara, H. Prevalence of visual impairment among adults aged forty years and above in a medical officer of health area in Sri Lanka: cross-sectional study. (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCherinet, F. M., Tekalign, S. Y., Anbesse, D. H. \u0026amp; Bizuneh, Z. Y. Prevalence and associated factors of low vision and blindness among patients attending St. Paul\u0026rsquo;s Hospital Millennium Medical College, Addis Ababa, Ethiopia. \u003cem\u003eBMC Ophthalmol.\u003c/em\u003e \u003cb\u003e18\u003c/b\u003e, 1\u0026ndash;6 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWiafe, B. \u0026amp; Universal, O. E. \u003cem\u003eGhana blindness and visual impairment study\u003c/em\u003e (International Agency for the Prevention of Blindness, 2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeme, T. G., Mengistu, M. \u0026amp; Getahun, F. Prevalence and associated factors of visual impairment among adults aged 40 and above in Southern Ethiopia, 2022. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e (1), 2542 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeshabane, M. M., Rampersad, N. \u0026amp; Mashige, K. P. Prevalence, causes and factors associated with vision impairment in Limpopo province. \u003cem\u003eAfr. Vis. Eye Health\u003c/em\u003e. \u003cb\u003e83\u003c/b\u003e (1), 1\u0026ndash;9 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. World Report on Vision. Geneva: WHO. (2019). available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications-detail-redirect/world-report-on-vision\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications-detail-redirect/world-report-on-vision\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNuertey, B. D. et al. Prevalence Causes, and Factors Associated with Visual Impairment and Blindness among Registered Pensioners in Ghana.J Ophthalmology. ; \u003cb\u003e2019\u003c/b\u003e:1717464. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2019/1717464\u003c/span\u003e\u003cspan address=\"10.1155/2019/1717464\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. (2019). PMID: 31687194; PMCID: PMC6800954.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOnakoya, A. O., Mbadugha, C. A. \u0026amp; Aribaba, O. T. Pattern of glaucoma presentation in Lagos, Nigeria: Implications for blindness prevention. \u003cem\u003eNiger J. Ophthalmol.\u003c/em\u003e \u003cb\u003e28\u003c/b\u003e (1), 21\u0026ndash;27 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTegegn, M. T., Assaye, A. K. \u0026amp; Belete, G. T. Prevalence, causes and associated factors of visual impairment and blindness among older population in outreach site, Northwest Ethiopia. A dual center cross-sectional study. \u003cem\u003eAfr. Health Sci.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e (3), 683\u0026ndash;695 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYau, J. W. Y. et al. Global prevalence and major risk factors of diabetic retinopathy. \u003cem\u003eDiabetes Care\u003c/em\u003e. \u003cb\u003e35\u003c/b\u003e (3), 556\u0026ndash;564. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2337/dc11-1909\u003c/span\u003e\u003cspan address=\"10.2337/dc11-1909\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012). Epub 2012 Feb 1. PMID: 22301125; PMCID: PMC3322721.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCherinet, F. M., Tekalign, S. Y., Anbesse, D. H. \u0026amp; Bizuneh, Z. Y. Prevalence and associated factors of low vision and blindness among patients attending St. Paul\u0026rsquo;s Hospital Millennium Medical College, Addis Ababa, Ethiopia. \u003cem\u003eBMC Ophthalmol.\u003c/em\u003e \u003cb\u003e18\u003c/b\u003e, 1\u0026ndash;6 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKee, Q. T., Abd Rahman, M. H., Mohamad Fadzil, N., Mohammed, Z. \u0026amp; Shahar, S. The impact of near visual impairment on instrumental activities of daily living among community-dwelling older adults in Selangor. \u003cem\u003eBMC Res. Notes\u003c/em\u003e. \u003cb\u003e14\u003c/b\u003e (1), 395. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13104-021-05813-3\u003c/span\u003e\u003cspan address=\"10.1186/s13104-021-05813-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021). PMID: 34689826; PMCID: PMC8543948.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Prevalence, Determinants, Visual Impairment, Adults Aged 40+, Military Hospitals, Addis Ababa","lastPublishedDoi":"10.21203/rs.3.rs-8243267/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8243267/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eVisual impairment (VI) remains a significant public health concern in Ethiopia, particularly among adults aged 40 years and above, where it is often attributable to preventable or treatable causes. This study aimed to assess the prevalence and determinants of VI among this population in military hospitals in Addis Ababa.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo determine the prevalence and identify associated factors of visual impairment among individuals aged 40 years and above attending selected military hospitals in Addis Ababa.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA facility-based cross-sectional study was conducted from January 20 to February 20, 2025, involving 213 participants selected through systematic random sampling (every 8th eligible adult patient from the follow-up registry). Data were collected using structured questionnaires and standardized vision assessment tools. Descriptive statistics summarized demographic and clinical characteristics. Chi-square tests assessed associations between categorical variables and VI. Bivariate and multivariate logistic regression analyses were performed to identify significant predictors at a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eThe mean age of participants was 56 years (range 40\u0026ndash;92), with 63% male and 46.5% retired. The prevalence of visual impairment was 51.6%. Major associated conditions included cataracts (33.8%), hypertension (29.1%), and diabetes mellitus (25.8%). Significant predictors of VI included older age, cataracts, glaucoma, refractive errors, diabetes mellitus, cigarette smoking, and difficulty watching television.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eVisual impairment affects over half of the study population and is significantly associated with modifiable and age-related factors. Early detection and targeted eye care services are urgently needed for this high-risk group.\u003c/p\u003e","manuscriptTitle":"Prevalence and Determinants of Visual Impairment among Individuals Aged 40 Years and Above Attending Military Hospitals in Addis Ababa, 2025: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-16 09:04:03","doi":"10.21203/rs.3.rs-8243267/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7675d20f-4b2a-465a-8b9d-c0dc301f944a","owner":[],"postedDate":"December 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59571626,"name":"Health sciences/Diseases"},{"id":59571627,"name":"Health sciences/Health care"},{"id":59571628,"name":"Health sciences/Medical research"},{"id":59571629,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-01-07T11:24:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-16 09:04:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8243267","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8243267","identity":"rs-8243267","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}