Shedding light on pharmacoepidemiology of eye diseases: a cohort study in Western Iran

Abstract

The primary goal in treating glaucoma and other eye disorders is to improve the quality of life for the patient while preserving vision, with minimal side effects. One has to understand the increasing demand for health resources by gaining insight into treatment norms and associated costs. Pharmacoepidemiologic studies examine the use of drugs, their effectiveness, and the safety aspects on large populations by observational studies to realize typical drug effects, adverse reactions, and risk factors. This study fills a gap in areas where little has been done, considering that the vast majority of studies done in this field are based in the US and Europe and only a handful have come from developing countries. The primary aim of this study was to evaluate the pharmacoepidemiology of ophthalmic medications and their association with ocular disease prevalence in a population-based cohort in western Iran. We analyzed the relationship between the pharmacoepidemiology of pharmaceutical medicines and the incidence of associated diseases, while considering significant and extraneous factors influencing disease occurrence. The present study seeks to specifically evaluate the prescribing patterns of the ophthalmic drugs in Kermanshah province. During a 6-year cohort study of 10,046 RaNCD participants, 16.23% used ophthalmic medications, with diabetes, hypertension, cardiovascular disease (CVD), aging, and female sex identified as high-risk factors, whereas normal BMI and regular physical activity were associated with lower prevalence. Dry eye disease (12.19%), allergic conjunctivitis (8.98%), and glaucoma (1.12%) were the most prevalent conditions, showing disparities between genders and across socioeconomic groups. From the perspective of medication, it was dry eye (42.26%, with major use of artificial tears), with many self-stopping (e.g., gentamicin: 38.46%), which points to an asymmetry between adherence and severity management of treatment. The overall eye disease prevalence in males was 26.33% and 34.02% in females, thus pointing to the greater incidence in women who exhibit higher rates for most of the ophthalmopathies, excluding uveitis. The country’s prevalence numbers for dry eye disease (DED), allergic conjunctivitis, blepharitis, and glaucoma were quite low compared with the global average, while those for infectious conjunctivitis seem to sit somewhere in between what is seen in developed countries, with uveitis perched above the global average. We also observed an inversely proportional relationship between chronic diseases and eye disorders; diabetes being associated with all the ophthalmic conditions considered except uveitis. In this population, the prevalence of DED, allergic conjunctivitis, blepharitis, and glaucoma was below the global average, while infectious conjunctivitis was similar to its prevalence in developed countries and uveitis exceeded the global average. In addition, we found that there is a reciprocal relationship between chronic diseases and eye disorders, with diabetes being paired with all ophthalmic conditions except uveitis.

Introduction

About 2.2 billion individuals globally have vision impairment; while almost 43 million are absolutely blind^1,2. These causes are problems with prevention: 157 million cataracts and refractive errors, 95 million uncorrected refractive errors, and 16 million diabetic retinopathies. Some 65% of avoidable blindness occurs in regions where 30% of the population live^3,4. With the aim of bringing down avoidable blindness by 25% by 2030 through increased surgeries and screenings, the WHO made the announcement⁵. Blindness and vision loss are significant health concerns that affect both the physical and mental well-being of patients, especially among the elderly⁶. Blindness is a severe visual impairment, preventing one from perceiving light or discerning shapes even with correction, classified by the WHO with a visual acuity of < 20/400 or a visual field of ≤ 10° in the better eye, the latter term being extended to legal and functional definitions where loss of vision so severe impedes activities of daily living that it may still be termed “functional blindness” where some residual sight remains^1,3,7. Before proceeding, a brief overview of common eye diseases may be helpful for readers. Common eye diseases are typically categorized based on clinical presentation and underlying pathology. These include structural disorders such as anterior segment conditions (e.g., cataracts, glaucoma) and posterior segment pathologies (e.g., age-related macular degeneration [AMD], diabetic retinopathy), as well as functional impairments such as refractive errors, which affect over 2.6 billion people globally. Infectious causes (e.g., conjunctivitis, keratitis) and systemic associations (e.g., hypertension, diabetes) represent additional distinct categories that often overlap with these classifications. However, our study focuses specifically on ocular conditions that are amenable to pharmaceutical treatment, as described in previous literature⁸. In the United States, age-related eye conditions such as glaucoma, cataracts, diabetic retinopathy (DR), and age-related macular degeneration (AMD) are the leading causes of blindness and vision impairment. Additionally, amblyopia and strabismus are two other common eye disorders⁹.

Ocular illnesses rank among the most common five disorders in which the advancement of the disease is strongly linked to inadequate patient compliance^10,11. The rates are similar to those observed with oral treatment for systemic hypertension (HTN) and other chronic asymptomatic diseases^11,12. Approximately 50% of patients with long-term medical conditions in affluent nations are believed to comply with their medication, and this issue is anticipated to be even more significant in developing countries¹³.

Improving the patient’s quality of life through keeping eyesight with minimal harmful effects is the goal of treating glaucoma and many other eye diseases. Assessing the impact of the rising prevalence of health resources requires knowledge of the treatment standards for these patients, as well as the prices of resources¹⁴. Research on the societal impact of pharmaceuticals can be effectively conducted through pharmacoepidemiologic or drug use studies. We selected this region for study because it has not been extensively researched by other scholars¹⁵. The epidemiologic classification of ocular diseases helps physicians in the diagnostic approach, management, and treatment of patients¹⁶. The etio-epidemiologic distribution of ocular diseases varies from region to region and parallels that of many studies that have investigated the pattern in different parts of the world. Most of the data in this field are from the US and Europe, and reports from developing countries are limited. Today, an acceptable number of reports that focus on the epidemiology of uveitis in Iran are available^17,18; however, all these studies have been conducted in university-based ophthalmology centers and cannot be generalized to society and public levels of referral system. also, in relation to the epidemiology of other ocular diseases, the data in our country is limited. Therefore, population-based cohort studies with the aim of investigating the pattern of ocular diseases, especially in the general population, can be of great help to ophthalmologists or proper screening and diagnosis. It is hoped that these studies will be suitable fodder for artificial intelligence (AI) screening, a novel field in telemedicine, for faster diagnosis and treatment with cost benefits especially in areas with limited resources. The aging of the population emphasizes the significance of timely and sufficient treatment of eye ailments to avert visual impairment and a decrease in quality of life. The aim of the current study is evaluating the prescribing patterns of ophthalmic medications in Ravansar population, Kermanshah Province, Iran; based on that, we can indirectly draw the pattern and prevalence of ocular diseases in this region. This study aimed to assess the pharmacoepidemiology of ophthalmic medications and analyze the relationship between systemic chronic conditions and ocular pathologies within the Ravansar Cohort in western Iran.

Methods

Study design and population

The Ravansar non-communicable diseases (RaNCD) cohort is a community-based study. The recruitment phase of this study began in November of 2014 and was completed in February 2017, and was followed by participant follow-up between the years 2017 and 2023, making a total follow-up period of seven years. During the course of the study, over 10,000 men and women aged between 35 and 65 years consented to participate. The city of Ravansar is located in West Iran, more particularly within Kermanshah province which is adjacent to the border of Iraq. It is comprised of urban and rural settings with total inhabitants approximating 50,000. Place of residence was categorized as either urban or rural, based on the official classification of residential areas within Ravansar County by the Iranian Ministry of Health and Medical Education. Urban areas refer to the central city of Ravansar and its adjacent neighborhoods, while rural areas include surrounding villages and settlements. The predominant population of Ravansar is of Kurdish ethnic origin. Additionally, it should be noted that the RaNCD cohort is an extension of the Prospective Epidemiological Research Studies in IrAN (PERSIAN) which was implemented alongside the Ministry of Health and Medical Education through various ethnicities in Iran. Other publications have presented the study design and justification of conducting RaNCD cohort and PERSIAN studies^19,20.

Inclusion and exclusion criteria

The Ravansar Non-Communicable Diseases (RaNCD) cohort had specific general inclusion criteria, including: being between the ages of 35–65 years, having resided in Ravansar for at least one year, providing written informed consent, and being able to communicate effectively with the research team while also holding Iranian citizenship. All eligible participants who entered the study during recruitment were included in the cohort, with no general exclusion criteria.

For this sub-study focusing on the pharmacoepidemiology of ophthalmic medications, we analyzed data from participants who had a documented history of using medications related to ocular pathologies during the 6-year follow-up period. This subgroup was selected to assess prescribing patterns and associated risk factors specifically among individuals with ocular conditions. Therefore, while the broader RaNCD cohort includes all enrolled participants, the current analysis is limited to those with documented use of ophthalmic drugs.

Written informed consent was obtained from all participants prior to enrollment. The consent process was conducted by trained personnel who explained the purpose of the study, data collection procedures, confidentiality policies, and the voluntary nature of participation.

The study was advertised through local health centers, community gatherings, public announcements, and collaboration with village and neighborhood leaders. Potential participants were invited to join via phone calls and face-to-face communication. These strategies ensured broad awareness and accessibility within the target population.

Data collection and measurements

This study used face-to-face interviews administered on site. Participants were also reminded the day before their scan appointments, through an additional phone call, to come without eating.

Weight while registering and when the biological samples were collected was assessed using a Bio Impedance Analyzer (BIA), also called InBody 770 BIOSPACE, KOREA; height on the other hand was collected majorly using a stadiometer that has an accuracy of 0.1 cm. The BMI is achieved by dividing the measured weight in kilograms over the height in Corners’ squared.

The smoking status was assessed according to the National Health Interview Survey (NHIS)²¹ criteria. An individual’s current smoker was defined as one who has yes smoked 100 cigarettes in their referring lifetime and continued to take them. A previous or an ex-smoker is a person that has stopped smoking cigarettes and/or other tobacco products²².

Diabetes mellitus (DM) is characterized by a fasting plasma glucose (FPG) level of 7mmol/L (126 mg/dL) and above, and may require the inclusion of insulin or oral antidiabetic drugs²³. On the other hand, dyslipidemia is characterized by elevated levels of low-density lipoprotein cholesterol (LDL-C) of 160 mg/dL and higher, total cholesterol levels of 240 mg/dL and higher, high density lipoprotein cholesterol (HDL-C) levels below 40 mg/dL, triglycerides levels of 200 mg/dL and higher and/or the use of related drugs²⁴.

The research sample included participants who had experience with medications related to ocular pathology. This study focused on ocular conditions amenable to pharmaceutical treatment and diagnosis based on clinical history and medication use. These included: dry eye disease (DED), allergic conjunctivitis, infectious conjunctivitis, glaucoma, uveitis, and blepharitis. Diabetic retinopathy and age-related macular degeneration (AMD) were not systematically diagnosed due to the absence of routine fundoscopic exams; however, cases receiving anti-VEGF agents (e.g., bevacizumab) or systemic vitamins suggestive of AMD were identified as potential indicators of posterior segment involvement. Due to the absence of routine fundoscopic exams and slit-lamp-based lens evaluations during the cohort follow-up, retinal pathologies such as diabetic retinopathy and age-related macular degeneration, as well as cataracts, were not systematically diagnosed or reported.

Ophthalmic conditions were identified based on participants’ self-reported medical history and current or past use of ophthalmic medications. These medications include both topical formulations (e.g., eye drops) and systemic drugs with recognized ophthalmic indications, such as oral antibiotics for blepharitis or systemic vitamins for age-related macular degeneration. The list of medications presented in Table 1 includes both systemic and topical ophthalmic formulations, while agents administered to fewer than ten individuals were excluded from the analysis due to low frequency of use. (Note: The percentages related to ophthalmic drug use were calculated based on the total count of medication items prescribed, rather than on the patient level, in order to better capture prescription patterns.)

Table 1.

Medication used based on ophthalmopathy (Eye drug use includes both topical (eye drops, ointments) and systemic medications used for ophthalmic indications.)

Ophthalmopathy	Drug name	ATC/DDD	Count (%)	Discontinued (%)
Mild DED	Artificial tear	S01XA20	1829 (32.31)	263 (14.47)
	Polyvinyl Alcohol	-	26 (0.46)	2 (7.69)
	Carbomer	-	42 (0.74)	5 (11.9)
Moderate DED	Vitamin A (ophthalmic oint.)	A11CA	50 (0.89)	9 (18)
Severe DED	Fluorometholone	S01BA07	414 (7.31)	46 (11.5)
	Loteprednol	-	10 (0.17)	-
Very severe DED	Cyclosporine	S01XA18	10 (0.17)	-
	Total		2392 (42.26)	326
Allergic conjunctivitis	Naphazoline	S01GA01	108 (1.92)	27 (25)
	Naphazoline/ Antazoline	S01GA51	16 (0.28)	3 (18.75)
	Olopatadine	S01GX09	59 (1.05)	8 (13.56)
	Ketotifen	S01GX08	52 (0.90)	9 (17.31)
	Cetirizine	S01GX12	14 (0.24)	2 (14.29)
	Betamethasone (Drop)	S01BA06	1153 (20.37)	133 (11.54)
	Betamethasone (systemic use)	S01BA06	13 (0.23)	-
	Ketorolac	S01BC05	16 (0.28)	-
	Total		1453 (25.67)	185
Infectious conjunctivitis	Sulfacetamide	S01AB04	75 (1.33)	26 (34.67)
	Chloramphenicol	S01AA01	517 (9.13)	63 (12.19)
	Levofloxacin (Ophthalmic)	S01AE05	10 (0.17)	-
	Ciprofloxacin (Ophthalmic)	S01AE03	285 (5.03)	27 (9.47)
	Ciprofloxacin (systemic use)	J01MA02	20 (0.35)	2 (15)
	Total		918 (16.25)	119
Glaucoma	Timolol	S01ED01	110 (1.94)	7 (6.36)
	Brimonidine	S01EA05	68 (1.21)	5 (7.35)
	Acetazolamide	S01EC01	19 (0.33)	2 (10.53)
	Dorzolamide	S01EC03	19 (0.33)	3 (4.92)
	Dorzolamide Timolol	S01ED51	61 (1.08)	-
	Total		339 (5.98)	18
Blepharitis	Erythromycin	S01AA17	64 (1.14)	13 (20.31)
	Tetracyclines	S01AA09	89 (1.58)	21 (23.60)
	Gentamicin	S01AA11	13 (0.23)	5 (38.46)
	Total		166 (2.93)	39
Uveitis	Tropicamide	S01FA01	10 (0.17)	2 (20)
	Homatropine Hydrobromide	S01FA05	11 (0.19)	2 (18.18)
	Diclofenac	S01BC03	102 (1.76)	7 (26.92)
	Total		153 (2.72)	16
Wet AMD	Bevacizumab	S01LA08	108 (1.92)	6 (5.56)
Dry AMD	Vitamin A (systemic use)	A11CA	15 (0.26)	-
	Vitamin B1	A11DA	10 (0.17)	2 (20)
	Vitamin E	A11	14 (0.24)	2 (14.29)
	Total		53 (0.94)	6
Tetracaine abuse	Tetracaine	S01HA03	38 (0.67)	5 (13.15)
HSV Keratitis	Acyclovir	S01AD03	19 (0.33)	2 (10.53)
Preseptal cellulitis	Cefalexin	J01DB01	12 (0.21)	-
			5745	762

Due to the absence of routine ophthalmoscopic exams and visual field assessments in the RaNCD cohort protocol, clinical diagnoses were not independently confirmed. Instead, drug utilization patterns and patient-reported disease history were used as proxies for disease prevalence. Medications were categorized based on current and trusted ophthalmological sources, including Vaughan & Asbury’s General Ophthalmology, and the opinion of a group of well-qualified ophthalmologists^8,25. As an example, Glaucoma was clinically defined based on intraocular pressure (IOP) measurements (> 21 mmHg), optic disc changes (increased vertical cup-to-disc ratio ≥ 0.6), retinal nerve fiber layer thinning, and/or characteristic visual field defects consistent with glaucomatous optic neuropathy. Diagnoses were confirmed by expert ophthalmologists following standardized ocular examinations. All participants underwent a comprehensive ophthalmologic examination including non-contact tonometry for IOP measurement, slit-lamp biomicroscopy, dilated fundus examination, and optical coherence tomography (OCT) when indicated. Visual fields were assessed using automated perimetry for suspected cases. In addition to clinical findings, individuals prescribed antiglaucoma medications such as timolol, brimonidine, latanoprost, or dorzolamide were included in the glaucoma category. These prescriptions were reviewed alongside clinical history and examination findings to confirm diagnosis. Dry eye disease was defined based on prescription of artificial tears and lubricants. Allergic conjunctivitis was identified by use of topical antihistamines or corticosteroids. Glaucoma was clinically defined by use of antiglaucoma medications such as beta-blockers, alpha agonists, and prostaglandin analogs. Uveitis and blepharitis were determined based on clinical history and prescribed anti-inflammatory or antibiotic regimens.

The ATC/DDD framework of analysis was used in evaluating the impact of each drug to enable accurate evaluation of each drug. Drug Utilization Studies (DUR) commonly employs the ATC system of classifying drugs and the Defined Daily Doses (DDD) classification. The ATC system describes medical compounds based on their characteristics and therapeutic potentials, while the DDD shows the average dosage maintained per day for the specific purpose of the drug for the adults. This methodology, also known as DDD WHO, is therefore recommended by the World Health Organization (WHO) and is regarded as the global standard for evaluating the use of drugs. The use of ATC/DDD system has increased the scope of international comparisons of national databases²⁶.

Statistical analysis and calculations

Descriptive statistics were used to summarize participant characteristics, with continuous variables (e.g., age, BMI, physical activity levels) presented as means and standard deviations, and categorical variables (e.g., gender, place of residence, socioeconomic status, smoking status) reported as frequencies and percentages.

For comparative analysis, Quantitative variables (e.g., age, BMI, physical activity levels) were compared between participants with and without ophthalmic drug use using independent samples t-tests. Qualitative variables (e.g., gender, place of residence, socioeconomic status, smoking status) were analyzed using the chi-square test to assess differences in distribution across groups.

To explore associations between demographic and clinical variables and ophthalmic drug use, Univariate logistic regression was first performed to identify statistically significant associations (p < 0.05) between each variable and ophthalmic drug use.

Variables found to be significant in univariate analysis were then included in multivariate logistic regression models, which were used to estimate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for each ophthalmic condition. Non-significant variables were systematically removed during model building to ensure parsimony and interpretability.

All statistical analyses were conducted using STATA software (version 18), and a p-value < 0.05 was considered statistically significant.

Ethics statement

This study was conducted in accordance with the Helsinki Declaration. All participants provided written informed consent after receiving a full explanation of the study’s objectives and procedures. The consent process was conducted by trained personnel, ensuring participants understood their rights and the voluntary nature of involvement. This study received support from Kermanshah University of Medical Sciences. The cohort study received ethical approval from the Ethics Committee of Kermanshah University of Medical Sciences (ethics approval number: IR.KUMS.REC.1403.145).

Results

From 10,046 participants in RaNCD cohort 1631 (16.23%) used medications for eye illnesses in duration of 6 years follow-up. There were significant association between the used of ophthalmic medications and gender, age, history of CVD (cardiovascular disease), BMI, Socio economic of status, DM and HTN, place of residence, and MET physical activity. The Prevalence ratio of eye disease in diabetics to non-diabetics is nearly two times; in those with HTN, it is nearly 1.5; and in those with CVD history, it is 1.7. Our study demonstrated that individuals with a normal BMI and those participating in over 44.5 min of weekly physical activity exhibit a lower prevalence of eye diseases, with no association found between eye color or marital status and ophthalmopathies (Table 2).

Table 2.

Demographic and clinical characteristics of participants in RaNCD cohort.

Variables		Total N (%)	Ophthalmic drug use		P value
			No N (%)	Yes N (%)
Total		10,046(100)	8415(83.77)	1631(16.23)
Sex	Male	4,763 (47.41)	4091(85.89)	672(14.11)	< 0.001
	Female	5,283 (52.58)	4,324 (81.85)	959 (18.15)
Age group	35–45	4,754 (47.32)	4,220 (88.77)	534 (11.23)	< 0.001
	46–55	3,203 (31.88)	2,689 (83.95)	514 (16.05)
	55–65	2,089 (20.79)	1,506 (72.09)	583 (27.91)
Marital status	Single	981 (9.76)	803 (81.86)	178 (18.14)	0.08
	Married	9,065 (90.23)	7,612 (83.97)	1,453 (16.03)
Place of residence	Urban	5,996 (59.68)	4,927 (82.17)	1,069 (17.83)	< 0.001
	Rural	4,050 (40.31)	3,488 (86.12)	562 (13.88)
Socioeconomic of status	Poorest	2,009 (19.99)	1,722 (85.71)	287 (14.29)	0.008
	2	2,009 (19.99)	1,663 (82.78)	346 (17.22)
	3	2,008 (19.98)	1,688 (84.06)	320 (15.94)
	4	2,008 (19.98)	1,642 (81.77)	366 (18.23)
	Richest	2,008 (19.98)	1,697 (84.51)	311 (15.49)
Smoking status	No	4,065 (40.46)	3,398 (83.59)	667 (16.41)	0.23
	Current	1,151(11.45)	982 (85.32)	169 (14.68)
	Former	869 (8.65)	712 (81.93)	157 (18.07)
	Passive	3,846 (38.28)	3,221 (83.75)	625 (16.25)
BMI	Under	175 (1.74)	142 (81.14)	33 (18.86)	0.01
	Normal	2,786 (27.73)	2,384 (85.57)	402 (14.43)
	Overweight	4,322 (43.02)	3,573 (82.67)	749 (17.33)
	Obese	2,648 (26.35)	2,220 (83.84)	428 (16.16)
MET Physical activity	min/36.5	3,043 (30.29)	2,510 (82.48)	533 (17.52)	< 0.001
	36.6/44.4	4,781 (47.59)	3,972 (83.08)	809 (16.92)
	44.5/max	2,222 (22.11)	1,933 (86.99)	289 (13.01)
DM	No	8,912 (88.71)	7,586 (85.12)	1,326 (14.88)	< 0.001
	Yes	1,085 (10.80)	783 (72.17)	302 (27.83)
HTN	No	7,794 (77.58)	6,664 (85.50)	1,130 (14.50)	< 0.001
	Yes	2,251 (22.40)	1,750 (77.74)	501 (22.26)
Dyslipidemia	No	5,611 (55.85)	4,718 (84.08)	893 (15.92)	0.32
	Yes	4,435 (44.14)	3,697 (83.36)	738 (16.64)
CVD	No	8,065 (80.28)	6,916 (85.75)	1,149 (14.25)	< 0.001
	Yes	1,981 (19.71)	1,499 (75.67)	482 (24.33)
Eye color	Brown/ Hazal	8,857 (88.16)	7,425 (83.83)	1,432 (16.17)	0.48
	Amber	506 (5.03)	428 (84.58)	78 (15.42)
	Green	510 (5.07)	424 (83.14)	86 (16.86)
	Blue / Gray	173 (1.72)	138 (79.77)	35 (20.33)

RaNCD: Ravansar non-communicable diseases, BMI: body mass index, MET: metabolic equivalent, DM: diabetes mellitus, HTN: systemic hypertension, CVD: cardiovascular disease, urban: central City and adjacent neighborhoods; rural: surrounding villages and settlements.

From a total of 10,046 participants in RaNCD, 1219 (12.19%) individuals had DED (Dry eye disease), 112 (1.12%) people suffered from Glaucoma, 52 (0.52%) persons had Uveitis, 665 (6.65%) individuals suffered from Infectious conjunctivitis, 898 (8.98%) people had Allergic conjunctivitis and 125 (1.24%) people suffered from blepharitis. DED, Glaucoma, Allergic conjunctivitis, and Infectious conjunctivitis exhibit a higher incidence in women compared to males. Conversely, Uveitis is more prevalent in men, whereas blepharitis affects both genders equally (Fig. 1). (Note: Disease prevalence percentages are based on the total number of participants, while drug use percentages are based on the total number of prescribed medication items.)

Fig. 1.

Prevalence of common eye diseases overall and in gender subgroups.

Among patients received eye diseases treatments, 1912 (62.2%) used one medication, 680 (22.1%) two medications, 201 (6.5%) three medications, and 278 (9.05%) had ≥ 4 medications. Glaucoma patients used the highest amount of medication simultaneously, while people suffering from blepharitis require the lowest amount (Table 3). (Please note: The figures in this table represent the total number of medications prescribed per condition and do not correspond directly to the number of individual patients, as some patients received multiple medications.)

Table 3.

Number of drugs prescribed per prescription.

Eye diseases	Number of medications (%)
	1	2	3	4 ≤
DED	665 (54.55)	313 (25.68)	85 (6.97)	156 (12.79)
Glaucoma	53 (47.32)	19 (16.96)	12 (10.71)	28 (25)
Uveitis	35 (67.53)	10 (19.48)	3 (6.49)	4 (6.50)
Allergic conjunctivitis	587 (65.37)	189 (21.05)	59 (6.57)	63 (7.01)
Infectious conjunctivitis	478 (73.23)	126 (18.95)	38 (5.71)	23 (3.45)
Blepharitis	94 (75.30)	23 (18.07)	4 (3.01)	4 (3.01)
Total	1912 (62.2)	680 (22.1)	201 (6.5)	278 (9.05)

With increasing age, the odds of developing all ophthalmopathies rise. Gender also influences the odds of all ophthalmopathies, except for blepharitis. Additionally, all ophthalmopathies, except blepharitis, are associated with socioeconomic status. Having DM increases the likelihood of developing all eye diseases except uveitis. Furthermore, place of residence and physical activity are associated with the prevalence of DED and glaucoma. Finally, CVD and dyslipidemia are specifically linked to glaucoma (Table 4).

Table 4.

Multivariable adjusted factors on pharmacoepidemiology by types of disease.

Variables		Eye problems	Glaucoma	DED	Uveitis	Allergic conjunctivitis	Infectious conjunctivitis	Blepharitis
		OR (95%CI)	OR (95%CI)	OR (95%CI)	OR (95%CI)	OR (95%CI)	OR (95%CI)	OR (95%CI)
Sex (ref: male)	Female	1.41 (1.22_1.63)	2.13 (1.26_3.59)	1.53 (1.30_1.80)	---	1.33 (1.08_1.65)	1.25 (1.05_1.49)	---
Age group (ref: 35–45 year)	46–55	1.45 (1.26_1.66)	2.43 (1.33_4.26)	1.50 (1.28_1.76)	2.18 (1.11_4.25)	1.66 (1.35_2.06)	1.70(1.38_2.08)	1.34 (0.85_2.12)
	55–65	2.81(2.41_3.28)	5.47 (3.05_9.80)	2.84 (2.39_3.37)	2.24 (0.98_5.10)	3.18 (2.54_3.99)	3.44(2.81_4.22)	1.78(1.08_2.94)
Marital status (ref: Single)	Married	---	---	---	---	---	---	---
Place of residence (ref: urban)	Rural	---	0.56 (0.34_0.93)	0.78 (0.67_0.90)	---	---	---	---
Socio economic of status (ref: poorest)	2	1.36 (1.13_1.63)	0.57 (0.27_1.20)	1.44 (1.17_1.76)	1.44 (0.39_5.2)	1.22 (0.95_1.58)	1.18 (0.92_1.52)	---
	3	1.27(1.05_1.54)	1.01(0.51_1.98)	1.28 (1.03_1.58)	3.19(1.0_10.1)	1.35(1.03_1.76)	1.32(1.03_1.70)	---
	4	1.61(1.32_1.95)	1.94(1.03_3.68)	1.63 (1.31_2.03)	1.92(1.0_6.78)	1.49(1.12_1.97)	1.47(1.14_1.90)	---
	Richest	1.55(1.25_1.93)	1.53(0.72_3.26)	1.66 (1.30_2.11)	3.79(1.08_13.1)	1.19(0.86_1.66)	1.15(0.86_1.55)	---
Smoking status (ref: No)	Current	---	---	---	---	---	---	---
	Former	---	---	---	---	---	---	---
	passive	---	---	---	---	---	---	---
BMI (ref: underweight)	Normal	0.69 (0.46_1.04)	---	---	---	---	---	---
	Overweight	0.77 (0.51_1.16)	---	---	---	---	---	---
	Obese	0.65 (0.42_0.98)	---	---	---	---	---	---
Physical activity (ref: )	Min/36.5	---	---	---	---	---	---	---
	36.6/44.4	---	0.82 (0.53_1.26)	1.00 (0.86_1.1)	---	---	---	---
	44.5/max	---	0.52(0.26_0,99)	0.81 (0.66_0.99)	---	---	---	---
Diabetes (ref: No)	Yes	1.61 (1.37_1.89)	1.75 (1.07_2.86)	1.61 (1.35_1.92)	---	1.61 (1.29_2.10)	1.61 (1.28_2.02)	2.01 (1.27_3.17)
HTN (ref: No)	Yes	---	---	---	---	---	---	---
Dyslipidemia (ref: No)	Yes	---	0.85 (0.75_0.97)	---	---	---	---	---
CVD (ref: No)	Yes	1.17 (1.01_1.37)	1.23 (1.03_1.64)	---	---	---	---	---
Eye color (ref: Brown/ Hazal)	Amber	---	---	---	---	---	---	---
	Green	---	---	---	---	---	---	---
	Blue / gray	---	---	---	---	---	---	---

Multivariate logistic regression models were adjusted for variables that showed statistical significance in univariate analysis.

Table 5 demonstrates that the duration of diabetes significantly contributed to the incidence of eye disease, whereas the duration of hypertension did not have a notable effect on the occurrence of eye disease.

Table 5.

The impact of diabetes and hypertension duration on eye disease incidence.

Disease	Duration	Total N (%)	Eye drug use		P value
			No N (%)	Yes N (%)
DM	≤ 5 years	215 (19.81)	165 (76.74)	50 (23.26)	< 0.001
	> 5 years	870 (80.27)	618 (71.03)	252 (28.97)
HTN	≤ 5 years	672 (29.85)	531 (79.02)	141 (20.98)	0.8
	> 5 years	1579 (70.14)	1219 (77.2)	360 (22.8)

The analysis of medication usage for ophthalmopathies indicates that DED is responsible for the highest quantity of prescribed eye medications, accounting for 42.26% of prescriptions, with artificial tears constituting 32.31% of total medications. Among individuals with DED, we observed that 79.30% of medications were related to the treatment of mild DED, such as artificial tears, Polyvinyl alcohol, and etc. Only 2.09% were prescribed for moderate DED, specifically Vitamin A ophthalmic ointment and lubricant gel. Furthermore, 17.72% of medications targeted severe DED, including Fluorometholone and Loteprednol, while a mere 0.41% were allocated for very severe DED, which involved Cyclosporine. Allergic conjunctivitis ranks second, comprising 25.67% of used medications, and is primarily treated with topical corticosteroids (Betamethasone Drop), prescribed in 20.37% of instances. Infectious conjunctivitis is the third most prevalent condition, with a medication usage rate of 16.27%; Key treatments include Chloramphenicol (9.13%) and Ophthalmic Ciprofloxacin (5.03%). Glaucoma follows as the fourth most common eye disease, representing 5.98% of total medication use, with Timolol (1.94%), Brimonidine (1.21%), and Latanoprost (1.21%) as primary treatments (Table 1). (Note: The reported percentages for drug use were calculated based on the total number of prescribed medication items (n=5745), rather than the number of individual patients, to reflect prescribing patterns.)

In our research, one person experienced Central Serous Retinopathy (CSR) while receiving treatment with Eplerenone, and two others had hypertensive retinopathy. The medications prescribed for managing Dry AMD included systemic Vitamin A, Vitamin B1, Vitamin E, and Vitamin C, with an average of 0.94% medications used. Among the participants, 108 individuals received intravitreal bevacizumab for wet AMD, and 53 individuals were prescribed systemic vitamins suggestive of dry AMD. However, formal ophthalmoscopic confirmation was not available for most cases. Additionally, Preseptal Cellulitis accounted for 0.21% of medication use, specifically Cefalexin. Besides we found that, among a community of 10,000 individuals in this study, 38 participants indicated misuse of Tetracaine. Out of a total of 5745 medication items, 762 were discontinued without a doctor’s prescription. The drugs with the highest rates of discontinuation without medical advice include gentamicin (38.46%), sulfacetamide (34.67%), tetracyclines (23.60%), and erythromycin (20.31%) (Table 1).

Discussion

This research is among the pioneering studies to fully assess the burden and impact of eye disease in the Iranian population and developing countries, adding more to the available literature on the subject. The difference between disease prevalence rates and medication use percentages is due to calculation methods: prevalence was based on the population, whereas medication use was based on the total number of prescribed drugs.

Global and regional prevalence of DED

DED is a common ocular disorder causing discomfort to millions of patients around the globe with the regional prevalence rates reported as low as 5%, and as high as 50%^27,28. In the current study, dry eye disease is found to be the most prevalent eye disease accounting for 12.19% of the detailed cases. The collation of the available prevalence data estimates about 10–30% of the population in the United States suffers from DED and it is higher, almost 50% among elderly people with certain risk factors^29,30. On the other hand, they claim that the dry eye disease prevalence in China is even more severe reaching estimates of 20 to 50% whilst it is mostly in city dwellers and above the age of fifty³¹. It is plausible that such differences in prevalence can arise due to a number of environmental and lifestyle factors and other characteristics of populations, for example, the level of air pollution or the access to medical care^32,33.

Allergic conjunctivitis: Iran vs. global rates

As per our study, we chart allergic conjunctivitis prevalence in Iran at 8.98 per cent which is a rather lower than average global rates of allergic conjunctivitis prevalence of 15 to 20%. In the United States, the prevalence of allergic conjunctivitis is estimated to be approximately around 15–40%³⁴. Which is obviously still higher than the estimate of 8.98% reported in the case of allergic conjunctivitis in Iran. The difference in epidemiological patterns of allergic conjunctivitis can be attributed to various factors such as the kind of allergens involved, seasonal variation, climatic conditions such as pollution and use of indoor allergens, health education, ethnic factors and health care^35–37.

Bacterial conjunctivitis in iran: socioeconomic implications

According to our research, the incidence of bacterial conjunctivitis in Iran stands at 6.65%. This figure is slightly more compared to other regions of the world, as fond statistics vary greatly with the geographical and social status of the specific area^38,39. For example, the prevalence rates in health care deficient population may go over 30% as a result of poor hygiene conditions⁴⁰. On the other hand, countries with economic development like the US tend to record lower ones at levels between 2% and 10%. In the US, the similar studies have found about 4% and 6% prevalence rates^41,42. Prevalence of bacterial conjunctivitis in Iran is on the level of developed countries, which indicates the success of the local health care system and rising awareness of eye care and healthcare services availability^43,44.

Blepharitis: underdiagnosis in population-based studies

The current investigation reveals that the prevalence of blepharitis is 1.24%, which is much lower than the global spectrum of 10–40%^45,46. This discrepancy could be attributable to the profiles of the population sample studied as they can be less symptomatic persons. In addition, the lower prevalence may also be compounded by the fact that there are different diagnostic criteria for identifying blepharitis^47,48. Last but least, the reason for the low prevalence observed can be the nature of the research where the study was conducted among the general population and not in a clinical setting as most patients in clinical setting tend to have more severe symptoms and are more willing to seek care⁴⁹.

Glaucoma in iran: lower rates and contributing factors

The results of studies conducted in various countries, including Iran, show that, the prevalence of glaucoma among the age category of 35–65 years is reported to be around 1.12%, which is lower than the global approximated average of 2 to 4% after the of same population age cohort^50,51. The pattern is however different, with records indicating between 3 and 4% of glaucoma prevalence within this particular age group in the United States. The record in Europe is not any different as the rates also range between 2 and 4%. This means that the prevalence rates for glaucoma in Iran is much lower as compared to U.S. and European regions^51,52. The differences in the estimation or assessment of the prevalence rates of glaucoma can be explained in many interacting ways. For example, these include genetic factors which vary among different ethnicities⁵³, variations in the provision of health care services and the policies related to screening healthy populations⁵⁴, and the concern of the public about this health problem^55,56. Lifestyle and other environmental considerations in addition to demographic age structures and social economic circumstances are also other causes of the variation, where the western countries tend to have better control and management systems for glaucoma patients^57,58.

Uveitis: higher incidence in Iran and etiological complexities

Uveitis global prevalence rates seem not to have standard figures and ranges from a low estimate of 38 to as high as two hundred cases in one hundred thousand individuals equivalent to about 0.038–0.2%⁵⁹. On the other hand, in this regard, our research has established the incidence rate to be a higher figure of 0.52% possibly arising from environmental and societal reasons including genetic composition and more contagious illness, availability of healthcare systems and their reporting^60,61. Trying to minimize this phenomena, the public could be educated on the signs and symptoms of uveitis, eye care services could be expanded, regular screening of vulnerable population groups could be done, vaccine offered against the causative organisms, and the health care providers trained appropriately in order to reduce the prevalence figures to global acceptable levels^62–65.

Gender disparities in eye disease prevalence

The investigation shows that the overall prevalence of eye ailments was found to be 26.33% in male participants and 34.02% in female participants, suggesting that, on an average, females are more affected than males^66,67. There are many reasons why female gender has more prevalence of the eye diseases than male gender. Among these reasons are hormonal affection towards the eye health which is prominent during menopause which leads to the commonness of the DED condition^68,69. In addition, women have a longer life expectancy compared to men which puts them at a higher risk of suffering from degeneration of such eyes diseases as cataract and AMD⁷⁰. Women are also more likely to suffer autoimmune diseases, which can lead to problems with the eyes as could be the case with the excessive rates of thyroid associated disorders and DM which add to the eyecare burden^71,72. In certain health systems, women report higher prevalence of the illness, where it is linked to certain behavioral patterns and socio-economic factors, such as the ability to obtain services and a greater tendency to consult. Moreover, there may be higher heritable factors of eye disease in women than in men and about some regions, women might work under jobs that have more risk of sustaining eye damage^73,74. All these factors, therefore, account for the higher tendency of women suffering from illnesses of the eye than men.

Uveitis in males: occupational and biological risks

Back to our research – the incidence rate of uveitis was determined to be 0.4% in females, and 0.64% in males, indicating a higher rate among males. The global projection rates show that the figures are about 17.9 cases of the morbidity assert per 100 000 person-years for women and 25.6 for men^75,76. This may be explained by the fact that men have more occupational exposures that aggravate the condition such as stress, hormonal disparities and variation in immunologic responses. In addition to that, men may be prone to certain diseases that are known to cause uveitis which as an autoimmune disease^77,78. Given these results, an even more exhaustive examination of these discrepancies is warranted.

Interplay between chronic systemic diseases and ocular health

We have observed that chronic diseases and eye diseases are interlinked issues. Eye diseases such as diabetic retinopathy, hypertensive retinopathy and others can be due to chronic conditions such as hypertension, coronary heart disease and diabetes^79,80. On the other hand, chronic diseases can also be made worse by eye diseases because they limit a person’s physical activity which is necessary in the treatment of these conditions^81,82. For example, lack of clear vision may affect one’s ability to move hence reduce the level of activities performed by patient’s which always predisposes the individual patient to cardiovascular diseases and high blood sugar levels^83,84. This interrelation calls for a more integrated health care system where chronic diseases and health of the eye are both catered for⁸⁵. Studies indicate that patients suffering from chronic ailments benefit from an enhanced treatment of their eye complications. Therefore, holistic care is justified in such cases^86–88.

Diabetes as a catalyst for multifactorial ophthalmopathies

Our study established that all eye diseases except for uveitis are associated with diabetes mellitus for several reasons as to why the prevalence is high. Furthermore, the duration of diabetes in a person is also an important factor in the eye diseases that may occur. Diabetic Retinopathy occurs when there is increased blood sugar, blood vessels within the retina get damaged hence leading to loss of vision; rest of the eye is affected by chronic hyperglycemia itself^89,90. In addition, poor DM control may lead to a reduced tear film, thus predisposing DED⁹¹. It is also noted that due to diabetes, such patients tend to form cataracts much younger and increase their chances of developing neuropath/glaucoma. Diabetes also contributes to poor blood flow to the eyes. Systemic factors such as glucose control ‘diabetes’ and diabetes type ‘neuropathy, ‘vasculopathy,’ can have direct and damaging effects on the eyes as well^92–94. The reason why those with diabetes are prone to these ophthalmopathies is due to the chronic nature of diabetes and its injurious effect on blood vessels and nerves in the body^95,96. Accordingly, we feel that, for this reason, it is important to perform eye disease screening in persons with diabetes more often.

BMI and ocular health: protective role of normal weight

Our investigation found that people having a normal BMI possess a lower prevalence of eye disorders as opposed to the other BMI groups. The people with a healthy BMI generally suffer from less eye diseases owing to the favorable metabolic profile, low inflammation, good blood flow, healthy lifestyle behavior and a balanced hormonal level^97,98. Therefore, it is of great importance that proper body weight is maintained in order to minimize the chances of developing various eye diseases⁹⁹.

Treatment paradigms: glaucoma vs. blepharitis management

The differences in medications prescribed to patients suffering from glaucoma and blepharitis illustrate important issues for health system planning. Medication for glaucoma patients is more complicated due to the fact that they may necessitate several kinds of drugs used together in their treatment since the goal is to lower the pressure inside the eyeball^100,101. On the other hand, the management of blepharitis is not as extensive because it includes the practice of typical cleanliness and use of topical agents only if necessary^102–104. The differences in these two from an economic point of view, speak to the need for appropriate distribution of services and even better designed education of practitioners who will handle services with more complicated conditions and promulgation of treatment guidelines^55,105. In addition, it is important to note that a range of medications, particularly for glaucoma patients, should also be available to the communities that are not well-resourced⁵⁷. Ongoing monitoring of the treatment and effectiveness of blepharitis medication may ease the prescription of several drugs for patients⁵⁷, while the integrated care approach will foster managing the treatment of differently designed patients¹⁰⁰.

Prevention strategies for reducing ophthalmopathy burden

In accordance to limit the development of ophthalmopathies, numerous approaches can be utilized, such as promoting the regular assiduity of eye check-ups for the diagnosis and treatment of diseases of the eye at their early stages, and even organizing outreach programs on the importance of eye care, their causes and signs in order for people to seek treatment in good time¹⁰⁶. Promoting healthy behaviours that include eating well and exercising can significantly reduce the incidence of diabetes related eye problems, for example, taking food supplements full of vitamins and omega 3 fats¹⁰⁷. Simple measures like promoting the use of UV protective sunglasses will go a long way in reducing the incidence of cataracts and other related injuries to the eyes. Besides, advocating for the cessation of smoking exercises is also effective in prophylaxis of certain visual disorders¹⁰⁸. Proper control of chronic diseases such as DM and HTN, is mandatory to avoid ocular related complications¹⁰⁹. As well, use of computers for long periods without taking breaks can lead to eye strain, and early access to treatment especially in the provision of eye care within the primary healthcare setting is very important for timely diagnosis and treatment¹¹⁰. The implementation of screening programs in the at-risk populations assists in increasing the early detection rates of certain diseases such as glaucoma, and further conducting studies aimed at coming up with more efficient treatment and prevention strategies will improve management of eye conditions^111,112. When these strategies are put together, there is a notable decrease in the occurrence of ophthalmopathies.

Study strengths, limitations and future directions

This research has its merits and demerits, notable merits include sufficiently larger sample size that considerably improves the validity of our results. Furthermore, the response rate was remarkably high standing at 99.06%, which means that our research sample is a valid representation of the wider population. However, it is crucial to note that this research was carried out on the Kurdish ethnic group, which is a minority group in the context of Iran, and one that has been largely overlooked in prior research. This study’s methodological strength however, was in surveying the general population instead of examining only medical records of patients with their disease that most of the previous studies on the epidemiology of ocular conditions have done within university or primary care facilities. The referral center surveys could have also been subject to a sponsorship bias to some extent as such population does not accurately depict the society’s disease pattern. However, since such studies form the bedrock of the screening systems and are the raw material for new screening, particularly AI in telemedicine, expansion of such epidemiologic investigations is suggested in the target population and in the area of general ophthalmology. In summary, this study contributes to the existing body of literature by providing one of the first population-based pharmacoepidemiological assessments of ocular diseases in western Iran. While the association between systemic diseases such as diabetes and ocular pathology is well established, our findings offer novel insights into the real-world prescribing patterns of ophthalmic medications and their relationship with sociodemographic and metabolic risk factors in a relatively understudied region. The study also highlights the importance of establishing baseline data for future implementation of AI-based screening tools, particularly in resource-limited settings.

The major drawback of this analysis is that there is no data about the categories of health care providers who ordered the treatment. In the Ravansar district also there is a scarcity of specialized medical experts. Therefore, it is likely that the treatment methods used are those recommended by the family doctors. One limitation of our study is the underrepresentation of posterior segment and lens-related pathologies such as cataracts and retinal diseases. This may be attributed to the lack of comprehensive ophthalmic evaluations, including fundoscopy and slit-lamp examinations, during the cohort follow-up. As a result, the study did not assess cataract prevalence or retinal pathology systematically due to the absence of routine fundus examination and slit-lamp evaluation in the cohort protocol. Therefore, the true burden of posterior segment diseases may be underestimated. Future studies incorporating advanced diagnostic tools are needed to provide a more complete picture of ocular disease burden in this population. Also, we acknowledge that visual field testing was not uniformly performed across all participants due to resource limitations; however, diagnosis was primarily based on consistent clinical findings and medication use verified through medical records. One limitation of the study is that not all glaucoma cases were confirmed by full structural-functional correlation (i.e., visual field + imaging). Future studies incorporating advanced diagnostics will refine prevalence estimates. One limitation of the study is the lack of systematic screening for diabetic retinopathy via fundoscopy or retinal imaging. Therefore, the true burden of retinopathy among diabetic participants may be underestimated. Given the strong association between diabetes and ocular complications, future studies should incorporate comprehensive retinal evaluations, particularly in high-risk populations such as those with long-standing diabetes, to better understand and manage the burden of diabetic eye disease. another limitation of our study is the reliance on self-reported medical history and medication use to identify ophthalmic conditions, rather than direct clinical diagnosis. This may result in underreporting or misclassification of certain conditions, particularly those requiring advanced diagnostic tools such as retinal imaging or intraocular pressure measurements.  It should also be noted that medication use percentages reflect prescription patterns rather than disease prevalence, as some patients may have received multiple medications or treatments for prophylactic rather than diagnostic purposes. Additionally, reasons for medication discontinuation were not systematically recorded, preventing detailed analysis of treatment adherence or tolerability.

It is believed that the aforementioned considerations will enrich the content of the studies directed at AI screening, an innovative branch of telemedicine, which seeks to speed up the diagnosis and treatment and to make them cost effective especially in the developing countries. This population-based dataset provides valuable insights into the regional burden and treatment patterns of ocular diseases, which can serve as a foundation for developing AI-based screening tools tailored to low-resource settings. Such tools could enhance early detection and improve access to care in areas with limited specialist availability.

Conclusion

This article investigated the connection between prevalence of diseases associated with the consumption and use of drugs and the consumption patterns of these drugs, and in the course of this analysis, appropriate and inappropriate factors related to the prevalence of each disease were also evaluated. In the results, it was found that subjects with normal body mass index health and practicing high level of physical activity had lesser eye related conditions, whereas prevalence ratios were also relatively higher- two times higher for diabetes mellitus, 1.5 times higher for patients with hypertension and 1.7 times higher for patients with a history of cardiovascular diseases. The association between diabetes mellitus and every category of eye disease with the exception of uveitis was noted and also that chronic diseases and their attendant eye problems also had a close link. The data revealed that the overall prevalence of ocular pathologies was 26.33% for the male group and 34.02% for the female group, prevalence rates were higher in females with women having higher prevalence rates for every ophthalmopathy except for uveitis. It also showed that DED, allergic conjunctivitis, blepharitis and glaucoma prevalence rates were at lower than the world average in Iran while infectious conjunctivitis was at the level of developed countries, uveitis prevalence was higher than the global average and overall, this shows that Iran does well in comparison to the world statistics. In conclusion, these studies hopes to better the use of AI screening in telemedicine in the near future for quicker and cheaper diagnoses where there are few resources.

Abbreviations

RaNCD

The Ravansar non-communicable diseases

PERSIAN

The Prospective Epidemiological Research Studies in IrAN

BMI

Body mass index

HTN

Hypertension

NHIS 

National Health Interview Survey

CVD

Cardiovascular disease

MET 

Metabolic equivalent

DED

Dry eye disease

CSR 

Central serous chorioretinopathy

AMD

Age-related macular degeneration,

DR 

 Diabetic retinopathy,

AI 

Artificial intelligence

FBS

Fasting blood sugar,

NHIS 

National Health Interview Survey

DUR

Drug Utilization Research

ATC 

Anatomical Therapeutic Chemical

Author contributions

Z. Mousavi and M. Moradinazar wrote the main manuscript text and M. Bagheri and M. Yavari helped in editing tables and figure and F.Najafi and O. Bahiraee helped in supervision and editing. M. Moradinazar was the corresponding author. All authors reviewed the manuscript.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

The data generated and analyzed during this study are available upon request from the correspondingauthor. Interested researchers should contact the Persian Cohort Portal at https://www.persiancohort-portal.com/ for access to the data.

Competing interests

The authors declare no competing interests.