Refractive errors, including myopia, hypermetropia, and astigmatism, are among the most common visual impairments worldwide, particularly affecting young adults. They are a prevalent ocular health concern among students, significantly impacting academic performance and quality of life. Studies consistently demonstrate a rising incidence of myopia, particularly in school-aged children and young adults, often attributed to increased near work and reduced outdoor activity.1

Medical students, with their prolonged exposure to academic tasks such as reading, computer use, and microscopic work, are at higher risk for developing such conditions. Refractive errors among medical students interfere in performing visual tasks required in medical practice like reading charts and examining patients in addition to negatively affecting their studies.2  

This cross-sectional study aims to assess the prevalence of refractive errors and identify potential determinants among medical students in Delhi. By evaluating factors such as age, gender, study habits, screen time, and family history of refractive errors, the study seeks to provide insights into the burden of visual impairment in this specific population. Understanding these factors is crucial, as early detection and timely correction can mitigate the impact of refractive errors on academic performance and overall well-being. 

Previous studies have indicated a rising trend of refractive errors in students, especially in urban settings, making this research pertinent to the medical student population of Delhi.3,4 (Sharma et al., 2019; Rathi et al., 2021).

Study-design:

This was a cross sectional study involving the undergraduate medical students studying in a reputed medical college in New Delhi.  All the students currently enrolled in MBBS course in the study medical college were eligible for participation.

Sample Size: Sample size was calculated by taking prevalence (P) of refractive errors as 48.3% from another study conducted by Dharmesh k Patel, et. al involving similar population in India.5 Sample size was calculated by using cochran’s formula, where Z1 a/2 = standard normal variate (1.96 at 5% type 1 error), d= precision (5%), the sample size came out to be 383. To account for a potential 10% non-response rate, the target sample size was increased to 430.

Sampling technique:

Simple random sampling was used for selection of participants. A computerized random number generator was used to select 110 participants from each of the four MBBS batches, ensuring representation across all academic years. Students corresponding to the selected roll numbers were invited to participate after receiving a detailed explanation of the study objectives and providing written informed consent. Nine students declined participation, resulting in a final sample of 431 participants.

All the participants who were using spectacles or contact lens and had their ophthalmological check-up record were considered to be suffering from refractive errors. For others, visual acuity examination was performed by using snellen’s chart. Findings were documented in a record sheet. In addition, data were collected using a self-administered, semi-structured questionnaire, which was developed to gather information on sociodemographic profiles, known refractive errors, corrective measures, screen time, reading habits, and eye exercise practices. The questionnaire underwent pilot testing with 30 participants, and its validity was assessed prior to the main study.

Statistical Analysis

Data were entered into Microsoft Excel, cleaned to identify and correct errors and missing values, and then analyzed using SPSS version 21.0. Descriptive statistics were used to summarize participant characteristics, and data were presented in tables and appropriate diagrams. Quantitative data were analyzed using t-tests, while qualitative data were analyzed using chi-square tests. A p-value of < 0.05 was considered statistically significant.

Ethical Considerations

The study was conducted after obtaining clearance from Institutional Ethics Committee. The participation was purely voluntary and informed consent was obtained from all the participants. Confidentiality of the data was strictly maintained.

Complete responses were obtained from 426 subjects, which were included for the final analysis.

Table 1. Distribution of participants according to Sociodemographic profile (N = 426)

Table 1 summarizes the socio-demographic profile of 426 participants, revealing a group predominantly comprised of individuals aged 20 or older (65.26%) and males (67.84%). The participants are distributed relatively evenly across four professional years, with each year group representing approximately a quarter of the total sample. This suggests a study population with a mature age demographic, a significant male majority, and a balanced representation from all four years of their professional program. A family history of refractive errors was reported by 247 (58%) of the participants.

Table 2: Type of refractive error (n=268)

Table 2 demonstrates the distribution of refractive errors among the study participants, revealing that myopia is the most prevalent condition, affecting a significant 87.1% of the group, with a notably higher occurrence in females. Conversely, hypermetropia is the least common, observed in only 3.7% of participants, with a slight male predominance. Astigmatism accounts for 9.2% of refractive errors and is distributed relatively evenly between males and females. In summary, the data highlights a strong skew towards myopia, particularly in females, within the study population.

Table 3: Association of various variables with prevalence of refractive errors

We tried to further investigate the association of various variables with prevalence of refractive errors among study population. The analysis reveals significant associations between refractive errors and several factors, such as age, gender, professional year of study, and family history of refractive errors. For instance, younger participants (<20 years) were more likely to have refractive errors, and males showed a higher prevalence compared to females. Additionally, participants in later years of study (third and fourth year) were more likely to experience refractive errors, suggesting a potential link between prolonged academic demands and vision issues. A family history of refractive errors was also a significant factor, with those having a family history being more prone to developing refractive errors. (Table 3)

On the other hand, no significant associations were found between refractive errors and factors like frequency of consuming Vitamin A-rich foods, screen time, and practicing eye exercises. This suggests that these variables may not be directly influencing the occurrence of refractive errors in this sample. Time spent reading printed material, however, showed a significant link, with longer reading durations associated with higher rates of refractive errors. These findings highlight the complex interplay of genetic, demographic, and behavioral factors in the development of refractive errors.

The current study revealed several significant associations with the prevalence of refractive errors among undergraduate medical students. Notably, older age (≥20 years) was associated with a higher prevalence, a finding consistent with studies demonstrating the progressive nature of myopia and other refractive conditions as individuals age. This aligns with research by Morgan et al. which discusses the "epidemics of refractive error" and the structural changes in the eye over time.1 Similar studies have also reported that older medical students are more likely to develop refractive errors, likely due to prolonged academic exposure, increased screen time, and close-up work.6

Gender also played a role, with females exhibiting a higher prevalence, which may be influenced by hormonal factors or lifestyle differences. Similar gender disparities have been reported in the European Eye Epidemiology (E3) Study by Williams et al, highlighting the need for further investigation into these potential causes.7 This aligns with findings from another research, which reported a higher prevalence of myopia in female medical students, potentially due to hormonal changes during puberty, increased indoor activities, and higher levels of academic stress.8

Furthermore, the professional year of study showed a strong association with the highest prevalence found in fourth-year students (75.7%). This could be due to the cumulative effect of years spent in academic settings, which often involve long hours of reading, studying, and working on computers. As students advance in their studies, the demands on their visual health intensify, leading to higher rates of refractive errors. This finding is consistent with other studies, such as one by Vashist et al., which found that the prevalence of myopia increased as students progressed in their academic years, primarily due to increased academic pressure and time spent on near-vision tasks.9

A positive family history of refractive errors also significantly increased the likelihood of having the condition, reinforcing the substantial genetic component of myopia, as evidenced by genome-wide association studies identifying numerous genetic loci associated with refractive error.10 This result aligns with numerous studies, including one by Gupta et al. (2018), which confirmed that family history is a key risk factor for developing refractive errors, particularly myopia. Genetic predisposition plays a substantial role in determining the likelihood of developing refractive errors, with children of myopic parents being at a significantly higher risk.11  The time spent reading printed material was significantly associated with refractive errors, supporting the "near work hypothesis" that prolonged close-up activities contribute to myopia development, as reviewed by Rosenfield (2011).12 This is consistent with other studies which suggest that prolonged near-vision tasks, such as reading printed materials, contribute to visual strain and may increase the risk of myopia.13

Conversely, no significant associations were found between the frequency of vitamin A consumption, screen time, or the practice of eye exercises and refractive errors. The lack of association with screen time, despite increasing digital device usage, is in contrast with other studies.13 this may be due to variations in usage patterns or breaks taken during screen time. Inconsistent association of screen time with myopia has been reported by Lanca C et al.14 Additionally, the study found no significant association between the practice of eye exercises and refractive errors, which is consistent with findings from other studies that have questioned the efficacy of eye exercises in reducing refractive error progression.15 While vitamin A is crucial for eye health, its direct role in refractive error development is less clear as documented by other authors as well.16 These  results suggest that other factors may play a more dominant role.

This study highlights a notably high prevalence of refractive errors (62.9%) among the student population, with myopia being the most dominant type. Significant associations were observed between refractive errors and factors such as age, gender, professional year of study, family history of refractive errors, and time spent reading printed material. These findings suggest that both genetic predisposition and academic-related visual strain contribute substantially to the development of refractive errors.

Conversely, lifestyle factors such as screen time, frequency of consuming Vitamin A-rich foods, and practicing eye exercises did not show a statistically significant relationship with the occurrence of refractive errors. These results emphasize the importance of early screening, especially among students in higher academic years and those with a family history of visual issues, as well as promoting healthy visual habits to mitigate the progression of refractive problems.

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