Dry eye among medical students before and during COVID-19

Abstract

Purpose:

Dry eye is a multifactorial disease of the ocular surface. It showed an increased incidence during the pandemic situation, which may be due to long hours of exposure to electronic gadgets. We aimed to find the prevalence of dry eye disease among medical students during the coronavirus disease 2019 (COVID-19) pandemic and pre-pandemic periods.

Methods:

This was a cross-sectional study conducted in a tertiary care teaching institute. This was an institution-based, cross-sectional study conducted among medical students. A modified Ocular Surface Disease Index (OSDI) questionnaire was used to find the severity and prevalence of dry eye disease. Considering 95% confidence interval (CI) and prevalence as 50%, the calculated sample size was 271. Online responses were collected and entered in an Excel sheet. The Chi-square test, univariate and multivariate logistic regression were used for statistical analysis.

Results:

Data were collected from 271 medical students; the prevalence of dry eye disease was 41.5 and 55.19 during the pre-pandemic and pandemic periods, respectively. There was a significant rise in dry eye disease cases during the pandemic when compared to pre-pandemic period (P < 0.05). The odds of getting dry eye disease were 1.7 times more during the pandemic than pre-pandemic.

Conclusion:

The lockdown situation during the pandemic forced people to use electronic gadgets for work, recreation, and academics. Prolonged screen time predisposes to the development of dry eye disease.

The coronavirus disease 2019 (COVID-19) outbreak worldwide affected people’s routine lives. The imposed containment measures compelled the public and students to use electronic gadgets with greater frequency for education, job, and recreational purposes, which predisposes them to dry eye.

“Dry eye is a multifactorial disease of the ocular surface characterized by a loss of homeostasis of the tear film, and accompanied by ocular symptoms, in which tear film instability and hyperosmolarity, ocular surface inflammation and damage, and neurosensory abnormalities play etiological roles.”[1] The study of dry eye disease (DED) is a rapidly expanding field which requires the ophthalmologist to stay abreast with not only newer management modalities but also diagnostic challenges that mimic, coexist, and aggravate dry eye. It is a disorder that affects all age groups, thereby causing considerable impact on the health sector both in terms of financial and manpower requirements. This study was undertaken to find the increase in prevalence of DED among medical students during the pandemic.

Methods

This was a cross-sectional study that was conducted in a tertiary care teaching institute among medical students from December 2021 to March 2022. Considering the prevalence of DED among the students to be 20% and the proportion of nonresponders as 10%, the required sample size was 271. All the students who were willing to participate in the study were included after getting informed consent from them. Participants with history of chemical injury and corneal surgery were excluded from the study. A modified Ocular Surface Disease Index (OSDI) questionnaire with a few additional questions was used for this study. The questionnaire included a pre-pandemic and a pandemic section to calculate the prevalence of DED before and during the pandemic. The responses were entered in a Google Excel sheet and analyzed using Statistical Package for the Social Sciences (SPSS) version 21. An OSDI score of 0–12 points was considered as normal, 13–22 points as mild disease, 23–32 points as moderate disease, and 33–100 points as severe disease. Along with these scores, number of hours spent with the electronic gadget and the type of gadget used were taken into consideration. The past history of DED was also taken into account.

Quantitative variables were expressed as mean and standard deviation, and categorical variables as frequency and percentages. Kolmogorov–Smirnov test was used to find the normality of distribution. Mann–Whitney U test and Chi-square test were used to find the significance of association between the factors and DED. Multivariate logistic regression analysis was done to find the factors associated with DED during the pandemic and pre-pandemic periods.

Results

A total of 274 students participated in the study, out of which three students were excluded from the analysis due to incomplete data. The prevalence of DED among the medical students was 41.5% and 55.19% during the pre-pandemic and pandemic periods, respectively. There was a significant difference in the number of DED cases before and during the pandemic (P < 0.005), and the odds of getting DED were 1.7 times more during the pandemic [Table 1].

Table 1.

Significance of increased dry eye disease

	Dry eye	No dry eye	P	Odds ratio
Pandemic	148	122	0.003	1.71 (1.22-2.41)
Pre-pandemic	112	158

Various characteristics like the average time spent for academic and nonacademic purposes, type of gadget used, and previous treatment history for DED were taken into consideration and their values were tabulated for the pre-pandemic and pandemic periods [Tables 2 and 3].

Table 2.

Factors associated with dry eye disease during the pre-pandemic period using multi logistic regression analysis

Characteristics Pre-pandemic	Disease		P	Adjusted odds ratio
	Yes	No
Total screen time
<2 h	17	25	0.086	0.67 (0.25-1.81)
3-4 h	28	68		1.53 (0.68-3.47)
4-5 h	29	28		0.64 (0.28-1.49)
>5 h	38	37		1
Screen time for academic use
<2 h	55	93	0.652	1.76 (0.7-4.41)
3-4 h	24	36		1.81 (0.65-5.03)
4-5 h	16	16		1.45 (0.48-4.37)
>5 h	17	13		1
Screen time for nonacademic use
<2 h	34	80	0.077	2.35 (0.86-6.4)
3-4 h	44	52		1.13 (0.45-2.87)
4-5 h	16	11		0.87 (0.28-2.7)
>5 h	18	15		1
Gadget for academic use
Mobile	82	113	0.444	0.81 (0.33-1.98)
Laptop	15	15		0.55 (0.17-1.71)
Tablet	5	12		1.72 (0.37-7.92)
iPad	10	18		1
Gadget for nonacademic use
Mobile	88	130	0.65	0.81 (0.27-2.42)
Laptop	9	10		0.65 (0.15-2.8)
Tablet	5	3		0.27 (0.04-1.91)
iPad	4	3		0.48 (0.07-3.21)
TV	6	12		1
Previous treatment for dry eye
Yes	12	21	0.016	2.66 (1.18-5.98)
No	91	146		1

Table 3.

Factors associated with dry eye disease in the pandemic period using multi logistic regression

Characteristics Pandemic	Disease		P	Adjusted odds ratio
	Yes	No
Total screen time
<2 h	08	29	<0.001	0.09 (0.02-0.36)
3-4 h	23	26		0.60 (0.20-1.82)
4-5 h	30	23		0.93 (0.33-2.60)
>5 h	88	43		1
Screen time for academic use
<2 h	49	66	0.001	0.69 (0.25-1.91)
3-4 h	35	27		0.71 (0.26-1.92)
4-5 h	30	12		1.29 (0.48-3.46)
>5 h	35	16		1
Screen time for nonacademic use
<2 h	54	52	0.380	1.49 (0.52-4.22)
3-4 h	48	42		0.71 (0.28-1.82)
4-5 h	19	12		0.71 (0.24-2.06)
>5 h	28	15		1
Gadget for academic use
Mobile	103	80	0.292	1.60 (0.60-4.27)
Laptop	17	22		0.53 (0.16-1.74)
Tablet	15	7		2.28 (0.53-9.73)
iPad	14	12		1
Gadget for nonacademic use
Mobile	118	97	0.759	0.90 (0.29-2.79)
Laptop	10	7		1.28 (0.27-6.03)
Tablet	7	3		1.74 (0.25-12.11)
iPad	5	7		0.50 (0.09-2.77)
TV	9	7		1
Previous treatment for dry eye
Yes	26	7	0.004	4.51 (1.65-12.36)
No	123	114		1
COVID-19
Yes	65	46	0.352	1.22 (0.69-2.17)
No	84	75		1
Vaccination
Partial	12	2	0.018	6.47 (1.26-33.38)
Full	137	119		1

COVID-19=Coronavirus disease 2019

Sixty-seven percentage of students who spent more than 5 h duration on electronic gadgets developed DED, with a significant P value of less than 0.001. The odds of getting DED were 91% less in students who used screen time of less than 2 h. Students who had taken treatment for DED in the past had an acute exacerbation of their symptoms during the pandemic. The odds of getting dry eye during the pandemic were 4.5 times higher in them when compared to students who had never taken treatment for dry eye [Table 3]. There was a 65% chance of getting DED in partially vaccinated students compared to those who had full vaccination (P < 0.018) [Table 3].

The median OSDI score was 10.4 before the pandemic and 12.5 during the pandemic. It was not normally distributed (checked by Kolmogorov–Smirnov test), so Mann–Whitney U test was used to check the significant difference between the pre-pandemic and pandemic mean OSDI scores [Fig. 1]. The P value was >0.05, indicating that there was no significant difference in the mean OSDI score between the pre-pandemic and pandemic periods, though there was a significant difference in DED cases between the pre-pandemic and pandemic periods by Chi-square test (P < 0.05).

Figure 1.

Box and whisker plot showing the median Ocular Surface Disease Index scores during the pre-pandemic and pandemic periods. OSDI_P- ocular surface disease index score during pre pandemic OSDI- ocular surface disease index score during pandemic

Discussion

A total of 271 medical students were included in this study. One hundred and twelve students had DED before the pandemic and 148 students had DED during the pandemic, which shows a significant rise in DED with a P value of 0.003. This increase in prevalence could be attributed to the increased usage of visual display terminals (VDT) by the medical students during the pandemic for online lectures, assignments, and tests. In this study, the number of students who spent more than 5 h on digital screen increased by 1.7 times during the pandemic, out of which 67% developed DED. Prolonged screen time causes tear film instability due to reduced blink rate which increases tear film evaporation. Not only infrequent blink, but also incomplete blinking contributes to DED by affecting the renewal of tear film and meibomian gland secretion. The environment also plays a major factor in tear film instability as closed space with low humidity, air-conditioned room, and eye cosmetics alter the lipid layer of the tear film, which predisposes to DED.[2]

Our findings are consistent with those of Iqbal et al.,[3] who found that increased screen time of more than 3 h is associated with an increased risk of developing DED. Munshi et al.[4] also found that electronic devices were one of the predisposing factors to develop DED. A prospective cross-sectional study conducted by Tangmonkongvoragul et al.[2] among medical students found that, in addition to increased screen time, psychological stress from COVID-19 pandemic also contributed to DED. Exposure to blue light near bedtime affected the quality of sleep, and an association between sleep quality and DED was found by Pavithra and Sundar.[5]

In our study, students who had previously received treatment for DED experienced worsening of symptoms during the pandemic due to disease exacerbation. Grittiness and sensitivity to light were the most commonly reported symptoms. Niveditha and Dheepak Sundar,[6] in their study, state that 51% of their study population reported increase in symptoms during the lockdown and the most common symptoms were headache followed by eye strain and dry eyes.

The results also show that students who have been partially vaccinated are more prone to develop DED. Mobile phone was found to be the commonly used gadget for both academic and nonacademic purposes. There was no significant association between the gadget used and the prevalence of dry eye as mobile phones were widely used by all students during the pandemic and pre-pandemic.

Tripathi et al.[7] emphasized that with the new era of digitalization, not only medical students, but also the younger population, in general, are at risk of developing DED. Napoli et al.[8] coined a new term “quarantine dry eye,” stating that in addition to increased usage of VDT, poor nutrition, psychological stress, depression, sedentary lifestyle, sleep deprivation, and poor air quality during a lockdown contributed to DED. Also, the prevalence of dry eye was found to be associated with getting partially vaccinated for covid, which can be due to the immune-mediated reaction of the vaccine; those with partial vaccination had a 65% chance of getting DED. A study conducted by Nyankerh et al. showed dry as one of the reported ocular adverse reactions associated with covid vaccination.[9]

To reduce the incidence and severity of DED, electronic gadgets should be used judiciously. One simple way to prevent DED is by educating students about the 20–20–20 rule, which states that an individual should take a break for 20 s after spending 20 min with the electronic gadget and focus on something 20 ft away and blink their eyes many times.[10]

Limitations of this study include that it was a single-center, questionnaire-based study. No clinical examination or investigation was performed to evaluate the disease.

Conclusion

In conclusion, DED is not only a problem to oneself, but also a burden to the society as it reduces the productivity of the affected people, thereby hindering their contribution. Creating awareness about the adverse effects of increased screen time among students will mitigate the severity and reduce the incidence of DED.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.