|Year : 2019 | Volume
| Issue : 3 | Page : 145-149
Prevalence of visual impairment in school-going children among the rural and urban setups in the Udupi district of Karnataka, India: A cross-sectional study
Avinash V Prabhu1, Ramesh S Ve1, Juthika Talukdar2, Varalakshmi Chandrasekaran3
1 Department of Optometry, Manipal College of Health Professions (MCHP), Manipal Academy of Higher Education, Manipal, Karnataka, India
2 Department of Public Health, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, Karnataka, India
3 Department of Community Medicine, Melaka-Manipal Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, India
|Date of Web Publication||11-Oct-2019|
Dr. Ramesh S Ve
Department of Optometry, Manipal College of Health Professions (MCHP), Manipal Academy of Higher Education (MAHE), Manipal - 576 104, Karnataka
Source of Support: None, Conflict of Interest: None
| Abstract|| |
AIM: The aim of this study is to estimate the prevalence of visual impairment among school-going children in Udupi district, Karnataka.
MATERIALS AND METHODS: A cross-sectional study across eleven schools from both urban and rural parts of Udupi taluk was conducted to report the magnitude of visual impairment among the schoolchildren. Complex survey design was used in allocating the sample size through stratification and clustering. Totally 1784 schoolchildren between the age groups of 5 and 15 years participated in the study. Presenting visual acuity and objective refraction was measured using computerized logMAR acuity charts and Plusoptix A09 photorefractor, respectively. Manifest ocular deviation or squint was also recorded.
RESULTS: The mean age of the students was found to be 10.62 ± 2.72 years. The prevalence of visual impairment, i.e., visual acuity worse than or equal to 20/40 in the better eye was found to be 4.32% (95% confidence interval: 3.38%, 5.26%). The prevalence rate was significantly higher among students from urban area (5.6%) compared to those from rural area (3.6%) (P = 0.011).
CONCLUSION: Visual impairment was found to be 4.32% in the school-going population of Udupi district. Effective and user-friendly devices aided the visual deficit screening including refractive error and squint.
Keywords: Plusoptix, prevalence, schoolchildren, screening, visual impairment
|How to cite this article:|
Prabhu AV, Ve RS, Talukdar J, Chandrasekaran V. Prevalence of visual impairment in school-going children among the rural and urban setups in the Udupi district of Karnataka, India: A cross-sectional study. Oman J Ophthalmol 2019;12:145-9
|How to cite this URL:|
Prabhu AV, Ve RS, Talukdar J, Chandrasekaran V. Prevalence of visual impairment in school-going children among the rural and urban setups in the Udupi district of Karnataka, India: A cross-sectional study. Oman J Ophthalmol [serial online] 2019 [cited 2019 Dec 14];12:145-9. Available from: http://www.ojoonline.org/text.asp?2019/12/3/145/268913
| Introduction|| |
Uncorrected refractive errors are the leading cause of avoidable visual impairment in children. It has emerged as a major public health problem needing effective programs from health-care workforce, education professionals, and caretakers. Multiple surveys conducted among school-aged children across the globe have reported varying magnitudes of uncorrected refractive error burden (Nepal: 8.1%, Pakistan: 8.9%, Malaysia: 17.1%, Iran: 3.8%, South Africa: 1.4%, Brazil: 4.82%, Australia: 10.4%, and Chile: 15.8%). Studies from India show that the prevalence of uncorrected refractive error varies from 2.63% to 7.4%.
Globally, around 12.8 million children in the age group of 5–15 years are visually impaired due to uncorrected or inadequately corrected refractive errors. A prevalence of 0.96% with the highest prevalence in urban and highly developed urban areas in Southeast Asia and in China has been reported. To cater the rising prevalence issue, various school eye screening programs have been evolved in the Indian context  majorly under the initiative of the District Blindness Control Society since 1996. To detect subnormal vision at an early stage and to yield the highest benefit from timely referral, emphasis was given to the effective use of instrument-based screening procedures.,
This study, therefore, attempted to report the prevalence of visual impairment in the schoolchildren of the southern coastal region of Karnataka with a specific emphasis on refractive errors.
This study also tried to establish the comparison of visual impairment status in rural versus urban population in this geographic location.
| Materials and Methods|| |
A school-based cross-sectional study was conducted across urban and rural parts of Udupi taluk, Karnataka. Considering a 5% prevalence of visual impairment from the earlier studies conducted in South India  with 95% confidence interval (CI) and 25% of relative precision, the sample size was calculated to be 1168.
Complex survey design
Stratified cluster random sampling technique was used and a design effect of 1.5 was incorporated, and thus, the final sample size came to 1752. A total of 1782 school students were examined. A complete list of schools was obtained from the concerned government authorities, and schools were stratified based on their geographical location to urban and rural areas. Using proportional allocation technique, the required number of students from each stratum was calculated. Schools were selected using simple random sampling technique without replacement using lottery method from each stratum. A total of 1191 students from 8 rural schools and 593 students from 3urban schools were enrolled in the study. An equal proportion of schools (rural and urban) were approached for the study considering the geographic location spread and strength of students. Among them, 8 schools located and listed under the rural setup and 3 schools in urban setup gave their consent to be a part of the study. The educational department classifies schools as urban and rural based on the area of school location, student strength, availability of modern facilities, and the monthly income of parents. Students from Class 1–10 in the age group of 5–15 years and those present on the day of examination were included in the study.
Data collection tool included the measurement of visual acuity with the use of computerized logMAR charts (NHS trust, UK) and Plusoptix photorefractor (Plusoptix A09, Germany) to measure the objective refraction. The field testing for these instruments have been done earlier and reported elsewhere.,,,,,,,, Students with their presenting visual acuity ≤20/40 in the better eye were considered visually impaired, and a cutoff of ≤20/40 in either eye was used to define abnormal vision. Myopia was considered when the measured objective refraction was more than or equal to −0.75 spherical equivalent diopters in one or both eyes. Participants were categorized as hyperopic when the measured objective refraction was >+2.00 spherical equivalent diopters in one or both eyes, provided that no eye was myopic. Astigmatism was considered to be visually significant if ≥1.00 D. However, as the Plusoptix photorefractor gives an overcorrection of 1.50 D for Indian eyes, the calibration factor was incorporated during analysis and reporting the prevalence. The study period was from August 2012 to May 2013 for which the ethical clearance was obtained from the Institutional Review Board. Permission was received from the Deputy Director of Public Instructions for carrying out the study in various schools. The study was conducted in accordance with the Declaration of Helsinki (1964). Individual permission from the school authorities was also taken before conducting the study.
The data entry and analysis was done using statistical software package, SPSS Statistics for Windows, version 15.0 (SpSS lnc., Chicago, ltt., USA). Prevalence was reported in terms of percentage with 95% CI. Univariate analysis for finding the statistical significance of associations was done with Chi-square test. P < 0.05 was considered as statistically significant.
| Results|| |
A total of 1782 students were enrolled in the study. The mean age of the participants was 10.62 ± 2.72 years within the range of 5–15 years. The distribution of females was found higher (53.58%) as compared to males (46.42%). Family history of refractive error among the siblings was seen among 44.8% of the students from urban schools and 55.2% from rural schools. Among various ocular symptoms reported, watering was found among 6.7% of the students, followed by blurring for vision or difficulty in seeing blackboard letters 5.4% and 2.8% from eyestrain while doing near activities. Occasional pain and frequent redness of the eyes were also observed in about 2.1% and 1.4% of the students, respectively.
The prevalence of visual impairment was found to be 4.32% (95% CI: 3.38%, 5.26%). The prevalence in the urban area was found to be 5.9% while the same in the rural area was 3.6%. This was tested by Chi-square test with 95% class interval reporting. However, no child was found with severe visual impairment and blindness that was denoted by the visual acuity of ≤20/200 in the better eye [Table 1]. The prevalence of abnormal vision that is visual acuity equal to worse than 20/40 in at least one eye was found to be 8.9% (95% CI: 7.48, 10.12).
At the time of examination, 47 (2.6%) of 1782 children were wearing spectacles and around 51.1% of the students who were wearing glasses have good visual acuity of 20/30 or better in both the eyes. A total of 29.8% of students wearing glasses have poor visual acuity of 20/40 or worse in the better eye. Furthermore, of the 77 with visual impairment in both eyes, only 14 (18.2%) were wearing spectacles at the time of examination [Table 2].
|Table 2: Distribution of students wearing glasses across the presenting visual acuity|
Click here to view
The distribution of abnormal vision was seen to be almost equal in the age groups of 5–8 years and 9–12 years that is 9.9% and 9.2%, respectively. There was a slight decrease in the presence of visual impairment (7.5%) in the age group of 13–15 years. However, this variation was not found statistically significant (P = 0.421). Furthermore, there was no difference in reduced vision found across males (8.8%) and females (8.9%). A higher percentage of students (11.3%) from urban schools had abnormal vision as compared to students from rural schools (7.7%). This difference was found to be statistically significant (P = 0.011) [Table 3]. Statistically significant association was also seen with the presence of reduced vision and less participation in sports and extracurricular activities (P = 0.001).
The prevalence of refractive error measured with photorefraction was found to be 12.2% with 95% CI (10.68, 13.72). The prevalence was found higher (15.3%) among urban students as compared to that of students from rural schools (10.7%). Of 216 with the presence of refractive error, 31.9% of children were visually impaired at the time of examination. The prevalence of myopia and hyperopia was 4.0% and 0.8%, respectively, whereas the prevalence of mixed and simple astigmatism was found to be 9.9% with 95% CI (8.51, 11.29).
The prevalence of myopia increased from 1.9% to 5.6% as the age increased from 5 to 15 years, whereas the prevalence of hyperopia decreased from 1.2% to 0.4% as the age increased. The distribution for the presence of either hyperopia or myopia was found to be significantly different across the three different age groups (P = 0.035) [Table 4]. The prevalence of squint was found to be 2.1% with 95% CI (1.43, 2.77). Of 34 students with ocular deviation, 16.7% had visual impairment at the time of examination.
|Table 4: Distribution of myopia and hyperopia across different age group|
Click here to view
| Discussion|| |
This study observed the prevalence of visual impairment as 4.32% with a higher prevalence in the urban schools (5.9%) compared to the rural schools (3.6%). This prevalence rate was comparable to other studies reported from India, where the prevalence ranged between 2.63% and 7.4%. Murthy et al. reported the prevalence of 4.9% from urban population in New Delhi, whereas Dandona et al. reported the prevalence to be 2.6% from the rural part of South India. The study done by Kalikivayi et al. among the schoolchildren in South India reported the prevalence as 5.1% which is comparable to our study. The prevalence of blindness and severe visual impairment reported in other studies was at a lesser rate ranging from 0.20% to 0.93%.,, A study from the Darjeeling district of West Bengal conducted by Bhattacharya et al. noted a prevalence of abnormal visual acuity of <20/30 in either eye in the 7–8 years of age group similar to the findings in our study where the prevalence is seen highest in the age group of 5–8 years (9.9%). The findings from other studies where a comparison of visual impairment prevalence was done between the rural and urban children showed a similar trend seen in our studies; the rate was higher in urban area compared to that in the rural side.
The methodology adopted in this study was robust as computerized logMAR (COMPlog) acuity was used for the mass screening where the printed distant acuity charts are generally used. The COMPlog computerized clinical visual acuity measuring system of thresholding has been tested for its validity against the current gold standard ETDRS chart and is developed as an alternative to it for routine and research use. Randomly generated optotypes to tackle the memorization effect of test takers was one of the significant advantages of COMPlog over conventional charts. The training- and technician-related errors are minimized with the help of standardized and controlled setup available with COMPlog. These facilities would aid to develop a new school eye screening protocol on the COMPlog platform so that schoolteachers, nurses, and other support staff can effectively contribute to the efforts to reduce the burden of avoidable blindness. In addition, the provision to automatically denote the visual acuity in any of the preferred acuity notations (decimal, Snellen fraction More Details, logMAR, etc.) would potentially reduce scoring errors and subsequent false referrals observed generally with traditional acuity charts. The scope of a typical screening protocol in school-going population was limited to visual acuity, refractive error, and squint assessment. On the other hand, the prevalence of ocular diseases such as trachoma (tropical), retinal, or corneal diseases is very low in the Indian population. Thus, we did not include other less common ocular morbidities within the scope of this screening.
The refractive error was measured with photorefraction technique. Several studies have proved its efficacy in the screening for vision anomalies among larger population as it conveniently determines the refractive state together with accommodative response, pupil size, corneal reflexes, and interpupillary distance noninvasively.,,,, Screening of children in schools is most commonly carried out by trained schoolteachers or as a part of vision screening programs conducted by governmental or nongovernmental organizations with the help of eye care professionals. Primary vision screening through schoolteachers is an effective way to reduce the workload of optometrists and ophthalmologists but with a concern of associated errors in assessment and referral. The computerized and user-friendly screening devices (similar to COMPlog and photorefractor used in this study) would clearly enhance the effectiveness of the desired output even in the absence of trained professionals by providing rapid test outcome, lesser errors due to deviation in child concentration, noninvasive nature, and their proved reliability and validity. The feature of quick understanding with a shorter learning curve encourages the schoolteachers and vision technicians to use it at a primary level and decide for referral to an eye care professional without losing time.
The exact underlying causes for the prevalence of visual impairment could not be reported in this study due to lack of time and workforce.
The internal factors such as the screen resolution and luminance level of COMPlog monitor have been preset before the study, but external factors such as level of classroom illumination were not uniform throughout the examination. This might have slightly influenced the accuracy of acuity measurement but within a desirable limit of a screening environment.
| Conclusion|| |
This study reported the prevalence of visual impairment to be 4.32% in the school-going population of Udupi district with higher prevalence from urban schools (15.3%) compared to rural schools (10.7%). Myopia was more prevalent (4.0%) than hyperopia (0.8%).
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Sheeladevi S, Seelam B, Nukella PB, Modi A, Ali R, Keay L. Prevalence of refractive errors in children in India: A systematic review. Clin Exp Optom 2018;101:495-503.
Joshi RS. Screening for visual impairment: Outcome among school children in a rural area of Delhi – Suggestions to improve compliance. Indian J Ophthalmol 2013;61:777.
Resnikoff S, Pascolini D, Mariotti SP, Pokharel GP. Global magnitude of visual impairment caused by uncorrected refractive errors in 2004. Bull World Health Organ 2008;86:63-70.
Sudhan A, Pandey A, Pandey S, Srivastava P, Pandey KP, Jain BK. Effectiveness of using teachers to screen eyes of school-going children in Satna district of Madhya Pradesh, India. Indian J Ophthalmol 2009;57:455-8.
] [Full text]
Limburg H, Kansara HT, d'Souza S. Results of school eye screening of 5.4 million children in India – A five-year follow-up study. Acta Ophthalmol Scand 1999;77:310-4.
Padhye AS, Khandekar R, Dharmadhikari S, Dole K, Gogate P, Deshpande M. Prevalence of uncorrected refractive error and other eye problems among urban and rural school children. Middle East Afr J Ophthalmol 2009;16:69-74.
] [Full text]
Miller JM, Lessin HR. American Academy of Pediatrics Section on Ophthalmology, Committee on Practice and Ambulatory Medicine, American Academy of Ophthalmology, American Association for Pediatric Ophthalmology and Strabismus. Instrument-based pediatric vision screening policy statement. Pediatrics 2012;130:983-6.
Kalikivayi V, Naduvilath TJ, Bansal AK, Dandona L. Visual impairment in school children in Southern India. Indian J Ophthalmol 1997;45:129-34.
] [Full text]
Laidlaw DA, Tailor V, Shah N, Atamian S, Harcourt C. Validation of a computerised logMAR visual acuity measurement system (COMPlog): Comparison with ETDRS and the electronic ETDRS testing algorithm in adults and amblyopic children. Br J Ophthalmol 2008;92:241-4.
Srinivasan K, Ramesh SV, Babu N, Sanker N, Ray A, Karuna SM. Efficacy of a remote based computerised visual acuity measurement. Br J Ophthalmol 2012;96:987-90.
Sreelatha OK, Ramesh SV, Jose J, Devassy M, Srinivasan K. Virtually controlled computerised visual acuity screening in a multilingual Indian population. Rural Remote Health 2014;14:2908.
Hunt OA, Wolffsohn JS, Gilmartin B. Evaluation of the measurement of refractive error by the PowerRefractor: A remote, continuous and binocular measurement system of oculomotor function. Br J Ophthalmol 2003;87:1504-8.
Allen PM, Radhakrishnan H, O'Leary DJ. Repeatability and validity of the PowerRefractor and the nidek AR600-A in an adult population with healthy eyes. Optom Vis Sci 2003;80:245-51.
Choi M, Weiss S, Schaeffel F, Seidemann A, Howland HC, Wilhelm B, et al.
Laboratory, clinical, and kindergarten test of a new eccentric infrared photorefractor (PowerRefractor). Optom Vis Sci 2000;77:537-48.
Matta NS, Singman EL, McCarus C, Matta E, Silbert DI. Screening for amblyogenic risk factors using the PlusoptiX S04 photoscreener on the indigent population of Honduras. Ophthalmology 2010;117:1848-50.
Arthur BW, Riyaz R, Rodriguez S, Wong J. Field testing of the PlusoptiX S04 photoscreener. J AAPOS 2009;13:51-7.
Bharadwaj SR, Sravani NG, Little JA, Narasaiah A, Wong V, Woodburn R, et al.
Empirical variability in the calibration of slope-based eccentric photorefraction. J Opt Soc Am A Opt Image Sci Vis 2013;30:923-31.
Negrel AD, Maul E, Pokharel GP, Zhao J, Ellwein LB. Refractive error study in children: Sampling and measurement methods for a multi-country survey. Am J Ophthalmol 2000;129:421-6.
Murthy GV. Vision testing for refractive errors in schools: 'screening' programmes in schools. Community Eye Health 2000;13:3-5.
Murthy GV, Gupta SK, Ellwein LB, Muñoz SR, Pokharel GP, Sanga L, et al.
Refractive error in children in an urban population in New Delhi. Invest Ophthalmol Vis Sci 2002;43:623-31.
Dandona R, Dandona L, Srinivas M, Sahare P, Narsaiah S, Muñoz SR, et al.
Refractive error in children in a rural population in India. Invest Ophthalmol Vis Sci 2002;43:615-22.
Bhattacharya RN, Shrivastava P, Sadhukhan SK, Lahiri SK, Chakravorty M, Saha JB. P.C. Sen memorial best paper award on rural health practice: A study on visual acuity and Vitamin A deficiency among primary school students in Naxalbari village, Darjeeling district of West Bengal. Indian J Public Health 2004;48:171-80.
Uzma N, Kumar BS, Khaja Mohinuddin Salar BM, Zafar MA, Reddy VD. A comparative clinical survey of the prevalence of refractive errors and eye diseases in urban and rural school children. Can J Ophthalmol 2009;44:328-33.
[Table 1], [Table 2], [Table 3], [Table 4]