Abstract
Little is known about the distribution of eye and vision conditions among school children in Qatar. The aim of the study was to examine the effects of excessive internet use and television viewing on low vision and its prevalence with socio-demographic characteristics. This is a cross-sectional study which was carried out in the public and private schools of the Ministry of Education and Higher Education of the State of Qatar from September 2009 to April 2010. A total of 3200 students aged 6-18 years were invited to take part of whom 2586 (80.8%) agreed. A questionnaire, that included questions about socio-demographic factors, internet use, and television viewing and computer games, co-morbid factors, and family history and vision assessment, was designed to collect information from the students. This was distributed by the school authorities. Of the school children studied (n=2586), 52.8% were girls and 47.2% boys. The overall prevalence of low vision was 15.2%. The prevalence of low vision was significantly higher in the age group 6-10 years (17.1%; P=0.05). Low vision was more prevalent among television viewers (17.2%) than in infrequent viewers (14.0%). The proportion of children wearing glasses was higher in frequent internet users and television viewers (21.3%). Also, low vision without aid was higher in frequent viewers. The study findings revealed a greater prevalence of low vision among frequent internet users and television viewers. The proportion of children wearing glasses was higher among frequent viewers. The prevalence of low vision decreased with increasing age.
Key words: children, vision, internet, television, Qatar
Introduction
Visual impairment is a global public health problem. Children with low vision may suffer delayed developmental growth and education problems.1 Over 285 million people in the world are visually impaired, of whom 39 million are blind and 246 million have moderate to severe visual impairment.2 The World Health Organization3 reported that every minute somewhere in the world, a child goes blind. For most of them, there is no prospect of curative treatment of the underlying pathology. Vision plays a vital role in a child’s interpretation of the world. Visual impairment has a serious impact on a child’s physical and emotional development.4 However, visual function changes with age and most changes are amenable to correction with glasses and do not affect daily activities.
Controlling the problem of visual impairment is a priority for every country because failure to detect visual impairment early may have a permanent effect on long-term vision outcomes, education achievement and self esteem. Therefore, the American Academy of Ophthalmology and the American Association of Paediatric Ophthalmology and Strabismus has recommended that children be examined for eye problems at four stages: as newborns in the nursery, at 6 months, at 3 years, and 5 years of age and older.5
A revolution in information technology (IT) is rapidly taking place worldwide. Across all generations, children and adults are spending an increasing amount of time in front of the computer and on the internet. Television and the internet are now recognized as a powerful source of information for people of all ages. For many children, internet use and television viewing are an inevitable part of their daily lives. Sutherland6 reported that along with the benefits of television and internet, there are also various factors that can have a harmful impact upon children. It was reported that daily television viewing and internet use for long hours at a time will damage children’s eyesight from eye strain.
Very few studies have been published on the prevalence of visual impairment in the Arabian population, but no surveys have been carried out to determine the adverse effects of internet use and television viewing on visual impairment of children. Therefore, this study aimed to determine the effects of excessive use of the internet and television viewing on children’s low vision and its prevalence.
Materials and Methods
This is a cross-sectional study including schoolchildren and adolescents aged 6-18 years, studying at state and private primary, preparatory and secondary schools in the State of Qatar. A multi-stage stratified random sampling technique was used and the schoolchildren were randomly selected to take part. The list of names of schools in urban and semi-urban areas was obtained from the Supreme Council for Education and Higher Education. A total of 151,050 students are studying in primary, preparatory and secondary schools. There are 299 schools, of which 152 are for boys and 147 for girls, located in 21 different districts. During the first stage, one school from each of these 5 districts was selected randomly, thus overcoming the so-called cluster effect. Similarly, the classrooms and schoolchildren were selected in the second and third stages of the study using the same simple random sampling procedure. This resulted in the final selection of 3200 students who were a true random sample of the study population; this is 2.1% of the total student population in Qatar.
Data collection took place from September 2009 to April 2010. Of the 3200 students approached, 2586 students participated in the study and completed the questionnaires with a response rate of 80.8%. The survey instrument was tested and validated on 125 students.
The questionnaire was in three parts. The first part included the socio-demographic details of the students, the second with questions concerning internet use, television viewing and computer games, the third with co-morbid factors and family history of the children, and the last part with vision assessment made by nurses. The children studied were classified into frequent and infrequent viewers of TV/internet. The questions concerning the frequent TV/internet viewers were: i) How often do you watch TV/use the internet? with three possible answers, daily, week days and weekends; and ii) How many hours do you watch TV/internet every day? From these two questions, frequent TV/internet viewers were classified as children watching television or internet for more than three hours a day.
The International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) was used to define visual impairment categories. Eye examination was carried out using a Slit Lamp, (Topcon) and visual acuity with tumbling E letters at a distance of 20 feet (6 meters). The participants’ visual acuity without correction was measured separately for each eye. Visual acuity was then tested with best spectacle correction. Visual acuity was recorded as the smallest line in which the patient could read the four letters correctly. If the person was unable to read the largest E letters in the chart (20/400 E letters) at 20 feet (6 meters), then finger counting was performed at 1 meter or more. Low vision was defined as having best corrected vision in the good eye worse than 20/60, lower than 20/400, and worse than 20/400, respectively.
Student’s t-test was used to verify the significance of differences between mean values of two continuous variables and confirmed by non-parametric Mann-Whitney test. c2 and Fisher’s exact tests (two-tailed) were performed to test for differences in proportions of categorical variables between two or more groups. One-way analysis of variance (ANOVA) was used to compare several group means and to determine the presence of significant differences between group means. P<0.05 was considered significant.
Results
Table 1 shows the socio-demographic characteristics of the school children studied according to gender. Most of the participants were in the 6-10 year old age group (37.6%) and girls (52.8%) outnumbered boys (47.2%). A significant difference was observed between both genders in terms of their nationality (P<0.001), age group (P<0.001), academic performance (P=0.008), father’s occupation (P<0.001) and family income (P=0.032).
Table 1.
Socio-demographic characteristics of the studied children according to gender (n=2586).
| Variable | Total n=2586 n(%) |
Boys n=1220 n(%) |
Girls n=1366 n(%) |
P |
|---|---|---|---|---|
| Nationality | ||||
| Qatari | 1854 (71.7) | 833 (68.3) | 1021 (74.7) | <0.001 |
| Non-Qatari | 732 (28.3) | 387 (31.7) | 345 (25.3) | |
| Age group | ||||
| 6-10 | 973 (37.6) | 510 (41.8) | 463 (33.9) | <0.001 |
| 11-14 | 870 (33.6) | 435 (35.7) | 435 (31.8) | |
| 15-18 | 743 (28.7) | 275 (22.5) | 468 (34.3) | |
| Academic performance | ||||
| Very good | 804 (31.1) | 342 (28.0) | 462 (33.8) | 0.008 |
| Good | 1040 (40.2) | 507 (41.6) | 533 (39.0) | |
| Average | 614 (23.7) | 301 (24.7) | 313 (22.9) | |
| Poor | 128 (4.9) | 70 (5.7) | 58 (4.2) | |
| Father’s education | ||||
| Illiterate | 138 (5.3) | 67 (5.5) | 71 (5.2) | 0.528 |
| Primary | 360 (13.9) | 181 (14.8) | 179 (13.1) | |
| Intermediate | 538 (20.8) | 262 (21.5) | 276 (20.2) | |
| Secondary | 745 (28.8) | 340 (27.9) | 405 (29.6) | |
| University | 805 (31.1) | 370 (30.3) | 435 (31.8) | |
| Father’s occupation | ||||
| Not working | 227 (8.8) | 116 (9.5) | 111 (8.1) | <0.001 |
| Sedentary/professional | 835 (32.3) | 434 (35.6) | 401 (29.4) | |
| Manual | 310 (12.0) | 117 (9.6) | 193 (14.1) | |
| Business man | 647 (25.0) | 283 (23.2) | 364 (26.6) | |
| Government officer | 567 (21.9) | 270 (22.1) | 297 (21.7) | |
| Mother’s education | ||||
| Illiterate | 449 (17.4) | 229 (18.8) | 220 (16.1) | 0.496 |
| Primary | 471 (18.2) | 221 (18.1) | 250 (18.3) | |
| Intermediate | 628 (24.3) | 287 (23.5) | 341 (25.0) | |
| Secondary | 610 (23.6) | 283 (23.2) | 327 (23.9) | |
| University | 428 (16.6) | 200 (16.4) | 228 (16.7) | |
| Mother’s occupation | ||||
| Sedentary/professional | 562 (21.7) | 259 (21.2) | 303 (22.2) | 0.620 |
| Manual | 556 (21.5) | 258 (21.1) | 298 (21.8) | |
| Business man | 521 (20.1) | 240 (19.7) | 281 (20.6) | |
| Housewife | 947 (36.6) | 463 (38.0) | 484 (35.4) | |
| Family income | ||||
| <5000 | 19 (0.7) | 10 (0.8) | 9 (0.7) | 0.032 |
| 5000 – 9999 | 834 (32.3) | 413 (33.9) | 421 (30.8) | |
| 10,000 – 14,999 | 988 (38.2) | 479 (39.3) | 509 (37.3) | |
| >15,000 | 745 (28.8) | 318 (26.1) | 427 (31.3) | |
| Do you have the following at home?* | ||||
| Computer | 2046 (79.1) | 944 (77.4) | 1102 (80.7) | 0.040 |
| Television | 2105 (81.4) | 972 (79.7) | 1133 (82.9) | 0.033 |
| Internet | 2147 (83.0) | 994 (81.5) | 1153 (84.4) | 0.047 |
*Multiple options therefore the percentage does not add to 100%.
Table 2 examines the socio-demographic characteristics of the children studied with low vision according to gender. The overall prevalence of low vision in children was 15.2%. The mean age±SD of boys with low vision was 11.5±4.0 and of girls 12.3±4.1 (range 6-18) years, with a significant difference between boys and girls (P=0.04). The proportion of children with low vision was significantly higher in the 6-10 year old age group (42.2%; P=0.006). Nearly half of the studied children with low vision were excessive internet users and TV viewers (50.6%). A good proportion of the parents of the children were in a consanguineous marriage (34.6%).
Table 2.
Socio-demographic characteristics of the studied children with low vision according to gender (n=393).
| Variable | Total n=393 n(%) |
Boys n=177 n(%) |
Girls n=216 n(%) |
P |
|---|---|---|---|---|
| Age group±SD | 11.9±4.1 | 11.5±4.0 | 12.3±4.1 | 0.044 |
| Age group | 0.006 | |||
| 6-10 | 166 (42.2) | 90 (50.8) | 76 (35.2) | |
| 11-14 | 132 (33.6) | 46 (27.1) | 84 (38.9) | |
| 15-18 | 95 (24.2) | 41 (22.0) | 56 (25.9) | |
| Nationality | ||||
| Qatari | 279 (71.0) | 118 (66.7) | 161 (74.5) | 0.087 |
| Non-Qatari | 114 (29.0) | 59 (33.3) | 55 (25.5) | |
| Rank of student in school exam | ||||
| Very good | 106 (27.0) | 39 (22.0) | 67 (31.0) | 0.177 |
| Good | 174 (44.3) | 80 (45.2) | 94 (43.5) | |
| Average | 98 (24.9) | 51 (28.8) | 47 (21.8) | |
| Poor | 15 (3.8) | 7 (4.0) | 8 (3.7) | |
| Father’s education | ||||
| Illiterate | 10 (2.5) | 6 (3.4) | 4 (1.9) | 0.865 |
| Primary | 48 (12.2) | 23 (13.0) | 25 (11.6) | |
| Intermediate | 64 (16.3) | 29 (16.4) | 35 (16.2) | |
| Secondary | 130 (33.1) | 56 (31.6) | 74 (34.3) | |
| University | 141 (35.9) | 63 (35.6) | 78 (36.1) | |
| Father’s occupation | ||||
| Not working | 31 (7.9) | 17 (9.6) | 14 (6.5) | 0.001 |
| Sedentary/professional | 142 (36.1) | 79 (44.6) | 63 (29.2) | |
| Manual | 54 (13.7) | 17 (9.6) | 37 (17.1) | |
| Business man | 89 (22.6) | 28 (15.8) | 61 (28.2) | |
| Government officer | 77 (19.6) | 36 (20.3) | 41 (19.0) | |
| Mother’s education | ||||
| Illiterate | 71 (18.1) | 31 (17.5) | 40 (18.5) | 0.305 |
| Primary | 80 (20.4) | 31 (17.5) | 49 (22.7) | |
| Intermediate | 89 (22.6) | 36 (20.3) | 53 (24.5) | |
| Secondary | 102 (26.0) | 52 (29.4) | 50 (23.1) | |
| University | 51 (13.0) | 27 (15.3) | 24 (11.1) | |
| Mother’s occupation | ||||
| Sedentary/professional | 87 (22.1) | 37 (20.9) | 50 (23.1) | 0.278 |
| Manual | 86 (21.9) | 32 (18.1) | 54 (25.0) | |
| Business | 89 (22.6) | 43 (24.3) | 46 (21.3) | |
| Housewife | 131 (33.3) | 65 (36.7) | 66 (30.6) | |
| Family income | ||||
| < 5000 | 3 (0.8) | 1 (0.6) | 2 (0.9) | 0.021 |
| 5000-9999 | 138 (35.1) | 72 (40.7) | 66 (30.6) | |
| 10,000 – 14,999 | 153 (38.9) | 72 (40.7) | 81 (37.5) | |
| >15,000 | 99 (25.2) | 32 (18.1) | 67 (31.0) | |
| Television viewing/internet use | ||||
| Always | 199 (50.6) | 79 (44.6) | 120 (55.6) | 0.40 |
| Seldom | 194 (49.4) | 98 (55.4) | 96 (44.4) | |
| Watching television/internet (h/day) | ||||
| <3 h | 293 (74.6) | 138 (78.0) | 155 (71.8) | 0.160 |
| ≥3 h | 100 (25.4) | 39 (22.0) | 61 (28.2) | |
| Consanguinity | ||||
| Yes | 136 (34.6) | 56 (31.6) | 80 (37.0) | 0.263 |
| No | 257 (65.4) | 121 (68.4) | 136 (63.0) | |
Table 3 compares the low vision and co-morbid factors between frequent and infrequent internet users and TV viewers. Of the total number of children studied, 36.8% were frequent TV/internet viewers. Low vision was significantly more prevalent among excessive internet users and television viewers (17.2%) than among infrequent viewers (14.0%) (P=0.03). The proportion of children wearing glasses among the frequent viewers (21.3%) was greater than among infrequent viewers (18.1%). Low vision without aid was higher in frequent viewers (8.6%). A significant difference was observed in co-morbid factors between frequent and infrequent television/internet viewers; double vision (P=0.009), painful eyes (P<0.001), tired eyes (P=0.042) and hearing (P=0.01).
Table 3.
Comparison of low vision and co-morbid factors between frequent and infrequent internet users and television viewers (n=2586).
| Variable | Internet/TV viewers | P | |
|---|---|---|---|
| Frequent viewers n=952 n(%) |
Infrequent viewers n=1634 n(%) |
||
| Low vision (both eyes) | |||
| Normal vision | 788 (82.8) | 1405 (86.0) | 0.028 |
| Low vision | 164 (17.2) | 229 (14.0) | |
| Vision | |||
| With glasses | 203 (21.3) | 295 (18.1) | 0.033 |
| Unaided | 667 (70.1) | 1222 (74.8) | |
| Low vision without aid | 82 (8.6) | 117 (7.2) | |
| Co-morbid factors | |||
| Headaches | 328 (34.5) | 569 (34.8) | 0.849 |
| Blurred vision | 302 (31.7) | 519 (31.8) | 0.983 |
| Double vision | 63 (6.6) | 157 (9.6) | 0.009 |
| Eyes hurt | 119 (12.5) | 119 (7.3) | <0.001 |
| Eye tired | 151 (15.9) | 212 (13.0) | 0.042 |
| Dizziness | 220 (23.1) | 359 (22.0) | 0.503 |
| Hearing | 190 (20.0) | 398 (24.4) | 0.010 |
Table 4 shows the prevalence of low vision among school children according to demographic characteristics and family history. The overall prevalence of low vision was higher in girls (15.8%) compared to boys (14.5%). Low vision was significantly more prevalent in children in the 6-10 year old age group (17.1%; P=0.05), and also in children with a family history of hypertension (22.6%; P<0.001) and diabetes mellitus (17.5%; P=0.04).
Table 4.
Prevalence of low vision among school children according to demographic characteristics and family history.
| Variable | No. examined n=2586 |
Children with low vision n=393 |
P | |
|---|---|---|---|---|
| n | % | |||
| Gender | ||||
| Male | 1220 | 177 | 14.5 | 0.356 |
| Female | 1366 | 216 | 15.8 | |
| Age Group | ||||
| 6-10 | 973 | 166 | 17.1 | 0.050 |
| 11-14 | 870 | 132 | 15.2 | |
| 15-18 | 743 | 95 | 12.8 | |
| Parents consanguinity | ||||
| Yes | 940 | 136 | 14.5 | 0.435 |
| No | 1646 | 257 | 15.6 | |
| Family history | ||||
| Diabetes | 773 | 135 | 17.5 | 0.036 |
| Glaucoma | 542 | 70 | 17.8 | 0.096 |
| High blood pressure | 473 | 107 | 22.6 | <0.001 |
| Amblyopic (lazy eye) | 196 | 22 | 11.2 | 0.107 |
| Epilepsy or seizures | 132 | 14 | 10.6 | 0.131 |
| Multiple scleroses | 161 | 20 | 12.5 | 0.311 |
| Other chronic disease | 15 | 2 | 13.3 | 0.279 |
| Frequent Internet/TV viewers | ||||
| Frequent | 952 | 164 | 17.2 | 0.028 |
| Infrequent | 1634 | 229 | 14.0 | |
Discussion
The burden of visual impairment is not distributed uniformly throughout the world; the least developed regions carry the largest burden. Low vision and blindness are important public health problems.7 This is the first survey In Qatar to examine the impact of internet use and television viewing on eyesight and the prevalence of low vision. The present study revealed that the overall prevalence of low vision in children (15.2%) was similar to other studies which reported 15% of prevalence of low vision among 4-15 year old children.8,9 Some studies demonstrated that 5-10% of preschool children have visual impairment and 13% of children will have some defect in visual acuity by the age of seven years.10,11 In the US,12 a lower rate was reported; here approximately 6.8% of children under the age of 18 years have a diagnosed eye and vision condition ranging from 8.6% in 1996 to 5.8% in 2001. The low vision rate in our study was higher than the rate in the US, a developed country. However, higher rates of frequency (6.4-22.3%) have also been reported in other studies.13 Consistent with another study by Sutherland,6 the average age of the studied children with low vision was 11.9 years. An explanation for this difference in prevalence could be due to the different policy implications for modifying or improving existing school services.
In our survey, the prevalence of low vision significantly declined with advancing age (P=0.006); this contradicts the results of other studies.14,15 A study by Peckham16 reported that 13% of children will have some defect in visual acuity by the age of seven years. In contrast, a high prevalence rate was observed in the children in our study in the 6-10 year age group (17.1%); this then declined with increasing age: 15.2% in the 11-14 and 12.8% in the 15-18 year age groups, respectively. This shows that screening for eye diseases in school children has been carried out as part of routine care by the school health department in the State of Qatar. In the current study, the prevalence of low vision was very high in the age group 6-7 years. A few studies17,18 have reported that both prematurity and low birth weight have been associated with an increased incidence of poor vision in later years. A review of the vision screening of children in Iran19 also reported a successful yield of 1:21 from screening and useful exercise. These study findings show that screening and surveillance for visual defects throughout childhood will help the early detection and treatment of relevant ophthalmic disorders.
All over the world, there are difference in distribution according to gender. Our results are consistent with previous studies20,21 that reported that girls have significantly higher risks of having low vision than boys. Visual impairment was associated with the level of education of the parents. The proportion of the study group with low vision whose fathers had a university degree was 35.9%, but was lower for the same level in their mothers (13%). Also, low vision was higher in children of working women (66.7%). A similar result was found in a study by Unsal et al.5 who reported that visual impairment was associated with gender, educational status of parents and working women. Many studies5,22 have reported that there were significant relationships between the parents’ educational and occupational status and visual acuity. Another important finding noted in the present survey is that parental consanguinity was present in almost one-third of the children with low vision (34.6%); this is similar to reports from a study carried out in India.23
In recent years, the prevalence of internet use and television viewing has increased remarkably worldwide. Medical journals have not given much space to discussion of the possible adverse effects of excessive internet use and television viewing on the physical, social and mental development of children.24-29 The present study has been carried out to determine whether or not internet use and television viewing impairs children’s eyesight and the study findings revealed that the internet/television has an enormous influence on school children. Our results showed that low vision was more prevalent in frequent internet/television viewers (17.2%). Furthermore, half of the children with low vision were always watching television (50.6%). It is evident from these results that internet use and television viewing as practiced by school children today causes eye strain sufficient to affect their eyesight. The study also found a higher proportion of children wearing glasses (21.2%) among the frequent internet/television viewers than among the non-viewers (18.1%). The current study shows that internet use and television viewing does affect children’s vision and health. Furthermore, there is indirect evidence to suggest that there is an association between low vision and internet use and television viewing. This is consistent with the previous reported studies.24-29 Recently, researchers have been turning their attention to the question of the possible effects of television on children.
Conclusions
The study findings revealed that the prevalence of low vision decreased with increasing age. Girls had a higher prevalence of low vision compared to boys. Low vision was more prevalent among frequent internet and television viewers, and the proportion of children wearing glasses was higher among frequent viewers. It is evident from these results that there is an association between internet use and television viewing and low vision. Health education programs need to raise public awareness of this association in order to facilitate the prevention and control of low vision.
Acknowledgements
This research project was generously supported and funded by the Qatar National Research Fund- QNRF UREP 06-022-3-010. The authors would like to thank the Hamad Medical Corporation for their support and ethical approval (HMC RP # 9121/09).
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