Association between Childhood Computer Use and Risk of Obesity and Low Vision

Bener, Abdülbari; Al-Mahdi, Huda S.; Al-Nufal, Mohammed; Ali, Awab I; Vachhani, Pankit; Tewfik, Ihab

doi:10.5963/phf0103002

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…The screen time is negatively related to the spherical equivalent. This result is comparable with a prospective cross-sectional study conducted in Qatar that confirmed a positive asso-ciation between obesity and low vision in school children aged 6 -18 years old as a result of the long time spent on watching TV and internet use (24).…”

Section: Discussionsupporting

confidence: 87%

A correlation between body mass index and refractive errors

Rattan¹,

Alrubaie²,

Salih³

et al. 2023

Acta fac medic Naissensis

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Background. Body mass index (BMI) is a person's weight in kilograms (or pounds) divided by the square of height in meters (or feet). Obesity affects a wide spectrum of age groups, from the young to the elderly, and there are several eye diseases related to obesity like diabetic retinopathy, floppy eyelid syndrome, retinal vein occlusion, stroke-related vision loss, age-related macular degeneration, and possibly, refractive errors. Refractive errors (RE) are optical imperfections related to the focusing ability of the eye and are the main cause of visual impairment which may result in missed education and employment opportunities, lower productivity and impaired quality of life. Aim. The study aimed to find an association between body mass index (BMI) and refractive errors. Methodology. A cross-sectional study was designed to involve a representative sample of medical students in Al-Kindy College of medicine, from December 8, 2021 to January 10, 2022. Weight and height were measured. BMI was estimated, and their refractive error was assessed. Results. A total of 400 students participated in the study, of which 191 (47.8%) had refractive errors, whereas 209 (52.2%) were emmetropic. Thirty-seven point eight percent of the participants had BMI > 25. A significant relationship between refractive errors and all BMI groups was found (p < 0.025). Compared to normal weight group, overweight and obese groups, only the underweight group showed a significant relationship with refractive errors, p < 0.006. Conclusion. Myopia is associated with being underweight, hence the link between the two is statistically significant. The severity of this condition, however, is unaffected by body mass index. Myopia was not a concern among students with normal or high body mass index (BMI).

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Section: Discussionsupporting

confidence: 87%

A correlation between body mass index and refractive errors

Rattan¹,

Alrubaie²,

Salih³

et al. 2023

Acta fac medic Naissensis

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show abstract

“…The study found that adolescents with a high IA score were heavier than the others, that they skipped or delayed meals because of being on the internet for prolonged periods of time, that they ate their meals while at the computer, and frequently snacked. According to study results set forth in Turkey by Canan et al, there is a significant correlation between Internet addiction and BMI 28 30 . These results suggest that Internet addiction promotes a sedentary lifestyle and leads to the adoption of unhealthy dietary habits.…”

Section: Discussionmentioning

confidence: 98%

Türk Ergenlerde İnternet Bağımlılığı Ve Erteledikleri Günlük Yaşam Aktiviteleri

Gür¹,

Şişman²,

Şener³

et al. 2016

Kocaeli Üniversitesi Sağlık Bilimleri Dergisi

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“…The brief Patients Health Questionnaire-4 (PHQ-4) developed and validated by Kroenke, Spitzer, Williams, & Löwe in 2009 [45] where response to first two questions help assess anxiety (GAD-2) and the other two the depression (PHQ-2) levels in an individual. This is based on the 4-point Likert type scale where scores are rated as normal (0-2), mild (3)(4)(5), moderate (6-8) and severe (9)(10)(11)(12). Total score of ≥3 for the first 2 questions suggests anxiety while a score of ≥3 for the last two questions suggests depression.…”

Section: Methodsmentioning

confidence: 99%

“…Across the USA and EU region, prevalence rates of this addiction varied between 1.5-8.2% [3], few other reports following IAT suggested this range from 6-18.5% [4]. The addiction defining criteria majorly depends upon the time invested on the internet [5,6] while other indistinctive criteria defined are individual/behavioral problems [7].…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Internet Addiction Disorder and its Association with Anxiety and Depression in Young Indian Adults: A Cross Sectional Study

Pandey

2024

TIJAR

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The phenomenon of involuntary engagement with internet devices, accompanied by a sense of emptiness in their absence, characterizes internet addiction disorder. A comprehensive meta-analysis spanning 80 studies worldwide from 1996 to 2012, involving 89,281 participants across 31 countries, revealed a 6% prevalence of this disorder among young individuals globally. A separate study funded by the Indian Council of Medical Research (ICMR) investigated 2,755 participants aged 18-65 in India, finding a prevalence rate of 1.3% for internet addiction. Notably, this disorder has not yet been recognized as Internet Addiction Disorder (IAD) in the Diagnostic and Statistical Manual of Mental Disorders (DSM). Numerous studies have examined the prevalence of internet addiction in the Indian population. This current study aimed to assess the prevalence, impact, and available treatment options for internet addiction among Indian adults. Utilizing a cross-sectional, close-ended online survey questionnaire distributed among the general public and experts, a total of 303 responses were collected. The findings revealed that 33.3% of Indian adults were addicted to the internet, with varying degrees of severity: severely (1.7%), moderately (10.2%), and mildly (20.8%) addicted. Notably, most severely addicted individuals (80%) fell within the 26-35 years age range. Male participants exhibited a higher prevalence of internet addiction compared to females (57.1% vs. 42.9%), with males also displaying a greater propensity for addiction (71.9% vs. 28.1%). Further analysis indicated that 11.2% of addicted individuals experienced symptoms of anxiety and/or depression, with males affected at a rate 50% higher than females.

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Association between Childhood Computer Use and Risk of Obesity and Low Vision

Cited by 7 publications

References 25 publications

A correlation between body mass index and refractive errors

A correlation between body mass index and refractive errors

Türk Ergenlerde İnternet Bağımlılığı Ve Erteledikleri Günlük Yaşam Aktiviteleri

Assessment of the Internet Addiction Disorder and its Association with Anxiety and Depression in Young Indian Adults: A Cross Sectional Study

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