The Burrow
Feb 10, 2026
Due to most tasks being carried out online, global screen time statistics have climbed rapidly over the past decade. From laptops in the office to smartphones on the sofa, much of modern life now happens through a screen. Figures show that many people spend several hours a day on digital devices, whether for work, entertainment or socialising. As a result, conversations around vision health, eye strain and longer-term visual wellbeing are becoming more common.
Extended exposure to screens is often linked with symptoms such as tired eyes, dryness and occasional blurred vision. While screens are now a normal part of daily life, researchers and public health bodies increasingly study how usage patterns may relate to overall vision health. However, studying wider data can help to build a clearer, evidence-based picture of where risks may be emerging, without assuming that screens alone are the cause.
To explore these patterns, the health insurance comparison experts at Compare the Market Australia has developed the Screen Time & Vision Health Index. The index compares screen time by country and screen time by US states, analysing average device use alongside vision-related indicators and eye health behaviours. By bringing these data points together, our campaign highlights where highly digital lifestyles may be placing greater demands on people’s eyes.
We used two data indexes to create our rankings. The country index ranks 35 nations by combining normalised data on average daily screen use, prevalence of moderate to severe visual impairment (MSVI) and prevalence of blindness to produce a score out of 100. The US state index uses the same scoring approach but replaces medical prevalence with search behaviour for eye-related symptoms and corrective vision, highlighting patterns in both exposure and awareness.
Let’s begin by looking at the countries that come out on top in our rankings for poor screen time and vision health outcomes.
Türkiye ranks first in the index, with average daily screen use of 7h and 13m, the ninth highest of global screen time by country comparisons. However, the country’s prevalence of moderate to severe visual impairment (MSVI) (6.37%) and blindness (1.00%) are the highest in the index.
South Africa records the highest device use figures at 9h and 37m per day. It also has the sixth highest rate of MSVI (2.45%) and the second-highest blindness rate (0.85%) relative to the other countries in the wider dataset.
Colombia reports average daily screen time of 8h and 44m, the third highest in the dataset. Its MSVI prevalence stands and blindness are both the fifth highest, at 2.61% and 0.54% respectively.
Indonesia’s average of 7h and 22m is eighth. MSVI prevalence is second in the index at 3.92% and blindness is fourth at 0.67%.
Thailand shows daily screen exposure of 7h and 54m, slightly higher than several peers. It records MSVI at 3.13% and blindness at 0.51%, with the latter being among the lower figures in the dataset.
While higher exposure does not automatically align with worse outcomes, the dataset shows eye strain remains a relevant consideration in highly digital lifestyles.
Countries at the lower end of the index show that less device use does not automatically translate into stronger vision health outcomes. In the bottom five are Japan (1.75), Denmark (10.23), Greece (11.85), Belgium (12.39) and France (score of 12.58). Between them, average daily use ranges from roughly 4 to 5.5 hours, which is relatively low by global screen time by country standards. Consequently, these countries also record some of the lowest levels of visual impairment.
Japan is a particularly notable example. It has the lowest average exposure in the dataset (4h and 9m), the 12th lowest MSVI at 1.09%, and the fourth lowest rate of blindness at 0.11%.
Australia sits mid-table in our Screen Time & Vision Health Index, ranking 18th overall with a total score of 21.01. Australians average 6h and 5m of daily device use, the 11th highest. In terms of vision health, Australia records a 1.3% prevalence of moderate to severe visual impairment, the 16th highest in the list, and 0.13% prevalence of blindness, the 17th highest in the index.
These screen time statistics suggest that Australia has a fairly balanced profile, where moderate screen exposure aligns with comparatively low impairment rates. While this does not remove the potential for eye strain, it indicates that Australia performs steadily rather than at either extreme of the index.
Overall, the data positions Australia as a country with manageable screen habits and solid vision-related outcomes compared with many global peers.
Alongside the global rankings, we also analysed screen time in US states to see how digital habits may be linking to eye-related concerns at a local level. Unlike the country index, which uses medical prevalence data, the US index looks at search behaviour, including symptom-related and corrective vision queries per 100,000 people. This offers insight into awareness, concern and potential experiences linked to eye strain and broader vision health, rather than diagnosed conditions. Below are the five states that rank highest on this search-based index.
Arizona tops the list, with residents averaging 8h and 50m of daily device use. The state records 434.7 symptom-related searches and 819.7 corrective vision searches per 100,000 people.
These screen time statistics point to both high exposure and strong search interest in vision correction. This may indicate notable awareness of eye strain and active steps towards managing vision health.
Washington also shows very high daily use at 8h and 17m, with 453.4 symptom searches and 829.6 corrective vision searches per 100,000 residents.
This combination suggests sustained digital exposure alongside frequent information-seeking around eye issues.
New York averages 6h and 13m of daily screen time, which is the lowest in the top five. However, it stands out for extremely high search activity: 650.8 symptom searches and 1,164.1 corrective vision searches per 100,000.
This gap between exposure and searches suggests elevated concern or awareness around vision health. High engagement with corrective options may reflect efforts to address eye strain or maintain visual comfort.
Texans record 7h and 20m of daily screen use, placing them above the national midpoint. The state has 466.9 symptom searches and 967.4 corrective vision searches per 100k.
These figures align moderate-high exposure with strong corrective search behaviour. Within the wider screen time in US states dataset, this can signal attention to managing digital eye demands.
Maryland residents average 7h and 14m of daily device time. The state logs 539.2 symptom searches and 834.7 corrective vision searches per 100,000 of the population.
Relatively high symptom search rates suggest noticeable public interest in eye discomfort and care. In terms of vision health, this pattern may indicate awareness of screen-related strain and a willingness to seek solutions.
Across the screen time in US states index, some clear regional patterns emerge. Western and southern states tend to report higher average daily device use, reflecting both lifestyle and work patterns that are closely tied to digital connectivity. At the same time, densely populated states often generate higher volumes of symptom-related and corrective vision searches, which can influence their overall ranking. This highlights how screen time statistics interact not just with behaviour, but with how actively people seek information about vision health and eye strain.
The data also suggests a difference between awareness and prevention. Searches about symptoms (such as sore or tired eyes) may point to people noticing discomfort, while corrective vision queries (like eye tests or glasses) suggest action-oriented steps. States that score highly often show strength in both, indicating not just concern but also follow-up actions. This reinforces that search behaviour can reflect engagement with eye care, not only exposure to screens.
At the lower end of the rankings, states such as Kansas, Maine, Idaho, Mississippi and Iowa record lower search volumes overall. On the surface, this might look positive, but lower search activity doesn’t necessarily mean fewer issues. In some cases, it may indicate reduced awareness of eye strain, fewer routine eye checks or more limited access to eye care services. As a result, lower visibility in search data should be interpreted cautiously when considering overall vision health.
Steven Spicer, Executive General Manager of Health, Life and Energy at Compare the Market, says:
“Digital devices are a normal part of modern life, but our research shows why it’s important to stay mindful of your vision health and not ignore early signs of eye strain. Devices nowadays often have adjustable settings for brightness and types of light to make them softer on your eyes at night, but it’s still important to be proactive with your eye health.
“Take regular breaks, use night mode or blue light filter settings on devices to adjust, and be sure to see an optometrist for eye checks if you need.
“Health insurance extras cover can help you to manage the cost of eye care and related services, glasses and contact lenses, making you better prepared to look after your long-term eye health.”
The first dataset ranks 35 countries based on both their screen time and vision health, by using three key factors. Each factor’s data was collected and normalised to a score between 0 and 1. If data was missing, a score of 0 was given. These scores were then combined to give each country a total score out of 100, and countries were ranked from highest to lowest.
The factors used are as follows:
The factors were indexed as follows:
The factors were weighted as follows:
All data is correct as of 20/01/26. The ranking data shown is a compilation of multiple data sources and may not be representative of real life. All data is accurate with regards to the sources provided.
The second dataset ranks US states based on both their screen time and vision health, by using three key factors. Each factor’s data was collected and normalised to a score between 0 and 1. If data was missing, a score of 0 was given. These scores were then combined to give each state a total score out of 100, and states were ranked from highest to lowest.
The factors used are as follows:
The factors were indexed as follows:
The factors were weighted as follows:
All data is correct as of 20/01/26. The ranking data shown is a compilation of multiple data sources and may not be representative of real life. All data is accurate with regards to the sources provided.