Introduction
Digital technology permeates every aspect of life. For example, social media apps, wearable devices and remote public services reshape how people work, socialise, access information and manage their health. Yet despite rapid technological progress, population health in the UK is not improving at the same rate. An analysis from the Health Foundation1 shows that healthy life expectancy has fallen by two years over the past decade. There are even more stark declines in deprived areas. The contrast of technological progress alongside worsening health outcomes raises questions about the implications of digitisation on health. Living in a digital age impacts not only mental health and wellbeing but many aspects of physical health. This includes direct physiological consequences, indirect effects on health behaviours and beliefs, and broader system-level implications. These consequences are not evenly distributed, with variations according to age, digital literacy and socioeconomic status. Understanding their extent is increasingly pressing for public health policy and healthcare delivery.
Physiological effects: Sleep, movement and eye health
Sleep duration and quality
Quality of sleep may be one of the most significant physiological consequences of increasingly digital living. Insufficient sleep is associated with elevated risks of obesity, cardiovascular disease, type 2 diabetes and all-cause mortality,2 making it a significant public health concern. Research consistently shows that digital device use is associated with shorter sleep duration and poorer sleep quality, particularly among children and adolescents.3 Social media appears especially problematic. Due to its interactive nature, it may increase psychological arousal more than passive activities such as television watching, delaying bedtimes and disrupt sleep.3 While the role of blue light from digital devices remains debated in the literature, the nature of digital interaction alone – notifications and stimulating content late at night – can at least in part explain sleep disruption across age groups.4
Physical activity and sedentary behaviour
A growing proportion of daily life now takes place online. Banking, shopping, entertainment, work and socialisation can all occur from a single device, reducing the incidental movement that would previously accompany everyday activities. Sedentary lifestyles are associated with increased risk of obesity, type 2 diabetes, cardiovascular disease and all-cause mortality.5 Among adolescents, highly sedentary behaviour has also been linked to reduced bone density and impaired musculoskeletal development6 – consequences that may compound over time and increase long-term disease burden. The shift to remote and hybrid working has contributed to further reduction in movement among adults, with many spending the majority of their waking hours seated.
Musculoskeletal health
Beyond reduced movement, the design and use of digital devices can create a source of strain on the body. Smartphones and tablets encourage sustained periods of looking down, contributing to neck and shoulder discomfort, sometimes referred to as "tech neck." Desk-based working, and remote work in particular, often involves unergonomic setups and prolonged time spent seated. These patterns are associated with musculoskeletal discomfort affecting the neck, back, shoulders and arms.7
Eye health
Prolonged screen use has been linked to eye strain, characterised by symptoms such as irritation, dryness, headaches and fatigue.8 Of particular concern is the relationship between screen time and myopia progression in children. Excessive screen time may contribute to myopia development, particularly when combined with reduced time spent outdoors, which is independently associated with protection against myopia.9 As children's leisure and educational activities increasingly revolve around screens, myopia prevalence is projected to rise significantly. Analyses estimate that by 2050, half the world's population could be myopic, with high myopia carrying increased risk of serious complications including retinal detachment and glaucoma.10
Indirect effects: Social media, marketing and behaviours
Many important health consequences of living in a digital world occur indirectly, through changes in behaviour, beliefs and social norms. Social media has become a primary source of health information, particularly for younger generations, with 33% of young people reporting seeking health information online.11 Influencers play a significant role, shaping attitudes and behaviours through perceived credibility and parasocial relationships with their audiences.12,13 At the same time, the same platforms that distribute health information operate as commercial environments with a range of consequences for health.
Harmful commercial content
Social media exposes users, often including minors, to the marketing of products harmful to health. Alcohol, tobacco and e-cigarettes are frequently promoted through targeted advertising.14 In some contexts, such as the Philippines, social media marketing has been identified as a key driver of youth vaping culture,15 with emerging evidence pointing to its pulmonary, cardiovascular and neurodevelopmental impacts.16 Alongside this, wellness influencers frequently promote supplements at doses exceeding national recommendations, often without disclosing the potential risks.17 This poses threats to consumer safety through toxicity and drug interactions, particularly among those with polypharmacy.
Nutrition and dietary behaviour
Social media use has been associated with higher consumption of unhealthy foods and less healthy dietary patterns.18 Passive exposure to food marketing and unhealthy food imagery is linked to increased unhealthy food intake,18 while algorithms often favour engaging content that is built on simplification – which can lead to the spread of viral fad diets. Online advice on nutrition from self-proclaimed wellness experts frequently does not meet dietary guidelines. 19 Nutrition information online is frequently low in quality or accuracy, which can drive unbalanced dietary behaviours and lead to weight gain, metabolic disorders and micronutrient deficiencies.20 In turn, this can increase the incidence of non-communicable diseases, including cardiovascular disease, type 2 diabetes and some cancers, contributing to increased healthcare costs and morbidity.20 Additionally, claims that chronic illnesses can be managed through diet alone may discourage adherence to prescribed treatments, with potentially serious consequences for those with complex medical needs.20 Among adolescents, unsafe dieting behaviours driven by social media trends can cause nutritional deficiencies affecting iron and calcium, disrupting normal growth and increasing long-term risk of osteopenia and osteoporosis.20
Misinformation and health beliefs
Digital platforms also shape broader health beliefs in ways that can have broad health consequences at the population level. The spread of anti-vaccination misinformation online during the Covid-19 pandemic was potentially associated with vaccine hesitancy and reduced uptake.21 One trial found that recent exposure to online misinformation about vaccines was associated with a reduction in the intent to take a vaccine in the UK and US,22 while anti-vaccine rhetoric around the HPV vaccine led to significant reductions in uptake in Japan.23 Online misinformation can translate into real-world preventable harms with potential implications for herd immunity on a larger scale.
The potential of social media
Social media is not inherently harmful. It can democratise evidence-based health information, build supportive communities for people living with health conditions, and has been shown to motivate physical activity and support informed dietary choices.24 Public health organisations are increasingly recognising this potential. For example, the European Medicines Agency's #HealthNotHype campaign worked directly with social media content creators to counter misinformation around GLP-1 receptor agonists.25 This illustrates how the same mechanisms that spread misinformation can be used to disseminate evidence-based guidance, especially for hard-to-reach populations or during acute disease outbreaks. Consequently, the challenge for policy may be less about rejecting digital platforms when it comes to health and more about shaping the conditions under which health-related content is created, shared and promoted.
System-level effects: Social connection, healthcare delivery and inequality
The physical health impacts of living in a digital age extend beyond individual choices and behaviours. The consequences can be observed in healthcare systems, social structures and the broader conditions under which health is produced and maintained.
Digital technologies have transformed healthcare delivery in many meaningful ways. Telehealth services, remote monitoring devices and self-management tools can reduce barriers to care, improve convenience and support the management of chronic conditions. For older adults in particular, these technologies may increase autonomy and provide a greater sense of control over long-term management of illnesses.26 Digital technology use for social wellbeing also appears beneficial in reducing social isolation among older adults.26 This may be important for public health, considering the well-established links between loneliness and poorer physical health outcomes – though further research would be needed to establish a clearer association between digital technology use, loneliness and health.
However, the benefits of digital innovation are not distributed equally. Device access and digital literacy varies across populations. In the UK, disparities have been observed in access to technologies such as continuous glucose monitors (CGMs), shaped by age, socioeconomic factors and ethnicity. Afro-Caribbean and South Asian groups face reduced prescribing rates, despite CGMs being a NICE-recommended intervention.27More broadly, those with greater financial resources are better positioned to benefit from emerging health technologies and private healthcare access, while disadvantaged groups face growing barriers. There are also concerns about bias in algorithmic health systems and AI-driven tools producing inaccurate results. In Kenya, an algorithm used to determine healthcare contributions reportedly overestimated the incomes of poorer households while underestimating those of wealthier ones, resulting in disproportionately higher costs for some of the most vulnerable citizens,28 demonstrating how digital systems can reproduce rather than reduce inequality.
Alongside the transformation of healthcare delivery, digital technologies have contributed to the rapid growth of a commercial wellness industry that is increasingly shaping how people manage their health. McKinsey valued the global wellness industry at $2 trillion in 2025.29 In part, this may be driven by social media platforms that connect consumers directly with wellness brands, influencers and health products. Younger generations are disproportionately engaged; they are more likely to seek health information through social media and to purchase wellness products online, while also reporting higher levels of burnout and worse self-rated overall health than older generations.29 This combination can make them an especially receptive audience for individualised health solutions.
A more independent approach to health may also be reflected in people turning to social media or AI for health information. A recent survey found that one in seven adults in the UK had consulted an AI chatbot for health advice rather than seeing a GP, of whom 21% avoided seeking professional support as a result.30 Against a backdrop of long NHS waiting lists and declining public trust in institutions, the wellness industry may in part contribute to a shift towards a more individualistic approach to health – reflected in the marketing of supplements and diagnostic tests on social media. The associated risks include misdiagnosis and incorrect treatment, contributing to potential health consequences and costs to the NHS.
The implications for health inequality are significant. Wellness products, private health technologies and premium digital health services are disproportionately accessible to those with greater financial resources and health and digital literacy, while those most in need face the greatest barriers to access. The result is an environment in which technological innovation in health continues to grow, but the results are unevenly distributed, and in some cases exacerbate existing inequalities. That healthy life expectancy has fallen most sharply in deprived areas of the UK, even as the wellness industry expands, is a stark reminder that commercially motivated health solutions are not a substitute for sustained public health investment.
Recommendations
Digital technology is likely to become increasingly embedded in everyday life, making it essential to mitigate its risks while leveraging its benefits for improving health and care delivery. While individuals have the autonomy to make choices about their own health, broader social structures should make it easier for people to make choices that support health than those with adverse impacts. This includes tackling disparities in access to care, addressing health literacy gaps, countering misinformation and more broadly The below recommendations encompass various stakeholders, including government, public health bodies, online platforms and researchers.
- Counteract the health effects of sedentary, screen-based lifestyles
Governments and local authorities should invest in education and infrastructure that supports active lifestyles and reduces excessive screen time, particularly among children and young people, in order to support healthy development and prevent long-term cumulative disease burden. This could include funding community sports initiatives, active travel infrastructure and embedding daily physical activity into the school curriculum. For working-age adults, employers should prioritise ergonomic work setups and workplace programmes encouraging movement for employee wellbeing, particularly as hybrid and remote working become increasingly normal. Greater awareness of how screen use affects sleep is needed in public health messaging, particularly among parents, given the evidence that young people’s device use at bedtime can significantly disrupt sleep. The case for investment is strong: sedentary behaviour drives long-term costs for NHS services through its contribution to obesity, cardiovascular disease and type 2 diabetes, while excessive screen time among children is associated with myopia.
- Enforce the regulation of online marketing and misinformation
Stronger regulation and platform accountability are needed to limit the spread of harmful health misinformation, particularly around diet, supplements, vaccines and medical treatments. This could include enforceable content standards, algorithmic transparency requirements and financial penalties for platforms that repeatedly amplify incorrect health claims. Restrictions on the marketing of products harmful to health, including high fat, salt and sugar foods, alcohol and e-cigarettes, should be extended across social media platforms. Given the evidence that children and young people are disproportionately exposed to and influenced by harmful content online, stronger age-appropriate protections should be a legislative priority. Government plans such as the under-16 social media ban in the UK must be accompanied by rigorous evaluation to identify and address any unintended consequences.
- Ensure equitable access to digital health tools
Governments should invest in affordable access to devices and digital literacy support to reduce the digital divide, ensuring that telehealth, remote monitoring and health apps are genuinely accessible to older adults, low-income groups and underserved communities. Without this, digital health innovation risks widening rather than closing health inequalities in an increasingly digital world. Equally, clear guardrails are needed for digital health tools to ensure safety and equity. This might include requirements for continuous evaluation of digital interventions and AI-driven tools to be validated across diverse populations to avoid embedding existing biases into clinical decision-making. Improving access will mean more people benefit from digital innovation, making it a priority for both health technology companies and healthcare systems in order to broaden reach and ultimately improve health outcomes.
- Consider integrating digital interventions into public health strategies
Digital platforms offer accessible, cost-effective routes for delivering public health interventions, disseminating evidence-based information, and promoting physical activity and healthy diets. Partnerships with trusted organisations and credible influencers can extend reach to hard-to-engage populations and transform public health responses, especially in acute circumstances such as pandemics. For chronic conditions, digital approaches including apps and self-monitoring tools can support management, reduce the burden on in-person services and improve outcomes – though it is crucial these are designed to meet diverse needs so as not to drive further inequalities. In terms of long-term health behaviour change, social media campaigns should be considered as a tool to promote evidence-based approaches to nutrition and exercise while countering online misinformation.
- Embed evaluation and build the evidence base
Ongoing research and evaluation should be built into digital health initiatives from the start, assessing real-world impact on health behaviours and outcomes, effects on inequalities, and any unintended consequences. Further research is needed to address evidence gaps in several areas, including the long-term physiological effects of childhood screen time, the population-level impact of nutrition misinformation and diet trends, and the effectiveness of digital public health interventions across different demographic groups. Evaluation findings should be shared openly to inform both policy iteration and knowledge globally, given that the health challenges posed by digital living are not unique to the UK.
Iida Kari, July 2026
References
- Mooney, A., Alarilla, A., & Cavallaro, F. (2026). Healthy life expectancy trends in the UK: a watershed moment. The Health Foundation. https://www.health.org.uk/reports-and-analysis/analysis/healthy-life-expectancy-trends-in-the-uk-a-watershed-moment
- Chaput, J.-P. et al. (2020) ‘Sleep duration and health in adults: An overview of systematic reviews’, Applied Physiology, Nutrition, and Metabolism, 45(10 (Suppl. 2)). doi:10.1139/apnm-2020-0034.
- Lund, L., Sølvhøj, I. N., Danielsen, D., & Andersen, S. (2021). Electronic media use and sleep in children and adolescents in western countries: a systematic review. BMC Public Health, 21(1). https://doi.org/10.1186/s12889-021-11640-9
- Bauducco, S., Pillion, M., Bartel, K., Reynolds, C., Kahn, M., & Gradisar, M. (2024). A Bidirectional Model of Sleep and Technology Use: A Theoretical Review of How much, For whom, And which mechanisms. Sleep Medicine Reviews, 76, 101933–101933. https://doi.org/10.1016/j.smrv.2024.101933
- Franssen, W.M.A. et al. (2025) ‘Sedentary behaviour and Cardiometabolic Health: Integrating the potential underlying molecular health aspects’, Metabolism, 170, p. 156320. doi:10.1016/j.metabol.2025.156320.
- Pehlivanturk Kizilkan, M. et al. (2024) ‘Problematic video gaming is negatively associated with bone mineral density in adolescents’, European Journal of Pediatrics, 183(3), pp. 1455–1467. doi:10.1007/s00431-023-05399-x.
- Chim, J. M. Y., & Chen, T. L. (2023). Prediction of Work from Home and Musculoskeletal Discomfort: An Investigation of Ergonomic Factors in Work Arrangements and Home Workstation Setups Using the COVID-19 Experience. International Journal of Environmental Research and Public Health, 20(4), 3050. https://doi.org/10.3390/ijerph20043050
- Kaur, K., Gurnani, B., Nayak, S., Deori, N., Kaur, S., Jethani, J., Singh, D., Agarkar, S., Hussaindeen, J. R., Sukhija, J., & Mishra, D. (2022). Digital Eye Strain- A Comprehensive Review. Ophthalmology and Therapy, 11(5), 1655–1680. https://doi.org/10.1007/s40123-022-00540-9
- Zong, Z., Zhang, Y., Qiao, J., Tian, Y., & Xu, S. (2024). The association between screen time exposure and myopia in children and adolescents: a meta-analysis. BMC Public Health, 24(1). https://doi.org/10.1186/s12889-024-19113-5
- Holden, B. A., Fricke, T. R., Wilson, D. A., Jong, M., Naidoo, K. S., Sankaridurg, P., Wong, T. Y., Naduvilath, T. J., & Resnikoff, S. (2016). Global Prevalence of Myopia and High Myopia and Temporal Trends from 2000 through 2050. Ophthalmology, 123(5), 1036–1042. https://doi.org/10.1016/j.ophtha.2016.01.006
- Edelman Trust Institute (2025) 2025 Edelman Trust Barometer: Special Report - Trust and Health, Edelman. Available at: https://www.edelman.com/trust/2025/trust-barometer/special-report-health (Accessed: 21 June 2026).
- Kaňková, J., Binder, A. and Matthes, J. (2025) ‘Health-Related Communication of Social Media Influencers: A Scoping Review’, Health Communication, 40(7), pp. 1300–1313. doi: 10.1080/10410236.2024.2397268.
- Kirvesmäki, I. (2021) The elements of health and fitness influencers’ credibility on social media. Thesis.
- Jafar, Z. (2023). Social media for public health: Reaping the benefits, mitigating the harms. Health Promotion Perspectives, 13(2), 105–112. https://doi.org/10.34172/hpp.2023.13
- Global Tobacco Control. (2026). Perceptions of E-cigarette Marketing & Packaging Among Filipino Youth | Global Tobacco Control. org. https://www.globaltobaccocontrol.org/en/resources/perceptions-e-cigarette-marketing-packaging-among-filipino-youth
- Overbeek, D. L., Kass, A. P., Chiel, L. E., Boyer, E. W., & Casey, A. M. H. (2020). A review of toxic effects of electronic cigarettes/vaping in adolescents and young adults. Critical Reviews in Toxicology, 50(6), 531–538. https://doi.org/10.1080/10408444.2020.1794443
- Ricke, J.-N. and Seifert, R. (2024) ‘Disinformation on dietary supplements by German influencers on Instagram’, Naunyn-Schmiedeberg’s Archives of Pharmacology, 398(5), pp. 5629–5647. doi:10.1007/s00210-024-03616-4.
- Mar, del, Ruiz-Gamarra, G. E., & Aparicio-Martínez, P. (2026). Social Media Use, Affect, and Dietary Choices Across Age Groups—Insights from the Special Issue “The Impact of Social Media on Eating Behavior.” Nutrients, 18(2), 335–335. https://doi.org/10.3390/nu18020335
- Sabbagh, C. et al.(2020) ‘Analysing credibility of UK Social Media Influencers’ weight-management blogs: A pilot study’, International Journal of Environmental Research and Public Health, 17(23), p. 9022. doi:10.3390/ijerph17239022.
- Alsararatee, H.H. and Yunusa, N.M. (2025) ‘The impact of nutrition misinformation on Public Health and Practice: A review’, British Journal of Nursing, 34(19). doi:10.12968/bjon.2025.0300.
- Pierri, F. et al. (2022) ‘Online misinformation is linked to early COVID-19 vaccination hesitancy and refusal’, Scientific Reports, 12(1). doi:10.1038/s41598-022-10070-w.
- Loomba, S., de Figueiredo, A., Piatek, S. J., de Graaf, K., & Larson, H. J. (2021). Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA. Nature Human Behaviour, 5(5), 337–348. https://doi.org/10.1038/s41562-021-01056-1
- Larson, H. J., Lin, L., & Goble, R. (2022). Vaccines and the social amplification of risk. Risk Analysis, 42(7). https://doi.org/10.1111/risa.13942
- Kaňková, J., Binder, A. and Matthes, J. (2025) ‘Health-Related Communication of Social Media Influencers: A Scoping Review’, Health Communication, 40(7), pp. 1300–1313. doi: 10.1080/10410236.2024.2397268.
- European Medicines Agency. (2025, October 21). EMA partners with content creators to promote safe and responsible use of GLP-1 medicines | European Medicines Agency (EMA). European Medicines Agency (EMA). https://www.ema.europa.eu/en/news/ema-partners-content-creators-promote-safe-responsible-use-glp-1-medicines.
- Sen, K., Prybutok, G., & Prybutok, V. (2022). The use of digital technology for social wellbeing reduces social isolation in older adults: A systematic review. SSM - Population Health, 17(101020), 101020. https://doi.org/10.1016/j.ssmph.2021.101020
- Seidu, S., Tetteh, J., Kunutsor, S., Choudhary, P., Khunti, K., & Ajjan, R. A. (2025). Prescription distribution and inequities in diabetes care: A comparative analysis of continuous glucose monitoring access by diabetes status, ethnicity and socio‐economic factors in England. Diabetic Medicine. https://doi.org/10.1111/dme.70130
- Down, A. (2026, May 4). Flaws in Kenya’s AI-driven health reforms driving up costs for the poorest. The Guardian; The Guardian. https://www.theguardian.com/global-development/2026/may/04/kenya-ai-healthcare-reforms-driving-up-costs-for-poor
- Pione, A., Medalsy, J., Weaver, K., Callaghan, S., & Rickert, S. (2025, May 29). The $2 trillion global wellness market gets a millennial and Gen Z glow-up. McKinsey & Company. https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/future-of-wellness-trends
- Clark, A., Duffy, B., Kim, A., MacAskill, F., May, G., & McCann, H. (2021). The use of AI in UK healthcare Public perceptions and healthcare priorities. https://www.kcl.ac.uk/policy-institute/assets/use-of-ai-in-healthcare.pdf