Abstract

There are many methods in the field of preventive medicine which consider social determinants of health to help prevent chronic illness more effectively and equitably. By utilising artificial intelligence (AI) and digital systems, we can strengthen the world of preventive medicine in ways traditional methods cannot. Furthermore, the distribution of vaccines based on social determinants of health is negatively impacting lower-income countries. The lack of education and healthcare is exacerbating the effects of chronic illnesses. Public health systems have incorporated campaigns and mobile clinics in an attempt to equally disperse medical treatment. Incorporating digital and more traditional practices, this paper examines how we can utilise social determinants of health in order to prevent chronic illnesses.

This paper also examines how social determinants of health influence individual behaviour and choices that contribute to chronic disease risk and exposes the limitations of relying only on behavioural interventions. Although behaviours such as diet, physical activity and smoking play important roles in chronic disease risk prevention, environmental conditions can affect an individual’s ability to make healthier choices. The paper argues that integrating an individual-based approach with addressing underlying social conditions can strengthen chronic disease prevention by 2035. Socioeconomic disparities also play a large role in chronic illness prevention. The lack of access to medical insurance and blood/genetic testing among less wealthy populations, as well as living in a rural area, contribute to the development and/or worsening of a condition like asthma or familial hypercholesterolemia. This paper states that public health systems need to allocate more resources to lower income communities and support legislation that aims to reduce exposure to chronic illness risk factors by 2035 in order to reduce chronic illness development among these communities.

Introduction

Although lifestyle choices such as smoking and physical activity influence chronic disease risk, these behaviours are determined by the social, economic and environmental conditions a person lives in. It is necessary for chronic disease prevention to consider both lifestyle choices and influencing conditions. Social determinants of health, including income, education, housing and access to healthcare, can either support or limit an individual’s ability to make healthy choices. Therefore, effective prevention requires public health systems to address not only individual behaviours but also the conditions that shape those behaviours. By combining individual-based interventions with strategies that address social determinants of health, chronic disease prevention can become more effective and equitable by 2035.

Digital and AI Prevention for Chronic Diseases

In many countries across the globe, people are yet to receive access to healthcare systems and tests for certain diseases, mainly due to the cost of healthcare and lack of doctors nearby. By utilising digital systems and artificial intelligence (AI), we can increase access to healthcare and increase disease prevention. AI can analyse and organise given information very quickly, which we can use to our advantage when regarding disease prevention. Many adults and children are impacted by chronic illnesses across the globe, with the health costs and need for materials skyrocketing. Because the cost of healthcare is also very expensive in many countries, specifically the United States, Germany and Sweden (Buchholz, 2023), by having AI-supported initial screening or triage, doctors can oversee patients more effectively and quickly, lowering the cost and increasing accessibility to families in need.

The Centres for Disease Control and Prevention (CDC) (2024) mentions how one of the main uses of AI in preventive medicine is predictive analysis. One of AI’s biggest strengths is being able to predict and notice patterns quickly and more accurately. Through this, researchers are able to implement predictive analysis into medicine. AI can also predict the risk of a patient developing chronic illnesses (Dankwa-Mullan, 2024), which would open up more opportunities for patients to get tested and know their risks of getting certain diseases. Because deaths by chronic illnesses make up around 70% of the world’s deaths (Goldstein et al., 2024), an accessible tool that could warn people about potential chronic illnesses would be especially impactful.  

It was also found that AI can be used to find and match specific medications to patients (Dankwa-Mullan, 2024). AI systems can analyse large datasets concerning medicines and their effects to support clinicians in identifying potentially appropriate treatment options. This process can traditionally be time consuming and expensive to prescribe medications, especially if the illness is severe. Clinicians can use AI as a decision-support tool, and patients can have more medicine options accessible to them. According to a study by Bin et al. (2022), using AI as a second hand for healthcare reduced each medical waiting time by 12 minutes and allowed doctors to save a total of 2,508 hours after 12 months (Bin et al., 2022). As AI can also save professionals time, more patients can be seen, aiding early detection and treatment.

Furthermore, Craig et al. (2021) highlight how AI models are able to analyse societal determinants and relate that data to the health of a community. What would be a very time consuming process for a person, AI can analyse large amounts of data to determine particular risks. For example, if the AI model shows that poor water quality is especially affecting the health of local citizens, health professionals and governing bodies know exactly the cause and what needs to be done in order to prevent further diseases.

Overall, with the use of digital technology, healthcare can become more accessible and accurate. Looking beyond the scope of chronic illnesses alone, AI’s predictive analysis capabilities may also support disease surveillance, outbreak prediction and earlier public-health interventions (Ong et al., 2024). There are many ways the medical field can utilise these powerful tools to improve healthcare and better the future of preventive medicine.

Social Determinants, Individual Behaviour and Chronic Disease Risk

Traditionally, the approach used in the healthcare system for preventing chronic illnesses has been to change individual behaviour. Public health recommendations such as reduced alcohol consumption, quitting smoking, a healthier diet and exercise are given in order to reduce risk factors, with the end goal being preventing chronic illness. Many chronic diseases are influenced by behavioural, genetic and environmental factors. The World Health Organisation (2025) identifies physical inactivity, smoking, drinking and poor diet as major risk factors for noncommunicable diseases, which are diseases that cannot be spread to another person. Reducing these risk factors can lower the chances of an individual developing certain chronic diseases.

However, individuals’ ability to adopt better behaviour is dependent on the social and environmental conditions in which they live. The social conditions we live in such as income, education, housing and employment all heavily influence one’s health, and often influence the individual behaviour that can lead to chronic illnesses. Focusing primarily on the individual overlooks the social conditions that influence people’s ability to make healthier decisions. For example, public health systems often focus on encouraging a healthier diet, but the ability to follow this advice depends on the food the individual can afford. The USDA Economic Research Service found that 9.7% of the US population, or 29.7 million people, live in low-income areas more than 1 mile away from a supermarket (Ver Ploeg et al., 2012). This indicates that individuals may have more difficulty accessing these stores, especially if they do not have a reliable mode of transportation. This creates increased barriers for people and therefore limits choices for food options. Limited access to nutritious foods can constrain dietary choices and may contribute to chronic illnesses like type 2 diabetes, obesity, cardiovascular issues, hypertension and more. The same relationship can be observed through physical activity as well. Public health campaigns often recommend regular exercise, but environmental conditions can determine whether an individual can follow through on this advice. Access to parks, sidewalks and local gyms can limit the choices an individual can make, and as a result impacts exposure to risk factors for chronic disease (CDC, 2026). Behaviours regarding health are not exclusively dependent on individual choice, but rather the social, economic and environmental conditions that people live in, which place restraints on the choices an individual can make.

However, addressing social determinants does not mean abandoning previous individual approaches to prevention. Health education is essential, especially for younger children in school. Increasing public knowledge benefits public health, and educating children on health can help them form healthy behaviours at an early age. Not only that, but interventions for diet, exercise and smoking have been shown to work and promote health and prevention. Smoking-cessation interventions, for example, have been shown to successfully increase the chances that smokers will quit (Community Preventive Services Task Force, 2015). This shows how individually targeted health interventions can work and change individual behaviour. Similarly, approaches that address social conditions also help, such as smoke-free laws and tobacco taxation. This demonstrates how public health can influence both individual behaviours and the environments that cause them, and a more effective approach to prevention is to address a combination of the individual and social conditions that cause chronic illness.

Ultimately, behaviours by individuals do play a key role in preventing chronic illnesses, but without acknowledging the social factors that influence and cause these behaviours, this method falls short. By 2035, public health systems must use a solution that integrates both behavioural aspects along with socioeconomic determinants to successfully prevent chronic diseases.

Ethics, Equity and Safeguards for Public-Health Prevention

Public health systems have an ethical responsibility to prevent chronic illness in ways that give people a fair opportunity to achieve good health. In doing so, public health systems uphold the four pillars of medical ethics: respecting autonomy; promoting beneficence; preventing harm through non-maleficence; and ensuring justice for all patients. This raises the question: if the conditions in which people live can significantly affect their risk of chronic illness, can public health systems ethically focus treatment without addressing those conditions? The World Health Organisation explains that social determinants strongly influence health outcomes and contribute to a difference in life expectancy of up to 33 years (World Health Organisation, 2025). This demonstrates that focusing only on medical treatment does not address the root causes of chronic illness. If factors such as income, education, housing and access to healthcare contribute to differences in health outcomes, then addressing these conditions becomes an ethical issue rather than solely a healthcare one. However, an equality-based perspective could argue that giving different levels of resources to different communities may be unfair because everyone is entitled to the same standard of public health services. Egalitarianism prioritises equal access for all individuals; however, beneficence emphasises prioritising patients based on their individual needs and the potential benefits of treatment, which may not be achieved when every patient is given an equal chance (Tsou et al., 2021). The ethical tension lies between equal treatment and equitable outcomes. Treating everyone in the same way may seem fair in principle but providing additional resources to disadvantaged or underserved populations may be necessary to create an opportunity for good health.

The principle of equity has direct implications for how public health resources should be allocated. Giving everyone the exact same resources does not necessarily create fair health outcomes. Resource allocation creates another ethical conflict because public health systems have limited funding and must decide which populations should receive priority. One line of reasoning suggests that resources should be directed toward communities experiencing the greatest health disadvantages because doing so can reduce preventable inequalities. For example, rural local health departments have smaller budgets because of smaller populations (Leider et al., 2020). This can limit their ability to provide resources that meet community health needs. A contrasting stance emphasises maximising overall health benefits. This creates a conflict between justice and efficiency. According to the Physician Foundation, adults with chronic diseases who have access to a regular, well-resourced primary care provider experience a 20% lower hospitalisation rate and 54% lower healthcare costs compared to those without (The Physicians Foundation, 2026). These findings highlight the need to consider both the overall health benefits of an intervention and whether it’s distribution disadvantages already underserved communities.

Public health systems must protect people’s privacy and autonomy. The systems need information about social conditions to identify communities experiencing health disadvantages, but people need to trust that their information will be protected. From a public-health outlook, collecting information about social conditions can help identify communities experiencing barriers and allow resources to be targeted more effectively. According to a policy statement from the American Heart Association (AHA) for chronic disease, communities have often emerged as strong advocates for surveillance, arguing that without understanding the patterns and causes of disease, population-level intervention can be difficult, if not impossible (Roger et al., 2020). However, a privacy-based stance argues that collecting sensitive information can threaten autonomy if individuals do not understand how their data will be used or shared. A framework by the American Medical Association (AMA) highlights that when patients discover their sensitive data is shared with data brokers for marketing without their knowledge, it erodes their trust (AMA, n.d.). Collecting information about such factors can raise concerns about how personal information is used. The ethical challenge is therefore to balance collective health benefits with individual privacy and autonomy. Balancing useful data collection with privacy can allow public health systems to identify health risks concentrated within a community without creating additional ethical problems.

Ethical principles should guide how public health systems incorporate socioeconomic factors into chronic illness prevention. Equity, justice, autonomy and beneficence are all necessary for an ethical prevention system. The CDC identifies social determinants as important drivers of health outcomes access (CDC, 2024). Chronic illness cannot depend solely on doctors or medical treatments; public health systems must also address the social conditions that influence people’s health. Incorporating ethical principles helps public health systems to address the root causes of chronic illnesses while ensuring prevention strategies are both more effective and equitable to all.

Socioeconomic Factors

Socioeconomic disparities lead to unequal access to healthcare services among minority and poorer communities, leading to worse health outcomes among these communities in comparison to wealthier communities. Research from the Office of Disease Prevention and Health promotion shows that, in the United States, people with a lower income are more likely to be uninsured, and minority groups account for over half of the US’s uninsured population. The evidence in this same study also shows that people who are uninsured are less likely to receive preventive health services for chronic conditions such as diabetes and cardiovascular disease. On a similar note, children who are uninsured are less likely to receive treatment and support for conditions like asthma (Office of Disease Prevention and Health Promotion, n.d.). This disparity suggests that people who live in under-resourced communities might be less likely to receive preventive services and early treatment, increasing their risk of developing a chronic condition or of a pre-existing condition going undetected. For example, in the case of familial hypercholesterolemia (FH), those afflicted by the condition are genetically predisposed to have elevated low density lipoprotein cholesterol (LDL-C), and their risk of cardiovascular events like developing heart disease is increased compared to the general population. However, those who do not have access to blood tests or genetic testing (due to factors such as low income or living in a rural area) may not even know they have FH and an increased risk of heart disease. In fact, according to the CDC, FH is extremely underdiagnosed and the majority of FH diagnoses come only after someone has had a cardiac event for the first time (Swann & Green, 2021). Because of this, people in low income and/or rural communities may face a higher risk of delayed diagnosis and treatment. Therefore, in order to effectively and equitably prevent chronic illness by 2035, public health systems must address the socioeconomic barriers (and geographical barriers for those in rural areas) that are preventing so many people from seeking care (such as the cost of medical care and insurance), rather than simply telling people to go seek care to prevent future chronic illness.

The prevalence of chronic conditions like asthma provides another example of how socioeconomic status can influence chronic illness development. According to research by the CDC, asthma is more common among people who live below the federal poverty line in the United States. The data shows that 11.4% of the tested population with family incomes below the federal poverty line currently experience asthma, while only 6.8% of participants with incomes at or above 450% of the federal poverty line experience asthma (Pate et al., 2021). The CDC also found that there is a strong correlation between income and whether people have gone to the emergency room (ER) or urgent care (UCC) recently for an asthma-related issue. For those living below the federal poverty line with asthma, 18.1% reported that they had an emergency room or urgent care visit in the past year, while only 7.1% of the surveyed population with asthma living at or above 450% of the federal poverty line reported an ER or UCC visit in the past year (Pate et al., 2021). This evidence demonstrates how socioeconomic disadvantages can affect both the likelihood of a person developing asthma and their ability to manage the condition. Several factors can contribute to this disparity, such as limited access to preventive healthcare services and environmental conditions like exposure to second-hand smoke and air pollution. In order to reduce this asthma disparity by 2035, public health services must focus on the socioeconomic and environmental factors that increase asthma risk, rather than intervening only after symptoms have become severe and require medical attention. To address these socioeconomic disparities, public health systems will need to move beyond the traditional lens of treating diseases only once they have developed and pose a risk to someone’s health. For example, if a public health system wants to reduce the risk of respiratory issues in lower income communities, they could run a campaign that helps replace toxic pest control chemicals with non-toxic alternatives that are less likely to irritate airways and the respiratory system.

By allocating resources for the communities who experience the greatest socioeconomic disadvantages, public health systems can reduce the development of chronic, preventable diseases while also narrowing health inequalities. This approach can make chronic disease prevention much more effective and equitable by addressing underlying conditions that pose health risks rather than simply telling people to seek care when doing so may not be a viable option.

Vaccine Access and Availability

Vaccines can prevent disease, protect communities and save lives, but their benefits depend on equitable access. Access to vaccines and vaccinations services remains unequal globally, with barriers including cost, geography, transport, education and healthcare infrastructure.

Vaccines and medication availability cannot be considered separately from factors such as income, geographic location, insurance coverage, transportation, education and healthcare access. According to Vardavas et al. (2023), a study that examined the social determinants of patients’ uptake of initial COVID-19 vaccination resulted in the following: not all, but most social determinants of health (SDoH) played an important role in determining who was able to get the vaccines; regional and economic factors affected the distribution of people who received the first dose. The following correlations were made:

“Age was a significant determinant of vaccine uptake [actual number of people who get the vaccine], with coverage increasing with age. Higher education levels were positively correlated with vaccine coverage [percentage of a defined population that is fully immune to a disease]. Vaccination coverage was lower in counties with higher socioeconomic and racial/ethnic minority status vulnerability. Deprivation and lower socioeconomic status were associated with lower vaccination rates” (Vardavas et al., 2023).

This quote directly addresses and proves the discussion at hand. There is an underlying issue in the vaccine uptake, or the number of people that are receiving vaccination. This unequal distribution of medication is being determined by SDoH. Moreover, this statement highlights the importance of reducing the levels that divide society in terms of healthcare, so that medicine can reach all equitably. When concluding their paper, the authors of the analysis highlight: “the results of this analysis could provide healthcare professionals with guidance for addressing vaccination inequity among individuals as the significance of social variables in ensuring equitable healthcare delivery is increasingly recognised” (Vardavas et al., 2023). The study agrees with the need for guidance to better meet society’s demands. Moreover, there is still a lot of work to be done to coordinate efforts for accessibility for all patients. 

Although HPV vaccination can prevent the infections responsible for most cervical cancer cases, access to this protection remains unequal around the world. According to Gould et al.’s (2026) study that was focused on the accessibility women had in receiving the HPV vaccine around the world, it was concluded that socioeconomic factors do play a role in vaccination rates. Barriers to vaccination include geography, education, socioeconomic disadvantage and healthcare access. According to Gould et al. (2026), “high-risk persistent human papillomavirus (HPV) infections cause approximately 95% of cervical cancer cases. Vaccination between ages 9 and 14 years is highly effective in preventing infection. Many countries have implemented publicly funded programmes targeting girls aged under 18 to reduce HPV transmission. Despite these efforts, only 1.4% of women worldwide have completed the full vaccine series through such programmes” (Gould et al., 2026). This information is crucial to the studies that are conducted around the world and is strongly correlated with the low rates of vaccination. Because of the lack of education and understanding of the importance of vaccination, many women do not recognise the benefits of receiving the HPV vaccine or understand the health risks associated with remaining unvaccinated. Therefore, in order to restore accessibility for vaccination, targeted communities should receive clear information about the healthcare resources available to them.

Mobile clinics and vaccination drives have been used to expand access in underserved communities. Pharmacists and scientists are aware of the ongoing problems in healthcare and vaccination access. Moreover, they have taken multiple measures to ensure patients receive access. Instead of bringing patients to their clinics, pharmacists have brought clinics to patients. One attempt in doing this was bringing mobile pharmacy vans to underserved neighbourhoods with medications and vaccines. The CDC is putting its focus on “programmes to increase vaccine access, confidence and demand in communities with low vaccination coverage” (CDC, 2024) and on measuring “vaccine distribution and uptake [] to address differences among groups of people” (CDC, 2024). Providing resources and joining efforts to seek availability is a huge step toward the equal distribution of vaccines. In mobilising clinics and building programmes for the benefit of the people, public health systems should evaluate and expand interventions that reduce inequalities in vaccine distribution. Regarding both educational and socioeconomic barriers, sustained efforts to ensure that everyone has an equal opportunity to access vaccines will provide healthcare to all.

Conclusion

Social determinants of health have negatively contributed to the prevention of developing chronic illness in the public health systems. However, by utilising digital analysis features in AI, preventive medicine can improve accuracy in diagnosis, recognising medical patterns, saving doctors’ time and lowering healthcare costs in ways traditional medicine could not support. For some communities, distance, affordability and access to nutritious food sources have a crucial impact on an individual’s diet. Thus, this can contribute to the development of chronic illnesses. Because people who live in impoverished communities receive less preventive medicine, this also increases their risk of developing a chronic condition. Ethical principles, moreover, should uphold the four pillars of medicine and provide a guide for how public health systems should incorporate social determinants into preventive medicine. Equity is necessary for a functional prevention system. Social determinants are the root causes of chronic illnesses, far beyond genetic contributions. Additionally, the distribution of vaccines is a subject to address. Social determinants are deciding where vaccines get distributed. Civilisations that are hard to access become unrecognised in the dispersal of medication. To improve this, many pharmacists have started developing mobile clinics and programmes to address the prevention of chronic illnesses. As a result, to prevent chronic illness by 2035, public health systems must address the socioeconomic barriers that are preventing people from seeking care, like rising campaigns such as smoking cessation, which can improve the overall health of a human. The individual behaviours that the public health systems do address remain important in preventing chronic illnesses, but social conditions are what shape individuals’ abilities to make these healthier choices. Preventive medicine can only have a significant impact in society if social determinants of health are considered in public health.

American Medical Association (n.d.) AMA health data privacy framework. AMA [online]. <https://www.ama-assn.org/practice-management/hipaa/ama-health-data-privacy-framework>

Bin, K.J., Melo, A.A.R., da Rocha, J.G.M.F et al. (2022). The Impact of Artificial Intelligence on Waiting Time for Medical Care in an Urgent Care Service for COVID-19: Single-Center Prospective Study. JMIR Formative Research Journal, 6(2), 29012.

Buchholz, K. (2023) Charted: The countries with the most expensive healthcare. World Economic Forum [online]. <https://www.weforum.org/stories/health-and-healthcare-systems/charted-countries-most-expensive-healthcare-spending>

Centers for Disease Control and Prevention (2024) Ensuring Vaccine Access for All People. CDC [online]. <https://www.cdc.gov/vaccines/basics/vaccine-equity.html>

Centers for Disease Control and Prevention (2024) Social Determinants of Health (SDOH). CDC [online]. <https://www.cdc.gov/about/priorities/why-is-addressing-sdoh-important.html>

Centers for Disease Control and Prevention (2026) Strategies for Physical Activity Through Community Design. CDC [online]. <https://www.cdc.gov/physical-activity/php/strategies/increasing-physical-activity-through-community-design-prevention-strategies.html>

Craig, K.J.T., Fusco, N., Gunnarsdottir, T. et al. (2021) Leveraging Data and Digital Health Technologies to Assess and Impact Social Determinants of Health (SDoH): a State-of-the-Art Literature Review. Online Journal of Public Health Informatics, 13(3), 14.

Dankwa-Mullan, I. (2024) Health Equity and Ethical Considerations in Using Artificial Intelligence in Public Health and Medicine. Preventing Chronic Disease: Public Health Research, Practice, and Policy, 21(64), pp. 1-9.

Goldstein, S.P., Tovar, A., Espel-Huynh, H.M. and Stowers, K.C. (2024) Applying a Social Determinants of Health Framework to Guide Digital Innovations that Reduce Disparities in Chronic Disease. Psychosom Med, 85(7), pp. 659–669.

Gould, J., Litchfield, E., Jenkins, M., Nathoo, A., Pudwell, J. and Velez, M. P. (2026) Social determinants of health and human papillomavirus vaccination uptake: A systematic review. Journal of Obstetrics and Gynaecology Canada : JOGC = Journal D’obstetrique et Gynecologie Du Canada, 48(4), 103246.

Healthy People 2030 (n.d.) Access to Health Services. Office of Disease Prevention and Health Promotion [online]. <https://odphp.health.gov/healthypeople/priority-areas/social-determinants-health/literature-summaries/access-health-services>

Ledier, J., Meit, M., Resnick, B., et al. (2020) The State of Rural Public Health: Enduring Needs in a New Decade. American Journal of Public Health, 110 (9), pp. 1283-1290.

Ong, J.C.L., Seng, B.J.J., Law, J.Z.F., et al. (2024) Artificial intelligence, ChatGPT, and other large language models for social determinants of health: Current state and future directions. Cell Reports Medicine, 5(1), 101356.

Pate, C.A., Zahran, H.S., Qin, X., et al. (2021) Asthma Surveillance — United States, 2006–2018. MMWR Surveillance Summaries, 70(5), pp. 1–32.

Physician’s Foundation (2026) New Report: Primary Care is Missing Link in America’s Fight Against Chronic Disease and Rising Health Care Costs. The Physician’s Foundation [online]. <https://physiciansfoundation.org/new-report-primary-care-is-missing-link-in-americas-fight-against-chronic-disease-and-rising-health-care-costs/>

Roger, V.L., Sidney, S., Fairchild, A.L., et al. (2020) Recommendations for Cardiovascular Health and Disease Surveillance for 2030 and Beyond: A Policy Statement From the American Heart Association. Circulation, 141(9).

Swann, F. and Green, R.F. (2021) How Common is Familial Hypercholesterolemia? Centres for Disease Control and Prevention [online]. <https://blogs.cdc.gov/genomics/2021/01/25/how-common-is-fh/>

Tsou, A.Y., Graf, W.D., Russell, J.A. and Epstein, L.G. (2021) Ethical Perspectives on Costly Drugs and Health Care. Neurology, 97(14), pp. 685-692.

U.S. Preventive Services Task Force (2021) Tobacco Smoking Cessation in Adults, Including Pregnant Persons: Interventions. USPSTF [online]. <https://www.uspreventiveservicestaskforce.org/uspstf/document/RecommendationStatementFinal/tobacco-use-in-adults-and-pregnant-women-counseling-and-interventions>

Vardavas, C., Nikitara, K., Aslanoglou, K., et al. (2023) Social determinants of health and vaccine uptake during the first wave of the COVID-19 pandemic: A systematic review. Preventive Medicine Reports, 35(35), 102319.

Ver Ploeg, M., Breneman, V., Dutko, P., et al. (2012) Access to affordable and nutritious food: updated estimates of distance to supermarkets using 2010 data. U.S. Economic Research Service, Report No. 143 [online]. <https://ers.usda.gov/publications/45035>

World Health Organization (2025) Noncommunicable diseases. WHO [online]. <https://www.who.int/en/news-room/fact-sheets/detail/noncommunicable-diseases>

World Health Organization (2025) Social determinants of health. WHO [online]. <https://www.who.int/news-room/fact-sheets/detail/social-determinants-of-health>