Liviu Poenaru, Feb. 25, 2025
According to the County Health Rankings for 2024, social and economic factors account for about 40% of the variation in health outcomes—a striking statistic that powerfully illustrates that nearly half of community health is determined not solely by individual choices, but by broader structural conditions (County Health Rankings, 2024). This empirical framework emphasizes measurable variables such as education, employment, income, family and social support, and community safety. These indicators serve as indispensable benchmarks for public policy, offering clear, actionable targets to improve overall well-being (Braveman & Gottlieb, 2014). While these tangible determinants are critical, they are only the surface expressions of a much deeper system of economic unconscious codes—the implicit cultural and ideological narratives that have long dictated how societies assign worth, distribute resources, and prioritize opportunities (Marmot, 2005).
The reliance on quantifiable metrics is not without its merits; these data points allow us to monitor disparities and design interventions that can directly influence public health outcomes. Robust evidence indicates that communities with higher levels of educational attainment and income enjoy better health outcomes and longer life expectancies (Wilkinson & Pickett, 2009). Yet, it is essential to recognize that these measurable factors do not exist in isolation. Beneath every statistic lies a network of cultural assumptions and historical legacies—such as the widespread acceptance of meritocracy and the valorization of free-market principles—that do more than simply describe income disparities; they actively shape the policies and social practices that produce and sustain these disparities (Link & Phelan, 1995). These underlying economic unconscious codes subtly determine who is deemed worthy of investment and which groups are systematically marginalized.
This recognition that 40% of health outcomes are linked to social and economic factors compels us to look beyond the numbers. While the empirical data provide a crucial starting point, they do not capture the full complexity of the forces at play. Interrogating these deeper layers requires a multidisciplinary approach—one that integrates empirical research with insights from psychoanalysis, critical theory, and cultural studies—to illuminate the invisible forces behind observable disparities (World Health Organization, 2010). Such an approach not only deepens our understanding of health inequities but also encourages the development of policies that address the root causes of inequality rather than merely alleviating its symptoms.
In today’s digital era, the role of social media has emerged as a pivotal factor in this complex interplay between measurable determinants and underlying economic narratives. Platforms such as Twitter, Facebook, and Instagram have revolutionized how information is disseminated and public discourse is framed. They have become vibrant arenas where socio-economic realities are continuously discussed, contested, and redefined. Social media not only relays empirical data on issues like income inequality and educational access but also actively shapes the narratives that inform public understanding of economic policies and social equity (Berkman, Kawachi, and M. Glymour, 2014). By doing so, these platforms reveal that the measurable aspects of socio-economic health are inextricably linked to the broader ideologies perpetuated online.
Social media has proven to be a potent tool for mobilization and collective action. It provides marginalized communities with a digital space to voice their grievances, organize protests, and advocate for systemic change. Through viral campaigns and hashtag activism, these platforms enable groups to challenge entrenched disparities and push for reforms that address both immediate economic conditions and the deeper cultural codes that sustain inequality.
However, the algorithms driving these platforms tend to create echo chambers that reinforce pre-existing beliefs. This selective exposure intensifies dominant socio-economic narratives—such as those justifying disparities through the lens of meritocracy—and further solidifies the economic unconscious codes that underpin measurable health outcomes. The algorithmic reinforcement has not only contributed to the persistence of these ideological frameworks but has also emerged as a major risk factor for mental illness (Keles, McCrae, & Grealish, 2019; Primack et al, 2017). Numerous studies have linked extensive social media use to heightened levels of depression, anxiety, and other mental health disorders, suggesting that the very mechanisms that drive digital engagement can inadvertently exacerbate psychological distress. In this way, social media is not merely a platform for information exchange but a complex and influential force that can significantly impact both individual mental health and broader public health outcomes.
The feedback loop generated by algorithmic amplification and public discourse creates a self-reinforcing cycle where specific economic narratives become increasingly entrenched. As these digital narratives gain momentum, they contribute to a cultural milieu that subtly shapes public perceptions and influences policy priorities. In this way, the measurable determinants of health, as tracked by institutions like the County Health Rankings, are both a product of and a testament to these deeply embedded cultural codes. While 40% of health outcomes are directly linked to observable social and economic factors, the root causes of these disparities are intricately interwoven with the unconscious economic narratives circulating in our digital spaces.
This dual-layer understanding of health disparities—combining visible, quantifiable metrics with invisible, ideological forces—demands an integrated approach to public policy and social reform. The statistic that nearly 40% of health outcomes are explained by social and economic factors should not be viewed in isolation; rather, it should serve as an urgent call to examine both the empirical dimensions of community well-being and the underlying economic unconscious codes that shape them. Recognizing and challenging these deep-seated narratives is imperative for achieving meaningful social justice and lasting improvements in public health. Only by understanding both the tangible metrics and the ideological underpinnings can we hope to dismantle the structural inequities that have long dictated the distribution of resources and opportunities in our society.
REFERENCES
Berkman, L. F., Kawachi, I. and M. Glymour, M. (eds) (2014). Social Epidemiology, 2 edn (New York, 2014; online edn, Oxford Academic, 1 Mar. 2015), https://doi.org/10.1093/med/9780195377903.001.0001
Braveman, P., & Gottlieb, L. (2014). The social determinants of health: It’s time to consider the causes of the causes. Public Health Reports, 129(Suppl 2), 19–31.
County Health Rankings & Roadmaps (2024). Social & Economic Factors. Retrieved from https://www.countyhealthrankings.org/health-data/health-factors/social-economic-factors?year=2024
Keles, B., McCrae, N., & Grealish, A. (2019). A Systematic Review: The Influence of Social Media on Depression, Anxiety and Psychological Distress in Adolescents.
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Link, B. G., & Phelan, J. (1995). Social conditions as fundamental causes of disease. Journal of Health and Social Behavior, 35, 80–94.
Marmot, M. (2005). Social determinants of health inequalities. The Lancet, 365(9464), 1099–1104.
Primack, B. A., Shensa, A., Sidani, J. E., Whaite, E. O., Lin, L. Y., Rosen, D., Colditz, J. B., Radovic, A., & Miller, E. (2017). Social media use and perceived social isolation among young adults in the U.S. American Journal of Preventive Medicine, 53(1), 1–8.
World Health Organization (2010). A conceptual framework for action on the social determinants of health.Retrieved from: https://www.afro.who.int/sites/default/files/2017-06/SDH_conceptual_framework_for_action.pdf
Wilkinson, R. G., & Pickett, K. (2009). The Spirit Level: Why More Equal Societies Almost Always Do Better. Allen Lane.