Income as a Social Determinant of Health - Special Academic Support

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Income as a Social Determinant of Health

Introduction

Socioeconomic status (SES) affects different aspects of human well-being. However, its impact on health is profound. Many researchers understand this fact and seek to understand the relationship between the two variables. This paper joins this quest by investigating the findings of a documentary titled, In Sickness and in Wealth, by Adelman (2008), and using its findings to explore how the information presented in this video relates to health disparities and well-being. Coupled with the findings of a British Whitehall Cohort Study, this paper also uses the health outcomes of a sample group to explain the wealth-health gradient.

How the Information Presented In the Video Relates To Health Disparities and Well-Being

The Adelman (2008) video relates to health disparities and well-being because it shows how social and economic factors affect health outcomes. It also explores different real-life examples of how power, control, and economic resources affect peoples health.

How the Video Exemplifies Concepts like the Wealth-Health Gradient

The health-wealth gradient shows how SES affects human health. Adelman (2008) used Jim Taylor, Tondra Young, Corey Anderson, and Mary Turner (people from different SES) to explain the relationship between SES and health outcomes. Taylor is a wealthy man with good health. Comparatively Young is a middle-class Louisville citizen. She lives a comfortable life and has fewer health complications than Anderson (who hails from a lower SES) has. The situation is worse for Tuner. She is from a lower SES. Her life expectancy is nine years less than Taylors life expectancy. Similarly, unlike Taylor, Tuner suffers from many health complications, including heart disease, thyroid problems and arthritis (Adelman, 2008). This analysis shows that SES increases human mobility across the health-wealth gradient. Concisely people who have more power and control (Taylor) have better health outcomes than people with no power or financial resources (Tuner).

Data Map Differences of Disease Rates in the Louisville Council Districts

Adelman (2008) said Louisville had different death rates for different districts. Health outcomes differed across the east and the west (regions with different economic statuses). For example, there were low infant mortality rates in the East (the more affluent region) and high infant mortality rates in the west (the less affluent region). The same pattern replicated when Adelman (2008) analyzed the death rates from lung cancer across both regions. For example, there were higher rates of death from lung cancer in the west, and low levels of death in the East. These findings showed that affluent communities in the East suffered fewer health complications than communities that lived in the West. Therefore, good health is synonymous to high SES.

Most Profound Findings in the Whitehall Study

Whitehalls findings affirm the views of Adelman (2008). However, two issues, from this study, captivated my attention. One issue was the impact of gender on the health-wealth gradient. For example, Stringhini et al. (2012) said network scores and marital status explained up to 27% of the differences in health-wealth gradient. The same study showed that the two factors explained up to 29% of the relationship between SES and cardiovascular deaths (Stringhini et al., 2012). Another profound finding was the impact of social support on the wealth-health gradient. These two findings show that varying levels of social support and gender differences affect the relationship between SES and health outcomes. Similarly, these findings show that SES and health outcomes do not share an exclusive relationship.

Conclusion

This paper shows that wealth and SES affect peoples health outcomes. The differences of data-maps and disease rates in Louisville Council explain this relationship because they show the health disparities that exist across different socioeconomic groups. The health conditions of the four people described in this paper (Jim Taylor, Tondra Young, Corey Anderson, and Mary Turner) also affirm the same relationship because their socioeconomic statuses show their varied health outcomes. Findings from the Whitehall cohort study also prove the same relationship, although they show that gender differences and social support also affect health outcomes. Overall, these studies explain how to improve community health outcomes by highlighting how peoples socioeconomic statuses affect their health outcomes.

References

Adelman, L. (Executive Producer). (2008). Unnatural causes: Episode 1in sickness and in wealth [DVD]. Arlington, VA: Public Broadcasting Service.

Stringhini, S., Berkman, L., Dugravot, A., Ferrie, J., Marmot, M., Kivimaki, M., & Singh-Manoux, A. (2012). Socioeconomic Status, Structural and Functional Measures of Social Support, and Mortality. Am J Epidemiol, 175(12), 12751283.

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