Population Health and Impact of ZIP Codes Essay (Critical Writing)

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The life expectancy of people and the health of the population have geographic differences, which is the reason for the ZIP codes paradigm. The study by Holmes et al. (2018) examines differences in life expectancy by geographic area in Hawaii. The authors emphasize that the life expectancy of the population varies in geographical zones, but they do not investigate the factors influencing these disparities. However, Graham et al. (2015) emphasize that despite the identification of disparities, this theory does not allow addressing the causes of their occurrence. The researchers note that there is now a need to look at social and economic data across communities and neighborhoods. This article identifies the existence of a relationship between ZIP codes and population health but also emphasizes the limited nature of the information presented by it.

Health disparities are more local in nature and need to be studied from the perspective of more diverse variables. Goodwin et al. (2016) identify that areas that are medically underserved are characterized by a higher mortality rate for people admitted to hospitals with severe sepsis. However, the study highlights that “ZIP Code-based surrogates of socioeconomic status including median income, proportion below poverty level, and educational attainment, however, had a minimal association with sepsis mortality” (Goodwin et al., 2016, p. 1). Thus, the researchers note that access to health care, rather than socioeconomic conditions, plays a key role in infection mortality. This article provides an opportunity to consider additional factors that affect health indicators beyond ZIP codes. These findings are also supported by Graham (2016), who argues that the health of a population is determined by the interaction of many factors, including social, geographic, individual, and environmental. Thus, the ZIP codes paradigm is not a reliable representation of health disparities that exist in society.

Researchers are also attempting to view health predictors in terms of more specific geographic characteristics. The study by Airaksinen et al. (2016) examines the relationship between the neighborhood in which people live and their habits. Research results identify that people in urban areas are more likely to smoke and drink alcohol. Urbanization and socioeconomic status do not affect people’s engagement in physical exercising activities. At the same time, the study notes that urban residents are more interested in monitoring and maintaining their health, including healthy eating behaviors. Thus, the study identifies social causation between neighborhood and health behaviors. However, the researchers note that the findings are relevant to Finland, which has a rather homogeneous social environment.

Researchers are also paying increased attention to research on social determinants that affect population health. Obuobi et al. (2021) investigate the relationship between the social conditions in which people live and the risk of cardiovascular disease. In particular, the researchers note that such factors as “housing stability, food insecurity, transportation limitations, utility assistance needs, and interpersonal safety” (Obuobi et al., 2021, p. 984). The results of the study allow analyzing what motivates the geographical differences in the health of the population within the framework of the ZIP codes paradigm.

Other studies also support the assumption that health disparities depend on ZIP codes but are also socially determined. Qwaider et al. (2021) note that “patients with colorectal cancer residing in lower-income areas are screened less, received adjuvant chemotherapy less, and have worse outcomes” (p. 1). Thus, the ZIP code correlates with the income level of the population, which affects access to medical care and health outcomes. This study makes it possible to identify the relationship between this characteristic and social conditions, which are determinants of health. This finding is supported by Ritchie (2013), whose article emphasizes that geographic health disparities are more influential than genetic characteristics of individuals. In particular, it is noted that the habits of human life and social determinants play a more significant role than access to health care.

The researchers emphasize that ZIP codes illustrate well the social conditions in which a person lives and which determine individual health. Slade-Sawyer (2014) argues that social factors such as income, housing, and education can be much more important for the health of the population than the quality of the health care system. Seavey (2008) argues that poverty and disease have a complex relationship, as the poor are more likely to get sick. He argues that people living in poorer communities often have no job and health insurance. Thus, poor people tend to be in poorer health due to the inability to get help.

Thus, a review of the literature makes it possible to identify that ZIP codes correlate with disparities in the health of the population. Based on the information provided, two hypotheses can be presented that correspond to the research questions. Firstly, the geographic health disparities provided by the ZIP codes paradigm are related to the socioeconomic characteristics of the areas. Second, socioeconomic factors have a greater impact on the health of the population than the quality of the health care system. These hypotheses reflect the findings reflected in the literature review and allow us to investigate how ZIP codes reflect the health status of the population.

References

Airaksinen, J., Hakulinen, C., Pulkki-Råback, L., Lehtimäki, T., Raitakari, O. T., Keltikangas-Järvinen, L., & Jokela, M. (2016). The European Journal of Public Health, 26(3), 417-421.

Goodwin, A. J., Nadig, N. R., McElligott, J. T., Simpson, K. N., & Ford, D. W. (2016). Chest, 150(4), 829-836.

Graham, G. N. (2016). Why your ZIP code matters more than your genetic code: Promoting healthy outcomes from mother to child. Breastfeeding Medicine: The Official Journal of the Academy of Breastfeeding Medicine, 11, 396–397. Web.

Graham, G. N., Ostrowski, M., & Sabina, A. (2015). Health Affairs.

Holmes, J. R., Tootoo, J. L., Chosy, J., Bowie, A. Y., & Starr, R. R. (2018).Preventing Chronic Disease, 15, 1-3.

Obuobi, S., Belardo, D., & Gulati, M. (2021). Journal of the American College of Cardiology, 3(6), 982–984.

Qwaider, Y. Z., Sell, N. M., Boudreau, C., Stafford, C. E., Ricciardi, R., Cauley, C. E., Bordeianou, L. G., Berger, D. L., Kunitake, H., & Goldstone, R. N. (2021). The American Surgeon, 0(0), 1-6.

Ritchie, D. (2013). Rhode Island Medical Journal, 96(7), 14.

Seavey, J. W. (2008). . The University Dialogue, 42.

Slade-Sawyer, P. (2014).North Carolina Medical Journal, 75(6), 394-397.

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