Discuss how biases and barriers impact population health outcomes in Orange County, Florida, in particular when it comes to measuring obesity, in this essay. Lack of healthcare access hinders quantifying obesity in Orange County, Florida
Anne:Population health outcomes depend on several factors, including socioeconomic determinants of health, access to healthcare, and individual behavior. However, discrimination and barriers can also impact health outcomes, especially in some populations. We will discuss how biases and barriers impact population health outcomes in Orange County, Florida, in particular when it comes to measuring obesity, in this essay.
Lack of healthcare access hinders quantifying obesity in Orange County, Florida. According to Islami et al. (2022), uninsured people in the US are less likely to obtain preventative treatment, such as obesity screening. Poor health outcomes may follow from this lack of access to healthcare, which can cause undetected obesity. Additionally, the absence of safe locations to exercise and the availability of healthy food alternatives may be a factor in the high obesity rates in Orange County, Florida.
In many different ways, biases can affect population health outcomes. For instance, people from low-income regions may have less access to healthy food alternatives and secure exercise facilities, which might increase the prevalence of obesity. By restricting access to nutritious food alternatives and secure exercise facilities, prejudice can harm population health outcomes in Orange County, Florida. According to Ohri-Vachaspati et al. (2019), low-income communities featured fewer supermarkets and more fast-food restaurants than high-income neighborhoods, making it challenging for people to get healthy food alternatives.
In conclusion, bias and barriers can influence population health outcomes in Orange County, FL, particularly when evaluating obesity rates. Individuals in Orange County, FL, may suffer from poor health outcomes due to poor access to healthcare, good dietary alternatives, and
bias in obesity assessment. Overcoming these barriers and biases is critical to enhancing neighborhood population health outcomes.
Islami, F., Guerra, C. E., Minihan, A., Yabroff, K. R., Fedewa, S. A., Sloan, K., … & Jemal, A. (2022). American Cancer Society’s report on the status of cancer disparities in the United States, 2021. CA: A Cancer Journal for Clinicians, 72(2), 112-143. https://doi.org/10.3322/caac.21703
Ohri-Vachaspati, P., DeWeese, R. S., Acciai, F., DeLia, D., Tulloch, D., Tong, D., Lorts, C., & Yedidia, M. (2019). Healthy food access in low-income high-minority communities: A longitudinal assessment-2009-2017. International Journal of Environmental Research and Public Health, 16(13), 2354. https://doi.org/10.3390/ijerph16132354
Nicole: The year of 2020 really expressed to the world that there are explicit biases. Some were cheering healthcare workers and others were harming healthcare workers. Then the George Floyd incident proved that there is systemic racism in the world. This was an example of explicit bias on a national level. Implicit bias also occurs in the healthcare system and deeply affects patient-clinician communication and clinical decision making. Biases have also occurred in healthcare systems that affect admissions, promotions, bedside instruction as well as classroom instruction of clinicians (Vela et al., 2022). Although, this is not published, it is known that in our area, one hospital caters more toward minorities than the other hospital. I wonder, how could this affect patient outcomes? It does seem to create an implicit bias that is not quite so noticeable but relevant to those that are part of those effected by the bias.
There are many people in the area that are very vocal about the bias felt at some local establishment. The people affected by the biases are vocal on social media, they are vocal in local establishments, they are vocal in the schools.
According to the US Census Bureau, the population of Kankakee County is 106,074. 50% female, 50 % male, 18% over the age of 65, 23% 18 or under but older that 5 years of age. The county is 80.7 % white, 15.2% black or African American, 2.4% of other races, or two or more races (USCB, 2022).
Because the housing market is lower in this area, many people are relocating from the city of Chicago. Therefore, some people who are not local by nature, have been more vocal about the bias.
Some barriers in the county of Kankakee include lack of transportation. Recently in the last few years a public transportation bus system was created to eliminate this issue. Although it has, to some extent, the schedule is very far apart, making in not so convenient for those without transportation. There are maybe 3 uber drivers in the area and an ADA bus. However, the ADA bus will only pick up if there is a documented disability. Other barriers, include location of provider offices. Most are in the buildings of the two hospitals. The two hospitals are only a mile a part, but on the same side of town. Thus, making it difficult for some who are not near to that location.
With the barriers of the location of the hospitals, limited public transportation options, and known biases at one of the hospitals, this could lead to many illnesses in Kankakee County. Many illness that could be prevented with care that is accessible and unbiased. Some barriers are being worked on, to be eliminated, but the county has not quite achieved this goal. I do believe, that the county as a whole is moving in the right direction.
Charlesworth, T., Maharin, B., (2019). Age and Generation Issues. Research: How Americans’ Biases Are Changing (or not) over time. Harvard Business Review.
USCB. (2022). United States Census Bureau. Quickfacts Kankakee County, Illinois. Retrieved From. https://www.census.gov/quickfacts/fact/table/kankakeecountyillinois/PST045222
Vela, M. B., Erondu, A. I., Smith, N. A., Peek, M. E., Woodruff, J. N., & Chin, M. H. (2022). Eliminating Explicit and Implicit Biases in Health Care: Evidence and Research Needs. Annual review of public health, 43, 477–501. https://doi.org/10.1146/annurev-publhealth-052620-103528
Requirements: 200 words
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