NR 601 Week 1: Health Inequities

Chamberlain University NR 601 Week 1: Health Inequities– Step-By-Step Guide

This guide will demonstrate how to complete the Chamberlain University  NR 601 Week 1: Health Inequities  assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.

How to Research and Prepare for NR 601 Week 1: Health Inequities                        

Whether one passes or fails an academic assignment such as the Chamberlain University  NR 601 Week 1: Health Inequities depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.

After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.

How to Write the Introduction for NR 601 Week 1: Health Inequities                        

The introduction for the Chamberlain University  NR 601 Week 1: Health Inequities      is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.

How to Write the Body for NR 601 Week 1: Health Inequities                        

After the introduction, move into the main part of the NR 601 Week 1: Health Inequities      assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.

Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.

How to Write the Conclusion for NR 601 Week 1: Health Inequities                        

After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.

How to Format the References List for NR 601 Week 1: Health Inequities                        

The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.

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Sample Answer for NR 601 Week 1: Health Inequities

Los Angeles County and the state of California as a whole have very comparable statistics in terms of median income, percentage of individuals with health insurance, those living in poverty and the employment rate. As a resident of Los Angeles County for the last ten years, I was very surprised to see that it is not listed in the top 10 most expensive counties in the state, which explains the difference in median income for LA county at $82,516 and that of the whole state at $91,551 (U.S. Census Bureau, 2024).  Santa Clara county has the highest median income at $140,258 and the county in tenth (Taylor, 2023).  Overall, Los Angeles County has a large concentration of its population with employment and adequate healthcare coverage.  It was slightly concerning to see the percentage of those living in poverty was higher than the state average, which I can only imagine is attributed to the high cost of living.

Evaluate life expectancy data

After reviewing the data for Los Angeles County, census tract 4817.11 had the highest life expectancy at 93.3 and tract 2410.02 had the lowest life expectancy at 68.8.  The state of California’s highest life expectancy is 79 coming in second only to Hawaii with a rate of 80.7 years.  Mississippi has the lowest highest life expectancy at only 74.9 years (CDC, 2020). 

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Demographic factors that play a role in life expectancy include race, gender, age, literacy, education level, poverty and income.  Los Angeles county has a 13.9% poverty rate, almost 2% more than the state of California as a whole.  It also has almost 2% less of individuals with health insurance coverage.  While these statistics may allude to lower life expectancies, I was pleasantly surprised to see that the census tract 4817.11 had a life expectancy of 93.3 years of age.  Conceptualizing a county based on demographic data such as the stats listed above can help providers understand where the holes exist in adequate care, and how to fix them.  Targeting the 13.9% of individuals living in poverty and assisting them with access to healthcare and employment is a great starting point.  As a provider, I will help patients understand the importance of primary and secondary screenings to prevent long-term health complications and will do this through education and free clinics.  I believe these numbers can be flexible if a proper plan is put into place and executed.

References:

Centers for Disease Control and Prevention. (2020, March 9). Life expectancy data viz. Centers for Disease Control and Prevention. https://www.cdc.gov/nchs/data-visualization/life-expectancy/

Taylor, B. (2023, July 18). These are the 10 wealthiest counties in California, according to new median income ranking. Yahoo! News. https://news.yahoo.com/10-wealthiest-counties-california-according-180558881.html?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAAD6fZ76YlfLp-NF4iA_oZa_HqQabg-7QAbAUxW-tKOB8FWA7Kdi8eC8VguirfauYAKXkyc1YJ00_ILZE2rgcDTUbb10LUUjX8PZJ-DMIbOEG9orIlhlYx6uAoZoYsOXh6Z0EqDTJVG7kZOnyntYwBrSuwKTKFrYBEmTPrxIOMMcqLinks to an external site.

U.S. Census Bureau. (2024). California. Explore census data. https://data.census.gov/profile/Los_Angeles_County,_California?g=050XX00US06037

Sample Answer 2 for NR 601 Week 1: Health Inequities

• Identify your county and state. Briefly describe demographic data for your county, including total population, median income, percentage of residents with health insurance, poverty percentage, and one additional demographic. Compare the data to state averages and discuss your findings.

I currently live in Orange County, California. Orange County’s total population is 3,175,692, or roughly 12% of California’s 39,512,223 total population. According to estimates, the median household income is $142,593, and approximately 32.9% of families earn $20,0000 or more annually. It exceeds the $91,551 median household income in California. Orange County’s estimated poverty rate is 9.9%, roughly 3% less than the State of California. In Orange County, 6.3% of people do not have health insurance, which is 0.2% less than the state of California’s rate, so their living situation is mid-level. Orange County has a 2.6% higher employment rate than the state of California, at 62.6% (United States Department of Commerce, 2022).

Evaluate life expectancy data:

According to the Centers for Disease Control and Prevention (2020), the census tracts in Orange County with the highest life expectancy, 0011.01, was 82.0 years, and the lowest, 0747.01, was 78.8 years. It is longer than the 79.0-year life expectancy in California. The life expectancy in some other states is extremely low compared to California. For instance, among the states, Mississippi has the lowest life expectancy, at 71.9 years. It is 10.1 years shorter than Orange County’s life expectancy. The life expectancy in Lake County, California, was 74.8 years, the lowest of all the counties (Centers for Disease Control and Prevention, 2020).

Health disparities are closely linked to demographic factors like income, place of residence, and level of education. These factors affect people’s pursuit of well-being and lifestyle decisions, which greatly affect their longevity and general health. For example, obesity increases the risk of developing diabetes. Research findings indicate a robust association between obesity and a sedentary way of life. People who live in dangerous, high-crime areas usually don’t get enough exercise because it’s difficult for them to walk outside, like in the park. They typically engage in less moderate-intensity physical activity (Kyrou et al., 2020). As a result, poverty, health literacy, and household income all influence good health.

Explain the implications of this data for your future practice:

Understanding the results of life expectancy and demographic data is essential for my future work as a family nurse. According to one study, people without a four-year college degree have more difficulty leading successful lives, which is strongly linked to health problems (Case & Deaton, 2020). My understanding of the population will impact my future practice. Age, occupation, and educational attainment all impact leading a healthy life, and they will undoubtedly impact my treatment plan, referral rates, patient education, and preventative services. I will adjust my practices to improve care quality and health outcomes as I gain more knowledge about their demographic data.

References

Case, A., & Deaton, A. (2021). Life expectancy in adulthood is falling for those without a BA degree, but as educational gaps have widened, racial gaps have narrowedhttps://10.1073/pnas.2024777118/-/DCSupplementalLinks to an external site.

Centers for Disease Control and Prevention. (2020, Life expectancy at birth for U.S. States and census tracts. https://www.cdc.gov/nchs/data-visualization/life-expectancy/Links to an external site.

Kyrous, L., Tsigos, C., Mavrogianni, C., Cardon, G., Stappen, V., Latomme, J., Kevela, J., Wikstrom, K., Tsochev, K., Nanasi, A., Semanova, C., & Mateo-Gallego, R. (2020). Sociodemographic and lifestyle-related risk
factors for identifying vulnerable groups for
type 2 diabetes: a narrative review with
emphasis on data from Europe. https://doi.org/10.1186/s12902-019-0463-3Links to an external site.

United States Department of Commerce. (2022). United States Census Bureau. https://data.census.gov/profile/California?g=040XX00US06Links to an external site.

Sample Answer 3 for NR 601 Week 1: Health Inequities

After looking at the two demographic tracts for Robertson County, tract 0806.06 with the highest life expectancy, had a total population of 6,120 people. Tract 0803.02 had a total population of 3,160 people, roughly half the population of the other tract. After looking at the breakdown of race between the two tracts tract 0803.02, which had the lowest life expectancy at 70.9 years, had a 49.5% white race population compared to tract 0806.06 which had a 89.1% white race population. Tract 0803.02 had a 27.2% black population compared to tract 0806.06 having a 2.7% black population. The last demographic that stood out to me was that in tract 0806.06, 23.8% of people were renting whereas in tract 0803.02, 59% of people were renting. In a study by Singh and Lee (2021) life expectancy of homeowners was 4.1 years longer than for renters. Since the gap between these 2 tracts was almost 10 years the fact that so many residents in tract 0803.02 are renting may have a significant effect on the life expectancy.

The gap between the two tracts of Robertson County can be potentially alleviated if more affordable housing was built or planned in tract 0803.02, the United States has struggled in the last few years to provide affordable housing to many of those looking to purchase a home since there is too much demand for houses and not enough for people to purchase. The other potential solution could be to provide low-income housing solutions, rent in the greater Nashville area has increased as the city continues to grow and expand outward into the neighboring counties. These solutions may not fix the gap entirely but should help reduce it.  

Resources

Singh, G. K., & Lee, H. (2021). Marked disparities in life expectancy by education, poverty level, occupation, and housing tenure in the United States, 1997-2014. International Journal of MCH and AIDS, 10(1), 7–18. https://doi.org/10.21106/ijma.402Links to an external site.

United States Census Bureau. (n.d.). Profile of general population and housing characteristics. https://data.census.gov/table/DECENNIALDP2020.DP1?g=040XX00US47_1400000US47147080302,47147080606&d=DEC%20Demographic%20ProfileLinks to an external site.

Sample Answer 4 for NR 601 Week 1: Health Inequities

Over the previous 25 years, Orange County’s life expectancy has increased by 5.1 years. Improvements in public health and medical care have led to this. The average life expectancy was 76.9 years in 1990; after a decade, it rose to 81.9 years. Given that the 2010 national average life expectancy was 78.7 years, this represents a significant change in Orange County. I discovered that Orange County has made efforts to prevent mental illness and many other risk factors, such as smoking, diabetes, and coronary heart disease linked to high cholesterol, from causing premature death. All of these are health behaviors that can be changed, and they all involve early drug use. Mental illness was the leading cause of premature death, accounting for 3,883 deaths annually. Health conditions such as cardiovascular disease or cancer were the second most common cause of death, with an average age of 53.7 years. Suicide or self-harm accounted for about two-thirds of premature deaths, making it the third-most common cause. The fourth-most common cause was lung cancer. Emphysema and COPD are the fifth most common causes (Orange County Healthcare Agency, 2023). In general, I believe that my county’s efforts to manage public health effectively reduce the disparity in life expectancy. A healthcare provider can manage modifiable factors, which will also be relevant to my future practice. I’ll incorporate these tactics into my work and provide education on healthy eating, quitting smoking, and immunization follow-up.

References

OC healthcare agency. (2023). Mental illness linked to shorter life spans. https://www.ochealthinfo.com/page/life-expectancy-orange-county-report#:~:text=With%20advances%20in%20medical%20care,the%20state%20and%20national%20averages.Links to an external site.